[MODELS] Cleanup Jupyter Notebooks.

author Sridhar K. N. Rao <srao@linuxfoundation.org>

Tue, 3 May 2022 21:12:21 +0000 (02:42 +0530)

committer Sridhar K. N. Rao <srao@linuxfoundation.org>

Tue, 3 May 2022 21:13:10 +0000 (02:43 +0530)
author Sridhar K. N. Rao <srao@linuxfoundation.org>
Tue, 3 May 2022 21:12:21 +0000 (02:42 +0530)
committer Sridhar K. N. Rao <srao@linuxfoundation.org>
Tue, 3 May 2022 21:13:10 +0000 (02:43 +0530)
diff --git a/models/failure_prediction/jnotebooks/Attention_LSTM.ipynb b/models/failure_prediction/jnotebooks/Attention_LSTM.ipynb

index dad4e96..0640485 100644 (file)
--- a/models/failure_prediction/jnotebooks/Attention_LSTM.ipynb
+++ b/models/failure_prediction/jnotebooks/Attention_LSTM.ipynb
@@ -1,1679 +1,948 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "l43uL109ZssB"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "Attention_LSTM.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "14ee2b60-05d7-4163-d420-58970bc4e4b0"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "l43uL109ZssB"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "14ee2b60-05d7-4163-d420-58970bc4e4b0"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 521
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "87e645f2-f2f9-4e8e-e0b9-fd807224892a"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 41
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "747e6ee9-2da1-43af-c751-1261f54d6c2c"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3f424b5d0>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 42
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "46U0FXYB6AbD"
-      },
-      "source": [
-        "We showed here the histograms of Ellis data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "eeead93b-89b4-4798-976c-1b065bbbc4a3"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "c3ac6c2e-c7f3-48ae-c562-23bb7b60c5b4"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "d553c7b1-3a00-40dd-ad5f-cc695d3ecbae"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "9jTOMzOqEQEZ"
-      },
-      "source": [
-        "## Identifying trends in Time Series data\n",
-        "There are several ways to think about identifying trends in time series. One popular way is by taking a rolling average, which means that, for each time point, we take the average of the points on either side of it. Note that the number of points is specified by a window size, which we need to choose.\n",
-        "\n",
-        "What happens then because we take the average is it tends to smooth out noise and seasonality. We will see that below right now. Check out this rolling average of `'ellis-cpu.wait_perc'` using the built-in `pandas` methods.\n",
-        "\n",
-        "When it comes to determining the window size, here, it makes sense to first try out one of twelve months, as we're talking about yearly seasonality.\n",
-        "\n",
-        "Note that in the code chunk above we used two sets of squared brackets to extract the `'ellis-cpu.wait_perc'` column as a DataFrame; If we would have used one set, like `df_Ellis['ellis-cpu.wait_perc']`, we would have created a pandas Series.\n",
-        "\n",
-        "In the code chunk above, you also chained methods: you called methods on an object one after another. Method chaining is pretty popular and pandas is one of the packages that really allows you to use that style of programming to the max!"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "c8f8cd9a-8477-46b9-e350-9b501f8bf55b"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "iVBORw0KGgoAAAANSUhEUgAABJ4AAAJpCAYAAADsVPhxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzde5yXdZ03/tcww2k4DSdFkACPqHkWpL0zW6FQWC1RTF0Fazd310SsXVN26zbLXSxtTb2N7tolxDZN20xbExWtvdFVwVTUAkyEBEzFA3GGYZjfH/5kY2cG5vSd7xyez390Ptd1fa73NfP2D1+Pz/W5Sqqrq6sDAAAAAM2sU7ELAAAAAKB9EjwBAAAAUBCCJwAAAAAKQvAEAAAAQEEIngAAAAAoCMETAAAAAAVRVuwCWtLOnTtTVVVd7DKaRWlpSbt5FlqW3qGx9A5NoX9oLL1DY+kdGkvv0BQdtX86dy6t81iHCp6qqqqzbt3mYpfRLCoqytvNs9Cy9A6NpXdoCv1DY+kdGkvv0Fh6h6boqP0zcGCvOo951Q4AAACAghA8AQAAAFAQgicAAAAACqJD7fEEAAAANF5V1Y68++7a7NixvdiltEpvvFGS6ur2u7l4WVmX9O07MKWl9Y+TBE8AAABAvbz77tp061aeHj0GpaSkpNjltDqlpZ1SVbWz2GUURHV1dTZtWp93312bAQP2q/d1XrUDAAAA6mXHju3p0aO30KkDKikpSY8evRu82k3wBAAAANSb0KnjaszfXvAEAAAAQEEIngAAAIA27+yzT8+6deuSJB/72ElJkrfeWpsvfemLxSyrSa677mtZseKVJMncubOLXE3jCJ4AAACAdmnAgIG59tpvFLuMRrvqqi9nxIgDkiS33/79gt5rx44dBZnXV+0AAACABnln8/ZcM29Znn51XbZXVTfbvF1KS3LCBypy9amHpl95lzrPe/DBn+fHP74zlZU7cvjhR+Rv//aqWs/7/e9fyxe/eHluv/2uvPLK8syceU0qK3ekunpnrr32Gxk69AO7nb958+Z861vXZ+nS36SkpCSf/vRn89GPjs3HPnZSTj/9k1m48Kn0798/X/nKP6Vv37659NKLc+mll2fkyMOzbt26/OVfXpgf//hnu835wx/OTefOXTJ58rm5+eZv5uWXf5ubb/5OfvWrRfmP/7g3V199bW64YWaWLPlNtm3blj/907H5i7/4qyTZNf8vfvFItm3blosuOj8jRhyQq6++ttZn/du/nZZDDz0sL720NCNGHJAvfemr6datW5YuXZL/839uzObNm1NRUZG///uvZMCAAbn00otz8MGH5vnnn8u4ceNzzDHH5qabvpktW7akS5fOuemmWSkv79HQP+NuBE8AAABAg1wzb1n+a8W7zT7v9qrq/NeKd3PNvGW5adKRtZ6zcuWKPPLIw5k1a3bKyspyww3X5aGHHtjr3Pfe+++ZPPm8fPzjp6WysjI7d1bVOGfOnH9Jjx49M3fuj5Ik69evT5Js2bIlI0censsu+9t8//vfy/e//9184QtX1uuZjjrq2Nx55w8yefK5Wbp0SSort2fHjh1ZvPjZHH30sUmSiy++JL1790lVVVWmT/+bvPzyb3PQQQfvmuNv/mZafvKTuzJnzg/3eK9XX/1drrrqyznqqGPyT/90TX7yk7tzzjnn5Vvfuj4zZ34zffv2zSOPPJTvfvfW/P3fX50kqayszL/+6+2prKzM+eefna9+9Z9y2GFHZNOmjenSpWu9nnFPBE8AAABAg7zw2oaizf+rXy3MsmVL8pd/OSVJsm3b1vTt23evcx5xxFGZO3d23nzzjZx88ik1VjslydNPL8w11/zTrp979+6dJOnUqVNOOeVjSZKPf/y0/MM/1H/fqJEjD8uyZUuzadPGdO7cJYccMjJLl/4mixc/l8sv/7skyaOPPpz77rsnVVVVefvtt7Jy5Su7BU/1tc8+++aoo45JkowfPyE//vGdGTPmQ3nlleX5/Oc/lyTZubMq/fsP2HXN2LHvPderr/4uAwb0z2GHHZEk6dGjZ4PvXxvBEwAAANAgRw7uVZAVT388f12qq6tz2ml/lr/+60t3G3/ggf/Y45wf//ipOeKID+a//uuxXHHF9Fxxxd9n5coV+dnPfpokueGGm+pdX0nJe/8sLS3Lzp07kyTbt2+r9dyysrIMHjw4P//5f+TII4/KgQcelGeeeTpr1qzK8OEj8tpra3LHHT/I9743N717984//uNXsn379nrXsntdJf9zJNXVyYgRB+T//t/a94jq3r17o+5VXzYXBwAAABrk6lMPzZ+M6Jsupf8z6GiaLqUl+ZMRfXP1qYfWec7xx4/OL3/5SN59950kyfr1f8jrr/9+r3OvWbM6gwcPyeTJ5+bDHz45y5f/NmeddU7mzPlh5sz5YQYMGJhRo07MT35y965r3n/VbufOnfnlLx9Jkjz88Lxdq4r222+/LFu2NEl2Ha/NUUcdkzvuuD1HH31sjj762Pz0p/+egw8+NCUlJdm0aVO6deuenj175p133s6TT/5XrXOUlpbtdQPwN954PS+++PxudX7gA8Oybt27u8Z37NiRV15ZXuPaD3xgWN566+0sWfLrJMnmzZuaZcNxK54AAACABulX3qXOPZgKbcSIA/LZz/5NPv/5S1NdvTOlpWX12m/p0Ufn58EHf56ysrL069c/U6Z8usY5U6f+Rf75n7+eCy88J506leYzn/lsTj75lHTv3j1Llvw6t932r+nbt1+uuWZmkuS88y7M//7fV+W++36SD33ow7vmeeuttbnuuq/lhhtuTpIcffSxmTt3dj74waPSvXv3dOnSNUcf/V54dfDBh+SQQw7N+eefnX333TdHHnl0rfWfccaZmTr13BxyyMhaNxdP3guPfvKTuzNz5lczfPiInHnm2encuXOuvfbr+da3bsjGjRtTVVWVc845LwcccOBu13bu3Dlf/eo/5cYbr8+2bdvStWvXfOtb305ZWdOio5Lq6urm236+lausrMq6dZuLXUazqKgobzfPQsvSOzSW3qEp9A+NpXdoLL1DY+mdPXv99d9l0KBhxS6jxX3sYyfl4YcX7PW80tJOqara2QIV1fTHX/ArpNp6YODAul+N9KodAAAAAAXhVTsAAACAPajPaqeW8oc/rMv06ZfUGL/ppm8XfLVTYwieAAAAANqIPn0qMmfOD4tdRr0JnmhVnl39hzyx8p0M71ee8SP3SWmn5v1CAgAAAE1TXV2dkhL/r9YRNWabcMETrcYjL63NVT9bsuvnX61aly+Pr/sTmgAAALSssrIu2bRpfXr06C186mCqq6uzadP6lJV1adB1gidajT8OnZLkvhffyGUfOSB9uncuUkUAAAD8sb59B+bdd9dm48Z1xS6lVSopKWnUqqC2oqysS/r2HdiwawpUCzTIjp21/4f5/Gvrc9KB/Vu4GgAAAGpTWlqWAQP2K3YZrVZFRXnWrdtc7DJaFcETLWb91sqUdylLWaeSvPaHrblu/m+z/K1N+dCIfjnnmMG1XjP/pbWCJwAAAGijBE8U3NbKqsz4jyV57JV30qNLab449qD8yxO/y6p1W5Mk977weu594fVar/35b97MNaeNbMlyAQAAgGYieKLgfvirNXnslXeSJJu2V+XqB5YVuSIAAACgJXQqdgG0f7MeX1nsEgAAAIAiqNeKp3fffTfz58/PL3/5y7z00kt544030rlz5xxyyCGZNGlSzjrrrHTqVDPDeuaZZzJr1qwsXrw4W7duzbBhw3LWWWflwgsvTGlpaYMKffnll3PLLbdk4cKF2bhxYwYPHpyJEyfm4osvTrdu3Ro0F23Lth0707VMRgoAAABtTb2Cp3nz5uUrX/lKBg4cmBNPPDGDBw/OW2+9lYcffjhf+tKXsmDBgtx0000pKSnZdc38+fNz2WWXpWvXrjnttNPSp0+f/OIXv8jMmTPzzDPP5Oabb653kYsXL87UqVOzY8eOjB8/PoMGDcqTTz6ZW2+9NU888URuu+22dOnSpeFPT5vwhy2V2adX12KXAQAAADRQvYKn4cOHZ9asWfnoRz+628qmL3zhC5k8eXIefPDBPPTQQxk/fnySZOPGjfnyl7+cTp06Ze7cuTnyyCOTJJdffnmmTp2aBx98MPfff38mTpy413tXVVVlxowZ2bJlS7797W9n7NixSZKdO3fm8ssvz4MPPpg5c+bk4osvbvDD0zb8UZ4JAAAAtCH1en/pQx/6UE455ZQar9MNHDgw5557bpJk4cKFu8bnzZuXd955JxMnTtwVOiVJ165dM3369CTJHXfcUa8CFy5cmOXLl2fUqFG7Qqck6dSpU6644ookyZ133pnq6up6zUfbs/r///odAAAA0LY0eeOcsrL3Fk398Z5NTz75ZJLkpJNOqnH+qFGj0r179zz77LPZvn37Xuff01xDhw7N8OHDs2bNmqxatapR9dP6/fvi14pdAgAAANAITQqeduzYkXvvvTfJ7sHQihUrkrz3it7/VFZWlv333z87duyoV1i0p7n+ePz982h/SrxrBwAAAG1SvfZ4qss3v/nNvPTSSzn55JN3C542btyYJOnVq1et1/Xs2TNJsn79+r3eo75zbdiwYa9zlZaWpKKifK/ntQWlpZ3azbPsTZfOpR3mWVtCR+odmpfeoSn0D42ld2gsvUNj6R2aQv/U1Ojgae7cuZk9e3YOOOCAfOMb32jOmgqmqqo669ZtLnYZzaKiorzdPMveVFZWdZhnbQkdqXdoXnqHptA/NJbeobH0Do2ld2iKjto/AwfWvlgoaeSrdj/4wQ/yj//4jznooIMyd+7cVFRU7HZ8b6uQ3l/F1Lt3773eq75z1bUiCgAAAIDiaHDwNGfOnHzta1/LIYcckrlz52bgwIE1zhkxYkSSZOXKlTWO7dixI6tXr05ZWVmGDh261/vtaa4/Hn//PNofWzwBAABA29Sg4Om73/1uZs6cmcMOOyy33XZb+vfvX+t5Y8aMSZIsWLCgxrFFixZly5YtOfbYY9OlS5e93nNPc61atSorV67MkCFD6hVi0TbZXBwAAADapnoHT7feemu++c1v5ogjjsicOXPSr1+/Os899dRT07dv39x///154YUXdo1v27YtN910U5LkvPPO2+2aLVu2ZPny5Xnttdd2Gx89enQOPPDALFq0KI888siu8Z07d+b6669Pkpx77rnCCQAAAIBWpl6bi99zzz25+eabU1pamhNOOCG33357jXOGDBmSSZMmJXlvX6Zrr702l112WaZMmZIJEyakT58+efTRR7NixYqMHz8+EyZM2O36559/PlOmTMno0aN3m7+0tDQzZ87M1KlTM3369IwfPz777bdfnnjiibz44os57rjjctFFFzXhV0BrJ1IEAACAtqlewdPq1auTJFVVVbnttttqPWf06NG7gqckGTduXG6//fZ85zvfyUMPPZRt27Zl2LBhmTFjRi688MIGrVA6+uij8+Mf/zg333xzHnvssWzatClDhgzJ5z73uVx88cX1emWPtkvwBAAAAG1TSXV1dXWxi2gplZVV7eazhm3pE42jvvn/mnT9nx2xb64+9dBmqoa21Du0LnqHptA/NJbeobH0Do2ld2iKjto/Awf2qvNYg79qBwAAAAD1IXiioFav21LsEgAAAIAiETxRUFsrdzZ5jg7zLigAAAC0M4InCqoBe8gDAAAA7YzgiYJqluCp4+x/DwAAAO2K4ImCKoklTwAAANBRCZ4AAAAAKAjBEwVlvRMAAAB0XIInCqo59niywxMAAAC0TYInCqrEZ+0AAACgwxI8UVDNETvtqLLmCQAAANoiwROt3q9f31DsEgAAAIBGEDxRUM3xpt2aP2xt+iQAAABAixM8UVC2eAIAAICOS/BEQZU0yy5PAAAAQFskeAIAAACgIARPFJRX7QAAAKDjEjxRUM2RO+1f0a0ZZgEAAABamuCJVm94v/JilwAAAAA0guCJgirxrh0AAAB0WIInCqo5YqdS4RUAAAC0SYInAAAAAApC8ESrZ8ETAAAAtE2CJwqqutgFAAAAAEUjeKLVs0E5AAAAtE2CJ1o9sRMAAAC0TYInWj0LngAAAKBtEjzR6smdAAAAoG0SPFFQ1dXNsb246AkAAADaIsETAAAAAAUheKLVs8cTAAAAtE2CJ1o9uRMAAAC0TYInWj0rngAAAKBtEjzR6g3rW17sEgAAAIBGEDzR6g3o2aXYJQAAAACNIHgCAAAAoCAETwAAAAAUhOCJgqrey/FLPjw8Hz6gX5PmAAAAAFonwRNF1adbWUZ9oKLYZQAAAAAFIHii6E4/YlC6lJYUuwwAAACgmQmeKKqeXcvSq1tZbvjkERner3uxywEAAACakeCJgqreywZNHzmwf5LkQ8P75e5Pj8onjhzUAlUBAAAALUHwRFF161y628+1vnC3t/QKAAAAaJUETxTNnx48oMZYia2eAAAAoN0QPFE0f378kGKXAAAAABSQ4ImiOXpIn2KXAAAAABRQWX1PnDdvXhYtWpQlS5Zk6dKl2bRpU04//fTccMMNNc696qqrcs899+xxvjFjxuS2227b631Xr16dsWPH1nl8woQJufHGG/f+ABRFdWrfn6lX13q3Xh0zAAAAAK1dvf/vf9asWVm6dGnKy8szaNCgvPLKK3WeO27cuAwZUvtrVPfee29WrVqVj3zkIw0qdOTIkRk3blyN8YMPPrhB89A69C3vXOt4Se3biwMAAABtUL2DpxkzZmTQoEEZNmxYFi5cmClTptR57rhx42oNidavX59/+Zd/SefOnXPmmWc2qNDDDjss06ZNa9A1AAAAABRPvYOnMWPGNPlm9957b7Zu3ZqJEyemX79+TZ4PAAAAgNar/hvtNIO77rorSXLOOec0+No333wzd955Z9atW5eKioocc8wxGTlyZHOXSAsZM6xvvc+ttskTAAAAtEktFjw9++yzeemllzJ8+PBGrZ56/PHH8/jjj+82Nnr06Hz961/P4MGDm6tMmlldodF5x9e+B1iJLZ4AAACg3Wix4Kmxq526d++eSy65JOPGjcvQoUOTJMuWLcstt9ySp556KhdddFF++tOfpry8fK9zlZaWpKJi7+e1BaWlndrEs6zfWfv4B4f3r3W8S5eaLdm9vEubeNa2oq30Dq2P3qEp9A+NpXdoLL1DY+kdmkL/1NQiwdOGDRvywAMPNGpT8f79+2f69Om7jY0aNSqzZ8/O+eefn8WLF+fuu+/O1KlT9zpXVVV11q3b3KD7t1YVFeVt4lnWr99SY2xwn2511r59+44aY1s2b28Tz9pWtJXeofXROzSF/qGx9A6NpXdoLL1DU3TU/hk4sFedxzq1RAH33XdftmzZko9//OPNtql4WVlZJk+enCR5+umnm2VOAAAAAJpPiwRP779m96lPfapZ5+3b970Nqjdv7nhpIgAAAEBrV/DgafHixVm6dGmGDx+eE088sdnnTrJr7yfaBvuHAwAAQMdQ8ODpRz/6UZK9r3basGFDli9fnjfffHO38V//+tfZubPmDtVPPPFE5syZkyQ544wzmqdYAAAAAJpNvTcXnz9/fubPn58kWbt2bZLkueeey1VXXZXkvdferrzyyt2u2bhxYx544IF06dIln/zkJ/c4/8MPP5wZM2bkzDPPzHXXXbdr/LrrrsvKlStz7LHHZtCgQUne+6rdk08+mSSZPn16jjvuuPo+BgAAAAAtpN7B05IlS3LPPffsNrZq1aqsWrUqSTJkyJAawdN9992XzZs3Z+LEiY3eVPyMM87I/Pnz8+KLL2bBggWprKzMgAEDctppp+WCCy7ICSec0Kh5AQAAACiskurq6upiF9FSKiur2s1nDdvKJxpXvbslk2Yv2m1sSJ9u+elfjq71/Ovm/zb/vvj3u419cexBmXzM4ILV2NG0ld6h9dE7NIX+obH0Do2ld2gsvUNTdNT+GTiwV53HWuSrdvDHSuwuDgAAAB2C4AkAAACAghA8AQAAAFAQgicKqsNsIAYAAADUIHiixdniCQAAADoGwRMAAAAABSF4AgAAAKAgBE8AAAAAFITgiYKqrm769uLNMAUAAABQBIInWlxJSd3bi9t4HAAAANoPwRMAAAAABSF4AgAAAKAgBE8UlO2ZAAAAoOMSPAEAAABQEIInAAAAAApC8AQAAABAQQieAAAAACgIwROFZXdxAAAA6LAET7S4kgZfIb0CAACAtkjwRKtSUtLwWAoAAABonQRPAAAAABSE4ImC8pIcAAAAdFyCJ1qct+kAAACgYxA8AQAAAFAQgicAAAAACkLwBAAAAEBBCJ4oqGrbiwMAAECHJXiixZXE7uIAAADQEQieaPWqLZoCAACANknwRKtiLRQAAAC0H4InCspqJQAAAOi4BE+0PMuaAAAAoEMQPFFQO2tZ8rTi7c1FqAQAAABoaYInCurfF/++2CUAAAAARSJ4oqAETwAAANBxCZ4omGo7iwMAAECHJniiYF6xlxMAAAB0aIInCubfnl7dLPNYNwUAAABtk+CJgtm0varB15SUFKAQAAAAoCgETxTMCq/aAQAAQIcmeKJg1vxhS7FLAAAAAIpI8ETBbK+yOxMAAAB0ZIInAAAAAApC8EStdlZX5+W1m7Jh645ilwIAAAC0UWXFLoDWZ+3Gbbnk7uez8p0t6VSSXDn2oEw6enCxywIAAADamHoHT/PmzcuiRYuyZMmSLF26NJs2bcrpp5+eG264oca5q1evztixY+uca8KECbnxxhsbVOgzzzyTWbNmZfHixdm6dWuGDRuWs846KxdeeGFKS0sbNBd79v2nVmXlO+9tDL6zOvnGo8sz/rB90qOLnBIAAACov3onCbNmzcrSpUtTXl6eQYMG5ZVXXtnrNSNHjsy4ceNqjB988MENKnL+/Pm57LLL0rVr15x22mnp06dPfvGLX2TmzJl55plncvPNNzdoPvbs7ude2+3nqp3Vmb9sbT5x5H5FqggAAABoi+odPM2YMSODBg3KsGHDsnDhwkyZMmWv1xx22GGZNm1akwrcuHFjvvzlL6dTp06ZO3dujjzyyCTJ5ZdfnqlTp+bBBx/M/fffn4kTJzbpPuzZxm1VRbu3b+MBAABA21TvzcXHjBmT4cOHp6SkpJD11DBv3ry88847mThx4q7QKUm6du2a6dOnJ0nuuOOOFq0JAAAAgL0r6KY9b775Zu68886sW7cuFRUVOeaYYzJy5MgGzfHkk08mSU466aQax0aNGpXu3bvn2Wefzfbt29OlS5dmqRsAAACApito8PT444/n8ccf321s9OjR+frXv57Bg+v3lbQVK1YkSYYPH17jWFlZWfbff//89re/zapVq3LggQc2uea2YGtlVRb8dm12bt+RD+7XO6WdCr8KrYUXugEAAADtQEGCp+7du+eSSy7JuHHjMnTo0CTJsmXLcsstt+Spp57KRRddlJ/+9KcpLy/f61wbN25MkvTq1avW4z179kySrF+/vpmqb93Wba7Mx2Y9sevnzqUl+X+XfThlLRA+AQAAADREQYKn/v3779p/6X2jRo3K7Nmzc/7552fx4sW5++67M3Xq1ELcvk6lpSWpqNh72NWa/dXdT+72c2VVdRauWZ8JBf7iXHl5l2b93dU1V9eunWuMde/euc3/3VqT0tJOfp80it6hKfQPjaV3aCy9Q2PpHZpC/9RU0FftatysrCyTJ0/O4sWL8/TTT9creHp/RdOGDRtqPf7+iqjevXvvda6qquqsW7e5ARW3Ps+8uq7G2PS7FudPhvYp6H23bKls8O9uRP/yrHi79mvqmmvbtspmuTd1q6go9/ukUfQOTaF/aCy9Q2PpHRpL79AUHbV/Bg6s/S21pAFftWsuffv2TZJs3ly/P8SIESOSJCtXrqxxbMeOHVm9enXKysp2vdJH63H4vj2LXQIAAABQRC0ePC1evDhJ6h0UjRkzJkmyYMGCGscWLVqULVu25Nhjj/VFuwLb0w5S//ny25n6b8/mvNt+lfteeH3XeCc7kgMAAECHVpDg6de//nV27txZY/yJJ57InDlzkiRnnHHGbsc2bNiQ5cuX580339xt/NRTT03fvn1z//3354UXXtg1vm3bttx0001JkvPOO6+Zn4D/qa4I6dV3t+TKn/0mv3l9Q15+a1O+9tBLeWb1e68DdmqmDc+rq6ubZR4AAACgZdV7j6f58+dn/vz5SZK1a9cmSZ577rlcddVVSd57he7KK69Mklx33XVZuXJljj322AwaNCjJe1+1e/LJ9zbGnj59eo477rjd5n/44YczY8aMnHnmmbnuuut2jffs2TPXXnttLrvsskyZMiUTJkxInz598uijj2bFihUZP358JkyY0Njnb5e2VlZlyRsb84G+3dO/R2FXgv3b06tTtXP3YOg7j63Md889JqWNWPFUYpUUAAAAtBv1Dp6WLFmSe+65Z7exVatWZdWqVUmSIUOG7AqezjjjjMyfPz8vvvhiFixYkMrKygwYMCCnnXZaLrjggpxwwgkNKnLcuHG5/fbb853vfCcPPfRQtm3blmHDhmXGjBm58MILhRV/5OW3NuWSu57Pu1sqU5LkS+MPyRkfHNTkeev6FT/2yts1xp5dsz5J0kwLngAAAIA2qt7B07Rp0zJt2rR6nTt58uRMnjy5QYVMmjQpkyZNqvP48ccfn+9973sNmrMjueD2Z9K/R+f87p0teXfLe1+Gq07yz79YngmH75uyeqRAv3l9Q/7qR4ubraZ+5fbdAgAAgI6s3sETrduyNzfWOr5pe1UWr/lDjh9ake07dubu517LK29vyoeG98u4QwfuOq+6ujpT/+3ZPdyh4cuXykoteQIAAICOTPDUAWzb8d5G71c/sCzzX3pvf677Xnwj67dWZtLRg5MkT/3u3T3O4W1GAAAAoKEK8lU7WpfV67ZkzlOv7gqd3nfz/1ux699nP7Vqj3Mse3NjtlZWFaQ+AAAAoH2y4qkDuP7R5bWOb9r+30HShq079jjHvS+8noeWvplLTxqR19dvS/fOpTn9g/s2a50AAABA+yJ46uCuf+TlHD2kd9Zu3LbXc7dU7twtxPqPX7+eDdv2HFgBAAAAHcgvpdEAACAASURBVJfgqYO767nXctdzrzXq2tfW7z2sAgAAADouezwBAAAAUBCCJ1oVH88DAACA9kPwBAAAAEBBCJ5ocZ/44KBilwAAAAC0AMETLe6CE/YvdgkAAABACxA8tSF/2FJZ7BKa7Kyj98vw/uXFLgMAAABoAYKnNuRfnny12CU0SHV1zbFeXctavhAAAACgKARPbcidz6wpdglNVuKzdQAAANBhCJ4AAAAAKAjBE61eba/sAQAAAK2f4AkAAACAghA80arYAwoAAADaD8ETAAAAAAUheAIAAACgIARPAAAAABSE4ImCqY7P0QEAAEBHJniiRdk7HAAAADoOwRMAAAAABSF4AgAAAKAgBE+0enaKAgAAgLZJ8AQAAABAQQieAAAAACgIwRMAAAAABSF4omCqbc4EAAAAHZrgiZZVUlLsCgAAAIAWIngCAAAAoCAETwAAAAAUhOAJAAAAgIIQPAEAAABQEIInWr1qn8cDAACANknwRKtSEl+9AwAAgPZC8AQAAABAQQieKBgvyAEAAEDHJniiRXmRDgAAADoOwRMAAAAABSF4AgAAAKAgBE8AAAAAFITgCQAAAICCEDwBAAAAUBCCJ1qVEp+9AwAAgHajrL4nzps3L4sWLcqSJUuydOnSbNq0KaeffnpuuOGGGueuXLkyDz30UB577LH87ne/y9tvv53evXvn6KOPztSpUzNmzJh6F7h69eqMHTu2zuMTJkzIjTfeWO/5AAAAAGgZ9Q6eZs2alaVLl6a8vDyDBg3KK6+8Uue5N910U37+85/noIMOysknn5w+ffpkxYoVefTRR/Poo4/mH/7hHzJlypQGFTpy5MiMGzeuxvjBBx/coHloQdXFLgAAAAAopnoHTzNmzMigQYMybNiwLFy4cI/B0UknnZTPfvazOfzww3cbX7hwYT7zmc/kG9/4Rk499dTss88+9S70sMMOy7Rp0+p9Pq2TN+kAAACg46j3Hk9jxozJ8OHDU1KPTXgmTZpUI3RKktGjR2f06NGprKzMs88+27BKAQAAAGhT6r3iqdluWPbeLUtLSxt03Ztvvpk777wz69atS0VFRY455piMHDmyECUCAAAA0AxaNHhas2ZNnnjiiXTv3j2jRo1q0LWPP/54Hn/88d3GRo8ena9//esZPHhwc5YJAAAAQDNoseBp+/bt+bu/+7ts3749V1xxRfr06VOv67p3755LLrkk48aNy9ChQ5Mky5Ytyy233JKnnnoqF110UX7605+mvLx8r3OVlpakomLv59F0FRXl6datc43xbt067/Fv0LVrzZbs1r2Lv1szKi3t5PdJo+gdmkL/0Fh6h8bSOzSW3qEp9E9NLRI8VVVV5YorrsgzzzyTCRMm5C/+4i/qfW3//v0zffr03cZGjRqV2bNn5/zzz8/ixYtz9913Z+rUqfWoozrr1m1ucP003Lp1m7N1a2WN8a1bK/f4N9i2bUfNa7Zs93drRhUV5X6fNIreoSn0D42ld2gsvUNj6R2aoqP2z8CBveo8Vu/NxRvr/dBp3rx5Oe2003L99dfXa4PyvSkrK8vkyZOTJE8//XST56P1qq4udgUAAABAYxQ0eKqsrMwXvvCF3H///fmzP/uzfPOb39y1uXhz6Nu3b5Jk8+aOlya2V02PJAEAAIDWomCv2m3fvj2XX355HnnkkXzyk5/MzJkz06lT8+ZcixcvTpJdez/RulTHUiUAAADoyAqy4mn79u259NJL88gjj+Tss8+uV+i0YcOGLF++PG+++eZu47/+9a+zc+fOGuc/8cQTmTNnTpLkjDPOaLbaKaxmeMsSAAAAaCPqveJp/vz5mT9/fpJk7dq1SZLnnnsuV111VZL3Xnu78sorkyRXX311/vM//zN9+/bNvvvum1tvvbXGfKNHj86JJ5646+eHH344M2bMyJlnnpnrrrtu1/h1112XlStX5thjj82gQYOSvPdVuyeffDJJMn369Bx33HENemgAAAAACq/ewdOSJUtyzz337Da2atWqrFq1KkkyZMiQXcHT6tWrkyTvvvturaFTklx66aW7BU91OeOMMzJ//vy8+OKLWbBgQSorKzNgwICcdtppueCCC3LCCSfU9xEAAAAAaEH1Dp6mTZuWadOm1evc22+/vcGFTJo0KZMmTaoxPnny5F1frwMAAACg7SjoV+0AAAAA6LgETwAAAAAUhOCJVq+62AUAAAAAjSJ4AgAAAKAgBE8UTHUjliqVlDR/HQAAAEBxCJ5oUSWRLAEAAEBHIXgCAAAAoCAETwAAAAAUhOAJAAAAgIIQPAEAAABQEIInAAAAAApC8AQAAABAQQieaPWqq6uLXQIAAADQCIInCqZxcVFJM1cBAAAAFIvgiWb3gb7d6z4oVwIAAIAOQ/BEsxver7zYJQAAAACtgOAJAAAAgIIQPNHsbAYOAAAAJIInAAAAAApE8AQAAABAQQieAAAAACgIwRPNzg5PAAAAQCJ4alOmjh5a7BIapLkCKEEWAAAAtE2Cpzbkk0cOSkX3zsUuo0lK9nZ8bycAAAAAbYbgqQ3Zv6J7bvvzY3PZR0akW2d/OgAAAKB1k160MYP7dMuFo4Zm7qdHF7sUAAAAgD0SPLVRA3p2KXYJAAAAAHskeGqjOrXizZA2bN1R7BIAAACAVkDw1EYN7tMt/cpb50bjvbqVFbsEAAAAoBUQPLVRJSUl+ev/NbzYZQAAAADUSfDUhp151H750UXHZ6D9ngAAAIBWSPDUxh3Qv0fOOWZws8z1uQ8Pb5Z5dqmubt75AAAAgDZF8NQOfOLIQc0yT0kzbVi+Y2fdgdPebtF6t0wHAAAAGkrw1A70LW+eV+2aK/TpUqqtAAAAAMETf6SkJDl4YI9ilwEAAAC0E4IndnPFKQc1eQ6vywEAAACJ4KnduPrUQ5o8R3mX0nQta3pLNNNWUQAAAEAbJ3hqJ/7siEF55HMfyqUnjWj0HONH7pOeXcuasSoAAACgIxM8tSO9u3XO1NFDG3XtEYN6pWfXsnygb/dmrgoAAADoqCxv6aAu/pNhOWRgj/zk+d/nrKMH5yMH9i92SQAAAEA7I3hqh6adNCK3LFixx3NOO2yf7F/RPScfNKDGsa5lnbJtx84m11Hd5BkAAACAtsyrdu3Qn5+wf046oF+dx//04AHZv6LuV+quHNu0L9tV7yFxKmnEN+/2NB8AAADQegme2qHSTiX55zM/mKMG995tfP+Kbrl2wsj848SRe7y+b3nnQpa3R76IBwAAAO2HV+3asRvPPCLff2pVVr27JScf1D+nf3BQi9z3P5e/3SL3AQAAAFo3wVM71rtb50w/+YAGX7dPz64FqAYAAADoaOoVPM2bNy+LFi3KkiVLsnTp0mzatCmnn356brjhhjqveeaZZzJr1qwsXrw4W7duzbBhw3LWWWflwgsvTGlpaYOKfPnll3PLLbdk4cKF2bhxYwYPHpyJEyfm4osvTrdu3Ro0F3t38MAeGVrRLavWbS12KQAAAEAbVq89nmbNmpUf/OAHWbJkSfbdd9+9nj9//vxccMEFefrppzNu3Lj8+Z//eSorKzNz5sx8/vOfb1CBixcvztlnn51HHnkkf/Inf5IpU6akZ8+eufXWW/PpT38627dvb9B87F1JSUn++ZMfzDFDeqdPt7JMOHyfRs3z4+d+38yVAQAAAG1JvVY8zZgxI4MGDcqwYcOycOHCTJkypc5zN27cmC9/+cvp1KlT5s6dmyOPPDJJcvnll2fq1Kl58MEHc//992fixIl7vW9VVVVmzJiRLVu25Nvf/nbGjh2bJNm5c2cuv/zyPPjgg5kzZ04uvvji+jwGDTC8f3m+d+4xu37ep2fXzFm4qkFzbNi2o8bYTp+oAwAAgA6jXiuexowZk+HDh6ekHp8cmzdvXt55551MnDhxV+iUJF27ds306dOTJHfccUe9ilu4cGGWL1+eUaNG7QqdkqRTp0654oorkiR33nlnqoUZBTfx8L2vdKuPjduqmmUeAAAAoPWrV/DUEE8++WSS5KSTTqpxbNSoUenevXueffbZer0it6e5hg4dmuHDh2fNmjVZtaphK3FouH49Otc63rl072EkAAAA0DE1e/C0YsWKJMnw4cNrHCsrK8v++++fHTt21Css2tNcfzz+/nm0vIMH9iz4PapjRRsAAAC0Rc0ePG3cuDFJ0qtXr1qP9+z5XlCxfv36Zptrw4YNDa6ThilJ7SubGrreSYgEAAAAHUe9NhdvL0pLS1JRUV7sMppFaWmnFn2Wrttr35uptKz27LKu2rp17bzHurt1q/lKX7duXdrN3601aOneof3QOzSF/qGx9A6NpXdoLL1DU+ifmpo9eNrbKqT3VzH17t272eaqa0XU/1RVVZ116zbX69zWrqKivMWf5ajBvfP8a/+9Um3M8L7ZWMuX65LUWdvWbZV7rHvb1sqa12zd3m7+bq1BMXqH9kHv0BT6h8bSOzSW3qGx9A5N0VH7Z+DAunOZZn/VbsSIEUmSlStX1ji2Y8eOrF69OmVlZRk6dGiT5vrj8ffPo7CuOe3QjNynZzqVJEfu1yv/8LGDG/yqHQAAANBxNHvwNGbMmCTJggULahxbtGhRtmzZkmOPPTZdunRp0lyrVq3KypUrM2TIkHqFWDTd/hXdc/uFx+Wx6R/O7POPzaDe3dLwXZ4AAACAjqLZg6dTTz01ffv2zf33358XXnhh1/i2bdty0003JUnOO++83a7ZsmVLli9fntdee2238dGjR+fAAw/MokWL8sgjj+wa37lzZ66//vokybnnnpuSEuFHS+pc+t9tU9ev/qU3N9Y6Xm1vcQAAAOgw6rXH0/z58zN//vwkydq1a5Mkzz33XK666qokSd++fXPllVcmeW9fpmuvvTaXXXZZpkyZkgkTJqRPnz559NFHs2LFiowfPz4TJkzYbf7nn38+U6ZMyejRo3P77bfvGi8tLc3MmTMzderUTJ8+PePHj89+++2XJ554Ii+++GKOO+64XHTRRU3+JdD8Lrn7+WKXAAAAABRZvYKnJUuW5J577tltbNWqVVm1alWSZMiQIbuCpyQZN25cbr/99nznO9/JQw89lG3btmXYsGGZMWNGLrzwwgatUDr66KPz4x//ODfffHMee+yxbNq0KUOGDMnnPve5XHzxxfV6ZY+W94ettW86bnEaAAAAdBz1Cp6mTZuWadOmNWji448/Pt/73vfqde6JJ56YZcuW1Xn8oIMOys0339yg+9My5EgAAABAXZp9jyc6loauYGrMHk/2hQIAAIC2SfBEkzT7iifv4gEAAEC7IXiiaRoYFFm8BAAAAB2H4AkAAACAghA8AQAAAFAQgieapHOnBr5qZ6dwAAAA6DAETzTJmUftV+wSAAAAgFZK8ESTDOrdtdglAAAAAK2U4AkAAACAghA8AQAAAFAQgieaZPW6rQ06/+1N2xt8D9uRAwAAQNskeKJJNm/f0aDz57/01h6PN+wbeQAAAEBrJngCAAAAoCAETzRNiTVKAAAAQO0ETwAAAAAUhOAJAAAAgIIQPNEkXrQDAAAA6iJ4AgAAAKAgBE80ycZtO4pdAgAAANBKCZ5oknVbKgt/k+rC3wIAAABofoInWhV7RgEAAED7IXiiiURFAAAAQO0ETzRJidwJAAAAqIPgiSaROwEAAAB1ETzRJFY8AQAAAHURPAEAAABQEIInmqRLqRYCAAAAaic1oEn2692t2CUAAAAArZTgiSaxxxMAAABQF8ETrV51qotdAgAAANAIgidaFSuoAAAAoP0QPAEAAABQEIInmsQKJQAAAKAugicAAAAACkLwRJOUxJInAAAAoHaCJ5pE7AQAAADURfBEk1QXuwAAAACg1RI80STbq3YWuwQAAACglRI80SSdSwv/sl21ZVUAAADQJgmeaJLSkoYFTyP6le/xuM3KAQAAoP0QPNGiylpghRQAAADQOgieAAAAACgIwRNNUtLAV+122rAJAAAAOgzBEy1K7gQAAAAdh+CJFiV4AgAAgI5D8ESTNHSr8OpIngAAAKCjKCvUxD/5yU8yY8aMPZ7TqVOnLFmyZK9znXLKKVmzZk2txwYMGJDHH3+8UTXS8qx4AgAAgI6jYMHTYYcdlksvvbTWY08//XSefPLJfOQjH6n3fL169crUqVNrjJeXlze6Rlqe3AkAAAA6joIGT4cddlitxz71qU8lSc4555x6z9e7d+9MmzatWWqj+TTwo3aNIqwCAACAtqnF93hatmxZnnvuuey777756Ec/2tK3p8iq9/auXQsEWQAAAEDLKNiKp7rcddddSZKzzz47paWl9b5u+/btuffee/P73/8+3bt3z6GHHppRo0Y1aA6Kb6flSwAAANBhtGjwtHXr1tx3330pLS3N5MmTG3Tt2rVr88UvfnG3sf333z8zZ87M6NGjm7NMGqDhX7UDAAAAOooWfdXugQceyPr163PSSSdlv/32q/d1kyZNypw5c/L444/nueeey89+9rN86lOfypo1a/LZz342S5cuLWDVNKd+5Z2LXQIAAADQQlp0xdOPfvSjJP+9uXh9/c+v4x1yyCH56le/mh49emT27Nm55ZZbcuutt+51ntLSklRUtI+v4JWWdmoVz1Leo2uDzr/qtJF7rLtbt5rBVLdunVvFs7YXraV3aHv0Dk2hf2gsvUNj6R0aS+/QFPqnphYLnn7729/m2WefzaBBg3LyySc3y5znnntuZs+enaeffrpe51dVVWfdus3Ncu9iq6gobxXPsnnz9gadf1Cfbnuse+vWylrHWsOzthetpXdoe/QOTaF/aCy9Q2PpHRpL79AUHbV/Bg7sVeexFnvV7v3VTg3dVHxP+vXrlyTZvLnj/VHbqtJOPlsHAAAAHUWLBE/btm3btan42Wef3WzzPvfcc0mSoUOHNtucNMxx+/cpdgkAAABAK9UiwdMDDzyQP/zhD/nIRz5S56bilZWVWb58eV599dXdxpcvX17riqbVq1fna1/7WpLkjDPOaP6iqZeeXVt0mzAAAACgDWmR1OCuu+5Kkpxzzjl1nvPGG29kwoQJGTJkSB599NFd4z//+c8ze/bsjBo1KoMHD06PHj2yatWq/PKXv8y2bdty8skn5zOf+UzBn4HiqS52AQAAAECjFDx4Wr58eX71q181elPxE088MStWrMhvfvObPPPMM9myZUt69eqV448/Pp/4xCfyiU98IiUl9g0qlub+zftLAgAAQPtR8ODpwAMPzLJly/Z63v7771/reaNHj87o0aMLURoAAAAABdRiX7UDAAAAoGMRPNEk3nIEAAAA6iJ4AgAAAKAgBE80iQVPAAAAQF0ET7SYiYfvU+wSAAAAgBYkeKLFjDt0YLFLAAAAAFqQ4IkmKWnA7uIljX0xr7q6cdcBAAAARSV4olXxlTwAAABoPwRPtByhEgAAAHQogidajNwJAAAAOhbBEwAAAAAFIXiixdi/CQAAADoWwRMAAAAABSF4AgAAAKAgBE802cCeXep1njftAAAAoGMRPNFksyYfVewSAAAAgFZI8ESTDetXng8N77vX80oaueapulFXAQAAAMUmeKJZ3DTpgzl4YI89ntOja+le52lsOAUAAAC0PoInmkVJSUm+f/6x+csxH6jznMMH9WrBigAAAIBiEzzRbLqWdcpf/a/h+fihA2sc++v/NSydSqxmAgAAgI5E8ESzO+/4Iela9t+tdeR+vfLpE+teCQUAAAC0T2XFLoD254P79c7s847Jo799KwN6dMlph+9jtRMAAAB0QIInCuKQfXrmkH16FrsMAAAAoIi8agcAAABAQQieAAAAACgIwROtXnV1sSsAAAAAGkPwRKtiD3IAAABoPwRPAAAAABSE4AkAAACAghA8AQAAAFAQgicAAAAACkLwBAAAAEBBCJ4AAAAAKAjBEwAAAAAFIXgCAAAAoCAET7R61cUuAAAAAGgUwRMAAAAABSF4AgAAAKAgBE8AAAAAFITgCQAAAICCEDwBAAAAUBCCJwAAAAAKQvAEAAAAQEEIngAAAAAoCMETAAAAAAUheKLVq64udgUAAABAY5QVcvJTTjkla9asqfXYgAED8vjjj9d7rtdffz033XRTFixYkHXr1mWfffbJ2LFjc+mll6ZPnz7NVTJFVlLsAgAAAIBmU9DgKUl69eqVqVOn1hgvLy+v9xyvvvpqzj333Lz99tsZO3ZsDjjggDz//POZO3duFixYkDvuuCN9+/ZtzrIBAAAAaKKCB0+9e/fOtGnTmjTHNddck7fffjtf+tKXcuGFF+4anzlzZubMmZMbb7wxX/3qV5taKgAAAADNqNXv8fTqq6/msf+PvfuMj6pM2wB+TWbSO0koSYDQQglFKQE0SLWxq6zYsO+irrsu2HbVddXV1ddFV10FxbZKE6QoICpNQ5GEEkpIAiEhkN57m0yfOe+HkCGTmUmmZpLJ9f/Cb86cc+YZ5skp97mf+0lORlRUFB544AGD95YvXw4/Pz/88MMPkMlkLmohERERERERERGZ4vSMJ5VKhV27dqG8vBy+vr4YPXo0pk2bBrFYbNH2KSkpAICEhAR4eBjGyQICAjB58mQkJycjPT0dM2fOdHj7iYiIiIiIiIjINk4PPFVXV+OFF14wWBYdHY0VK1YgPj6+y+3z8vIAADExMSbfHzp0KJKTk5Gfn8/AExERERERERFRD+LUwNPixYsxZcoUjBo1Cv7+/iguLsbGjRuxbds2PP7449i6dSvGjBnT6T6kUimA1iLlprQtb25u7rI9YrEIISGWFzXvycRiD7f5Lu35+noZLfPxkbjld3UVd+075HzsO2QP9h+yFfsO2Yp9h2zFvkP2YP8x5tTA07Jlywxex8bG4o033oC/vz/WrFmDjz76CKtXr3ZmEwxotQIaGtyjFlRIiJ/bfJf25HKV0TKFQuOW39VV3LXvkPOx75A92H/IVuw7ZCv2HbIV+w7Zo6/2n4gI08lCgIuKiy9ZsgQAcPr06S7XDQgIAGA+o6ltubmMKHIHgqsbQEREREREREQ2cEngqV+/fgBg0Ux0w4cPBwAUFBSYfL+wsBAAMGzYMMc0jlxKJBK5uglERERERERE5CAuCTylpaUBAAYPHtzlutOnTwcAJCcnQ6fTGbwnlUqRmpoKX19fTJo0yfENJSIiIiIiIiIimzkt8JSbm2syo6mkpARvvvkmAOD222/XL1er1cjNzUVRUZHB+kOGDEFCQgJKS0uxadMmg/c++ugjyGQy3H777fDzY/EuIiIiIiIiIqKexGnFxffs2YM1a9Zg2rRpiIyM1M9qd/jwYSiVSsyePRtLly7Vr19ZWYmFCxciKioKBw8eNNjXa6+9hiVLluD//u//cPz4cYwYMQLp6elISUlBTEwMnn32WWd9DSIiIiIiIiIispHTAk/Tp09Hfn4+Lly4gNTUVMjlcgQGBmLKlClYtGgRFi1aZHE9nyFDhmD79u1YtWoVkpKScOTIEURERODhhx/GsmXLEBwc7KyvQURERERERERENnJa4Ck+Ph7x8fEWrx8dHY2LFy+afX/QoEFYsWKFI5pGRERERERERETdwCXFxYmIiIiIiIiIyP0x8ERERERERERERE7BwBMRERERERERETkFA0/U4wmCq1tARERERERERLZg4Il6FMvmOSQiIiIiIiKi3oCBJyIiIiIiIiIicgoGnoiIiIiIiIiIyCkYeCIiIiIiIiIiIqdg4ImIiIiIiIiIiJyCgSciIiIiIiIiInIKBp6IiIiIiIiIiMgpGHgiIiIiIiIiIiKnYOCJejzB1Q0gIiIiIiIiIpsw8EQ9ikjk6hYQERERERERkaMw8ERERERERERERE7BwBMRERERERERETkFA09EREREREREROQUDDwREREREREREZFTMPBEREREREREREROwcATERERERERERE5BQNPRERERERERETkFAw8ERERERERERGRUzDwRD2eILi6BURERERERERkCwaeiIiIiIiIiIjIKRh4IiIiIiIiIiIip2DgiYiIiIiIiIiInIKBJyIiIiIiIiIicgoGnoiIiIiIiIiIyCkYeCIiIiIiIiIiIqdg4ImIiIiIiIiIiJyCgSciIiIiIiIiInIKBp6IiIiIiIiIiMgpGHiiHk+A4OomEBEREREREZENGHiiHkUkErm6CURERERERETkIAw8ERERERERERGRUzDwRERERERERERETsHAExEREREREREROQUDT0RERERERERE5BQMPBERERERERERkVMw8ERERERERERERE7BwBMRERERERERETkFA09EREREREREROQUDDxRjyJydQOIiIiIiIiIyGEYeCIiIiIiIiIiIqdg4ImIiIiIiIiIiJxC4qwd19fXIzExEYcPH0ZOTg4qKyvh6emJ2NhYLF68GHfeeSc8PCyLe82bNw+lpaUm3wsPD8fRo0cd2XQiIiIiIiIiInIApwWe9u3bh9dffx0RERGYPn06IiMjUVNTg19++QWvvPIKkpKSsHLlSohEllX1CQwMxCOPPGK03M/Pz9FNJyIiIiIiIiIiB3Ba4CkmJgaffvop5syZY5DZ9Nxzz+Huu+/G/v378fPPP+Pmm2+2aH9BQUFYvny5s5pLREREREREREQO5rQaTzNnzsS8efOMhtNFRERgyZIlAICTJ0866+OJiIiIiIiIiMjFnJbx1OmHSlo/ViwWW7yNSqXCrl27UF5eDl9fX4wePRrTpk2zah9ERERERERERNR9uj3wpNFosGvXLgDArFmzLN6uuroaL7zwgsGy6OhorFixAvHx8Q5tIxERERERERER2a/bA0/vv/8+cnJyMHv2bIsDT4sXL8aUKVMwatQo+Pv7o7i4GBs3bsS2bdvw+OOPY+vWrRgzZoyTW06uIgiubgERERERERER2UIkCN13W79hwwa89dZbGD58ODZv3oyQkBC79vfOO+9gzZo1t3kplQAAIABJREFUWLBgAVavXt3l+jqdDlqte0QxxGIPaLU6VzfD4dYeK8C/92YbLPv9zKF4eeFYF7XI/bhr3yHnY98he7D/kK3Yd8hW7DtkK/Ydskdf7T+enubLIHVbxtPGjRvx1ltvYeTIkVi3bp3dQScAWLJkCdasWYPTp09btL5WK6ChQWb35/YEISF+bvNd2pPLVUbLlEqNW35XV3HXvkPOx75D9mD/IVux75Ct2HfIVuw7ZI++2n8iIgLNvtctgad169ZhxYoViI2Nxbp16xAWFuaQ/fbr1w8AIJP1vR+ViIiIiIiIiKinc3rg6YsvvsD777+PsWPHYs2aNfpgkSOkpaUBAAYPHuywfRIRERERERERkWN4OHPnq1evxvvvv4+4uDisW7eu06CTWq1Gbm4uioqKDJbn5uaazGgqKSnBm2++CQC4/fbbHdtwIiIiIiIiIiKym9Mynnbu3IlVq1ZBLBZj6tSp+Prrr43WiYqKwuLFiwEAlZWVWLhwIaKionDw4EH9Onv27MGaNWswbdo0REZG6me1O3z4MJRKJWbPno2lS5c662sQEREREREREZGNnBZ4KikpAQBotVqsX7/e5Drx8fH6wJM506dPR35+Pi5cuIDU1FTI5XIEBgZiypQpWLRoERYtWgSRSOTw9hMRERERERERkX2cFnhavnw5li9fbvH60dHRuHjxotHy+Ph4xMfHO7JpRERERERERETUDbplVjsiewiubgCRGxMEAScLG5BXJ8O0ISEYGe7v6iaRnTRaHQQAnmKnlnEkIiIiIrIIA09ERH3Yx0n52HCqdWi0xEOE934Xh+uHOW72Uepea1OKsP5kMXSCgPumRONP1w3lcHQiol6isE6GHRnl0GgF/G7iQIyKCHB1k4iIHIKPQ4mI+iiFWostqaX61xqdgE2nS1zYIrJHemkjPkkuQItKC7lahzUninCysMHVzSIiIgvUtKjwx63p+OZMKballeGPW9NR0iB3dbOIiByCgScioj4qvbQJKq3hYNZTRQxU9FafHi0wWrbqSF73N4SIiKz20/kK1MnU+tdSpRbfppWZXX9vViUe3ZyG5dvPIa2ksTuaSERkMwaeiIiI3MD58majZTnVLS5oCRERWatt2Ht735wpNbEmcKqoHv/ccxEZZU04UVCPp3acQ41U6ewmEpEdlBodsiubodToXN0Ul2DgiYior2LpH7ciCJyKgYioL/g0ucDgtVytw86MCtc0hoi6lFHWhFs+O46HNp7FzZ8ex9k+mKXIwBMREREREZEDSJUaFNTKnPow4JyJDNekvFqnfR4R2ee9g5chVWoBAC0qLd49eNnFLep+nNWOiKiPYsITERGR42xPL8O7By6jrXziLWP745qoINw+fiA8xXzeT9RXZVVKDV5fqm6BRquDpA8dF/rONyUiIgMiRp6IiIgcolmhMQg6AcC+rCq8nXgZr+29aLS+UqNDUb1cnxllyTlZqxNQUCdzVJOJiLoNM56IiIiIiIgscKqoHsfz6xET5oeF4wZA4tEaMdqbVQmtmdF1v1ysxnNzRyDc3wsA8OvlWryyOwsKjQ5DQn3x8V0TuvzcS9VSLN9+HrUtKod9FyJynRaVFsG+fScPiIEn6vFYMJfIOUQcbEdE1C1kKi32XKhEdYsK80aGY/SAAFc3iWzwc3YVXt6drX99tqQRr90yGgDQKNd0um1GaSPmxUagtFGOv+3K1C8vqpdjdVJ+l5/97sFcBp2I3Mj+7Crcc22Uq5vRbfpOiI16BRHH/hB1G/65uReG6Il6Jp0g4Jmd5/HOgctYc6IIj25JQ0ZZk6ubRTb43/FCg9c/ZVaiUa4GAFRKlZ1uW96kxBNb0/G7L08Zvbc/uxrmnrM+9HUq0koa++QsWETurLK5bwWSGXgiIiIiInKSrEqpQdBAqdFh4+kSF7aIbFVQJzdadr6iGTUtKuw6V9Hpth/+mofUToJHzUrTGVPZVVI8veO8dQ0loh7D3OidQ5equ7klrsXAExERERGRk+zJrDRaduhSjQtaQs6g0uiwP6vKqZ8hU2udun8i6n7FDQpXN6FbscYTEREREZGTcBise/v7jxeg449MRGaYOzzMHhHWre1wNWY8ERERERER2YBBJyLqjLn6bdlV0u5tiIsx8ERE1EexuDgRERERUferbO58QgJ3w6F2REREREREHWh1AraeLcW5siZMiAxydXOIqBdiUmQrBp6IiPooEZjyREREZM7KX/OwObUUAJCYw4LwRES2YuCJiKiPYtiJiIjIvLagU2+QVSnFj+crcLKoAbER/lgyOQqeYlZVIXI5c0We+hgGnoiIiIiIiHq5N/bnAAD2ZQGXqlvwxsIxLm4REVErhsGpR2EGBhERERG5mtDLsxT2ZlVBqtS4uhlEfV7vPpI4DjOeiMgmGq0OYg8RRJwajahH6OX3SEREPYJWJ+BUUT3Kmnr/jFMVTUqMjODtHvUduTUt+OF8BSQeIvxuwiAMDvV1dZN4fXYFj0REZBW1Voe3fs5BYk4N+vl54u8LRuG6Yf1c3SyyAWOGREREht76OQc/Zla6uhkOoeUdL/UhpY1y/HFrOpoUrZl+uy9UYdNDkxHm7+Xilpk2pAcExboTh9oRkVU2nS7B7gtVUGp0KG9S4oUfLkCm0rq6WdTH/ZxdhSe2puO5nedxvrzJ1c0hsptWJ+CzowV4ZNNZvLHvIhpkalc3icjtVTYr3SboBACfHS1wdROIus2O9HJ90AkAaltU2HPB9X/P5sK/vp7ibm2HqzHwRERWWZ1cYPBaqdFhX3aVaxpDBOB0UQNe3p2N1JJGJOXVYdl351AnU7m6WUR2+fxYAb46UYQLFc34MbMSL/yQ6eomEbm9nzIrXN0Eh0rOq3N1E3oFhVqL3JoWaHXMEOvNNpwqMVq2NqW429tR0iDHB4mX8OnRApQ0yM2up+tjGYkcakdEdiupN39QpZ7LXepzfXG80OB1i0qL7zMqsHTGEBe1qPcTBMGu/tFWlNdd+pgrdLxYPlvahMpmJQYEeruoRUTuT6dzdQuoux28VINXd2dBpRUQGeSN1XdPRHRI3xoC5c6Ebi7tXdWsxB1fndK/XnOiCBsfnGxy3b4WeGLGExFRH+UuIYGzJY1Gyw5frnFBS3q/c2VNuH/DGcz9+Bj+te8iVBrr78K2pJbiN1+k4LdfpGDb2TIntLLvqmhSuLoJRO7NXU6MZBGtTsBbP+dApW0NAJQ1KfFJh8x+Imu8nXjJaNnHyfkm1+1rCXYMPBGR3frYcZN6AYW67z22tvfvUKMT8OzO87hU3YIWlRY/ZVZibUqRVftIL23E+4dyUS1VoUqqwrsHL+NcGWtuOUofezhK1O0a5ayl1pdklDUZ1AQCgF8uVruoNdQbFdXLsT+rSj+kLsnE8NYTBfUmtxX62EmdgSfq8frY32SvxN+od3LnUVD5dTJXN6HXOZZfh8YOF+BfnrAu8GSqkG3HoZC9hUYnoLRR3ucuDIn6sr4WdFBpdChvUvTZ45xMzclxyHb7s6pw99pTeGVPNu5acwoHL1mXbd/XMp5Y44l6FDe+D3Zr3T1+mhyjqIfU5kopqMey7ecAAHdfE4nn543ok7WBlBod1pwoxPnyZlwTFYw/TB8Mibj7ng+VNto/jOt0sfGwx1OFpp/0OVNSbi1WJ+ejSaHBHRMH4bEZQ6zqU2dLGvH8rkw0KjSICvbBqjsn9Llpj4n6oro+NHvkz9lVeGN/DpQaHcYOCMDKxeMR6tczp513Fne60lBpdEgrbYTYQ4SJkUHw7MbrB1cob1Jgf1YVJGIP3DK2P8L9u7/vfnK0QB880grAiz9csGr7vhbwZeCJiKiXEgQB608W47v0cgR4i/FkwjDcMCLM4u0vVbc4pA1rU4qxI6McQT4SPJkQg4ThlrehUa7WB50A4Nu0MgT5SPCn62Psbpu1dIKAqivFm10R+FqReAm7r0zjfbKoAfVyNV6YP7Lb2+Fo3X1ZVSNV4oUfLkBz5Wrwi2OFGBrqi5vG9Ld4H//ad1Gf/VXaqMB/D+Xiw8XjndJed1dYJ8PXp0rQqFDjtvEDrTpGuYu+dnNBPZ9CrdUHnQAgq1KKL48X4Xk3OOdYw12ecclUWiz7LgPnypsBAFMHB+ODO8bDx1Ps4pZZR6XRYX92FcqbFLhhRBjGDAg0uV5lsxJ/+CYNtS2tMxjvSC/Dugeu7c6mQqHWoszOB3Z9LePJvUOhRERu7NClGqxOLkBlsxK5NTK88MMFVDUrLd5e44AzXmJODT492tqGS9UteHZnJqqllrfB1FCur6wc3mVKTD/rslOyKpvxm89TcNv/TuJ3X51CQa31Q/WkSg2O5tUhr7bF6htNjU7QB53afJvmuMLcMpUWR/PrcLna+rbZq7vvub9LLzfq2+8fyrV4+7JGhVH219F866ckr5Eq8c2ZEmxOLUXNlYvjvkam0uJP2zKw63wFDl+uxd++z8Spou7PgCP3IggCaqTKPjcjlCP9erlWH3Rqs82B5xzqXocv1+iDTkBr9rG5ukLOVNmsxKbTJdh2thT1MuvPey/vzsIb+3Pwv+NFWLo5zez5YmdGuT7oBADFDQok5Zo+T0uVWlx2wINWZ+hrxzAGnoioV2pRaXC8oA4FdtTy0Wh1aHBxIdGKJgWO5tWhwYb0/o+SDGfJ0OoEfJdu+YWjRmt/Ae5//JRltGyNFYGjEwXW39Bbwtpz+Zv7c/TBgbJGBd45YDwrSWcK62S4a+1pPLPzPO5dd8ZkraPOdPVbXK5pwdqUIuzOrLR6prnSRjnuXnsKz+w4j/s2nMGqI6ZnV3EWAcCXxwuRkl+HzIpmnClucEjfM8dUMXNrhs/YMpNfR/UyFR7dnIYPDufhv4dy8ejmNJv+xnu7xJxqg6CbgNYMNGvUyVT486ZU3PrZCbz0YxaaO9QhI8uVNsrxduIlvPTjBRw1UQDXEs0KDY7m1+kL6Xa3iiYF7ttwBrd+noJbPj2BNBOzmtqqxoqHJr1do6LvHY9McZOEJ7yx76LRsncPXu7WNlQ1K7H0m7P48Nc8vHswF49vSTc6XusEAXVmAlKljXIcvlyrf63WCth4usTkuqYeUH5iZuY4APj9N2eRXuq4YwUAVEvtf6BU38euCzjUjqgX0Wh1+OBwHo7k1mJIqC9emD8SQ/v5ubpZ3Z7RUFAnw91rT+tfJwzvhw/usG4YzP6sKqxIvIQWlRYzhobi7dvHwt+rew+Jey5U4vW9FyEA8PX0wMrFE3BtdHCX2xXXy/HOgUsoaTBO8T1r4UW4XK2FVOWcoprfpZfjqdnDIQLMpnnXyVQ4kFODgjrzNy/Zlc04XlCPoaG+mDMqHB5W5MR37JLlTQoU1MkwYVAQArwNf2epUmM07PB0cSOmvX/EYNlLC0ZCqtRi9sgwo7+7jadLDJ6+rU0pxn2ToxHi52lRe80N7cuqbEaTXGM0HHHt/ddAqtTC19NDXwdKayaDbfOZUlS1u0DaeLoEd10zCFHBhllhagcEXMz5/FghPm8XcIgbGIiP75pg9FsAQF5tC949mIvSBjnmjAzHU7OHQ+Jh+P8jCAJya2VolKsxflAQvCVXn6OZ6yafHy3AI/GD4Sn2wLmyJsg1WozuH4B+HWuaOOBO5JeLNShrunoTW9aoQGJONe66JtKu/fa2Z6OHTBRaTSu1bpbD1/ZcxIkrdcISc6oBCFhx2zhHNK9PUai1+N2Xp/SvE3Nq8MndEzBtSKjF+8ipkuLJbzP0w1CfnTMc90+JdnhbO/PB4Tzk1rQ+cKqXq/Hqnmz88Hi8Q4ZH/9gh69Rd6ATBxPnTXUIuBLTWF+qoWWldkF4QBBTUyVHTosSEQUFmr99+OFeBN3/OQYivJx6fORT3XNt6XtubVWVwrVFYL0dSXi0WjhsAoPX69O8/XkCdTI1+fp64NjoYIgC3jhuAG0aE4WCO8fniWL7lWVteEvP5NEqNDltSyzApqutrbEv9c2+23fswdQ3kzvrWtyWyU36tDMl5tRgY5IM5I8O6vXDf/04U6VOhK5qVeHrHeex8dJrLCzF3d6po+6ATACTn1aFaqkREgLdF20uVGry276L+Rv1EYT2+PlXSrXWFdIKAlb/m6W8k5WodPj9WgM/umaRfR67W4lxZE6JDfBEZ7IMGuRr7s6rwXifDhtJKm/QXmUqNDh8n5eNUUT2iglsDlf0DvLDqSL7Zp0gAkJxXC4mHCKMiAhDm74X8WhlOFTVg2IBATB4YgItVUtTJVPjfcfOZTTesOgoAiAz2wa7H4gG0Pg1bnZyPwjo5MiuazW4LAF+dKMRnRw0DFR/eMR6rjuThx8xKhPt7dTp8qX3h9O/SyvDOgatP/p6ZPRxjBwagqE4OmVprcbBuReLlK20rwvu/i8PUISE4X96E00UN+P5chcG6AoBd5yvw27gBOFFQj/ImBXw8xbh9/AAEekuQU92CM8UNaFRo0KLUmE2Jf3jjWaNlmRXNiP9vksGyR2cMMdvurWeNs+Da34ACwKTIIKSbyBQyR6XR4dClGpwuboC3xAMTI4OQYkUR8cyKZrx3KBev3DjKoIC6ThDw1PbzqLwyZHRzaimCfCR4bOZQ/TqCIODtxMvYkVEOoHVY5af3TOqysOiXJ4qw7mSxySGmAwO98dFdExAd4otiBxTdN/Wk+d2Dl+0OPFnrTHEDVicVoEmhxh0TB+GBqd0bJLCXQq3VB53aJObUYIWV+xEEAYX1ctS2qDBhUFCnNyjuavcF46DKk9+ew6m/3mDxPtamFBnMfPlJcgHunBRpEPh1to6zRlU0K1FQJ8ewMPsfwincdIazrEop4gYa1sopqnfMzK/tr4vnjgzr1gkx2qi1Opwvb0aQjwTDw/wsviaWKjVYvv28k1vnOp1dmqu1OmSWNyOw3f/ZB4fzsDm1FAAQHeKDz++ZhP6BhtfV286W4t2DrdegDXI13j14GdEhPrhuWD98nGSccbTqSD4WjhsAQRDwyu4sffZxnUyNA1cCTYk5Nfht3ACMCPe36/t2dU+WmFONFRhr0b50goAWpRaBPuZDJefLO7+OtfRz+hIGnogslFHWhCe/zdCPiZ8fG463u/mpa8chTKWNCmRWNGP8oKBubUdHlt64O9PLP2XhiyXXWLTu3qwqo+yQr04UWR14OlPcgB8zKxHgJcaSyVGIDrG8rlBxvdxo+M+Z4kY8tjnNZAAgMtjH4iKG7yRexnNzRyBhZbJ+WW6NDEdyazvZ6qpnd2YavPYSi6Ay9TjNAmWNCqPMIUu0DzoBrYGKGz89rn9tSc0cc5/74a95VrenPZlaiz9/m9Hleh8n5RtdiK2087PNsbculjVBJ0EQ8PtvzhpkiZkKbnVld2YlUgrq8e0fpuqf+p0tadQHndp8fqxQH3gqa1Rg/clifdAJAArq5NiZUY7H2wWnzDFX16yiWWkU0O6JrHnE0CBT4+kd5/XnrA9/zcPAIG/Mj41wTuNMsPeaWuWgIZl3rjmF4nYZonufmI5wCx9UtLlc3YKzpY2IDvHBzJh+DmmXNQRBwPfnKnCysAGx/f1x/5RoqwI+byfaP+wmsUNGglKjw4mCeswe6dqC8TIHBYzc9Rbw27QyxN0yWv+6XqYye8xuUqhx+FIt1Dod5o4KN84IbSejrAmPbU7T/7/5e4kxMyYUAwJ9cP+UKH3Q4nJ1CzQ6HWL7BxhlXmWUNWF1Uj7qZCrcFjcQD02LtuphaoNMjT9/m4HLNa3no99NGIh/3Diqy31kljfh99+kWfw53aG2RYW82haMHRBocSZMvUxldqKYjv25TqZCbk0L1FoBT++4GnAbGOiNz+6dqA86AUBJgwLb0sqwbNYwyFRaqLU6BPt66oNO7T2943yXAezLNS0G2VAd/ZRZibEDAjrdR1fybajNaUpSbq1+gpHpQ0Pw9m3jnJaZZC5T3V0x8ERkoY2nSwwKMR7IqUFZowKRwT4ubFXrycHVgacmC2tuCIIAkUgEhVqLXy/XolGhxg0jwjAwyPj/UCcIUGl0qGhSYltaGVRaHSZFBpktuBzm3/lNhEarQ2ZFM8L8vfCTA9LpM8ubsOy7c/ob2UOXarD191MtPjlpzdyRmQsAWDNzxo6McoMbc3vZGnQi96ATBKi1At7cfxGXqltw3+Qoh8yICLQGEL8/V4EHr2TiFHaSbZRfK8Mjm1IhVxsHI744VmhR4MmVHJGXas1f4vfnyo2KB39wOK97A0923sqLHPC/djSvziDoBADPfZ+JDQ9OtngfiRer8VK7enZ3TByIf9wYa3fbLFUvU+H1fRf1w04Sc6pxuboFb/3Wsqf3zqR2Yr02Z9LoBEgVGouHQ/dmuzMrDbJL92ZVmV33j1vT9UMZN5wsxlf3X2s2m/TDw7kGf+EtKq0+OLnpTAmSn07Av3/JwZ4LrZ93bVQQVt45Ab5XhnBJlRos/+6cPnD4UVI+IgK9cOvYARZ/t+/PleuDTq2vK3DvtVEYGdF59synVtZhdLafs6vw6p5s6ITWAN7quyYgrotr+6TcWjz3fWan67T55WK1yZqcwJURFCYyv9afLMZ3aWVosaAsg7kJOGpbVEgrabToTJBVKbVgLedSanT4x09ZUFw5d6YUNuDL40V4Zs5wp3yeuXsBd8XAE/UZ+bUyrPw1D2VNCtw4OgKPzhhiVc0YU7Uq9mdX4Q/TzQ9x6Q7WXtgX1smw5kgu5GotFk0YZJR+bfIzrgSM7PGfA5dNBo2+PF6EL++7BkNCW7OFDl6qwYs/XDC5j10dhjO1NyLcfJp9TYsKf96W3mk9IWt1HLJTJVXh0KUa3DZ+oEXbO+KGiqg7SJUazF99NdvsrV+sK7zelZW/5ukDT+JO/iy2p5eZDDp1pHbjQOnFKqlFdeAAINVEJmrHbLKuNMjUeO/QZWRXSjF1SAiemT3cqum5e8I19TM7jW+orL3BeanDDdvOjAr8de7IbhlitjerEv/cY1w4+OeL1XjpxlEurxFi7aVBbk0LdqSXQ0BrAG9UhH1ZDrb42/eZ+LVdBvDBv1yHQB+JW5+VZ36YrM9K2Z5u/sFUW9AJAMqalDiYU6Ov4dPRuS6GGr31c45BkOtsaRO+OFaIv8wahoM51fj6VIlRttoHh/KsCjytTi4wWrb+VDHeXDim0+1SChss/oyOBEHAngtV2JZWBj9PDzwzewRG25GtoxMEvH8oF22XlC0qLT5JLsDquyd2up2lQSetTjAbdGpj7qGPJUEnAHhmh/khi49vTceEQV3fa/QEOzPK9UGnNpvOlKB/oBemDQlx+PFK1zvj9jZj4Il6PEdct2p0Av7yXYZ+BoIvjhUiwFuC+yZH2bVfsYtrKwHWXdg3ytV44OtU/c3H3gtVWPvAtRhpZlz1sfw6vLE/B7UtKtw4OgIv3zTKdBuu/FvepMD7B3NR2azETWMicN/kKEjEHjh0qcZsplK9XI0fz1fgL7OG4c/fZuB0kW0XA8fy6xDs64mZMaFGQ94+OpJnUdDJVIBNo9UBIpFRceP2M2+0+SmzEreNH4j9WVV4ZU82Rob7491F40wOwesBXYfIIocvWTZE0xE6C3B3NZzvnnWnsXLxeJMBF3cR4G150McRx5iXdmfpj8mF9XLoBMGqTB97z989+Th5urgB1w9z7pA7mUprMujUprJZ6fLAkzUqmhT449Z0fZb03qxKbHpoit2Z43k1LRY9RAOAS9VSg6ATANy19hT2/3mmy+tlOludTNXp0DlT3j142WzgqSumMqs2ni5BSmG92azZegfMNCztpKh2SYMcd3x1yuz7ljheUI/X280i9+DGVPy6/Hr4eVl+fAaA1JIGPLE1A94SD6Ps1JNdXAtbMkuqUqODRifgYE61Ve1yhq6ClJ25/sMkRAb7OOThsVSpMThmHrxUgyO5tRga6oslk6Pwvpkaqh8cbi2TcMOIMNw+vrUYuiMw44nIhTo751c1K3E0vw79/Lxw3bBQqwp7pxTWG017+d9DuXYHniSdPZ43QycI0OkElxRg/PlitcETb4VGh29Ol+Cf7cb+t1FqdAZjwH+5WI3GTi4IBEHAk99m6Gday66SIr20Ce/9Lg4vmMlgarPuZDEemznU5qAT0HpSazux3T8lCqP7ByBheD8E+Xjq07y7ohOuZlwIgoDPjhZgS2qZwRO5YB+J2aEqJQ1yfJtWhv9cKWR9uaYFd3x1Cr88ORMhvobp/O59eUvu5M2fc5z+GRcrpfgxswK/mgjoWiq/VoZ/Ozgbq70/bUvH3+aNNBmo1+oEnC1pRF6tDFOHOG7WnI7+tS8HOVUteHbOcIfdJNdIlWhSahAV7AtviQd+vVyLpNxaBPt6Gh2Td2ZU4KkbhqNKqkSYnxeCfbsYpuTG19RB7W5eypsUSCmox6wRYQjrosh9e5erWzAi3Hwx5Ce7qCXX3ROcmGKuFzYp1EjOq4NYJML1w/shwFuC3RcqDYbmS5Va7Mwox19mDbOrDf87XmhxtvGT354zWtZWb9Hdz8u7zlXgD9OHdHotZ4miejnOWVEXsCNrh2o3ytU4ml8HiUdrX7JnBmJ7g04ADK6N2zy2JQ1j+gdgUJAPlkyOMipKrVBr8dT2cyisl2P60FD8ZdYwPLG19e+7Y9DJlCaFGgdzauDnJUbC8DDUybuucwkAD2w4Y3T/09uotILDRizM/fgYXr5xFGaNCMOO9HJ8cfxqPdFPTGTPdXQktxZHcmtx02jHDFlXanRIvFiNBQ7aX0/HwBP1eKWNchTUyfD4lnQ0XDlZzhreD6/dMhrHCuoQ4CVBwvB+nV6E51Q5Z9xwxyyYrnyXVobPjhZArRVw1zWDsGzWMLtvHqwJln9rImPgx8xKk4Gn5DzjG8DOnsBcrJLqg05tfs2tRUGdZcX+9mdbFhyyxDdnWgskDgn1xWsmvps5giCg7dLzWEE91qQUG63TqNCYrZ9UJVXpg07t/ZRZqR9KRETGHtzAsdjRAAAgAElEQVSY2un7s9oVyu+MudkBHeFMcSPuW38GH985AdNjQqHS6HC8oB5/22XhcAehteD9e4vGYfbIcACthXXza1twTVQwhvazbFauzaml2Jxaivmx4XgyYZh+mLI1tDoBuTUtSM6rw/+OF0KjEzA8zA/BPhKcLe38hvLutadR06JCsI8E//ebMZgR0w9SpQZH8+pQJVVi2pAQjO4fYPW5TRAEFNbJUdqkwPAwPwwyUfvPkZZvP4f7p0R1WSjc3KxDq5Pz8endEw1mgsKVwOe/bh2tn0K8M/dtOINro4PxwR1xJm+mu5r9s6pZ2eXvr9LocPiycamAzmi0Oosfju3NqsLkwSGQqbRY9OVJs+sdXn4dvjQxE+q6k8V2B57Km5Sol6lw/Mrff0mDHOVNSoT5eyGmfwA8dQJSSxqRV9uiv47sSOgDmQfyKw/RGi2sy9lmw8lijBsYiMyKZuzPrnJYjb+uqLU67DpXYTArra+nBxaOG4BzZU0Y1d/0sKe2I49Gq4PYQ6Q/Fln7G+/PrMD/juRhzqhwPDg1GoIgwNxI7kvVLfr/ly+OF+Lw8uvg7yXBz9lV2HOhyqAG0t6sqk7rbHX02dECowlEVt053qJt8xxUcNudvPXLJf2x2lY/X3RcFtlLP2Uh2FeCaUNCHbbPnkok9IUj7RVqtRYNDe7xBxgS4uc236W99tN0tjdhUGCnaZp+nmL8+tT10OoE/PdQLrKrpFg0YSAmRQYh2McTt3+ZYrI2yMnnZqGsSQGxSGSywHV7pmbIenBqNJ6ebVxwrqq5tSA2ACy5NhLhAd7IrWnBkvVnDNZ757axmNche0au1qJaqkI/P0+jFHpTbXjtllj8Nu7qkz6pUoPaFhXCA7yMLmSXrD9tMH6/zfzYcPzp+hjEtLvxMXWiM2dAoDcenTHEZLaBj8TDaLx0TzZ2QAC8JR5I6+Lmy1rXRgdjYmQQmhUaeEs8cP2wfli23fjJKxH1fEeeuh43rDpq8/ZTBgfjTLHjhgR+evdEXKhoxkdXZlH8+M4J+M/ByyjqpFi7o4jQOvV2xwLe6+6/Bn/ddQG1Jmag7DgDUoNMbTBrZZu9T0zHrZ+nGC2PGxiI/oHeeDLB8LxlSlezai4c1x//utW4HoxGq8PyHec7zcR9c+EYvLonu9P9P3HdUBzNr+ty6u3hYX6YHB2MiABv3DQmApnlzXili30DwG1xA/DyTbEQm3gQ1qLS4LHN6QbFlztKeW4WzhQ3QAQRvCUeWLr56kxfC8f1x6s3j9Y/ZLNlhtI291wTqb8u6ujrB6+Fv5cEi9dczUbpH+CFSVHBuGFEGKYNCUGwjwS5tTI8+LXpIHU/P0+jmWKpd9r9x+lIyqu1aybGaUNCcOrK3+6oCH9US1WQq7UWZRcRucLiiYPw0o2mS5r0JhER5oc9M/DUS/W1wJMl7r4m0mwdIUs9P28E1p9szXJ5bu4IzI+NgFrbOrNa+wui9p5MiEH80FAEeUswKNgHTQo17ll7Wv9EKdhHgu+WTsN/D+WafMIR7u8FhUaL2SPDUStV4URh6xO7EF9P/N9vxmD60FC8nXjJbDHIJ64bisdmDkWzQoNtaaVG09C3GRbm1+VUo7+JG4B7r43EqHB//GN3tsmC6qYE+0gwITIIyXmmZ7UgIiIypX+AV6fTbHfFVH0UIiKi3ubZOcNx/5TePUKCgacrGHjq+ewJPPVkvxnXH7strDNEREREREREfUvHjODeprPAk+urEhL1AQw6ERERERERUV/k1OLiFRUVWLlyJZKSktDQ0ID+/ftj/vz5WLZsGYKDLZ/1paGhAatXr8aBAwdQVVWFkJAQzJo1C08//TQGDrRsFgvqHVTmqvYRERERERER9WDXDQvFk3NHYmiAF3w8xZCptJj9ke11Id2F0wJPRUVFWLJkCWprazF//nwMHz4cGRkZ2LBhA5KSkrB582aEhnZdvb2+vh5LlixBQUEBZsyYgYULFyIvLw87duzAr7/+iq1bt2Lw4MHO+hrUzb48bro+EREZWziuP+aNisCsEf3wduIl7Myo0L9nrqbXhEGBkHiIupy5ypF+eDwenmIPpBY3IL20yWyB2c58cvcE/JRZCV9PMe69NgqDQ31RLVUis7wZl2taUCNVIbOiudMiugAwZ2QYfD3FGDMgAHEDAzEi3B9nSxqRVtqEDaeMZzG0xJMJMfppeCcMCsTwMH+cLW3ssrDz3+aOwL2To1BYJ8MDX6ca1KlZd/81iBsUhBqpEgHeEvh4igG0Tqns5yVBSYMctS0qjB8UBG+JB5oUagR6S1DSoMB/Dl5GjVSFhOH98Ej8YGRXSrEi8ZLJ9vQP8MLOR+Oh1Oiw50Il3jtk21Dn6UND8PFdE42WK9RazF99rEc8VEh8ciaCfT0NlhXUyfDE1nR9UWJ/LzHeWxSHP3cxjT0RERFRe5Ojg7Fy8Xj4eIoNyuL4eYkt2v7bP0x1ZvNczmk1nh599FEkJyfjlVdewUMPPaRfvmLFCqxbtw733nsv3njjjS73889//hNbt27FH/7wB/z973/XL9+wYQPeeustJCQk4KuvvrKoTazx1PPZM2MKuafkpxPgLfFA4sVq7MuqQnmTAjndNJWvK2x8aDJGt5siuLhejsJ6GRrlGmw4VYxgHwleXDAKI8L9jbYtrpejrFGBCZFB+pNcg1yNCxXNiI3wR3iAt37d4wV1eHV3tr4I/p2TBpktYG+JtgK/I8L9IFdpodEJmDsqHM/OGWFytqU2Sbm1WJtSjHPlrYGwMH8v/OPGUXjhhwvQ6gTE9PPFR3dO6HLWyfaqpUo8suksqqUqjIrwx1f3XQNfz65P+uaOP3EDA/FkQgwmRAZZtJ82giCgUaFBgLcE+7Iq0aLUYu6ocPQP9Da9rvzKhAS+EqunoreoLXINgn0lKG9S4vDlGgR4STAvNtxg9kxbj8GmgjrtNSs0GBgRAGmTHPH/TbLpM+zxxsLRuHWs6entZSotzpU1ITLYB4OvTE0/9+OjkCq13dlEIiIi6sV2/3G6/hqv4736MzvO42h+55Mw9fb6ToALiosXFRXhxhtvRFRUFBITE+HhcbWUlFQqxaxZsyAIAo4dOwY/P/PT4La0tOC6666Dh4cHkpKSEBBw9WZMp9NhwYIFKC0tRWJiokVZTww89Xx7LlTitb0XXd0M6kFMHYRzqqR4wMyUyr3ZjaMj8O/fju22z9PqBDQq1Ojn56VfVtGkwNnSRmi0Am4YEYakvFocvlSL6BBfPHNTLASlGnUyNfr5eTo8OFLbokKonyc8HLxfS5kKuhxadp1BYMbdFdTKcPe601ZtMzMmFKvunNDlem3nrb9+n4kjubW2NtEmJ5+bZVV/bZCrceMnx53YIiIiInIXc0eF4z+3j9O/7nivfr68Ccu+O4cWlfFDrVER/vjm4Snd0k5n6yzw5JSr6ZSUFABAQkKCQdAJAAICAjB58mQkJycjPT0dM2fONLuf9PR0KBQKJCQkGASdAMDDwwMJCQnYunUrTpw4weF2buKm0REMPJHeJ3ebvpkdFWGc7WONQ8uuQ1mjoscFr/5x46hu/Tyxh8gg6AQAA4N8cGu77KLfxg3Eb+Naa+mF+HmhQaVBmL/hNo7irP1aatNDkw36xKMzhvSpoBMAxIT54bN7JuJP27oearYgNhxvLhwDidi6eUre/10cDl+qwfM/XOiwvwiIPYD92dVW7a8rJ561LugEACG+njjx7CycKqpHcl4dpEoNvCVi7MjoPCvwD9MHY22KbUM2HWVSZBDSyzofSvvUDcPw4/lK5Ne53wMsIleaGBmEjC7+/hxJ4iHCs3NG4MvjhaiXq7vtc6nvuueaSCy/YRj2ZlXh379c6nTdhOH90KLU2FzeYemMIYgfEoItqaUI9fPEI/GD8eHhPFyqbsFt4wdgZkw/JOXWIiLQGzePiYCfpxirjuRj4+kSAK0Pxv55y2h4iUW4+dMT0OgEPDg1GqkljSisk6FFpcWfrh+K38cPgYcI2JtVhQsVzZgRE4r8WhnOFDeiXq7G1MHBmDYkBG/uz0GVVGXQxgmDgvDuonFdXsOOHxSE7x+Lx7myJgwL80N0iK9N/ye9mVMynt555x2sWbMGL774IpYuXWr0/htvvIFNmzbhtddew/333292P5s2bcIbb7yBBx98EK+++qrR+1999RX+85//4LHHHsPzzz/fZbuY8dQ7yNVa3L32NCqblXbtZ35sOEaG+2PXuQpU2LkvdyL2EOGGEWE4dKnG1U3p1IyYUHx4x3izw7R2Z1bi9X3WBym/fvBajBnQGo0va1Rg0Zcn7WqnOW8sHI0PDuUZXAh+eMd4HMuvQ1JeLcqbrvbJG0aE4e3bxsLTyhv47ubOx502zQoNsquaEernhZEmhjOS7WztP2qtDkqNDj6eYkg6GbbZpkaqxN6sKnhLxLh9/AB9fSxXEwQBGWVN0OgEjB0QCJ0gwN9LbHFQTKXRoU6mQqCPBP5ezguIVkuVCPX1tDqgaC+NTkBVsxJBPhKj39qWviNVaiDxEMHHUwy5WgulWocQP/PDQdso1Fo0KzX6YbWeYg94ikWQqbT6/XUkCAKqpSqE+XtB7CFCi0oDEUQW1fXQaHVQaHTwlnigSqrEtrNlqJOp8WRCDAK9JUZ9RK7WXuk7V/uAUqNDvUyFEF9P1MnU8JZ4GGWlylRaCGjdrlmhgafY9HexhEYnoF6mQri/F0QiEcqbFMgsb8aIcH8MDvU1+O3UWh0a5WqDod4A0CBTw9vTA76eYhTXy1HRrMDwMH+E+XtBodbibGkjfCVihPl7Yd3JIshUWtwwMgw3je6vvy5QanT4ObsKF6ukqGhSYvSAANw0OgJBPhJUNaswLMwP/cMD9H2n7f+gRalFQZ0MUSE+iAo2ffPXIFPDS+KBc+VN8PUUY9zAQIuOP8DV/tDP38vibfT/t1od6uVqRAQYD8m2hELdOtTdz0tsNnvYmv7Z9nckEomg1urMHrMyy5sgU2sxKiIAHiIgyKfrvzVnat+/uqLVCUgrbcSFimZEhfhiZkwofDvU6AFarw+0utbbZolYpP+/kCo1kCo18BCJ0D/QG3K1Flqd5cd3nSBAptLCS+wBL8nV465GJ0Cu0sLXy7Jzn61kKi1aVBr4e0n0fUIQBJwvb4ZSo8OkqCCHXp+29VFrzn+9UV+4Zjal2zOepFIpACAw0PQHty1vbm7udD9t73fMdrJ2P9S7+HqK8dMfpztsf4/NHGrxuhqtDi0qLXw9xQYHf2tdqGhGg1yNYWF+CPPzMtqXXK2FWqtDoLdxLZe290QQQUDrySjM3wueYg9UNSuRXyvDoGAfDAk1vFgSBAFVUhX6+Xl2eoKw90Co1QmQKjXw8RTD24r/I6VGB6my62yZZoUGIhG6zDT5TdwADAr2RnppE0J8PXHr2P7w8RRDqtSgrFGBYF9PHMmtRf8AL0yIDDLK7AGAyGAfg6F8DXI1RIBBrZr8WhmqmpUY1d8fwT6eOJBTjdxaGeIGBuKGEWGdttFUTZnrh/fD8/NHdroduU6gjwTThnQ98QV1n9Ybf8uPNeEB3nhoWs/LghaJRJgUZfmMvh15STysqnVmK1tveO0l8RAhMthx36/tHCIIAnw9xRbXZ/PxFJsMyHR2ThJdueFsY01gUCL2QMCV/h0V7Itn54zodH1T38O7Xd+IDDb9PdsHGQJ97Lv8l3iIDPrJoCAfDDLTNz3FHkZBJwAGQcDBob76+mpA628wM6af/vWrN482uW9viQduGz8Qt5l4L9TEOb/t/8DfS2Ky1p6p9k0fav35oGN/sIZE7GHX36AlwURr+mf7ft/ZNV/coCCL99kdLAkytxF7iDBlcAimDA7pdD1zfzcB3hKD/ydrakECgIdIZPL4IvEQ2f23agk/L7FREFIkEmFCpHN+057yMIi6X58aQyAWixASYr6mVG8iFnu4zXfpacIdsI/ruvhtOju1dfpeiB9iB5u/CAoN7TpDwxF9p/Nwi3mmS/sa6vy0b2heiB/mjY802j56QOvJcnQn/1cmP9vEh1/b4f/qnhl9NwuGxx2yB/sP2cqeviMIgls/VafO8bhDtmLfIXuw/xhzSuCpLUPJXCZS23JzGVFt2t5vy6CydT9ttFrBbVLe+mr6HtmPfYdsxb5D9mD/IVux75Ct2HfIVuw7ZI++2n86G2rnlAH8w4cPBwAUFBSYfL+wsBAAMGzYsE730/Z+V/uJiYmxvpFERERERERERORUTgk8TZ/eWp8nOTkZOp3O4D2pVIrU1FT4+vpi0qRJne5n0qRJ8PHxQWpqqlHWk06nQ3JyMgBgxowZDmw9ERERERERERE5glMCT0OGDEFCQgJKS0uxadMmg/c++ugjyGQy3H777fDzuzruMTc3F7m5uQbr+vv7Y9GiRZDJZPj4448N3tu4cSNKS0uRkJCAwYN7XhFRIiIiIiIiIqK+TiQIguCMHRcVFWHJkiWora3F/PnzMWLECKSnpyMlJQUxMTHYsmULQkOvFv4dPbp1xoqLFw2nR6+vr8eSJUtQUFCAGTNmYOLEicjNzcWBAwcQFhaGLVu2YMiQIRa1Sa3Wus1Yy746bpTsx75DtmLfIXuw/5Ct2HfIVuw7ZCv2HbJHX+0/3V7jCWjNetq+fTsWL16MjIwMrF27FsXFxXj44Yexbds2g6BTZ0JDQ7F161Y89NBDKCoqwtq1a5GRkYHFixdjx44dFgediIiIiIiIiIioezkt46knYsYTEfsO2Y59h+zB/kO2Yt8hW7HvkK3Yd8gefbX/uCTjiYiIiIiIiIiI+jYGnoiIiIiIiIiIyCkYeCIiIiIiIiIiIqdg4ImIiIiIiIiIiJyCgSciIiIiIiIiInIKBp6IiIiIiIiIiMgpGHgiIiIiIiIiIiKnYOCJiIiIiIiIiIicgoEnIiIiIiIiIiJyCgaeiIiIiIiIiIjIKRh4IiIiIiIiIiIip2DgiYiIiIiIiIiInIKBJyIiIiIiIiIicgoGnoiIiIiIiIiIyClEgiAIrm4EERERERERERG5H2Y8ERERERERERGRUzDwRERERERERERETsHAExEREREREREROQUDT0RERERERERE5BQMPBERERERERERkVMw8ERERERERERERE7BwBMRERERERERETmFxNUNIMtVVFRg5cqVSEpKQkNDA/r374/58+dj2bJlCA4OdnXzyAr19fVITEzE4cOHkZOTg8rKSnh6eiI2NhaLFy/GnXfeCQ+Pq3HhkpISzJ8/3+z+Fi5ciA8++MDkezt37sSmTZuQm5sLDw8PjBs3DkuXLsXcuXNNrq/VavH1119j+/btKCwshI+PDyZNmoQ///nPmDx5ssltFAoFvvjiC+zevRtlZWUICAhAfHw8nnrqKYwYMcKK/xmy1Lx581BaWmryvfDwcBw9etRoeWpqKj799FOkp6dDoVBg6NChuPPOO/HQQw9BLBab3NehQ4ewZs0aXLhwATqdDiNHjsT999+PO+64w2zbuqPPkW127NiBl156qdN1PDw8kJWVBYDHnr5o3759OHXqFLKyspCdnY2WlhbcdttteO+998xu407HFvYp+1jTfwoKCvDzzz8jOTkZhYWFqK2tRVBQECZNmoRHHnkEM2bMMNqmq2PY66+/jvvuu89ouS2/a0NDA1avXo0DBw6gqqoKISEhmDVrFp5++mkMHDjQ5Da8VredNX3HHc9NtvQ3usqa/vP3v/8dO3fu7HR/M2bMwPr16/Wveeyxn0gQBMHVjaCuFRUVYcmSJaitrcX8+fMxfPhwZGRkICUlBcOGDcPmzZsRGhrq6maShTZv3ozXX38dERERmD59OiIjI1FTU4NffvkFzc3NuPnmm7Fy5UqIRCIAV0+wY8aMwYIFC4z2N2rUKNxyyy1Gy9955x2sWbMGAwcOxM033wy1Wo09e/agoaEBr776Kh588EGD9QVBwNNPP439+/dj2LBhmDt3LhobG7F3714olUqsWrXK6PNVKhUeeeQRpKamYvz48ZgxYwYqKiqwb98+eHp6Yv369Zg0aZID//cIaA08NTU14ZFHHjF6z8/PD48++qjBssTERDz11FPw9vbGrbfeiuDgYBw6dAj5+fm4+eabsWrVKqP9bNy4EW+++SZCQkKwcOFCeHp6Yv/+/aioqMDSpUvx4osvGm3THX2ObJeVlYXExEST750+fRonTpzAnDlz8PnnnwPgsacvWrRoEbKzs+Hn54eBAwciLy+v08CTOx1b2KfsZ03/efbZZ7Fnzx6MHDkSU6ZMQXBwMPLz83Hw4EFotVq8/PLLePjhhw22abv5mz9/PsaOHWu0zzlz5mDChAkGy2z5Xevr67FkyRIUFBRgxowZmDBhAvLy8nDgwAGEhYVh69atGDx4sME2vFa3jzV9x93OTbb0NzJkTf9JTEzUP2DraNeuXSguLsYLL7xgcC3NY48DCNQrLF26VIiNjRU2bNhgsPzf//63EBsbK7z66qsuahnZ4tixY8KBAwcErVZrsLyqqkqYPXu2EBsbK+zbt0+/vLi4WIiNjRVefPFFiz/jzJkzQmxsrLBgwQKhoaHBYF/x8fHC+PHjheLiYoNtfvzxRyE2Nla49957BYVCoV+enp4uxMXFCTNmzBCam5sNtvnss8+E2NhYYfny5Qbf55dffhFiY2OFhQsXGn1Pst/cuXOFuXPnWrRuc3OzMGPGDCEuLk7IyMjQL1coFMK9994rxMbGCj/99JPBNsXFxcL48eOF+Ph4g37S0NAgLFiwQIiNjRVSU1MNtumuPkfOcc899wixsbFCYmKifhmPPX3P8ePHhfz8fEGn0wknTpwQYmNjhb/+9a8m13W3Ywv7lP2s6T/bt28XMjMzjZanpKQIcXFxQlxcnFBZWWm0TWxsrLB9+3aL22TL7/rqq68KsbGxwooVKwyWr1+/XoiNjRWWLl1q9Dm8VrePNX3H3c5NtvQ3MmRN/zGnsbFRmDhxohAXFyfU1tYavMdjj/1Y46kXKCoqQnJyMqKiovDAAw8YvLd8+XL4+fnhhx9+gEwmc1ELyVozZ87EvHnzDIbTAUBERASWLFkCADh58qRdn7FlyxYAwJ/+9CeDFMvo6Gjcf//9UKlU2LFjh8E2mzdvBgA888wz8Pb21i+fOHEiFi5ciLq6Ouzfv1+/XBAE/ec8//zzBt9nwYIFmDp1Ki5fvmz3dyH77Nu3D3V1dfjNb35j8DTG29sbTz/9NICrv32b7du3Q6VS4YEHHkB0dLR+eXBwMJ544gkAV/tYm+7oc+QcFy9eRFpaGgYMGIA5c+bYtS8ee3q3GTNmICYmRp9x2xl3OrawTzmGNf1n8eLFGDdunNHy+Ph4xMfHQ61W4+zZs3a1x5bftaWlBbt27YKfnx+WLVtmsL8HH3wQUVFRSE5ORnFxsX45r9XtZ03fsUVPPY7Y0t/ImCP6z65du6BQKHDTTTehX79+drWHxx5jDDz1AikpKQCAhIQEo0BFQEAAJk+eDLlcjvT0dFc0jxxMImktvWaqLkZVVRW2bNmCzz77DFu2bEF2drbZ/Zw4cQIAMGvWLKP3brjhBoN1AECpVOLs2bPw9fXF1KlTLdqmqKgIZWVliImJMZkCbGobchyVSoVdu3bhs88+w/r163HixAlotVqj9TrrC9OmTYOvry/Onj0LlUpl0Tbmftfu6HPkHNu2bQMA3HXXXTz2kMXc6djCPtWzdHYtBLQOG163bh2++OILfP/996ioqDC5ni2/a1utssmTJyMgIMBgfQ8PDyQkJBhtw2t113CHc5Mt/Y2co+1a6J577jG7Do89tmNx8V4gLy8PABATE2Py/aFDhyI5ORn5+fmYOXNmN7aMHE2j0WDXrl0ATJ8Yjx49alQ0Oj4+Hu+88w4iIyP1y2QyGSorK+Hn54f+/fsb7Wfo0KEAWgt7tikqKoJWq8XgwYP1F3xdbZOfnw8AGDZsmMnvY2obcpzq6mq88MILBsuio6OxYsUKxMfH65e1/U6mjiESiQTR0dG4dOkSiouL9YUOO9umf//+8PPzQ0VFBeRyOXx9fbutz5HjKRQK/PDDDxCLxbj77rtNrsNjD5niTscW9qmeo7S0FMePH4evry+mTZtmcp0NGzYYvBaLxbjrrrvw8ssvG2Sm2PK7dtZHzW3Da3XXcIdzky39jRzv7NmzyMnJQUxMjMmJDdrw2GM7Bp56AalUCgAIDAw0+X7b8ubm5m5rEznH+++/j5ycHMyePdsg8OTr64snn3wSCxYs0EfNL168iI8++ggpKSn4/e9/j++//x5+fn4ArvaFrvrM/7d370FRVn8cxz8siq2JiYiAqCmh6KgpJZp5q2wSyXuMt0HNbmNFMlaajmlefg6VYSnYxZnMuDiapmUo2iBTaRPeb1FZ4ySxeDdZL8s1+P3h7OYKLLCwiPR+/QXPc87ZA8+X8zzz5ZzzXLlyxXbMWufWDHtt1CE2a9/YsWP14IMPqlOnTrr77ruVnZ2tpKQkffHFF3r++ee1YcMGdenSRVLlY4j1+t18batSx2Kx6OrVqzIajXUWc6h9qampunLlih555BH5+/vbnWPsgSMNaWwhpuqHwsJCvf766yosLNSsWbPKvI2pbdu2mj9/vvr37y8/Pz9dvXpVBw8e1PLly7VhwwZdv35dsbGxtvLOXFdn6vCsXrca0r2Jsad+qGy2E2NPzbHUDqgnEhIStGbNGgUGBurdd9+1O+ft7a3o6Gh169ZNzZs3V/PmzRUaGqo1a9aoZ8+eysrK0saNG29Tz3E7REVFqV+/fmrVqpWMRqM6d+6sxYsXa9q0acrPz1dcXNzt7iLuEBs2bJAkjR8/vsw5xh4AdeWff/7RrFmzdOjQIYWHh5d5O6t0YzZLZGSkOnbsKKPRqNatW2vYsGFKSEjQPffco5SUFIfLrdAwcG9Cbbp69apSU1PVuHFjjRkzptwyjEWTLiAAAA+0SURBVD01R+LpDmDNelaUqawsi4/6LykpSUuXLlVQUJASEhLUokWLKtVr1KiRbWnMgQMHbMcry25bjzdv3rxMHWvmvDbrEJt1x7o5/c3xUNkYYr1+N1/bqtaxXtu6ijnUrj/++EOHDx+Wn5+fBg8eXOV6jD2QGtbYQkzdXtak044dOzRs2DAtW7asWpsE+/v72/ZM2b9/v+24M9fVmTo8q9cPd+K9ibHn9tu6davy8vKc2lScsafqSDzdAQIDAyVVvLY3KytLUsVrSFG/rV27VkuWLFHnzp2VkJAgHx+fatX38vKSJLu3FTRt2lS+vr6yWCw6f/58mTrWmLl5PXD79u3l7u6u7OxsFRcXV6mONeasa5KrUgeuZb1h3hwP1utU3hhSXFwsk8mkRo0a2W1+6KjO+fPnZbFY5OfnJ6PRKKnuYg61yzrbqaJNxR1h7EFDGluIqdunqKhIr776qrZt26bhw4crNja23D11KmO9/+Xl5dmOOXNdHcVoRXV4Vq8/7rR7kzPxhtplXWZX3szvqmDsqRoST3eAvn37SpL27NmjkpISu3PXrl3ToUOHZDQa1bNnz9vRPdTA6tWrFRMTo65du+rzzz+Xt7d3tduwvqXg1jcmWDfG2717d5k6P/zwg10Z6cbrr0NCQpSXl2f3XyJHddq3b682bdro1KlT5b7mtbw6cK0jR45Iso8HR7Gwf/9+5eXlKSQkRB4eHlWqU9F1rYuYQ+0pKCiwbSoeERFR7fqMPWhIYwsxdXsUFhYqOjpaO3bs0OjRo7Vs2bJqJ8Gtjh07JunGXixWzlzXnj176q677tKhQ4fKzDwoKSnRnj17ytThWb3+uNPuTc7EG2rP0aNH9dtvv6lDhw62v+PqYuypGhJPd4D27dtrwIABysnJUXJyst25uLg4WSwWjRw50raBHu4Mq1atUmxsrLp166a1a9c6nNqZmZlZZjCRpJ9++klr166VJI0cOdLunHXJ1ccffyyz2Ww7bjKZtG7dOnl4eGjs2LF2dSZOnChJ+uCDD1RQUGA7fuzYMW3fvl0tW7bU0KFDbcfd3Nxsn7Ns2TK7PqalpenAgQMKCgqye8Maau7kyZN2/8mzMplMWrJkiST7eAgLC5OXl5e2bdum48eP244XFBRoxYoVkv699lZjx46Vh4eHkpOTZTKZbMfNZrM++eQTSf/GmFVdxBxqT2pqqsxmswYNGlRmU3Erxh440pDGFmKq7hUWFioqKkq7du1SRESEYmJiyrwO/FY3x5lVSUmJPvnkEx0+fFheXl62ZS+Sc9f17rvv1qhRo2SxWBQfH2/3WUlJScrJydGAAQPsEhs8q9ethnRvcibeUHsc7XN5M8aemnMrLS0tvd2dQOX++usvTZgwQZcuXdKQIUN033336ejRo9q7d686dOig9evX26aWov7bsmWL5syZI3d3d0VGRpa77jYgIMB2A5w8ebJOnTqlkJAQ+fn5Sbrx9o6MjAxJUnR0tF566aUybbz99tv67LPP5Ofnp6FDh6qoqEjbt29Xbm6u5s+fr8jISLvypaWlio6O1s6dOxUYGKhHH31Uubm5Sk1NVUFBgVauXKnHH3/crk5hYaGmTJmiw4cPq3v37urXr5/OnDmjHTt2qHHjxvr888/rRZa9IYmLi9OaNWsUGhqqNm3a2N5q991336mgoECDBw9WfHy83SyDtLQ0zZgxQ02aNFF4eLjuuecepaen688//9TQoUO1YsWKMvtpJCYm6n//+59atGih8PBwNW7cWDt37tTZs2f1zDPP6I033ijTt7qIOdSOSZMm6eDBg/roo4/02GOPlVuGsee/Jy0tTWlpaZKkCxcuaM+ePWrXrp169+4t6cYylpv/9hvS2EJM1Vx14mfu3LnavHmzvLy8NGnSpHL3dOrTp4/dLITg4GB17txZwcHB8vX11dWrV22vQTcajYqPj9eAAQPs2nDmul6+fFkTJkzQqVOn9NBDD+n+++/XyZMntWvXLnl7e2v9+vVq3769XR2e1WumOrHT0O5NzsQb7FX33iXdmBE0cOBAFRcX6/vvv3c4CYCxp+ZIPN1Bzpw5o5UrV2r37t3Kzc2Vj4+PHn/8cUVFRZV53Szqt7i4uDKZ7Fv16dNHiYmJkqSNGzcqLS1Nf/zxhy5fvqyioiK1atVKvXr1UmRkpG1QLc/mzZuVnJyskydPys3NTd26ddOzzz6rRx99tNzyxcXFSkpK0pdffqmsrCw1adJEvXr10osvvqgHHnig3Dp5eXlavXq1tm3bptOnT6tZs2bq06ePZsyYoaCgoCr+VlBV+/bt0/r16/XLL7/o4sWLysvLk6enp7p27apRo0Zp1KhR5T7AHzx4UB9//LGOHDmigoIC3XvvvXrqqac0efLkCpc2pKena82aNcrMzFRpaanuu+8+RUZGVvjWD6luYg41c/LkSYWHh8vPz0/p6ekVXn/Gnv+eyu5PAQEBSk9PtzvWkMYWYqpmqhM/kydP1r59+xy2FxUVpVdeecX2/TvvvKPjx4/r1KlTMpvNMhgM8vf318MPP6xp06ZVOCvEmeuam5ur+Ph47dq1SxcuXFCLFi00cOBARUdH25Idt+JZ3XnViZ2GeG9yJt7wL2fuXevWrdOiRYv05JNPavny5Q7bZ+ypORJPAAAAAAAAcAn2eAIAAAAAAIBLkHgCAAAAAACAS5B4AgAAAAAAgEuQeAIAAAAAAIBLkHgCAAAAAACAS5B4AgAAAAAAgEuQeAIAAAAAAIBLkHgCAAAAAACAS5B4AgAAKEdJSYkmTpyo4OBgBQcHa926dVWu+/vvv6t79+4KDg5W3759deHCBRf2FAAAoP4i8QQAAFAOg8GgmJgYGY1GSdKyZcuUnZ1dab3i4mLNmTNHRUVFkqQ333xTPj4+Lu0rAABAfUXiCQAAoAIdOnTQzJkzJUkWi0Xz5s1TaWmpwzqrV69WZmamJOmJJ57QiBEjXN5PAACA+orEEwAAgANTpkxRaGioJGnv3r1KTk6usOyJEyf04YcfSpK8vLy0cOHCuugiAABAvUXiCQAAwAE3NzfFxMSoadOmkqTY2Nhyl9wVFxdr7ty5tiV2CxYskLe3d532FQAAoL5xK61svjgAAACUnJysxYsXS5JCQ0OVmJgoNzc32/lVq1Zp5cqVkqSwsDCtWLHCdq6kpEQ7duzQt99+q2PHjunSpUsyGAzy9fVV3759NWnSJAUHBzv8/NOnTys9PV379u3TiRMndP78eRUVFcnT01NBQUEaOHCgJk6cKE9PzwrbMJlMGjJkiCRpzJgxevvtt3Xu3DmtW7dO6enpOnv2rK5cuaKoqCi98sorTv+uAAAArEg8AQAAVEFpaamefvppZWRkSJLmzZunKVOmSJJ+++03RUREqKioSN7e3kpJSVHLli0lSX/99ZdmzJihX3/9tcK2DQaDpk+frujo6HLP7927V1OnTq10f6mWLVsqLi5OvXv3Lvf8rYmnJ598Uq+99prMZrNdORJPAACgtjS63R0AAAC4E7i5uWnp0qUaMWKELBaLli9frsGDBysgIMBuid3ChQvtkk7jxo3T5cuXJUkPPvigHnnkEQUEBOiff/5RZmamtmzZIrPZrA8//FAGg6HchE9BQYFKS0vVqVMn9e3bV4GBgfLy8lJBQYHOnDmjtLQ0ZWZm6u+//9b06dP11VdfqW3btg5/nqysLEVHRysvL0/h4eHq16+fmjVrJpPJpNatW9fybw8AAPxXMeMJAACgGtavX6+33npL0o1EUr9+/RQfHy9JGj58uGJjYyXdWF4XERGhzMxMeXh46N1339WwYcPKtHfx4kU999xz+vXXX2UwGLR161Z16tTJrkxOTo6uXbvmcDleSkqKZs2apZKSEo0dO1YxMTFlytw840mSmjZtqtWrV9s2TwcAAKhtbC4OAABQDRMmTFD//v0lSQcPHrQlnXx8fDR//nxbOessJEmaPXt2uUknSWrVqpXef/99ubu7q6SkRAkJCWXKBAQEVLoH1PDhwzVy5EhJ0vbt220zsByZOXMmSScAAOBSJJ4AAACqaenSpWrWrJndsUWLFqlFixa277/++mtJUrNmzTRu3DiH7XXs2FH333+/JOnHH390ul8hISGSpPz8fJ04ccJhWaPRqIiICKc/CwAAoCrY4wkAAKCa/P39NX36dL333nuSpEGDBtktYZOkAwcOSLoxE2r37t2Vtmkw3Ph/YE5OjvLz83XXXXeVKXP06FFt3bpVR44ckclk0vXr1yuc2XT27Fl17969ws/r2rWrmjZtWmm/AAAAaoLEEwAAgBO8vb3L/VqSrl+/rtzcXEnSn3/+qZdffrlabZvNZrvEU2Fhod58803bLKqquHbtmsPzvr6+1eoTAACAM0g8AQAA1LLKkj6VuXUW0+LFi21JJw8PDw0ePFg9evSQr6+vjEaj3N3dJUkZGRlKTEyUdGNzc0fKm1EFAABQ20g8AQAA1LKbl7CFhoYqKSnJ6bZMJpM2bdokSfLz81NSUpLatWtXbtlz5845/TkAAACuwObiAAAAtczT09OWfDp79myN2srIyFBpaakk6YUXXqgw6STd2B8KAACgPiHxBAAA4AKhoaGSpOzsbGVlZTndzqVLl2xfO0o6SdKePXuc/hwAAABXIPEEAADgAqNHj7Z9vXLlSqfbuXkvpuzs7ArLpaWl6cSJE05/DgAAgCuQeAIAAHCBsLAw9ejRQ5KUkpKipUuXqrCwsMLy+fn52rx5s7Zt22Z33NqGJH366acym81l6h49elTz5s2rpZ4DAADUHjYXBwAAcAGDwaC4uDiNHz9e586dU0JCglJTUxUWFqYuXbrI09NTFotFp0+f1s8//6yMjAxZLBZFR0fbtRMSEqJu3bopMzNTOTk5GjZsmCZMmKCOHTsqPz9fGRkZSk1NlSSNGDFC33zzze34cQEAAMpF4gkAAMBF/P39tWnTJs2ePVs//fSTLly4oMTExArLu7u7y8fHx+6Ym5ub3n//fU2dOlVnzpzRpUuXtGrVKrsyTZo00YIFC2QwGEg8AQCAeoXEEwAAgAu1bt1aa9eu1b59+5SSkqJDhw7p3Llzun79uoxGo/z8/NS5c2f16dNHQ4YMUevWrcu0ce+992rLli367LPPlJaWJpPJJHd3d/n6+qp///6aOHGigoKCtHnz5tvwEwIAAFTMrdT6fl4AAAAAAACgFrG5OAAAAAAAAFyCxBMAAAAAAABcgsQTAAAAAAAAXILEEwAAAAAAAFyCxBMAAAAAAABcgsQTAAAAAAAAXILEEwAAAAAAAFyCxBMAAAAAAABcgsQTAAAAAAAAXILEEwAAAAAAAFyCxBMAAAAAAABcgsQTAAAAAAAAXOL/9Jeq9NUYew8AAAAASUVORK5CYII=\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "JKNmf5TeFvQt"
-      },
-      "source": [
-        "We have successfully removed the seasonality and we saw an upward trend for `ellis-cpu.wait_perc`! But how do these two search terms compare?\n",
-        "\n",
-        "We can figure this out by plotting the trends of `'ellis-cpu.wait_perc'`, `cpu_system_perc` and `'load_avg_1_min'` on a single figure:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "02683682-38ad-4745-c7bb-99a9058bb755"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "PTkbQPa_6MNb"
-      },
-      "source": [
-        "We established the correlation matrix for Ellis data.\n",
-        "Seaborn has five built-in themes to style its plots: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`. Seaborn defaults to using the darkgrid theme for its plots, but we can change this styling to better suit our presentation needs.\n",
-        "\n",
-        "To use any of the preset themes pass the name of it to `sns.set_style()`."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "6e2c3c3c-5a69-42ef-87a8-7dfdd65e7ceb"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tdg8lD0OHEtH"
-      },
-      "source": [
-        "Correlation between rows or columns of two DataFrame objectsCompute pairwise"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "ab6efc64-5329-4ad2-e5a8-acecf7c79eff"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 49
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "3e1fc354-aefb-496b-9e08-d05a458f9c23"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 50
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "a8c2999d-5fd1-4de3-f8fd-05cd6ff14622"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f21c0790>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f217f790>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f2132b90>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f20e9f50>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 51
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Q23ry_WpH6tt"
-      },
-      "source": [
-        "train test split for simple time series moving window average"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "6375471f-a7ec-4416-95e0-4f9a82872168"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "22Y4ztlZIpFG"
-      },
-      "source": [
-        "Defined a `multivariate_data` function to generate multivariate data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "MxS23z--ZtQt"
-      },
-      "source": [
-        "Generate multivariate data using a defined function `multivariate_data`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "3f2a841e-eec2-4cf9-e370-4ab5a8bcc725"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "DQ8txbggaJ2-"
-      },
-      "source": [
-        "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
-        "- Creating a source dataset from our input data.\n",
-        "- Applied dataset transformations to preprocess the data.\n",
-        "- Iterate over the dataset and process the elements.\n",
-        "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
-        "Once we have a dataset, we can apply transformations to prepare the data for our model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "719a1cea-6548-4597-fc05-b183cc485387"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "IN6IQykaEzcF",
-        "outputId": "f7877fba-a745-4f3e-f654-c8cdeed5181e"
-      },
-      "source": [
-        "x_train_ss.shape[-2:]"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "(120, 4)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 57
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "SIc3631raYA_"
-      },
-      "source": [
-        "We used a custom loss function to evaluate the model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "004c1521-5b4c-4304-fa58-76bd01a9dcca"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "from keras.utils.vis_utils import plot_model\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:])))\n",
-        "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "#single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "\n",
-        "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Bi-LSTM.png', show_shapes=True, show_layer_names=True)\n",
-        "single_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 52s 924ms/step - loss: 0.0746 - rmse: 0.1454 - val_loss: 0.0103 - val_rmse: 0.0111\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 45s 900ms/step - loss: 0.0075 - rmse: 0.0093 - val_loss: 0.0136 - val_rmse: 0.0137\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 45s 898ms/step - loss: 0.0068 - rmse: 0.0077 - val_loss: 0.0027 - val_rmse: 0.0033\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - ETA: 0s - loss: 0.0050 - rmse: 0.0061Epoch 5/20\n",
-            "50/50 [==============================] - 44s 893ms/step - loss: 0.0089 - rmse: 0.0104 - val_loss: 0.0058 - val_rmse: 0.0062\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 45s 896ms/step - loss: 0.0081 - rmse: 0.0088 - val_loss: 0.0100 - val_rmse: 0.0102\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 45s 908ms/step - loss: 0.0063 - rmse: 0.0072 - val_loss: 0.0054 - val_rmse: 0.0057\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 45s 911ms/step - loss: 0.0030 - rmse: 0.0038 - val_loss: 0.0044 - val_rmse: 0.0046\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 45s 913ms/step - loss: 0.0056 - rmse: 0.0066 - val_loss: 0.0055 - val_rmse: 0.0055\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0045 - rmse: 0.0055 - val_loss: 0.0070 - val_rmse: 0.0070\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 45s 910ms/step - loss: 0.0035 - rmse: 0.0040 - val_loss: 0.0014 - val_rmse: 0.0015\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 44s 898ms/step - loss: 0.0198 - rmse: 0.0304 - val_loss: 0.0077 - val_rmse: 0.0077\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 45s 900ms/step - loss: 0.0051 - rmse: 0.0065 - val_loss: 0.0012 - val_rmse: 0.0013\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 48s 965ms/step - loss: 0.0060 - rmse: 0.0074 - val_loss: 0.0026 - val_rmse: 0.0026\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0041 - rmse: 0.0053 - val_loss: 0.0017 - val_rmse: 0.0018\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 45s 914ms/step - loss: 0.0040 - rmse: 0.0053 - val_loss: 0.0035 - val_rmse: 0.0035\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 45s 910ms/step - loss: 0.0025 - rmse: 0.0027 - val_loss: 0.0025 - val_rmse: 0.0026\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - ETA: 0s - loss: 0.0025 - rmse: 0.0027Epoch 19/20\n",
-            "50/50 [==============================] - 45s 909ms/step - loss: 0.0024 - rmse: 0.0027 - val_loss: 0.0023 - val_rmse: 0.0024\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0020 - rmse: 0.0024 - val_loss: 7.3451e-04 - val_rmse: 8.8589e-04\n",
-            "Model: \"sequential_3\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "bidirectional_3 (Bidirection (None, 120, 64)           9472      \n",
-            "_________________________________________________________________\n",
-            "lstm_7 (LSTM)                (None, 100)               66000     \n",
-            "_________________________________________________________________\n",
-            "activation_3 (Activation)    (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "dense_3 (Dense)              (None, 1)                 101       \n",
-            "=================================================================\n",
-            "Total params: 75,573\n",
-            "Trainable params: 75,573\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "rePzISUuFmlM"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "90d76f79-4228-4f67-ef58-eb0c6f9e9390"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "16fab4ff-15d9-424a-a599-6f03e1ad0e8b"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "xFJT1rZDAUVL",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "d0dc9e7a-bc96-4f19-815f-da9ed8a82408"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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sVDCCGEalI8hBBCqCbFowJWSxdj9vPeCtuY/bwXq6WLaymREELUDwZdMM/MzGT69OlcunSJli1bsnjxYho3blymnYuLC87OzgA0b96ckJCQUvPnzp3Lpk2bOHr0KAArV65k48aNaLVabGxsmD9/Pi1btqxSX9WpsOvjNJrsy42vVlGgZ8wps5/36uarlZWVybRprwCQkZGOiYkJTZqUjDG1YsUaTEwMf3hv6tQA0tOvYWFR8oS5r+9EnnpqgN62V65cJj7+BF5egwxerxDi3mdQ8QgNDcXV1ZWAgABCQ0MJDQ1lxowZZdpZWloSFRWlt4/4+HiysrJKTXNxcWHTpk1YWVmxdu1aFi1axOLFiyvtq7oV9HHjxler9BaQOwuHvsJSmcaNmxAWthYoPYIulDw7kZeXXy3Dp8+ePZcOHTpW2u7KlctER29TXTyKiooAeYufEPcbg05bxcTE4OPjA4CPjw/R0dGqli8qKiIoKKhMwenVqxdWVlYAdOnShatXKx7xtibdWUBun8IytHCUZ968D1m0aD6TJk0gOHgJy5cvY+3aNbr5L7wwhitXLgOwffsWJk+egJ/f8wQFzfv/X+JVW8euXf/7c7r9QqqQkP9y/PhR/Pye59tvvyn1YiqAmTMDiYs7oltm6dLP8PV9jpMnT9x1FiGE8TLon7bp6enY29sDYGdnR3p6ut52eXl5jBo1ClNTUwICAhgwoOTUSXh4OB4eHro+9ImIiMDN7X9f0OX1VRGNpuQJzTulpmrQaqtWO4v79Sd7+WoaTZpAnv+LWKz8muzlqynu24/qGBnKxESDiYkGjUbDX3+lERq6Eq1Wy9dfh2Bi8r+cGk3Jzykp54mN3Ulo6EpMTc1YtGgB0dHbGTJk2D+2W8OcObOwsLAAYOnSEDQaDSYmJqW2Xas14dVXX+ebb1bz6adLANi8+Qfd+u5sp9WakJuby6OPPkZg4JucP/8na9aEVZqlNmg0mjJ/zv+k1ZpU2qa+MKasYFx5jSkr1M+8lRYPPz8/rl27VmZ6YGBgqc8aTcmXnz67du3CwcGBlJQUfH19cXZ2xsLCgm3btrFmzRq9ywBERUVx8uRJwsPDK+zroYceqnAbFIUyj/YriqJqWI2iJ/ui9Z1Ew08WcuuNmeQ92ReqaViO4mKF4mIFRVF0w6cXFRXrpt/OeTvz4cOHOHXqD/z9S05z5eX9TePGTcpsj6IofPDBv0udtlIUheLi4lJti4r+9/n2/2/n0ddOq9Xi5vYURUXF/Prr4SplqQ2KolQ6hIMxDUthTFnBuPIaU1Yw0uFJwsLCyp1na2tLWloa9vb2pKWlYWNjo7edg0PJcOeOjo706NGDhIQELC0tSU5OxsvLC4Dc3Fw8PT3ZuXMnAAcOHCAkJITw8HDMzc0r7Kuy4lEdzH7ei9Wq5dx6YyZWq5ZT0MetWk9Z3Xbn8OlarRZF+d+XcH5+PlDyJTl48DCmTJmqun+tVktxcclwZsXFxRQU6H9xzZ3tAPLy8nU/m5ublxqN926zCCGMl0HXPNzd3YmMjAQgMjISDw+PMm2ysrJ0X3oZGRnExcXh5ORE//792b9/P7GxscTGxmJlZaUrHCXvmfiA4OBgbG1tK+2rpt15jSPn7ffLXAOpKc2bt+DMmVMAnD59Sne9o1u3HuzeHcP16xlAyRsIr169UqU+mzVrzunTfwDw8897KSwsealVyRDvOXe0a8HZs2coLi4mNfUqf/zxu97+une/+yxCCONl0DWPgIAAAgMDiYiIoEWLFro7ouLj41m/fj3z5s0jKSmJ2bNno9FoUBSFyZMnV/qFHxQURE5ODtOmTQP+d0vu3fRlKH0Xxyu6C6s69e/vzrZtmxk/fgwdOz6Co2PJEVbr1m2YPPllpk+fiqIUo9Wa8sYbb9GsWfNK+xw+fCRvv/0mvr7P0bOnq+7GBCendpiYmODr+xxDhgxjzJjnad68BePHP0OrVq1xdm6vtz9DsgghjJcMyV6Byu6qqqm7rurTMOeVqU9ZZUj2umVMeY0pK9TPax7yhHkFTI/GVVgYbh+BmB6Nq+VkQghRt2RI9grkvhZYaZuaunAuhBD1mRx5CCGEUE2KhxBCCNWkeAghhFBNrnlUwbmsPwk+tpSIMxu4VZBNQzNrRjuP4eUur9G6cZu6jieEELVOjjwqEXNhB/2/fZLwhNVkF9xEQSG74CbhCavp/+2TxFzYcdd99+nTnTlzZuk+FxYWMmzYAN5883VV/Ywe7U1mZuZdtRk92psJE57F13cs06e/Snp62aFoquqfAzn+07Vrf/H++zMBSEw8zcGDP6tex9SpAZw6lXDXGYUQ1UOKRwXOZf3JxO0TyC3MoVApPYxHoVJAbmEOE7dP4FzWn3fVv5WVFX/+mURe3t8A/PrrIR58sPxBImvKkiXLWLVqPR06dGTNmpWl5t0eC6s6PPigHXPnBgGQmHiGgwf3V0u/QojaJ6etKhB8bCkFRfrHfrqtoKiAZce/4GO3T+9qHa6uvTlw4GeeemoA0dHbGTDAixMnjgElQ30sWDCHy5cvYWFhycyZ7+Hk1I6srEw+/PA9/vrrLx599DHufM5z+/YtRESsp6CgkI4dH+HNN98uNQ5VRTp37kpExHquXLnMG29MpWPHRzl9+hSffPI5sbE7iY2NpqAgHze3p5g06SUAwsK+ZvPmn2jatCn29g60b+8CwMWLKSxatIDMzOtotSb8+98LMTExYebMQFas+Iavvw4hPz+PEyeO88ILfjz5ZF8++yyIc+eSKCwsZOLEAPr27U9e3t/Mn/8RZ88m8tBDD5OXl3dX+1kIUb3kyKMCEWc2lDni+KdCpYCNZ9bf9To8PLyIidlBXl4eSUln6djxUd285cuX0a5de1atWs9LL73K3LmzAVi58is6depCePgG3NyeIjW15H0n58+fIyZmJ8HBKwgLW4uJiZYdO7ZWOcuBA/to06ZkuJeLF1MYOfIZwsM3kJx8gZSUFL76ahUrV67l9Ok/OHYsjlOn/mDnzh2Eha3lk08+L3U66aOP3mfUqGdYtWodwcErsLV9UDfPzMyMF1+cgru7J2Fha/Hw8GL16hV06/YEX321miVLlvHFF0vIzc3l++8jsLCw5JtvIpg06SXdWF9CiLolRx4VuFWQXXkjIDu/au30cXJqx5UrV4iO3o6ra+9S806cOKY7zdOt2xPcuJHFrVvZHDt2lHnzSqY/+WQfHnigEQC//XaY06f/4MUXJwAlw6M3bdq00gyvv/4SJiZa2rZ1YvLkV8jOvkmzZs159NHHADh8+Bd+/fUX/P3HAZCbm8PFi8nk5OTQr99TupGA+/z/hyVzcm5x7dpf9Ov3FIDufSIVOXz4F37+eQ/r1pUMv5+fn0dq6lWOHz/K6NFjdfuqbduaHwhTCFE5KR4VaGhmTXbBzUrbWZtbG7SePn3c+OKLz1m6dBlZWRVf+K7I3Q7VvmTJMpo0aaL7nJ19s9TQ8IqiMH68Hz4+T5dabsOGtXed9Z8URWHevCAeeujhautTCFFz5LRVBUY7j8FUY1ZhG1ONGc84jzVoPUOHDsfff3KZf1V37tyVnTu3ARAXd4TGjRvTsKE1Xbr8b/rBg/u5efMGYNhQ7RXp2dOVzZt/0A3Z/tdfaVy/nkHnzo+zd+8u8vL+JifnFvv37wNKhne3s7Nn797dQMl7SP7+++9SfTZo0KDUEPA9e7oSEfGt7vrN7dNTd+6DP/88S1LSWYO3RwhhOCkeFXi5y2uYaSsuHmZaM17q/KpB67G3d+CZZ8oWoIkTAzh9+g98fccSEvJf3nvvIwD8/Sdz/PhRxo8fw969u3BwaAaUHh7d13csgYGv6n0LpFo9evTC03MQU6b4M2HCs7z//lvk5OTQvn0HBgzwwtf3ed588/VSbyycNWsOERHr8fUdy5QpE8vcAvz44905f/4cfn7PExOzAz+/SRQWFuLrO5bx48fw9dchAIwcOZrc3BzGjRvN118vw9m5g8HbI4QwnAzJXomYCzuYuH0CBUUFpS6em2rMMNOasWLgajxaeVVr3vo0zHll6lNWGZK9bhlTXmPKCjIku1HyaOXF7mcPMOERPx4wfwANGh4wf4AJj/ix+9kD1V44hBDCGMgF8ypo3bgNH7t9etfPcgghxL3mvj7yuA/O2N035M9SiNp13xYPU1Nzbt26IV869wBFUbh16wampuZ1HUWI+8Z9e9qqaVM7rl//i+zsu3+uoqZoNBqjKWr1JaupqTlNm9rVdQwh7hv3bfHQak158MHmdR1DL2O6E8SYsgohqs99e9pKCCHE3ZPiIYQQQjWDTltlZmYyffp0Ll26RMuWLVm8eDGNGzcu087FxQVnZ2cAmjdvTkhISKn5c+fOZdOmTRw9ehSAlStXsnHjRrRaLTY2NsyfP5+WLVsCcPnyZd5//32uXLmCRqMhNDSUf/3rX4ZshhBCCJUMKh6hoaG4uroSEBBAaGgooaGhzJgxo0w7S0tLoqKi9PYRHx9PVlZWqWkuLi5s2rQJKysr1q5dy6JFi1i8eDEAb731FlOmTKF3797cunULExM5eBJCiNpm0DdvTEwMPj4+APj4+BAdHa1q+aKiIoKCgsoUnF69emFlZQVAly5duHq15H0VZ8+epbCwkN69S4Yub9iwoa6dEEKI2mPQkUd6ejr29iWvTbWzsyM9PV1vu7y8PEaNGoWpqSkBAQEMGDAAgPDwcDw8PHR96BMREYGbW8l7Is6fP0+jRo2YOnUqFy9exNXVlf/7v/+r9E15Gk3JXUHGQqs1MZq8xpQVjCuvMWUF48prTFmhfuattHj4+fnpHZk1MDCw1GeNRoNGo9Hbx65du3BwcCAlJQVfX1+cnZ2xsLBg27ZtrFmzptx1R0VFcfLkScLDS14QVFhYyJEjR4iMjKR58+ZMnz6d7777jmeeeabCbVAUjOp2UmO6/dWYsoJx5TWmrGBceY0pK9TPgRErLR5hYWHlzrO1tSUtLQ17e3vS0tKwsbHR287BwQEAR0dHevToQUJCApaWliQnJ+PlVTKwYG5uLp6enuzcuROAAwcOEBISQnh4OObmJU8ON2vWDBcXFxwdHQHw8PDg+PHjlW2CEEKIambQNQ93d3ciIyMBiIyMxMPDo0ybrKws8vPzAcjIyCAuLg4nJyf69+/P/v37iY2NJTY2FisrK13hSEhI4IMPPiA4OBhbW1tdX4899hg3btwgI6PkZUeHDh3CyUleSyqEELXNoGseAQEBBAYGEhERQYsWLXR3RMXHx7N+/XrmzZtHUlISs2fP1g1jMXny5Eq/8IOCgsjJyWHatGnA/27v1Wq1vPXWW/j6+gLwyCOPVHrKSgghRPW7b18GVZ8Z0/lYY8oKxpXXmLKCceU1pqxQP695yEMSQgghVJPiIYQQQjUpHkIIIVST4iGEEEI1KR5CCCFUk+IhhBBCNSkeQgghVJPiIYQQQjUpHkIIIVST4iGEEEI1KR5CCCFUk+IhhBBCNSkeQgghVJPiIYQQQjUpHkIIIVST4iGEEEI1KR5CCCFUk+IhhBBCNSkeQgghVJPiIYQQQjUpHkIIIVST4iGEEEI1U0MWzszMZPr06Vy6dImWLVuyePFiGjduXKadi4sLzs7OADRv3pyQkJBS8+fOncumTZs4evQoACtXrmTjxo1otVpsbGyYP38+LVu25JdffmHBggW65f78808+++wzBgwYYMhmCCGEUMmg4hEaGoqrqysBAQGEhoYSGhrKjBkzyrSztLQkKipKbx/x8fFkZWWVmubi4sKmTZuwsrJi7dq1LFq0iMWLF9OrVy9dP5mZmXh5edG7d29DNkEIIcRdMOi0VUxMDD4+PgD4+PgQHR2tavmioiKCgoLKFJxevXphZWUFQJcuXbh69WqZZbdv307fvn117YQQQtQeg4480tPTsbe3B8DOzo709HS97fLy8hg1ahSmpqYEBAToTjOFh4fj4eGh60OfiIgI3NzcykzfvHkz/v7+Vcqp0UCTJg2q1LY+0GpNjCavMWUF48prTFnBuPIaU1aon3krLR5+fn5cu3atzPTAwMBSnzUaDRqNRm8fu3btwsHBgZSUFHx9fXF2dsbCwoJt27axZs2actcdFRXFyZMnCQ8PLzU9LS2NM2fO0KdPn8riA6AokJT5nycAABs+SURBVJmZU6W29UGTJg2MJq8xZQXjymtMWcG48hpTVqi7vHZ2D5Q7r9LiERYWVu48W1tb0tLSsLe3Jy0tDRsbG73tHBwcAHB0dKRHjx4kJCRgaWlJcnIyXl5eAOTm5uLp6cnOnTsBOHDgACEhIYSHh2Nubl6qv61bt+Lp6YmZmVll8YUQQtQAg655uLu7ExkZCUBkZCQeHh5l2mRlZZGfnw9ARkYGcXFxODk50b9/f/bv309sbCyxsbFYWVnpCkdCQgIffPABwcHB2Nralulz8+bNDB061JDoQgghDGDQNY+AgAACAwOJiIigRYsWLF68GCi5g2r9+vXMmzePpKQkZs+ejUajQVEUJk+ejJOTU4X9BgUFkZOTw7Rp04DSt/devHiRK1eu0KNHD0OiCyGEMIBGURSlrkPUtOJihfT07LqOUWXGdD7WmLKCceU1pqxgXHmNKSvUz2se8oS5EEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVTA1ZODMzk+nTp3Pp0iVatmzJ4sWLady4cZl2Li4uODs7A9C8eXNCQkJKzZ87dy6bNm3i6NGjAKxcuZKNGzei1WqxsbFh/vz5tGzZEoCgoCD27NlDcXExvXv35r333kOj0RiyGUIIIVQy6MgjNDQUV1dXduzYgaurK6GhoXrbWVpaEhUVRVRUVJnCER8fT1ZWVqlpLi4ubNq0iR9//JGBAweyaNEiAOLi4oiLi+OHH37gp59+Ij4+nsOHDxuyCUIIIe6CQcUjJiYGHx8fAHx8fIiOjla1fFFREUFBQcyYMaPU9F69emFlZQVAly5duHr1KgAajYb8/HwKCgp0/3/wwQcN2QQhhBB3waDTVunp6djb2wNgZ2dHenq63nZ5eXmMGjUKU1NTAgICGDBgAADh4eF4eHjo+tAnIiICNzc3ALp27UrPnj3p06cPiqIwfvx42rZtW2lOjQaaNGmgdvPqjFZrYjR5jSkrGFdeY8oKxpXXmLJC/cxbafHw8/Pj2rVrZaYHBgaW+qzRaMq99rBr1y4cHBxISUnB19cXZ2dnLCws2LZtG2vWrCl33VFRUZw8eZLw8HAALly4QFJSEnv27AFg4sSJHDlyhO7du1e4DYoCmZk5FbapT5o0aWA0eY0pKxhXXmPKCsaV15iyQt3ltbN7oNx5lRaPsLCwcufZ2tqSlpaGvb09aWlp2NjY6G3n4OAAgKOjIz169CAhIQFLS0uSk5Px8vICIDc3F09PT3bu3AnAgQMHCAkJITw8HHNzcwB27txJ586dadiwIQB9+/bl6NGjlRYPIYQQ1cugax7u7u5ERkYCEBkZiYeHR5k2WVlZ5OfnA5CRkUFcXBxOTk7079+f/fv3ExsbS2xsLFZWVrrCkZCQwAcffEBwcDC2tra6vlq0aMGvv/5KYWEhBQUF/Prrr1U6bSWEEKJ6GXTNIyAggMDAQCIiImjRogWLFy8GSu6gWr9+PfPmzSMpKYnZs2ej0WhQFIXJkyfj5ORUYb9BQUHk5OQwbdo04H+39w4cOJBffvkFb29vNBoNffv2xd3d3ZBNEEIIcRc0iqIodR2iphUXK6SnZ9d1jCozpvOxxpQVjCuvMWUF48prTFmhfl7zkCfMhRBCqCbFQwghhGpSPIQQQqgmxUMIIYRqUjyEEEKoJsVDCCGEalI8hBBCqCbFQwghhGpSPIQQQqgmxUMIIYRqUjyEEEKoJsVDCCGEalI8hBBCqCbFQwghhGpSPIQQQqgmxUMIIYRqUjyEEEKoJsVDCCGEalI8hBBCqCbFQwghhGpSPIQQQqgmxUMIIYRqBhWPzMxM/P398fLywt/fn6ysLL3tXFxcGDFiBCNGjGDKlCll5s+dO5euXbvqPq9cuZIhQ4bg7e2Nr68vly5d0s1btGgRw4YNY9iwYWzZssWQ+EIIIe6SQcUjNDQUV1dXduzYgaurK6GhoXrbWVpaEhUVRVRUFCEhIaXmxcfHlyk6Li4ubNq0iR9//JGBAweyaNEiAHbv3k1CQgKRkZFs2LCB5cuXk52dbcgmCCGEuAsGFY+YmBh8fHwA8PHxITo6WtXyRUVFBAUFMWPGjFLTe/XqhZWVFQBdunTh6tWrAJw9e5bu3btjampKgwYNaN++PXv37jVkE4QQQtwFU0MWTk9Px97eHgA7OzvS09P1tsvLy2PUqFGYmpoSEBDAgAEDAAgPD8fDw0PXhz4RERG4ubkB0KFDB/773/8yceJEcnNzOXToEE5OTpXm1GigSZMGajevzmi1JkaT15iygnHlNaasYFx5jSkr1M+8lRYPPz8/rl27VmZ6YGBgqc8ajQaNRqO3j127duHg4EBKSgq+vr44OztjYWHBtm3bWLNmTbnrjoqK4uTJk4SHhwPQp08f4uPjGTt2LDY2NnTp0gUTk8oPnhQFMjNzKm1XXzRp0sBo8hpTVjCuvMaUFYwrrzFlhbrLa2f3QLnzKi0eYWFh5c6ztbUlLS0Ne3t70tLSsLGx0dvOwcEBAEdHR3r06EFCQgKWlpYkJyfj5eUFQG5uLp6enuzcuROAAwcOEBISQnh4OObm5rq+Xn75ZV5++WUA3nzzTVq3bl3ZJgghhKhmBl3zcHd3JzIyEoDIyEg8PDzKtMnKyiI/Px+AjIwM4uLicHJyon///uzfv5/Y2FhiY2OxsrLSFY6EhAQ++OADgoODsbW11fVVVFTE9evXATh16hSnT5+md+/ehmyCEEKIu2DQNY+AgAACAwOJiIigRYsWLF68GCi5g2r9+vXMmzePpKQkZs+ejUajQVEUJk+eXOl1iqCgIHJycpg2bRoAzZs3JyQkhMLCQsaNGweAtbU1ixYtwtTUoE0QQghxFzSKoih1HaKmFRcrpKcbzy29xnQ+1piygnHlNaasYFx5jSkr1M9rHvKEuRBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1QwuHpmZmfj7++Pl5YW/vz9ZWVl627m4uDBixAhGjBjBlClTysyfO3cuXbt21X1et24d3t7ejBgxgueee46zZ8/q5i1btgxPT08GDhzIvn37DN0EIYQQKpka2kFoaCiurq4EBAQQGhpKaGgoM2bMKNPO0tKSqKgovX3Ex8eXKTre3t4899xzAMTExLBgwQKWL1/O2bNn2bx5M5s3byY1NRV/f3+2b9+OVqs1dFOEEEJUkcFHHjExMfj4+ADg4+NDdHS0quWLiooICgoqU3Csra11P+fm5qLRaHTrGzp0KObm5jg6OtKqVStOnDhh4FYIIYRQw+Ajj/T0dOzt7QGws7MjPT1db7u8vDxGjRqFqakpAQEBDBgwAIDw8HA8PDx0fdzpm2++YeXKlRQUFLBq1SoAUlNT6dy5s66Ng4MDqampFWbUaKBJkwZ3tX11Qas1MZq8xpQVjCuvMWUF48prTFmhfuatUvHw8/Pj2rVrZaYHBgaW+qzRaHRHCP+0a9cuHBwcSElJwdfXF2dnZywsLNi2bRtr1qzRu8y4ceMYN24cP/74I8HBwSxcuLAqcctQFMjMzLmrZetCkyYNjCavMWUF48prTFnBuPIaU1aou7x2dg+UO69KxSMsLKzceba2tqSlpWFvb09aWho2NjZ62zk4OADg6OhIjx49SEhIwNLSkuTkZLy8vICS01Oenp7s3Lmz1LJDhw7lww8/1PVz9epV3bzU1FRd30IIIWqHwdc83N3diYyMBCAyMhIPD48ybbKyssjPzwcgIyODuLg4nJyc6N+/P/v37yc2NpbY2FisrKx0heP8+fO65Xfv3k2rVq1069u8eTP5+fmkpKRw/vx5OnXqZOhmCCGEUMHgax4BAQEEBgYSERFBixYtWLx4MVByB9X69euZN28eSUlJzJ49G41Gg6IoTJ48GScnpwr7DQ8P5+DBg5iamtKoUSPdKat27doxePBghgwZglar5YMPPpA7rYQQopZpFEVR6jpETSsuVkhPz67rGFVmTOdjjSkrGFdeY8oKxpXXmLJC/bzmIU+YCyGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEII1aR4CCGEUE2KhxBCCNWkeAghhFBNiocQQgjVpHgIIYRQTYqHEEJUA6ulizH7eW+Fbcx+3ovV0sW1lKhmSfEQQohqUNj1cRpN9i23gJj9vJdGk30p7Pp4LSerGVI8hBCiGhT0cePGV6v0FpDbhePGV6so6ONWRwmrl8Hv8zAGf2XncfLyDQB+S8mksZUZWbkFlf6/m2OTKi+jpm1ly+QrYK6hxtdTHf3nK9DRrmGNZqrO7ZB9e2/uWzXLdHNsglsNvQ/8zgJyu1Dci4UD7pPikXrjbyatO4YGUPvyEjXL1HT/tbVMfcx0N8tIpppbpj5mquoyFqYmrPG3oHUjC5U9V82dBSTXdxJWq5bfc4UD7rPTVnfz1is1y9R0/7W1TH3MdDfLSKaaW6Y+ZqrqMoVFxRw6l3EXPVddQR83cn0n0fA/QeT6TrrnCgfcJ8VDA5hpNZhpNboN1lTyfxNN1ZdR07Y+L1MfM90r21EfM92P22GiAVOtCT1b21CTzH7ei9Wq5dx6YyZWq5ZXeheWMbovTlvZN7IkZExnoP6cz66v547lvLzsW2Pct2qveXR9qGmNvdb1n9c4Cvq43ZPXPOQd5vWQMb1f2ZiygnHlNaasYFx5aypreRfHDb1oLu8wF0KIe1RFBaKi23iNlRQPIYSoBqZH4yo8srhdQEyPxtVyspphUPHIzMzE398fLy8v/P39ycrK0tvOxcWFESNGMGLECKZMmVJm/ty5c+natavu87p16/D29mbEiBE899xznD17FoDr16/zwgsv0LVrV+bMmWNIdCGEqFa5rwVWekqqoI8bua8F1lKimmXQBfPQ0FBcXV0JCAggNDSU0NBQZsyYUaadpaUlUVFRevuIj48vU3S8vb157rnnAIiJiWHBggUsX74cCwsLpk2bRmJiIomJiYZEF0IIYQCDjjxiYmLw8fEBwMfHh+joaFXLFxUVERQUVKbgWFtb637Ozc1Foym50a5BgwZ0794dC4uaebhHCCFE1Rh05JGeno69vT0AdnZ2pKen622Xl5fHqFGjMDU1JSAggAEDBgAQHh6Oh4eHro87ffPNN6xcuZKCggJWrVplSEwhhBDVrNLi4efnx7Vr18pMDwwsfd5Oo9HojhD+adeuXTg4OJCSkoKvry/Ozs5YWFiwbds21qxZo3eZcePGMW7cOH788UeCg4NZuHBhVbZHLxMTTYW3nNVHxpTXmLKCceU1pqxgXHmNKSvUv7yVFo+wsLBy59na2pKWloa9vT1paWnY2Oh/atPBwQEAR0dHevToQUJCApaWliQnJ+Pl5QWUnJ7y9PRk586dpZYdOnQoH374YRU3RwghRG0w6JqHu7s7kZGRAERGRuLh4VGmTVZWFvn5+QBkZGQQFxeHk5MT/fv3Z//+/cTGxhIbG4uVlZWucJw/f163/O7du2nVqpUhMYUQQlQzg655BAQEEBgYSEREBC1atGDx4pI3ZMXHx7N+/XrmzZtHUlISs2fPRqPRoCgKkydPxsnJqcJ+w8PDOXjwIKampjRq1KjUKSt3d3eys7MpKCggOjqaFStWVNqfEEKI6nVfDE8ihBCieskT5kIIIVST4iGEEEI1KR5CCCFUu+eKx9atWxk6dCgdOnQgPj5eN33//v2MGjUKb29vRo0axcGDB3XzTp48ibe3N56ensydO5faugxUXlaAZcuW4enpycCBA9m3b59u+t69exk4cCCenp6EhobWSk59/vjjD8aMGcOIESMYNWoUJ06cAEBRFObOnYunpyfe3t78/vvvdZbxn9asWcOgQYMYOnQoQUFBuunl7eu6tmLFCtq3b09GRslb7+rjvl24cCGDBg3C29ubV199lRs3bujm1df9Wl9+h/S5cuUKL7zwAkOGDGHo0KG6B6SrOo5grVLuMWfPnlWSkpKU8ePHKydOnNBN//3335WrV68qiqIop0+fVvr06aOb9/TTTytHjx5ViouLlUmTJim7d++u06yJiYmKt7e3kpeXpyQnJyseHh5KYWGhUlhYqHh4eCjJyclKXl6e4u3trSQmJtZK1n/y9/fX7afdu3cr48eP1/08adIkpbi4WDl69KgyevToOsn3TwcPHlR8fX2VvLw8RVEU5dq1a4qilL+v69rly5eViRMnKv3791fS09MVRamf+3bfvn1KQUGBoiiKEhQUpAQFBSmKUn/3a336HdInNTVVOXnypKIoinLz5k3Fy8tLSUxMVBYuXKgsW7ZMURRFWbZsmW4/16V77sijbdu2tGnTpsz0jh076h5WbNeuHXl5eeTn55OWlkZ2djZdunRBo9Hg4+NDTExMnWaNiYlh6NChmJub4+joSKtWrThx4gQnTpygVatWODo6Ym5uztChQ2st6z9pNBpu3boFwM2bN3VDzNwe70yj0dClSxdu3LhBWlpanWS807p16wgICMDc3BwoecAVyt/XdW3BggXMmDGj1KgN9XHf9unTB1PTkjv+u3TpwtWrV4H6u1/r0++QPvb29jzyyCNAyRh/bdq0ITU11eBxBGvCPVc8qmL79u107NgRc3NzUlNTadasmW5es2bNSE1NrcN0lMnk4OBAampqudPrwrvvvktQUBD9+vVj4cKFvPHGG0DZ7PVhf0LJg6dHjhzhmWeeYfz48bovsvq0T2+Ljo7G3t6eDh06lJpeX/ftbZs2bcLNrWRI8vq4X6H+5tLn4sWL/PHHH3Tu3LnK4wjWJqN8h3lF423dHnSxPImJiXzyySesWLGipuKVYkjWulZR9l9++YV33nmHgQMHsmXLFt57770Kh7KpDRXlLSoqIisriw0bNhAfH09gYGCd/ouzoqzLli2rtb+fVVGVv8PBwcFotVqGDx9e2/HuSbdu3eL111/n3XffLTXKOFQ8jmBtMsricbdfUlevXmXq1KksXLiQhx56CCj5l8ftQ+3bbW6f3qoOd5P1n5lSU1N1mcqbXhMqyv7WW2/x3nvvATB48GDef/99oOb3Z0Uqyrtu3To8PT3RaDR06tQJExMTrl+/XuG+rousp0+f5uLFi4wYMQIo2X+jRo1i48aNdbZvK/s7/N1337F7927CwsJ0X2p1tV8rU19z3amgoIDXX38db29v3dh/VR1HsDbdN6etbty4QUBAAG+++SbdunXTTbe3t8fa2ppjx46hKEq5Y3TVJnd3dzZv3kx+fj4pKSmcP3+eTp068dhjj3H+/HlSUlLIz89n8+bNuLu710lGe3t7Dh8+DMAvv/zCww8/rMseGRmJoigcO3aMBx54QO+Q+7VtwIABHDp0CIBz585RUFBA06ZNy93XdaV9+/YcPHhQN+Zbs2bN+O6777Czs6uX+3bv3r18/fXXBAcHY2VlpZte3/brbfXpd0gfRVF47733aNOmDf7+/rrpVRlHsLbdc8OT7Ny5k3//+99kZGTQqFEjXFxcWL58OV9++SWhoaGlBllcsWIFtra2xMfH88477/D333/j5ubGrFmzauWwsLysUHIaYNOmTWi1Wt5991369esHwJ49e5g/fz5FRUU8/fTTvPzyyzWeU58jR44wf/58CgsLsbCwYPbs2Tz66KMoisKcOXPYt28fVlZWzJ8/n8cee6xOMt4pPz+fd999l1OnTmFmZsbMmTNxdXUFyt/X9YG7uzsRERHY2NjUy33r6elJfn4+TZo0AaBz5866V0TX1/1aX36H9Dly5Ajjxo3D2dkZE5OSf9u/8cYbdOrUicDAQK5cuaIbR/D2Pq8r91zxEEIIUfPum9NWQgghqo8UDyGEEKpJ8RBCCKGaFA8hhBCqSfEQQgihmhQPIYQQqhnlE+ZC1Ibr16/j5+cHwLVr1zAxMcHGxobk5GRGjBjBhx9+WCPrPXbsGPPmzSM/P5/8/HyGDBnCa6+9xqFDhzAzM+Pxxx+vkfUKoYY85yFEFSxdupQGDRowadKkGl/XwIED+fzzz+nQoQNFRUWcO3cOJyenWs0gRGXkyEMIlQ4dOsSKFStYtmwZS5cu5eLFi6SkpHDlyhXeeecdjh07xr59+7C3tyckJAQzMzNOnjzJxx9/TE5ODk2bNmXBggXlDi2SkZGBnZ0dAFqtFicnJy5evMj69esxMTHhhx9+YNasWbRp04bZs2dz+fJloGSk427durF06VKSk5NJTk7m+vXrvPjii4wZM6bW9o+4P0jxEMJAycnJrF69mqSkJJ599lmWLFnCzJkzefXVV9mzZw/9+vVj7ty5fPnll9jY2LBlyxY+++wzFixYoLc/X19fBg0aRI8ePejbty8jR47kX//6F2PHji115PHmm2/i6+tL9+7duXz5MpMmTWLr1q1AyQCLGzZsICcnh5EjR9KvX796NwCgMG5SPIQwkJubG2ZmZjg7O1NUVKR7p4WzszMXL17k3LlznDlzRjfQXXFxse7IQp+pU6cyfPhwfv75Z3766Sc2b97MmjVryrQ7cOAAZ8+e1X3Ozs7WvaDLw8MDS0tLLC0t6dmzJ/Hx8VI8RLWS4iGEgW6/ndDExAQzMzPdoJomJiYUFRWhKArt2rXj22+/rXKfDz30EM8//zxjxozB1dWV69evl2lTXFzMhg0bsLCwKDOvPrzvQdzb5FZdIWpY69atycjI4OjRo0DJ+xoSExPLbb97925u38dy4cIFTExMaNSoEQ0bNtQdWUDJK2DvPCL5448/dD/HxMSQl5fH9evXOXz4cJ2PvivuPXLkIUQNMzc3Z8mSJcydO5ebN29SVFSEr68v7dq109s+KiqKBQsWYGlpiVar5ZNPPkGr1fLUU0/x+uuvExMTw6xZs3jvvfeYM2cO3t7eFBUV0b17d91w6O3bt2fChAlcv36dV155RU5ZiWont+oKcY+RW3pFbZDTVkIIIVSTIw8h6shHH31EXFxcqWkTJkzg6aefrqNEQlSdFA8hhBCqyWkrIYQQqknxEEIIoZoUDyGEEKpJ8RBCCKHa/wO2ZZGb4zkI1gAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Lu7m2Rr4AbMK",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "e0d07c10-c644-4a91-8723-5fc94e35c3a5"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "fjXexah9C8yg",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8e521731-9e70-48b3-b630-44adc32f93fb"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "7mtLZ6S-DPU-",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "outputId": "c6ae5f81-b61d-47e6-cd05-f96a5658ae2d"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "eaIjVnzCJwCS"
-      },
-      "source": [
-        "Bi-directional LSTM:\n",
-        "On some sequence prediction problems, it can be beneficial to allow the LSTM model to learn the input sequence both forward and backwards and concatenate both interpretations. This is known as bidirectional.\n",
-        "\n",
-        "Here, `tf.keras.layers.Bidirectional` is a bidirectional wrapper for RNNs which inherits from `Wrapper`, `Layer`, and `module`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "snN_Flr5DWQN",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "be27d60a-53b9-4e83-f1e3-45bf9b751196"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:])))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 54s 946ms/step - loss: 0.1534 - rmse: 0.2114 - val_loss: 0.0481 - val_rmse: 0.0489\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0785 - rmse: 0.0995 - val_loss: 0.0406 - val_rmse: 0.0412\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 46s 916ms/step - loss: 0.0619 - rmse: 0.0781 - val_loss: 0.0095 - val_rmse: 0.0100\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 46s 919ms/step - loss: 0.0526 - rmse: 0.0661 - val_loss: 0.0170 - val_rmse: 0.0172\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 46s 915ms/step - loss: 0.0466 - rmse: 0.0584 - val_loss: 0.0077 - val_rmse: 0.0080\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0421 - rmse: 0.0529 - val_loss: 0.0325 - val_rmse: 0.0326\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 47s 937ms/step - loss: 0.0390 - rmse: 0.0489 - val_loss: 0.0140 - val_rmse: 0.0141\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 47s 936ms/step - loss: 0.0365 - rmse: 0.0458 - val_loss: 0.0085 - val_rmse: 0.0086\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 47s 935ms/step - loss: 0.0342 - rmse: 0.0429 - val_loss: 0.0196 - val_rmse: 0.0196\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 46s 927ms/step - loss: 0.0325 - rmse: 0.0406 - val_loss: 0.0135 - val_rmse: 0.0136\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0308 - rmse: 0.0385 - val_loss: 0.0187 - val_rmse: 0.0187\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 45s 918ms/step - loss: 0.0297 - rmse: 0.0371 - val_loss: 0.0072 - val_rmse: 0.0074\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 46s 924ms/step - loss: 0.0281 - rmse: 0.0352 - val_loss: 0.0015 - val_rmse: 0.0018\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 46s 922ms/step - loss: 0.0269 - rmse: 0.0336 - val_loss: 0.0153 - val_rmse: 0.0154\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0257 - rmse: 0.0323 - val_loss: 0.0049 - val_rmse: 0.0050\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 45s 905ms/step - loss: 0.0252 - rmse: 0.0315 - val_loss: 0.0031 - val_rmse: 0.0033\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 45s 907ms/step - loss: 0.0239 - rmse: 0.0299 - val_loss: 0.0178 - val_rmse: 0.0178\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 45s 906ms/step - loss: 0.0230 - rmse: 0.0289 - val_loss: 0.0084 - val_rmse: 0.0085\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 45s 906ms/step - loss: 0.0224 - rmse: 0.0280 - val_loss: 0.0072 - val_rmse: 0.0072\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 45s 913ms/step - loss: 0.0216 - rmse: 0.0271 - val_loss: 0.0101 - val_rmse: 0.0101\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Ay5m27doDsTt",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "outputId": "74bc7df8-2315-401b-8cd8-d7632c14abb7"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6ZFP49W4D2wp",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "cdd29cbc-c26e-46d0-aaaf-0d2a8a4cb047"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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/n5O1t1bW/++MfnlJn5F2Vm/kVXXjnc67hPP92v7dvfa9G1TdOUu17NFwAAaB2rLh8nnv6TTj6VZhm6W7uduPvb67r7NK/+2ltJh1UpSP05dqbaam/8O3oCnUnNb0w1P9ia4nlJttXyDB8+Qp999pny8j7SihXpCgkJ0cGDB/Xyy+uUnv6Mduz4l86cqdKtt05WfHyCTNPU//t/y/TPf/5DERF91a3bdz+yWbNmatasFF166WX64IP3lZHx/8nlcqt379564IGHlJPzqvz8/LRp05uaPXuuBgy4WE89tUTHjh2TJP3613M0bNgIlZeX6ZFHFuqbb77RFVdcqZZUCtWeQ1lZme6+e5peeeVVrViRrqoqp3bu/ETTpiXrwIEvFRR0gaZMmSZJmjYtUcuWpUmS5syZpcsuu0L79u3VU0/9Qbm5m5Wbu0VnzlTpuut+orvu+oUtnz0AAOcbZ0Ki1wxTf5OX4NTFzd4spkZN4K15ncCsteqx4H4ZpSWWq8/uWiUg9TW2E6S7f4zPG9G0F8J1LY1tBWrHD/Ps2bP64IP39cMf/kiStH//Xv35z39Vv37Rysl5VcHBwVqx4s+qqqrSfffdpVGjrtann+7TV18d1OrV61RaWqKpUycrLu6WOtctLS3VsmWpeuaZDPXrF63jx8vVs2cvTZw4qU6gfeSRhUpMvEPDh4/Q0aNH9dvfztLLL6/XypXPa9iwEZox4x69//7/6W9/y/H6Hn7961/Iz8+hbt266fnnX7Ic061bN919973au3eP5syZJ0l64YXnvF7z0KECLVy4WFdccaU+/PADFRQU6PnnX5JpmnrggTn6+OM8jRhxVYs+awAA4J230F17kVGqrnG23MlR1oHXmZBYHdpLSxqeYxiNrjy7o/tbhvvGAnlnRLiupa0akzudTiUnT5FUvXL9059OVH7+Jxo69HL16xctSfrnPz/QZ599prffzpUkVVSc1KFDBfr44x264YbxcjgcuvDCcF111X82uP7u3fkaPnyk51o9e/aynMdHH32oAwe+9DyuqKjQqVOn9PHHO5SaukyS9KMfXauQkJ5e38sf//icevfu3YpPwbu+faN0xRVXSpI+/PAD/fOfH2jGjDskSZWVp3To0FeEawAA2ljt8oyaFW1n7HgFrXm5buBuYrtxr7nJNBWculghv7zHckv0ioWLGob7c6QUpDbCdS1ef2PysXi+pua6vqBa9U6maWr27Ln64Q9H1xnT0rrlxpimW889t1KBgYG2XdPh8PfUSVdVORsZ55BpfldPXVVV5flz9+7da83R1NSpyYqPT7BtjgAAoHmsVrTPjrra08FDDodUrzd1/fISb3lKhuE5blV6axXuawdwTycRi+c6E25orMXbXbXt8RvTqFGjlZ293nNz41dfHVRlZaVGjBip3NzNcrlcKioqUl7eRw3OvfzyK/XJJzv09deHJUnHj1e3qLnggmBVVn7XmvA///NqZWX91fP400/3SZJGjBipzZvfklQd5k+cON7seUdFRWnfvr2SpLff3uo5fsEFF+jUqVO1xvXT/v3V4/bt26sjR762vN4Pfzhab7zxmufcb74pVKnFPy0BAID24UxIrM5CQUEyXC4Z+jYc//o+hfzml83b6MWivMRqAxlnQqJK8nZ7doKsHaytNpWxo/GE3QjXtXi7q7Y9fiuaMCFeF188UHfeeYemTUvUk08ukcvl0nXX/UT9+8do6tTJevzxhz3lE7X16dNHc+cu0MKFc5WU9HM9/PB8SdI11/xY77yzTcnJU/TJJzuUkjJXe/f+W0lJt2vq1MnKzs6SJM2YcY8++WSHpk5N1DvvbFNkZN9mz/vnP5+m7Oz1mjFjSp32fVdd9R86cOBLJSdP0datmzRmzFgdP35cU6cmKivrr4qJGWB5vVGjrlZs7E26994Zmj79Z3rwwXl1QjoAAGh/lvelnTkjo9a/REveN3qRl2YJfocKPF3awoZcrLBLL7bs2NbYfXGdDZvI4JzEzxUAgJbxpaziwshe3rdOr8dqoxevG9p4uWFSqlvb7e31O3JTGTaRAQAAOM949u+I6KmQX97TaFlFY3t9tOT+M6uxlqW3jQRrqe7KtLfX74ybyhCuAQAAuqD6Ox42VvPcVE2zZTju1k1mQEDdY/qu1KN2OLcqvfVWKlJbzbX8DhXINOp2zu6snUQI1wAAAF1QUzseSt+1zWuqptnyvrQ/LlflHdPrhF7j2/9qh/OaFfGQX94jSTrx7PPVfasdjqbfxLcdRmp+OTANQ6bUrvfFtdR50YrPNE0Zhrdd6nGu6UK3CQAA0Gaas09HTVlFc/b6sGrTF5y62Gtph1FZWb1b4+lKy92vm9pu3ZTFartpytXJN5Xp8ivX/v4Bqqg4TiDrIkzTVEXFcfn7BzQ9GACA81hT9ci1yypaWtNcsxrt18R26UZpieWKeMisX3iflyR3n1Cvz/u6uV9b6/Ir1336hKu09BudPFnW9GCcE/z9A9SnT3hHTwMAgE7NcsdDw5BMs8HW5S3ZHbGmPrupkpPGGF5WrWvmZxwvl7eaA3d0/069oUyXb8UHAABwvmpJCG3uWG9t9eozg4JkBgXJr6TpzeBMSWqie0jNuMoZd7d4S/a24K0VH+EaAAAAXtUP3X7f3mBYnylV36TocnlWxiU1a5XblLyuVNfm7hMqMzjYMty3dy22t3Dd5ctCAAAA0Dhvq9bB8+YoKPMFz4qyo6YlnsXarLuRcFtzbfn5eS0JaYoZFKSTS5Z5uo7U11lqsVm5BgAA6OKswrP0beg9VNCgJMMMClLl7XfUCda11d8AprllGVb12s0pHzEdDp145jk5ExK9lqV0lpVrwjUAAEAXZhlou3WrDtRVVV7PMx0O7zceqnqlujW13M7Y8QrcvLFB0G+sfKT2Nuf1V9OlzlVzTVkIAABAF2a5QcyZM02f2Ej5RmMlILXVD/aOQwUKWvOy1yAcMusXloG+piVgYNba6psZawdrw1Dl7Xd0mm4hXb7PNQAAwPmstbXI3m4wNCUZpyp0YWSvBtuc19fUzo+1ORMSdeKZ5xpus16rJaDl9UxTgZs3Nv2G2gnhGgAAoAtrajOZlqhZL/YrKZFhmnW2ObfSnJ0fa7PcZr3WKndLr9cRqLkGAADowlpbc11fTWC0WtH2djOh3TcfdpabGSXvNdesXAMAAHRxZvcgmaoOyKafn3TmjMzgHnKHhqrZq6wOh9dSEW8rxxULF3kt86jZQr2p8pLa44yKCpkBAZbX6ywI1wAAAF1Uzaq1X2mJDFWvOhtutwyp+lhlpSpn3N0wANe7jhkU1PgNjl5KT7yVeUjV3UEchwoaLS+pmX/NOL/Skurt20NDLctGOgPKQgAAALqo5mxV7vp2N8Wm2uUFpy62vJZpGDrx7PMtCrje5lW7n3Wj4yTPLpAdFazpcw0AAHCeuTCyl+UmMLU1t2e1Ze22Yagy+S5VPPG0bfOq3bO6qfl3RH/rGtRcAwAAnGea1SnEMJosz5C8lHg8+3yLg3Vg1lrJz3sErd2qr6n5e2vr15F8WrkuKyvT7NmzdfjwYUVHRystLU29evVqMG7o0KEaPHiwJCkqKkrp6emSpAULFmjXrl0yTVOXXHKJli5dquDgYM95Gzdu1K9//WutX79eV155ZZPzYeUaAADgO1arzbXV38a8Rlt132hqPrXnVXSsvFnja+/e2J7aZOU6IyNDo0eP1qZNmzR69GhlZGRYjuvevbtycnKUk5PjCdZSdbh+7bXX9PrrrysqKkovv/yy57mTJ0/qz3/+s4YPH+7LFAEAAM5b9Veb3X1C69wMKC9rrG3VN9pqExgrNSvWdebfxNjOwqdwvXXrVsXHx0uS4uPjtWXLlhad36NHD0mSaZo6ffp0nef+8Ic/6J577lFgYKAvUwQAADivORMSVZK3WyeefV5mcLCM0lJPbbW7f4zlOW0VWJsT2uu31vPMf/mKRndv7Cx8CtfFxcWKiIiQJIWHh6u4uNhynNPp1KRJk5SYmNgggM+fP1/XXHONvvjiC02bNk2StHv3bh09elRjxozxZXoAAABQw5Z2NbXVztjx7RpYGwvtptRoa72mdm/sLPybGpCcnKyioqIGx1NSUuo8NgxDhmHdWnzbtm2KjIxUQUGBkpKSNHjwYA0YMECStHTpUrlcLj322GPasGGDbr31Vv3+97/X0qVLW/N+AAAAUI9VOYZRWanAzRt14uk/1WnD15bt7SoWLlLIL++xrPN2N6PO25mQ2OnCdH1NhuvMzEyvz4WFhamwsFAREREqLCxUaGio5bjIyEhJUkxMjEaNGqU9e/Z4wrUkORwOxcXFacWKFbrxxhu1f/9+TZ8+XZL0zTff6L777tPy5cubdVMjAAAA6vJWjuF3+JBtgTUwa22TId2ZkCj/Dz9QUOYLdQJ2ZyzvaC2fykLGjh2r7OxsSVJ2drbGjRvXYEx5ebmqvt23vqSkRHl5eRo0aJBM09TBgwclVddc5+bmauDAgQoJCdE//vEP5ebmKjc3VyNGjCBYAwAA+MBbOYZdtdXeyk6sWvpVPPG0Tjz7fKcv72gtn1rxlZaWKiUlRUeOHFG/fv2Ulpam3r17Kz8/X2vWrFFqaqry8vK0aNEiGYYh0zQ1ffp0TZ48WW63W1OmTFFFRYVM09SQIUO0ePFiz02ONaZNm6b777+fVnwAAACtZLkBjI0bsHjbSbGtWvp1BuzQCAAAcB5rTtlGS8bV5m0nxY7qQd0eCNcAAABoVGtXuFm5/g7bnwMAAJynArPWKvSqy3VhZC+FXnW5eiy837KrSFNbjFcsXHRO9KBuD012CwEAAEDXU3+V2nGowOsuiE1t/lKzqt1eLf06M8pCAAAAzkPeSjmsuPuEqnjfgbad0DmGshAAAAB4NGcrcg/rfQJhgXANAABwHmpJj2ujtLQNZ9K1EK4BAADOQ5Y3IRrWS9R2bTZzPiBcAwAAnIecCYk68fSf6uyUWJl8F10/fMQNjQAAAPBozSYy5yM2kQEAAABsQrcQAAAAoI0RrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJsQrgEAAACbEK4BAAAAmxCuAQAAAJv4+3JyWVmZZs+ercOHDys6OlppaWnq1atXg3FDhw7V4MGDJUlRUVFKT0+XJC1YsEC7du2SaZq65JJLtHTpUgUHB0uSNmzYoGeeeUaGYejSSy/V//zP//gyVQAAAKDNGaZpmq09edmyZerdu7dmzpypjIwMlZeXa+7cuQ3GjRw5Ujt27Ghw/OTJk+rRo4ckaenSpQoLC9PMmTN14MABpaSk6KWXXlKvXr1UXFyssLCwJudz5oxLZWWnWvt2AAAAgGYJDw+xPO5TWcjWrVsVHx8vSYqPj9eWLVtadH5NsDZNU6dPn/YcX7t2re644w7PKnhzgjUAAADQ0XwK18XFxYqIiJAkhYeHq7i42HKc0+nUpEmTlJiY2CCAz58/X9dcc42++OILTZs2TZJ04MABffnll7r99tuVmJiod955x5dpAgAAAO2iyZrr5ORkFRUVNTiekpJS57FhGDIMw/Ia27ZtU2RkpAoKCpSUlKTBgwdrwIABkqrLQVwulx577DFt2LBBCQkJcrlcOnjwoFatWqWjR49q6tSpev3119WzZ8/WvEcAAACgXTQZrjMzM70+FxYWpsLCQkVERKiwsFChoaGW4yIjIyVJMTExGjVqlPbs2eMJ15LkcDgUFxenFStWKCEhQZGRkRo+fLi6deummJgYXXzxxTpw4ICGDRvWwrcHAAAAtB+fykLGjh2r7OxsSVJ2drbGjRvXYEx5ebmqqqokSSUlJcrLy9OgQYNkmqYOHjwoqbrmOjc3VwMHDpQk3XDDDfrwww895xw4cEAxMTG+TBUAAABocz51CyktLZDi/JUAABQTSURBVFVKSoqOHDmifv36KS0tTb1791Z+fr7WrFmj1NRU5eXladGiRTIMQ6Zpavr06Zo8ebLcbremTJmiiooKmaapIUOGaPHixerRo4dM09Tvf/97vfvuu3I4HLr33nsVFxfX5HzoFgIAAID24K1biE/hurMhXAMAAKA9tEkrPgAAAADfIVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANvH35eSysjLNnj1bhw8fVnR0tNLS0tSrV68G44YOHarBgwdLkqKiopSeni5JWrBggXbt2iXTNHXJJZdo6dKlCg4O1tdff6158+bpxIkTcrlc+t3vfqfrr7/el6kCAAAAbc4wTdNs7cnLli1T7969NXPmTGVkZKi8vFxz585tMG7kyJHasWNHg+MnT55Ujx49JElLly5VWFiYZs6cqYceekhDhw7VlClT9Nlnn2nmzJnKzc1tcj5nzrhUVnaqtW8HAAAAaJbw8BDL4z6VhWzdulXx8fGSpPj4eG3ZsqVF59cEa9M0dfr0ac9xwzB08uRJSdKJEycUERHhyzQBAACAduFTWUhxcbEn+IaHh6u4uNhynNPp1KRJk+Tv76+ZM2fqhhtu8Dw3f/58/f3vf9f3vvc9PfDAA5KkWbNm6a677tLq1atVWVmplStX+jJNAAAAoF00Ga6Tk5NVVFTU4HhKSkqdx4ZhyDAMy2ts27ZNkZGRKigoUFJSkgYPHqwBAwZIqi4Hcblceuyxx7RhwwYlJCTojTfe0K233qo777xTO3bs0P3336+//e1v8vPj/ksAAAB0Xk2G68zMTK/PhYWFqbCwUBERESosLFRoaKjluMjISElSTEyMRo0apT179njCtSQ5HA7FxcVpxYoVSkhI0Pr167VixQpJ1fXaTqdTpaWlCgsLa8l7AwAAANqVT0vBY8eOVXZ2tiQpOztb48aNazCmvLxcVVVVkqSSkhLl5eVp0KBBMk1TBw8elFRdc52bm6uBAwdKqu4osn37dknS559/LqfT6TW4AwAAAJ2FT91CSktLlZKSoiNHjqhfv35KS0tT7969lZ+frzVr1ig1NVV5eXlatGiRDMOQaZqaPn26Jk+eLLfbrSlTpqiiokKmaWrIkCFavHixevTooc8++0wPPvigTp06JcMwNHfuXF177bVNzoduIQAAAGgP3rqF+BSuOxvCNQAAANpDm7TiAwAAAPAdwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE8I1AAAAYBPCNQAAAGATwjUAAABgE5/CdVlZmWbMmKEbb7xRM2bMUHl5ueW4oUOHauLEiZo4caLuvffeBs8//vjjGjlypOdxVVWVUlJSFBsbq8mTJ+vQoUO+TBMAAABoFz6F64yMDI0ePVqbNm3S6NGjlZGRYTmue/fuysnJUU5OjtLT0+s8l5+f3yCUr1u3Tj179tTmzZuVnJysp556ypdpAgAAAO3Cp3C9detWxcfHS5Li4+O1ZcuWFp3vcrm0bNkyzZ07t87x3Nxc3XrrrZKk8ePHa/v27TJN05epAgAAAG3Op3BdXFysiIgISVJ4eLiKi4stxzmdTk2aNEmJiYl1Avjq1as1btw4zzVqHDt2TFFRUZIkf39/hYSEqLS01JepAgAAAG3Ov6kBycnJKioqanA8JSWlzmPDMGQYhuU1tm3bpsjISBUUFCgpKUmDBw9WYGCg3nrrLa1ataqVUwcAAAA6lybDdWZmptfnwsLCVFhYqIiICBUWFio0NNRyXGRkpCQpJiZGo0aN0p49e9S9e3d99dVXuvHGGyVJlZWVio2N1ebNmxUZGakjR46ob9++Onv2rE6cOKE+ffq04u0BAAAA7censpCxY8cqOztbkpSdna1x48Y1GFNeXq6qqipJUklJifLy8jRo0CCNGTNG7733nnJzc5Wbm6ugoCBt3rzZc93//d//lSRt3LhRV199tddVcQAAAKCz8Clcz5w5U++9955uvPFGvf/++5o5c6ak6g4gCxculCR9/vnnSkhI0C233KKkpCTdc889GjRoUKPXve2221RWVqbY2FitXLlSv/vd73yZJgAAANAuDLMLteE4c8alsrJTHT0NAAAAdHHh4SGWx9mhEQAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALAJ4RoAAACwCeEaAAAAsAnhGgAAALCJvy8nl5WVafbs2Tp8+LCio6OVlpamXr16NRg3dOhQDR48WJIUFRWl9PT0Os8//vjjysrK0o4dOyRJK1eu1Lp16+RwOBQaGqolS5YoOjral6kCAAAAbc6nleuMjAyNHj1amzZt0ujRo5WRkWE5rnv37srJyVFOTk6DYJ2fn6/y8vI6x4YOHaqsrCy9/vrrGj9+vJ588klfpgkAAAC0C5/C9datWxUfHy9Jio+P15YtW1p0vsvl0rJlyzR37tw6x6+++moFBQVJkkaMGKGjR4/6Mk0AAACgXfgUrouLixURESFJCg8PV3FxseU4p9OpSZMmKTExsU4AX716tcaNG+e5hpX169fruuuu82WaAAAAQLtosuY6OTlZRUVFDY6npKTUeWwYhgzDsLzGtm3bFBkZqYKCAiUlJWnw4MEKDAzUW2+9pVWrVnl97ZycHO3atUurV69uapoAAABAh2syXGdmZnp9LiwsTIWFhYqIiFBhYaFCQ0Mtx0VGRkqSYmJiNGrUKO3Zs0fdu3fXV199pRtvvFGSVFlZqdjYWG3evFmS9P777ys9PV2rV69WQEBAS98XAAAA0O58KgsZO3assrOzJUnZ2dkaN25cgzHl5eWqqqqSJJWUlCgvL0+DBg3SmDFj9N577yk3N1e5ubkKCgryBOs9e/bo4Ycf1vLlyxUWFubLFAEAAIB2Y5imabb25NLSUqWkpOjIkSPq16+f0tLS1Lt3b+Xn52vNmjVKTU1VXl6eFi1aJMMwZJqmpk+frsmTJze41siRIz2t+JKTk7V//36Fh4dLsm7fZ+XMGZfKyk619u0AAAAAzRIeHmJ53Kdw3dkQrgEAANAevIVrdmgEAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGzi39ETAAAAQNuYNy9QmZndZJodPZO2ExwsPfXUaSUknO3oqUgiXAMAAHRJ8+YFauXKbpKMjp5Km6qokGbN6i6pcwRswzS7zu8yZ864VFZ2ql1f88Tps3r4zb0qrzzTrq8LAABgZdLwKP308r6Kiuohl6trB+va+vd3Ky+vot1eLzw8xPI4K9c+MgwpOMChs64u8zsKAAA4hwX6OyRJLlcHT6SdHT7cOX6RIFz7qEegvx6PG9rR0wAAAKjD4Ti/AnZ0dOdY6KRbCAAAQBc0ffoZSZ0jcLY1h8PUwoXOjp6GJFauAQAAuqQnnqgOm3QLaV/c0AgAAAC0kLcbGikLAQAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGxCuAYAAABsQrgGAAAAbEK4BgAAAGzSpbY/BwAAADoSK9cAAACATQjXAAAAgE0I1wAAAIBNCNcAAACATQjXAAAAgE0I1wAAAIBNCNct9OabbyouLk6XXnqp8vPzPcffe+89TZo0SRMmTNCkSZO0fft2z3O7du3ShAkTFBsbq8cff1x0P2w+b5+3JD333HOKjY3V+PHj9e6773qOv/POOxo/frxiY2OVkZHR3lPuUv79738rMTFREydO1KRJk7Rz505JkmmaevzxxxUbG6sJEyZo9+7dHTzTrmPVqlW66aabFBcXp2XLlnmOe/u+wx4vvviihgwZopKSEkl8x9vKE088oZtuukkTJkzQf//3f+v48eOe5/iOtw3+TuwAJlrks88+Mz///HNz6tSp5s6dOz3Hd+/ebR49etQ0TdPct2+fee2113qeS0hIMHfs2GG63W7zrrvuMt9+++12n/e5ytvn/emnn5oTJkwwnU6n+dVXX5njxo0zz549a549e9YcN26c+dVXX5lOp9OcMGGC+emnn3bgOzi3zZgxw/N9ffvtt82pU6d6/nzXXXeZbrfb3LFjh3nbbbd15DS7jO3bt5tJSUmm0+k0TdM0i4qKTNP0/n2HPb7++mvzzjvvNMeMGWMWFxebpsl3vK28++675pkzZ0zTNM1ly5aZy5YtM02T73hb4e/EjsHKdQt973vf08CBAxscv+yyyxQZGSlJ+v73vy+n06mqqioVFhbq5MmTGjFihAzDUHx8vLZu3dre0z5nefu8t27dqri4OAUEBCgmJkYXXXSRdu7cqZ07d+qiiy5STEyMAgICFBcXx+ftA8MwVFFRIUk6ceKEIiIiJFV//vHx8TIMQyNGjNDx48dVWFjYkVPtEl555RXNnDlTAQEBkqSwsDBJ3r/vsMfSpUs1d+5cGYbhOcZ3vG1ce+218vf3lySNGDFCR48elcR3vK3wd2LHIFy3gY0bN+qyyy5TQECAjh07pr59+3qe69u3r44dO9aBs+sa6n+ukZGROnbsmNfjaJ0FCxZo2bJluv766/XEE09ozpw5khp+/nyv7XHgwAF99NFHmjx5sqZOneoJF3yv286WLVsUERGhSy+9tM5xvuNtLysrS9ddd50kvuNthc+1Y/h39AQ6o+TkZBUVFTU4npKSohtuuKHRcz/99FM99dRTevHFF9tqel2OL583fNfY5//BBx9o/vz5Gj9+vDZs2KCFCxcqMzOz/SfZhTT2ebtcLpWXl2vt2rXKz89XSkoKq0w2aOwzf+655/j/tc2a8//05cuXy+Fw6JZbbmnv6QFtjnBtobXh4ejRo5o1a5aeeOIJDRgwQFL1b4k1/+xVM6amfATVWvN51/9cjx075vlcvR2HtcY+/3nz5mnhwoWSpJtvvlkPPvigJL7Xvmjs837llVcUGxsrwzA0bNgw+fn5qbS0tNHvO5rm7TPft2+fDh06pIkTJ0qq/h5PmjRJ69at4zvug6b+n/7qq6/q7bffVmZmpqcUh+942+Bz7RiUhdjk+PHjmjlzpn7729/qBz/4ged4RESEevTooY8//limaSo7O1vjxo3rwJl2DWPHjtUbb7yhqqoqFRQU6MCBAxo2bJiuvPJKHThwQAUFBaqqqtIbb7yhsWPHdvR0z1kRERH68MMPJUkffPCBLr74YknVn392drZM09THH3+skJAQTz02Wu+GG27QP/7xD0nSl19+qTNnzqhPnz5ev+/wzZAhQ7R9+3bl5uYqNzdXffv21auvvqrw8HC+423knXfe0YoVK7R8+XIFBQV5jvMdbxv8ndgxDNOkL1xLbN68WY899phKSkrUs2dPDR06VC+88IKeffZZZWRk6KKLLvKMffHFFxUWFqb8/HzNnz9fp0+f1nXXXaeHHnqozo0z8M7b5y1V/7NiVlaWHA6HFixYoOuvv16S9Pe//11LliyRy+VSQkKC7rvvvo58C+e0jz76SEuWLNHZs2cVGBioRYsW6YorrpBpmnr00Uf17rvvKigoSEuWLNGVV17Z0dM951VVVWnBggXau3evunXrpvvvv1+jR4+W5P37DvuMHTtW69evV2hoKN/xNhIbG6uqqir17t1bkjR8+HA9+uijkviOtxX+Tmx/hGsAAADAJpSFAAAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2IVwDAAAANiFcAwAAADYhXAMAAAA2+f8BtPce0D0lGLsAAAAASUVORK5CYII=\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "befefa8a-e8e1-4147-d23f-db668c092471"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 132s 186ms/step - loss: 0.0101 - rmse: 0.0102\n",
-            "MAE: 0.010171186178922653\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YXcsNZ8yu9Ay"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "uCFgbZEOvZ9A"
-      },
-      "source": [
-        "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
-        "\n",
-        "plt.figure(figsize=(10,5))\n",
-        "plt.plot(y_pred_test)\n",
-        "plt.plot(y_val_multi)\n",
-        "plt.ylabel(\"Value\")\n",
-        "plt.xlabel(\"Timestap\")\n",
-        "plt.legend(loc='upper left')\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "dHPRJUt4aXoq"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 521
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "87e645f2-f2f9-4e8e-e0b9-fd807224892a"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "747e6ee9-2da1-43af-c751-1261f54d6c2c"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "46U0FXYB6AbD"
+   },
+   "source": [
+    "We showed here the histograms of Ellis data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "eeead93b-89b4-4798-976c-1b065bbbc4a3"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "c3ac6c2e-c7f3-48ae-c562-23bb7b60c5b4"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "d553c7b1-3a00-40dd-ad5f-cc695d3ecbae"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9jTOMzOqEQEZ"
+   },
+   "source": [
+    "## Identifying trends in Time Series data\n",
+    "There are several ways to think about identifying trends in time series. One popular way is by taking a rolling average, which means that, for each time point, we take the average of the points on either side of it. Note that the number of points is specified by a window size, which we need to choose.\n",
+    "\n",
+    "What happens then because we take the average is it tends to smooth out noise and seasonality. We will see that below right now. Check out this rolling average of `'ellis-cpu.wait_perc'` using the built-in `pandas` methods.\n",
+    "\n",
+    "When it comes to determining the window size, here, it makes sense to first try out one of twelve months, as we're talking about yearly seasonality.\n",
+    "\n",
+    "Note that in the code chunk above we used two sets of squared brackets to extract the `'ellis-cpu.wait_perc'` column as a DataFrame; If we would have used one set, like `df_Ellis['ellis-cpu.wait_perc']`, we would have created a pandas Series.\n",
+    "\n",
+    "In the code chunk above, you also chained methods: you called methods on an object one after another. Method chaining is pretty popular and pandas is one of the packages that really allows you to use that style of programming to the max!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "c8f8cd9a-8477-46b9-e350-9b501f8bf55b"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JKNmf5TeFvQt"
+   },
+   "source": [
+    "We have successfully removed the seasonality and we saw an upward trend for `ellis-cpu.wait_perc`! But how do these two search terms compare?\n",
+    "\n",
+    "We can figure this out by plotting the trends of `'ellis-cpu.wait_perc'`, `cpu_system_perc` and `'load_avg_1_min'` on a single figure:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "02683682-38ad-4745-c7bb-99a9058bb755"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PTkbQPa_6MNb"
+   },
+   "source": [
+    "We established the correlation matrix for Ellis data.\n",
+    "Seaborn has five built-in themes to style its plots: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`. Seaborn defaults to using the darkgrid theme for its plots, but we can change this styling to better suit our presentation needs.\n",
+    "\n",
+    "To use any of the preset themes pass the name of it to `sns.set_style()`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "6e2c3c3c-5a69-42ef-87a8-7dfdd65e7ceb"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tdg8lD0OHEtH"
+   },
+   "source": [
+    "Correlation between rows or columns of two DataFrame objectsCompute pairwise"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "ab6efc64-5329-4ad2-e5a8-acecf7c79eff"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "3e1fc354-aefb-496b-9e08-d05a458f9c23"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "a8c2999d-5fd1-4de3-f8fd-05cd6ff14622"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Q23ry_WpH6tt"
+   },
+   "source": [
+    "train test split for simple time series moving window average"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "6375471f-a7ec-4416-95e0-4f9a82872168"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "22Y4ztlZIpFG"
+   },
+   "source": [
+    "Defined a `multivariate_data` function to generate multivariate data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MxS23z--ZtQt"
+   },
+   "source": [
+    "Generate multivariate data using a defined function `multivariate_data`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "3f2a841e-eec2-4cf9-e370-4ab5a8bcc725"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "DQ8txbggaJ2-"
+   },
+   "source": [
+    "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
+    "- Creating a source dataset from our input data.\n",
+    "- Applied dataset transformations to preprocess the data.\n",
+    "- Iterate over the dataset and process the elements.\n",
+    "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
+    "Once we have a dataset, we can apply transformations to prepare the data for our model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "719a1cea-6548-4597-fc05-b183cc485387"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "IN6IQykaEzcF",
+    "outputId": "f7877fba-a745-4f3e-f654-c8cdeed5181e"
+   },
+   "outputs": [],
+   "source": [
+    "x_train_ss.shape[-2:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "SIc3631raYA_"
+   },
+   "source": [
+    "We used a custom loss function to evaluate the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "004c1521-5b4c-4304-fa58-76bd01a9dcca"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "from keras.utils.vis_utils import plot_model\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:])))\n",
+    "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "#single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "\n",
+    "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Bi-LSTM.png', show_shapes=True, show_layer_names=True)\n",
+    "single_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "rePzISUuFmlM"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "90d76f79-4228-4f67-ef58-eb0c6f9e9390"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "16fab4ff-15d9-424a-a599-6f03e1ad0e8b"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "d0dc9e7a-bc96-4f19-815f-da9ed8a82408"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "e0d07c10-c644-4a91-8723-5fc94e35c3a5"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "8e521731-9e70-48b3-b630-44adc32f93fb"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "c6ae5f81-b61d-47e6-cd05-f96a5658ae2d"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "eaIjVnzCJwCS"
+   },
+   "source": [
+    "Bi-directional LSTM:\n",
+    "On some sequence prediction problems, it can be beneficial to allow the LSTM model to learn the input sequence both forward and backwards and concatenate both interpretations. This is known as bidirectional.\n",
+    "\n",
+    "Here, `tf.keras.layers.Bidirectional` is a bidirectional wrapper for RNNs which inherits from `Wrapper`, `Layer`, and `module`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "be27d60a-53b9-4e83-f1e3-45bf9b751196"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:])))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "74bc7df8-2315-401b-8cd8-d7632c14abb7"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "cdd29cbc-c26e-46d0-aaaf-0d2a8a4cb047"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "befefa8a-e8e1-4147-d23f-db668c092471"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YXcsNZ8yu9Ay"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "uCFgbZEOvZ9A"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
+    "\n",
+    "plt.figure(figsize=(10,5))\n",
+    "plt.plot(y_pred_test)\n",
+    "plt.plot(y_val_multi)\n",
+    "plt.ylabel(\"Value\")\n",
+    "plt.xlabel(\"Timestap\")\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "Attention_LSTM.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb b/models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb

index 195dd3c..caae594 100644 (file)
--- a/models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb
+++ b/models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb
@@ -1,1661 +1,930 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "l43uL109ZssB"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "Bi-LSTMstacked-LSTM_Correlation.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "14ee2b60-05d7-4163-d420-58970bc4e4b0"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "l43uL109ZssB"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "14ee2b60-05d7-4163-d420-58970bc4e4b0"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 521
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "87e645f2-f2f9-4e8e-e0b9-fd807224892a"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 41
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "747e6ee9-2da1-43af-c751-1261f54d6c2c"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3f424b5d0>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 42
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "46U0FXYB6AbD"
-      },
-      "source": [
-        "We showed here the histograms of Ellis data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "eeead93b-89b4-4798-976c-1b065bbbc4a3"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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LBhZunSpebcuXPmv//9rwkLCzOpqalVriumTJli/vrXv5ri4mKTn59vvvjiiwr39/jjj5vu3bub3bt3m8LCQjN16lQzefJkY4wxp0+fNn379jVr1641hYWFZu/evaZ79+5m//799nX//Oc/V7jt8mIcMGCAOXDggDl79qy57777zB//+MfLHo+SbUyZMsWcPn3afPvtt6ZHjx7m448/NsYYM3bsWPPGG2/Yl1+wYIGZO3euMcaYdevWmXvuuafU9hYsWGAeeughc+LECXPq1Cnz0EMPmcWLFxtjjFm8eLF5+umnTUFBgSkoKDBffPGFOX/+fIWx/fjjj6Zv374mMzPTHuvBgweNMca8/vrrJjY21hw7dsycO3fOPP3002bKlCnGGGMOHz5sunbtat59911TUFBgjh8/br755pvLHgcAaEj1w4EDB0xgYKBJS0szBQUFJiEhwdxxxx3m3LlzxhhjbrzxRpORkVEqlpLtlfzGr4oXX3zR/OpXvzLvv/++KSgoMCtXrjT9+/c3BQUFxhhj3nvvPZOZmWmKi4tNUlKSCQwMNDabzT4vNDTU7N6925w/f95kZGSYw4cPG2OM6d+/v/n444/Nnj17TL9+/cyWLVuMMcbs3bvX9OzZ0+zatcsUFRWZ9evXm/79+9vLVbJeiTfffNM89NBD5syZM6aoqMh8/fXX5tSpUxWW5/Tp0yYoKMj8+OOPxhhjbDab+f77740xxnz44YfmjjvuMD/88IMpLCw0f/nLX8zIkSONMcacOnXKhISEmFdeecXk5+ebU6dOmV27dlXpGMJxtGRCrTl//rwmTJigm266SampqVq1apVWrVql7du3V3kbL7zwgkJCQvTFF18oNTVV991332WXf//99zV58mR9+umnatasmUaOHKmAgAB9+umnGjhwoJ555pkqx1aSlf/iiy908803a8yYMTp//rxSU1M1adIkzZw5s9wYNm/erHbt2mnFihXauXOnmjVrJknauHGj5s2bp3//+99q27atRo8erSFDhuiTTz7R888/rzlz5uiHH36QJC1evFj/+c9/lJiYqOTkZGVlZekvf/lLpcfr559/1rlz55Samqr4+Hg99dRTeuedd7Ru3Tq98cYb+utf/6pDhw7Zl09JSdGdd96pzz//XEOGDNHEiRNVWFhY6X4AoKZ8/fXXOn78uB5++GE1a9ZMHTp00N13321/Q1wVbm5uOnr0qLKystS8eXN7K56K3HHHHbr11lvl5uamu+66S/v27ZMkbd26Ve3bt9eIESPk5uamX/3qVxo4cKD+9a9/Vbt8w4cP1y9/+Uu1aNFCd955p31flZk0aZJatmypm266ScOHD7e/MR42bJj9LW5xcbGSkpI0dOjQcrdhjNHq1av15JNPysvLSx4eHnrooYeUlJQk6cJx++mnn3T06FE1bdpUwcHBslgsFcZktVpVUFCgH3/8UYWFhbr22mv1i1/8QpL01ltvacqUKfL391ezZs308MMP64MPPlBRUZE2bdqk3r17a8iQIWratKnatGmjm2++ucrHEEDj1JDqh/fee0/9+vVTSEiImjZtqjFjxig/P187d+6sclmqKiAgQHfeeaeaNm2quLg4FRQUaPfu3ZKkQYMGyc/PT02aNNHgwYPVsWNHpaenS7rQKmjs2LG69dZbZbFY1LFjR7Vv396+3S+//FITJkzQs88+q/79+0u60Ipr5MiRCgwMlNVq1bBhw9S0aVPt2rWr3Njc3NyUk5OjgwcPymq16pZbbpGHh8dly9OkSRPt379f+fn58vX1tfcWeeuttzRu3Dhdf/31cnNz0/jx47Vv3z4dOXJEW7du1dVXX63Ro0erefPm8vDwUGBgoMPHFlVDkgm1xhkVQ3h4uG655RY1b95c4eHhat68uaKjo2W1WjV48GB7RVGV2IKDg9WnTx+5ubnpzjvv1IkTJzRu3Dg1bdpUgwcP1pEjR3Ty5Mkql2XYsGHq3Lmz3NzctH379gorqsoeCio7XhMmTLDHeOLECT3wwAPy8PBQ586ddcMNN+i7776zL3+5SggA6sKRI0eUlZWl4OBg+38rVqyotPn8xaZNmyZjjGJiYhQZGam1a9dKklasWGHvXnDxi4Grr77a/neLFi105swZeyzp6emlYnn33Xf1008/Vbt8Pj4+9r/d3d3t+6rMNddcY/+7ffv2ysrKkiQNGDBAP/74ow4dOqSPP/5YHh4euvXWW8vdxvHjx3X27FkNHz7cXp6xY8fau9uNGTNGHTt21OjRozVgwAAlJCRcNqaOHTvqySef1NKlS9W7d29NmTLF3m3j6NGjmjRpkn0/gwcPVpMmTZSdna1jx47Zk1EAUFUNqX7IyspSu3bt7P9u0qSJrrnmmst2fasuf3//Uvvx8/Oz1yGJiYn2rm3BwcHav3+/vU6o7F791ltvKSgoSD169LBPO3r0qF577bVSxyUzM9O+v0sNHTpUoaGhmjp1qkJDQ/Xcc89d9gV3y5Yt9fzzz+utt95SaGioxo0bZ+9mePToUS1cuNC+3+7du8sYI5vNRr3jZAz8jVpzccVQori4WMHBwaVuspczbdo0vfDCC4qJiVHr1q0VFxenmJgYrVixQi+99JIkKSoqSnPnzpUkeXt729dt0aLFZSuKimIrcem22rRpY/9iUIsWLSRJZ86cUatWrapUlosfGC6uqC7e/1133VXqoaCEqeI4Tl5eXmVivLgczZs31+nTp+3/vlwlBAB14ZprrtG1116r5OTkMvOWLl1apW34+Pho/vz5ki68aY2Li1O3bt00fvz4CsfGqCiWbt266bXXXit3/uVa+dS0Y8eO6frrr5d04Ye0r6+vpAv38UGDBumdd97RgQMHSrViujS+Nm3aqEWLFkpKSpKfn1+ZfXh4eGj69OmaPn26vv/+ez344IPq0qWLevXqVWFcUVFRioqKUl5enmbOnKnFixfrj3/8o/z9/bVw4ULdfvvtZda55ppr7G/KAaCqGlL94Ovrq++//97+b2OMjh07Zr9echjWAAAgAElEQVQ3u7u76+zZs/b5P/30k33eldY9mZmZ9r/Pnz8vm80mX19fHTlyRE899ZRef/11BQUFyWq1lqpDrrnmmlJjUF1qzpw5evnll7Vw4UI9+eST9nXGjx+vCRMmVCm2pk2b6uGHH9bDDz+sw4cPa9y4cfrlL3+p2NjYCtfp06eP+vTpo/z8fC1ZskRPP/20/vnPf9r3fdddd5VZ5+jRo1fUsAE1i5ZMqDUlFcOXX35p/2/nzp16+eWXq7yNkoohLS1Nc+bM0Zw5c3Tw4EGNHz9eO3fu1M6dO+0JprqO7UpdXEGUVFSX7n/OnDmlHgpK5n311Ve10py2okoIAOrKrbfeqquuukoJCQnKz89XcXGxvv/++ytKSrz//vv2+1nr1q1lsVjUpMmV/8T59a9/rYyMDCUmJqqwsFCFhYVKT0+3vzX19vbW4cOHr3i71fHXv/5VZ8+e1f79+7V+/XoNHjzYPm/o0KHasGGDtmzZUuoBwdvbWzabTQUFBZIuvDyIjY3VwoULlZ2dLenCILolXcM/+ugjHTx4UMYYeXp6ymq1XvZh5sCBA9qxY4cKCgrUrFkzNW/e3H6c7733Xi1ZssQ+6Orx48e1efNmSRcSU5988onee+89FRUV6cSJE1XuNgig8WpI9cOgQYO0bds27dixQ4WFhXr11VfVrFkzBQUFSZL+7//+T5s2bVJxcbFSU1P1xRdf2Nf19vZWTk6OTp06VaVY9+7dq+TkZBUVFWnVqlVq1qyZAgMDdfbsWVksFrVt21bShQ9M7N+/375eTEyMXn31Ve3Zs0fGGB08eLDUQNpXXXWVVq5cqS+//FKLFy+WJMXGxuqtt97S7t27ZYzRmTNntHXrVuXl5Um60DLs4qE6Pv30U3333XcqLi6Wh4eH3NzcLns+fv75Z23evFlnzpxRs2bN1LJlS/vy99xzjxISEuxlOHXqlN5//31JF87XTz/9pNdff10FBQXKy8ujt0YdIsmEWuNKFUNtxOaIy1VUlT0U1KSKKiEAqCtWq1UrVqzQt99+qwEDBqhnz5566qmn7D9Qq+Lrr79WbGysgoKCNGHCBM2YMUMdOnS44lg8PDz0yiuv6L333lOfPn0UGhqqxYsX25M2MTEx+uGHHxQcHKyJEydKksaOHVsrX6zp3r27wsPDNWrUKI0ePVqhoaH2ebfffruaNGmigICAUuNl9OzZUzfccINCQ0Pt3RmmTZumjh076u6779Ztt92mUaNG6T//+Y+kC19diouLU1BQkEaOHKl7771XPXv2rDCmgoIC/elPf1KPHj0UGhqq48ePa+rUqZKkBx54QGFhYRo9erSCgoJ099132+vUdu3a6eWXX9Zrr72m7t27Kzo6utTXjgCgPA2pfujUqZP++Mc/at68eerZs6c++ugjrVixwj5264wZM/TRRx/Zu+Hdcccd9n1ff/31ioyM1B133KHg4OBKu9gNGDBA7733nrp166aNGzdq6dKlatq0qW644QaNHj1a99xzj3r37q3vv/9et912m329QYMGafz48Xr00Ud12223adKkScrNzS217VatWunVV19VamqqlixZoi5dumjevHmaO3euunXrpoiIiFJfDx03bpyWL1+u4OBgvfLKK/r5558VHx+v22+/XYMHD1b37t0rHFdQuvAS/PXXX1efPn3UvXt3ffHFF5o9e7akC8OkjB07VlOnTtVtt92mIUOGKDU11X6+Xn31VX300UcKCQnRwIED9dlnn132uKHmWIwxxtlBoOGy2Wx69tln9dlnn6mgoEC//OUvNXnyZH311Vc6ePCgFi9erMOHD2vAgAHau3ev3NzcdP/99+uuu+5SbGysnnvuOb377rvKy8uTt7e3fve732nkyJHl7mv69Ony8/PTlClTJElr1qzRO++8o7///e+SLvyYHjRokL755pvLxta7d28tXbrUHp8kffLJJ3rqqae0ZcsWSVJRU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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "c3ac6c2e-c7f3-48ae-c562-23bb7b60c5b4"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "d553c7b1-3a00-40dd-ad5f-cc695d3ecbae"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "9jTOMzOqEQEZ"
-      },
-      "source": [
-        "## Identifying trends in Time Series data\n",
-        "There are several ways to think about identifying trends in time series. One popular way is by taking a rolling average, which means that, for each time point, we take the average of the points on either side of it. Note that the number of points is specified by a window size, which we need to choose.\n",
-        "\n",
-        "What happens then because we take the average is it tends to smooth out noise and seasonality. We will see that below right now. Check out this rolling average of `'ellis-cpu.wait_perc'` using the built-in `pandas` methods.\n",
-        "\n",
-        "When it comes to determining the window size, here, it makes sense to first try out one of twelve months, as we're talking about yearly seasonality.\n",
-        "\n",
-        "Note that in the code chunk above we used two sets of squared brackets to extract the `'ellis-cpu.wait_perc'` column as a DataFrame; If we would have used one set, like `df_Ellis['ellis-cpu.wait_perc']`, we would have created a pandas Series.\n",
-        "\n",
-        "In the code chunk above, you also chained methods: you called methods on an object one after another. Method chaining is pretty popular and pandas is one of the packages that really allows you to use that style of programming to the max!"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "c8f8cd9a-8477-46b9-e350-9b501f8bf55b"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "JKNmf5TeFvQt"
-      },
-      "source": [
-        "We have successfully removed the seasonality and we saw an upward trend for `ellis-cpu.wait_perc`! But how do these two search terms compare?\n",
-        "\n",
-        "We can figure this out by plotting the trends of `'ellis-cpu.wait_perc'`, `cpu_system_perc` and `'load_avg_1_min'` on a single figure:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "02683682-38ad-4745-c7bb-99a9058bb755"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "PTkbQPa_6MNb"
-      },
-      "source": [
-        "We established the correlation matrix for Ellis data.\n",
-        "Seaborn has five built-in themes to style its plots: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`. Seaborn defaults to using the darkgrid theme for its plots, but we can change this styling to better suit our presentation needs.\n",
-        "\n",
-        "To use any of the preset themes pass the name of it to `sns.set_style()`."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "6e2c3c3c-5a69-42ef-87a8-7dfdd65e7ceb"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tdg8lD0OHEtH"
-      },
-      "source": [
-        "Correlation between rows or columns of two DataFrame objectsCompute pairwise"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "ab6efc64-5329-4ad2-e5a8-acecf7c79eff"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 49
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "3e1fc354-aefb-496b-9e08-d05a458f9c23"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 50
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "a8c2999d-5fd1-4de3-f8fd-05cd6ff14622"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f21c0790>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f217f790>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f2132b90>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f20e9f50>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 51
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Q23ry_WpH6tt"
-      },
-      "source": [
-        "train test split for simple time series moving window average"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "6375471f-a7ec-4416-95e0-4f9a82872168"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "22Y4ztlZIpFG"
-      },
-      "source": [
-        "Created multivariate data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "3f2a841e-eec2-4cf9-e370-4ab5a8bcc725"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "MMSskyxNaMj3"
-      },
-      "source": [
-        "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
-        "- Creating a source dataset from our input data.\n",
-        "- Applied dataset transformations to preprocess the data.\n",
-        "- Iterate over the dataset and process the elements.\n",
-        "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
-        "Once we have a dataset, we can apply transformations to prepare the data for our model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "719a1cea-6548-4597-fc05-b183cc485387"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "IN6IQykaEzcF",
-        "outputId": "f7877fba-a745-4f3e-f654-c8cdeed5181e"
-      },
-      "source": [
-        "x_train_ss.shape[-2:]"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "(120, 4)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 57
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "004c1521-5b4c-4304-fa58-76bd01a9dcca"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "from keras.utils.vis_utils import plot_model\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:])))\n",
-        "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "#single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "\n",
-        "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Bi-LSTM.png', show_shapes=True, show_layer_names=True)\n",
-        "single_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 52s 924ms/step - loss: 0.0746 - rmse: 0.1454 - val_loss: 0.0103 - val_rmse: 0.0111\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 45s 900ms/step - loss: 0.0075 - rmse: 0.0093 - val_loss: 0.0136 - val_rmse: 0.0137\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 45s 898ms/step - loss: 0.0068 - rmse: 0.0077 - val_loss: 0.0027 - val_rmse: 0.0033\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - ETA: 0s - loss: 0.0050 - rmse: 0.0061Epoch 5/20\n",
-            "50/50 [==============================] - 44s 893ms/step - loss: 0.0089 - rmse: 0.0104 - val_loss: 0.0058 - val_rmse: 0.0062\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 45s 896ms/step - loss: 0.0081 - rmse: 0.0088 - val_loss: 0.0100 - val_rmse: 0.0102\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 45s 908ms/step - loss: 0.0063 - rmse: 0.0072 - val_loss: 0.0054 - val_rmse: 0.0057\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 45s 911ms/step - loss: 0.0030 - rmse: 0.0038 - val_loss: 0.0044 - val_rmse: 0.0046\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 45s 913ms/step - loss: 0.0056 - rmse: 0.0066 - val_loss: 0.0055 - val_rmse: 0.0055\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0045 - rmse: 0.0055 - val_loss: 0.0070 - val_rmse: 0.0070\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 45s 910ms/step - loss: 0.0035 - rmse: 0.0040 - val_loss: 0.0014 - val_rmse: 0.0015\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 44s 898ms/step - loss: 0.0198 - rmse: 0.0304 - val_loss: 0.0077 - val_rmse: 0.0077\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 45s 900ms/step - loss: 0.0051 - rmse: 0.0065 - val_loss: 0.0012 - val_rmse: 0.0013\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 48s 965ms/step - loss: 0.0060 - rmse: 0.0074 - val_loss: 0.0026 - val_rmse: 0.0026\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0041 - rmse: 0.0053 - val_loss: 0.0017 - val_rmse: 0.0018\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 45s 914ms/step - loss: 0.0040 - rmse: 0.0053 - val_loss: 0.0035 - val_rmse: 0.0035\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 45s 910ms/step - loss: 0.0025 - rmse: 0.0027 - val_loss: 0.0025 - val_rmse: 0.0026\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - ETA: 0s - loss: 0.0025 - rmse: 0.0027Epoch 19/20\n",
-            "50/50 [==============================] - 45s 909ms/step - loss: 0.0024 - rmse: 0.0027 - val_loss: 0.0023 - val_rmse: 0.0024\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0020 - rmse: 0.0024 - val_loss: 7.3451e-04 - val_rmse: 8.8589e-04\n",
-            "Model: \"sequential_3\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "bidirectional_3 (Bidirection (None, 120, 64)           9472      \n",
-            "_________________________________________________________________\n",
-            "lstm_7 (LSTM)                (None, 100)               66000     \n",
-            "_________________________________________________________________\n",
-            "activation_3 (Activation)    (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "dense_3 (Dense)              (None, 1)                 101       \n",
-            "=================================================================\n",
-            "Total params: 75,573\n",
-            "Trainable params: 75,573\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "rePzISUuFmlM"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "90d76f79-4228-4f67-ef58-eb0c6f9e9390"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "16fab4ff-15d9-424a-a599-6f03e1ad0e8b"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "xFJT1rZDAUVL",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "d0dc9e7a-bc96-4f19-815f-da9ed8a82408"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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4uqd9/oh1ox6kGHavssLCwkIOBZ7edr13IZONC9UruoqAjWr/8ec3Nzrl+/TrNmzfD1HastLgCzZs1gxIjHGTHicX78MZbPPlvMwoWfAPDXX5mEha1ArVbTtKkV27dvYfz4Zzl8+CDOzp2kcAhxG7zU41W+O7WGkpKqi4eZ2owXu79yB1PVHxnbo5byCku4eXVIUco/G8rCwoKIiG+1/73wQuVxvwA6duzE3Lnv8vPPP1X5QOTvvx/Dy6v8/dLDh4/i2LGj2nmPPTZUu9yoUaPZunUzAJs3xzJy5GiDt0MIAe1bdGDFsFVoTJtgqqr4TnpTlRka0yasGLbqrnlQUI48gFEPOtR4lHDs4jVeXn+MktIyTNUm/N8o13o/dXXT4sWh/PZbEvv27WbVqhVERup3t4alpaX2aweHVrRsacuRI4dISUnh/ffn3e64QtyzPNt5s/Op/Sz77UvW/7GWvKI8rMyteNLlaV7s/spdUzhAiketdWvdnK+e7HbHrnncVFZWRmZmBr169aFbtx7ExW2joKCAJk2akp9/Q9vuoYe6ERf3M8OHj2Lbti1069azyj59fHyZO/c9hg0bWaehXYQQVWvfogMfuX/CR+6fNHSUeiXFQw/dWje/Y0XjprKyMubOfY8bN/JQFIVx456mWbNmDBgwiPfee5M9e3YxY8ZMZsyYxYIFH7JmzWrtBfOqDBw4mAUL5jJqlJyyEkLUjTzn0QjV97MTJ0+m8Pnn/+arr74xuC95zqP+GFNWMK68xpQV5DkP0QisXh1BTEy0XOsQQhhEisc95vnnA3j++YCGjiGEMHJyq64QQgi9SfEQQgihNykeQggh9CbFoxqaJaGY7d1dbRuzvbvRLAm9Q4mEEKJxkAvm1Sjp2YvmU/y59nUkxTrGnDLbu1s7X1+5uTlMn/4yANnZWZiYmGBtXT7G1IoVqzExMfzhvWnTgsjKuoKFRfkT5v7+k3jssaE62166dJHk5GN4ew83eL1CiLufFI9qFA9059rXkToLyK2FQ1dhqUmLFtZERHwLVBxBF8qfnSgsLLotw6fPmTOPLl261tju0qWLxMVt1bt4lJaWAvIWPyHuNVI8aqCrgBhaOKpyc/j006f/4OGHu9GkSdMKReX558cTEhKKo2Nrfv75J6Kj11JcXELXrg/yxhtv1WqokfnzP+DRRwdqj0BuvpAqLOwLzp37k4CAZxkxYhTNmjXn5MkUXn/9TQBmzQrm6acn0KtXH7y8BjF69FgOHz7IzJlvceHChTplEUIYL7nmUQu3FpAmH82rl8Jx019/ZRIevpJXX329yjZnz/5JfPx2li5dQUTEt5iYqNm2bYvOth9++C4BAc8SEPAsubk5VfY5deo0unfvSUTEtzz11HPVZiwoKKBr14eIjFxDixYtap1FCHH3kCOPWioe6E6B/2Sa/juEG6/PqpfCAf8bPr26IT+OHDnIqVMneOGFiQAUFv5d5Ts5anvaSh9qtZohQzwAOHSo9lmEEHcPg4pHTk4OM2bM4MKFC7Rp04bQ0FBatGhRqZ2rqysuLi4AODo6EhYWVmH+vHnz2LBhA0lJSQAcOnSIBQsWcOrUKf79738zfPj/zsOHhISwa9cuysrKGDBgALNnz0alqv9z7mZ7d6OJXM6N12ehiVxO8UD3eikgtw6frlarUZT/FZGioiIAFEVhxIjHmTp1mt79q9VqysrKhzMrKyujuFj3i2tubQdQWFik/drc3LzCaam6ZhFCGC+DTluFh4fj5ubGtm3bcHNzIzw8XGc7S0tLYmNjiY2NrVQ4kpOTyc2t+DJ4R0dHFi5cyOOPP15hemJiIomJiXz//ff8+OOPJCcnc/DgQUM2oVZuvcaR/9a72lNYNd3GayhHx9b88cdJAE6dOsmlSxcB6N27Lzt3xnP1ajZQ/gbCy5cv1arPVq0cOXXqBAB79+6mpKT8pVblQ7zn39KuNWfO/EFZWRkZGZc5ceJ3nf316VP3LEII42VQ8YiPj8fPzw8APz8/4uLi9Fq+tLSUkJAQZs6cWWH6/fffT5cuXTAxqRhPpVJRVFREcXGx9v/33XefIZtQI10Xx2+9BlKfBWTIEA+uXbvGhAnj2bDhO5yc2gLQvn0Hpkx5iRkzpuHv/zTBwa9w5cqVWvU5evQYjh5NxN//GY4fP4ZGowHA2bkTJiYm+Ps/w3ff/Ydu3brj6NiaCROeJDT0Y1xcOuvsz5AsQgjjZdCQ7H369OHw4cNA+amURx55RPv5Vl27dqVLly6YmpoSFBTE0KHld/pERkaiKAoBAQH07NlTe9rqprfeeoshQ4ZUOG21aNEi1q9fj6IoTJgwgRkzZtSYU1EUSkoqXkM4deokrVs/UO1ypnt2YTV5InnLV1EyaLDe88WddfHiWTp37lJtm8Y0hHxNjCkrGFdeY8oKDZfXzKzquyZrvOYREBCg8y/J4ODgCp9VKlWV1x527NiBg4MD6enp+Pv74+LigoWFBVu3bmX16tU1RdA6d+4cqamp7Nq1C4BJkyZx+PBh+vTpU+1yikKlsfAVRanxm2F+5Ej5Ecejg0BH29JHB1H2dSSmR45Q+uigWm9HTYzpH3ZjyqooSo3vPDCm9zgYU1YwrrzGlBWM9H0eERERVc6ztbUlMzMTe3t7MjMzsbGx0dnOwaH8/eBOTk707duXlJQULC0tSUtLw9vbGyi//dPLy4vt27dXub7t27fTvXt3mjZtCsCgQYNISkqqsXjUVcGrwTW2qa8L50II0ZgZdM3Dw8ODmJgYAGJiYvD09KzUJjc3V3uXUHZ2NomJiTg7OzNkyBD27dtHQkICCQkJaDSaagsHQOvWrTl06BAlJSUUFxdz6NAhOnbsaMgmCCGEqAODikdQUBD79u3D29ub/fv3ExQUBJTfQTV79mwAUlNTeeKJJxg9ejT+/v5MmTIFZ2fnavs9duwY7u7ubN26lTlz5jBq1CgAhg0bRtu2bfHx8cHX15cuXbrg4eFhyCYIIYSoA3mHeSPUmK4j1KQxZZV3mDcsY8prTFnBSK95CPgz978sPbqE6D/WcaM4j6ZmVoxzGc9LPV6lfYsODR1PCCHuOBnbqgbx57Yx5LtHiUpZRV7xdRQU8oqvE5WyiiHfPUr8uW117nvgwD7Mnfue9nNJSQmPPz6UN954Ta9+xo3zISen6nGrqmszbpwPEyc+hb//08yY8QpZWXV/RmP58mV8+23Vd89dufIX7747C4DTp0/xyy979V7HtGlBnDyZUueMQojbQ4pHNf7M/S+Tfp5IQUk+JUrFYTxKlGIKSvKZ9PNE/sz9b53612g0/Pe/qRQW/g3AoUMHuO8+e4Nz6+vzz5cRGbmWLl26snr1ygrzFEWhrOz2nJa67z475s0LAeD06T/45Zd9t6VfIcSdJ6etqrH06BKKS3WP/XRTcWkxy377ko/cP6nTOtzcBrB//14ee2wocXE/M3SoN8eOHQXKh/pYuHAuFy9ewMLCklmzZuPs3Inc3Bw++GA2f/31Fw899DC3Xraq61DtAN279yQ6ei2XLl3k9den0bXrQ5w6dZKPP/6MhITtJCTEUVxchLv7Y0ye/CIAERHfsHnzj7Rs2RJ7ewc6d3YF4Pz5dBYvXkhOzlXUahP+7/8WYWJiwqxZwaxY8R+++SaMoqJCjh37jeefD+DRRwfx6ach/PlnKiUlJUyaFMSgQUMoLPybBQs+5MyZ07Rt+wCFhYV12s9CiNtLjjyqEf3HukpHHP9UohSz/o+1dV6Hp6c38fHbKCwsJDX1DF27PqSdt3z5Mjp16kxk5FpefPEV5s2bA8DKlV/TrVsPoqLW4e7+GBkZlwH9hmrXZf/+PXToUH4n3Pnz6YwZ8yRRUetISztHeno6X38dycqV33Lq1AmOHk3k5MkTbN++jYiIb/n4488qnE768MN3GTv2SSIj17B06Qpsbf83jIyZmRkvvDAVDw8vIiK+xdPTm1WrVtC79yN8/fUqPv98GV9++TkFBQVs2hSNhYUl//lPNJMnv6gd60sI0bDkyKMaN4rzam4E5BXVrp0uzs6duHTpEnFxP+PmNqDCvGPHjmpP8/Tu/QjXruVy40YeR48mMX9++fRHHx1Is2bNAf2Gar/Va6+9iImJmo4dnZky5WXy8q7TqpUjDz30MAAHD/7KoUO/EhhY/p6PgoJ8zp9PIz8/n8GDH9OOBDzw/z8smZ9/gytX/mLw4McAsLCwqDHDwYO/snfvLtasiQKgqKiQjIzL/PZbEuPGPa3dVx07Vn+btxDizpDiUY2mZlbkFV+vsZ2VuZVB6xk40J0vv/yMJUuWVfvCpprUdaj2zz9fhrW1tfZzXt71CkPDl48jFoCf3xMVllu37ts6Z/0nRVGYPz+Etm0fuG19CiHqj5y2qsY4l/GYqsyqbWOqMuNJl6cNWs+oUaMJDJxS6a/q7t17sn37VgASEw/TokULmja1okeP/03/5Zd9XL9+DTBsqPbq9OvnxubN32uHbP/rr0yuXs2me/de7N69g8LCv8nPv8G+fXuA8uHd7ezs2b17J1D+HpK///67Qp9NmjSpMAR8v35uREd/p71+c/P01K374L//PUNq6hmDt0cIYTgpHtV4qcermKmrLx5majNe7P6KQeuxt3fgyScrF6BJk4I4deoE/v5PExb2BbNnfwhAYOAUfvstiQkTxrN79w4cHFoB9Tc8et++/fHyGs7UqYFMnPgU7777Jvn5+XTu3IWhQ73x93+WN954rcIbC997by7R0Wvx93+aqVMnVboFuFevPpw9W/7O9Pj4bQQETKakpAR//6eZMGE833xT/t6XMWPGUVCQz3PPjeObb5bh4lL9qLlCiDtDnjCvQfy5bUz6eSLFpcUVLp6bqswwU5uxYtgqPNt539a8jemp7Zo0pqzyhHnDMqa8xpQVGucT5nLkUQPPdt7sfGo/Ex8MoJl5M1SoaGbejIkPBrDzqf23vXAIIYQxkAvmtdC+RQc+cv+kzs9yCCHE3eaePvK4B87Y3TPkeynEnXXPFg9TU3Nu3Lgmv3TuAoqicOPGNUxNzRs6ihD3jHv2tFXLlnZcvfoXeXl1f66ivqhUKqMpao0lq6mpOS1b2jV0DCHuGfds8VCrTbnvPseGjqGTMd0JYkxZhRC3zz172koIIUTdSfEQQgihN4OKR05ODoGBgXh7exMYGEhubq7Odq6urvj6+uLr68vUqVMrzZ83bx49e/bUfl65ciUjR47Ex8cHf39/Lly4oJ23adMmvL298fb2ZtOmTYbEF0IIUUcGFY/w8HDc3NzYtm0bbm5uhIeH62xnaWlJbGwssbGxhIWFVZiXnJxcqei4urqyYcMGfvjhB4YNG8bixYuB8mL1xRdfsG7dOtavX88XX3xRZcESQghRfwwqHvHx8fj5+QHg5+dHXFycXsuXlpYSEhLCzJkzK0zv378/Go0GgB49enD5cvn7Kvbu3cuAAQOwtramRYsWDBgwgD179hiyCUIIIerAoOKRlZWFvX35a1Pt7OzIysrS2a6wsJCxY8cyfvz4CgUmKioKT09PbR+6REdH4+5e/p6IjIwMWrVqpZ3n4OBARkaGIZsghBCiDmq8VTcgIEDnyKzBwcEVPqtUKlQqlc4+duzYgYODA+np6fj7++Pi4oKFhQVbt25l9erVVa47NjaW48ePExUVVVPMaqlU5beUGgu12sRo8hpTVjCuvMaUFYwrrzFlhcaZt8biERERUeU8W1tbMjMzsbe3JzMzExsbG53tHBwcAHBycqJv376kpKRgaWlJWloa3t7lAwsWFBTg5eXF9u3bAdi/fz9hYWFERUVhbm6u7efgwYPafjMyMujbt2+NG6koGNWzCMb07IQxZQXjymtMWcG48hpTVrgLR9X18PAgJiYGgJiYGDw9PSu1yc3NpaioCIDs7GwSExNxdnZmyJAh7Nu3j4SEBBISEtBoNNrCkZKSwvvvv8/SpUuxtbXV9jVw4ED27t1Lbm4uubm57N27l4EDBxqyCUIIIerAoCfMg4KCCA4OJjo6mtatWxMaGgqU30G1du1a5s+fT2pqKnPmzNEOYzFlyhScnat/D3VISAj5+flMnz4dAEdHR8LCwrC2tubll19m3LhxALzyyisVXp8qhBDizrhnXwbVmBnTIbUxZQXjymtMWRW0rHMAAB6FSURBVMG48hpTVrgLT1sJIYS4N0nxEEIIoTcpHkIIIfQmxUMIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9SfEQQgihNykeQggh9CbFQwghhN6keAghhNCbFA8hhBB6k+IhhBBCb1I8hBBC6E2KhxBCCL1J8RBCCKE3KR5CCCH0ZmrIwjk5OcyYMYMLFy7Qpk0bQkNDadGiRaV2rq6uuLi4AODo6EhYWFiF+fPmzWPDhg0kJSUBsHLlStavX49arcbGxoYFCxbQpk0bTpw4wQcffEBeXh4mJia89NJLjBw50pBNEEIIUQcGFY/w8HDc3NwICgoiPDyc8PBwZs6cWamdpaUlsbGxOvtITk4mNze3wjRXV1c2bNiARqPh22+/ZfHixYSGhmJpacmiRYt44IEHyMjI4IknnmDgwIE0b97ckM0QQgihJ4NOW8XHx+Pn5weAn58fcXFxei1fWlpKSEhIpYLTv39/NBoNAD169ODy5csAtG/fngceeAAABwcHbGxsyM7ONmQThBBC1IFBRx5ZWVnY29sDYGdnR1ZWls52hYWFjB07FlNTU4KCghg6dCgAUVFReHp6avvQJTo6Gnd390rTjx07RnFxMW3btq0xp0oF1tZNarNJjYJabWI0eY0pKxhXXmPKCsaV15iyQuPMW2PxCAgI4MqVK5WmBwcHV/isUqlQqVQ6+9ixYwcODg6kp6fj7++Pi4sLFhYWbN26ldWrV1e57tjYWI4fP05UVFSF6ZmZmcycOZNFixZhYlLzwZOiQE5Ofo3tGgtr6yZGk9eYsoJx5TWmrGBceY0pKzRcXju7ZlXOq7F4REREVDnP1taWzMxM7O3tyczMxMbGRmc7BwcHAJycnOjbty8pKSlYWlqSlpaGt7c3AAUFBXh5ebF9+3YA9u/fT1hYGFFRUZibm2v7ysvL48UXX2TGjBn06NGjpvhCCCHqgUHXPDw8PIiJiQEgJiYGT0/PSm1yc3MpKioCIDs7m8TERJydnRkyZAj79u0jISGBhIQENBqNtnCkpKTw/vvvs3TpUmxtbbV9FRUV8corr+Dr68vw4cMNiS6EEMIABl3zCAoKIjg4mOjoaFq3bk1oaChQfgfV2rVrmT9/PqmpqcyZMweVSoWiKEyZMgVnZ+dq+w0JCSE/P5/p06cD/7u9d8uWLRw+fJicnBw2bdoEwEcffYSrq6shmyGEEEJPKkVRlIYOUd/KyhSysvIaOkatGdP5WGPKCsaV15iygnHlNaas0DivecgT5kIIIfQmxUMIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9SfEQQgihNykeQggh9CbFQwghhN6keAghhNCbFA8hhBB6k+IhhBBCb1I8hBBC6E2KhxBCCL1J8RBCCKE3KR5CCCH0JsVDCCGE3qR4CCGE0JtBxSMnJ4fAwEC8vb0JDAwkNzdXZztXV1d8fX3x9fVl6tSplebPmzePnj17aj+vXLmSkSNH4uPjg7+/PxcuXKjQPi8vD3d3d+bOnWtIfCGEEHVkUPEIDw/Hzc2Nbdu24ebmRnh4uM52lpaWxMbGEhsbS1hYWIV5ycnJlYqOq6srGzZs4IcffmDYsGEsXry4wvzQ0FAeeeQRQ6ILIYQwgEHFIz4+Hj8/PwD8/PyIi4vTa/nS0lJCQkKYOXNmhen9+/dHo9EA0KNHDy5fvqydd/z4cbKyshgwYIAh0YUQQhjA1JCFs7KysLe3B8DOzo6srCyd7QoLCxk7diympqYEBQUxdOhQAKKiovD09NT2oUt0dDTu7u4AlJWVsWjRIhYvXsz+/ftrnVOlAmvrJrVu39DUahOjyWtMWcG48hpTVjCuvMaUFRpn3hqLR0BAAFeuXKk0PTg4uMJnlUqFSqXS2ceOHTtwcHAgPT0df39/XFxcsLCwYOvWraxevbrKdcfGxnL8+HGioqIA+Pbbb3F3d6dVq1Y1xa5AUSAnJ1+vZRqStXUTo8lrTFnBuPIaU1YwrrzGlBUaLq+dXbMq59VYPCIiIqqcZ2trS2ZmJvb29mRmZmJjY6OznYODAwBOTk707duXlJQULC0tSUtLw9vbG4CCggK8vLzYvn07APv37ycsLIyoqCjMzc0BSEpK4siRI6xZs4YbN25QXFxMkyZN+Ne//lXTZgghhLiNDDpt5eHhQUxMDEFBQcTExODp6VmpTW5uLhqNBnNzc7Kzs0lMTOSFF17A2dmZffv2adv17NlTWzhSUlJ4//33+eabb7C1tdW2+eSTT7Rfb9y4kePHj0vhEEKIBmBQ8QgKCiI4OJjo6Ghat25NaGgoUH4H1dq1a5k/fz6pqanMmTMHlUqFoihMmTIFZ2fnavsNCQkhPz+f6dOnA+Do6FjpLi0hhBANR6UoitLQIepbWZlCVlZeQ8eoNWM6H2tMWcG48hpTVjCuvMaUFRrnNQ95wlwIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9SfEQQgihNykeQggh9CbFQwghhN6keAghhNCbFA8hhBB6k+IhhBBCb1I8hBBC6E2KhxBCCL1J8RBCCKE3KR5CCCH0JsVDCCGE3qR4CCGE0JtB7zDPyclhxowZXLhwgTZt2hAaGkqLFi0qtXN1dcXFxQXQ/T7yefPmsWHDBpKSkgBYuXIl69evR61WY2Njw4IFC2jTpg0AFy9e5N133+XSpUuoVCrCw8O5//77DdkMIYQQejKoeISHh+Pm5kZQUBDh4eGEh4czc+bMSu0sLS2JjY3V2UdycjK5ubkVprm6urJhwwY0Gg3ffvstixcvJjQ0FIA333yTqVOnMmDAAG7cuIGJiRw8CSHEnWbQb974+Hj8/PwA8PPzIy4uTq/lS0tLCQkJqVRw+vfvj0ajAaBHjx5cvnwZgDNnzlBSUsKAAQMAaNq0qbadEEKIO8egI4+srCzs7e0BsLOzIysrS2e7wsJCxo4di6mpKUFBQQwdOhSAqKgoPD09tX3oEh0djbu7OwBnz56lefPmTJs2jfPnz+Pm5sa//vUv1Gp1tTlVKrC2blKXTWwQarWJ0eQ1pqxgXHmNKSsYV15jygqNM2+NxSMgIIArV65Umh4cHFzhs0qlQqVS6exjx44dODg4kJ6ejr+/Py4uLlhYWLB161ZWr15d5bpjY2M5fvw4UVFRAJSUlHD48GFiYmJwdHRkxowZbNy4kSeffLLabVAUyMnJr2lTGw1r6yZGk9eYsoJx5TWmrGBceY0pKzRcXju7ZlXOq7F4REREVDnP1taWzMxM7O3tyczMxMbGRmc7BwcHAJycnOjbty8pKSlYWlqSlpaGt7c3AAUFBXh5ebF9+3YA9u/fT1hYGFFRUZibmwPQqlUrXF1dcXJyAsDT05Pffvutpk0QQghxmxl0zcPDw4OYmBgAYmJi8PT0rNQmNzeXoqIiALKzs0lMTMTZ2ZkhQ4awb98+EhISSEhIQKPRaAtHSkoK77//PkuXLsXW1lbb18MPP8y1a9fIzs4G4MCBAzg7OxuyCUIIIerAoGseQUFBBAcHEx0dTevWrbV3RCUnJ7N27Vrmz59Pamoqc+bMQaVSoSgKU6ZMqfEXfkhICPn5+UyfPh343+29arWaN998E39/fwAefPDBGk9ZCSGEuP1UiqIoDR2ivpWVKWRl5TV0jFozpvOxxpQVjCuvMWUF48prTFmhcV7zkIckhBBC6E2KhxBCCL1J8RBCCKE3KR5CCCH0JsVDCCGE3qR4CCGE0JsUDyGEEHqT4iGEEEJvUjyEEELoTYqHEEIIvUnxEEIIoTcpHkIIIfQmxUMIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9SfEQQgihN1NDFs7JyWHGjBlcuHCBNm3aEBoaSosWLSq1c3V1xcXFBQBHR0fCwsIqzJ83bx4bNmwgKSkJgJUrV7J+/XrUajU2NjYsWLCANm3aABASEsKuXbsoKytjwIABzJ49G5VKZchmCCGE0JNBRx7h4eG4ubmxbds23NzcCA8P19nO0tKS2NhYYmNjKxWO5ORkcnNzK0xzdXVlw4YN/PDDDwwbNozFixcDkJiYSGJiIt9//z0//vgjycnJHDx40JBNEEIIUQcGFY/4+Hj8/PwA8PPzIy4uTq/lS0tLCQkJYebMmRWm9+/fH41GA0CPHj24fPkyACqViqKiIoqLi7X/v++++wzZBCGEEHVg0GmrrKws7O3tAbCzsyMrK0tnu8LCQsaOHYupqSlBQUEMHToUgKioKDw9PbV96BIdHY27uzsAPXv2pF+/fgwcOBBFUZgwYQIdO3asMadKBdbWTfTdvAajVpsYTV5jygrGldeYsoJx5TWmrNA489ZYPAICArhy5Uql6cHBwRU+q1SqKq897NixAwcHB9LT0/H398fFxQULCwu2bt3K6tWrq1x3bGwsx48fJyoqCoBz586RmprKrl27AJg0aRKHDx+mT58+1W6DokBOTn61bRoTa+smRpPXmLKCceU1pqxgXHmNKSs0XF47u2ZVzquxeERERFQ5z9bWlszMTOzt7cnMzMTGxkZnOwcHBwCcnJzo27cvKSkpWFpakpaWhre3NwAFBQV4eXmxfft2APbv309YWBhRUVGYm5sDsH37drp3707Tpk0BGDRoEElJSTUWDyGEELeXQdc8PDw8iImJASAmJgZPT89KbXJzcykqKgIgOzubxMREnJ2dGTJkCPv27SMhIYGEhAQ0Go22cKSkpPD++++zdOlSbG1ttX21bt2aQ4cOUVJSQnFxMYcOHarVaSshhBC3l0HXPIKCgggODiY6OprWrVsTGhoKlN9BtXbtWubPn09qaipz5sxBpVKhKApTpkzB2dm52n5DQkLIz89n+vTpwP9u7x02bBi//vorPj4+qFQqBg0ahIeHhyGbIIQQog5UiqIoDR2ivpWVKWRl5TV0jFozpvOxxpQVjCuvMWUF48prTFmhcV7zkCfMhRBC6E2KhxBCCL1J8RBCCKE3KR5CCCH0JsVDCCGE3qR4CCGE0JsUDyGEEHqT4iGEEEJvUjyEEELoTYqHEEIIvUnxEEIIoTcpHkIIIfQmxUMIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9GVw8cnJyCAwMxNvbm8DAQHJzc3W2c3V1xdfXF19fX6ZOnVpp/rx58+jZs6f285o1a/Dx8cHX15dnnnmGM2fOaOctW7YMLy8vhg0bxp49ewzdBCGEEHoyNbSD8PBw3NzcCAoKIjw8nPDwcGbOnFmpnaWlJbGxsTr7SE5OrlR0fHx8eOaZZwCIj49n4cKFLF++nDNnzrB582Y2b95MRkYGgYGB/Pzzz6jVakM3RQghRC0ZfOQRHx+Pn58fAH5+fsTFxem1fGlpKSEhIZUKjpWVlfbrgoICVCqVdn2jRo3C3NwcJycn2rVrx7FjxwzcCiGEEPow+MgjKysLe3t7AOzs7MjKytLZrrCwkLFjx2JqakpQUBBDhw4FICoqCk9PT20ft/rPf/7DypUrKS4uJjIyEoCMjAy6d++ubePg4EBGRka1GVUqsLZuUqftawhqtYnR5DWmrGBceY0pKxhXXmPKCo0zb62KR0BAAFeuXKk0PTg4uMJnlUqlPUL4px07duDg4EB6ejr+/v64uLhgYWHB1q1bWb16tc5lnnvuOZ577jl++OEHli5dyqJFi2oTtxJFgZyc/Dot2xCsrZsYTV5jygrGldeYsoJx5TWmrNBwee3smlU5r1bFIyIiosp5tra2ZGZmYm9vT2ZmJjY2NjrbOTg4AODk5ETfvn1JSUnB0tKStLQ0vL29gfLTU15eXmzfvr3CsqNGjeKDDz7Q9nP58mXtvIyMDG3fQggh7gyDr3l4eHgQExMDQExMDJ6enpXa5ObmUlRUBEB2djaJiYk4OzszZMgQ9u3bR0JCAgkJCWg0Gm3hOHv2rHb5nTt30q5dO+36Nm/eTFFREenp6Zw9e5Zu3boZuhlCCCH0YPA1j6CgIIKDg4mOjqZ169aEhoYC5XdQrV27lvnz55OamsqcOXNQqVQoisKUKVNwdnautt+oqCh++eUXTE1Nad68ufaUVadOnRgxYgQjR45ErVbz/vvvy51WQghxh6kURVEaOkR9KytTyMrKa+gYtWZM52ONKSsYV15jygrGlbc+smqWhFLSsxfFA92rbGO2dzemSYkUvBpcZRtdGuM1D3nCXAghboOSnr1oPsUfs727dc4327ub5lP8KenZ6w4nqx9SPIQQ4jYoHujOta8jdRaQm4Xj2teR1R6ZGBODr3kYg7/yCjl+8RoAR9JzaKExI7eguMb/93ayrvUy+rStaZkiBcxV1Pt6bkf/RQp0tWtar5lu53bIvr07960+y/R2ssa9np6ZuLWA3CwUd2PhgHukeGRc+5vJa46iAvS9wKPPMvXd/51apjFmqssykqn+lmmMmWq7jIWpCasDLWjf3ELPnmvn1gJS4D8ZTeTyu65wwD122qoudwbos0x993+nlmmMmeqyjGSqv2UaY6baLlNSWsaBP7Pr0HPtFQ90p8B/Mk3/HUKB/+S7rnDAPVI8VICZWoWZWqXdYFUN/zdR1X4Zfdo25mUaY6a7ZTsaY6Z7cTtMVGCqNqFfe90PM98uZnt3o4lczo3XZ6GJXF7lRXRjdk+ctrJvbknY+PLxsBrL+ezGeu5YzsvLvjXGfavvNY+ebVvW262v/7zGUTzQ/a685iHPeTRC9/r98vXJmPIaU1Ywrrz1lbWqi+OGXjSX5zyEEOIuVV2BqO42XmMlxUMIIW4D06TEao8sbhYQ06TEO5ysftwT1zyEEKK+1WbIkZvXQO4GcuQhhBBCb1I8hBBC6E2KhxBCCL3dE7fqCiGEuL3kyEMIIYTepHgIIYTQmxQPIYQQepPiIYQQQm9SPIQQQuhNiocQQgi9SfEQQgiht7uueGzZsoVRo0bRpUsXkpOTtdP37dvH2LFj8fHxYezYsfzyyy/aecePH8fHxwcvLy/mzZvHnXr0paqsAMuWLcPLy4thw4axZ88e7fTdu3czbNgwvLy8CA8PvyM5dTlx4gTjx4/H19eXsWPHcuzYMQAURWHevHl4eXnh4+PD77//3mAZ/2n16tUMHz6cUaNGERISop1e1b5uaCtWrKBz585kZ5e/9a4x7ttFixYxfPhwfHx8eOWVV7h27Zp2XmPdr43lZ0iXS5cu8fzzzzNy5EhGjRpFZGQkADk5OQQGBuLt7U1gYCC5ubkNnBRQ7jJnzpxRUlNTlQkTJijHjh3TTv/999+Vy5cvK4qiKKdOnVIGDhyonffEE08oSUlJSllZmTJ58mRl586dDZr19OnTio+Pj1JYWKikpaUpnp6eSklJiVJSUqJ4enoqaWlpSmFhoeLj46OcPn36jmT9p8DAQO1+2rlzpzJhwgTt15MnT1bKysqUpKQkZdy4cQ2S759++eUXxd/fXyksLFQURVGuXLmiKErV+7qhXbx4UZk0aZIyZMgQJSsrS1GUxrlv9+zZoxQXFyuKoighISFKSEiIoiiNd782pp8hXTIyMpTjx48riqIo169fV7y9vZXTp08rixYtUpYtW6YoiqIsW7ZMu58b0l135NGxY0c6dOhQaXrXrl1xcHAAoFOnThQWFlJUVERmZiZ5eXn06NEDlUqFn58f8fHxDZo1Pj6eUaNGYW5ujpOTE+3atePYsWMcO3aMdu3a4eTkhLm5OaNGjbpjWf9JpVJx48YNAK5fv469vb02u5+fHyqVih49enDt2jUyMzMbJOOt1qxZQ1BQEObm5gDY2toCVe/rhrZw4UJmzpyJSqXSTmuM+3bgwIGYmpYPzt2jRw8uX74MNN792ph+hnSxt7fnwQcfBMDKyooOHTqQkZGh/d4D+Pn5ERcX15AxgbvwtFVt/Pzzz3Tt2hVzc3MyMjJo1aqVdl6rVq3IyMhowHRUyuTg4EBGRkaV0xvCO++8Q0hICIMHD2bRokW8/vrrQOXsjWF/Apw9e5bDhw/z5JNPMmHCBO0vssa0T2+Ki4vD3t6eLl26VJjeWPftTRs2bMDdvXy48ca4X6Hx5tLl/PnznDhxgu7du5OVlaX9A83Ozo6srKwGTmek7/MICAjgypUrlaYHBwczdOjQapc9ffo0H3/8MStWrKiveBUYkrWhVZf9119/5e2332bYsGH89NNPzJ49m4iIiDsf8hbV5S0tLSU3N5d169aRnJxMcHBwg/7FWV3WZcuW3bF/n7VRm3/DS5cuRa1WM3r06Dsd765048YNXnvtNd555x2srKwqzFOpVBWOSBuKURaPuv6Sunz5MtOmTWPRokW0bdsWKP/L4+ah9s02N09v3Q51yfrPTBkZGdpMVU2vD9Vlf/PNN5k9ezYAI0aM4N133wXqf39Wp7q8a9aswcvLC5VKRbdu3TAxMeHq1avV7uuGyHrq1CnOnz+Pr68vUL7/xo4dy/r16xts39b0b3jjxo3s3LmTiIgI7S+1htqvNWmsuW5VXFzMa6+9ho+PD97e3kD5adbMzEzs7e3JzMzExsamgVPeQ6etrl27RlBQEG+88Qa9e/fWTre3t8fKyoqjR4+iKAoxMTF4eno2YFLw8PBg8+bNFBUVkZ6eztmzZ+nWrRsPP/wwZ8+eJT09naKiIjZv3oyHh0eDZLS3t+fgwYMA/PrrrzzwwAPa7DExMSiKwtGjR2nWrJn2cLshDR06lAMHDgDw559/UlxcTMuWLavc1w2lc+fO/PLLLyQkJJCQkECrVq3YuHEjdnZ2jXLf7t69m2+++YalS5ei0Wi00xvbfr2pMf0M6aIoCrNnz6ZDhw4EBgZqp9/83gON4ncU3IVDsm/fvp3/+7//Izs7m+bNm+Pq6sry5cv56quvCA8Pp127dtq2K1aswNbWluTkZN5++23+/vtv3N3dee+99+7IYWFVWaH8NMCGDRtQq9W88847DB48GIBdu3axYMECSktLeeKJJ3jppZfqPacuhw8fZsGCBZSUlGBhYcGcOXN46KGHUBSFuXPnsmfPHjQaDQsWLODhhx9ukIy3Kioq4p133uHkyZOYmZkxa9Ys3NzcgKr3dWPg4eFBdHQ0NjY2jXLfenl5UVRUhLW1NQDdu3dn7ty5QOPdr43lZ0iXw4cP89xzz+Hi4oKJSfnf9q+//jrdunUjODiYS5cu0bp1a0JDQ7X7vKHcdcVDCCFE/btnTlsJIYS4faR4CCGE0JsUDyGEEHqT4iGEEEJvUjyEEELoTYqHEEIIvRnlE+ZC3AlXr14lICAAgCtXrmBiYoKNjQ1paWn4+vrywQcf1Mt6jx49yvz58ykqKqKoqIiRI0fy6quvcuDAAczMzOjVq1e9rFcIfchzHkLUwpIlS2jSpAmTJ0+u93UNGzaMzz77jC5dulBaWsqff/6Js7PzHc0gRE3kyEMIPR04cIAVK1awbNkylixZwvnz50lPT+fSpUu8/fbbHD16lD179mBvb09YWBhmZmYcP36cjz76iPz8fFq2bMnChQurHFokOzsbOzs7ANRqNc7Ozpw/f561a9diYmLC999/z3vvvUeHDh2YM2cOFy9eBMpHOu7duzdLliwhLS2NtLQ0rl69ygsvvMD48ePv2P4R9wYpHkIYKC0tjVWrVpGamspTTz3F559/zqxZs3jllVfYtWsXgwcPZt68eXz11VfY2Njw008/8emnn7Jw4UKd/fn7+zN8+HD69u3LoEGDGDNmDPfffz9PP/10hSOPN954A39/f/r06cPFixeZPHkyW7ZsAcoHWFy3bh35+fmMGTOGwYMHN7oBAIVxk+IhhIHc3d0xMzPDxcWF0tJS7TstXFxcOH/+PH/++Sd//PGHdqC7srIy7ZGFLtOmTWP06NHs3buXH3/8kc2bN7N69epK7fbv38+ZM2e0n/Py8rQv6PL09MTS0hJLS0v69etHcnKyFA9xW0nxEMJAN99OaGJigpmZmXZQTRMTE0pLS1EUhU6dOvHdd9/Vus+2bdvy7LPPMn78eNzc3Lh69WqlNmVlZaxbtw4LC4tK8xrD+x7E3U1u1RWinrVv357s7GySkpKA8vc1nD59usr2O3fu5OZ9LOfOncPExITmzZvTtGlT7ZEFlL8C9tYjkhMnTmi/jo+Pp7CwkKtXr3Lw4MEGH31X3H3kyEOIemZubs7nn3/OvHnzuH79OqWlpfj7+9OpUyed7WNjY1m4cCGWlpao1Wo+/vhj1Go1jz32GK+99hrx8fG89957zJ49m7lz5+Lj40NpaSl9+vTRDofeuXNnJk6cyNWrV3n55ZfllJW47eRWXSHuMnJLr7gT5LSVEEIIvcmRhxAN5MMPPyQxMbHCtIkTJ/LEE080UCIhak+KhxBCCL3JaSshhBB6k+IhhBBCb1I8hBBC6E2KhxBCCL39P3FZ8DXeCDnVAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Lu7m2Rr4AbMK",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "e0d07c10-c644-4a91-8723-5fc94e35c3a5"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "fjXexah9C8yg",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8e521731-9e70-48b3-b630-44adc32f93fb"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "7mtLZ6S-DPU-",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "outputId": "c6ae5f81-b61d-47e6-cd05-f96a5658ae2d"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "eaIjVnzCJwCS"
-      },
-      "source": [
-        "Bi-directional LSTM:\n",
-        "On some sequence prediction problems, it can be beneficial to allow the LSTM model to learn the input sequence both forward and backwards and concatenate both interpretations. This is known as bidirectional.\n",
-        "\n",
-        "Here, `tf.keras.layers.Bidirectional` is a bidirectional wrapper for RNNs which inherits from `Wrapper`, `Layer`, and `module`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "snN_Flr5DWQN",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "be27d60a-53b9-4e83-f1e3-45bf9b751196"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:])))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 54s 946ms/step - loss: 0.1534 - rmse: 0.2114 - val_loss: 0.0481 - val_rmse: 0.0489\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 46s 917ms/step - loss: 0.0785 - rmse: 0.0995 - val_loss: 0.0406 - val_rmse: 0.0412\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 46s 916ms/step - loss: 0.0619 - rmse: 0.0781 - val_loss: 0.0095 - val_rmse: 0.0100\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 46s 919ms/step - loss: 0.0526 - rmse: 0.0661 - val_loss: 0.0170 - val_rmse: 0.0172\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 46s 915ms/step - loss: 0.0466 - rmse: 0.0584 - val_loss: 0.0077 - val_rmse: 0.0080\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0421 - rmse: 0.0529 - val_loss: 0.0325 - val_rmse: 0.0326\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 47s 937ms/step - loss: 0.0390 - rmse: 0.0489 - val_loss: 0.0140 - val_rmse: 0.0141\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 47s 936ms/step - loss: 0.0365 - rmse: 0.0458 - val_loss: 0.0085 - val_rmse: 0.0086\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 47s 935ms/step - loss: 0.0342 - rmse: 0.0429 - val_loss: 0.0196 - val_rmse: 0.0196\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 46s 927ms/step - loss: 0.0325 - rmse: 0.0406 - val_loss: 0.0135 - val_rmse: 0.0136\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0308 - rmse: 0.0385 - val_loss: 0.0187 - val_rmse: 0.0187\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 45s 918ms/step - loss: 0.0297 - rmse: 0.0371 - val_loss: 0.0072 - val_rmse: 0.0074\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 46s 924ms/step - loss: 0.0281 - rmse: 0.0352 - val_loss: 0.0015 - val_rmse: 0.0018\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 46s 922ms/step - loss: 0.0269 - rmse: 0.0336 - val_loss: 0.0153 - val_rmse: 0.0154\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 46s 920ms/step - loss: 0.0257 - rmse: 0.0323 - val_loss: 0.0049 - val_rmse: 0.0050\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 45s 905ms/step - loss: 0.0252 - rmse: 0.0315 - val_loss: 0.0031 - val_rmse: 0.0033\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 45s 907ms/step - loss: 0.0239 - rmse: 0.0299 - val_loss: 0.0178 - val_rmse: 0.0178\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 45s 906ms/step - loss: 0.0230 - rmse: 0.0289 - val_loss: 0.0084 - val_rmse: 0.0085\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 45s 906ms/step - loss: 0.0224 - rmse: 0.0280 - val_loss: 0.0072 - val_rmse: 0.0072\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 45s 913ms/step - loss: 0.0216 - rmse: 0.0271 - val_loss: 0.0101 - val_rmse: 0.0101\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Ay5m27doDsTt",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "outputId": "74bc7df8-2315-401b-8cd8-d7632c14abb7"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6ZFP49W4D2wp",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "cdd29cbc-c26e-46d0-aaaf-0d2a8a4cb047"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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0HXNk1T5eXldQ8EAAB1ctlCr1oQNg1DRXGPVwmp9b1B0Piu1/TFV//kug7bbq/YnKaOko4qXwZcXKo11Va74laf67amepPypuidOGDAQB09elSZmZ9r5coV8vPz0/Hjx/XWW+u1YsUftWfPP1RaWqKHHhqvqKgYmaap//f/kvT3v/9NISGd1a7d97+yGTPiNWNGgm699TZ9+uknSk7+/2S3l8vf31/PPPOc0tPfkYeHhzZv/kAzZ85W9+436eWXF+vcuXOSpKeemqX+/QeqoCBfv/nNfH377be6445+akh3xqvnkJ+fryeemKS3335HK1euUElJsfbu/VKTJsXp2LGv5ePTQRMmTJIkTZoUq6Skir7os2bN0G233aFDhw7q5Zd/r4yMLcrI2KrS0hINHXqfHn/855a89wAAXE9cBmTTlL1buNONXSo3fVEDskDlarJv4kKnbfIMVWQqn7VvqeiRR+W9ZZPT53b2ZaDKtFtZbbUrhOurNHQr0IYqKyvTp59+oh/96MeSpMOHD+rPf/4fde0apvT0d+Tr66uVK/+skpISPfnk4xo8+C4dOXJIJ04c15o165WXl6uJE8crMnJslevm5eUpKSlRf/xjsrp2DdOFCwW64YZOGjcuukqg/c1v5is29lENGDBQZ8+e1a9+NUNvvbVBq1b9Sf37D9TUqdP0ySf/p7/+Nd3la3jqqZ/Lw8Omdu3a6U9/etPpmHbt2umJJ6br4MEDmjVrjiTp9ddfc3nNU6dOav78hbrjjn767LNPdfLkSf3pT2/KNE0988wsffFFpgYOvLNB7zUAANc7lxvFuOgJ7WwnxPo+j1TRVaS28ytrpl31o3b1ZcD8bs4ttRNjQxGur9JUvROLi4sVFzdBUsXK9YMPjlNW1pfq2/d2de0aJkn6+98/1dGjR/XRRxmSpMLCSzp16qS++GKPRo4cLZvNphtvDNadd/57jevv35+lAQMGOa51ww2dnM7j888/07FjXzt+Liws1OXLl/XFF3uUmFix/fyPf3yP/PxucPla/vCH1+Tv79+Id8G1zp276I47+kmSPvvsU/39759q6tRHJUlFRZd16tQJwjUAAA3kLOzWtvrrauW4+mYxVR5r107G5ULdGNpJ5WHdvl+ZdlHaUVumauiXgdaKcH2VhmwF2hCVNdfV+VxVd2SapmbOnK0f/WhIlTENrVuujWmW67XXVsnb29uya9psno466ZKS4lrG2WSa39dTl1zVXL59+/ZXzdHUxIlxioqKsWyOAABcj6psG+6kDKO62oJvZRmJ6R8gGZKRlyfTP0BG4SV55OZKqlr64ZPyutPSktoyVUO/DLRW3NB4FadN0pvplzp48BClpW1w3Nx44sRxFRUVaeDAQcrI2CK73a7z588rM/PzGufefns/ffnlHn3zzWlJ0oULBZKkDh18VVT0/Xbw//7vdyk19X8cPx85ckiSNHDgIG3Z8qGkijB/8eKFes+7S5cuOnTooCTpo4+2OY536NBBly9fvmpcVx0+XDHu0KGDOnPmG6fX+9GPhuj99991nPvtt9nKy8ut93wAAMD3GtJZw+UGLd+tHJ8/V6CcQ8eUc/CYzp8rkOnrW2MnRqOoSD5/XuV6u/TvVrmdNY0ojolt9W326oNwfZWW/KWOGROlm266RY899qgmTYrVSy8tlt1u19Ch96lbt3BNnDheixY97yifuFpAQIBmz56n+fNna8qUn+n55+dKku6++yfasWO74uIm6Msv9yghYbYOHvynpkx5RBMnjldaWqokaerUafryyz2aODFWO3ZsV2ho53rP+2c/m6S0tA2aOnVClfZ9d975bzp27GvFxU3Qtm2bNWzYcF24cEETJ8YqNfV/FB7e3en1Bg++SxER92v69KmaPPmnevbZOVVCOgAAaBp1LTLWu2e23e7yOTxyc6tsCuM7Z1aVa0py+WWgKTq6NQXDbEhriFautNSu/PyqQezs2ePq3LlHC80ITYXfKwAAdavs/lGfspDaxju72dE0DNcr1PWcX/WxppeXLv7+1RpzdPr8Pj4turIdHOzn9DjhGtckfq8AANTOykAaeOftTu9Lq2+Qbmjgrt4dxNXz21vwZkdX4ZqyEAAAgDbIVYthvyefcFpWUVvZRWM7p5mqCMBmYGC9z6nsi+036xeOOTRVR7emQLgGAABog1wFT2fh1dlW6Vc/3ujOaZXbqpuqsYNjXaUTRlGROs57uqIW20WhRWvcsfG6CNdtqPIF4vcJAEB91BU8KzfKk2rfSE9yfbNjXSvSpn+A/Gb9Qh55uY6yEFNSeWCgTF/fOl+DkZfrcjv01tqmr82Ha09PLxUWXiCQtRGmaaqw8II8Pb1aeioAALRqzgJxdZWr23WVXVTvqFYeECjTx0dGbq5Mw3k1tenjU9ETu3pol2R28NWll38vs127WufnNFRLrbpNX5u/odFuL1Ne3rcqKytxcRauNZ6eXgoICJbNxh5IAADUxtH9w8Xqb+UNgQ25YdBV5xCZpmSzSXa744ZEv/+c5rKjiAzj+01pvtuIxqg2xmm4NgydP1dQ52tvatdttxAAAIDrXV2dQ1w97tjO/KrWfL6JC+sdxF2F9quZPj4yfXwcOz3Wxf5dcG9Ii8GmQLgGAAC4jtXV87r648URo+Wz9i2nK9T1XVF2FtqdqXdLP8NQUdzjNefVAj2vCdcAAABwylnwdrVC7SoIu+o5ffW1XQZzF9d0Nq68W3ir6HlNn2sAAIDrVG09rF214XO1vbkh1biJsbbOHcUxsY4tzcu7hTsdY353g2RdyruFu5xXa+l5TbgGAABow1yFZ985sxR45+3ye/IJp234ZLO5vqhpytT3bfVqK8m4OtgbhYUyvap2/DJ9fHRpcZIuvvLfFV1IXD2lj4+KI0ZLLrqTtJae14RrAACANsxVD2uflNdd9pCWJNntLoOucfV/tdRTVw/2Hnm5kmlW9Lk2jCot9YpjYmX6+jovG7HZdPGV/5b3lk3Ou49UblbTClBzDQAA0IbdGNrJaSC1kqt654a0+JNcz7XyZkmXj0s6n32hcZNvJGquAQAArkNWlUtUloE4U9cmNLUdv7psRB7Oo2nla3D1WlzVcrcEwjUAAEAb5nTrchd1y7UyDJch1mXoreN49bIRw0kpytU3S7rahr21lIRIhGsAAIA2rfrW5fZu4SqKe7xe3TmuVtn7uiGdQuoKw07rwVVRY+2Y6yOPyjdxoW4M7STfxIUqeuTRKq+ltW2DTs01AADAdaiurdGvVrlbo7NNZYriHlfh0lfqfp5qm9d4p66r6FTi7Pm+q7Gua2fJlsQmMgAAANehq8Ot6R8gGZKRl1f3ZjE2m1Re3qhtz+szp9p2bqy8ZkNviGxOhGsAAIDrTF0h1uWKtJPV4bo6eTSEq9Bc/bmtfE6r0S0EAADgOuOspvlqRlGRvLdsqlGT7azsoqE3LbrinbrO5S6LplTluV1e2zRr7DTZWhCuAQAA2qj6bAnuceqk05ro6qzo1OFYSXfxeHm38CrP7ew5pYqbHit3mmxtAZtwDQAA0EbVa1XZMGpsje4ssDrrOtLQGwtrW0l3FtSrPKezqRcVyTdxYb2fvzlQcw0AANBG1VlzLTldRW6qGwZr22Hx4vKVtQb11lZ/Tc01AADAdaZy5de02Rp0Xn3KSaq7eqdFV/XQrlbSzYDAOlfArar5bmqEawAAgDasOCZWKi9v0DmNuUnx6p0WXZWXFM5fILNduxrnG4WX6qydvhZ2Z5QI1wAAAG1ebSvGVgRWpzstOqmHLo6JlelXs5zCKCmps3baiprv5kDNNQAAQBtX206HkurVLaQ2DamHbm21041FzTUAAMB1qrZV3+KYWOVm7tf5cwWOmxjrqp2uriH10NdK7XRjEa4BAACuA9VDtLPV6frWTlfXkHroa6V2urHcCtf5+fmaOnWqRo0apalTp6qgwPlSft++fTVu3DiNGzdO06dPdxyfN2+exo4dqzFjxuipp55SYWFhlfM2bdqkPn36KCsry51pAgAAoB7qWztdXUPqoa+V2unGcqvmOikpSf7+/oqPj1dycrIKCgo0e/bsGuMGDRqkPXv21Dh+6dIldezYUZK0ZMkSBQUFKT4+3vHYz3/+c5WWluq5555Tv3796pwPNdcAAACN11bqoZtDk9Rcb9u2TVFRUZKkqKgobd26tUHnVwZr0zR15cqVKo/9/ve/17Rp0+Tt7e3OFAEAAFBPbb0eujm4Fa5zcnIUEhIiSQoODlZOTo7TccXFxYqOjlZsbGyNAD537lzdfffd+te//qVJkyZJkvbv36+zZ89q2LBh7kwPAAAAtai+8UvZLT1rbDNuSiqOGN0S07smedY1IC4uTufPn69xPCEhocrPhmHIMJxtoClt375doaGhOnnypKZMmaLevXure/fukirKQex2u1588UVt3LhRDz30kH77299qyZIljXk9AAAAqIfq7flsp07K4/SpGtuhG5K8t2xS4dJmn+I1qc5wnZKS4vKxoKAgZWdnKyQkRNnZ2QoMDHQ6LjQ0VJIUHh6uwYMH68CBA45wLUk2m02RkZFauXKlRo0apcOHD2vy5MmSpG+//VZPPvmkli9fXq+6awAAANTN6c2LLm7Fa8x26Ncrt8pChg8frrS0NElSWlqaRowYUWNMQUGBSkpKJEm5ubnKzMxUr169ZJqmjh8/Lqmi5jojI0O33HKL/Pz89Le//U0ZGRnKyMjQwIEDCdYAAAAWa0hgpua6/upcua5NfHy8EhIStGHDBnXt2lXLli2TJGVlZWnt2rVKTEzUV199pQULFsgwDJmmqWnTpqlXr14qLy/XnDlzVFhYKNM01adPHy1cWHubFwAAAFijPKybbKdO1jhuGkaVFey21IO6ObD9OQAAwHXI1ZboRY88Ku8tm9zaDv164KoVH+EaAADgOuWduk6+iQsJ0o1AuAYAAAAs0iSbyAAAAAD4HuEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwiKc7J+fn52vmzJk6ffq0wsLCtGzZMnXq1KnGuL59+6p3796SpC5dumjFihWSpHnz5mnfvn0yTVM333yzlixZIl9fX0nSxo0b9cc//lGGYejWW2/V7373O3emCgAAADQ5wzRNs7EnJyUlyd/fX/Hx8UpOTlZBQYFmz55dY9ygQYO0Z8+eGscvXbqkjh07SpKWLFmioKAgxcfH69ixY0pISNCbb76pTp06KScnR0FBQXXOp7TUrvz8y419OQAAAEC9BAf7OT3uVlnItm3bFBUVJUmKiorS1q1bG3R+ZbA2TVNXrlxxHF+3bp0effRRxyp4fYI1AAAA0NLcCtc5OTkKCQmRJAUHBysnJ8fpuOLiYkVHRys2NrZGAJ87d67uvvtu/etf/9KkSZMkSceOHdPXX3+tRx55RLGxsdqxY4c70wQAAACaRZ0113FxcTp//nyN4wkJCVV+NgxDhmE4vcb27dsVGhqqkydPasqUKerdu7e6d+8uqaIcxG6368UXX9TGjRsVExMju92u48ePa/Xq1Tp79qwmTpyo9957TzfccENjXiMAAADQLOoM1ykpKS4fCwoKUnZ2tkJCQpSdna3AwECn40JDQyVJ4eHhGjx4sA4cOOAI15Jks9kUGRmplStXKiYmRqGhoRowYIDatWun8PBw3XTTTTp27Jj69+/fwJcHAAAANB+3ykKGDx+utLQ0SVJaWppGjBhRY0xBQYFKSkokSbm5ucrMzFSvXr1kmqaOHz8uqaLmOiMjQ7fccoskaeTIkfrss88c5xw7dkzh4eHuTBUAAABocm51C8nLy1NCQoLOnGbBQUQAABPNSURBVDmjrl27atmyZfL391dWVpbWrl2rxMREZWZmasGCBTIMQ6ZpavLkyRo/frzKy8s1YcIEFRYWyjRN9enTRwsXLlTHjh1lmqZ++9vfaufOnbLZbJo+fboiIyPrnA/dQgAAANAcXHULcStctzaEawAAADSHJmnFBwAAAOB7hGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKe7pycn5+vmTNn6vTp0woLC9OyZcvUqVOnGuP69u2r3r17S5K6dOmiFStWSJLmzZunffv2yTRN3XzzzVqyZIl8fX31zTffaM6cObp48aLsdrt+/etf695773VnqgAAAECTM0zTNBt7clJSkvz9/RUfH6/k5GQVFBRo9uzZNcYNGjRIe/bsqXH80qVL6tixoyRpyZIlCgoKUnx8vJ577jn17dtXEyZM0NGjRxUfH6+MjIw651Naald+/uXGvhwAAACgXoKD/Zwed6ssZNu2bYqKipIkRUVFaevWrQ06vzJYm6apK1euOI4bhqFLly5Jki5evKiQkBB3pgkAAAA0C7fKQnJychzBNzg4WDk5OU7HFRcXKzo6Wp6enoqPj9fIkSMdj82dO1cff/yxevbsqWeeeUaSNGPGDD3++ONas2aNioqKtGrVKnemCQAAADSLOsN1XFyczp8/X+N4QkJClZ8Nw5BhGE6vsX37doWGhurkyZOaMmWKevfure7du0uqKAex2+168cUXtXHjRsXExOj999/XQw89pMcee0x79uzR008/rb/+9a/y8OD+SwAAALRedYbrlJQUl48FBQUpOztbISEhys7OVmBgoNNxoaGhkqTw8HANHjxYBw4ccIRrSbLZbIqMjNTKlSsVExOjDRs2aOXKlZIq6rWLi4uVl5enoKCghrw2AAAAoFm5tRQ8fPhwpaWlSZLS0tI0YsSIGmMKCgpUUlIiScrNzVVmZqZ69eol0zR1/PhxSRU11xkZGbrlllskVXQU2b17tyTpq6++UnFxscvgDgAAALQWbnULycvLU0JCgs6cOaOuXbtq2bJl8vf3V1ZWltauXavExERlZmZqwYIFMgxDpmlq8uTJGj9+vMrLyzVhwgQVFhbKNE316dNHCxcuVMeOHXX06FE9++yzunz5sgzD0OzZs3XPPffUOR+6hQAAAKA5uOoW4la4bm0I1wAAAGgOTdKKDwAAAMD3CNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARQjXAAAAgEUI1wAAAIBFCNcAAACARdwK1/n5+Zo6dapGjRqlqVOnqqCgwOm4vn37aty4cRo3bpymT59e4/FFixZp0KBBjp9LSkqUkJCgiIgIjR8/XqdOnXJnmgAAAECzcCtcJycna8iQIdq8ebOGDBmi5ORkp+Pat2+v9PR0paena8WKFVUey8rKqhHK169frxtuuEFbtmxRXFycXn75ZXemCQAAADQLt8L1tm3bFBUVJUmKiorS1q1bG3S+3W5XUlKSZs+eXeV4RkaGHnroIUnS6NGjtXv3bpmm6c5UAQAAgCbnVrjOyclRSEiIJCk4OFg5OTlOxxUXFys6OlqxsbFVAviaNWs0YsQIxzUqnTt3Tl26dJEkeXp6ys/PT3l5ee5MFQAAAGhynnUNiIuL0/nz52scT0hIqPKzYRgyDMPpNbZv367Q0FCdPHlSU6ZMUe/eveXt7a0PP/xQq1evbuTUAQAAgNalznCdkpLi8rGgoCBlZ2crJCRE2dnZCgwMdDouNDRUkhQeHq7BgwfrwIEDat++vU6cOKFRo0ZJkoqKihQREaEtW7YoNDRUZ86cUefOnVVWVqaLFy8qICCgES8PAAAAaD5ulYUMHz5caWlpkqS0tDSNGDGixpiCggKVlJRIknJzc5WZmalevXpp2LBh2rVrlzIyMpSRkSEfHx9t2bLFcd3//d//lSRt2rRJd911l8tVcQAAAKC1cCtcx8fHa9euXRo1apQ++eQTxcfHS6roADJ//nxJ0ldffaWYmBiNHTtWU6ZM0bRp09SrV69ar/vwww8rPz9fERERWrVqlX7961+7M00AAACgWRhmG2rDUVpqV37+5ZaeBgAAANq44GA/p8fZoREAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALCIpzsn5+fna+bMmTp9+rTCwsK0bNkyderUqca4vn37qnfv3pKkLl26aMWKFVUeX7RokVJTU7Vnzx5J0qpVq7R+/XrZbDYFBgZq8eLFCgsLc2eqAAAAQJNza+U6OTlZQ4YM0ebNmzVkyBAlJyc7Hde+fXulp6crPT29RrDOyspSQUFBlWN9+/ZVamqq3nvvPY0ePVovvfSSO9MEAAAAmoVb4Xrbtm2KioqSJEVFRWnr1q0NOt9utyspKUmzZ8+ucvyuu+6Sj4+PJGngwIE6e/asO9MEAAAAmoVb4TonJ0chISGSpODgYOXk5DgdV1xcrOjoaMXGxlYJ4GvWrNGIESMc13Bmw4YNGjp0qDvTBAAAAJpFnTXXcXFxOn/+fI3jCQkJVX42DEOGYTi9xvbt2xUaGqqTJ09qypQp6t27t7y9vfXhhx9q9erVLp87PT1d+/bt05o1a+qaJgAAANDi6gzXKSkpLh8LCgpSdna2QkJClJ2drcDAQKfjQkNDJUnh4eEaPHiwDhw4oPbt2+vEiRMaNWqUJKmoqEgRERHasmWLJOmTTz7RihUrtGbNGnl5eTX0dQEAAADNzq2ykOHDhystLU2SlJaWphEjRtQYU1BQoJKSEklSbm6uMjMz1atXLw0bNky7du1SRkaGMjIy5OPj4wjWBw4c0PPPP6/ly5crKCjInSkCAAAAzcYwTdNs7Ml5eXlKSEjQmTNn1LVrVy1btkz+/v7KysrS2rVrlZiYqMzMTC1YsECGYcg0TU2ePFnjx4+vca1BgwY5WvHFxcXp8OHDCg4OluS8fZ8zpaV25edfbuzLAQAAAOolONjP6XG3wnVrQ7gGAABAc3AVrtmhEQAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALCIZ0tPAAAAAE1jzhxvpaS0k2m29Eyajq+v9PLLVxQTU9bSU5FEuAYAAGiT5szx1qpV7SQZLT2VJlVYKM2Y0V5S6wjYhmm2ne8ypaV25edfbtbnvHilTM9/cFAFRaXN+rwAAADORA/oogdv76wuXTrKbm/bwfpq3bqVKzOzsNmeLzjYz+lxVq7dZBiSr5dNZfY28x0FAABcw7w9bZIku72FJ9LMTp9uHV8kCNdu6ujtqUWRfVt6GgAAAFXYbNdXwA4Lax0LnXQLAQAAaIMmTy6V1DoCZ1Oz2UzNn1/c0tOQxMo1AABAm7R0aUXYpFtI8+KGRgAAAKCBXN3QSFkIAAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYJE2tf05AAAA0JJYuQYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuG6gDz74QJGRkbr11luVlZXlOL5r1y5FR0drzJgxio6O1u7dux2P7du3T2PGjFFERIQWLVokuh/Wn6v3W5Jee+01RUREaPTo0dq5c6fj+I4dOzR69GhFREQoOTm5uafcpvzzn/9UbGysxo0bp+joaO3du1eSZJqmFi1apIiICI0ZM0b79+9v4Zm2HatXr9b999+vyMhIJSUlOY67+rzDGm+88Yb69Omj3NxcSXzGm8rSpUt1//33a8yYMfqv//ovXbhwwfEYn/Gmwd+JLcBEgxw9etT86quvzIkTJ5p79+51HN+/f7959uxZ0zRN89ChQ+Y999zjeCwmJsbcs2ePWV5ebj7++OPmRx991Ozzvla5er+PHDlijhkzxiwuLjZPnDhhjhgxwiwrKzPLysrMESNGmCdOnDCLi4vNMWPGmEeOHGnBV3Btmzp1quPz+tFHH5kTJ050/Pnxxx83y8vLzT179pgPP/xwS06zzdi9e7c5ZcoUs7i42DRN0zx//rxpmq4/77DGN998Yz722GPmsGHDzJycHNM0+Yw3lZ07d5qlpaWmaZpmUlKSmZSUZJomn/Gmwt+JLYOV6wbq2bOnbrnllhrHb7vtNoWGhkqSfvCDH6i4uFglJSXKzs7WpUuXNHDgQBmGoaioKG3btq25p33NcvV+b9u2TZGRkfLy8lJ4eLh69OihvXv3au/everRo4fCw8Pl5eWlyMhI3m83GIahwsJCSdLFixcVEhIiqeL9j4qKkmEYGjhwoC5cuKDs7OyWnGqb8Pbbbys+Pl5eXl6SpKCgIEmuP++wxpIlSzR79mwZhuE4xme8adxzzz3y9PSUJA0cOFBnz56VxGe8qfB3YssgXDeBTZs26bbbbpOXl5fOnTunzp07Ox7r3Lmzzp0714Kzaxuqv6+hoaE6d+6cy+NonHnz5ikpKUn33nuvli5dqlmzZkmq+f7zubbGsWPH9Pnnn2v8+PGaOHGiI1zwuW46W7duVUhIiG699dYqx/mMN73U1FQNHTpUEp/xpsL72jI8W3oCrVFcXJzOnz9f43hCQoJGjhxZ67lHjhzRyy+/rDfeeKOpptfmuPN+w321vf+ffvqp5s6dq9GjR2vjxo2aP3++UlJSmn+SbUht77fdbldBQYHWrVunrKwsJSQksMpkgdre89dee43/v7ZYff4/ffny5bLZbBo7dmxzTw9ocoRrJxobHs6ePasZM2Zo6dKl6t69u6SKb4mV/+xVOaayfAQVGvN+V39fz50753hfXR2Hc7W9/3PmzNH8+fMlSQ888ICeffZZSXyu3VHb+/32228rIiJChmGof//+8vDwUF5eXq2fd9TN1Xt+6NAhnTp1SuPGjZNU8TmOjo7W+vXr+Yy7oa7/T3/nnXf00UcfKSUlxVGKw2e8afC+tgzKQixy4cIFxcfH61e/+pV++MMfOo6HhISoY8eO+uKLL2SaptLS0jRixIgWnGnbMHz4cL3//vsqKSnRyZMndezYMfXv31/9+vXTsWPHdPLkSZWUlOj999/X8OHDW3q616yQkBB99tlnkqRPP/1UN910k6SK9z8tLU2maeqLL76Qn5+fox4bjTdy5Ej97W9/kyR9/fXXKi0tVUBAgMvPO9zTp08f7d69WxkZGcrIyFDnzp31zjvvKDg4mM94E9mxY4dWrlyp5cuXy8fHx3Gcz3jT4O/ElmGYJn3hGmLLli168cUXlZubqxtuuEF9+/bV66+/rldffVXJycnq0aOHY+wbb7yhoKAgZWVlae7cubpy5YqGDh2q5557rsqNM3DN1fstVfyzYmpqqmw2m+bNm6d7771XkvTxxx9r8eLFstvtiomJ0ZNPPtmSL+Ga9vnnn2vx4sUqKyuTt7e3FixYoDvuuEOmaeqFF17Qzp075ePjo8WLF6tfv34tPd1rXklJiebNm6eDBw+qXbt2evrppzVkyBBJrj/vsM7w4cO1YcMGBQYG8hlvIhERESopKZG/v78kacCAAXrhhRck8RlvKvyd2PwI1wAAAIBFKAsBAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACzy/wPhbNRrIjkuDgAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "befefa8a-e8e1-4147-d23f-db668c092471"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 132s 186ms/step - loss: 0.0101 - rmse: 0.0102\n",
-            "MAE: 0.010171186178922653\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YXcsNZ8yu9Ay"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "uCFgbZEOvZ9A"
-      },
-      "source": [
-        "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
-        "\n",
-        "plt.figure(figsize=(10,5))\n",
-        "plt.plot(y_pred_test)\n",
-        "plt.plot(y_val_multi)\n",
-        "plt.ylabel(\"Value\")\n",
-        "plt.xlabel(\"Timestap\")\n",
-        "plt.legend(loc='upper left')\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "dHPRJUt4aXoq"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 521
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "87e645f2-f2f9-4e8e-e0b9-fd807224892a"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "747e6ee9-2da1-43af-c751-1261f54d6c2c"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "46U0FXYB6AbD"
+   },
+   "source": [
+    "We showed here the histograms of Ellis data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "eeead93b-89b4-4798-976c-1b065bbbc4a3"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "c3ac6c2e-c7f3-48ae-c562-23bb7b60c5b4"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "d553c7b1-3a00-40dd-ad5f-cc695d3ecbae"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9jTOMzOqEQEZ"
+   },
+   "source": [
+    "## Identifying trends in Time Series data\n",
+    "There are several ways to think about identifying trends in time series. One popular way is by taking a rolling average, which means that, for each time point, we take the average of the points on either side of it. Note that the number of points is specified by a window size, which we need to choose.\n",
+    "\n",
+    "What happens then because we take the average is it tends to smooth out noise and seasonality. We will see that below right now. Check out this rolling average of `'ellis-cpu.wait_perc'` using the built-in `pandas` methods.\n",
+    "\n",
+    "When it comes to determining the window size, here, it makes sense to first try out one of twelve months, as we're talking about yearly seasonality.\n",
+    "\n",
+    "Note that in the code chunk above we used two sets of squared brackets to extract the `'ellis-cpu.wait_perc'` column as a DataFrame; If we would have used one set, like `df_Ellis['ellis-cpu.wait_perc']`, we would have created a pandas Series.\n",
+    "\n",
+    "In the code chunk above, you also chained methods: you called methods on an object one after another. Method chaining is pretty popular and pandas is one of the packages that really allows you to use that style of programming to the max!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "c8f8cd9a-8477-46b9-e350-9b501f8bf55b"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JKNmf5TeFvQt"
+   },
+   "source": [
+    "We have successfully removed the seasonality and we saw an upward trend for `ellis-cpu.wait_perc`! But how do these two search terms compare?\n",
+    "\n",
+    "We can figure this out by plotting the trends of `'ellis-cpu.wait_perc'`, `cpu_system_perc` and `'load_avg_1_min'` on a single figure:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "02683682-38ad-4745-c7bb-99a9058bb755"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PTkbQPa_6MNb"
+   },
+   "source": [
+    "We established the correlation matrix for Ellis data.\n",
+    "Seaborn has five built-in themes to style its plots: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`. Seaborn defaults to using the darkgrid theme for its plots, but we can change this styling to better suit our presentation needs.\n",
+    "\n",
+    "To use any of the preset themes pass the name of it to `sns.set_style()`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "6e2c3c3c-5a69-42ef-87a8-7dfdd65e7ceb"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tdg8lD0OHEtH"
+   },
+   "source": [
+    "Correlation between rows or columns of two DataFrame objectsCompute pairwise"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "ab6efc64-5329-4ad2-e5a8-acecf7c79eff"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "3e1fc354-aefb-496b-9e08-d05a458f9c23"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "a8c2999d-5fd1-4de3-f8fd-05cd6ff14622"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Q23ry_WpH6tt"
+   },
+   "source": [
+    "train test split for simple time series moving window average"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "6375471f-a7ec-4416-95e0-4f9a82872168"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "22Y4ztlZIpFG"
+   },
+   "source": [
+    "Created multivariate data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "3f2a841e-eec2-4cf9-e370-4ab5a8bcc725"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MMSskyxNaMj3"
+   },
+   "source": [
+    "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
+    "- Creating a source dataset from our input data.\n",
+    "- Applied dataset transformations to preprocess the data.\n",
+    "- Iterate over the dataset and process the elements.\n",
+    "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
+    "Once we have a dataset, we can apply transformations to prepare the data for our model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "719a1cea-6548-4597-fc05-b183cc485387"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "IN6IQykaEzcF",
+    "outputId": "f7877fba-a745-4f3e-f654-c8cdeed5181e"
+   },
+   "outputs": [],
+   "source": [
+    "x_train_ss.shape[-2:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "004c1521-5b4c-4304-fa58-76bd01a9dcca"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "from keras.utils.vis_utils import plot_model\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:])))\n",
+    "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "#single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "\n",
+    "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Bi-LSTM.png', show_shapes=True, show_layer_names=True)\n",
+    "single_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "rePzISUuFmlM"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "90d76f79-4228-4f67-ef58-eb0c6f9e9390"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "16fab4ff-15d9-424a-a599-6f03e1ad0e8b"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "d0dc9e7a-bc96-4f19-815f-da9ed8a82408"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "e0d07c10-c644-4a91-8723-5fc94e35c3a5"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "8e521731-9e70-48b3-b630-44adc32f93fb"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "c6ae5f81-b61d-47e6-cd05-f96a5658ae2d"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "eaIjVnzCJwCS"
+   },
+   "source": [
+    "Bi-directional LSTM:\n",
+    "On some sequence prediction problems, it can be beneficial to allow the LSTM model to learn the input sequence both forward and backwards and concatenate both interpretations. This is known as bidirectional.\n",
+    "\n",
+    "Here, `tf.keras.layers.Bidirectional` is a bidirectional wrapper for RNNs which inherits from `Wrapper`, `Layer`, and `module`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "be27d60a-53b9-4e83-f1e3-45bf9b751196"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:])))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "74bc7df8-2315-401b-8cd8-d7632c14abb7"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "cdd29cbc-c26e-46d0-aaaf-0d2a8a4cb047"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "befefa8a-e8e1-4147-d23f-db668c092471"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YXcsNZ8yu9Ay"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "uCFgbZEOvZ9A"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
+    "\n",
+    "plt.figure(figsize=(10,5))\n",
+    "plt.plot(y_pred_test)\n",
+    "plt.plot(y_val_multi)\n",
+    "plt.ylabel(\"Value\")\n",
+    "plt.xlabel(\"Timestap\")\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "Bi-LSTMstacked-LSTM_Correlation.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/CNN.ipynb b/models/failure_prediction/jnotebooks/CNN.ipynb

index c43b840..566f36f 100644 (file)
--- a/models/failure_prediction/jnotebooks/CNN.ipynb
+++ b/models/failure_prediction/jnotebooks/CNN.ipynb
@@ -1,1406 +1,800 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ywp6YMCFQKEQ"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "CNN.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "21d3bdb5-0ac2-44a6-90ec-a3f2677014c4"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ywp6YMCFQKEQ"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "21d3bdb5-0ac2-44a6-90ec-a3f2677014c4"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "b6f5691d-1e76-43a4-de55-3156dbc02b4d"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 35
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "ed2f1595-c32c-43eb-ae2f-b5fce96e9a92"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5b0e04f8d0>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 36
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "63f0c61a-8a5a-41af-cbec-42fe0625b4d1"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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LBhZunSpebcuXPmv//9rwkLCzOpqalVriumTJli/vrXv5ri4mKTn59vvvjiiwr39/jjj5vu3bub3bt3m8LCQjN16lQzefJkY4wxp0+fNn379jVr1641hYWFZu/evaZ79+5m//799nX//Oc/V7jt8mIcMGCAOXDggDl79qy57777zB//+MfLHo+SbUyZMsWcPn3afPvtt6ZHjx7m448/NsYYM3bsWPPGG2/Yl1+wYIGZO3euMcaYdevWmXvuuafU9hYsWGAeeughc+LECXPq1Cnz0EMPmcWLFxtjjFm8eLF5+umnTUFBgSkoKDBffPGFOX/+fIWx/fjjj6Zv374mMzPTHuvBgweNMca8/vrrJjY21hw7dsycO3fOPP3002bKlCnGGGMOHz5sunbtat59911TUFBgjh8/br755pvLHgcAaEj1w4EDB0xgYKBJS0szBQUFJiEhwdxxxx3m3LlzxhhjbrzxRpORkVEqlpLtlfzGr4oXX3zR/OpXvzLvv/++KSgoMCtXrjT9+/c3BQUFxhhj3nvvPZOZmWmKi4tNUlKSCQwMNDabzT4vNDTU7N6925w/f95kZGSYw4cPG2OM6d+/v/n444/Nnj17TL9+/cyWLVuMMcbs3bvX9OzZ0+zatcsUFRWZ9evXm/79+9vLVbJeiTfffNM89NBD5syZM6aoqMh8/fXX5tSpUxWW5/Tp0yYoKMj8+OOPxhhjbDab+f77740xxnz44YfmjjvuMD/88IMpLCw0f/nLX8zIkSONMcacOnXKhISEmFdeecXk5+ebU6dOmV27dlXpGMJxtGRCrTl//rwmTJigm266SampqVq1apVWrVql7du3V3kbL7zwgkJCQvTFF18oNTVV991332WXf//99zV58mR9+umnatasmUaOHKmAgAB9+umnGjhwoJ555pkqx1aSlf/iiy908803a8yYMTp//rxSU1M1adIkzZw5s9wYNm/erHbt2mnFihXauXOnmjVrJknauHGj5s2bp3//+99q27atRo8erSFDhuiTTz7R888/rzlz5uiHH36QJC1evFj/+c9/lJiYqOTkZGVlZekvf/lLpcfr559/1rlz55Samqr4+Hg99dRTeuedd7Ru3Tq98cYb+utf/6pDhw7Zl09JSdGdd96pzz//XEOGDNHEiRNVWFhY6X4AoKZ8/fXXOn78uB5++GE1a9ZMHTp00N13321/Q1wVbm5uOnr0qLKystS8eXN7K56K3HHHHbr11lvl5uamu+66S/v27ZMkbd26Ve3bt9eIESPk5uamX/3qVxo4cKD+9a9/Vbt8w4cP1y9/+Uu1aNFCd955p31flZk0aZJatmypm266ScOHD7e/MR42bJj9LW5xcbGSkpI0dOjQcrdhjNHq1av15JNPysvLSx4eHnrooYeUlJQk6cJx++mnn3T06FE1bdpUwcHBslgsFcZktVpVUFCgH3/8UYWFhbr22mv1i1/8QpL01ltvacqUKfL391ezZs308MMP64MPPlBRUZE2bdqk3r17a8iQIWratKnatGmjm2++ucrHEEDj1JDqh/fee0/9+vVTSEiImjZtqjFjxig/P187d+6sclmqKiAgQHfeeaeaNm2quLg4FRQUaPfu3ZKkQYMGyc/PT02aNNHgwYPVsWNHpaenS7rQKmjs2LG69dZbZbFY1LFjR7Vv396+3S+//FITJkzQs88+q/79+0u60Ipr5MiRCgwMlNVq1bBhw9S0aVPt2rWr3Njc3NyUk5OjgwcPymq16pZbbpGHh8dly9OkSRPt379f+fn58vX1tfcWeeuttzRu3Dhdf/31cnNz0/jx47Vv3z4dOXJEW7du1dVXX63Ro0erefPm8vDwUGBgoMPHFlVDkgm1xhkVQ3h4uG655RY1b95c4eHhat68uaKjo2W1WjV48GB7RVGV2IKDg9WnTx+5ubnpzjvv1IkTJzRu3Dg1bdpUgwcP1pEjR3Ty5Mkql2XYsGHq3Lmz3NzctH379gorqsoeCio7XhMmTLDHeOLECT3wwAPy8PBQ586ddcMNN+i7776zL3+5SggA6sKRI0eUlZWl4OBg+38rVqyotPn8xaZNmyZjjGJiYhQZGam1a9dKklasWGHvXnDxi4Grr77a/neLFi105swZeyzp6emlYnn33Xf1008/Vbt8Pj4+9r/d3d3t+6rMNddcY/+7ffv2ysrKkiQNGDBAP/74ow4dOqSPP/5YHh4euvXWW8vdxvHjx3X27FkNHz7cXp6xY8fau9uNGTNGHTt21OjRozVgwAAlJCRcNqaOHTvqySef1NKlS9W7d29NmTLF3m3j6NGjmjRpkn0/gwcPVpMmTZSdna1jx47Zk1EAUFUNqX7IyspSu3bt7P9u0qSJrrnmmst2fasuf3//Uvvx8/Oz1yGJiYn2rm3BwcHav3+/vU6o7F791ltvKSgoSD169LBPO3r0qF577bVSxyUzM9O+v0sNHTpUoaGhmjp1qkJDQ/Xcc89d9gV3y5Yt9fzzz+utt95SaGioxo0bZ+9mePToUS1cuNC+3+7du8sYI5vNRr3jZAz8jVpzccVQori4WMHBwaVuspczbdo0vfDCC4qJiVHr1q0VFxenmJgYrVixQi+99JIkKSoqSnPnzpUkeXt729dt0aLFZSuKimIrcem22rRpY/9iUIsWLSRJZ86cUatWrapUlosfGC6uqC7e/1133VXqoaCEqeI4Tl5eXmVivLgczZs31+nTp+3/vlwlBAB14ZprrtG1116r5OTkMvOWLl1apW34+Pho/vz5ki68aY2Li1O3bt00fvz4CsfGqCiWbt266bXXXit3/uVa+dS0Y8eO6frrr5d04Ye0r6+vpAv38UGDBumdd97RgQMHSrViujS+Nm3aqEWLFkpKSpKfn1+ZfXh4eGj69OmaPn26vv/+ez344IPq0qWLevXqVWFcUVFRioqKUl5enmbOnKnFixfrj3/8o/z9/bVw4ULdfvvtZda55ppr7G/KAaCqGlL94Ovrq++//97+b2OMjh07Zr9echjWAAAgAElEQVQ3u7u76+zZs/b5P/30k33eldY9mZmZ9r/Pnz8vm80mX19fHTlyRE899ZRef/11BQUFyWq1lqpDrrnmmlJjUF1qzpw5evnll7Vw4UI9+eST9nXGjx+vCRMmVCm2pk2b6uGHH9bDDz+sw4cPa9y4cfrlL3+p2NjYCtfp06eP+vTpo/z8fC1ZskRPP/20/vnPf9r3fdddd5VZ5+jRo1fUsAE1i5ZMqDUlFcOXX35p/2/nzp16+eWXq7yNkoohLS1Nc+bM0Zw5c3Tw4EGNHz9eO3fu1M6dO+0JprqO7UpdXEGUVFSX7n/OnDmlHgpK5n311Ve10py2okoIAOrKrbfeqquuukoJCQnKz89XcXGxvv/++ytKSrz//vv2+1nr1q1lsVjUpMmV/8T59a9/rYyMDCUmJqqwsFCFhYVKT0+3vzX19vbW4cOHr3i71fHXv/5VZ8+e1f79+7V+/XoNHjzYPm/o0KHasGGDtmzZUuoBwdvbWzabTQUFBZIuvDyIjY3VwoULlZ2dLenCILolXcM/+ugjHTx4UMYYeXp6ymq1XvZh5sCBA9qxY4cKCgrUrFkzNW/e3H6c7733Xi1ZssQ+6Orx48e1efNmSRcSU5988onee+89FRUV6cSJE1XuNgig8WpI9cOgQYO0bds27dixQ4WFhXr11VfVrFkzBQUFSZL+7//+T5s2bVJxcbFSU1P1xRdf2Nf19vZWTk6OTp06VaVY9+7dq+TkZBUVFWnVqlVq1qyZAgMDdfbsWVksFrVt21bShQ9M7N+/375eTEyMXn31Ve3Zs0fGGB08eLDUQNpXXXWVVq5cqS+//FKLFy+WJMXGxuqtt97S7t27ZYzRmTNntHXrVuXl5Um60DLs4qE6Pv30U3333XcqLi6Wh4eH3NzcLns+fv75Z23evFlnzpxRs2bN1LJlS/vy99xzjxISEuxlOHXqlN5//31JF87XTz/9pNdff10FBQXKy8ujt0YdIsmEWuNKFUNtxOaIy1VUlT0U1KSKKiEAqCtWq1UrVqzQt99+qwEDBqhnz5566qmn7D9Qq+Lrr79WbGysgoKCNGHCBM2YMUMdOnS44lg8PDz0yiuv6L333lOfPn0UGhqqxYsX25M2MTEx+uGHHxQcHKyJEydKksaOHVsrX6zp3r27wsPDNWrUKI0ePVqhoaH2ebfffruaNGmigICAUuNl9OzZUzfccINCQ0Pt3RmmTZumjh076u6779Ztt92mUaNG6T//+Y+kC19diouLU1BQkEaOHKl7771XPXv2rDCmgoIC/elPf1KPHj0UGhqq48ePa+rUqZKkBx54QGFhYRo9erSCgoJ099132+vUdu3a6eWXX9Zrr72m7t27Kzo6utTXjgCgPA2pfujUqZP++Mc/at68eerZs6c++ugjrVixwj5264wZM/TRRx/Zu+Hdcccd9n1ff/31ioyM1B133KHg4OBKu9gNGDBA7733nrp166aNGzdq6dKlatq0qW644QaNHj1a99xzj3r37q3vv/9et912m329QYMGafz48Xr00Ud12223adKkScrNzS217VatWunVV19VamqqlixZoi5dumjevHmaO3euunXrpoiIiFJfDx03bpyWL1+u4OBgvfLKK/r5558VHx+v22+/XYMHD1b37t0rHFdQuvAS/PXXX1efPn3UvXt3ffHFF5o9e7akC8OkjB07VlOnTtVtt92mIUOGKDU11X6+Xn31VX300UcKCQnRwIED9dlnn132uKHmWIwxxtlBoOGy2Wx69tln9dlnn6mgoEC//OUvNXnyZH311Vc6ePCgFi9erMOHD2vAgAHau3ev3NzcdP/99+uuu+5SbGysnnvuOb377rvKy8uTt7e3fve732nkyJHl7mv69Ony8/PTlClTJElr1qzRO++8o7///e+SLvyYHjRokL755pvLxta7d28tXbrUHp8kffLJJ3rqqae0ZcsWSVJRU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jXe8JknV9/WlyQZuq8rzz9/YrJHm1Kz9bybnzTbM8o3M03GZ4szmQAAgJmg4cflAAAAAOA1SiYAAAAASlMyAQAAAFCakgkAAACA0pRMAAAAAJSmZAIAAACgNCUTAAAAAKUpmQAAAAAoTckEAAAAQGlKJgAAAABKUzIBAAAAUJqSCQAAAIDSlEwAAAAAlKZkAgAAAKA0JRMAAAAApSmZAAAAAChNyQQAAABAaUomAAAAAEpTMgEAAABQmpIJAAAAgNKUTAAAAACUpmQCAAAAoDQlEwAAAAClKZkAAAAAKE3JBAAAAEBpSiYAAAAASlMyAQAAAFCakgkAAACA0pRMAAAAAJSmZAIAAACgtNIl0/j4eHp6evJbv/VbSZLDhw9n48aNqdVq2bJlS0ZHR5Mko6Oj2bJlS2q1WjZu3Jhnn312Yo8/+ZM/Sa1WS2dnZ5544omJ9YGBgXR2dqZWq2XHjh1lRwUAAADgPCldMn3ta1/LNddcM/H6C1/4Qj7ykY/kW9/6VubPn59du3YlSR555JHMnz8/3/rWt/KRj3wkX/jCF5Ikhw4dSl9fX/r6+rJz58587nOfy/j4eMbHx3P33Xdn586d6evry2OPPZZDhw6VHRcAAACA86BUyTQ8PJzvfOc72bBhQ5KkKIp873vfS2dnZ5Jk/fr16e/vT5Ls27cv69evT5J0dnbmwIEDKYoi/f396erqypw5c9Le3p4lS5ZkcHAwg4ODWbJkSdrb2zNnzpx0dXVN7AUAAADA9NJc5uJ77703W7duzUsvvZQkOXLkSObPn5/m5tPbtrW1pV6vJ0nq9XquvPLK09+0uTktLS05cuRAbQGkAAANjklEQVRI6vV6li9fPrFntVqduKatre2M9cHBwTedqampktbWy8rESpJJ2WM6aWp626zLdLbZnlG+2eFiyAgAAFycGi6Z/vqv/zoLFy7MO9/5znz/+9+fzJlKGR8vcvToy2/5ukWLWs543cge01lr62WzLtPZZntG+WamyfhsOXsPAACA6ajhkukHP/hB9u3bl4GBgbzyyit58cUX8/nPfz7Hjx/P2NhYmpubMzw8nGq1muT0nUjPPfdc2traMjY2lhMnTuTyyy9PtVrN8PDwxL71en3imv9tHQAAAIDppeEzmT71qU9lYGAg+/btyx//8R9n5cqV+eIXv5h3v/vd2bNnT5Kkt7c3HR0dSZKOjo709vYmSfbs2ZOVK1emUqmko6MjfX19GR0dzeHDhzM0NJR3vetdWbZsWYaGhnL48OGMjo6mr69vYi8AAAAAppdSZzK9ka1bt+YTn/hEHnjggVx77bXZuHFjkmTDhg3ZunVrarVaFixYkPvvvz9JsnTp0tx0001Zt25dmpqasm3btjQ1NSVJtm3bls2bN2d8fDw333xzli5dOtnjAgAAADAJKkVRFFM9xGQ6dWq84TNPrr6tL0kydF9Xnn/+xGSPNqVm63k3P2m2Z5RvZpqMzxZnMgEAADNBw4/LAQAAAMBrlEwAAAAAlKZkAgAAAKA0JRMAAAAApSmZAAAAAChNyQQAAABAaUomAAAAAEpTMgEAAABQmpIJAAAAgNKUTAAAAACUpmQCAAAAoDQlEwAAAAClKZkAAAAAKE3JBAAAAEBpSiYAAAAASlMyAQAAAFCakgkAAACA0pRMAAAAAJSmZAIAAACgNCUTAAAAAKUpmQAAAAAoTckEAAAAQGlKJgAAAABKUzIBAAAAUJqSCQAAAIDSlEwAAAAAlKZkAgAAAKA0JRMAAAAApSmZAAAAACit4ZLpueeey4c//OGsW7cuXV1d+epXv5okOXr0aDZt2pS1a9dm06ZNOXbsWJKkKIps3749tVot3d3defrppyf26u3tzdq1a7N27dr09vZOrD/11FPp7u5OrVbL9u3bUxRFo+MCAAAAcB41XDI1NTXltttuyze+8Y385V/+Zf7iL/4ihw4dyo4dO7Jq1ars3bs3q1atyo4dO5IkAwMDGRoayt69e3PPPffkrrvuSnK6lHrwwQfz8MMP55FHHsmDDz44UUzdddddueeee7J3794MDQ1lYGCgfGIAAAAAJl3DJdPixYtz3XXXJUnmzZuXt7/97anX6+nv709PT0+SpKenJ9/+9reTZGK9UqlkxYoVOX78eEZGRrJ///6sXr06ra2tWbBgQVavXp0nnngiIyMjefHFF7NixYpUKpX09PSkv79/EiIDAAAAMNmaJ2OTZ599Nv/4j/+Y5cuX54UXXsjixYuTJIsWLcoLL7yQJKnX62lra5u4pq2tLfV6/XXr1Wr1Dddfe/+baWqqpLX1stKZJmOP6aSp6W2zLtPZZntG+WaHiyEjAABwcSpdMr300ku55ZZb8gd/8AeZN2/eGV+rVCqpVCplv8VbMj5e5OjRl9/ydYsWtZzxupE9prPW1stmXaazzfaM8s1Mk/HZcvYeAAAA01Gpny536tSp3HLLLenu7s7atWuTJFdccUVGRkaSJCMjI1m4cGGS03coDQ8PT1w7PDycarX6uvV6vf6G66+9HwAAAIDpp+GSqSiKfOYzn8nb3/72bNq0aWK9o6Mju3fvTpLs3r07N9544xnrRVHk4MGDaWlpyeLFi3P99ddn//79OXbsWI4dO5b9+/fn+uuvz+LFizNv3rwcPHgwRVGcsRcAAAAA00vDj8v93d/9XR599NG84x3vyAc/+MEkySc/+cl89KMfzZYtW7Jr165cddVVeeCBB5IkN9xwQx5//PHUarXMnTs39957b5KktbU1H/vYx7Jhw4Ykycc//vG0trYmST772c/m9ttvz8mTJ7NmzZqsWbOmVFgAAAAAzo9KURTFVA8xmU6dGm/4zJOrb+tLkgzd15Xnnz8x2aNNqdl63s1Pmu0Z5ZuZJuOzxZlMAADATFDqTCYAAAAASJRMAAAAAEwCJRMAAAAApSmZAAAAAChNyQQAAABAaUomAAAAAEpTMgEAAABQmpIJAAAAgNKUTAAAAACUpmQCAAAAoDQlEwAAAAClKZkAAAAAKE3JBAAAAEBpSiYAAAAASlMyAQAAAFCakgkAAACA0pRMAAAAAJSmZAIAAACgNCUTAAAAAKUpmQAAAAAoTckEAAAAQGlKJgAAAABKUzIBAAAAUJqSCQAAAIDSlEwAAAAAlKZkAgAAAKA0JRMAAAAApSmZAAAAAChNyQQAAABAaUomAAAAAEqb9iXTwMBAOjs7U6vVsmPHjqkeBwAAAIA3MK1LpvHx8dx9993ZuXNn+vr68thjj+XQoUNTPRYAAAAAZ5nWJdPg4GCWLFmS9vb2zJkzJ11dXenv75/qsQAAAAA4S/NUD/B/qdfraWtrm3hdrVYzODj4f15zySVNWbSopaHvN3Rf18SvG91jOpuNmc422zPKNzPN9s8WAACAZJrfyQQAAADAzDCtS6ZqtZrh4eGJ1/V6PdVqdQonAgAAAOCNTOuSadmyZRkaGsrhw4czOjqavr6+dHR0TPVYAAAAAJxlWp/J1NzcnG3btmXz5s0ZHx/PzTffnKVLl071WAAAAACcpVIURTHVQwAAAAAws03rx+UAAAAAmBmUTAAAAACUdtGVTAMDA+ns7EytVsuOHTte9/XR0dFs2bIltVotGzduzLPPPjsFUzbuzfL96Z/+adatW5fu7u782q/9Wv7jP/5jCqZs3Jvle82ePXvyMz/zM/mHf/iHCzjd5DiXjN/4xjeybt26dHV15VOf+tQFnrCcN8v3n//5n/nwhz+cnp6edHd35/HHH5+CKRt3++23Z9WqVfnABz7whl8viiLbt29PrVZLd3d3nn766Qs8IQAAwHlSXETGxsaKG2+8sfj3f//34pVXXim6u7uLH/3oR2e858///M+LO++8syiKonjssceKW2+9dSpGbci55Dtw4EDx8ssvF0VRFF//+tdnXb6iKIoTJ04UH/rQh4qNGzcWg4ODUzBp484l449//OPigx/8YHH06NGiKIriv/7rv6Zi1IacS7477rij+PrXv14URVH86Ec/Kt73vvdNxagNe/LJJ4unnnqq6OrqesOvf+c73yl+4zd+o3j11VeLH/7wh8WGDRsu8IQAAADnx0V1J9Pg4GCWLFmS9vb2zJkzJ11dXenv7z/jPfv27cv69euTJJ2dnTlw4ECKGXI2+rnkW7lyZebOnZskWbFiRYaHh6di1IacS74k+dKXvpTf/M3fzKWXXjoFU5ZzLhkffvjh/Mqv/EoWLFiQJLniiiumYtSGnEu+SqWSF198MUly4sSJLF68eCpGbdjP/dzPTfzZvJH+/v709PSkUqlkxYoVOX78eEZGRi7ghAAAAOfHRVUy1ev1tLW1TbyuVqup1+uve8+VV16ZJGlubk5LS0uOHDlyQeds1Lnk+0m7du3KmjVrLsRok+Jc8j399NMZHh7Oe9/73gs83eQ4l4xDQ0P58Y9/nF/6pV/KL/zCL2RgYOBCj9mwc8n3O7/zO/mrv/qrrFmzJh/96Edzxx13XOgxz6uzfw/a2tr+z3+nAAAAM8VFVTLx/z366KN56qmnsnnz5qkeZdK8+uqrue+++/L7v//7Uz3KeTU+Pp5/+7d/y5/92Z/li1/8Yu68884cP358qseaNH19fVm/fn0GBgayY8eOfPrTn86rr7461WMBAADwJi6qkqlarZ7xeFi9Xk+1Wn3de5577rkkydjYWE6cOJHLL7/8gs7ZqHPJlyTf/e538+UvfzkPPfRQ5syZcyFHLOXN8r300kv553/+5/zqr/5qOjo6cvDgwfz2b//2jDr8+1z/jnZ0dOSSSy5Je3t7rr766gwNDV3gSRtzLvl27dqVm266KUnysz/7s3nllVdmzN2E5+Ls34Ph4eE3/HcKAAAw01xUJdOyZcsyNDSUw4cPZ3R0NH19feno6DjjPR0dHent7U1y+ieUrVy5MpVKZSrGfcvOJd8zzzyTbdu25aGHHppRZ/kkb56vpaUl3//+97Nv377s27cvK1asyEMPPZRly5ZN4dRvzbn8Gf78z/98nnzyySTJf//3f2doaCjt7e1TMe5bdi75rrzyyhw4cCBJ8i//8i955ZVXsnDhwqkY97zo6OjI7t27UxRFDh48mJaWlhl37hQAAMAbaZ7qAS6k5ubmbNu2LZs3b874+HhuvvnmLF26NF/60pfyzne+MzfeeGM2bNiQrVu3plarZcGCBbn//vuneuxzdi75/uiP/igvv/xybr311iSn/0P/5S9/eYonPzfnkm+mO5eM73nPe/I3f/M3WbduXZqamvLpT396xtxtdy75brvtttxxxx35yle+kkqlkvvuu2/GFL1J8slPfjJPPvlkjhw5kjVr1uR3f/d3MzY2liT55V/+5dxwww15/PHHU6vVMnfu3Nx7771TPDEAAMDkqBQz5UenAQAAADBtXVSPywEAAABwfiiZAAAAAChNyQQAAABAaUomAAAAAEpTMgEAAABQmpIJAAAAgNKUTAAAAACU9v8AY++2og5KowAAAAAASUVORK5CYII=\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "31ad3663-dfe7-4ac5-ddc1-bb5bd6e5bdfd"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "dbc14537-5eb4-4433-f71b-8ad22f551fe8"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "af90f36e-850f-4ae6-f350-c7a55c2db05b"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "bcf199b4-b7f9-4a8c-ba2b-aff666038715"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YoQA_MIBMknS"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "189c418a-6688-4f58-c7f4-1354e235add7"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "708e7b7c-10ce-4d4a-ebbb-894567d167c9"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 43
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "92bf698d-e2bd-4438-bd84-346da3cfa696"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 44
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "91c28242-4c9a-4ce3-9649-501eafa9247e"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f5b0bd33310>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5b13aef050>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5b0be82050>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5b0e9d9fd0>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 45
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "c34ed8fa-edd0-41d0-e041-29a0853a3370"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "fd7abe27-940d-4f71-e581-5deb3ac42262"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "3c3a50d3-6f47-400e-edd0-18a46154f7fc"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1cKtTAzqyiyL"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "from keras.utils.vis_utils import plot_model\n",
-        "from keras.layers import Flatten\n",
-        "from keras.layers.convolutional import Conv1D\n",
-        "from keras.layers.convolutional import MaxPooling1D\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(Conv1D(filters=64, kernel_size=2, activation='relu', input_shape=(1,48))\n",
-        "single_step_model.add(MaxPooling1D(pool_size=2))\n",
-        "single_step_model.add(Flatten())\n",
-        "single_step_model.add(Dense(50, activation='relu'))\n",
-        "single_step_model.add(Dense(1))\n",
-        "single_step_model.compile(optimizer='adam', loss='mae', metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "\n",
-        "\n",
-        "#single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
-        "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "#single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "#single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "single_step_model.summary()\n",
-        "plot_model(single_step_model, to_file='/content/drive/MyDrive/Failure/lstm/CNN-LSTM.png', show_shapes=True, show_layer_names=True)\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "81b15b3b-0132-428e-d545-d689caa2e2eb"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "89bda316-e762-4aef-b32d-e7649da9ac39"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "xFJT1rZDAUVL",
-        "outputId": "a045ab0c-628b-456c-9ef6-5b92926358c6"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Lu7m2Rr4AbMK",
-        "outputId": "8e070f0a-fc5e-47a3-e330-ea8c8803c2c8"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "fjXexah9C8yg",
-        "outputId": "ed05331e-fdf2-460f-a2f5-4bac3be78bc8"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "id": "7mtLZ6S-DPU-",
-        "outputId": "02416632-1109-425e-af81-0f17a79e3120"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "snN_Flr5DWQN",
-        "outputId": "87a55e55-7cfd-4c10-9b15-db992065dd67"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "\n",
-        "multi_step_model.add(Conv1D(filters=64, kernel_size=2, activation='relu', input_shape=x_train_ss.shape[-2:]))\n",
-        "multi_step_model.add(MaxPooling1D(pool_size=2))\n",
-        "multi_step_model.add(Flatten())\n",
-        "multi_step_model.add(Dense(50, activation='relu'))\n",
-        "multi_step_model.add(Dense(1))\n",
-        "multi_step_model.compile(optimizer='adam', loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "\n",
-        "#multi_step_model.add(tf.keras.layers.LSTM(32,\n",
-        " #                                         return_sequences=True,\n",
-        "  #                                        input_shape=x_train_multi.shape[-2:]))\n",
-        "#multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
-        "#aDD dropout layer (0.3)\n",
-        "#multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "#multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 3s 50ms/step - loss: 0.1172 - rmse: 0.1745 - val_loss: 0.0284 - val_rmse: 0.0356\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0441 - rmse: 0.0501 - val_loss: 0.0656 - val_rmse: 0.0727\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0327 - rmse: 0.0378 - val_loss: 0.0332 - val_rmse: 0.0391\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0278 - rmse: 0.0319 - val_loss: 0.0291 - val_rmse: 0.0337\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0176 - rmse: 0.0209 - val_loss: 0.0173 - val_rmse: 0.0207\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0184 - rmse: 0.0213 - val_loss: 0.0162 - val_rmse: 0.0193\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0151 - rmse: 0.0185 - val_loss: 0.0086 - val_rmse: 0.0108\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0096 - rmse: 0.0123 - val_loss: 0.0079 - val_rmse: 0.0099\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 2s 45ms/step - loss: 0.0145 - rmse: 0.0188 - val_loss: 0.0245 - val_rmse: 0.0257\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0106 - rmse: 0.0141 - val_loss: 0.0079 - val_rmse: 0.0096\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0085 - rmse: 0.0103 - val_loss: 0.0151 - val_rmse: 0.0161\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0297 - rmse: 0.0410 - val_loss: 0.0295 - val_rmse: 0.0303\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0121 - rmse: 0.0153 - val_loss: 0.0346 - val_rmse: 0.0351\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0222 - rmse: 0.0265 - val_loss: 0.0098 - val_rmse: 0.0115\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0221 - rmse: 0.0244 - val_loss: 0.0078 - val_rmse: 0.0098\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0190 - rmse: 0.0214 - val_loss: 0.0331 - val_rmse: 0.0342\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0108 - rmse: 0.0131 - val_loss: 0.0111 - val_rmse: 0.0126\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0083 - rmse: 0.0104 - val_loss: 0.0059 - val_rmse: 0.0074\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0057 - rmse: 0.0071 - val_loss: 0.0112 - val_rmse: 0.0123\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 2s 44ms/step - loss: 0.0055 - rmse: 0.0068 - val_loss: 0.0045 - val_rmse: 0.0056\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Ay5m27doDsTt",
-        "outputId": "9b8f5274-03f9-427f-84ce-6dfafc9e7b45"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6ZFP49W4D2wp"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "403d8d4d-ca00-40d2-a179-f13879819f15"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 6s 8ms/step - loss: 0.0110 - rmse: 0.0279\n",
-            "MAE: 0.027902377769351006\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "oDXXSFLy07gH",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "47b9dcf3-cc67-43d3-e88a-8b51ea85a993"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "174/174 [==============================] - 1s 8ms/step - loss: 0.0057 - rmse: 0.0125\n",
-            "MAE: 0.027902377769351006\n"
-          ]
-        }
-      ]
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "b6f5691d-1e76-43a4-de55-3156dbc02b4d"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "ed2f1595-c32c-43eb-ae2f-b5fce96e9a92"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "63f0c61a-8a5a-41af-cbec-42fe0625b4d1"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "31ad3663-dfe7-4ac5-ddc1-bb5bd6e5bdfd"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "dbc14537-5eb4-4433-f71b-8ad22f551fe8"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "af90f36e-850f-4ae6-f350-c7a55c2db05b"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "bcf199b4-b7f9-4a8c-ba2b-aff666038715"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YoQA_MIBMknS"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "189c418a-6688-4f58-c7f4-1354e235add7"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "708e7b7c-10ce-4d4a-ebbb-894567d167c9"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "92bf698d-e2bd-4438-bd84-346da3cfa696"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "91c28242-4c9a-4ce3-9649-501eafa9247e"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "c34ed8fa-edd0-41d0-e041-29a0853a3370"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "fd7abe27-940d-4f71-e581-5deb3ac42262"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "3c3a50d3-6f47-400e-edd0-18a46154f7fc"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1cKtTAzqyiyL"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "from keras.utils.vis_utils import plot_model\n",
+    "from keras.layers import Flatten\n",
+    "from keras.layers.convolutional import Conv1D\n",
+    "from keras.layers.convolutional import MaxPooling1D\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(Conv1D(filters=64, kernel_size=2, activation='relu', input_shape=(1,48))\n",
+    "single_step_model.add(MaxPooling1D(pool_size=2))\n",
+    "single_step_model.add(Flatten())\n",
+    "single_step_model.add(Dense(50, activation='relu'))\n",
+    "single_step_model.add(Dense(1))\n",
+    "single_step_model.compile(optimizer='adam', loss='mae', metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "\n",
+    "\n",
+    "#single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
+    "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "#single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "#single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "single_step_model.summary()\n",
+    "plot_model(single_step_model, to_file='/content/drive/MyDrive/Failure/lstm/CNN-LSTM.png', show_shapes=True, show_layer_names=True)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "81b15b3b-0132-428e-d545-d689caa2e2eb"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "89bda316-e762-4aef-b32d-e7649da9ac39"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "a045ab0c-628b-456c-9ef6-5b92926358c6"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "8e070f0a-fc5e-47a3-e330-ea8c8803c2c8"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "ed05331e-fdf2-460f-a2f5-4bac3be78bc8"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "02416632-1109-425e-af81-0f17a79e3120"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "87a55e55-7cfd-4c10-9b15-db992065dd67"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "\n",
+    "multi_step_model.add(Conv1D(filters=64, kernel_size=2, activation='relu', input_shape=x_train_ss.shape[-2:]))\n",
+    "multi_step_model.add(MaxPooling1D(pool_size=2))\n",
+    "multi_step_model.add(Flatten())\n",
+    "multi_step_model.add(Dense(50, activation='relu'))\n",
+    "multi_step_model.add(Dense(1))\n",
+    "multi_step_model.compile(optimizer='adam', loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "\n",
+    "#multi_step_model.add(tf.keras.layers.LSTM(32,\n",
+    " #                                         return_sequences=True,\n",
+    "  #                                        input_shape=x_train_multi.shape[-2:]))\n",
+    "#multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
+    "#aDD dropout layer (0.3)\n",
+    "#multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "#multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "9b8f5274-03f9-427f-84ce-6dfafc9e7b45"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "6ZFP49W4D2wp"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "403d8d4d-ca00-40d2-a179-f13879819f15"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "oDXXSFLy07gH",
+    "outputId": "47b9dcf3-cc67-43d3-e88a-8b51ea85a993"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "CNN.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/Decision_Tree.ipynb b/models/failure_prediction/jnotebooks/Decision_Tree.ipynb

index d7cc012..1867b36 100644 (file)
--- a/models/failure_prediction/jnotebooks/Decision_Tree.ipynb
+++ b/models/failure_prediction/jnotebooks/Decision_Tree.ipynb
@@ -1,892 +1,549 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "FxPrqgIEVsdg"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sV1Drb9ccUFw"
+   },
+   "source": [
+    "We mounted the drive to access the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "Decision_Tree.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "FxPrqgIEVsdg"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "sV1Drb9ccUFw"
-      },
-      "source": [
-        "We mounted the drive to access the data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "df8b6b61-66a0-4bca-9ec5-c21216f5b46d"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /content/drive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "yhhkDCI7cc43"
-      },
-      "source": [
-        "We are importing libraries to read the CSV and to train the models"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "9wFIhTogcl4z"
-      },
-      "source": [
-        "We are reading CSV file using `read_csv` function and dropping the `Timestamp` column and storing it in a DataFrame called `df_Ellis`."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "2-UpMVsSnfCI",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "outputId": "38b85609-e8c4-493f-ee6d-43d1b627db7f"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis=df_Ellis.drop(columns='Timestamp')\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 7 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "        ellis-cpu.system_perc  ...  Label\n",
-              "0                         0.5  ...      1\n",
-              "1                         0.4  ...      1\n",
-              "2                         0.4  ...      1\n",
-              "3                         0.4  ...      1\n",
-              "4                         0.5  ...      1\n",
-              "...                       ...  ...    ...\n",
-              "176995                    0.4  ...      0\n",
-              "176996                    0.2  ...      0\n",
-              "176997                    0.6  ...      0\n",
-              "176998                    0.6  ...      0\n",
-              "176999                    0.4  ...      0\n",
-              "\n",
-              "[177000 rows x 7 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 45
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "o9SAQoIodC1V"
-      },
-      "source": [
-        "First we stored the `feature_cols` and defined the `X` matrix and `y` vector where `X` is a matrix and containing all the feature matrix and `y` is a vector which is having target value."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "27TqMF9VNQgh"
-      },
-      "source": [
-        "\n",
-        "# define X and y\n",
-        "feature_cols = ['ellis-cpu.wait_perc',\t'ellis-load.avg_1_min',\t'ellis-net.in_bytes_sec','ellis-cpu.system_perc','ellis-mem.free_mb']\n",
-        "\n",
-        "# X is a matrix, hence we use [] to access the features we want in feature_cols\n",
-        "X = df_Ellis[feature_cols]\n",
-        "\n",
-        "# y is a vector, hence we use dot to access 'label'\n",
-        "y = df_Ellis.Label"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "lBGYYW2Fdsra"
-      },
-      "source": [
-        "We splitted `X` and `y` into `X_train`, `X_test`, `y_train`, and `y_test` using `train_test_split` function."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6YiG55Z8NqJR"
-      },
-      "source": [
-        "# split X and y into training and testing sets\n",
-        "from sklearn.model_selection import train_test_split\n",
-        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=5)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "UfHBs8eweLT_"
-      },
-      "source": [
-        "We are training the model with Decision Tree."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "r1LWPgeBNvMA",
-        "outputId": "3fb01e3e-9d22-4547-b5ec-355821675af6"
-      },
-      "source": [
-        "# train a logistic regression model on the training set\n",
-        "from sklearn.linear_model import LogisticRegression\n",
-        "from sklearn import tree\n",
-        "\n",
-        "# instantiate model\n",
-        "logreg=tree.DecisionTreeClassifier()\n",
-        "\n",
-        "# fit model\n",
-        "logreg.fit(X_train, y_train)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
-              "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
-              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
-              "                       min_samples_leaf=1, min_samples_split=2,\n",
-              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
-              "                       random_state=None, splitter='best')"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 119
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "koopvyUxe1BR"
-      },
-      "source": [
-        "We are making predictions for test set"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YNrCzlWVODRZ"
-      },
-      "source": [
-        "# make class predictions for the testing set\n",
-        "y_pred_class = logreg.predict(X_test)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "61cWU-hAejuK"
-      },
-      "source": [
-        ""
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "r9XsgzK6e8Sj"
-      },
-      "source": [
-        "Here, we are calculating the accuracy using `sklearn` library"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "nrmeurYhOF9A",
-        "outputId": "af9f0179-2e24-4b85-e702-09f8cf5dd176"
-      },
-      "source": [
-        "# calculate accuracy\n",
-        "from sklearn import metrics\n",
-        "print(metrics.accuracy_score(y_test, y_pred_class))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "0.6620338983050847\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "We67ligTfEyz"
-      },
-      "source": [
-        "We are examining the class distribution of the testing set using a `pandas` series method"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "zdWWQ7p9OLuA",
-        "outputId": "d30b7eed-a72b-42dc-946b-6ce13f9d46e1"
-      },
-      "source": [
-        "# examine the class distribution of the testing set (using a Pandas Series method)\n",
-        "y_test.value_counts()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0    33686\n",
-              "1    19414\n",
-              "Name: Label, dtype: int64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 122
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "2mHqdHaOfPHh"
-      },
-      "source": [
-        "We counted the value for each lables"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "5y6mGyYwOQf4",
-        "outputId": "d8aaf9cc-eb8a-417e-8804-4613e034e8a1"
-      },
-      "source": [
-        "y_train.value_counts()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0    78460\n",
-              "1    45440\n",
-              "Name: Label, dtype: int64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 123
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "gHYoAXK3fUNr"
-      },
-      "source": [
-        "We are calculating the percentage of ones because `y_test` only contains ones and zeroes, we can simply calculate the mean = percentage of ones"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "bGLlh0lVOVMp",
-        "outputId": "f389d7cb-bf0b-4cf5-8b5b-6bf962c68717"
-      },
-      "source": [
-        "# calculate the percentage of ones\n",
-        "# because y_test only contains ones and zeros, we can simply calculate the mean = percentage of ones\n",
-        "y_test.mean()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0.3656120527306968"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 124
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "vjerEaxJfhAw"
-      },
-      "source": [
-        "We are calculating the percentage of zeros"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "GbU1cj6OOcGq",
-        "outputId": "8d1936a2-35c3-4813-be8f-9873c680f59f"
-      },
-      "source": [
-        "# calculate the percentage of zeros\n",
-        "1 - y_test.mean()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0.6343879472693033"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 125
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "t8w_x6f4OgCL",
-        "outputId": "23b3fc85-aa56-4060-922d-cdb04dcbf75e"
-      },
-      "source": [
-        "# calculate null accuracy in a single line of code\n",
-        "# only for binary classification problems coded as 0/1\n",
-        "max(y_test.mean(), 1 - y_test.mean())"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0.6343879472693033"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 126
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "iEsa9XIwOkX5",
-        "outputId": "9f890113-031a-48ef-f497-644550336b88"
-      },
-      "source": [
-        "# calculate null accuracy (for multi-class classification problems)\n",
-        "y_test.value_counts().head(1) / len(y_test)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0    0.634388\n",
-              "Name: Label, dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 127
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "uYAoMBHPOqPB",
-        "outputId": "58da15d1-50c6-42cb-d09c-3f719e333b79"
-      },
-      "source": [
-        "\n",
-        "# print the first 25 true and predicted responses\n",
-        "print('True:', y_test.values[0:50])\n",
-        "print('False:', y_pred_class[0:50])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "True: [0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 1 1 1 0 0 0 1 0 0\n",
-            " 0 0 0 1 1 0 0 1 1 1 0 0 1]\n",
-            "False: [0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 1 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0\n",
-            " 0 0 0 1 1 1 1 0 0 0 0 0 0]\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "puC1RxKmOw8C",
-        "outputId": "30df8b66-f7dc-4cb4-c869-179e2630c240"
-      },
-      "source": [
-        "# IMPORTANT: first argument is true values, second argument is predicted values\n",
-        "# this produces a 2x2 numpy array (matrix)\n",
-        "print(metrics.confusion_matrix(y_test, y_pred_class))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[[24355  9331]\n",
-            " [ 8615 10799]]\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "eXqJUVOlPA_z",
-        "outputId": "bbfb9a96-d2fc-4726-e4af-d87fcd9ef7ee"
-      },
-      "source": [
-        "# save confusion matrix and slice into four pieces\n",
-        "confusion = metrics.confusion_matrix(y_test, y_pred_class)\n",
-        "print(confusion)\n",
-        "#[row, column]\n",
-        "TP = confusion[1, 1]\n",
-        "TN = confusion[0, 0]\n",
-        "FP = confusion[0, 1]\n",
-        "FN = confusion[1, 0]"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "[[24355  9331]\n",
-            " [ 8615 10799]]\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "klBfDQSgPG4C",
-        "outputId": "9928f546-6f0b-4aa9-e647-6a0c0487f798"
-      },
-      "source": [
-        "\n",
-        "# use float to perform true division, not integer division\n",
-        "print((TP + TN) / float(TP + TN + FP + FN))\n",
-        "print(metrics.accuracy_score(y_test, y_pred_class))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "0.6620338983050847\n",
-            "0.6620338983050847\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "aeoA5XY_fyfU"
-      },
-      "source": [
-        "We are defining a function `print_results` to print the result of `y_test` and `y_pred`."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "D8GDuytFHL0o"
-      },
-      "source": [
-        "def print_results(y_test, y_pred):\n",
-        "    \n",
-        "    #f1-score\n",
-        "    f1 = metrics.f1_score(y_test, y_pred)\n",
-        "    print(\"F1 Score: \", f1)\n",
-        "    print(classification_report(y_test, y_pred))\n",
-        "    \n",
-        "    conf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
-        "    plt.figure(figsize=(12,12))\n",
-        "    plt.subplot(221)\n",
-        "    sns.heatmap(conf_matrix, fmt = \"d\",annot=True, cmap='Blues')\n",
-        "    b, t = plt.ylim()\n",
-        "    plt.ylim(b + 0.5, t - 0.5)\n",
-        "    plt.title('Confuion Matrix')\n",
-        "    plt.ylabel('True Values')\n",
-        "    plt.xlabel('Predicted Values')\n",
-        "\n",
-        "    #roc_auc_score\n",
-        "    model_roc_auc = metrics.roc_auc_score(y_test, y_pred) \n",
-        "    print (\"Area under curve : \",model_roc_auc,\"\\n\")\n",
-        "    fpr,tpr,thresholds = metrics.roc_curve(y_test, y_pred)\n",
-        "    gmeans = np.sqrt(tpr * (1-fpr))\n",
-        "    ix = np.argmax(gmeans)\n",
-        "    threshold = np.round(thresholds[ix],3)\n",
-        "\n",
-        "    plt.subplot(222)\n",
-        "    plt.plot(fpr, tpr, color='darkorange', lw=1, label = \"Auc : %.3f\" %model_roc_auc)\n",
-        "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
-        "    plt.scatter(fpr[ix], tpr[ix], marker='o', color='black', label='Best Threshold:' + str(threshold))\n",
-        "    plt.xlim([0.0, 1.0])\n",
-        "    plt.ylim([0.0, 1.05])\n",
-        "    plt.xlabel('False Positive Rate')\n",
-        "    plt.ylabel('True Positive Rate')\n",
-        "    plt.title('Receiver operating characteristic')\n",
-        "    plt.legend(loc=\"lower right\")"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 578
-        },
-        "id": "X2tMErOPHQZQ",
-        "outputId": "f6e44631-e5fe-4423-9cae-b6bed5c7a874"
-      },
-      "source": [
-        "import sklearn.metrics as metrics\n",
-        "import seaborn as sns\n",
-        "\n",
-        "from sklearn.metrics import classification_report\n",
-        "print_results(y_test, y_pred_class)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "F1 Score:  0.5461764110863848\n",
-            "              precision    recall  f1-score   support\n",
-            "\n",
-            "           0       0.74      0.72      0.73     33686\n",
-            "           1       0.54      0.56      0.55     19414\n",
-            "\n",
-            "    accuracy                           0.66     53100\n",
-            "   macro avg       0.64      0.64      0.64     53100\n",
-            "weighted avg       0.66      0.66      0.66     53100\n",
-            "\n",
-            "Area under curve :  0.6396243607472745 \n",
-            "\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 864x864 with 3 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "-NpF2Zc4lIdW"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "df8b6b61-66a0-4bca-9ec5-c21216f5b46d"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yhhkDCI7cc43"
+   },
+   "source": [
+    "We are importing libraries to read the CSV and to train the models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9wFIhTogcl4z"
+   },
+   "source": [
+    "We are reading CSV file using `read_csv` function and dropping the `Timestamp` column and storing it in a DataFrame called `df_Ellis`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "38b85609-e8c4-493f-ee6d-43d1b627db7f"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis=df_Ellis.drop(columns='Timestamp')\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "o9SAQoIodC1V"
+   },
+   "source": [
+    "First we stored the `feature_cols` and defined the `X` matrix and `y` vector where `X` is a matrix and containing all the feature matrix and `y` is a vector which is having target value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "27TqMF9VNQgh"
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "# define X and y\n",
+    "feature_cols = ['ellis-cpu.wait_perc',\t'ellis-load.avg_1_min',\t'ellis-net.in_bytes_sec','ellis-cpu.system_perc','ellis-mem.free_mb']\n",
+    "\n",
+    "# X is a matrix, hence we use [] to access the features we want in feature_cols\n",
+    "X = df_Ellis[feature_cols]\n",
+    "\n",
+    "# y is a vector, hence we use dot to access 'label'\n",
+    "y = df_Ellis.Label"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "lBGYYW2Fdsra"
+   },
+   "source": [
+    "We splitted `X` and `y` into `X_train`, `X_test`, `y_train`, and `y_test` using `train_test_split` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "6YiG55Z8NqJR"
+   },
+   "outputs": [],
+   "source": [
+    "# split X and y into training and testing sets\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UfHBs8eweLT_"
+   },
+   "source": [
+    "We are training the model with Decision Tree."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "r1LWPgeBNvMA",
+    "outputId": "3fb01e3e-9d22-4547-b5ec-355821675af6"
+   },
+   "outputs": [],
+   "source": [
+    "# train a logistic regression model on the training set\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn import tree\n",
+    "\n",
+    "# instantiate model\n",
+    "logreg=tree.DecisionTreeClassifier()\n",
+    "\n",
+    "# fit model\n",
+    "logreg.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "koopvyUxe1BR"
+   },
+   "source": [
+    "We are making predictions for test set"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YNrCzlWVODRZ"
+   },
+   "outputs": [],
+   "source": [
+    "# make class predictions for the testing set\n",
+    "y_pred_class = logreg.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "61cWU-hAejuK"
+   },
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "r9XsgzK6e8Sj"
+   },
+   "source": [
+    "Here, we are calculating the accuracy using `sklearn` library"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "nrmeurYhOF9A",
+    "outputId": "af9f0179-2e24-4b85-e702-09f8cf5dd176"
+   },
+   "outputs": [],
+   "source": [
+    "# calculate accuracy\n",
+    "from sklearn import metrics\n",
+    "print(metrics.accuracy_score(y_test, y_pred_class))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "We67ligTfEyz"
+   },
+   "source": [
+    "We are examining the class distribution of the testing set using a `pandas` series method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "zdWWQ7p9OLuA",
+    "outputId": "d30b7eed-a72b-42dc-946b-6ce13f9d46e1"
+   },
+   "outputs": [],
+   "source": [
+    "# examine the class distribution of the testing set (using a Pandas Series method)\n",
+    "y_test.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2mHqdHaOfPHh"
+   },
+   "source": [
+    "We counted the value for each lables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "5y6mGyYwOQf4",
+    "outputId": "d8aaf9cc-eb8a-417e-8804-4613e034e8a1"
+   },
+   "outputs": [],
+   "source": [
+    "y_train.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "gHYoAXK3fUNr"
+   },
+   "source": [
+    "We are calculating the percentage of ones because `y_test` only contains ones and zeroes, we can simply calculate the mean = percentage of ones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "bGLlh0lVOVMp",
+    "outputId": "f389d7cb-bf0b-4cf5-8b5b-6bf962c68717"
+   },
+   "outputs": [],
+   "source": [
+    "# calculate the percentage of ones\n",
+    "# because y_test only contains ones and zeros, we can simply calculate the mean = percentage of ones\n",
+    "y_test.mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "vjerEaxJfhAw"
+   },
+   "source": [
+    "We are calculating the percentage of zeros"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "GbU1cj6OOcGq",
+    "outputId": "8d1936a2-35c3-4813-be8f-9873c680f59f"
+   },
+   "outputs": [],
+   "source": [
+    "# calculate the percentage of zeros\n",
+    "1 - y_test.mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "t8w_x6f4OgCL",
+    "outputId": "23b3fc85-aa56-4060-922d-cdb04dcbf75e"
+   },
+   "outputs": [],
+   "source": [
+    "# calculate null accuracy in a single line of code\n",
+    "# only for binary classification problems coded as 0/1\n",
+    "max(y_test.mean(), 1 - y_test.mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "iEsa9XIwOkX5",
+    "outputId": "9f890113-031a-48ef-f497-644550336b88"
+   },
+   "outputs": [],
+   "source": [
+    "# calculate null accuracy (for multi-class classification problems)\n",
+    "y_test.value_counts().head(1) / len(y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "uYAoMBHPOqPB",
+    "outputId": "58da15d1-50c6-42cb-d09c-3f719e333b79"
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "# print the first 25 true and predicted responses\n",
+    "print('True:', y_test.values[0:50])\n",
+    "print('False:', y_pred_class[0:50])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "puC1RxKmOw8C",
+    "outputId": "30df8b66-f7dc-4cb4-c869-179e2630c240"
+   },
+   "outputs": [],
+   "source": [
+    "# IMPORTANT: first argument is true values, second argument is predicted values\n",
+    "# this produces a 2x2 numpy array (matrix)\n",
+    "print(metrics.confusion_matrix(y_test, y_pred_class))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "eXqJUVOlPA_z",
+    "outputId": "bbfb9a96-d2fc-4726-e4af-d87fcd9ef7ee"
+   },
+   "outputs": [],
+   "source": [
+    "# save confusion matrix and slice into four pieces\n",
+    "confusion = metrics.confusion_matrix(y_test, y_pred_class)\n",
+    "print(confusion)\n",
+    "#[row, column]\n",
+    "TP = confusion[1, 1]\n",
+    "TN = confusion[0, 0]\n",
+    "FP = confusion[0, 1]\n",
+    "FN = confusion[1, 0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "klBfDQSgPG4C",
+    "outputId": "9928f546-6f0b-4aa9-e647-6a0c0487f798"
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "# use float to perform true division, not integer division\n",
+    "print((TP + TN) / float(TP + TN + FP + FN))\n",
+    "print(metrics.accuracy_score(y_test, y_pred_class))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aeoA5XY_fyfU"
+   },
+   "source": [
+    "We are defining a function `print_results` to print the result of `y_test` and `y_pred`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "D8GDuytFHL0o"
+   },
+   "outputs": [],
+   "source": [
+    "def print_results(y_test, y_pred):\n",
+    "    \n",
+    "    #f1-score\n",
+    "    f1 = metrics.f1_score(y_test, y_pred)\n",
+    "    print(\"F1 Score: \", f1)\n",
+    "    print(classification_report(y_test, y_pred))\n",
+    "    \n",
+    "    conf_matrix = metrics.confusion_matrix(y_test, y_pred)\n",
+    "    plt.figure(figsize=(12,12))\n",
+    "    plt.subplot(221)\n",
+    "    sns.heatmap(conf_matrix, fmt = \"d\",annot=True, cmap='Blues')\n",
+    "    b, t = plt.ylim()\n",
+    "    plt.ylim(b + 0.5, t - 0.5)\n",
+    "    plt.title('Confuion Matrix')\n",
+    "    plt.ylabel('True Values')\n",
+    "    plt.xlabel('Predicted Values')\n",
+    "\n",
+    "    #roc_auc_score\n",
+    "    model_roc_auc = metrics.roc_auc_score(y_test, y_pred) \n",
+    "    print (\"Area under curve : \",model_roc_auc,\"\\n\")\n",
+    "    fpr,tpr,thresholds = metrics.roc_curve(y_test, y_pred)\n",
+    "    gmeans = np.sqrt(tpr * (1-fpr))\n",
+    "    ix = np.argmax(gmeans)\n",
+    "    threshold = np.round(thresholds[ix],3)\n",
+    "\n",
+    "    plt.subplot(222)\n",
+    "    plt.plot(fpr, tpr, color='darkorange', lw=1, label = \"Auc : %.3f\" %model_roc_auc)\n",
+    "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
+    "    plt.scatter(fpr[ix], tpr[ix], marker='o', color='black', label='Best Threshold:' + str(threshold))\n",
+    "    plt.xlim([0.0, 1.0])\n",
+    "    plt.ylim([0.0, 1.05])\n",
+    "    plt.xlabel('False Positive Rate')\n",
+    "    plt.ylabel('True Positive Rate')\n",
+    "    plt.title('Receiver operating characteristic')\n",
+    "    plt.legend(loc=\"lower right\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 578
+    },
+    "id": "X2tMErOPHQZQ",
+    "outputId": "f6e44631-e5fe-4423-9cae-b6bed5c7a874"
+   },
+   "outputs": [],
+   "source": [
+    "import sklearn.metrics as metrics\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from sklearn.metrics import classification_report\n",
+    "print_results(y_test, y_pred_class)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "Decision_Tree.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/FeatureCreation.ipynb b/models/failure_prediction/jnotebooks/FeatureCreation.ipynb

index ae0ccec..a9eaf19 100644 (file)
--- a/models/failure_prediction/jnotebooks/FeatureCreation.ipynb
+++ b/models/failure_prediction/jnotebooks/FeatureCreation.ipynb
@@ -1,1257 +1,389 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zyycU3DFlecK"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "gehKp2rySVf8"
+   },
+   "outputs": [],
+   "source": [
+    "# Import libraries use for visualization and analysis\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from pandas import Series,DataFrame\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.preprocessing import scale\n",
+    "from sklearn.decomposition import PCA\n",
+    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
+    "from scipy import stats\n",
+    "from IPython.display import display, HTML"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "FeatureCreation.ipynb",
-      "provenance": []
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
+     "base_uri": "https://localhost:8080/"
      },
-    "language_info": {
-      "name": "python"
-    }
+    "id": "tkuBlbCXSsdP",
+    "outputId": "2b3ef633-a851-4c53-80eb-6b1bf4ffcc1c"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/gdrive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "zyycU3DFlecK"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "gehKp2rySVf8"
-      },
-      "source": [
-        "# Import libraries use for visualization and analysis\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "\n",
-        "%matplotlib inline\n",
-        "import matplotlib\n",
-        "import matplotlib.pyplot as plt\n",
-        "\n",
-        "from pandas import Series,DataFrame\n",
-        "import matplotlib.pyplot as plt\n",
-        "import seaborn as sns\n",
-        "from sklearn.preprocessing import scale\n",
-        "from sklearn.decomposition import PCA\n",
-        "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
-        "from scipy import stats\n",
-        "from IPython.display import display, HTML"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "tkuBlbCXSsdP",
-        "outputId": "2b3ef633-a851-4c53-80eb-6b1bf4ffcc1c"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/gdrive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "text": [
-            "Drive already mounted at /gdrive; to attempt to forcibly remount, call drive.mount(\"/gdrive\", force_remount=True).\n"
-          ],
-          "name": "stdout"
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "wZXe8D88S-6R"
-      },
-      "source": [
-        "# **Loading the Data**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "KiDSpl37Sy39"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Final.csv\")\n",
-        "#df_Bono  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Bono.csv\", error_bad_lines=False)\n",
-        "#df_Sprout  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Sprout.csv\", error_bad_lines=False)\n",
-        "#df_Homer  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Homer.csv\", error_bad_lines=False)\n",
-        "#df_Homestead  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Homestead.csv\", error_bad_lines=False)\n",
-        "#df_Ralf  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Ralf.csv\", error_bad_lines=False)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "dpy8jAm-TsCs",
-        "outputId": "d8ad2072-1fa3-4b3c-fb55-b5128767b349"
-      },
-      "source": [
-        "df_Ellis.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14/09/2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14/09/2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14/09/2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14/09/2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14/09/2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "         Timestamp  ...  ellis-net.out_packets_sec\n",
-              "0  14/09/2016 0:00  ...                     62.067\n",
-              "1  14/09/2016 0:00  ...                     59.567\n",
-              "2  14/09/2016 0:01  ...                     61.200\n",
-              "3  14/09/2016 0:01  ...                     60.400\n",
-              "4  14/09/2016 0:02  ...                     61.700\n",
-              "\n",
-              "[5 rows x 7 columns]"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 264
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 297
-        },
-        "id": "dJa9FgJNgqpI",
-        "outputId": "54d6c43d-489f-4347-93e5-12e4a4da2066"
-      },
-      "source": [
-        "df_Ellis.describe()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>count</th>\n",
-              "      <td>177000.000000</td>\n",
-              "      <td>177000.000000</td>\n",
-              "      <td>177000.000000</td>\n",
-              "      <td>177000.000000</td>\n",
-              "      <td>1.770000e+05</td>\n",
-              "      <td>177000.000000</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>mean</th>\n",
-              "      <td>2.315540</td>\n",
-              "      <td>1.024163</td>\n",
-              "      <td>0.198842</td>\n",
-              "      <td>4206.847232</td>\n",
-              "      <td>1.855987e+07</td>\n",
-              "      <td>1336.694851</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>std</th>\n",
-              "      <td>1.170977</td>\n",
-              "      <td>3.127178</td>\n",
-              "      <td>0.262227</td>\n",
-              "      <td>173.364297</td>\n",
-              "      <td>5.612164e+06</td>\n",
-              "      <td>2220.146124</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>min</th>\n",
-              "      <td>0.100000</td>\n",
-              "      <td>0.000000</td>\n",
-              "      <td>0.000000</td>\n",
-              "      <td>2320.000000</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>0.000000</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>25%</th>\n",
-              "      <td>1.500000</td>\n",
-              "      <td>0.200000</td>\n",
-              "      <td>0.095000</td>\n",
-              "      <td>4095.000000</td>\n",
-              "      <td>1.797602e+07</td>\n",
-              "      <td>182.033000</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>50%</th>\n",
-              "      <td>1.700000</td>\n",
-              "      <td>0.200000</td>\n",
-              "      <td>0.140000</td>\n",
-              "      <td>4214.000000</td>\n",
-              "      <td>2.087674e+07</td>\n",
-              "      <td>200.067000</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>75%</th>\n",
-              "      <td>3.500000</td>\n",
-              "      <td>0.400000</td>\n",
-              "      <td>0.198000</td>\n",
-              "      <td>4331.000000</td>\n",
-              "      <td>2.160859e+07</td>\n",
-              "      <td>1069.667000</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>max</th>\n",
-              "      <td>16.700000</td>\n",
-              "      <td>22.400000</td>\n",
-              "      <td>2.580000</td>\n",
-              "      <td>4633.000000</td>\n",
-              "      <td>2.339041e+07</td>\n",
-              "      <td>7887.552000</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "       ellis-cpu.system_perc  ...  ellis-net.out_packets_sec\n",
-              "count          177000.000000  ...              177000.000000\n",
-              "mean                2.315540  ...                1336.694851\n",
-              "std                 1.170977  ...                2220.146124\n",
-              "min                 0.100000  ...                   0.000000\n",
-              "25%                 1.500000  ...                 182.033000\n",
-              "50%                 1.700000  ...                 200.067000\n",
-              "75%                 3.500000  ...                1069.667000\n",
-              "max                16.700000  ...                7887.552000\n",
-              "\n",
-              "[8 rows x 6 columns]"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 265
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "xGVleQbnhRm6"
-      },
-      "source": [
-        "#df_Ellis['SLO1'] = 0\n",
-        "#print('Column names are: ',list(df_Ellis.columns))"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "b-F_gA61xowR",
-        "outputId": "f9bd6232-2603-40ad-ccff-18887839e2da"
-      },
-      "source": [
-        "df4 = df_Ellis[\"ellis-load.avg_1_min\"] > 2.45\n",
-        "df4\n",
-        "df4.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/EllisLoadAvgLabel_lessthan0198.csv')\n",
-        "df4.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     False\n",
-              "1     False\n",
-              "2     False\n",
-              "3     False\n",
-              "4     False\n",
-              "5     False\n",
-              "6     False\n",
-              "7     False\n",
-              "8     False\n",
-              "9     False\n",
-              "10    False\n",
-              "11    False\n",
-              "12    False\n",
-              "13    False\n",
-              "14    False\n",
-              "15    False\n",
-              "16    False\n",
-              "17    False\n",
-              "18    False\n",
-              "19    False\n",
-              "20    False\n",
-              "21    False\n",
-              "22    False\n",
-              "23    False\n",
-              "24    False\n",
-              "25    False\n",
-              "26    False\n",
-              "27    False\n",
-              "28    False\n",
-              "29    False\n",
-              "30    False\n",
-              "31    False\n",
-              "32    False\n",
-              "33    False\n",
-              "34    False\n",
-              "35    False\n",
-              "36    False\n",
-              "37    False\n",
-              "38    False\n",
-              "39    False\n",
-              "40    False\n",
-              "41    False\n",
-              "42    False\n",
-              "43    False\n",
-              "44    False\n",
-              "45    False\n",
-              "46    False\n",
-              "47    False\n",
-              "48    False\n",
-              "49    False\n",
-              "Name: ellis-load.avg_1_min, dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 267
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "8xcPRerCz8nA",
-        "outputId": "fb66f20e-7365-40ec-857a-9dd9a8072401"
-      },
-      "source": [
-        "df3 = df_Ellis[\"ellis-cpu.wait_perc\"] > 5\n",
-        "df3\n",
-        "df3.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/ellis-cpu>5.csv')\n",
-        "df3.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     True\n",
-              "1     True\n",
-              "2     True\n",
-              "3     True\n",
-              "4     True\n",
-              "5     True\n",
-              "6     True\n",
-              "7     True\n",
-              "8     True\n",
-              "9     True\n",
-              "10    True\n",
-              "11    True\n",
-              "12    True\n",
-              "13    True\n",
-              "14    True\n",
-              "15    True\n",
-              "16    True\n",
-              "17    True\n",
-              "18    True\n",
-              "19    True\n",
-              "20    True\n",
-              "21    True\n",
-              "22    True\n",
-              "23    True\n",
-              "24    True\n",
-              "25    True\n",
-              "26    True\n",
-              "27    True\n",
-              "28    True\n",
-              "29    True\n",
-              "30    True\n",
-              "31    True\n",
-              "32    True\n",
-              "33    True\n",
-              "34    True\n",
-              "35    True\n",
-              "36    True\n",
-              "37    True\n",
-              "38    True\n",
-              "39    True\n",
-              "40    True\n",
-              "41    True\n",
-              "42    True\n",
-              "43    True\n",
-              "44    True\n",
-              "45    True\n",
-              "46    True\n",
-              "47    True\n",
-              "48    True\n",
-              "49    True\n",
-              "Name: ellis-cpu.wait_perc, dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 268
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "EED56Wiq_NjM",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "20b06258-c5ba-457b-a022-cf5823217cbf"
-      },
-      "source": [
-        "df5 = df_Ellis[\"ellis-net.out_packets_sec\"] > 1000\n",
-        "df5\n",
-        "df5.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/ellis-net.in_bytes_sec21139.csv')\n",
-        "df5.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     False\n",
-              "1     False\n",
-              "2     False\n",
-              "3     False\n",
-              "4     False\n",
-              "5     False\n",
-              "6     False\n",
-              "7     False\n",
-              "8     False\n",
-              "9     False\n",
-              "10    False\n",
-              "11    False\n",
-              "12    False\n",
-              "13    False\n",
-              "14    False\n",
-              "15    False\n",
-              "16    False\n",
-              "17    False\n",
-              "18    False\n",
-              "19    False\n",
-              "20    False\n",
-              "21    False\n",
-              "22    False\n",
-              "23    False\n",
-              "24    False\n",
-              "25    False\n",
-              "26    False\n",
-              "27    False\n",
-              "28    False\n",
-              "29    False\n",
-              "30    False\n",
-              "31    False\n",
-              "32    False\n",
-              "33    False\n",
-              "34    False\n",
-              "35    False\n",
-              "36    False\n",
-              "37    False\n",
-              "38    False\n",
-              "39    False\n",
-              "40    False\n",
-              "41    False\n",
-              "42    False\n",
-              "43    False\n",
-              "44    False\n",
-              "45    False\n",
-              "46    False\n",
-              "47    False\n",
-              "48    False\n",
-              "49    False\n",
-              "Name: ellis-net.out_packets_sec, dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 269
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "phlI40_y0mug",
-        "outputId": "7fa177b9-bf9a-4b96-db65-7402f7f6cf32"
-      },
-      "source": [
-        "# We are applying Logical OR Operator between df4 and df3\n",
-        "df6 = (df4[0:176999]) | (df3[0:176999])\n",
-        "df6.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     True\n",
-              "1     True\n",
-              "2     True\n",
-              "3     True\n",
-              "4     True\n",
-              "5     True\n",
-              "6     True\n",
-              "7     True\n",
-              "8     True\n",
-              "9     True\n",
-              "10    True\n",
-              "11    True\n",
-              "12    True\n",
-              "13    True\n",
-              "14    True\n",
-              "15    True\n",
-              "16    True\n",
-              "17    True\n",
-              "18    True\n",
-              "19    True\n",
-              "20    True\n",
-              "21    True\n",
-              "22    True\n",
-              "23    True\n",
-              "24    True\n",
-              "25    True\n",
-              "26    True\n",
-              "27    True\n",
-              "28    True\n",
-              "29    True\n",
-              "30    True\n",
-              "31    True\n",
-              "32    True\n",
-              "33    True\n",
-              "34    True\n",
-              "35    True\n",
-              "36    True\n",
-              "37    True\n",
-              "38    True\n",
-              "39    True\n",
-              "40    True\n",
-              "41    True\n",
-              "42    True\n",
-              "43    True\n",
-              "44    True\n",
-              "45    True\n",
-              "46    True\n",
-              "47    True\n",
-              "48    True\n",
-              "49    True\n",
-              "dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 270
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "9xKYzZcLAZGy",
-        "outputId": "bc15e547-c791-4104-8bb2-8ed4d3288ac1"
-      },
-      "source": [
-        "df6.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/OR_TwoCondition(2).csv')\n",
-        "df6.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     True\n",
-              "1     True\n",
-              "2     True\n",
-              "3     True\n",
-              "4     True\n",
-              "5     True\n",
-              "6     True\n",
-              "7     True\n",
-              "8     True\n",
-              "9     True\n",
-              "10    True\n",
-              "11    True\n",
-              "12    True\n",
-              "13    True\n",
-              "14    True\n",
-              "15    True\n",
-              "16    True\n",
-              "17    True\n",
-              "18    True\n",
-              "19    True\n",
-              "20    True\n",
-              "21    True\n",
-              "22    True\n",
-              "23    True\n",
-              "24    True\n",
-              "25    True\n",
-              "26    True\n",
-              "27    True\n",
-              "28    True\n",
-              "29    True\n",
-              "30    True\n",
-              "31    True\n",
-              "32    True\n",
-              "33    True\n",
-              "34    True\n",
-              "35    True\n",
-              "36    True\n",
-              "37    True\n",
-              "38    True\n",
-              "39    True\n",
-              "40    True\n",
-              "41    True\n",
-              "42    True\n",
-              "43    True\n",
-              "44    True\n",
-              "45    True\n",
-              "46    True\n",
-              "47    True\n",
-              "48    True\n",
-              "49    True\n",
-              "dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 271
-        }
-      ]
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "wZXe8D88S-6R"
+   },
+   "source": [
+    "# **Loading the Data**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "KiDSpl37Sy39"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Final.csv\")\n",
+    "#df_Bono  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Bono.csv\", error_bad_lines=False)\n",
+    "#df_Sprout  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Sprout.csv\", error_bad_lines=False)\n",
+    "#df_Homer  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Homer.csv\", error_bad_lines=False)\n",
+    "#df_Homestead  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Homestead.csv\", error_bad_lines=False)\n",
+    "#df_Ralf  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/matrices/df_Ralf.csv\", error_bad_lines=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "wRADpDibBZo5",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "dfc6dc79-3d9f-4979-8210-e62e77b1aa6e"
-      },
-      "source": [
-        "df7 = (df6[0:176999]) | (df5[0:176999])\n",
-        "df7.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     True\n",
-              "1     True\n",
-              "2     True\n",
-              "3     True\n",
-              "4     True\n",
-              "5     True\n",
-              "6     True\n",
-              "7     True\n",
-              "8     True\n",
-              "9     True\n",
-              "10    True\n",
-              "11    True\n",
-              "12    True\n",
-              "13    True\n",
-              "14    True\n",
-              "15    True\n",
-              "16    True\n",
-              "17    True\n",
-              "18    True\n",
-              "19    True\n",
-              "20    True\n",
-              "21    True\n",
-              "22    True\n",
-              "23    True\n",
-              "24    True\n",
-              "25    True\n",
-              "26    True\n",
-              "27    True\n",
-              "28    True\n",
-              "29    True\n",
-              "30    True\n",
-              "31    True\n",
-              "32    True\n",
-              "33    True\n",
-              "34    True\n",
-              "35    True\n",
-              "36    True\n",
-              "37    True\n",
-              "38    True\n",
-              "39    True\n",
-              "40    True\n",
-              "41    True\n",
-              "42    True\n",
-              "43    True\n",
-              "44    True\n",
-              "45    True\n",
-              "46    True\n",
-              "47    True\n",
-              "48    True\n",
-              "49    True\n",
-              "dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 272
-        }
-      ]
+    "id": "dpy8jAm-TsCs",
+    "outputId": "d8ad2072-1fa3-4b3c-fb55-b5128767b349"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 297
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "w6BrDjX4CODn",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "a6c956e7-6aed-4bdd-f37f-505a994de51a"
-      },
-      "source": [
-        "df7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/FinalORLabel8.5.csv')\n",
-        "df7.head(50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0     True\n",
-              "1     True\n",
-              "2     True\n",
-              "3     True\n",
-              "4     True\n",
-              "5     True\n",
-              "6     True\n",
-              "7     True\n",
-              "8     True\n",
-              "9     True\n",
-              "10    True\n",
-              "11    True\n",
-              "12    True\n",
-              "13    True\n",
-              "14    True\n",
-              "15    True\n",
-              "16    True\n",
-              "17    True\n",
-              "18    True\n",
-              "19    True\n",
-              "20    True\n",
-              "21    True\n",
-              "22    True\n",
-              "23    True\n",
-              "24    True\n",
-              "25    True\n",
-              "26    True\n",
-              "27    True\n",
-              "28    True\n",
-              "29    True\n",
-              "30    True\n",
-              "31    True\n",
-              "32    True\n",
-              "33    True\n",
-              "34    True\n",
-              "35    True\n",
-              "36    True\n",
-              "37    True\n",
-              "38    True\n",
-              "39    True\n",
-              "40    True\n",
-              "41    True\n",
-              "42    True\n",
-              "43    True\n",
-              "44    True\n",
-              "45    True\n",
-              "46    True\n",
-              "47    True\n",
-              "48    True\n",
-              "49    True\n",
-              "dtype: bool"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 273
-        }
-      ]
+    "id": "dJa9FgJNgqpI",
+    "outputId": "54d6c43d-489f-4347-93e5-12e4a4da2066"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xGVleQbnhRm6"
+   },
+   "outputs": [],
+   "source": [
+    "#df_Ellis['SLO1'] = 0\n",
+    "#print('Column names are: ',list(df_Ellis.columns))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "wwv2cjFAIFHL"
-      },
-      "source": [
-        "df_Ellis.insert (7, \"Label\", df7)"
-      ],
-      "execution_count": null,
-      "outputs": []
+    "id": "b-F_gA61xowR",
+    "outputId": "f9bd6232-2603-40ad-ccff-18887839e2da"
+   },
+   "outputs": [],
+   "source": [
+    "df4 = df_Ellis[\"ellis-load.avg_1_min\"] > 2.45\n",
+    "df4\n",
+    "df4.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/EllisLoadAvgLabel_lessthan0198.csv')\n",
+    "df4.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "hrPqpjd96I1x"
-      },
-      "source": [
-        "#df_Ellis.insert (8, \"Label\", df7)"
-      ],
-      "execution_count": null,
-      "outputs": []
+    "id": "8xcPRerCz8nA",
+    "outputId": "fb66f20e-7365-40ec-857a-9dd9a8072401"
+   },
+   "outputs": [],
+   "source": [
+    "df3 = df_Ellis[\"ellis-cpu.wait_perc\"] > 5\n",
+    "df3\n",
+    "df3.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/ellis-cpu>5.csv')\n",
+    "df3.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "_zKkQLOz6qPY"
-      },
-      "source": [
-        "# We applied Logical OR operator in two features only known as  and df3 and df4 and stored result in df6 which is known as Final Label after applying OR condition\n",
-        "df_Ellis\n",
-        "df_Ellis.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv')"
-      ],
-      "execution_count": null,
-      "outputs": []
+    "id": "EED56Wiq_NjM",
+    "outputId": "20b06258-c5ba-457b-a022-cf5823217cbf"
+   },
+   "outputs": [],
+   "source": [
+    "df5 = df_Ellis[\"ellis-net.out_packets_sec\"] > 1000\n",
+    "df5\n",
+    "df5.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/ellis-net.in_bytes_sec21139.csv')\n",
+    "df5.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "3rEy1vtp67M9",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 606
-        },
-        "outputId": "4e2175cc-dccb-4aaf-a152-e2452de241b0"
-      },
-      "source": [
-        "df_Ellis.head(100)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14/09/2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14/09/2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14/09/2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14/09/2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14/09/2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>95</th>\n",
-              "      <td>14/09/2016 0:47</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>10.8</td>\n",
-              "      <td>0.45</td>\n",
-              "      <td>3948</td>\n",
-              "      <td>5187.133</td>\n",
-              "      <td>60.100</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>96</th>\n",
-              "      <td>14/09/2016 0:48</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>10.4</td>\n",
-              "      <td>0.42</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5223.100</td>\n",
-              "      <td>60.233</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>97</th>\n",
-              "      <td>14/09/2016 0:48</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>13.0</td>\n",
-              "      <td>0.56</td>\n",
-              "      <td>3947</td>\n",
-              "      <td>5335.200</td>\n",
-              "      <td>60.667</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>98</th>\n",
-              "      <td>14/09/2016 0:49</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>10.1</td>\n",
-              "      <td>0.47</td>\n",
-              "      <td>3948</td>\n",
-              "      <td>5185.733</td>\n",
-              "      <td>60.367</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>99</th>\n",
-              "      <td>14/09/2016 0:49</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>10.8</td>\n",
-              "      <td>0.28</td>\n",
-              "      <td>3948</td>\n",
-              "      <td>5204.233</td>\n",
-              "      <td>59.600</td>\n",
-              "      <td>True</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>100 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "          Timestamp  ellis-cpu.system_perc  ...  ellis-net.out_packets_sec  Label\n",
-              "0   14/09/2016 0:00                    0.5  ...                     62.067   True\n",
-              "1   14/09/2016 0:00                    0.4  ...                     59.567   True\n",
-              "2   14/09/2016 0:01                    0.4  ...                     61.200   True\n",
-              "3   14/09/2016 0:01                    0.4  ...                     60.400   True\n",
-              "4   14/09/2016 0:02                    0.5  ...                     61.700   True\n",
-              "..              ...                    ...  ...                        ...    ...\n",
-              "95  14/09/2016 0:47                    0.5  ...                     60.100   True\n",
-              "96  14/09/2016 0:48                    0.5  ...                     60.233   True\n",
-              "97  14/09/2016 0:48                    0.6  ...                     60.667   True\n",
-              "98  14/09/2016 0:49                    0.6  ...                     60.367   True\n",
-              "99  14/09/2016 0:49                    0.6  ...                     59.600   True\n",
-              "\n",
-              "[100 rows x 8 columns]"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 277
-        }
-      ]
+    "id": "phlI40_y0mug",
+    "outputId": "7fa177b9-bf9a-4b96-db65-7402f7f6cf32"
+   },
+   "outputs": [],
+   "source": [
+    "# We are applying Logical OR Operator between df4 and df3\n",
+    "df6 = (df4[0:176999]) | (df3[0:176999])\n",
+    "df6.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "11Qu45RY0HNG",
-        "outputId": "305c5dd5-ec61-48a8-abb6-e29bbc4b9e42"
-      },
-      "source": [
-        "# pandas count distinct values in column\n",
-        "df_Ellis['Label'].value_counts()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "False    112145\n",
-              "True      64854\n",
-              "Name: Label, dtype: int64"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 278
-        }
-      ]
+    "id": "9xKYzZcLAZGy",
+    "outputId": "bc15e547-c791-4104-8bb2-8ed4d3288ac1"
+   },
+   "outputs": [],
+   "source": [
+    "df6.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/OR_TwoCondition(2).csv')\n",
+    "df6.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "0sB-W_Ny4eHk"
-      },
-      "source": [
-        "#final.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/FinalLabel.csv')"
-      ],
-      "execution_count": null,
-      "outputs": []
+    "id": "wRADpDibBZo5",
+    "outputId": "dfc6dc79-3d9f-4979-8210-e62e77b1aa6e"
+   },
+   "outputs": [],
+   "source": [
+    "df7 = (df6[0:176999]) | (df5[0:176999])\n",
+    "df7.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "ERsufys7wcSg"
-      },
-      "source": [
-        "#df_Ellis.loc[(df_Ellis[\"ellis-cpu.wait_perc\"] > 5) & (df_Ellis[\"ellis-load.avg_1_min\"] > 2)]"
-      ],
-      "execution_count": null,
-      "outputs": []
+    "id": "w6BrDjX4CODn",
+    "outputId": "a6c956e7-6aed-4bdd-f37f-505a994de51a"
+   },
+   "outputs": [],
+   "source": [
+    "df7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/FinalORLabel8.5.csv')\n",
+    "df7.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "wwv2cjFAIFHL"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.insert (7, \"Label\", df7)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "hrPqpjd96I1x"
+   },
+   "outputs": [],
+   "source": [
+    "#df_Ellis.insert (8, \"Label\", df7)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "_zKkQLOz6qPY"
+   },
+   "outputs": [],
+   "source": [
+    "# We applied Logical OR operator in two features only known as  and df3 and df4 and stored result in df6 which is known as Final Label after applying OR condition\n",
+    "df_Ellis\n",
+    "df_Ellis.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 606
      },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "9le7MwnDhlnH"
-      },
-      "source": [
-        "# **Creating New Features**"
-      ]
+    "id": "3rEy1vtp67M9",
+    "outputId": "4e2175cc-dccb-4aaf-a152-e2452de241b0"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.head(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
      },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "090QXGpPlEF6"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+    "id": "11Qu45RY0HNG",
+    "outputId": "305c5dd5-ec61-48a8-abb6-e29bbc4b9e42"
+   },
+   "outputs": [],
+   "source": [
+    "# pandas count distinct values in column\n",
+    "df_Ellis['Label'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "0sB-W_Ny4eHk"
+   },
+   "outputs": [],
+   "source": [
+    "#final.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/FinalLabel.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ERsufys7wcSg"
+   },
+   "outputs": [],
+   "source": [
+    "#df_Ellis.loc[(df_Ellis[\"ellis-cpu.wait_perc\"] > 5) & (df_Ellis[\"ellis-load.avg_1_min\"] > 2)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "9le7MwnDhlnH"
+   },
+   "source": [
+    "# **Creating New Features**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "090QXGpPlEF6"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "FeatureCreation.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/LSTM.ipynb b/models/failure_prediction/jnotebooks/LSTM.ipynb

index 1f331f0..15d23e0 100644 (file)
--- a/models/failure_prediction/jnotebooks/LSTM.ipynb
+++ b/models/failure_prediction/jnotebooks/LSTM.ipynb
@@ -1,1517 +1,818 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mF-r4kHqhhr0"
+   },
+   "source": [
+    "Contributors: Rohit Singh Rathaur, Girish L.\n",
+    "\n",
+    "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
+    "\n",
+    "http://www.apache.org/licenses/LICENSE-2.0\n",
+    "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0lwwYh5Yhk-n"
+   },
+   "source": [
+    "We mounted the drive to access the data from google drive"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "LSTM.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "552d1331-3807-437c-aded-2e495ae0f860"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "mF-r4kHqhhr0"
-      },
-      "source": [
-        "Contributors: Rohit Singh Rathaur, Girish L.\n",
-        "\n",
-        "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
-        "\n",
-        "http://www.apache.org/licenses/LICENSE-2.0\n",
-        "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "0lwwYh5Yhk-n"
-      },
-      "source": [
-        "We mounted the drive to access the data from google drive"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "552d1331-3807-437c-aded-2e495ae0f860"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "OwlM7YM2htFR"
-      },
-      "source": [
-        "We are importing the libraries:\n",
-        "- TensorFlow: to process and train the model\n",
-        "- Matplotlib: to plot the training anf loss curves\n",
-        "- Pandas: used for data analysis and it allows us to import data from various formats\n",
-        "- Numpy: For array computing"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "qlVZPlu-iiYw"
-      },
-      "source": [
-        "We are reading the CSV file using `read_csv` function and storing it in a DataFrame named `df_Ellis`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "06698528-eedb-475b-fa32-e347d03e9980"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 7
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "t5gl1fqmjBdt"
-      },
-      "source": [
-        "`plot()` function is used to draw points"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "547a5311-6db3-42b6-d5bd-3bc171446eac"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7fbb837d7f90>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 8
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "KYRyARNcjJkz"
-      },
-      "source": [
-        "Using multivariate features:\n",
-        "- Storing only the multivariate features in a dataframe named `features_3`\n",
-        "- Extracting the Timestamp column from `df_Ellis` dataframe\n",
-        "- and combining it with the dataframe `features`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "8bb3a951-1f2d-4f40-aa40-668e00bdc238"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.system_perc', 'ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-mem.free_mb', 'ellis-net.in_bytes_sec', 'ellis-net.out_packets_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.system_perc  ...  Label\n",
-              "Timestamp                               ...       \n",
-              "14-09-2016 0:00                    0.5  ...      1\n",
-              "14-09-2016 0:00                    0.4  ...      1\n",
-              "14-09-2016 0:01                    0.4  ...      1\n",
-              "14-09-2016 0:01                    0.4  ...      1\n",
-              "14-09-2016 0:02                    0.5  ...      1\n",
-              "\n",
-              "[5 rows x 7 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 9
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "jO-JgNPQj99-"
-      },
-      "source": [
-        "Plotted features"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 437
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "3a6ee243-5136-4614-93e6-8c2f7f4c13af"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fbb836b5d10>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb83221150>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb836b5690>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb8318f890>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb83146c50>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb830fefd0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fbb830c3490>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 10
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 7 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "9337b00a-1d3f-4dbc-91d5-2f445eda21e5"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 7)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "vOzDoRCrlTBc"
-      },
-      "source": [
-        "We spliited the multivariate data in tarining and validation and printed the shape of that data."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "73165ad2-6043-42c9-ed7d-ff050af74e34"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 7) (140880,)\n",
-            "(34608, 120, 7) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "YU_j8yNblhOO"
-      },
-      "source": [
-        ""
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "QialFchyl9Rt"
-      },
-      "source": [
-        "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
-        "- Creating a source dataset from our input data.\n",
-        "- Applied dataset transformations to preprocess the data.\n",
-        "- Iterate over the dataset and process the elements.\n",
-        "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
-        "Once we have a dataset, we can apply transformations to prepare the data for our model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "08bfc16c-0e6b-43d8-8fa3-97b84c124bfb"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 7), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 7), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "F-ntkTP2njMy"
-      },
-      "source": [
-        "We used a custom loss function to evaluate the model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "kTwy7LdqoGpM"
-      },
-      "source": [
-        "We are building a single step LSTM model for training data with dropout 0.3 and we used ADAM optimizers."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "f6ec7f52-8cf8-4e81-82c8-8ca59e89f429"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "from keras.utils.vis_utils import plot_model\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "single_step_model.summary()\n",
-        "plot_model(single_step_model, to_file='/content/drive/MyDrive/Failure/lstm/LSTM.png', show_shapes=True, show_layer_names=True)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 9s 136ms/step - loss: 0.0899 - rmse: 0.1852 - val_loss: 0.0184 - val_rmse: 0.0281\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0069 - rmse: 0.0119 - val_loss: 0.0130 - val_rmse: 0.0175\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 6s 125ms/step - loss: 0.0047 - rmse: 0.0078 - val_loss: 0.0058 - val_rmse: 0.0093\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 6s 124ms/step - loss: 0.0034 - rmse: 0.0046 - val_loss: 0.0103 - val_rmse: 0.0105\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 6s 127ms/step - loss: 0.0083 - rmse: 0.0106 - val_loss: 0.0089 - val_rmse: 0.0089\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0057 - rmse: 0.0070 - val_loss: 0.0018 - val_rmse: 0.0021\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 6s 125ms/step - loss: 0.0039 - rmse: 0.0044 - val_loss: 0.0052 - val_rmse: 0.0054\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 6s 124ms/step - loss: 0.0038 - rmse: 0.0041 - val_loss: 0.0036 - val_rmse: 0.0038\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 6s 127ms/step - loss: 0.0035 - rmse: 0.0038 - val_loss: 0.0035 - val_rmse: 0.0038\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0033 - rmse: 0.0039 - val_loss: 0.0015 - val_rmse: 0.0021\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 6s 125ms/step - loss: 0.0069 - rmse: 0.0082 - val_loss: 0.0030 - val_rmse: 0.0033\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0057 - rmse: 0.0083 - val_loss: 0.0044 - val_rmse: 0.0046\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0061 - rmse: 0.0073 - val_loss: 0.0109 - val_rmse: 0.0110\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 6s 125ms/step - loss: 0.0071 - rmse: 0.0088 - val_loss: 9.9332e-04 - val_rmse: 0.0014\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0031 - rmse: 0.0034 - val_loss: 0.0026 - val_rmse: 0.0028\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 6s 127ms/step - loss: 0.0030 - rmse: 0.0031 - val_loss: 0.0032 - val_rmse: 0.0034\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0029 - rmse: 0.0031 - val_loss: 0.0026 - val_rmse: 0.0028\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 6s 128ms/step - loss: 0.0028 - rmse: 0.0030 - val_loss: 0.0030 - val_rmse: 0.0032\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 6s 126ms/step - loss: 0.0028 - rmse: 0.0031 - val_loss: 0.0021 - val_rmse: 0.0024\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 6s 127ms/step - loss: 0.0026 - rmse: 0.0029 - val_loss: 0.0027 - val_rmse: 0.0030\n",
-            "Model: \"sequential\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "lstm (LSTM)                  (None, 32)                5120      \n",
-            "_________________________________________________________________\n",
-            "dense (Dense)                (None, 1)                 33        \n",
-            "=================================================================\n",
-            "Total params: 5,153\n",
-            "Trainable params: 5,153\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
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\n",
-            "text/plain": [
-              "<IPython.core.display.Image object>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 17
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ch-I96MromT8"
-      },
-      "source": [
-        "We defined the `plot_loss` function to plot the train and test loss"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "c8794bd3-d704-4244-8f32-7be7d73f0890"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "06250b6b-9899-4eb1-af6c-14afd3ae70f8"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tBNraVXSqqfH"
-      },
-      "source": [
-        "We defined a function `create_time_steps` to create time steps and function `plot_time_series` to plot the time series data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "kX1mtI44q4U7"
-      },
-      "source": [
-        "We plotted the time series and predicted values"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "xFJT1rZDAUVL",
-        "outputId": "37fe707b-40d1-476b-c668-631789537c57"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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LRxmZk1s3olD0m7SnpS0tL05xcesSdpT0nzJRVJWiRpfM620yUtkFQs6XFJ3dL1V0l6O92nSNLInH0uk7RM0hJJx9Yn/hpdemnNLYoRI5JyZmZtSH1bHhOApyOiH/B0+r6i1cAhEVEAHAxMkNRLUgfgJmBEROQDxcCFOftNioiC9PVXAEkDgDHAQODrwH9L8tebzcyaWH2Txyhgaro8FTipYoGI2BQRn6Zvt885ptLXTpIEdAZW1eJ490TEpxHxOrAMOKh+p2BmZlnVN3n0iIiyW2veAXpUVkjS7pKKgZXALyNiVUSUAhcAC0iSxgDg9zm7XZh2Z03J6Q7bLa2jzFvpusqOeZ6kuZLmrlmzpq7nZ2ZmlagxeUh6StLCSl6jcstFcttWpbduRcTKtGtqb2CcpB6S8kiSx2CgF0m31WXpLrcCewEFJN1eN2Y9sYi4LSIKI6Kwe/fuWXffyvJ1y/neo9+j8y860+7qdnT+RWe+9+j3WL5ueb3qNTNrrWpMHhFxVETsV8nrIeBdST0B0p/v1VDXKmAhMJwkMRARy9PEMx04NF33bkRsjogtwO/4vGvqbWD3nCp7p+sazWNLHyN/cj63z7+dkk0lBEHJphJun387+ZPzeWzpY3WuWxJnnnlm+fvPPvuM7t27c/zxx2eqp0+fPrz//vt1KtOnTx/2339/8vPzOeaYY3jnnXcyHTtXxYkcK1q1ahWjR48GoKioiL/+9a+Zj3H44YdT8bZrM2t69e22ehgYly6PAx6qWEBSb0k7pMtdgGHAEpIP/QGSypoFRwOL03I9c6o4mSThlB1vjKTtJfUF+gGVf/W5ASxft5zR943mk9JPKN1SutW20i2lfFL6CaPvG13nFshOO+3EwoUL2bBhAwBPPvkku+1WaS9co5o5cybFxcUUFhZy3XXXbbUtIraapqQ+evXqVT6jb12Th5m1DPVNHhOBoyUtBY5K3yOpUNLtaZn+wIuSXgGeAW6IiAVpK+RqYHY6HlIAlH1yXV92Cy8wArgYICIWkbRQXgUeB74fEY02//eNz99I6ebSasuUbi5l0guT6nyMkSNH8uijjwJw9913c/rpp5dvW7duHSeddBL5+fkMHTqU4uJiIHmQ1DHHHMPAgQM599xzyf2iZ32mRz/ssMNYtmwZK1asYN999+Wss85iv/32Y+XKlfzqV79iyJAh5Ofnc+WVV5bvc+2117LPPvswbNgwlixZUr5+2bJlHHXUUQwaNIgDDjiA5cuXs2LFCvbbbz82bdrEFVdcwb333ktBQQH33nsvH3/8Meeccw4HHXQQgwcP5qGHkr9DNmzYwJgxY+jfvz8nn3xyeaI1s+ZVr+QREWsj4siI6Jd2b61L18+NiHPT5ScjIj8iBqU/b8vZf3JE9E/XnxARa9P1YyNi/3T9iTmD8kTEtRGxV0TsGxF17zOqhTuL7/xCi6Oi0i2l3FF8R52PMWbMGO655x42btxIcXExBx98cPm2K6+8ksGDB1NcXMx1113HWWedBcDVV1/NsGHDWLRoESeffDJvvvkmkG2q9sr85S9/Yf/99wdg6dKlfO9732PRokUsWbKEpUuXMmfOHIqKipg3bx6zZ89m3rx53HPPPeWtiJdyvix5xhln8P3vf59XXnmF5557jp49P29MbrfddlxzzTWcdtppFBUVcdppp3HttddyxBFHMGfOHGbOnMmPf/xjPv74Y2699VZ23HFHFi9ezNVXX10+L5eZNS/PqluN9ZvWN2i5yuTn57NixQruvvtuRo4cudW2v//979x///0AHHHEEaxdu5aPPvqI2bNn88ADDwDwjW98gy5dkpvR6jo9+ogRI2jfvj35+fn8/Oc/58MPP2TPPfdk6NChADzxxBM88cQTDB48ODnf9etZunQpJSUlnHzyyey4444AnHjiiQCUlJTw9ttvc/LJJwPJLLw1eeKJJ3j44YfLx0w2btzIm2++yezZs7nooovKr1V+fn6NdZlZ43PyqEan7TpRsqmkVuXq48QTT+RHP/oRs2bNqvaBTTWp6/ToM2fOpFu3buXvP/zww62mho8ILrvsMs4///yt9vvNb35T51grigjuv/9+9t133war08waj+e2qsaZ+WeS1y6v2jJ57fIYmz+2Xsc555xzuPLKK8u7jMoMHz68vNtp1qxZdOvWjc6dO3PYYYdx1113AfDYY4/xwQcfAI03Pfqxxx7LlClTWL8+aWG9/fbbvPfeexx22GE8+OCDbNiwgZKSEh555BEgmd69d+/ePPjggwB8+umnfPLJJ1vVWXEK+GOPPZabb765fPzm5ZdfBtjqXBcuXFg+7mNmzcvJoxqXHHIJee1rSB7t87h4aPWPba1J7969y7tmcl111VXMmzeP/Px8JkyYwNSpyZf5r7zySmbPns3AgQN54IEH2GOPPYDGmx79mGOO4dvf/jaHHHII+++/P6NHj6akpIQDDjiA0047jUGDBnHccceVd5cB3HHHHfz2t78lPz+fQw899Au3AI8YMYJXX321fMD88ssvp7S0lPz8fAYOHMjll18OwAUXXMD69evp378/V1xxBQceeGC9z8fM6s9TstfgsaWPMfq+0ZRuLt1q8DyvXR557fOYccoMjut3XIPHbNl4Snazhucp2evhuH7HUTy+mPMOPI/O23emndrRefvOnHfgeRSPL3biMLM2yQPmtbDXrntxy8hbuGXkLc0diplZi9CmWx5tocuuLfC/o1nTa7PJo2PHjqxdu9YfPK1cRLB27dpafZfEzBpOm+226t27N2+99Raerr3169ixI717927uMMzalDabPPLy8ujbt29zh2Fm1iq12W4rMzOrOycPMzPLzMnDzMwyc/IwM7PMnDzMzCwzJw8zM8vMycPMzDJz8jAzs8ycPMzMLDMnDzMzy8zJw8zMMnPyMDOzzJw8zMwsMycPMzPLzMnDzMwyc/IwM7PMnDzMzCwzJw8zM8vMycPMzDJz8jAzs8ycPMzMLDMnDzMzy8zJw8zMMnPyMDOzzOqVPCTtKulJSUvTn10qKbOnpPmSiiQtkjQ+Z9vpkhZIKpb0uKRu6fqrJL2d7lMkaWS6vo+kDTnrJ9cnfjMzq5v6tjwmAE9HRD/g6fR9RauBQyKiADgYmCCpl6QOwE3AiIjIB4qBC3P2mxQRBenrrznrl+esH4+ZmTW5+iaPUcDUdHkqcFLFAhGxKSI+Td9un3NMpa+dJAnoDKyqZzxmZtYE6ps8ekTE6nT5HaBHZYUk7S6pGFgJ/DIiVkVEKXABsIAkaQwAfp+z24Vpd9aUCt1hfSW9LOkZScOrCkzSeZLmSpq7Zs2aepyimZlVVGPykPSUpIWVvEbllouIAKKyOiJiZdo1tTcwTlIPSXkkyWMw0Iuk2+qydJdbgb2AApJurxvT9auBPSJiMPD/gLskda7imLdFRGFEFHbv3r2m0zQzsww61FQgIo6qapukdyX1jIjVknoC79VQ1ypJC4HhwBvpuuVpXdNJx0wi4t2cY/wO+Eu6/lPg03R5nqTlwD7A3JrOw8zMGk59u60eBsaly+OAhyoWkNRb0g7pchdgGLAEeBsYIKmsWXA0sDgt1zOnipOBhen67pLap8tfBfoBr9XzHMzMLKMaWx41mAhMl/QdkpbEqQCSCoHxEXEu0B+4UVKQDJDfEBEL0nJXA7Mllab7n53We72kApJusBXA+en6w4Br0vJb0mOsq+c5mJlZRkqGKrZthYWFMXeue7bMzLKQNC8iCivb5m+Ym5lZZk4eZmaWmZOHmZll5uRhZmaZOXmYmVlmTh5mZpaZk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZebkYWZmmTl5mJlZZk4eZmaWmZOHmZll5uRhZmaZOXmYmVlmTh5mZpaZk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZebkYWZmmTl5mJlZZk4eZmaWmZOHmZll5uRhZmaZOXmYmVlmTh5mZpaZk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZVav5CFpV0lPSlqa/uxSSZk9Jc2XVCRpkaTxOdtOl7RAUrGkxyV1y9n2A0n/TPe5Pmf9ZZKWSVoi6dj6xG9mZnVT35bHBODpiOgHPJ2+r2g1cEhEFAAHAxMk9ZLUAbgJGBER+UAxcCGApBHAKGBQRAwEbkjXDwDGAAOBrwP/Lal9Pc/BzMwyqm/yGAVMTZenAidVLBARmyLi0/Tt9jnHVPraSZKAzsCqdNsFwMSy/SLivZzj3RMRn0bE68Ay4KB6noOZmWVU3+TRIyJWp8vvAD0qKyRpd0nFwErglxGxKiJKSZLEApKkMQD4fbrLPsBwSS9KekbSkHT9bmkdZd5K11V2zPMkzZU0d82aNfU4RTMzq6jG5CHpKUkLK3mNyi0XEQFEZXVExMq0a2pvYJykHpLySJLHYKAXSbfVZekuHYBdgaHAj4Hpaeuk1iLitogojIjC7t27Z9nVzMxq0KGmAhFxVFXbJL0rqWdErJbUE3ivqrJpXaskLQSGA2+k65andU3n8zGTt4AH0oQ0R9IWoBvwNrB7TpW903VmZtaE6ttt9TAwLl0eBzxUsYCk3pJ2SJe7AMOAJSQf+gMklTULjgYWp8sPAiPSffYBtgPeT483RtL2kvoC/YA59TwHMzPLqMaWRw0mknQpfYekJXEqgKRCYHxEnAv0B26UFCQD5DdExIK03NXAbEml6f5np/VOAaakrZRNwLi0FbIobaG8CnwGfD8iNtfzHMzMLCMln8nbtsLCwpg7d25zh2Fm1qpImhcRhZVt8zfMzcwsMycPMzPLzMnDzMwyc/IwM7PMnDzMzCwzJw8zM8vMycPMzDJz8jAzs8ycPMzMLDMnDzMzy8zJw8zMMnPyMDOzzJw8zMwsMycPMzPLzMnDzMwyc/IwM7PMnDzMzCwzJw8zM8vMycPMzDJz8jAzs8ycPMzMLDMnDzMzy8zJw8zMMnPyMDOzzJw8zMwsMycPMzPLzMnDzMwyc/IwM7PMnDzMzCwzJw8zM8vMycPMzDJz8jAzs8ycPMzMLDMnDzMzy6xeyUPSrpKelLQ0/dmlkjJ7SpovqUjSIknjc7adLmmBpGJJj0vqlrPtB5L+me5zfbquj6QNaV1FkibXJ34zM6ub+rY8JgBPR0Q/4On0fUWrgUMiogA4GJggqZekDsBNwIiIyAeKgQsBJI0ARgGDImIgcENOfcsjoiB9jcfMzJpcfZPHKGBqujwVOKligYjYFBGfpm+3zzmm0tdOkgR0Blal2y4AJpbtFxHv1TNOMzNrQPVNHj0iYnW6/A7Qo7JCknaXVAysBH4ZEasiopQkSSwgSRoDgN+nu+wDDJf0oqRnJA3Jqa6vpJfT9cPrGb+ZmdVBjclD0lOSFlbyGpVbLiICiMrqiIiVadfU3sA4ST0k5ZEkj8FAL5Juq8vSXToAuwJDgR8D09PWyWpgj4gYDPw/4C5JnauI+zxJcyXNXbNmTY0XwszMaq9DTQUi4qiqtkl6V1LPiFgtqSdQbfdSRKyStBAYDryRrlue1jWdz8dM3gIeSBPSHElbgG4RsQYo68qaJ2k5SStlbiXHug24DaCwsLDSpGZmZnVT326rh4Fx6fI44KGKBST1lrRDutwFGAYsAd4GBkjqnhY9GlicLj8IjEj32QfYDnhfUndJ7dP1XwX6Aa/V8xzMzCyjGlseNZhI0qX0HZKWxKkAkgqB8RFxLtAfuFFSkAyQ3xARC9JyVwOzJZWm+5+d1jsFmJK2UjYB4yIiJB0GXJOW35IeY109z8HMzDJS0jO0bSssLIy5c7/Qs2VmZtWQNC8iCivb5m+Ym5lZZk4eZmaWmZOHmZll5uRhZmaZOXmYmVlmTh5mZpaZk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZebkYWZmmTl5mJlZZk4eZmaWmZOHmZll5uRhZmaZOXmYmVlmTh5mZpaZk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZebkYWZmmTl5mJlZZk4eZmaWmZOHmZll5uRhZmaZOXmYmTWE66+HmTOrLzNzZlJuG+DkYWbWEIYMgVNPrTqBzJyZbB8ypGnjaiROHmZmDWHECJg+vfIEUpY4pk9Pym0DOjR3AE3hvZJPuevFNwX0YnAAAAq9SURBVPngk00M/WpXAF54bS1ddtyODz7ZVOXPLGWbap+WGJPPo2XF5POovuzQr3blwD27NMAnSyVyE0hZotgGEweAIqK5Y2h02/fsFz3H/QYApetqc9ZZyjbVPi0xprrs0xJjqss+LTGmuuzTEmOqyz61Kdsxrx3Tzh3aeAkEPk8YF1wAt97aahOHpHkRUVjZtjbXbRXU/j9ulrJNtU9LjKku+7TEmOqyT0uMqS77tMSY6rJPbcqWfraFF15bmzGKjEaMSBLHz36W/GyFiaMmbSp5tBNs115s16Fd+Ymrip9ZyjbVPi0xJp9Hy4rJ51F92XaCvA7tyru3Gs3MmUmL4/LLk5813YXVCtVrzEPSrsC9QB9gBXBqRHxQocyewJ9JElUecHNETE63nQ78hOSPhVXAmRHxvqR7gX3TKnYBPoyIgnSfy4DvAJuBiyLibzXF2aNzR647ef9toh+4Jcbk82hZMfk8mnHMA744xjFihMc8vrCzdD2wLiImSpoAdImI/6hQZrv0OJ9K6gQsBA4F3iNJGAPShHE98ElEXFVh/xuB/4uIayQNAO4GDgJ6AU8B+0TE5uriLCwsjLlz59b5PM3MaqWqwfFWOmjemGMeo4Cp6fJU4KSKBSJiU0R8mr7dPueYSl87SRLQmSSZ5AYu4FSShFF2vHsi4tOIeB1YRpJIzMyaV3UJorrbeFup+iaPHhGxOl1+B+hRWSFJu0sqBlYCv4yIVRFRClwALCBtgQC/r7DrcODdiFiavt8traPMW+k6M7Pm9dJL1bcsyhLISy81bVyNpMYxD0lPAV+pZNNPc99EREiqtA8sIlYC+ZJ6AQ9KmgGsI0keg4HXgJuBy4Cf5+x6Op+3OjKRdB5wHsAee+xRlyrMzGrv0ktrLlM2BrINqDF5RMRRVW2T9K6knhGxWlJPknGM6upaJWkhSYvijXTd8rSu6cCEnLo7AN8EDsyp4m1g95z3vdN1lR3rNuA2SMY8qovLzMyyqW+31cPAuHR5HPBQxQKSekvaIV3uAgwDlpB86A+Q1D0tejSwOGfXo4B/RsRbFY43RtL2kvoC/YA59TwHMzPLqL7Tk0wEpkv6DklL4lQASYXA+Ig4F+gP3Jh2aQm4ISIWpOWuBmZLKk33Pzun7jFU6LKKiEVpC+VV4DPg+zXdaWVmZg2vTUxPIqmEpLXTWnQD3m/uIGqpNcUKrSve1hQrtK54W1Os0Hzx7hkR3Svb0CYmRgSWVHWvckskaW5ribc1xQqtK97WFCu0rnhbU6zQMuNtU9OTmJlZw3DyMDOzzNpK8rituQPIqDXF25pihdYVb2uKFVpXvK0pVmiB8baJAXMzM2tYbaXlYWZmDcjJw8zMMtvmkoekUyQtkrQl/bJi2fqjJc2TtCD9eUTOtgPT9csk/TadzbfZYk23XZbGs0TSsTnrv56uW5ZOg98sJBVIekFSkaS5kg5K1yu9hsskFUs6oLlizCXpB5L+mV7v63PWV3qdWwJJl0gKSd3S9y3u2kr6VXpdiyX9WdIuOdta5LVtKb9DlUknkZ0p6dX0/+q/p+t3lfSkpKXpz0Z8IEktRcQ29SL5Rvu+wCygMGf9YKBXurwf8HbOtjnAUJJvwD8GHNfMsQ4AXiGZwr4vsBxon76WA18FtkvLDGim6/xE2XUCRgKzcpYfS6/lUODFFvB/YgTJs1+2T99/ubrr3NzxprHtDvyNZOaFbi342h4DdEiXf0kya3aLvbYt6Xeoivh6AgekyzsD/5tey+uBCen6CWXXuTlf21zLIyIWR8QXvk0eES9HRNnzQhYBO6RzZPUEOkfEC5H8y/yJSp5L0pSxUvVzSw4ClkXEaxGxCbgnLdscguQZLABf4vNnsYwC/hSJF4Bd0mvcnC4AJkb6XJmIKJvAsyU/H2YScClbP5K7xV3biHgiIj5L375AMlkptNxr25J+h74gIlZHxPx0uYRkvr/dqMWzk5raNpc8aulbwPz0w2Q3kueClGkJzwip6rklLel5Jj8EfiVpJXADyXT60LJiLLMPMFzSi5KekTQkXd8SY0XSKJKW8SsVNrXIeHOcQ9IygpYba0uN6wsk9SHpMXmRWj47qSm1yulJqnvGSER8YWbfCvsOJGleH9MYsVVyvDrH2txqeJbLkcDFEXG/pFNJHuRV5fT9ja2GWDsAu5J09Qwhmczzq00Y3hfUEO9PaKL/n7VRm//Dkn5KMlnptKaMbVul5JHd9wM/jIiPcodhI6p+dlJTapXJI6p5xkh1JPUG/gycFelzREimhu+dU6zKZ4TURR1jre65JbV6nklDqC52SX8C/j19ex9we7pc62euNKQaYr0AeCDtlpwjaQvJRHPNEitUHa+k/UnGCF5JPzB6A/PTGxJa3LUFkHQ2cDxwZHqNoRmvbQ1aalzlJOWRJI5pEfFAujrTs5OaQpvptkrvAnmUZNDpH2Xr06bgR5KGpndZnUUlzyVpYlU9t+QloJ+kvpK2I5m2/uFminEV8K/p8hFA2aOCHwbOSu8MGgr8X05zu7k8SDJojqR9SAZK36cFPh8mIhZExJcjok9E9CHpVjkgIt6hBV5bSV8nGZs5MSI+ydnU4q5tqiX9Dn1B+hn0e2BxRPw6Z1ONz05qcs09Yt/QL+Bkkl+4T4F3gb+l6/8T+BgoynmV3XVTCCwkuQvjFtJv3jdXrOm2n6bxLCHn7i+SO27+N93202a8zsOAeSR3q7wIHJiuF/BfaXwLyLmLrBlj3Q64M/03ng8cUdN1bikvYAWf323VEq/tMpIxhLLfqckt/dq2lN+hKmIbRnKTRHHONR0JdAWeJvkj7Slg1+aO1dOTmJlZZm2m28rMzBqOk4eZmWXm5GFmZpk5eZiZWWZOHmZmlpmTh5mZZebkYVYFSV3TKeeLJL0j6e10eb2k/27E4w5N5+EqkrRY0lXp+sMlHdpYxzXLolVOT2LWFCJiLVAAkH6Ar4+IG5rg0FOBUyPiFUntSabtBzgcWA881wQxmFXLLQ+zjNIWwF/S5askTZX0rKQ3JH1T0vVKHi72eDpPUdkDx55R8iCyv9UwlfqXgdUAEbE5Il5NZ1gdD1yctkiGS+ou6X5JL6Wvr+XEdIek59OHB323Ma+HtU1OHmb1txfJ/F4nkkyDMjMi9gc2AN9IE8jNwOiIOBCYAlxbTX2TgCVKnsx3vqSOEbECmAxMioiCiHgWuCl9P4TkMQO359SRn8Z0CHCFpF4NeL5m7rYyawCPRUSppAUkT6p7PF2/AOhD0u20H/BkOlNue9KWRWUi4hpJ00imZf82cDpJl1VFRwEDcqbr7pxO5Q3wUERsADZImknyEKQH63qCZhU5eZjVX9kTCrdIKo3PJ4zbQvI7JmBRRBxS2wojeWTArZJ+B6yR1LWSYu2AoRGxMXdlmkwqTlrnSeysQbnbyqzxLQG6SzoEkuc1pA8lq5Skb+jz5kQ/YDPwIVBC8lzrMk8AP8jZryBn2yhJHdOkczjJVORmDcbJw6yRRfKs7NHALyW9QjLNdnW33I4lGfMoAu4AzoiIzcAjwMllA+bARUChpGJJr5IMqJcpBmaSPFf8ZxGxCrMG5CnZzbYxTXxbsbVRbnmYmVlmbnmYNRNJ/wV8rcLqmyLiD80Rj1kWTh5mZpaZu63MzCwzJw8zM8vMycPMzDJz8jAzs8z+P0S47FDszZuCAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "5ghCNUvcrBMi"
-      },
-      "source": [
-        "We splitted the data in the form of training and validation for multistep forcasting:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Lu7m2Rr4AbMK",
-        "outputId": "4aeabbf6-4ca3-4340-d1b1-e94ad1f78faf"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 7)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Rv5mugNBrVdY"
-      },
-      "source": [
-        "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
-        "- Creating a source dataset from our input data.\n",
-        "- Applied dataset transformations to preprocess the data.\n",
-        "- Iterate over the dataset and process the elements.\n",
-        "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
-        "Once we have a dataset, we can apply transformations to prepare the data for our model:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "fjXexah9C8yg",
-        "outputId": "13cf8949-9ebc-4ea9-b5ac-f33c6e146a00"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 7), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 7), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "gMIQq83Ercb2"
-      },
-      "source": [
-        "We created a `multi_step_plot` function to plot between `history` and `true_future` data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "id": "7mtLZ6S-DPU-",
-        "outputId": "eadda952-c8bc-4b54-e55f-0500d73115c1"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAscAAAFwCAYAAABU0dZ+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9eZQdV33v+901nKkHzZJHDZYxIGNZnjEGIiCQdROGmwc8SASxIYnirEt44cHj5cZ35XLz8AtkcfFLSIKf1r0Ol9AJIQ6QcHlhNG0bD8iSLeNBtpEstWZL6pbUfbrPUMN+f1TtOnVO17Brru7en7W82qpzTp06Nf72b39/3x+hlEIgEAgEAoFAIBAAUtEbIBAIBAKBQCAQlAURHAsEAoFAIBAIBDYiOBYIBAKBQCAQCGxEcCwQCAQCgUAgENiI4FggEAgEAoFAILARwbFAIBAIBAKBQGBTuuCYEHIfIeQ0IeTZFNb1FkLIPtd/bULIv+f87HsIIT+3P7eHEPJGn/f9BiHkGfu93yOErHa99geEkBcIIc8RQv7cXlYhhPyt/ZmnCSHbXe//nr3sOULIvYQQOeEuYOs8Twj5n0nXJRAIBAKBQLDYIWXzOSaEvBlAE8BXKaWvS3G9KwEcAHAZpXSO4/3DAGYppZQQshXANyilrxl4jwLgBIAtlNKzdgA8Ryn9DCHkLQDuAvBrlNIOIWQtpfQ0IeQ/ALiRUvoRQshaAP8G4CZKqUkIGaWUThNCCID7AfwTpfTrCX/32wA0APwepfSdSdYlEAgEAoFAsNgpXeaYUvoQgCn3MkLIZjsDupcQ8jAh5DU+Hw/ifQD+jScwtrejSXsjhyEAXqMIYv83ZAe0o7CCZQD4fQCfo5R27PWdtpdvAfCAa9l5ADfa/56236MAqLDvTPL7KaU/BjDD+36BQCAQCASCpUzpgmMfdgH4A0rpDQA+BeBvYqzjgwD+IcoHCCG/Tgh5AcB3AXx08HVKqQYrCH4GdgYZwH+3X74KwJsIIT8jhDxICLnJXv40gHcTQhRCyCYANwC43PWd3wdwGlZAe7+9OI3fLxAIBAKBQCAIQSl6A8Kw5Q1vAPBPVnIWAFC1X/tfAPypx8eOU0p/xbWOiwFcA+D7rmV/BuBdHp/9NqX0PwEApfRbAL5lSz3+LwC/PLBtKqzg+DoALwP4EoD/COCzsPbtSgCvB3ATgG8QQq4AcB+A1wLYA2ACwKMADLZOSumvEEJqAMYAvJUQ8ljS3y8QCAQCgUAg4KP0wTGs7PZ5Sum2wRcopd8E8E2OdfyvAL5lZ3rZZ/8jrEA2FErpQ4SQKwghqymlZ10vbbNfPwgAhJBvAPgj+7VjAL5pSzN2E0JMAKsppWcAfIKtgBDyKICXBr6vTQj5FwDvAfAzJP/9AoFAIBAIBAIOSi+rsHW4hwgh7wcAYnFtxNX8BqJLKq60dcQghFwPK1s7OfC24wC2EELW2P9+O4D99v9/G8Bb7M9fBUtDfJYQ0iCEDNnL3w5Ap5Q+TwgZtjPcrNDv1wC8kNLvFwgEAoFAIBBwULrMMSHkHwBsB7CaEHIMwH8GsAPAlwkh/wmACuDrsLS7POvbCEvT+2DETXkvgN8ihGgAWgA+wAr0CCH7KKXbKKUnCCH/BcBD9vsmANxhf/4+APfZlnRdALfbzhdrAXzfziQfB/Bh+/1DAP6VEFKFNWj5CYB77deS/P6HAbwGwLC9P3+bUvr9kI8JBAKBQCAQLElKZ+UmEAgEAoFAIBAURellFQKBQCAQCAQCQV6I4FggEAgEAoFAILApleZ49erVdOPGjYV89+zsLIaGhgr57qWI2N/5IvZ3/oh9ni9if+eL2N/5I/Z5+uzdu/cspXTN4PJSBccbN27Enj17Cvnu8fFxbN++vZDvXoqI/Z0vYn/nj9jn+SL2d76I/Z0/Yp+nDyFkwmu5kFUIBAKBQCAQCAQ2IjgWCAQCgUAgEAhsRHAsEAgEAoFAIBDYlEpz7IWmaTh27Bja7Xam37Ns2TLs378//I2LmFqthssuuwyqqha9KQKBQCAQCASFUPrg+NixYxgZGcHGjRthd3POhJmZGYyMjGS2/rJDKcXk5CSOHTuGTZs2Fb05AoFAIBAIBIVQellFu93GqlWrMg2MBQAhBKtWrco8Qy8QCAQCgUBQZkofHAMQgXFOiP0sEAgEAoFgqbMgguOiGR4e7vv3V77yFXzsYx8DANx777346le/6vvZ8fFxPProo5lun0AgEAgEAoEgHUqvOS47d955Z+Dr4+PjGB4exhve8Abudeq6DkURh0YgEAgEAoEgb0TmOCGf+cxn8IUvfAEA8Jd/+ZfYsmULtm7dig9+8IM4fPgw7r33Xtxzzz3Ytm0bHn74YRw+fBhvfetbsXXrVrztbW/DkSNHAAB33HEH7rzzTtxyyy349Kc/jVe96lU4c+YMAMA0TVx55ZXOvwUCgUAgEAgE2bCg0pP/5TvP4fkT06muc8slo/jP77o68D2tVgvbtm1z/j01NYV3v/vd8973uc99DocOHUK1WsX58+exfPly3HnnnRgeHsanPvUpAMC73vUu3H777bj99ttx33334eMf/zi+/e1vA7CcOR599FHIsoxly5ZhbGwMf/iHf4gf/ehHuPbaa7Fmzbz23wKBQCAQCASCFBGZYw7q9Tr27dvn/Penf/qnnu/bunUrduzYga997Wu+sojHHnsMv/mbvwkA+PCHP4yf/vSnzmvvf//7IcsyAOCjH/2oo2W+77778JGPfCTNnyQQCAQCD37xykzRmyAQCApmQWWOwzK8RfPd734XDz30EL7zne/g7rvvxjPPPBPp80NDQ87/X3755Vi3bh0eeOAB7N69G2NjY2lvrkAgEAhcPHv8At75pZ/i2//hNmy7fHnRmyMQCApCZI5TwjRNHD16FG95y1vw+c9/HhcuXECz2cTIyAhmZnqZiDe84Q34+te/DgAYGxvDm970Jt91/s7v/A4+9KEP9WWUBQKBQJANU7NdAMDE5GzBWyIQCIpEBMcpYRgGPvShD+Gaa67Bddddh49//ONYvnw53vWud+Fb3/qWU5D3pS99CX/7t3+LrVu34u/+7u/wF3/xF77rfPe7341msykkFQKBQJADhkkBAGdmOgVviUAgKJIFJasoimaz2ffvO+64A3fccQcAy62C4dYPM6666ir8/Oc/71v2wAMPzHvfV77ylXnLnn76aVx77bV4zWteE32jBQKBQBAJzTABiOBYIFjqiOC4pHzuc5/Dl7/8ZaE1FggEgpwQmWOBQAAIWUVp+aM/+iNMTEzgjW98Y9GbIhAIBEsCzQ6OT4vgWCBY0ojgWCAQCAQCALqQVQgEAojgWCAQCAQCAIDOZBVNERwLBEsZERwLBAKBQABAN6zgeGq2i65uFrw1AoGgKERwLBAsMr6x5yhOXWgXvRkCwYLDMHsB8eSsyB4LBEsVERyHMDk5iW3btmHbtm246KKLcOmllzr/7na7qXzH9u3b8epXv9pZ7/333+/73sOHD+Pv//7vU/leweJjtqPj0/f/HGM/myh6UwSCBYdmZ44BoTsWCJYyiy44HhsDNm4EJMn6m9QJbdWqVdi3bx/27duHO++8E5/4xCecf1cqFei6nsZmY2xszFnv+973Pt/3xQ2ODcNIsnmCBUJLs47zxORcwVsiECw8mJUbAJyeFsGxQLBUWVTB8dgYsHMnMDEBUGr93bkzeYA8yB133IE777wTt9xyCz796U/jM5/5DL7whS84r7/uda/D4cOHAQBf+9rXcPPNN2Pbtm34vd/7Pe4g9Y477ujLIA8PDwOwLN4efvhhbNu2Dffccw++8pWv4GMf+5jzvne+850YHx93PvPJT34S1157LR577LHY2yJYOLS6dnA8JYJjgSAqmktWIYryBIKly6IKju+6C5gbiAnm5qzlaXPs2DE8+uij+OIXv+j7nv379+Mf//Ef8cgjj2Dfvn2QZdm3qceOHTscWcXk5KTvOj/3uc/hTW96E/bt24dPfOITgds4OzuLW265BU8//TRWrVrFvS2ChUtHt4LjI5OzBW+JQLDw0IWsQiAQYJF1yDtyJNryJLz//e+HLMuB7/nxj3+MvXv34qabbgIAtFotrF271vO9Y2NjuPHGG1PdRlmW8d73vjfytvDy4/2v4OCZJna+eXPibRWkQ1uzMl/n5jRMtzWM1tSCt0ggWDjoJgUhwLK6itMzoqhVIFiqLKrgeP16S0rhtTxthoaGnP9XFAWmazqu3bZuqpRS3H777fizP/uzyOt3r9M0Td/iP7/vBoBareYE8Em2xYuObuCPv/UMpma7+K1bN6KmBg8UBPnANMcAcGRyDq+7dFmBWyMQLCx0w4QiEawZrorMsUCwhFlUsoq77wYajf5ljYa1PEs2btyIJ598EgDw5JNP4tChQwCAt73tbbj//vtx+vRpAMDU1BQmvKJ3n3Xu3bsXAPCv//qv0DQNADAyMoKZmZm+9+3btw+maeLo0aPYvXu35/qSbIsX33ryOF6Z7kAzKJ46cj72egTp0nYHx0J3LBBEwjApFEnCmhERHAsES5lFFRzv2AHs2gVs2AAQYv3dtctaniXvfe97MTU1hauvvhp/9Vd/hauuugoAsGXLFnz2s5/FO97xDmzduhVvf/vbcfLkSa51/u7v/i4efPBBp5iOZaq3bt0KWZZx7bXX4p577sFtt92GTZs2YcuWLfj4xz+O66+/3nN9SbZlEMOkuPfBg3jVWqtIcM/hqVjrEaQPk1UAwrFCIIiKZlAoEsHakaooyBMIIsCcwggBFMX6m4ZjWFEsKlkFYAXCWQXDn/nMZzyX1+t1/OAHP/B87QMf+AA+8IEPBK6XuUu4WbduHR5//HHn35///OcBAKqq4oEHHuh7r19hXbPZjLwtPPx/z5zE4ck53Puh63HPD3+B3SI4Lg0tkTkWCGKjmyYUmWDNSBWnpzuglIIQUvRmCQSlhjmFMUMEZoTFHMOA7JOUabOoMseC7KGU4q9/cgCb1wzhHVsuwk2bVuDJiXPQDdFqtQwwWcXq4SqOTAnHCoEgCrpJIduyio5uYqaTjo+9QLCY8XIKY2TlGJY1IjgWROInL57GC6dm8Pvbr4QkEdy0cSVmuwb2n5wJ/7Agc1hw/OqLhoWsQiCIiG6YUGWCtSM1AMLOTSDgIcwRLAvHsKwRwbGAGytrfBCXLq/jPdsuAQDcvGklAOAJIa0oBU5wvG4UJ8630NVFRl8g4EU3qSOrAESXPIGAhzBHsCwcw7JmQQTHlNLwNwkSE7afdx+awt6Jc9j55iugytapc/GyOi5dXhfBcUlgBXlXrRuGSYET51sFb5FAsHDQjZ5bBSC65AkEPHg5hTHycAzLglSCY0LIJwkhlBCy2v73DkLIzwkhzxBCHiWEXBt33bVaDZOTkyJAzhhKKSYnJ1Gr1Xzf8zfjB7F6uIIP3HR53/KbN63EE4enxDEqAS3NgCoTXLHGchIRbaQFAn5003TcKgAhqxAIeHA7hQEA64+Wl2NYFiR2qyCEXA7gHQDcqpJDAH6JUnqOEPLvAOwCcEuc9V922WU4duwYzpw5k3RTA2m324GB4VKgVqvhsssu83zt5TNNPPjSGfwfv/LqeQ0/btq4Et966jgOnZ11gjJBMbQ1AzVFxvqV1jDeaiO9Zt77PvVPT+OSZTX87+94dc5buLB58dQMdv7dHvzz778Bq4erRW+OIGV0g0KWCJbVVagyEV3yBAJOsnQKK4I0rNzuAfBpAP/CFlBKH3W9/jgA74iLA1VVsWnTpvhbx8n4+Diuu+66zL9nofKKrb27fv2Kea/dvMla9sThKREcF0xbM1GryFg7UkVVkTyL8tqagX/ddwK3XLGygC1c2Dxy4CwmJudw/FxLBMeLEN2kUGUJhIgueQLBUiZRcEwIeQ+A45TSpwO8IH8bwL8FrGMngJ2A5e3r5fmbB81ms7DvXgg8e9Yq9Hr25/vQOdqfOaaUYlgFvvP4fqybfZlrfWJ/Z8PhY21AN/HQQw9iVY3iyZeOYHz8dN/+fumcga5h4pWzU+IYROSh56xgafeevTh3MLhlujjH8yWN/X36bBstjWJ8fBw1dPHSxClxDH0Q53f+iH2eH6HBMSHkRwAu8njpLgB/DEtS4ffZt8AKjt/o9x5K6S5YsgvceOONdPv27WGblAnj4+Mo6rsXAvSF08CeJ3DjDdfjOo/s8a1H9+ClV2a496HY39nwj8f2YrnexPbtv4QtE0/g2LkWtm9/c9/+fu4nBwC8iNrQCLZv9700BR58+cXHAExh67XbcMsVqwLfK87xfEljf+/6xeOoGya2b38DvjaxB8fOzWH79jens4GLDHF+54/Y5/kRWpBHKf1lSunrBv8D8DKATQCeJoQchiWdeJIQchEAEEK2AvhvAN5DKZ3M7icI8kCzm3wwl4pBbt64EhOTczg9LTR6g2iGCdPMp1ixrRmoV6yM5vqVQzgyNTevUJI5i3Q0YfMWlYNnrK6Tek7HU5AvzK0CANaMCFmFQLBUie1WQSl9hlK6llK6kVK6EcAxANdTSk8RQtYD+CaAD1NKX0ppWwUFwoIBRfaWz9xk+x2LVtLz+d++/hT+4OtP5fJdLbsgDwDWr6xjrmv02VEZJsXew+cAAG3d8FyHwJvzc12cbXYB9AaLgsUFax8NAGtHqpia64pjLRAsQbLyOf4TAKsA/A0hZB8hZE9G3yPICSc4lrxPmasvGUVdlbHHDrwEFpphYvzFMzh+Lh+/4bZmoqpax2jDqiEAwBFXUd4Lp6Yx09ExVJGdhiECPljWGLAGGYLFh25SKJIVHK8ZqYJSYGq2W/BWCQSCvEktOLYzyGft//8dSukKSuk2+78b0/oeQTHodvaEPTgGUWUJ161fjt2HRObYzfMnpjHXNaCb+WSf2pqBum21t36Vbefm8jpmg5dbN69yGoYI+Dh4etb5f80QwfFiRDcoFLknqwBElzyBIG3GxoDVqwFCrP9Wr7aWlYkF0SFPUDy6ESyrACy/4/2npjHd1vLarNLD9L16TsFUWzMcH+rLVtRBCPrs3HYfnsLFy2q4Ys0wOkJWEYkDInO86GFNQAD0GoE0RR2FQJAWY2PARz4CTLoq0SYngY9+tFwBsgiOOTk900azoxe9GYWhmcEFeYDVKY9SYO+EkFYwWCY9L91iWzNRs2UVVUXGxaM1J3NMKcUTh6Zw08aVqCkS2popuhpG4ODpJqqKtW+zmAmglOLA6aY4JgWim/Mzx6Ior5wcOze3aPXgL56aWbTP0bvuAjSP/Fm3a71WFkRwzMlv/ffd+K8/eLHozSgMw9Ec+2eOr1u/HBIBnjpyPq/NKjWUUuyxb3B5TcO39Z6sArCkFROTlhzgyNQcTs90cNOmlaja7+noi/PhkgUHzjRx1boRANkcz//6g5fwy198EE8I3X5hWG4V1j2ONXkRsory0eoaePsXH8I/7z1W9KZkwl//5AA++Y19RW9GJhw5Eu+1vBHBMSeTs128soRtylgw4FeQBwCNioL1Kxs4cHomr80qNQfPzGJqtouKLDma7axpdY2+9t4bVg7hyJRVDMiCrps3rnTeI4JjPtqagaNTc3j1RVZwbKScOf7y+EH81U8OAAAutIQsqSh0oyerqKkyltXVPrcXQTmYaWtoaQZOL9KsvuWasjjDs/Xr472WN4tz72eAZpiY6y5djaZTkBegOQaAK9cO9xUuLWWY3vi69cuh5aBRNU2Kjm46WWHAyhyfbXbQ1i1JxbK6iletHXbkAR3hWMHF4clZmBR4zUXpZ46/+thhfP57L+C69csBAF0xYCkMS1bRu8cJr+Ny0rLvW61Fev/SXDMYi41f/VXv5ZUKcPfd+W5LECI45kQ36NIOjkN8jhmb1wzj0NnZ3DKlZeaJQ1NYPVzBVetGctHGsSxwn6xipeVYcaZF8cThKdy4YQUkiTiZY+FYwQcb8PUyx+kEx/fvPYY/+Zfn8PYt6/Dn790KQHgoF4ll5dZ7LK4Zri7a7ORChj2LW4v0mawbZmB9z0JlbAz4H/9j/vLhYeC++4AdO/LfJj8W397PiK5hLtoLkQfmtqAGyCoAYPPaYXQNE8dy8vUtM7sPT+HGDSuhylIubhXMt5gV5AHABtvO7cA5Ay+fnXWatbD3CMcKPg6cboIQuDTHyQPY7z17Ep++/2m88crV+NJvXOd0Nuwu4eD4zEwHzxy7UNj364bZlwBYOyoyx2WEZYwXq1f74AzGYuGuu4C5ufnLV60qV2AMiOCYG0tWsXTdKnTThEQAKWSqZ/OaYQBWMLGUOXmhhWPnWrhp00qoMsklG8g63g1qjgHgkRPWuXvTRis4rioicxyFg2eauHR5HcNVBUA6mePPfnc/rr5kGXb91g2oqTIqttRlKcsq/vonB/Dh+35W2Pe7m4AAVub4zExHOIiUDJaoWqyzuZphhiaiFiJ+BXdlKsRjLL69nwGGSUHp4p3C4cHSQIWfLleutYJjdzexpYi7+E2RiSNLyRJ2frplFcsaKpbVVRw4b1m8XXPpMgC9zLFoIc3HgdNNbF4z7GRzkh7Pc7NdHDvXwju3XoxGxQq4K/Y06lKWVZy60Mb5Oa0w20x3ExDA0hy3NAOzS/jeX0YcWcVizRwbizNz7FdwV6ZCPIYIjjlgD6u5RXoh8jA43ejHsrqKNSPVJZ85fuLQFIYqMl578QhUWYJhUpgZB8gsC+yWVQA93fG2y5c72UnHrUJkjkMxTYqXzzZx5dphJ5uTNIDdf3IaALDlklFnGdMYLuXM8eSsJWE4daEYZyB3ExDAklUAwOkl7FRURha7rEIzKeQUCvLGxoCNGwFJsv5m3WQj7PvuvhtoNPqXNRrlKsRjiOCYAyc4XsLZg8HpxiA2rxnq6ya2FHni8BSu37ACiiw5QY+WcQtplgV2u1UAvTbSTFIBwHGrWKwPlzQ5fr6FtmZi85phSBIBIcllFc+dsILjqy9Z5ixjA5elnDk+2+wCQCG2maZJYVIMFOTVAIhGIGWjZUscF+tsbhoFeWNjwM6dwMQEQKn1d+fO7AJknu/bsQPYtQvYsMFqG71hg/XvsumNAREcc8Fsm7q6uWTbxuom/8Vq2bkt3U5fF+Y0vPjKjBOMskFF1kV5bQ9ZBQBsWDk/OHbcKoSsIhQmEWKSIVWSElu5PX9yGhcvq2HlUMVZxs6TbgbnCaUUX999BDMlb+1+tllc5tjLkcfpkie8jktFa5HLKowIySg/vIrf5uay60LH+307dgCHDwOmaf0tY2AMiOCYC7ct2VItytMN/mmezWuGMd3Wl+wDZe+RKVDaC0bVnLSkXgV5AHDblauxfkTCDRtWOMtqipBV8MIkQpvXWMWNskQSNwF57sQFbLl4tG8ZIQQVRcpEVnHsXAt/9M1n8L1nT6W+7rTo6AZm2tb99VQBmWPWErxPVjEiuuSVkblF73OcPHOcd/HbQiq240EExxy4rZUW6zROGJpBI2WOASzZZiC7D52DKhOnqYNqZ6KybiHNNMeDmePbrlyNP72tjiHbaQEAqqIgj5uDZ2axoqFild1OWJFJomPZ1gwcPDOLqy8ZnfdaRZYyGUQxy74yy2imZrvO/xchq3C6gLruc8vqKlSZLNmBfllhz+H2In0ep2Hllnfx20IqtuNBBMccuKfDl6ru2GpnyZ85BrBkdcdPHJ7CNZcuczK47GGrZ6w5Zg+MwYI8L2rCyo2bg7ZTBUOVpUTH8sVTMzBMii0uvXFv3SSTzDEL/Mp8vCebveC4CFkFk8y5M8eSRLB6WHgdlw3Hyq3Eg70k6JzuUEHkXfy2kIrteBDBMQdan6xicV6MYUQpyLt4WQ2NioyDS9Cxoq0Z+Pmx806zDSBHzbGPrMKLqmgCws3BM01nNgRgsor4x7JXjOeROVayyRyzdZY5c8z0xiNVpZDMMZPPDSYB1o6ILnllw5FVLNLnsSWrSJY5zrv4bSEV2/GghL9F4J5CbWlLVXNsco9kCSHYvGZ4SXodP330PDSD4qYNveDYae6QtebYsXLjCI4dt4ryZhLLwLnZLiZnu/2ZYymZrOK5ExcwUlNw2Yr6vNdUWcrkPGHb2ymxTRzLHL/2klFMTOYvyWIFeYPNF9aMVHH8vLByKxNMTtHRTZgmDW1OtdBIq0Pejh35Bqd5f1+WiMwxByJzHN2UnDlWLDVY2+xXresFU2xQkXnm2KN9tB+EEFQVCZ0SZxLLwKBTBQDIcrLM8fMnp7Hl4lEQMv96yqogT18AmWPmcXz1JaM4M9PpK4TOA3Z9DhYeL29UcGGu6/URQUG4n8OLsW5Ci5CMEmSD2PscuPWFSzU41sz+zlFhXLl2GCcutDFbUKeromDnirt4UXEK8rLOHBsgpNdpLYyaKpc6WCoDPacKd+Y4vvTBMCleODnT52/sJquCPEdzXOJA4myzi6oiYfOaYZi053mcF45bxUASoK7Ki9YVYaHiPh6LUVqhGzSxrEKQDBEcc9DVXbKKRXgh8mCYJtQIU1fM9mqpSSu6xnyv1LzaArc1A3VV9sxIelFTpVJPs5eBg2eaqCoSLnVJIBSZxJ4FOHR2Fi3N8NQbA7asIouCPDvwK7N139lmB6uHq7ho1Gq8kbedm+NzPJCxa1REcFw23M/hxXhsrAJ4EZ4Vidj7HIjMsZV5itLO0rFzW2LBMZsKrnhkjvWMG8i0NINLb8yoKiJzHMaB001sWj3Ud+7LkhT7WD534gKA/rbRbqyCvPTPE80OuNslHgxNNrtYPVzBRcvs4DhnxwrNpyDPmmExM2//LuBnzlX7s9juYZRSyzp1kemoFxoiOOZAi9kEhFKKT/3T09g7MZXFZuVK1HaW61daAcWBJaY71j28UlkmKihz/LOXJ/Efv/lMou9uayZqCv8xqqmSKMgLgFKKl17pd6oALLu1uFZuz5+YRkWR5q3Tve4sCvJYMF/mQGJytoNVw1WsszPHeTtWeFm5AUC9YjfMKfHAImv++FvP4PGXJ4veDIdW13CKilvdxXVcnPNQZI4LRex9DrSYPsdzXQP37z2GB144ncVm5UrU6tmKImHDqsaSawTCAhv3A5Zpx4Km4h/6xRn8w+4jiQq9WpqBWnZQmmsAACAASURBVIU/c1xTZWHlFsDDvziL4+dbePOr1vQtT2Ll9vzJabx63YjvQLOiyBn5HNuyihIHeJPNLlYNVbBqqAJVJrnLKryagAC9pjqLcfqeB8Ok+PufHcGDL50pelMcWl0Dq+zW64uta61XG3NB/ojgmIO4bhXsQeTu/LRQ0WKYkm9eM7zkGoGwANgd/PC0j2YP5iS65I5mOM09eKgqInMcxN+MH8BFozX8++su7VsetyCPUornTkzPaxvtpiKTbAvyShrgUUqt4Hi4CkkiWDtSwys5yyoMx8ptfkEesHSDY3Y+lqnepqUZWGEHx4vtuLD9PWgpKMgXsfc5cGf8WhFGqSwrtxiCY8OMbkp+5dphTEzOZl6IViZ004RE+u2gFI720SxbmESX3NZMLhs3Rk2VS+1eUCR7J87h8Zen8LtvvsLxqWbELcg7Nd3G1GwXV1/qHxxnVZDHtPBlte6b6ejoGiZWD1sBz7rRKk7mHByzfTRYW8FmY8oUHOZJb9ahPL9/rmtgpR0cl3XAFxfdo6g7iLExYONGQJKsv2Nj2W0bL2XcpqiI4JiDbtzMsZ2VOzerpb5NeaNHLMgDgCvXDEMzKI5MzWW0VeWja8yvMlY52kezB5CWIDBqaYajj+Shqsildi8oki+PH8CKhorfuPnyea/JEok1iHne7owXmDnOuENeWWUVrAHIKjs4vmhZLXfNseaj9WSZ48UWhPGil6z1uGlSdHTTkVUsusyxYykYHp6NjQE7dwITEwCl1t+dO4sNRsu4TXEQwTEH7MEyVJEj9XJ3ZBWLwEBeM6MV5AHAZuZYsYSK8nSPKmM+WYUZ+p4w2lFlFapU6szxyQstvP2LD+LE+Vau3/vCqWn8aP9pfOS2TWhU5jcRVWUpVkHecyemQQjw2oDgWJUzcqsouaxi0m4dvWqoCgBYN1rDqek2KM3PIcJgQYmPrGLpOhWVS1bBguGV9rlSloK8VtfAO7/0MJ46ci7RehxpHkcy6q67gLmB3NPcnLW8KMq4TXEQwTEH7GRdVlcj3SC6i0hzrBt03kMjDOZ1vJR0x7phQh2chpfCZRWO5jiRrCKalVut5JnjF0/N4Benm7k7nnx5/CCGKjJuv3Wj5+uyFE9W8dyJC9i0aghD1fkBN6OiZOM9zYL5smT/BjnLgmOWOR6tYa5rYCbHJkKaz3Q2m41ZbBlKXtjMaVkG0myQsnJIBVCe43J6po1nj0/jOXuGKC5ejkd+HDkSbXkelHGb4iCCYw7YyHm0rkaqjGUarfNz3UQuBGVAj9ghDwBGairWjVaXlJ2bZs4vXHRkFUGa4xRkFZbmOIpbhVQqHeEgsx1r2+LapsVhYnIW33n6BD70+g1Y1lA932NZucWQVZycxmt9/I0ZWXfIK+vxZt3wVg9b2UDmdZxnUZ5TkOfnVlGSzGnesHOnLL+/PZA5LstsCBvUJh3cak6X1fBk1Pr10ZbnQRm3KQ4iOOaA3RxGI2aO2UViUmC6tbB1x7phRs4cA1ZR3sEzS8fOTdPnFy72moAEyCr0lGQVEQryrCYg5cwkAnBaj2chM/Dj3gdfhiJL+O03bvJ9jyxJkQe7F1oajk61fDvjMVSZZGrlVtbjzTTHKxqsIC//LnmaT0EeyxyXJQjLG+fcKYlenWWOR+sKZImUxsqNzcIlvX6dzDGHW8XddwONRv+yRsNaXhRl3KY4iOCYAydzXFMjWrn13rvQdce6Ec3nmLF5zTAOnm7mqh0sEt2k8zJP7N9BN02WiUwSCEaWVahSqR/4TTs4jtuqOSqvTLfxz3uP4f03XIa1dnDmhSpFt1vbf9Kaar36kmWB78u6IK+tG6W8FidnO1hWVx1nEKeFdI6Z457WU/gcu9FK5nTCjkOjIqOuyqXRHLPnfdLZGb9OjV7s2AHs2gVs2AAQYv3dtctaXhRl3KY4iOCYA90wQQgwWlNiuVUAC193HKcgD7CC42ZHxxlbU+jF1GwXW/7ke3ji8MLvJKgZ5rybmsrRPjppQR6l1HKriBQcy9BN6lhYlQ2WOc5LVvGNJ45CM0383ps3B74vjpXbC3Zw/NqLRwLfZxX70dRbFbPtpTTfTDwvrHU0w5FV5Jg5ZrMB8qDmWMgqAJRncMAyxXVVQU2VS7NdackqdEfew5eM2rEDOHwYME3rbxmC0DJuU1REcMxB16BQJQmNarQL0X2RLPTg2DCjF+QBwHJbtznT9p/6OnmhhbmugYnJhW/5phnmvMwTmx4LCkK7CWUVmkFhUkSUVVjvLau916wdjOQVzJ2cbmPVUAXrVzUC3ydLUmTN8dScJatabesk/WCZ07RbSLvXV5bCKjdnm1braEZNlbGsruYrq2Baz3k+x3ab4pIEYXnTk+SU4/ez7ahXZNQr5Zn9Yhnj5LIK5poiwrMiEXufA92wdKSNihJJ3+S+SM4t4OCYUmp3yIseHPNkXdhrZc1gRsFLfsIyAN1AtwoWHMcLBFnAE01WUW4tpZM5zum8mG5pGKl5F+G5sQryom3TbEfHUEWGFHINVThs/+LgznSX8XhPzvZnjgFLWnHqgv+MU9oYPj7HFVmCRMq53/KA1UOURa/OZm8bFRkNVSlNRr/rZI6TyipE++gyIIJjDjS7sUNdtQqYeKc8F4vm2O+hwQOPDRJ7bTF00tM8NMeEECgSCQzykraPbnfjBMclzxyzgrycnF5m2jpGav42awxZIjAiDmKabT3Qwo3Bo0+PgzuYL6N932Sz43gcM9bl3AiEXYODBXmEsMRIOYKwvGHXX1ky5+w41FUZtUr5ZBWJM8eOWwX/83YxdKQrGyI45oAFPI2Ifpd9sormwg2OdTP+SJbts6AHC3stKLMKWA/Qsmdv2CzDIEqI/RcLiuPqa1lWJ0pwXFXKnTlu5pw5nmlrGOXKHEvOFDwvza6OYY7Am8kq0paSdPXe+spm56YbJs7NaY7HMeOi0Wqusgp2nnldv2XStuaN5gr60tbCx6FPVqFKpTkubNCZWHPsuFXwt49eDB3pyoYIjjlg9lw8gZ4bdpGsHq4u6MwxC9wGtbQ81FUrIAia+mpzZo7f//8+hr964EDkbcgTzTA9tWKqFOxCwDSh7iAmCkxWEa0gz9rOskyXDjLbzdetgjdzrMRoAtJs6xiOkDlOXVbhCubLdrxZPYZbcwxYsoqzzU5uM0ps8DqYOQZgaVuXaubYtf/LMMvkllVYs7nlOC6OW0XC60uLqDleLB3pyoYIjjlg9lz1Snig54ZZ36wbrS5ozbGRIHPck1X4a7XZzS6sAcaZmY7TSausaAad1yEPANQQi66kbhUtR1YRoSCPaY5LlklksCYgUbO0cYkUHJs0kiXabIcvOK5kVCTpPq/KEkwwnAYgQ/2Z43XLaqDUuu7zwM/KDbAGnWXJUOaNu5izDPvAudcpMuoVuTRyF0dWkXAwF/V5u1g60pUNERxz0LXtuZzMcUCg56ajm6gqElYNV51q9YWIFnGax40jRQnwomQ3uzBtqWaYpbShcqOb5rxqdyA826jZGeP4sorommPHraJkmUTGbM4+x9NtvoI8pr2P0gik2eHTHFdk1mo87eDYLaso1/GenGWto+dnjoH8GoEYpmXZ6VU0uZSDY61kxZwtu9mRJBFL7lKy4DhxQV5EK7fF0pGubIjgmAPdMFGRJScLGkVWUVUkrGyomJotd8YzCBawxSnIY8FakMsHb0GeZtBcWwnHQdO9m6WoshQY2DuZ45iyilaM4LhW+sxxfppj3TAx1zW4C/KAYN/qQZodHSMRMsepF+SVOHPMuuMNao5Zl7y8WkhrJvWVjpUpCMubsp07rW7Pz71csoq0OuRFk1Uslo50ZUMExxxotj1XI6IZfEc3UVVlrBiq4NxssszxudkuXjg1nWgdcYlaIOCmlzkOKsizXQkCbiqGSWGYNFdHi8dfnoxcgKKZpucgQpWDu6o5muO4bhVOQR7/JV2zC/LK0vlqkGaObhXsu/gK8uIFx1HcKrLIHDNZR9k0x0wqNegBzRqB5Jc59u8CWq+UJwjLG61ksoq5roGGLXEsU0a/1yEvpYK8CE1AFkNHurIhgmMONMO03SqsC5JltMLo6IadOa6g2dETTbfsevhlfOi/7Y79+ST0OvZEP11UWYIikWArt2643japD3BUXjg1jQ/uehyPH5qM9DndoI5XrRtFlgKz3o5bRcygqBPD57haYis3SmmvCUgO28ea1PBpjsOburihlFqaY451O1ZuqQfHphMcl82tYnK2C1UmGK3375+VjQpUmeQWHGuG6VmMB1hBWFm0rXnT7ZNVFH+vaGm6M4vbsK3cytAS3XGrSFqQF8PKbTF0pCsbIjjmgHU94/HsddPRTVQUCSvt6cLzCXTHM20NM+1idMssCPB7cIQRVjTBivWCMoRJg8eoXLCP1XSLv+kLYG2fV4ZdkUiIrIL2/Y1Ky+X9yUuZm4B0dNPR9EbtRheHafva4tMcR8scd3SzL3MbRFayCs0wneC8DAGOG+ZxTEj/dSNJBGtHarnJKnRjvkc5o14iP9286XOrKME+cMsqahUZlJZjgJ9WQV6SmVpBeojgmAPLgSCGlZtmoqrIWNmwguPJBF7Hmp6vpKDvu41oBQKDNEKmJFscGUK2DXkESu7vi7rPuwb1kVVIvoG9aUtGrM/nV5BXU8pr5eaencnjvGeDoNFImWO+c5H9Fq7g2JFVpHue6yZ1suJlGwxNNrvz9MaMi5bVcssc6yYNzByXbb/lhfu+XIYBwlzXcBJV9RIN8HtWbkk75MWv8RGkh9j7HOi2d210n2NLVrHCtig6l8DrWDNMmDRahXxaOAV5MXu9h01JOlZuGVqdRaVrxOvap5um4zjgxtIcex87t1VZXGeGth5Dc2w/WMo2zQ70bNyAfNwqZqJkjp2CPL5zoxklOM4sc0xdsopyDYbONjvznCoYF43W8Mp0XlZu3k4zgK1tXaKyCveMXhkG0m2tvyAP4H8mZ0lqmeOIbhWCbBDBMQddg/kcs+KyaFZuK+3geCqB13E35+DQTZIOeQBQryic7aP9gyAWLORl68W+L3Jw7JM5VmR/n2P3707sc6xEt3IrwwNvkKY7c5yDQ0kkzTGTVXCei+y3FFuQZ7oK8ooPJNycbXbneRwz1o3WcOpCOxdNqVWQFyyrKIO2NW/KWZBnB8cRpY5Zwp4ZSTXHUd0qBNkg9j4HrCVwRZYgS4R7lNq13SpWppA51mNO86dBTwMVN3MsBWZd2GtBI+68M8dxbXmYJ/YgakD7aPe0Zdzf19YNVBTJ06PVD8UulixbsAT0uuMB+WaOR+vhmWM5auY4QuDNskVpF+TphlX/UJGlUln3UUoxOdsJkFVU0dIMTLejaf/joJnUV+dZU2WYNP3jshBw35/KcK9oaT1ZRS2ig1SW9HyOk3bIE5njMiCCYw6YWwUhlp1bVJ/j5fYDN5Hm2Mg3c+rGGcnG1hwrgT7HbH8GFdslLViLCvuebsTv0+3izUHUwMyxOziO9/s6muloiKNQU+XSTbMD/ZrjPLyto2SOWXaXV//OAn2uJiAZyipUWUJVlUrV9GWua6Ctmb6yCsfrOAfdse4zsAVc2taAZkaLFc0wwcYMpQiOu/NlFWXYLqY17hpmohkG3bRcUwYLVAX5IoJjDpjPMWBPr0XQHFcUCYosYVldTZQ5LlJWEbVjzyA1VUYr4IHc5pBVOIODnJqAxJFVmCaFSb0teBTJvwlI10ieOW65ilSiUFWkUjxYBmGaYznE5SMtptsaaqrEZZ/kaI45t4sF3tEK8tKXVagysQdD5TneTgMQH1mF0yUvB8cKqyDPX1YBlGP6Pm+6BnW0+GW4V5RVVuFOMiRJOOiG/wyGID9EcMyBZnfIAyznhTleKzfNdHSdK4cqiTTH7GFZxLSekbAgr1GRA3Xacxyyim7OmfOuHt1jVzP9M+yqTHwz42lojtu6EcmpglFT5VJqjlnmeFldzcW+b6atcxXjAdGt3FigX2RBnm5SKJJkD4bKc7zP2p1DV/sV5OXYCITJ57zoFWNnL+8oG7pholGRIZHi6xMopZasYiBzXCZZBZDsOc1meQTFIo4AB7rZO1nrFSViQZ518SYNjllQWISsggVvcX2OGyEeoTzto1mQmkdxFhCvY12QVsxqAuKjOU5BVtHWjEjFeIyqKpUqk8hgRWzL62ou9n1WcBwevALRm4A0O5aeOUoTkNQzx7olDStt5thHc5xnC2k9RHMMlCNDmTearVevlcDOjgXnddYhr1SZ4942JJEu6aa/vEeQHyI45kDTeydrI6ShhRtm5QYAKxrpZI6LLMiLO5qthei0W1xWbrbmWM9bc8y/v1mw5LWfVJn4ZgO7KRTktTQTtViyinJmjlmGbrSu5uNz3Na4WkcDbis3XrcK6/xucGT22bqjat3D0EwmqyhX5niyGZw5rqkyGhUZ51vZN0CyprN9ZBUl0rbmDctk1krQqpl9f922rCzTcXEHxEkGoFrAeSjID3EEONDMAVlFJLcKJqtIqjlO1iQiCXqAXICHoCYgumFySSZYxjgvzTGbIosSjLOA2rMJiOTfPlpLQXNsZY7jFOSVNXNsoCJb3uL5uFVEyByzgjxeK7e2juGqwuUkQghBRZGyK8hTis/+uZm0EwYrfTTHADLZH14EZex6Np7lGVjkRdfu+lkvgQSLDZobLHNcIp/jrmFiyD5PkpyvQfIeQX6I4JgDd0Feg7Mgj1LaJ6tYMVTBuVktdhVrkW4VjlwgQRMQzfDu8OfORARauTkFcuX1OWbv9WokoMjE99j1a47julXE1ByXLFhizHZ0DFVlyx86p/bR3Jlj+17AK/Fhv4WXSoCzSRwopbaHL7EHQ+UJ8M7MdDBSVQLP3YqcV3Ac3CEPKMf0fd4wG8CqWrwNILtX1ctYkKcZTt1CooI8k2YqqxgbAzZuBCTJ+js2ltlXLWhEcBwCa+2rOpljBXNauOaYBXpMVrFqqIKuYfY1N4hCkbIKI2HmuB7QWdA90OCRVeRRnAX0guMoD2U9KHMsS77BfxqZY3eRShSqJQuWGLMdHY2KAlXyL2RMk2iaY+s6MCI0AeEpxmOknSnVXLKosg2GJmf9W0czKor/tZMmekAh1NLWHNtNsFQZ7YIztOwZwu51TiOjEmSOO7qJ0bp1nSe5fjUfO9A0GBsDdu4EJiYASq2/O3eKANkLERyHwLJDvYI8vswxCzjcmmMAODcbTzunFyircOQCMQvyWHDs9VBmDxtVJoESBmdwkFP77DiDkd654udWEWzlpkgkgazCjNQ6mlG2YInBAsqgjHuazLS16AV5EdpHRwmOrVbjaQbHvfOyqpbLum8yoHU0Iz9ZRUDmmN3DShCE5U3XZQNYdOaYBcfMPYQQS+5R9KCFzRSnkjk2sssc33UXMDfXv2xuzlou6EcExyH0itFsWQVnExAmzndbuQHAVEzdcd5WZm56TUDiW7kB3pljtmy0pgYGG73fn3PmOFJBnn/houVW4ZM51lkFdnx9bVuL53NctgItxlzXwFBVDmyekhaaYaKtmZFlFfwFeTqXUwUjaJYhDu4OlzWlXE1fJptdX49jRkXOZ3YjSOu5lGUVrAlWGe4VbP+7i4/D3JDygF2vbICdpI5DN83MCvKOHIm2fCmTyhEghHySEEIJIasHlt9ECNEJIe9L43uKQHOyer2CvJZmhGqH2cXh1hwDwLmYjhWFulWYTC4QM3OsWjcMr4w7u6mN1tXA7BD73SYFjByyx3GarmiuDPAgqt3Mwuu8YZn5oYoSOyhqaYZzrkWhqpTL2ovR7OgYqipWcJxxEWaU7nhA9CYgsx0dQ5XiZBXsnFIVCdUSFFW5sVpHB2eOqznJKgzT3yUgaIC/2GHBcV3lb4CVFa2BzDFgN5kquFCSDd7YADuZrIJmVpC3fn205UuZxMExIeRyAO8AcGRguQzg8wB+kPQ7isTR6yk9n2NKw83Q2cXB3CpYdmQybnAco0AsLVhwHLsgzymamK+3Zjc7y7IrQFaRgt1ZFLoxCgA1VxAySFDLYZZRblTl2L+to5kxm4AUnw3yYpbJKqTsZRXTtk0YbxOQqF7EM+1omeO0C/LY+aVKBFVFctrcFo1hUkzNdrGaR3OcwwBOM01f6RibASw6Q1kEuh2sVUsgq2gNaI4B6/lStFSIPS96meOkPsfZZI7vvhtoNPqXNRrWckE/aRyBewB8GsDgE+wPAPwzgNMpfEdhDDoQsBHrbEgjkHma48SZY9r3N0+YlCFJExDA2wbJCY5rCldBHsA/nZ0EpwlIlIK8gEFEkP0X+464tmWGSdE1zFgFeWUw9vdi1s4cK7J/2+20iJo5ZtcB7wzGbLfYgjx3oWgZdKOM83NdmNS/dTQjN81xgNaTaVvLeK1kTZfJKhQ5UXOLNJgbcKsAUArNsZM5rqeTOc6qffSOHcCuXcCGDQAh1t9du6zlgn7479geEELeA+A4pfRpQoh7+aUAfh3AWwDclGgLC6ZXzNIryAPC21X2gmPr/SNVBapMYmmOKaXO1HIRmeOgzm889Lwo5w8o5lyyCt20ZAfuc4nhnlbNQ3ccR3PMstt+7aMBKztVR38Qy/Zvo6LgbKcTeVvZAztOQV5VsfScfvu9KJodHUMVGRTZe1vPtKNljntWbuHBMaXU8TnmRU15QODIKmwrN82wHHjiDnbTwvE4DivIkyVcMHJoAmJSyAGzY7zF2IsNzbB8/usVqfAgtO3IKnrXU12VC2/rzWZjUtEcG2bf70ubHTtEMMxD6BEghPwIwEUeL90F4I9hSSoG+X8A/J+UUjPsgUsI2QlgJwCsW7cO4+PjYZuUCc1m0/O7TzStB8svXnwB4zMHcPikdRE++MjjuGzE/0b64pR1cex/7hmQU1YwNKQAzx2YwPj4qUjbZpgUTKr6zPP7sXL6QKTPJ+XgoS4kAjz44IOxPn/S3od7n34WlTMvAOjt76eOWQ+92akzAIAf/2Tcc9T8i4O9QcWDDz+CZdVsH+ynz7YAAJNT57nPyWfOWOfGM0/vQ/tIfwB8eML6neMP/RSjlf5tf95+rT1zATOzZuRrYLprnRxHD7+McXrU8z2+5/dRa7/+8IFxVEpiPE8pxWxHx+QrJ9A1KNodPdP7wt5XrOP20nP70Dkann2fsff3Cy++hPH2Id/3NZtN/PCBcegmxenjR7iv+9mZFpoUqf3mYzPW9ffSC/txZs76/x89MI6qUuzxPnjeukceeul5jJ97yfd90+fbOMdxXfid47y02h2cPnUC4+OTnq8TQ8Oho8cxPn429ncsRJqzbZw98wrqCjDb7l2LSfd3HJ4/YN2vdj/6MCQ7tphrtjGn0cJiBwA4al9jp45Y94Nnnn8R62ZfjrWuc+db0CvE8/cUsc+XKqHBMaX0l72WE0KuAbAJAMsaXwbgSULIzQBuBPB1e/lqAL9KCNEppd/2WP8uALsA4MYbb6Tbt2+P90sSMj4+Dq/v3n9yGvjpw7j2mqux/ZqLYb7wCvD0Hlx97XW4bv0K3/VJL50Bdu/GzTdchxs3rgQAXLTvIVRHG9i+/cZI29bqGsAPvgcA2HzlVdj++g2RPp+Ux1r7oR457Ll/eDhxvgX89AFsuvIqbL/ZUv6z/X34kUPAs8/jNZs3YPzYQdx625sw5JFle6LzAnDgIADg5te/Hhcvq8f+PTx8af+jwNQ51IeHsX37m7g+Y+x/Bdi7B7fcdAO2Xra877XjP5sA9j+LW15/K9aN1vpeO/Dwy8D+/bjs4jU4PXE+8n4+dm4OeOAn2LrlNdh+0+We7/E7vw8qh4BfPI9bbn0jljX4MqdZ09YMGN//Hl77qisw3dLw4PH45x4PZ/YcBZ76Od76xltx+cpG6Pun2xrwwA+w6YrN2P6mK3zfNz4+jtfdeCvwwx9h65arsP3WjVzbc9/LuzHd0rB9+228PyGQZ49fAB75KbZtvcY6V156HjfdeltgV7o8qL08CTz+OG68bhtuu3K17/v++eRTmDwWfl34neO8kPHvY8Pll2P79i2ery/fO45lq0axffv1sb9jISI9/ENcfulFWNGo4AcTB/BLv/RLIIQk3t9xeKy1H5XDh/HWt7zFWfYPR/fg8Nk5bN/+5ly3xc2+o+eBRx7BDVu34KvP78PGkHtDEJ9/+mGsXV73jBOK2OdLldi5e0rpMwDWsn8TQg4DuJFSehZW0MyWfwXA//QKjBcCg40dgpwX3AzKKgDL6ziO5tg9tV9IQV5CDVSglZs9HbXM1mr5/b6+LnIRWjrHRYuhOR50NnHDdMhev48d30YlWHftByuoq8aUVQBsGrAcwfGs3ShnuKpgrqtnrjGfjulWwSN9YL8lkltFRj7Hiu1VCySb9k2L7kBdhh+VHHTnQLi/bL1SfBOMInDcKioyKLXuV3GccdKg3Z3f7KgUmmMmD0zF51i0jy4Dwuc4BLdeD+C39Bl0qwAsr+M4muMkHdRY69gk6Eay6tmgFp/trgFC4FTz+2l83UFq1tZe7u+L5lbhr81WFX/7LxbsNyrx3Cp6muN4BXnWOsrjWDHbsX7PUFWBIkm2rCi74Ihpjnl1wWzwY3Cch6zYL5JbRdoFea5CUaZLL8PxZr+xEhYcKzn5HAe4VQBAQ1WWqJUbtdpHK8WfO3Ndo8/GDbAcpAoPju3zczgFt4oy1AMIUgyOKaUb7azx4PI7KKX3p/U9eaMPFOQ5wXHIxdjzOe4PjuNkjt0BVdQMyl3ffha/9pcPYyqmSwZgFR4lGclWZAkS8c62z9mZAKZ39ft9Wl9BXg5uFXHaRw90U3SjBGSONcOEbNtsxcmQseA4nluF/cArQSaR0XSyrXKvkDHDYz7T1tGoyNwDwDiZ4+gFeSlmjnVXhzzFv1tl3nQ4g+NqTlZuuhk8Q1YrQbOJItDsTGZQp9O8aHk0OypDW2v2nKgpsj2Yi789mmn6tjEX5Ic4AiH0aIgiEgAAIABJREFUsoGDbhW8Vm4uWcVQBedbWuRMbpLM8cHTTbxwaga/dd/PLK1kDHQjWcceQggaPqP7lmYFx44PsK+sIl9pScfJHEeRVfg3SwkK8tjDJ25QxDI5cTLH7Pws2qLJDas8Z1ZuQLaOFVFaRwOAJBFIhM/KrRk7OE5vMKCZPWkYGwyVoUte1+hvlORHJYcmIKzoOWiAVC9Z6+08ME0K3aSOlRtQcHDsJasogYtGxzVTbHmJJ5FVZGflJuBHBMchsCl8xZFVWA+5sOk1pkHqyxw3VFBq+XtGIYnmuNnRcenyOl48NYOP/u0TsSxvdDN5r/eaT9vtVtfKBIQ1VnBni3P1OY7RIS8oc+wV5DEfUVWWHDu7KCSxcit15thuAgJknznmbR3NUDg797l/Cy9pywhY5rhSkgCHwS2rkLP3OdYH7vNelEHbmjeaazasDBKsluYhq1Bl6CbNxQvbD/dMcVWREw3mNINm1gREwI84AiG4HywAv+bYa8rQaQQSMThOIimY7ei4YcMK/OUHr8OTR85h51f3Rn4wpjGSbVRkz2w7k1WwgLLrU2yXd1Gi0647iqyCZY692kcrwbKKiizFlhC0EskqyhMsMZjmeNhuHw1k6209HTFzDIC7cx8LjqOsP6sOeYpMnBqIMhzvzsC91Y+KIsGk2Z4DQdcuYyn6HOuuOop6pfgugXNdY94MGft3kdvlft4nzhyb4QV5Y2PAxo2AJFl/x8aifUfSzy8FRHAcglPMYt/Aq4oE4qOfdTPYIQ8AVg1ZZvdTs9HkDe6HcNQRabNjta79d9dcjD9/37X46YGz+NjfPxXp4ZtGO0u/rAvLBFQUFhiWQ1aRevvogAyoplMnc+xeDy+JCvJKKKtwHB6qspPJy3K2YKatczcAYSgS4ZJVzMbMHKeZBXMXijoymjLIKjyKlr1gCYYspRW94Nh/W2pLMXPsmg0rw6xDy7Mgr/jt6s0Uy5ZGPsG5aiWj/M/DsTFg505gYgKg1Pq7cyd/gJv080sFERyH4LZBAmz9rI9EwE1HNyBLpC+oXDFkPYCnZqN1QUsqq2B6x/fdcBk+864t+NH+V/Cdp09wryONdpb1SrCsIqhgjW0DI9eCPMPkljk4QUjE9tGaYUJViCtLGlFWwRlkeFEts6yiogRa4KWFFRxHyxzz6sObbR2EAI0IAxc1Iyu3/qnx4o83b+a4N6uUYXDMKasow37Lk67r3KmW4NxhNSpu2L+LzOq7k2EVRXKC5TiwGhQ/7roLmJvrXzY3Zy3nIennlwoiOA6BBTzuG7hlHROs3e3q5jz/Tma6HzVz7J7ajxI46YaJtmb2FQP9+vWX2dvAL+0w7IKMJPg9WAYL8oLcKpi9TdbthFkRSiVkmwbRDf8HrLt99CA9zTFx/h0FVqkdS1ahFK8jHMRdkKcqeWiOtciZY5kzczzT0TFUUSBFGFwy7bmZUrbc7dXu+FqX4Hh7za554WSOMw2OwzPHdVWGZtBCvOaLwj3rUC9BcDzXNVAf8Ayvl0BW4fbsriasGQir8TlyJNrytD+/VBDBcQiDmWPAmu7l0RwP3vRXNOJqjuPJKtx+sYxqjClKd2Aal4ZP5niuq6NRUUJlFV3ddLJvWTcEYPtmqMq+j29fOa4AXppjFmh73DR7muMCZBUl0qAymh0DFdnKwDiFjJlqjnWM1uNkjvlkFVGcKoD0ZQRur/ayNQGpyBLsTqq+VOXsHTb0gGuXEeTXvljR+2Ydivc5bnsV5JXguHR005kpripy7IEc60sQNEhbvz7a8rQ/70ccHXOZtc8iOA5h0OcYsEaq4W4V87sI1VQZQxU5sudwv96WPzCc6VgZ6hHXw5llQ6NkjnQjmc8xYBezeDUB0UzU1HC3Cs0wnZtg1rKKXnCsBG7TIKyzkdfDPkg7a+1fKYGswpLwxMnul0mDypjt6M7AJGuf47ZmoKubkd0qrMwxn1sF+y28VGIOkvxw7mElawLS0Y1QpwogL80xh6yCaVuXUFFemSQ5lFLMdXVfWUWRx6WjG07iKYnPcVAjKcbddwONgS73jYa1nIekn/cijo657NpnERyH0PXQkTY4qpb9bvwrhiqJguMoGTSvzLEkEagyifSgsTpHpVCQ55s55tMcRw1W48JG/Szjx7uvtAA/6KDf17WDaiWmrKLVNWNJKgCUyr2AYQXH1r4PssBLg5mIraMZikycmYIgmh0DwxED77RlBE5WtGRNQLykZ17kIavQXNITP8owfZ83zD1IlaXCf3/XMGFSzG8CUpLMMTtPkxTk9bTv/ufhjh3Arl3Ahg0AIdbfXbus5Twk/bwXcXTMZdc+R3siLEGcrIvSG8k1KkqoX7CXrAKwW0hHDo57uucogWHTzhwPtq6N6huqmxQ1NStZhVWQVwnRlmpGLwDMKzjuBeP8BXl+macg/bJmt+eOmzFs60Ysj2MALg1qeR74TVunC/QyeVlljlnr6MgFeZLENVBttjUMR8wch+nvo+IuqlJlq4FJGWYKuq6AIgh2XWQZHBs8soolGByze1FFIYX7HLd8aivYv4ts7W3NFLsyxzH3kTNIC5Ex7tiRLJhN+vlB4uiYy659FpnjEBzNsSsj6Oe84Kajm57uASsaldg+x/WK7GSyeWg6frH9N5OqKkea9knD59ir9appUnR0c6Agz0dzbJiO1izrJiBsG1hwzPtQ1k3Tt/LekVV4+hxbxX9BjhZBtD28P3khhCQuIEmbua7hklVkqzl2MsfVbAryZjtGZM1xXO25Hz2vWkvfWyuJ60KHNzjOQVbRu88Ht48GinVFyBv3848Ff0UNDtgzd1BzXA6fY8OZlUlyP/WScS4E4uiYs9I+p8XCOgIF4KUBavjoZ91YU4bzA5ZVMTLH7KHQqMiRgoRmm7Wu7X/wR80cs8xmEhqqgq5u9gUUbB82ODrk9WuOc8ocVyIW5On+mWMnA+oRUPXaR8d0q9DjB8cAShMsMZp9sopsfY7jyiosuzW+JiBRPI6BXjCY1oBFM0xIBE5RbU2VS2HdVyZZheGSnvixNDPHvYGVJNkD6YJ+v9PsqIw+x65zOUlBns5xHvpRZHFbHB1zFtrnNBHBcQiWjrS/yKpRkR09rx9ugb6bJJrjekWOlE1yN1NwU1WjjWx1M42CvPlZB/fNzvEy9ZNV6NQlq8g2c9wZ1Bxz7istQJtdCciAdnXLyi22rEIzY8sqAMuxogwFWgy3w4OSchZ1ECarGK1nkzludvS+glgeKo6UJK3guL8dbdIOXmnRNSJmjvPwOQ6xcgPKodfOC7esAih2IB0mqygyo991zRQnK8jrFc9Goejitjg65iy0z2kiguMQNNuD1k1dVTxbIbsJ0hzPdY1INxg2LTpUUSLJKmY63lPGkTXHAYVmvDBvSrdW232zc1wJfLZLM0wnA5e1z3F8twr/QURQkGc1AYkvq2h15xvjR6GqRJPZpMGZmQ5++Pwrnq+5C/JUR46SzYBoOqbmWOHQ/1NKE2WOUyvIM0ynQyPAMsfFB8fuqeggHIedLINjIzxj13BkFcXvuxdPzeCpI+cy/x5tYJrfr9NpHvRmGvuvp3LIKsw+WUXszDHHeehFGYrbduwADh8GTNP6yxPkxvlMXojgOASvIqtGRcacZgR2TvOycgN6GarpFn8jEC2mrMIvcxy1PW2YKTkPDcdup/e9Xpljv8C365JVZJ051mJmjnVz/kCKoQS1j7Y1x2rMjGFyWUX+meNv7DmKnX+3x8ncunF3dczPrSJ6++gwqYdmWtP1gwWxYaStOWaDL0ZVkUqR/WQ+x2HE8WaPCk8TkJpT+BWcGMmDz373efzJvzyX+fcMBsdFzjIxzTGbhWTIttyjeM2xO3OcnVuFF2UvbluIiOA4BNagwU29IoPS4EyGn5VbNYae0K05juZWoaOmSvMutKgFA2kU5LHAds7VWdBdYBFWoa8b1NUEJJ/McaMaLRjv6tT3phbkYdzTHMcLAto+AzFeitCgzrR1UAqcON/uW255mfaM/rP2OZ52dPnRM8dhwXHLPtXjFuSlFQxqA00FrILc4rOf3G4Vin8DnbTwavY0SBm0rYxj51q5BOndgZqbcsgq5l9P9YpcsM+x28pNhm5SLtnVII7GO+LztuzFbQsRERyHoPtkjoFg6xg/WUWc4FizvSYbFSVaE5C2Pq8YD4iTOU5ekFf32Gfs5l5zySr8tkszLE2XRHJoAmJvw0hUWYVp+soqZMmy0PKVVSRpAqIZ84pUolCEBpXJkk6cb/Ut7+gmdLPnaa2EzCgkZaatYbiqRO4AqUokdBanbV+3sTvkpVWQp5uOjhkAaiXJHPvdIwfJw61iIVm5UUpx/HwrlwHOoHtCrVBZhXXP8LrX8TTmyhK3lRvTHse5ft2t3qNQtuK2Mne+40UExyF4aY57wbH/yN0t0HfT60gWQXNsWtXmVTWaz7FV2DT/RlJRZHQitY+mkUeyg3h1MWq7NGSEENsBYP52mSa1iwKtLLiWteZ4wOeY96HMOt354bftrCAvtqxCM1DjCDL8KCJzzB6wxwaCYyYFGh5wq8jO51jHaETZA8BXkNeyg+PImuOUfY4tWVTv/Kipcil8rcvkc9zzlw2XVRStOT7b7KKrm7kEx16yiqKKOf2s3IBitdBAv36+p5GPvj2aGT6D4UWZituKLg5MCxEch6CZ8wMeVlwWVB3rFui7qcbICnVZZlGK2gRE99Q7RrXjMUx/uQAvXtn2wZud4vP72A3D2gck9/bRvMeqazub+OG37ZpBUVGkBLKKZJrjqiLnriNkx34wczzY1TFuNp2X6ZYWWW8MWNsVdi227VM9sltFypnjrmH2PWwtzXHxsorIPsc5WLkFufLIEkGlYG0r0Ltm8hjg9GQVvcxxUTaAjqzCIzgu2o7SbUuYRuY4qlsFUJ7itjIUB6aBCI5D0PT5U+UNlUdW4W3lFldWUZElqEq0wNDdacxNJWJ7Sy0k6OPBa0py0JrHzzvW3SFQVaINEOLQ8zmO6lbhX5AHAKri3VVtUHMc2a0iqaxCjW89FBf2IDt+rj84bjqZY3vAxNwqMizIi+pUAViBUrjmOF7mOP0mIP11E7WITYCywi+BMEgesgp2foXJa+ol8AQ/zoLjPDLHOktMWPulrsqFWab5WbkBVsBcuFsFs3JL4K7Cng9JC+CLZLEUB4rgOATdw7s2THNsmBSaQT1v/HGyIJqd+VHlaEFt0+fBH9VqJg23irpjg+TtcwxY+8Yzc+y6QVvZ5Xwyxyzrzq85Dt5PiiTNs+KjtCcZiSOroJRaPsdJZBWKnPtUqV/mmEmVmF2TmvGU+kxHixUcK3L4QLXNCvJiNBgB0gsGB+smyuJr3fVJIAySh5WbNpAh9aPI4JBxwhUcBzkmpcF8WUWBmWPN6EsiuCn6uPRZuanRpZMMjWMGo+wsluJAERyH0DVonw0S4Ar0NG/NMXuQe7tVsAsnWnDMCrYiaY673h6rUdwqKLWqbpP6HLNgJzhz7BMcsxu0YgWQeXXIY9lLXm9pLURz7LXt7ocyO8+iHGN2HKuJrdzyfbCw4Pj4ee/M8Tyf4ww75MWSVUhSaDa7VZKCvO7AjEZVKUeHPF5ZBSEksjd7VAzOzDGz8SwS9zWTZTYd6F13ZbFy85OPWZnj4gZ8bneqOLPDDCdznPB5WyRlKw6My8I9AjlhTUkOulWwhhbeN0k2YvSUVajRxfos6FI5slVumm3d88Ec5UGjpzSSrXtIUeY8g+P5v6/ryl4ocvh0dlJYcBpVc8zkEX54bbvTgcrWlFvL+H8fC2qTNwHJ98HCtvuV6XbfYIBpjuf5HGfWIU/HaD2GrEIOL8hrGzGD49RlFbRPw1hkURWDUoquwedWAUR32ImKU5AXcp+rlSBz7JYiZblP3Ovvs3Ir6Pe3NcOzGA8oVu7Smynu+RwD8YJj3vOwzJSpODAJ0Z8KSwzNoztcmKyi62Tz5t/441Rea3abVdX2VjVNColDA+xupuCmGkFzyIJxOeFIlrU3dncWbGnWtCr7LYqPW0Wf5jhiUWIcBt0qomiOg0b8XrIYt79qHFkFy+IkbwKSf+aYEMCkVoB82Qor1TDYuCZLn2NKafyCPMlbH++mpVsPB78Huh+pW7kNtGlmU+OUUhBSzENYNykoBVcTEIDVSWR3jhocTUAA20+36IK8C73guKObGMnwu9iAn50nRcoqLP9z75ClSFmF87x3dchzL4+C7io+X8js2LHwguFBFvYRyAEtSFbhmznuv1jc9DLHUWUVPa0Vj5WZZlhWP0kzxz2niGQPUULIPLudVrc/E1AJk1WwzHFOPsdO0xHuzHGIrEKaX5DnzorLEgEh0bKk7EFd8xiI8VJTLdP6rOUqblqagctW1AH0Z8KaA1ZuhBC7+C39bWtrlqdyvII8KTxzrFMM2zaFUUi9Q96A405NtZoYZT0lH0QnIIHghSqTjDPHfIVQRVuGAdb1kiQ7GYXB5FBdlaEZ+d4rGGGyiqI6Fw7OFCeTVYT7bQvyQQTHIWiGOc/jNyxzHCSriJs5VqRewRZPcDg7oN3s2wZFgkn5grA0L9ZGRZ4nq3BnAnxlFbo7u5p95rhjZ9oUWfJt3OEFl6zCGJRV9LLihBCoHkV7QbRSkFWwwLqdo7Si1TVw5ZphAP2ZsMGCPMBu1ZzBgIi1ro5n5eY9y+GmrUd3qgB611qU8yAIfeC8TPLwTgunLiNK5jjD7XXkYyGZ46JlFXNdHefmNGxcZc20ZG3nZg34+4s5gXzvFYwgWYVl5VbM+Tw4U+zUFcU4NoMab0FxiCMQgldjh5rCMsfeI1V2kXprjqNXsrKiwCgZpRnWFtfHrcLaBp7gmAWmyU+Vwe5Klj9vb71+AYdbl2s10shYc6xTVO3fa0kh+L4vzK1C9dh2x4lDIfZ7woMuN73McTLNMZCPbyrAWkTr2GwHx/2ZYwMVWeqTAfgNmpLCWkfHaQLCo31v6TSyUwVgF6ClGAwONjJi96CifWEBqyERD5WITj1RYbMAoVZuBcsqWLv1TauHAOSTOR6U5ADFnDtzXd03CVBXZXQNs5CM9uBMsSOriLEtbPujduwUpI8IjkNgNmpuJInMy4K6CXIQcALTCKNcVhTIAlSei2622z897SaKplE3080ct/oyx3p/htBH7tHn6MDRtjcpXaNXeRxJghKqOSbzJBqDVkl+Xsh+sMEG7/S0F3lng7qGCZMCK4YqWDVUwXH7gQ9YMx5DA10drUA0/W3rZY7jyyqCrLTiZo4Bf4lRHCwrN1eAE+MelDZBs2teVBQ5H1lFqM9xsU1AmFPFptXWwDKP4HhQkgMEN8DKipZm+vq51yvFZbTZuVwZLMiLcX2x5MlCLshbLIjgOATNND2n/oIsfZyLxeNziq0rjdqEQ5UlxzWDZ4q52eYIjqPIKlLIHDcGjNpbmtGXCajYBYeD9AJIkpvm2B2sRpFVBFlTKR72X92B4NjLCzkIdgNOJqvINxvktvC7ZHm9z+vYCo77z9msvK17meN4BXlAsMVc26CRu+Mx0swcdwekYUl8WNMiyO7Si0oE+8k4GCaFRBBa6NyoKIUGx+xauWKNlTnO2q1isI6iVuC50wrJHFvvyX+7BmeKWQY5SeY4Toc8QbqIIxCCpntPldcr/tqzoGITQkgkn2HAklUocjRZxaBfrJveNDpHYV9KBXmAdWN1Z9tb3f7Obn6SAieAtKUlPAWJSei6/FejyBx0gwZmnhSPDoBuzbH1twhZRb6ZRBZcNCoyLl1e7/Nt9XJYycrbOonmWLavh6CivJZO52XBeYkqrwliUBrGMsdFNgLpRAyOqxn7HGsD2XU/Bu9heXP8XAuyRLB+pa05zjhIHWw9XuS50wqycrNnIIuQe/RkFYOZ4xia40Vg5bZYEMFxCIPTSoyGqjhFb4N0By6WQaIa2mt6v6wiSnDsNWXcyxyHX7y9gryUMsfzCvLcwbH3ftFdAWRWxVluNIP2TZHxZABYp7ugB6zXVHlasopEPscsc5xTNsjxt670MsdMnjB4TgB8+t44MF1+HFlFz5Pa/1i1dWC4Gj3wBrxt/+KimwMBTgk0x4MBRRhRW95HxTDnF157UVcteUeYU0lWnDjfwkWjNae1fdYD2sHW470GWEVojg1/WYVa3Hb1JEL9muNYPseLxMptMSCOQAh+wXFQL/cgKzcgms8wYD3c3LIKninmILeKSAV5Jp/FEQ+D+2xQVuEnYXAHkLm4Vei9B4JfwD4IC94GG8a48XSrGDDZVzj8c92k4nOsFCmrqGGua+D8nJXFbXrIKrLytk6iOVY4JE4tnTpdFqOSqqxCH+yQVyK3ihI1AeEpgnK0rQUNLI6fb+GS5bVYlqBx8JNVFPH7W13DX1ZhH5cisvrz3SoS+BxzukONjQEbNwKSZP0dG+Nbf9zPJVlXmt+ZJ6IJSAiDVjaMwII8ViTlc+OvKtE6VPU65MVwqwjQHPO5VaRXkFdXlb7M8TxZhU9g6NYc5xEcdw3T8bbmLYzq+aQGaI49JCFuyQgQPWOYhs9xXg9aRk9WofS8js+3sGKogtmOjouX1fren5XOfKatgxA4WbgoKCGaY0op2oa3WwwPqRbkmYN2XGXIHPdn28LIun00S0CE4c5Qxi22TMLx8y3csGGFM3jPWlYxaE/ZG0ibiDcnEn87dJMGWrkBxWiOB2dBmAVokvbRQQO1sTFg505gbs7698SE9W8guPFG3M8lWVea35k3InMcgjUl6VOQF0NzDNjFJREefCzzE0VWwdrwDnncTJhNGV9GND0rt3pFCs4cy96Sgl4L03zaR3d1o8/KjSeTq3EMIiqyFOhzDFjnRhxZRRqZ47ys3HqyCgmXLO8Fx4B/QV4WbhXTLQ0jVYWr2+Qg7Hrw2662ZjlyxHariJAp3XN4Crf83z/CtJ0JH8Ry3PHK/hWfOS6PrIIvc1xkEGaYFKcutHHp8npuA9rBWQeWoc1bvsDuGb5NQAoc8HnNFFcVOdb5qtkD2aDGQXfd1Qs2GXNz1vIg4n4uybrS/M68EcFxAJRS365n9Yri63PsXCyyj6xCkSNmjlmHPH5ZRbOjoa7KnkFtlBurY6OWipWb4jR5oJTOK7BQFW+nBieAVCQrUMrBrcKtOeYZjOgD2mEvLMlEsOY4qqyio1ltmHmDDC8cK7e8CvIcWYWCS+3gmFXhz3YNz4K8LNwqZtp6rGI8oJfZ8TsXHc1/zOA4irfzL0438cp0B6en2/Ne87qH9WQVBbpVMO/yCMExb6fKOIR1t2Swma4igrDTM23oJsUly+u5eZPP88jOWYLFaLtmm7woUgvtNVNcUaSYBXnBdqAAcORItOVJP5dkXWl+Z96I4DiAXtckD1lFQNWyM2UYkDmOZ+UWpSDPf9qvYgftPJkpw/FdTCFzbHcxMk0KzQQoBWoR20enWcXvh7sgT5VJtEFEmKxiXua4X3McWVahm6gqUuQWxW7ytvZqaVbgWK/IWDlUQVWRnKI8b5/jjDLHbT2W3hjoHS+/WYwgtxje9fOeByxw8BrcGB73sDJkjjsBjZK8yCNzzFNXUWThFxtAXrqinqjRRBT8JDl5zTIx2LPW162iRLIK9v+xCvKM8PNw/fpoy5N+Lsm60vzOvBHBcQDagB7UTZCVW1hr1GrEUSWzYorqVuH34I/SBETj0EDx4mRddAO26gONPllFcIe83DTHutkXrEbTHAd1yJvfzGIwqI4sqwgoUuElb3umVtf6nkZFBiHEsXPr6ExX6JE51rNpHx3H4xiwmoAA/i3YWUGsl+afhyhNL9hD2Cub55xffV3Oii0qA2JkjuVsfY41w+QsyCsuCGPNci5dXs/NfnG+rKKYwQGbcQyTVRTjVjFfVhG3gJRH+3733UCj0b+s0bCWJ/lclMI53m3weh8ANJvlL8wTwXEAQTpS1gTEq0MWczvw0zJG9zk2oSrRZBVeGTj391vbyW/llobPMRv1z3UNdOz1DnbIC/Q5ZprjgN/f0Q3nRhqXrmE6bW15C6OcWYaw9tEhHfKiu1UYifTGQP4FWoMPuktX1HH8fNs3oMzK23omSeY4pCAvqCCWhyh+10GZY7bf3PcwZ0q+QLcKlhzwSyAMUs3YrUI3KFfjBRaE+TWAyhLWZv2S5XUosgRZ4pvVSoLmKk4GivM57skq/NwqitQcz58pjps5DvPKB6xCtl27gA0bAEKsv7t2hRe4BX2OFc5NTFgzuqxwzi+A5d0G9r5Vq/qXT04Gr78MiOA4gP+fvTcNsuw4s8POXd59S1V3V3U1GiDWxkKCBLiBBDDkUCSLQ86MxLA1ClvyIoQsyQozHPIfOxQhKTQ/7AiP/tgeyw6PrQjaM/bEDEIzVngiKCk43FkgSJBAY9/3XoBuoIGuXqrednf/uDfvzZc3M2/m3V4VUCeC0UTVq/fuu0vmlyfPd44vYTdGjoUwirnbWq4fSbcLdQd6P/Wa1JJVzIthCgR68dFkcq1/q9DNLIR4GTA+x35YjOQlrGFm5SYplP67f/Mi/sH/83it4/QoK7dE61herCppji0jiwcl4MkqdJjxSxOvdtd819ZeM2aL9PojQ5y7PMubSAsNee24VezMfRweVmOOs4Y8wXFlhX5VtwqNMYIUKlzmOCjel3177zDHfcWFHZFVyOK66yBQbMjLirAlMMfnr8xwZNjLxvWETW9bcxwvSHLsVNrW9b1De6PzsMxGSd5Ocd+2KssqVLTvDzwAnD4NRFHyr6rzg+jvqjTOqR7DAw8Aq6vFn+/1xryD4lgCWQAGSeThPYxuEAr1xgB5cNQe4jCKEcXJMejKKkTFsY5ezW+BOZ75FHO8EB/NZ+P8MIJpJNKOskLpnasznLo4qXWcXkgn5KlpHclrZIuInlmUTGROHOTzNOKq536IR97Yxq/delTp9SLYabhKZz7HfphJZICEOb44dnFp6gFAwRtYtKNQF3WY49znlKbYAAAgAElEQVTKjX9c9TXH6t+ZjCW8EJd8RyO/L03TgGObnYW+8FAmPWPhWCbiWB7XXQfJdvbe1hwnHsfD7L/7vXalJgDf539giz3+2wLtjc4D6UdZBqPP2ylO4s4rNOQxgT1doe3Guf3YmHdQHEvAsno0aIkACzeIpP6dOs0lue5Z162inDlW0auRhp5GNMcc5njIMMdAsfinB+ikOavILhN4QYTLaZFVFV6aSEiOSYlhV1hE9CwTUbwYOcxauYm8nnl4+LWLmPkhfvvu65ReL8MgbZbsAlNvUQpCJvzX3xsDKBaUvRbs++I4luryy2ArNuR14VaRM8divT474Q40vdabhhtEMAz1RbfOblcVqFq5Lbsh7wa6OO7gGvphXOi56Xc4VhBkSaAC5hhIxrClNOT5UWF3uU1ZRRuQNc41EeKxHxvzDopjCcpkFYC4OJY1mugMatkxaMoqeH6xBI4Wc1wuF1DFkKM55hbHjIzBoyJMy7SebhDBDaJag+SilZua9lPFD9rOFjf5+xXiozUYw++/8C4ODWx84baN8heXoF+R6aiCOWPhd/1aEvrx2oVdAEW7JpvDuNfF1AsRRnFtKzfRtarLHDsak6ubaY4lDXlMEaqb0tk0iHRJ1WWl7eKY9YIWYbDUhrwZbljLA3KqeunqwA+jArs/dKrZlNUBK8XiIXFDWo7mmJVRVm3IEyXytg1Rg903v6mnRdZ9/7ImwmXioDiWwJfJKiQaJ4/zsNDQWVXSbgaZrELhb3fdQKh3zNOV1BvNmtjqIUXP3M/dKoaMWwWAgqaYbgoh/4qKEjIgXZlVZ49pWYVqQ54XqDDHxcKelowARFahpnH+8UsX8PWPH1fu+Jeha+aYvu43riWj5itpcczueNgt+ByThrnqVm7JOQ8Fi7SJG8CAfDKXQSchT+ZWIdLCD3rmcq3cSggEFjoL+ioIBEmoLJYVNrEz97E7D3DDOsMcd5yQByxHVpFZufXEz+vQ6f64ALJTzDLH1TTHgaKlYNMQNdh997vNhHhUbSJcJg7ioyWQySoII0QYIhq8h4WGzqqS9fgFynV3XhDBCyKsCgzTDcNQ1kSRybWJhrys09sLs7CPkYqsIsgnLjtj7MSyCgC4PPHxkSND7mtkCKMYYRRnXtCq29uEOZaHgBTtvzyGKehxgkJ4eOz0JVye+o1IKoBEv9iVBnXmh5lmHwCuOzKAYQCvXSCyisWCstdCQt6FNDDj6Mip9Pd2SQjI7jzAwEZl/2m9hjwxcyzSwg/s5bBsBGXSMxZkQd8WcxxEMUYKYxwZh7suwojHcUFz3LqsosioD5bA0GZJoI74Gg2XJasIokJjaaIH1z8WXyEEpC088ECxWP07f4f/2ipaYd7772UcMMcSyCQFR9Iu96schjJxqxAP/DoNeWQysKkGpjL2RKVTvq+qpVWwKFNFLkUJcuZYQVZBbzWRf0Xb7OS8XqmoO6Y13sm/eppjmV6sx2G//CBe2LZUlVX84IUL6NsmvnrnNaWvVUGS2thRceyFGFINq45t4vihfhYhzWOOm3arePzMZQDAZ29eq/T32UJHwhwP7erPjE7YDVnU8Jhgct4cm5VVtN/MJYNXQiCwyPokWiuOI+UU0IEkAKot0DZuBFXZSVWIEmKHveU05FmmIW3gXBZzzNspVp1fWajuYHSF/agVbgoHxbEEvE5vgvWVhHG6MvULvytzq3DspDFLRUdJjsFJbcyAYvHIQkXvqDo5ksm1iYY82k+XK6sQbJ36UV5AljVCZcwx57qogJwThyrGVSykVLTZPQ7byPqI2lZ5PHYcx/jBC+/iyx+9RhinqotBh8XS1AsKx01P+sUQkObdKh4/fQk3rg8r7S4A1H0o0RwPathP99LG00ihEdGVWLmJrBiXzRzT0iUVtM4ch2oNecBytK2EOb6Rek7atnLL557iwqprSQ6RYsl2YpanOebIKiqOp0G0POaYxYMPJmEdLPa6Vrgp7I2rsEfhU6wti/VRwhzzirAyWYWOryxddFmmAdMQ20cRqHTKO4orW19BLqAKuomRyCoWimNBk5NPpTQRo36h5jispzkm54RcI/JvmZRFNT4a4BTH1P3lpLHBsmL8uXNXcf7qHH/1k81IKoBui6WZHxW6zklx7FhmoWiyzWbdKuI4xsnTl3DfieoWeHZJY+jYDTCowRzraGznEis3ooUvuFUsqZAgcH15XwaL1jXHkZq/LCBPR20L567M4Vgmjq32s5+1zf6LFvzLklXInCqA5TDaAN+tQnV+ZaESH90FSCjI9vbizzc29r5WuCkcFMcSeBI2cNiz4Ngmd/texa2CvK70GDITf8paTFFWIWOOVTWNKnIBVQwoGyQ3TAYQm5EU0J9J4KcJgQDN2AncKlJGg8foE1yd+fjpy+9xf8c6lPQ4DhM85G4V5Q15dMNhQXNc0ugFJC4VlmngG584Lj0mHXTJBs28oOBXShgxXqqjCpuug1MXJ7g49uoVx+RelfgcD2uQ+jrONDIrN3J87HZ0VauppqDNHLfsVhGE6v6yyyjCzl2Z4SNrgwUv3bat3OjwJRrLYGh5YwaLgdO93AUgbhWs5riaG4xKfHQX4IWCAEmYx4ehMAYOimMpZN61hmFgbdjjeup6pT7HVva6MuQaWMrqq0RWsauiOVbUPQcN+hxbpoG+bWKWWrmxTIBIVkEXkKKmPQI3JA15Yub4z0+exX/+xyexMy8W0PliZPHzyq5VxhzLQkA4x+6Hi5rjPOhFVhxfwK/dehRrFZvJeBho6ODrYsZYuQE5c8xb0PUso9H46JOnLwEA7r91vfJ7lDWGTppijhXGCFlDXu5zvHz2j4brFy3CZOiiIU91jBv0LMw6lhWcvzLD9YwEqG0rt5wcYncdliOrKHN+GfaspSQX8t0qksWnbqLjsnyOWezH0I6mcVAcS1CmI10fOWLNsRJzXP4gs0VXEoigxhxLZRXKzHEE2zQqd92zIE0TXlhMOxKxtIsNeeKiJI5jyspNzBxf2HERx/l5ouEVmGO17Vy2kY8HnsMBLRlJPs+Qft4b74/x+nvjxlwqCLqc8NgQEABZuAEvuMY2k3Q0GZuug8dOXcb6qIfbr+FkmiqCsIyiYxrPAwxqbI/2FBZJBLmVW/H6iX2Ol2vl5oWRtC+DRS6raKf4CcJYurClsYwi7NzlxXQ8gDDHbWqO+fPfsGd1nq6oEtizNFlFULyXqyY6LsvnmMWHuRGPYPlXYQ/DL3FqWBv1BMVxuZUboMaCBMzqXaU5aTxXaMhTTOlr2ndxlHZ6u2FcYAJEW8k0u5q7BBSPnf4+MreK7bELAJi4PI3m4ja0o1ikqFje8ZjjIIoWCmpyb4gavb7/wrsAgN+6+1rp8eiiSyaRDQEB5MwxLzylDh4/cwn3njhaa8HHs+WjUVdWUbZDQoNcN95iOxBo4dt2OigDCQFRReuyiiiGpSqr6NgVwQ8jXNidL3gcAx1ojgWyimUk0e3OxYmvBMvzOebJKqq5qyzL55jFfgztaBoHxbEEfsBfOROsjfiyCtcv+h7S0NIcc2QVnqJbhUxW4Sjq1fwwUmZUVECaWdywGAVqC4vjvGnNljDH9MQpc6vYTiUX3AAXhjkm/5YFr4gYOho8NtAL44WC2jblxfj3X7iAz9x4pLLLgghdaVD9MIIfxoVdA8Ic87ZOdfS3ZXhvZ44z21PcX0NvDMgb8kg0dR0rNx3rMplbRSarMItb412nnNHgFRQy6IyZVaBj5dZ1Efbu1TniGAvpeADgWO0ucNi5hyDR0+pLBuogYY7laZYkyEjF4aVJ8GwJq8qAAmY+WBb2Y2hH01j+VdjDKIsEXh85he37OI7LZRVpYaAjq3AoWYGqW8WKxObLUWWOG+6ezWUVxQJJJJnwAjWfY3qikDHHF8fJ7yYeR1YRLBbHqrIKpRAQjv2XzzBosgbAd6/O8cxbV/BbDUsqgO6YY9Iwwy6MDg9trPZtvqyipAlTB4+leuP7bq1ZHEuOae5HiGKgYvgegNw+q2xBEEVxdm/yZRUSx4Flx0drWbmp92lUQRjGSvHRQPdhE8T/+4a1RSqvatCEKrLmZGb8J+N2l6qc3bk48ZWALKy73hHhW7mpz/E0koa85TPHQFIInz4NRFHy74epMAYOimMpvBI2cG3k4MrUW1hBB1GMKIZcVqER35w31KjLKiZugJFjSRtM+qqa4yiG1eBKdtSzsxAQtkASyypyL2AZY0c7e8jcKoisgh/9vSiryDTAisyxmlsF63NclFXwrvFL7+wAAH6tZmHHQ1dsECnAWS9jwzDwN+65Hl/+aDHUJNtRaKAp7+SpSxj2LNx9/eFa75Mx/JxjIouufo1JTlVGQI8hfOZYsDVuW/DDuDEdty60i+PsuWjneP0oUm6E6lrbup0u5o8dWmzA7adR820xpb5AKjboEcKglY/lYnfuS3toADqBtUh6tAmelVu206G5gtDx2z5AuziIj5Yg0/sKisP1UQ9+GGPihRnj5TLMIw86eiSW+bEVZRUyvXFyfGpbckHY7Ep24Fi4OvMFzLFYc0y2PEWOFkBeSBw/NMC7O3PEcVzQlUZRjEsTDeZYUqwuHqP8XgH4rLcfRguMiExWQSbkMgalCuhta7ZZrknkzHHxPP3e3/gU92944SlV8djpy/jcLWu1m16yhjwuc5x8x5LmeilUNcd0QcxjgvMdjWJDHpAwW00FyeigrC+DRb5YaK8hT9nKrWOfYzJOsTuBRJbihREGZvPPbLawstniOP3cjhZWXhDBDaLyhjzKR3+jiwMDvVPMED0Vfbn3SkPeAQ6YYylYGzUWa2kQCL2Fn4dISKzcNPRIrKzCUZJVhKWrbFWT8jYa8mYpc8zqS7NCVBYfnTVCFQdmUuwfP9xHGMWZpR2Nnbmfsc5TTkMe63PcV27Ii2EaWPAhZWFzAkw8Jp5VJqsgheWo13wxQya8Nn1TgZytH2p8B154ShXszH28/O4O7r2lPvOeWblxCgQib3BqMECqch5yzxuG3K2iYOWW3t/Lcqyoyhy3YV0Wx7HWDtkgZY670tzOBFKkquykKnJihi+r6Gp9QFyFyhryyHzSJasv2ikm8782cxztDSu3JvHgg8CJE4BpJv8++OCyj0gNB8WxBNnEIrhZic8svYVPNEYyVmRQkzkud6vwS5ljVb1aKw15fggvKg72WUIeU/wvyCoksb2k2L/2UNK4cmVSlFYQvTHA337LGvJIMa64va2y4udpqv2Q0RxLmOpZerwDDutaF+SebFuHOvOT71CWdkWDF55SBU+cuYw4Bu5vQJZiGAYs00DIOSbC5tYh4FVlFeSzjgx70oa8oldtNU1kU3D3UHw0kZYoN+T1utW2Zotitjim2P824DNjIUEuq+hmcbA7Jw3m8oY8OoG1K5B7oGDlVtF6MNDQvu8HkKS9M2eAOE7+/da39keB3MhVMAzjHxmGERuGcYz62aZhGE8bhvGCYRgPNfE5XUPF5xjAgmMFWSnKPDzzVaVacZocg5H9WxYCMnHD0lW2Y6m5E4Qa5vgqyNwqgrjAHmZbycxx0bZPPN1u9rp0ILr2cBKxynMSuZjqjQFgwhlE3WDxmqtub/thefwsL1WNjY/uKcgq2tgGr8p06EI00ctgS3YLdHDy1CXYpoF7bl6r9T4EtmkIdjBSWUWN0VXVQpAsZtaGPe61CwRjGBmflsEcEz9yHbcKVe1/FWRBR8oJecm560pakS2K2a17jd6VKhAFyPQzWUUrH1vArpuQHOU+x8nvu9Qci3aKq7L6/h5qyGsCvKS96TT5+V5H7eLYMIybAPwWgLPUz9YA/B8A/nocx3cD+Ft1P2cZIFvlouKQyCouLzDHCrIKjS1C8vDZVLFWxqDtKmiO+z01WYXf8Eo29zmWyCoK8dFxbuUm8ZclA9HxwwlzzCuOtynmWNaQRwa3slAOgiAqj5/NCntqcSMKAZHJKspiVKugM+a4wndoyuf45OlLuPuGI40tLmzT4Bavmayii4a89LOOjBx4YVRosPMEu1+k0FpGSh55lnQ0x4ZhJPaTLcgqgow5Vjsecv90tX0/9UIMe1ZBslXVEUEVXuZzvFxZBfHtL5MKZrKKTplj/k5xFevBMIoRx3Kv/P2G/Zy018RV+BcA/jEAelT+2wD+Io7jswAQx/F7DXxO5yjbKifF8VWaOVaQVeisKsnA7dDFsYJbRdkqu2+pxVs2bS0zdJLiOAZHViEoROnrICuUyMR5bVocX+Wk5G1PaOa4yDAUNMfKDXnlzHHGQlOLGy+MFzTtUlmFH8KxzVa6mbsqlkhBUUVWoZs2RWPuh3jmrau4/0T1yGgWtmW2JqvQbcg7MkzGIrZQIg21bGPqoGNpAA030C+OgWTMaoU5ZhyByjDoWNs65YTmAPn5a4v9JztcRVkFKY67llWoFcedyir8xfmCQMennIB1pvogYD8n7dUqjg3D+B0A5+I4fob51ccArBuGsWUYxhOGYfxndT5nWaCT2XhYGxJZRZE5lunpdJjjPIhEXVaRuFXIZ2ZVa6Sms97poqjgVsFpWCPNMqRYkG03k4Eqk1VMeLIKD4YBHFt1uA15Ip9jFbeKMs0iNz6a1RzLZBUef5JsAlUTnXQxqyWrqH5sz527Ci+McG/N8A8aPctosSFPbcdinl6vtbQ4ZgulpMGnOBblhdUSmGOFMZIH1ch7XZBFl46VG9ClrCLEiDOetx2MIpIVdu1zPFZsyMvdKrqTVYh2ijOZmgarn+1gfICKY17SnmEA3/zmco5HB6X7i4Zh/AgAL3XgdwH8MySSCt77fh7A1wEMAfzSMIxfxXH8Kuf9vwXgWwBw7bXXYmtrS/ngm8R4PC589um3XMRRID2mgQU89+qb2LLOAQBe3E4ehhefexbhOX4BQLY+X3ntDWzFb0mP67U3PRgAHv7ZQzAMA5e357g6jqTHtDPzcOnCO9ja2ha+5q0zSUH/462HpEleFy/NEMdo7LqcO50vJM6eeh1bwZmF35sG8Mabp7G1dR5APmC8fTb52a6X/PdLr7yKrfmphb99+p1kUDz98nMAgKdefA0n/MX3f+5VF6s9wIp8nH77PLa2Li38/pU3koL6kZ8/DNs0sD1LBr9nX3gJ61dfF3+v83P4nvy6TP3k2F9+9TVseacBAHPPx7vn38bW1vsAgLd2k897+tnn0HvvpYW/P3XWhRmFla4F7/6m8erl5L599PGnMDndnpXbs+n1f+LRX2HVUZsEXkqfqZNPPIVxxWP7d+l19c69hK33X670HiwC38fb584XnrOnzyXf0Z9PKz83V9zkPnj+xZdxfPyG8HVPXkju+cnlZHPupz/7OTaGeTFz6owLxMV75vX0ej/2xFOYn+3Wyo08U6defw1b7mnlv4tDH2ffLp5vgrJ7XITL8+R43lA8nlcvJufukccex8X19p4VgrPn54g5Ywt5Lh57/Ensnmr+OJ57O31WTz6K09Q99d40OV87k3kn8/WTZ5PjeO7JkzjbF48ZZG549oVXcO3kzdaPCwBOXU2uwasvv4CVS69kP38/PUfPPv8ijlx5Tem9xunxn37zTWxF/Lqg6j2+LNxwA/Cbv3kHvvOdGwAk1y6OgT/6oxBHj76Cb3xj74oKSkfFOI6/wfu5YRifAnArgGfSLbsbATxpGMb9AN4GsB3H8QTAxDCMnwH4DIBCcRzH8bcBfBsA7r333nhzc7PaN6mJra0tsJ/9/UvPYnT5vcLPaWz86ic4dPQoNjc/CwCIXr4AnHwcX7jv8/jMTeLGH/tH38VHbrwZm5sflx7Xr2Yvo3fmFL72ta8BAL5z4Wm8410SHpMXRAi+95e466O3YnPzo8L3PeOcBl55Afd/4dexsdoXvu4PXnoEjm1ic/ML0uNUxYWTZ/FgWrze86m7sPnZGxZ+7/z4L3H9jTdhc/MTAFIbnx98H3d+9HZsfuV27Mx94Cc/wK233Y7NL9+28LcXn3gbeOYZfPXXv4DDTzyM9WtvwObm3Quv+bO3nsBHvDF6lonVwwNsbt638PsnvFdgvP46vv61TRiGgfd3XeChH+G2Oz6GzS/cIvxe//r8kzgU7EjvlZkXAj/+Hm4+cRs2N28HAEQ//C5uO3FLdh+88f4Y+MVD+NjHP1E4N//6/JNY8+SfIQLv/qax8fZV4NGf4867PonNu67Vfn9VvPDT14GXX8Fv/sZXlBuyVk5fAk7+Ep/89Ke5ISEsnn7rCv7rP3tqgX2/PI1wx/FV/Pu/9dXKx144rl/9BMeO588+wblHzwDPPY+1Q6NK1wpI7SF/+kPcevsd2PzSrcLX7TxzHnjqKdx1xwn8+OzruOfe+3HbNavZ73905TmMLr5bOI5rzlPXu4XERRlOXZwAD23h05/8BDbvuVH57w6d/CmOXrOGzc17uL8vu8dFePvyFNj6Ke76xMexee9N5cdx5hLw+C/x8bs/ja98rPx+rIs/fONRHHMCbG5+aeHnh89eBk4+gk988lPYvPN445/79q/OAM8/jy9/6dezPg4AuLAzB372Y5i9fuX7Wwcvbb0BvPgyfvs3viL1YJ/7IfCT7+H6W27F5uYdrR8XkI5Nv/wl7r3nMwtj03vpObqVM2/8t995Hp+6cQ1/8/OL9/77uy7wkx/hE3d+FJtfPMH9vKr3+DLx9/5e8Weua+FP//Qu/N7v3dX58aiiMmUQx/FzALIn0jCM0wDujeP4omEY3wHwB4Zh2AAcAL+GRJu8r+AF5TrS9ZWetlsFoL5FyG7Xl8kqVD0hVaUdfhRj1GBDHj248Qa6nrUYa81u7clkB5lLgG1ifcXhN+RNXGys9BFEEVeb5qUyB6LRzOQnZVZuTAw0D6wNXRzHBa1ymayijWY8IA/laFtHOfNCmEZRxygDT44iw9NnL+P09hS/89nrF87tbzdcBNoW362iy4Y8VnPMyir8gO9T3l9mQ16WQql3L/da0xzrbWeTcasrzbFITrUsWcWga7eKuQ/bNEo16n3bhGF025AndqsQa/r/4qlzuDz1C8Ux0Xh/kKzcgP3blNfKflocxy8ZhvE9AM8CiAD8X3EcP9/GZ7UJlWa09ZGj7VaR/F7NSi2gPH6BZKCShYAQfVapW4Xi5BsoaGl1QDsF8AZ8h2k49JgBWsXnuG+bWBv2Fq4LwfbYw13XH8buPFgIb6Hfg9ZCiiKtWaiEpbDBEVnAy0JDnrjhsE3NMbkuU05wSpOYekkiG9sgJoOq7puAWPT9D3/z01p2YbqwTYMbv5w15NWY41S/MxlDiOc66zaSWEMVDyTzWl+ClVtlzXFbxTEpShRdAsgCtauFxdQLs+ZvGm0Xx9mioZCQR4iVbhryxmmDedmYYRhG5obUFUQN+KLFrRuE2J0H3IVVIHCW2e+4+ebE35j3872MxpYocRyfiOP4IvXf/2Mcx3fFcfzJOI7/l6Y+p0v4YVS6ijsy7C0UWSpuFYA6c1xMUJP/HSmOy9wqVLtpdWJVVUAXd7xCz2aYcTYhMCswJcWxY5tYGzkLLiIE749dHFvtY+TwB1GPYYBV/VX9MCqdXA3DSJj/9NjzSZneGRA3n039sLVo5646vWcVvoOt6VYxdgP0LKPVwhgQO8e4fgjDqFcck3uirABxC8wx61bB3/1aZgiI6hjJwrHNVhLytBvyOrYMm/khhhz7QR2//CrIiYnF85LsrHXHHI/nQalTBcHQsbOgoS5Q7laxeG0upU3ivHunLFdhv4LXlDcaJT/fy/hgXYWGoSSrGDm4MtNzqwCSgU01oY4t1mQOE+rMcbo1VlYcR+VFnw5UZBW01Vnm1pEyqlmBySmU6HO/Pioyx2TVvrHiYOTY4uKYunaWacAw1NwqVKQCtmlmha+f+YgWZRW8omjeBXPccqf3zAu0v4M2c6zg890ELBFzHETpFm/1RSXx9VWVVRBmkWWCk0Vb8TgGGfu5j5hjxd02XWSMnWJRQuLbu/M5DjDijJWdySqY8d8wDAx7VqnTUVPYmQdY7cvT8QhEpEdbENkSWqYB2zQKzy/x2ecyx2SR9gFyqwCABx4Avv1t4JZbEqeKW25J/vuBB5Z9ZHIcFMcSqMkqerg687NJkg2REEFVVlFIUFOUVahqjssKdBW5gA4WmePiMSayikWrM2CxgKQLTBpeEME0EgZobVTUHJNV+8ZqHyt9i+tz7DGxtkkxbpYyeKoMu00tbjJmRlFWMfWDVtLxgOR+6FkGNzWwScwEnq0yyHTYPIzdACstnScatmUKrNyaYfhZiREPcz+558nzzjLHIv/tZVq5qRIILPp7xMqNxLd3VYRNvZDrC65KcFSFH0awTKMQPgIki6sqX/8vnnwbv/O//0Lrb8auX7oTStB9cZzugggWL+wcTxJaeceY+Rx/gEJACB54ADh9Goii5N+9XhgDB8WxFGUhIECi9YtjYCdlj1U1xzoNeTSjYafFoyi8g6QJqcRH08crQuJz3NxtQjeU8ZrLepa50PzmcQYMW8Cek8LWMAysjXrYnQcLRTRZtW+sOlkYCQseA9xXKFL8SC1J0KEWN1ngiKUmq5h5UWuyCiC5Hm1vFU+9GrIKReZ4qhCf3gQSzXHxmOZ+WIj6rQKVMcINkvOZMcGs5jjkL/B7VhIm03YiIg9VQ0Ba0xxrhi84lgmzw8YvYUNey97kAZVMymJgm5VkFc+f28Ezb13h7riIMHaD0nQ8gqHT/hhGQ3Yv93vF3eGMOeYQM7qNoQdoFwfFsQS+QgAG2c4k0opMb1hyg6szx4vMj1Oiv8zcKsoS8khThYKWtsmHlR7keWxIzzYWCtG8aa2cPXf9MCts19MGJTolj6zaj632seLYie0dU3B5QXFB1FMoUlQbF2lNNZ8VF2tNq0gSdLDSt7P7py3MKzDHWSqi4oQ68QJuaELTkMVHD+oIjlPQ+nQR5n4i4cjivwshIOIF/sA2l9OQVyE+GuhCc6x2PIZhCCGoefYAACAASURBVGVZTcMLIgRRLGxeBlqMj5aQQwPHqtSQR8YXnR2LXQ3NccIcd6855t3LvMUcSWjlyyo+mG4V+xUHV0ECn9li54EUYWQL31XUG+owxzxmUTRpqmqOVZnjMIobjSseSBLygGSCoosgUQHJs9Dywijb3iKLFlp3TFbtx1advAGNGaTcoHjNVYoUlV2G5NhzTTXvu7FNewRxHGPqt2flBqTR3i1vs08r2NERWYUqczx2g26YY8vgHlNTsgrW1pAH8lmi+G9fIvfp96zlMMc+acjTO0etJeSF+lrPoWN10vhFWFBeQ55pJmNFm5pjUR/FwK4mqyBSNh299niu/jwPe90sWgjyhR6f2S/KKpI5iL9rmTLHDbtVPPggcOIEYJrJvw8+2Mzf1nnf/YBuo5H2GVSikzPmeKE4Lh/0+7bFtRJjwRZdZFXpB3HiIM2A5NCXaS5VrdxUiz5VkMYSy+BrDh1GVpHHZzOOHVyXgHwwJ9ZW9Dkmq/aN1T5lXRbi8CBv9mAb8mSfR0NVc9yjvHE9TkMe+W+26HKDCHHMZ9ubwopjt27lNhPoJ2XIZRWKzLEb4NpDg/IX1oRtmgij4vmaB2SRVq9oUZNVRIuyCk5DnqiwGNjmchryiJxoj8gqfI5rTBm60rZO0wJctNvSt63W2H+RRzaQ2Lm5nj5zTM6ZjvRh1w1waKDWkLfStxpplJx5IRzbLCWGZDvFvPuV7F7ymHPdxlAVPPgg8K1vAdNp8t9nziT/DZTrfmV/C1R/3/2CA+ZYAlXNMQBcnhDNcai0Xagsq2AGKCfbYub/7cRNtt7LHmp1t4ryBYIObMuEY5kQ1UesrIL1OU7+P585dsMok4usZ4uWRea4b5tYcaxssmGb8vww4npWljWDifxkC9+P0i9nmmMmvpu3XZ8xSC0zx3uyIY8sCCWNqDQmbtiJW4XIOSbRHNcfWtUa8pLxRtRgJ7JyA5KmqrZYRxnyEBB9WYWqY4kOwlBPVgEkz2EnxXH6GeLi2GxNViGb/4ZOReZYU1bhBiG8IOq8Ie8b//ND+L9/car0dW6wGBpFg8cck91LP4wL93K2SGtQxvi7v5sXsATTafLzOn9b5333Cw6KYwlUiuN1VnPMYR55UJZVMEWXiqxCZQtKz+e42dtk0DPRFwwArHcs63MMJAU2T3NMexSzchcg2dI6ttpPNYN8r1Kezi5hAOQDrh+Im1dokIbK5LvxfS15RQBhQ1rVHHfQzFJFVqGbkDfxAqx2oDkWWbm5TblVqFi5pSy1aSbWb7yGPNHi1rHNpbpVlKWIsmhNVlGhKBl11PhVtihWJVmqwI9iuayiwsdmzLHifafaYE4w7Nm1r0sQRjh3ZYYz29PS1xIZJQ88u1ayewkUpRVZQ16DDfB10ulkf7tfU+90cFAcS+BLunUJDg96MA1WVqHCHKuxNqzua0FWwYFucVxW9KnY2eli5NgQ1S6sbVpWQFLsqqgRij73RzjM8cWxi43VpGgmzCLbgMaGgJBjKmOOg6g8MCZ5LyObjHmseP55i/fGNNMetlf0jfo2196uSYgCDWSwsuJY3ed41Inm2OSy2c015JXfdy7FUvMa7HwmYZPGoGctOT66gs/xHggBAZA25LWvOc6ZY/793O9Z7Vm5cZqTCSo35BHNsWIBqxpqRUAa8kRuTiqYuGH6b/n1dYOQa+MGCBryxjlZU9zlaZ45FqXQqaTTyf62zvvuFxwUxxIECgl5pmngyLCXN+T5appjVUN7P2AT8uSyirGr1tmbaY4lk00UxYhiNNqQByQFniNkjhebnHjsKk+TCySFPjn3h/o2bNPAldmi5nhjxcmOASg25PE1xyoNebFSI0Vy7Ivx0ewExLOqIwNpm7KKUctWbmEUwwsi7e8gC35h4QYh/DDuzMqNx2bPg6Ya8ozyhrwgt/fjFbuy+3LA2fbtApkfuWZx3E+LjTqFDw9VtJ5daY5JMSlaFLcuq7AF907Vhry04FRt/N3VZY4dC1Fcz95unJ7zsUpx7EuYY+b5iuMY22MP1x7uAygyx2R8a5KMqpNOJ/vb/Zp6p4OD4lgCNrpZhLWRkzGUyUpSVXOslpBHMz+EbREVaxPFAIRMViFp5iAFeNNxlsOeJWWOy2UVAp9jqrAlXsesW8XGajIwrVANeTT8MOZGgapYualMrraZFzy+gEGTMcdthYAA7Vu5EaatijREFPzCgrA+Ky0y7ARJQ55Ic9yErKKcFXT9vMeBVxzL7sukmWs58dFVor3Jc9l0MlsevqApq+jg3M2UNMftLHC8UJyOOuiZ8DS8ignIeDtXrKyz4liDOQbqeVCTpmSVxY/L6VEhYJnjXTeAF0a4aX3EPcaMOW5QVlEnnU72t/s19U4HB24VEqhKCtZGPao4VpRVKLI2HuOfWyar2J0HuOnoiPs7GrZpwDTkzHHGqDTMHF+/NsROPOH+jt1KFjHHvMWBG0RYG+WvOzLsZXIXsmonsorMyo3ZGnV5PseWWVo0ipLIeN+PfCZPMgLwG7GmGYPU3npWFIzSFEgxMahSHJfEphNMFK0Mm4BoR6EpWYWjsGPhLjDHRfcJP5I15C3JrUKxL4OFQ+12Vfl7EcIKsb3DjnyOyxrynBa9qmVWbkl8tN77xXGsbeVG2NvDim4VtEXnut7hFT5TnTkWLFyYhlciqbjp6AiPn7lcsAKsYimoAlLMNv23dd53P+CAOZZAprmisU5FFStbuSluEbLd5mWyiqQZqbwwMAyjVNrRhrUMAPyv/8ln8Q8+2ef+jrVNy4tj2uvZ4IageMzCZJ1i9Mmq/dhK8rl5cczKKopuI46ClZuvuJCyqWMXaY7lsooWmWPHQpBKH9pAxoJVkByUxaYTkMm3i+JY1JDXWHy0SkOeH2aF+IDjWywL8RlwEry6gCqBwIIUak3fn75mCAjQZUNemayivWsYhLFYVtGz4IbQkri4QQTyuKgXx8n4rS6rSF7HS6BTha7mWLRQ69vmws7MdmrjdtP6MD3Gxfs4yGQVB2XZXsDBVZBAxrrQWBtSzLEvflhoEBF/adHF6L4yWYVggtAxTC/zDQ0q+H+qYKVvoy8YdFk2jhwfLS0RbbGzjNLayMlkFXR0NDkGoGjlxmOlkkhr8SQQRjHiWG1y7VHnXNSdvKyGPDKxtNVoVMdxQ6TvZdEtc1y8TnEcJ8VfQyEgalZuKXNs82QV4jGsvyyf48rMsZr9pC7CirKKuo1fKihtyGvTrUKWkNczEUNP4kIXm6oLC21ZRfrcTdzqCwbCGKsVxxJZBZPoSDyOb0x3dtlxtq35VgVdBXrsp+CQg+JYAtXo5ERznBRfnkSDREOVBWGtxTJZhWBQmrih8kDCbvuwCCpsN9YF3bAG8DXHIn9ZtjlifZTLKrap6GgAaYphcZD2w6J9UZm/aqZZVA0BiRgrN2ah0DOXZ+UGqGntqoC8bxVZhYpzAwCM00mxKys3dgeDPE+duVUEuYSjz5FJeGEkCXJYUkJeRVlE7rDTbDFYZZxrovFLBdMyK7deO/Z2gLznJgud0bh/6HFF1SVFtyFPtCOog4mOrEKyEO4zkheSjncjYY45zbNA9/HRJOzjzBkgjvNAj6YL164+pykcFMcCEDZQTVbRw8RLzMpV3SpI017Z4MrqvmSyCjcI4UkSsVg4lrwpMCveGmwQKINYVsEwxzyf4wJznLuIXGSYY8MwsOLYCwxDGMUIo2JDXllCXhbmoRgfTVhvkc9xEoQiCAFp2coNaI85nteSVZTrb4FumWObI+8hk34zDXlyVjCO4wUJh6ghT/T8DnrtpavJoDpGssg1x80W9CLXGBnIPdy2tGKWymZEjkGqlqBVUCbJAdQb64DFYlNHc+xYprJMiYyPdaK9yfg39cLSnQG6IZYFaz1Idi9vXCtryOuWOe4q0GO/BYccFMcC6LCBayt5VHGyklRzqwBUiuPFhLyeRFYxyVgzRea4RNPYVoOADKQJiQxKfpjYPlkLTYki5jiEY+WD6NrIwdyPMPfDzHydMMdAMpDSg2gm4Sgwx0Zj54lmAz3BpMyzqusiIY9M+G0zx1UKfFHwCwsyAas4ttRFjyPvIcxtI5rjElmFHyZWi7RbBT2ehKkVo6jou2a1j5kf4rULu7WPVQdVG+rI4rPpYjBM7ysdy0oic2jbF3zqBVKHmmUl5JE5RoVdJaAX3apjzO7cV94JBfLrUmcMI7tPQRSX3mtsnwuNfuo2Q+ay7YmLI8MeDg/5x7iMnVqgu0CP/RYcclAcC+BpsIFrwzwlTzU+WmWLMEqZTH5CXrE4JGlCqqxZWcMPeVib9jmWoWeZiOO8g9zjWFGJigYvXFyYkJS8K1MfF3e9hZ8BiYyAZo6zcAKe5lhWpGQJWyqa45wBFTHOtrkYhAIk3dc9y2i1WWPUr6/Xk2FaU3OsIquYdsgcW6aBKE6eU4KMOW7CraLk+SRb2hlzzCTelS3w/8PP34hhz8K/fOiN2seqAy8I0a9wH5OY9cYb8iq48gwbsAxTQVmipKpffhXI9OqEZHh/1+X+ngd6XFGVVej00ADNyirY/8+DrAGfJcCIW1LObhebZ4Fud2qB7gI99ltwyEFxLICOjVkWVTzx1N0q0tdIZQ0cn2GyzcVj0cgqXoc5lmuO2/E5loHVVPtBUQNsW8XmrCiKC3rhtTQl7/LUy1btdOHLplxlCyKOW4WsMMt10XpuFX7GVDNWbnZRQjDzmnFAkGHUckMe2YKt8j1EwS8sJulnrHSgOc6fRao4Dqp/R977yxZlRBLRF8gqyHGJFvhHVxz8p/ffjO88fR5vXSqPym0KqrtrLMiuUOMNeVEMyzRgGHoNeUB7uywEMy+ULiZZXWuTYPtdaFxzKC2Ox+rFMT2u6CTkqabjAc0sWsYLxbH8fVxJcykbtHVx7OLYSh+OZcLk9LsEYQzTSILFukSbgR50A954DDjO4u/3cnDIQXEsQN4spcAcU0WYbJuFhkpDHr8ZTfx3+sWxPGSgLZ9jGVhNNU/3xtti5xW2a1SENO1xTMCmXJH3YFmtni3XHOuYt9tUs50fRjCMIjMvklW02YwHdNGQR0JA9Fldnr6Xh7EboGcZlTSturDS603fi7msopmGvCCKF5hpGqQQzmUViw15ZPEl26b9L75yK0wD+D8ffrP28aqCF9GuAocpNpqCH0XaY9ywo+J4Wloct2fllvS78M/L8UPVmWOdAJWdJTPHZbIR2U5xxhynz+T2JJmDDMPAyLGLzHGkFiTVNNoK9GAb8La3k383NvZHcMhBcSyAzhbHeqo5JgOFmpVbuX6OxyzKZBXkoVbVaLFWM4XPFzSMtYksBSugi2OmWOVssZPzyPocA4kWnKzaaYz6dsY0ArRtXLFYlXlS+xqaY9r5gnSDs4xVUkAXZRVt6o2B9hvyZukkUaXI5zl48DBxg04kFYCAOW64IQ8QF4MuK6tI3Scyvb6C3OcjR4b4D+65EX9+8i2tQqcOvKrMcVtuFYoBPjTIAq9O45cKZl4o1ej3bRNRDKVdFV34gbhYOzLswTKA9zTuGTKubKw62VhQhvFcjzkmz10dn2O6sC4bC2W7IOzzuz12M4KGF7gUSKLe28YDDwCnTwNRlPzbRMHKa8DzfWB1tdnPaQsHxbEAWQezwI+XBtEcv7szBwAl5jiTVSjEN9uasgrV6FynpJmjSnJUXbDFP29rz+Ywqx6nOM4ZfT9btdMY9ayFQTTTHFuL58/hFEE0dBYRtF+vKIHKsY1CQZRMku0WfW035M28AIah9nyw4ElpeBgrxqc3AcL408eVsbkNNeQB4qj4jKWmGvLiOJ+MA0W5z3+5eTv8MMIf/eJU7WNWgVuVOW4pBITIKnTQlaxi6pc05Cm6HlWBLPXTNA0c6RtaCyrS6Lax0ld2uUhkFWrpeOS4hr16SZ9jReY4juN0p1gc0AIkjeJBGOHy1M+02kNm7gHkUe/7EfutAY/FB+dKNAydrfKRY8GxTLx7NRkoVCZGFVsirqxCwp5MNdPBytwqyOd33ZCXfDZhjvnWakXmmGwx5+c+Y45n3sKqnWDUX2zI8znSDN4xscjCPFSK43SrPI5joVUSV1bhB63LKkhDXmvFccp+62g7CWzLzJLMZJi6YSd6YyBftLYlqyhjSlnmmCw6yDH4imPYrcdW8Nc+9RH8yS/P4OrMr33cZWgiPrpJqPrZ0xi2vJAkmJYyx6R3pdlzEscx/EgsqwCgXRxP08Xx+qinZeWmI6sAUrmcbrY1hYkbYCPdDZZpjnm7lTTohrxLU2Ilmie0FmUVsfZ9uJex3xrwWBwUxwKIon15MAwDa6MeLmgxx4t6JB58zjY/kXnwZRVpM5Iic1YaH72EhrxMc0yK46A4cfUso+DzzHOaGPQsDHomLu56uDz1scHKKpgByuW8B/3fopS8nOFXkFVQLLTIKoknq5iVdK03AcdK/FRVkqGqoKzzXoaeaSg25HUoq+Awx2zBWuv9SwJ/SBFMW7kByCJr892v8uf3H27ejrEb4E9/dabeQSsg0Wnqnx9V+0td1GGOW/c59kKpL7iTnZNmj0PF5/+IY2jJKiZuiBXHLjRCixDHsbaVG5BadNZkjo8fHgCQu1VkPSoSn2MgmZuIW9KxtOgecNjtIIy0Isz3AmSJd202+nWB/XUlOkTOBqoNmrrFsQoLwtuuz2QVnL/LGp4UmbPS+OilNOQtFgRBxJFVmIt2b4DYaWJ95ODNi2MAwDGGOU5CQHg+x0XNMQC4ApZfFAPNg02x0F7A37bscWQVZQxSE0gaReptScpQpp+UQUdWocs0VQUpqEKulVuTxbG65jg5hkXmWEXHePf1R/C1O6/BH/78VOsFX13mWEV7rgM/jLWLkib8dFVQ3pBXTrJUgUpaWxXmeKVvpa4q5cfrBhH8MNZ+nlcUi28RJl6Aaw/3s/8vPD7GLYYFzeoTn32aOeZFvXftcVwHZYl3bTX6dYWD4lgA3Wa0tZFDFccqVm7lgxqPvU4sh/gTxNgN4dim8jGXRY8uoyGPLQh4EaY2wy4D1EDFTLpHhj28/l5SHG+sssyxDTeIFjyVee/hlDB4+XlSsHIzybEnzDGvSHC4sor2mWOAOHi01ZBX/TsksgrFhryONMe84pXVAdeBU8KUsoEjRMpB7OQChQKHxj/82h24NPHw5yfbFQXWDQFpXnMsjtgWYdAj8fNdNOTJQkDakVV4CmPaWt/ApYm7sDiUYeIR5ljNrYLofQ9XYI7rLFqmbpi5cciY40zKJ3i+aOZ4m0lo5emi/Ui/MXSZUEm8a6PRryvsnyvRMXQcCIBER7WThnBoNeRJtsN47LVhGOhxQiKAdGWuwcw5ljx6NFxKCEhq9E/JKtjmHZ5LgIw5PndlBmAxHQ+gm2qC7LOAYkMekbXwUgkBOmyh/LqTwS8II6HW0TaTDnR60unCyg0grEt7CXlVv0PPVGOOJ27Ymawia8hriTl2OItAGgUrN9ta+Hnuk672/N534ig+ft0h/ODFC9UPugTEj7xKU2ZbbhV+FGvvjhlG/cavMgRhBC+M1JjjhmUVgWA8pXGkn4TgbCt6HU/dAKO+pSx72J3ruS8RjBqQVayPHDiWmTUR8pBpjgX9BfS1uZieI+KYNOQsEBJZxf5hjvd7w10ZDopjAUTpZSLQyWs6sgqplZuAue1ZfP3lxA21PGTLErhIA1SXTQIZS0tbuTGOIWQLlC5WCXPMXq/1lR6IAxuvIQ/It0bFISBWdiw86EhwaNmIL9CYZcU49XldhIAAyTlptSGvsqxCNQQk6KwhL5c40cXxIptbB+UNeSxzzMgqBHHoMnzhtg08dfZK49IFAtEzpoL2rNzEYRcy1G38KoNKoiQpzNpKDZRqjvvJ/a+qOx67ifPGoJcUhiJrzOz1pDjuq7tVAEX/eh0EYQQ3iDBy7LRhW0FWIWrIo5xEticebNPIoqN5BbwfxvvKrWK/N9yVYf9ciY4RaEQCA8CRUf4Aq3h4qjSXiJoCezbf83WqWRj0U59j0SCl49jRFHIHgNzujPf9ASxssxPXD1b/dWSYF8QFn2PGjkmsOV5ks1mougIAi5IQP4y5zVI8C6+Z3w1zPOrV0+vJUKepMGnCVGGOu2vIs3khIEES893EbkuZ5piNqs5kFenPg6i8wGFx34mjmPkhXji/U+2gS5A1vVYoAuxUUta0W0WVhjwgkWW1qc8m770MtwoVSd0RJzlnqil5Uy/EimNlY0DZMe+6iXOKjs8xAAw5ARuqyJra+1ahJ4UFzyGJBi0DIm5JxKmHt+uQ9NfsH+Z4vzfcleGgOBbAC/RY00XmWMHKTSMhj9eQxpNVTDx95hgQD1KBprSkCbCFKE9zzHMJ8AST7nq6aKFX7QTkXJEBkOd4Acjt84CcYXcUPLF7jFsFzyqJ1iWTzw2iuJviuEXmeOrJPVtlsM1y5tgNwkoNPFVhCUJAmggAAag0zBKfYzLe5Mzx4k6IzvN734l1AMDJU5cqHHE5soKiwiLJMIzSJuIqqMrYtanPB/JF+zJkFSqaY8IcqzblTbwAo76NYbqIK1tYZLIKXSu3XvXrMvbyz1zt2/KGvDIrt2wRECYJrRQ5wyvgg1Bf3rNM7PeGuzIcFMcC6NqYrdPMscKWoWkmA71uQh6QaBG5bhWuPnMMiCdfMul3yRz3OLIKtuDN2OUFCy2+/ossWuhVO8EK03EullXIG/J0GPai5pgnq1hkDGcN6ljLMHLkW4n/9P97Fj+sqEmd+1Hl72BbxVREFrmVYUeyCrN4H879qJEAEEDd55iOjwaAefp6HRcVguOHB7hlY4THTrdTHGdhPRW3j8vsJ6sgrKA5Buo3fpWBPIfDnrg4zAiOxt0qFJhjzeJ46oZYdew8eruE3SWyCn3muPp1mbp5VsAK44PPwhPMOQQ0AXaRCaEa9ix4VDM4kJzz/SSrAPZ3w10Z9teV6BC6Tg309r2qh2e/JKFOVKCLZBVE06WKfsnkG2j49zaF3K4pl1Wwn595IVPb2aLtWiJ3YT2OgXy7krAM+cTNJOSVWEj5GgwdKaC9MOKy4kBxO32WMUjtM6KyreIoivH/Pv4WfvxSteI4YY6rFY6OVR4fPXH1QnDqIk/Io7XvYSMBIED5omzuJ64PZnocfaYhjxyXSsonjftOHMXjpy8hUnQh0EFZE1MZiBSsSfgVG6HqNn6VYaaiOW7J+1kl2MixDBwa2JrMsZUtkMvOHXGr0EnIA+pdF/KZq30bK31bmpCXzzkCKzdaczx2cQ3VEJ75ZFMLhOADFgKy33FQHAvgazRZAQxzrDjwlzXEeUJZBZ9Fm3qh1hZUmazCr8A81UUuKcibiniyEoAvq2BZe5o5ZrEiaMhji4my7W1ekqEIdBMX77vRryHvS4r3odP+dRg5FiaCiWXXDRDFwMXUlkgX9RryDGF8N8FEMyGyLniuKfOgucbJMuZ47ocL9zsbAuJp7GjQuP/EUVye+pk/eJMQyZ9U0YasIqhooTXstefsAijKKqit+yahIqsAgOOH+krFcRzHqebYzhb5rM8vi915ojnWbbAdORaCKK50nxCmeORoaI5L3SoiXGQSWgcMMQPszxCQDzIOroQAuszx+kp+46sO/P2SLUJfMJH0BCyaLjNHmCYhc1xBs1gXlX2Os+J48fuTRQtr4wYkzWdAsSFPZB1Xfp5UGvLyJq7E55gfH02/L2EXZNurTUHGHO+k0cIXFRtwaERRjLkfVfc5Ns00tUtcIHfNHIvio5tijstDQBZlKnlD3qKsQrcQve/WowCAx05d1jtgBYh0/aooIxSqIKjckKfm11sVs2xRXM4cN67DVlzEXHOoj/d256XvR/zkR/28Ia/s3O26ARzb1E5THGZyOX3d8XhBVlFSHJe4VZBzd3niYe5HCz77JPVw7uXXzQ/3DnMsS777sOCgOBZA1wZprQXm2JcwmbwJU9fjtSx6NFiCzzFPVsE2rfHcHEST7hphjleKzHFu5ZbLKkyjWOTyPo9Gps1WsnIjhbY4PpplqlW61pvCimMlkg/OfXk1LY5J2pMOSDBFZZ9jhk3ngXiSrnZk5WZzGkObbciTu6SwEg62IU9H7kPjxMYIx1YdnGxBdyxaxKqileJY4DdehjJ9fl1MFeRUbckqVBLyAOCaQwMl5jhbuDp2tgNWKquYB9oBIEDRhUgHE5duyBPvogHl97JhGHBsE+evJj779ByUHaNPMcfR3mCOy5LvPixY/pXYo9ApeABgbViFObak22G+oCGux2lOCqNY2+6rzDFDRXfWNFi2jFdA2pztbFFxfDQdkK45VGSO2YY8YWJdieY424LUaciLUis3BVmFivawKZACnDdxXZmmxXEFWcW0ZoHPY2lZdM8cC9wqupJVBOHCxNyzTFimkS1EfM0xjMAwDNx34igea8GxohHmeI9YuamGWVSFmltF21Zuzcgq6O8yUGSOq0bB1ymOp16RORbtVrENsTz0LRPnryTMOr17OeAc416Jj1ZJvvsw4KA4FiBzLlAsDB3bxIpjwTYN5Y7Tfq85WQUZaHSic8sM5IMogmEsJyFvoThmBp8sBGRBVhHCNov+skdXHPzB374Hf+vemwqfRSJgSYeyK9QAEwcNkVuFuj6dZhu9EuaYyCqywrIDtwpSWNKMBgFhjqdeqL1lOav5HVh7Ox7GFDvVBVh9PNCsrKJsx4L3WQPbpGQV1fW99504inNXZjifpks2BeJHXrU47rVi5VbNJYCEgJSFWVTFTKE4JmOO27C8Q1VWeM2hPiZeWMqgTyiLtCGzwyHC7jzQTscD8jGmysIl331KiuMgioVzdJlbBfkdeYZozXEuq8iP0Y+qhdE0jQ968p0qln8l9igyj1+NwnBt5GjFopY1l+jIKkiBN9LYUiaTpqwhr8tmPGAxQS6OYy67yksm8wI+6wsA/96nr88YZBqGYWDUy7fOvDDiXj/y+a4wNAdnbgAAIABJREFUIS/5ucoigmbGRT7HrKyCTCJdyCrIRMyzMCLFMaDPHs9qfgd2wcDDtGvmOH02QqYhr0srN1bCMehZHFmF/jN8f6o7blpaUabTLENrDXkVQ0DCKG6cySZQkVUYhlHau1IFWZNxyXUiDgxl7HHW6Na3pbtTNMbzqsxxdc3xxA1gGglxspKNhfz3UQm06dtWFpJCa46HIuZ4D/gcf9CT71RxUBwL4If6rOnaqKc1MZYyx5L4aJZBoy1o1D+/vCGv620eungk29VsAcnbYncDfmFbhqFjLzTk8QY6NtKahZc2UrA+yjwsxEcru1V0J6sgEwtXVjHLC+LtiV5xXPc78CQMLMgip6v4aJuzSHP9qPEQEDlzzCuOya5L9fj3j193CKt9u/HiuE58NPk70SK1KoIwhlWBBKjDUKpg6icNaWVzUDvFsRpzfPxwWhyXNOlmcgUqIa9M9rDrBto2bgCUfZR5GLsBVhwbhmFki2yR17EbhLBKdood2wTZWOBpjlkrt73gc/xBT75TxfKvxB4FYU1VCh6C9ZGjtYVZxoJ4AvaayxxX8MItY46rdnHXgWUaMI2cWQX4VnZAnmKY/H8xcyzDSj9PUxJpjglzL2zIE8gjeMiLPHF89FJlFYQt4bAui8yxXlMeKSCq6nF7HCkNi7EboGcZlZu9dJHHR7Oa42aG1TwuWeRzHBYWhP2emWuONbTwhc+2TNxz8xpONuxYUZYqVoZ+K24V1RvygGraVhXMPLUekn5P3rtSBbkNoPy8kF6O93YUmWPHVtYc7859HKqhOa6yaKHj5wnRJErJc/1yQob8frVvM84yxWOs2hjaND7oyXeqOCiOBfAr3KjXHh7gyFB9pVvWkEceFrZA5xXHeTewhqyi1K1iORqonpU03fgBvyGQHDfNHHuCwrYMI4Y55n1fFbcK1e0wUqh4QZRojjl/xzKGXcoqZFueOzMf5FbUl1Wksp+q8dEclpYFPbF1AXqhQ9BkQ55hGFKNLWvlBgAD28r0p0EYwzSQhYTo4v4TR/HKhV1cmVbztebBbaIhr+FCsE5DHtBecTz1wkybKkObzLG6rEJu55Y3y1ro2yZMo1xzPHaraY7rNeSF2c5TzhyLZRVlxTE5f6zPfrZD57Oyir1Rkn2Qk+9U0d1Mss8QVGjS+Cd/7c4sD14FKrIK0bY7K6vImGMdWUVZQt6SNFCOZcIPYiqUg88cL8ZHh5UYw5FjLVi58SYDizB4Qm22+iKCsNAk4lcmq/AyWUWig6sanKCDFQlbcmXq44a1Id6+PMNFTTu3WernWV1WUe5WQbZEuwKvSXAeNNeQB8iTAed+WGgGGvTyhry6DT7E7/iJM5fx9U9cW/l9aIhSKFXhWG0k5FULAZFJkJrAzFMLzWmjOFZ1KlofObBNQ1lWMUolC8Oe3OkjjmOM54F2dDRAL/Cr+RwTxpiMhaKUPJU5h8yxrM8+r4D3K+5gHKAd7I1lyh6EKNpXhuOHBrj9mlXl15c35InjhdnGpImnzxxnxbEk+W0ZzHGShpbLKljNMU+LKdILlyHxKs0b8njFccbgCVhLXsS1CIQZIAO3iqxi5kXZpNI2Mj2goCHvusMDjBxLmznOUv4qyyrK3SqmbtiZ3hjIC/Ywyp1VwihuTHMMyH19535UmJwXGvKCes/vZ29aQ88y8FiDuuOyVLEytOFzXJU5zgucdryOk1Cn8uLQsa2s0bEpqFq5maaBY6v9clkF0w8wLAlQmftJz8lqX19zPGIsOnUwcfNzTo5VrDmOSu9j8nyyPvt9O3FKmi0k5OndhySowzAA207+7SKw48MSEHJQHAvQhf6njDkWWX3ZnEJt6uozx5msQjCwhlHUueYYyGUjQs0xpznLrag5HlFepbICW8bgBRqLCHJPkYFbah2XJeQFnUgqAMrKTcAcr4162Fh1tFPy6rpVZMyxTFbhdSyrYAp2UpQ2JasAyC6RxK2iwBxbmea4qpaWfq9P37iGkw36HdeOj7ZN6QKpCnQWtzTqNH6pYKrFHLcVH11+na451C9njt0AhpEvjgc9eXG86yb9DXWs3KoUx2NKmkV2oUSyCk9LVrHIHGfseXoO4jjWasijgzoAIHVIbD2w48MUEHJQHAugs1VeFY5lyZnjgG/15XAmzMytQsfnmMRHi5jjaDmm5InOMpY05BVtvaq6Vaw4dsa6y3TLyaQsPk/qxTFhjlO/V875tRlZxcwLO2nGAygrN87EcnXm4/Cwh2OrfX3NcV2fY+LgUSKrqGL9VBWkOCZWbkTO0KisQhJ64XLdKihZRUX/Xhr3nljHc+eulupDVeEFEWzTqKyDLhszqyCxcqu2sAZalFUohjq1ojkW9HvwoBIEMvHCzAUCSMYB2T01TuWJVRLyLNPAoGdWivaeeEGWsFnakKdAyOSyiqKV6LBnZQU8IXpULQV5QR0EbQZ2fJgCQg6KYwG6KAwT5ljSkCdYSfJkFdm2dZWGPAFzHIRR5z7HQF6IeoIBmtXkAtXdKoaKzLGMwfPTCV8F5J4iA66sAZB2q+jCxg1A1iwjasg7MuxhY6WvzRzXddzI3CokRcCkY82xlWnfFxsnm/I5BsShF8Rfl10QDuz8fk4cd+qNYZ+/eR1+GOOld3ZqvQ9B1UUsQdOyijiOq8sqetW371Wg+twnbhXNO3iYilam1ygUx4lEJP8uQ8eSnjfSu1N1sZs0WuvLXRJp1qLmWMQcz7zyqPiMOeb47NPSkixXQXExWxbI0VZgx4cpIOSgOBbAr6hh1UE/3SKMBN6tnkDaYVvFrcWJF8KxTK0C0TIN2KaRpVaxWFacJSlERbo3XiBEssWlX5Ss9CnmWFJg9ywxO6Pj6kGKPD1ZRXMOCGUwDGOBTScIwgi7boC1oYNjq462zzGxHavKGPY4UhoWE2pi6wKGkTw/5JjIQrfJayWS85ACkf0s2tYr4KRL6uIjR4YAqkWG81B1EUtAmPSmUukyxq6GrKJK45cKkh2j8vu5DXs7kaSPh2sOJYvlUPJsjplnc1DSkFfFt58GzcrqgN59cmwTjmVmqXksLk08brgUjb5AVkGOMVvIRmoab4KyQI62Ajs+TAEhB8WxAEEHzHGWgCVhJPnMolGYIKZuoJWORx+DOD56OW4VtpkU/3qa46LnqwpGThKaEEax0OcYIEWKqCEvVh7UzNTHmQyKvOIlkxBQsoqumGMgZXWYCWEnZXKODG1srDq4NPGEizoe6rLfNrNg4CHRC3Z3ngDSPMrIKmoWpDREz2emb2aZ4wVZRf3nd30laYi6pLkYEqHqIpagrIlYF6SgqxICQu619pjjQENW0XB8dBArk0PHD/URxfJ7ZOoufpdk3FVgjivIKsj768pdgjCCG0QLTZCjviVkjrcnLrfopZE15HFkFSMec6z4vPKCOrL3pQI7mm6e432uYQDf/Ga9992LOCiOBehCc0weHJGsQRhKkXXJ58UJ0XTpwpHo1YKovmaxCnpEViFKCOQEQlT3Oc4N6aUNebYp3NLXPU89y8w0vdz4aOb7TTvUHAMJm842GZEAkCOjRFYRRvFCKEgZkuK4OqvLiwwvfka3DXkAWcgtyiqabcjjL8rmAV/CwcZH1x3DCDN2qSGvYzcI6zHHJFq9IaZU1ZWBB7KlvnRZRUtuFarkEAkCkUkrJt6i5GlY0pBHmOPDFRLyAGLRqXddiCsFvcBecWxucRxGMS5NPK6WmAa511krN2BRWkJ2QVXnETqoAwCIMyId2NFG89wDDwB/9+8CtHFSHAN//McfvKa8g+JYAL8DvW2m+RXJGgTMbc6iUcyxIsvAQrYl1wTzVAVOJqtI46PtxWMg7Csb21uNOU51g26QbCVKZBVizbHeeepZZm7lxhkMTdOAZRoLRVdXbhVAuiXJTAgkCGJt6GQsyLaG13Hd5Lg8jU7s3OCHcacNeUDCHBcb8pqVVfBYUlfQ/DewLQRRjCCVJdUtjoe9JLThclPMccVFLEG229ZQcazL2NEwTaO0yKuKMIrhBpHScy8jOKpC597JUvIkQSB0uAZQXhzvzlO3iqqyigrM8dgrSjlW+0WJGZCMh1HM1xLTyGQVPM3xgqxCX95DgjriGAiC5F86sKOt5rnvfhdgVU0fxKa8g+JYgCTat+WGvJKGOFFiW96Qlv8dq+lShVRW0QF7zkNm5SYJyrCZYrUuczz1wqT7WNKQJ3b10Pts2zKkmmPyeWRx0GVDHkAitfnMMXGrAICLGjpUVc9WEXqM1IRFxvp0eJ6AXAIE0Mxxc89MTySrIPrmgs+xmf4+akQaZhgGNlb0NeYiqNhfyVAmRdMFkcRYFcc5OkSoSZDCcWmyCg17yuOHBgBKmGM3WLAZHThWFgzEw7i2rMLG1Ne7LtMsxS//zJW+xfU5Js/DsUNyWcWJYyu4/sgAayOerMKmZBUkrru5saOt5rkPS1PeQXEsQBeFYVYcS5LXeEVXFp9MTRDTinpLR9potpyGPOLjLNIcA0UNcPUQkNyux+d0/xPIYnx1kwQT5risOM6L/5nfraxiyOn0JsUx8TkG9Jq06n6HsoS8CWdi6wK2aWQhIPNWGvL4LimEpS4m5Fnp78PGpGHrK05jzHFVP3KCpmUV5H6q6upR5rpQFbn7kEJDXolffhXI+i9YkMWyzOt46oULC9dSKzc3wKBnVr5/q1yXMRVxTbDSt7kJeRfThcDGirw4/o/uvQm/+Ke/wXX9oJsS/cytorn5tq3muQ9LU95BcSyA10HOeVl8s2j1bmea1EXNcRVmrm+LbYCWFx9tIJBojoE8RY9AJa2IBzIQzrxQ2kkv9TnW9JPtmUa2VcdKRrLX0MWxFypNkk1hhTOxZJrj1MoN0JNVqEbhisCLaqYxXlZxbBnZ1nzekNd+Ql7ekCdgjv1Qq1FUhqMrToOa43ouQG3JKqqGHVVp/FJBFuqksNDq24n3c1MOHgCRVaidk6Fj4VDflqbkjd3FnaPETSIQHvPOPKiUjkcw6hWbisuQ7z5RzLFAc3yRMMclmmMAwmTThYa8SDzX6YBuwBuPAYc5PLpZryp4TXlNvO9ew0FxLECycm5bVpE25Am2xEQDVL7FTDHHXlBpS1kWMhBEUesLBB5IYUgmLt5kSm9nh1HiVepY+t+fbFvuzH1EsXhwkrtV6E34tmWqySqCOFskdMkcJx6hTHE8zYvjoysODCNnT1RQlznO7fv414Awbctgjv2oRVmFQOtOFrS8hrzkWKLGdr/WR80yx3V8oJ2S3TZd5FZuVRlKmxuYUxfk+VOVVQDNSU2AdMGvMfbLUvLiOC5qjh0LUSw+5rEb4FBFSQVQTe7CW2Cv9PnF8Xb6XcvcKmQYUsdYR/tOwDbgbW8n/25sJA10dLNeHdDNgE2+715DtzPJPkKgOThUQRkLImIkyd/Rk+bEDbWio+n3cgXbW8vzOWas3DiLlF7KLgNUJG2NhrwrafEn8zmWWt5pnCfbMjK2SXSP9SwTfhRpaQ+bwsixCk0oV2Y+VhwrKyKOjpyMPVFBfSs3Yt8nmkyT87TauZWbmcsqWggBES3KRIU4WXDP/bCx3a+jDWuOG2GOm9IcZy4BFZnjntWKz/HMVw91ouV5dWzyaHhhrOWRLQsCcYPEKpNljgFg7vGPeTz3axXHQ0rPq4oJx1t5tW9xFz/bYw+mAawNq7PbibQkQhTJJYSq4DXg+T6wugpcvFj5bbl44IEPXjHM4oA5FkCnIaEqyjXHfK9JnqyiKnPclzDHvka4RZMghahswKD9ZQnzXtXnGKCKYxGTK5FVBJpFiGOZ2bHLZRVxVkQPuiyOBQ15R6iJYGPVydgTFdSVVfQ49zyNZWqOyTGR57hJ5njkWFnnPo2sEBfIKtwgTJnjZmQVu/NA6jGtCq+iHzlBv3HNcT3GroplmApy5lgtBAQQN3ZXQRBGXJtJEWTFMfkudNGZBagICtjdeb0o+JFjLRAsKuDtPhHmmJV/bE9cHF3pVw41IscIJL0K2X1Y43n9sDTKdYWD4lgAHc1VVeSyCjFzrCKriKK4so9s3zaFg2oYVotVrYteqicm8dBcxw4zL+obYY5ncuZYZKkFiJMMRaAHQLmsgmKOu5RV9Gx4QbTQ8Hl15uMwXRyv9DtuyFuMamaRbYl2qM0GWCu3EIYhXmBVwTWH+tiZBwXplagQX5BVRM0s8NdTG6rLDeiO68ZH91rSHFdl2KtYhqlAT1Yhl+dVgW4zp6w4JgvXEdOQB4iLYzqprgpoFyJVjHk+x30bQWqrR+PiuNzjuAxD6hjJXF5np+fD0ijXFQ6KYwG6CAFRkVVwC0NGVkECG6oMJn3bkjDHzTT06IKVVfCKjZ5lZoVSpr+sMOmSgZD4+IpDQPiuAYC+swk9AMrcKoIo0pokm0KW/EVNXFenPtZGDHOsuNUexzFmflOyir3GHC+GgAxsS9iAUwWigAU3k1WINMdJg2kTsqijqQ3V5Yl66IsIteOjW3KrsKrKKlpijknBrSSryHYLmmOOPc2d0+OHBhi7AVfnS84PGx8NQLiw2J0HlW3cADraW/3aTNwApoGFRTzZjWV1x9tjl5t6p3WM1DkIMiKo+vO6Xxrlmk7tawuNVH+GYfwjwzBiwzCOpf99xDCMf2sYxjOGYbxgGMbfb+JzukQXettcVsF/gIU+x8wWM/FnbDw+ugPdNQ89K0mjy32OeUEouUuAW4M5Jt3+tTTHmvcKXYCLJiBiZ0eYlU5lFVkwClUcM7KKY6t9XFSUVbhBhDiu9x14qYg08gm4a5/jRbeKJiUVgLg4zqzcOPHR5PdBVE/fS0BS8nTcSUTwJHaJKmjL57hq4NOIY3vYBLL7eUmyCj/Q2w2TpeSNecxxqazCr5yOR3+WzrUZu0mKH724JQU9uwDannilNm5loM8BWaTVSaTdD41ybaT2tYXaI6dhGDcB+C0AtLLlvwLwYhzHnwGwCeD3DcOot8zqGJ6mA0EVlDHHgYC57TFbzBONgbRwDJbYQH5pDXl2ErjhhxEMg2+zZFtm5hLg1WCOTdPAyLFKZRWiGF+AyCp03Cry7yNkqtOGQ8J8dCqrIGwJNbEUNMepDlVlK3fawHfgpSLSGLsBepbRWEOSKlhZRZMex4A4YMEVeCoPqIY8v6HnlxTHTTDHrr+3EvLIYquqfGzotJOQl/scq8sqmnar0JVVAPzimKflHUqY4ziOa8sqhj1+USvDxC3Gz5NjYL2Ot8ceNxJaByOK3fYbcKsA8tS8KFpMy9sraCu1rw00Uf39CwD/GAA9a8UADhnJEmwVwCUAzS+vW0QXARgqISAyWQUZDHmaLuVj6JW4MCzF5zjZqvbCGD3T5G5T90yDklXwm5NUMXKsUllFT6I5Fi1iRKDZAVEKI7HwmmpsrzaFEWdL8srMW0h5IhZGlxSkFacujgEA1x0Z1jouO3Xw4IE3sXUB28yPaR5EjRfHeTRvkTm2TKMwPmSyiiDUtuMSYX0lWRQ14XVcOz66YVlFWCG2l8aop9/4pYKZluaYMMfNFem6evXjkuKY+Aerao5nfogorp6OR3+WzsKFtZsD8oKellXM/RBjN2hAVpEX8IGkv+aDhP3UNFhrNjEM43cAnIvj+BmmgPkDAP8GwHkAhwD8x3Ecc0cPwzC+BeBbAHDttddia2urziFVxng8zj47ihPf3HNvncXW1rutfeYsSB6IF195DVve6YXfxXEMP+Qfw+mryQP/1DPPAu/YeOVS8t+vv/wCnPdf1jqGC++4mLkB97x7QYjzb7+Nra33tN5TBfT5ZvH22SS3/o3TZ2Ai4r5uvDtDFANbW1vZ93/phedgvKtfnBihj3e2/ew97PdeKrzmnbc9+EGEn/70pwvFepzeK2+fVb9Xrl6eZ///kZ8/zF2A7FydY+rHeOKZ5wAAzz/9JC69Xn3glJ1vFq9dTM7nLx59HBePWvDCGHM/wvY7b2Fr6wIA4J0LyWTx/a1HcOKI/Jx/982kqPLOvYSti3r3Jw0zjnDq9NnsGGi8ccaFFYWdjx87V+bY9WJsbW3h7XfmCNw4Owadcy5CGMUwAJx87hXcOD+V/fy1Uy5sIy68/9hLxpTnX3oVrh/g3fPnsLX1fq1jINKDJ59/BTdRx6AL4kd+vsa4emWeTCPPv/Qyjk/eWPhdlfP9zPvJffzs009hfFp/7Dj/VjJu/OAnD2Gl1xyR8PLrHiwD+MXDPyt97WuXk+f15JNPYXa2mQXizniK7fdd6fmkz/eOm9wjv3jyeQy3X1l43RPnknP0wtNP4P1XkzHs/Di5jk888xx6zHhLrvE7Z97E1tZblY6fnJNfnXwSk9Nq5+TsO3NE3uIzRd7nkZNPYpy+z8VZcnwXz53C1tbblY4PAN68krz3Y08+hVTVhycfP4l3VsXjfBNjyjJx/PgXcOHCgPPzOba2frWEIxKj9K4xDONHAK7j/Op3AfwzJJIKFr8N4GkAvwHgdgA/NAzj4TiOd9gXxnH8bQDfBoB777033tzcVD74JrG1tQXy2W4QAt//Hj56+23Y3Lyjtc/0ggj40V/ipltOYHPzo8Xfff8v8bE7isfw8rs7wC8fxsc/cTc2P/URxK+8Bzx2El+873O45+Z1rWN4bP4yfnz2TbDnPY5jhN/7Lm6/9RZsbt5Z6fvJQJ9vFi/ideD1V3D0mo9g8P673Nf94RuPYnceYHPzS7Beex947DHc9/l7cN+Jo9rHsvH0z3DuygxAgHs/dw++ePtG4TXPR68hfuNVfPkrX11gfsl1+ujttxauoQh/9tYTeOb9pDj4+tc2ucz4n545iXeuznHrHbcAzzyHr/6VL+KGterMq+x8szh89jLw+CP42N2fwuadx/Hezhz44Y/x2bvvxOYXbgEAHDpzGf/bU4/gxMeT18jwJ6dP4rZrJvjrv632+SIMfvYDXHf99djc/GThd//qrcexEU6wufnVWp+hiz898zj8KzNsbn4Zf/jGo4j7yT0J6J1zGTYe+SFWjl2Hzc1PZT/78ZXnsfL+O4X3n/sh8JPv4cZbbkX06qu47cTN2Nz8eO1jOPyz7+PI8RuwuXl35feYegHwg+/jzo/ejs2v3l7pPa5MPWDrhzhx2x3Y/Cu3Lvyuyvn2X7wAPPE47r/vXnzyhiPax3P+0bP4Vy8/h8/f/0Vcd6Q46VfF1s4LWHnnbaXvs/H2VeDRn+POuz6FzbuubeTzrV/8CDfdcBybm58WHyN1vqMoxn/z0F9i7bqbC/PFW786Azz3PL725S9lOyHnrsyAn/8Et91xJzbvu2nh9a+/Nwa2HsLnPn0XNj97Q6XjP35+B3j0YXz0E3dj85MfUfqbP3jpEaweNrG5+YXsZ9e9m7zP7Xfejc1PJ+/zzFtXgId+gS997tO1zvf1F3aBX/0Md9x5d8JwP/sMvvTFL+DmjZHwb5oaU5aF3//9RGNMSytGI+D3f3+w575XKRUVx/E34jj+JPs/AG8CuBXAM4ZhnAZwI4AnDcO4DsDfB/AXcYLXAZwCUH+E7gh+A52jKuhZBgyDL6vI4yR5mmO+rKKqW0UQxYgYF4Aw813sfpuHbJ1OvKDUzQHIG1GqNvokXrIkzln8eUBR15dZ8FTQHDsWXzJCPs+nNMfdJuSlzSzpdiiJjl5baMhLthQvlti5RVGMx89cxv0VFi0s6FREFsmW6DJkFZS8p4WGPCBpfmSjeRNnjOJnkWdg7oeNWbkBaYR0zSCQzHLxgxQCUqHxSwVTL1C25uxT3tZNQVdzbJoGjq06fM1x5iSjJqsg+t66CXmArpVbUZpF+njo/gvSmNqUW8XUC2rfh/sF+6FpkKDy3RfH8XMAMsooLZDvjeP4omEYZwF8HcDDhmFcC+BOJMX0nsPZ7Sm+9SeP469eH2Az/Vl2o7bs1GAYRuKfyymO/UDsv1l0q0g1XRUT8oBkshmY+eBFtlKX43OcHNPUC4UTKe0SQCbKqlpGekAUFdjkmPwgBqgxsYpWjLxWtviy0wZAYqfWqZUbMyGQ4ngxBCRhgMqCQF59bxdXZz7ubaA4plMRWdRt4KmKhYa8IMya15oEL5p3LohhNgwDfdvMCoymFvjrK05tn+M88nrvaI7rhoAMKxRhKtBJlGzFraJCCNY1h/p4b3de+PnEDWAYebMoUFIczwnZ04RbhUZDnhcUEjZXOZpjQgjUbcgj987cD5NKER/84hjYP+l6bVV//z2AXzcM4zkAPwbwT+I4bjjAsBkcP9zHm+9P8PKlfGAhxZZOfGZV9G2TyxzLjoE0ceVuFSQAoVpCHlAcWIOajSp1QAblSepAIHoNYW1zt4pqBSTNyoomBBFj5UsYfhHIa2X3V89KfJXnXhIsUcf+ShdsQx6xuaN9jlccC33bLPU6Pnn6MgA0wxxTqYgsJqkNU9ewTSNvyEt9jpvG8UMDXOT4HIvuiUEv3wlpaufn6MjRCn3hoQnm2LZMmEbzPsdViZAqjV8q0EmULAuTqgI/jITNwiJ85MgwlactYuKFGPWshTQ5cu/y3CrIImx9VCOauYLP8dQt7j7xGvLIc9AccxwiJPP9EqxTD8BHY7NJHMcnqP9/Hnwt8p7DoGfhMzcdwauXr2Y/y9jADljTfs/iboflARhiWUUWAqIRNcqCFH1uGALIB6Ou2HMeyOp55ocSH+BifHQTzLEsIQ8o+uxWSTayM+ZY/DfEsWPqJclyTQZLlGGkwBwbhqHkdXzy1CVce7iPm47Wc6oAkolD5AowccNKPt91YVsmwhZ9joE8fSyO4+w+kDljDHpmxr41Kat48Z1Cy4gWcua43nVyJJH3usgstCrLKvQtw1RQhTn2GpZV6C5ibjk6wsOvvb9wnwKpRIQpOk3TwKBnchcVZEzZqMHMVrkuPFmFY5voWUaWngcku2XDnlVpvqVBs+dkh/bDwBzvFxwsUwDcd+Iozuzk+k4yAXdhq5L4DHNkFZJjIKtLEq9MGNYqxaEjYI670l2Y6kyyAAAgAElEQVRzj2mBORbJKswsJKQuI0UzNELNccqisIxVlWQjsuiSHa9tGZmsoku9MZAUV4aRsy684hhIU/IkbGIcxzh5+hLuO3G0keKeDn5hsSxZRc8yMr/tNnyOgaQ49sIouw7ks2TMcdOyCqI5jmP++VdBtoitOa6KpGhVkPVW1GWOm9Yc+yGG2prj5s5JFOufk1s2Rpj7UUF3PHFD7rM57PGjt7fHHkxjscdBF5aZzIdTX+26BGEEN4i4u08rfXuROZ54tVljgFogUD7HbdYc+yWZbq/goDhGUhyHMfDUW8kWcF02QQf9nqg4Fj8srKwiYRmqFQZ9gVygicSeqiDfeeaFQukBXZTU1TLSchSZzzEgZo71QkDM9F/x/UVkI3ON7dWmYBgGRj0r8ye9MvNhGMAhJrFqY8WRpqa9fXmGd67Ocf+t9SUVQDJZBwKf46m3HJ9jy2w3BATgByy4MubYtrA7Twrppibb9RUHbhDVkg/UCeuh4dhWY4Vgcw15TcsqAuXQHDJmNXVOsjFNU1Zx09HEZeHMpcWUh6S5sPhdhj1+gMr2xMXRlf6CDKMKRg6/+OaBjHW8hM0Vx15oyLs4dmvrjQmGPSv1OSY7kO3UHPspmW6v4KA4BvC5W9YTL9FTpDiur41ThbAhLyu6ymUVkxqsWb4lx2dEl9OQl3zmxAu5spLkNSYVAlLvetELizJZRdGtQn8h1dOUVXTZjEcw6tuYpazLzszHob5duBc2VvtS5vjxM5cAAPfe0kxx3EvZdBZukDAvS2nIo6QeSZNc82PGcU4QiOuHQgnHoGdiN2W6mppsj6YBMHV0x00Vx31J5L0uPggNebZlwjKNSm4V56/M8LX/aQtvvD/OflZ1/rtlYwUAcGZ7sTieuCGXkRWlC14ce5kbTh2M0sJTBWNP7Pi0yjLHDR0fkMw9Mz/MiJ625tv9lEy3V3BQHCPZLr7xkImTp5PJvEtZRaI51pNVkIE8k1UIVuYqyGQVbHG8BxryZl6J5pi4VdQujhWYY3vRIYSgiuY4a8hTkFXMliCrAJJzMqGs3I5wmmOIrEK01f7Yqcs4NLBx53WHGjkm2+Izxxnrs4RFBHFNiaIYXhC10pDHY45lLHWfashrUnMMoJZjRbaIrc0cN6c5DrLFbb2FtU7jlwp0GvKAtLG7glvFU2ev4NTFCX7+Wt4vX3WL/4a1IUwDOLs9Wfj5xAu4/QBDx8KcK6tohpkdajDHud0cT1aRj4VAwmxvrDTDHBNZRRBGsE2jtd6S/ZRMt1dwUByn+Ni6iSfPXkYQRt3KKmyTG/spK44Nw1iwtUqakaoyx8mgVWSOl9eQR3sKy3yOiUuAGyTNI1W34UYaDXmF85QuIhyNLUhyTkWsOJB8vzCKMfWCzmUVQDLpE+/WK1MPa8MiU3LNaqKF3XX5ur6Tpy/h3lvWG2NDbJPPHGfx6UuxckuuEyn8upJVzP1IrjluuDheT4vjOl7HXlPFsWU21nzmR/W2s8nCddK4z7HejpHI9agMZy4lhewL5/OG9KrkkGObuH5tiLOXWOaY7yQjllU0o+mlx7AyjDlezAQrfTv7fRTF2B43c3zkGGepJ3mb9cbNN+v9/AAHxXGGj60nWzAvvrPTqayiL2BBvEC+eqetzKZeUJk1cwSyimU25NGfKW7IW2SO60y4RNtnmYawkBNpjqssIoiWTzb5kN/tzIKlMMcrTr4leXXmF5rxgNzKiLfVfmni4fX3xrivIb0xsCiloTGuEYJTF4n2PUq8SoFW3CoO9W0MeuaCh6wbiJnjgZ27ADQ14TbJHFe1XCRwGpRVEKeRqsWxZSa+0k0yx1GU7hhp9JH0bavSOTmbSiBeOJ87kZD3qXLv3Hx0xNEc8wv9gag4HnuNMLNDx8JEV3PMa8hzclnFztxHEMW1nDQWjrFnYeoFiXVei0TUP//nSRIdjdEo+fkB+DgojlN8bD05FY+dulR7q00Hou0wWUIesMiiTdzqDXl5M8fiIBJmGqglMMdUoStiZJMt9hhxHMMLxZ37KiBsgWwxJPI59io09JBBUF4cJ++3M/drWwZVAT2xXBEVx+kExrNzezyVKFWJ8xZB5HNM2KFlNeTFMbKwljaYY8MwMjs3gsQ2TmTlVi4T0kUjmuOwnuUiQaNWbg1oPUeOurZVBbMKwT9JY7f+MRB98GsXxllRXIccumVjlBXcBBOORRrAd6v4/9s79+g4rjrPf29Vd0uttl5tSX7IluRX7PiROInthIQkzmPz4hECC4T15AVJFgIcYNiZA+OzwOxMmB1mdjPDDGQJSSAQn/EwO8MOC2ENAQIEYuwkJCRyXk4sy5bsKHq71VI/7/5RdaurW1XV1V2vlvr3OUfHUlU/rm9XV/3qd7+/728uk0MilXUpc2xfVpGwlFWEtM+30ADEncyxorvOI5vzNnO8kDrT1QoUHKu0N0roiTfh8MC4ZTGc25id6MstbUVCJZnjKj1eRQHRvMxxvvrsgVP0J2XT/786rkyOI5VxmDlWg0+rz1vsy5gULlZyIRFzat0ERNk3NZvxJOAqRywS0uyppi00x4Bxl7zDA+OIhCScs6rVtTGZtY8WHqSl3a38QN+wBvAmcwwoEhbRJY9zjrmslZVbYbtb39+WqFKQ6SRz7K6swi3bMudaT2X53r3guOBbb/94NrMELcfgeBJNERnpXB5HR5SivEK9SeWfU088hrGZtBZscs7V1u7GmuPSzLFoKuRKQV5Eti2rmLFYfVrSULBGFOc6tzTHSgCfRTaf9zwZt2cPMDAA5PPKvxQYW0PBsY6dfXE8PTBR6E7nS+bYuAlIJbKKGQdWbmYuDIVGKP4fIvoLuplcQZxIsvk80jmnwbGaObZY7jWdpyos78Rjy2mOgcq1h24hCvI456ayClE0M2qQTTw0MIHtq9ocL6HrMWsfPWOR9fEakXEUBXBeFOQBSpe8kWnlwpzJcXBunqXWb3erZoAxhvamCMZnMuUfbELKNSs3F90qXMjYKUGee5pjke2sRE5lZglqRTqbx6mpWVyxqQsAtCYvYm6rSQ71qHZuInuczuWRzXPD65NR5tjN4DMaDtkvyLNYfRI+x5xzLXh3S3MsrNwyOe5L0zHCPhQc69i1ph1jM2m8evoMAL+CY2NZhba0ZSor0Msq5veEt/3+6gl4Xvtoh/6fTtDPu+n/XypkjtNZ8+IkO4gTt9VrmGmOxU1MJZrFiA23Cv2FKRgrNyXrIk7cRob87SZL7cl0Fv1DU9i5pt3VMelvCPVoS6IBtY/Wj8GrLH9ncyFzPKfeTJsdr/qgqpJC0XLEY2GMW/hal8OtzHG4yiypEZkcd3wD4basQjSuqCThYZZkseLkRBJ5Dlx+VieiYVkrynPi1tS7VA2O1UI/KycZo8xxoTueS5ljm77cCSuf44YQsmrRrQjeXfM5jsiYy6huFQH0FCDMoU9Dxw5VH/nb18cA+BMYmskqCppj68xxPs8dNQHRNMel/r0O/T+dYEdWIbaLzkbuZI4tglVh5ZYtXtYv9zkZEbKlOS7sC0pWkUznTLvjAcp8tUbD8xqBPDc4iWyeu6o3BopvCPUEmTkW3w8xBi98jgElOJ5MZpDK5rTiP7M2zA0eZI4B5WZoogYyx2ZFzNWQy+edZ44r8NO1QzWyimqs3ETh3JqOGDataNaK8px0a+tRg2OhZbZykomGZe1YFhQ0vc6Dz0puWmZSWUjMOFsvAvuZVBajiTQYA9oNZGbVoGWOK3CroE53/kDBsY61HTF0LIngmUGlGYhfbhWGmeOsdVFgWG0+IO68q9UcF9pHlxbkBd8hr/R3PeJEklX9ZZ18VsKD02oZsaz8pIILbMhW5riwL4jMcTSi+G8L6y6j4BgwbiF9aGAcjCnNddwkbNIhT1wAq/0OOEF8P4R1mlc3MqIRyGgirZ0vGm1ojt1c/Vq6JIJxN3yOnbaPdlFWkcm7kzl2061Ck1V4bOV2Qg2Oe+NN2LKyBS8NT4Nz7qjmpqUxjPamsGbnpn03TWQVmRwvWg0S5xI3MsfRiOLgkTMo4i0lodrNGWnPxU13Mp3D2EwK7U0R166LTWr2PGvTreLxx7uo051PUHCsgzGGHb1xR1Y2lWKWOU6XOUGFQ0oWTfhrut0+OuPQ4sgJdqzcxIkknc0jlc050raKE7dV5jhiIquoZglSvJbVkrd+DoLwORZzcmpKsQ8zKsgDgI5YQ5FbxdDkLP758Als625FS6M72RWBvvGLnkQqi7DMXNU320V8TpqswqMx6L2OxfK5Vfvo0vG5gZI5dlaQF5Elx40OXC3Iy3HH57hK/HTtYBVQmlGNldvxsSQawxI6mxuwZWUrzqSyODE+q2sfXV140BNv0oJj7fpkUpAHoCh7PJZIIRqWXXHoKbT2Lv/ZmDlqAIUivUQqq9rMuaM3BoDGiAzOFfmJnXjjwQfXUqc7n6DguAS9L6tfBXm5PJ9XaFTOTkfIKpIWWik7mDa3cLC05hT9Xblp++hQSebYwVKtWEqzymiJ9zPzg67kRkr8/+xmjoPwORYXrtNTswDMM8cdzRGtSGXkzBz2fPMgEqksvnzTNtfHZKY5trqweY2wOkx47VahC47nMtbyhKKCPBe/v/FYBBPJNPI2MnFGOK0NEOidepyScUNW4XLmWARzFWWOq7ByOz6WRE+8CYwxbF7RAgA4cmpKO6dVm+HvWRrTZBVJzUlm/vdTHKd63fHYTBodzW7ZpNnvXmjmqAEUMseKrCLlWjEeUPDYn57L2PqujowYy02o0537UHBcws6+wlKwH04N4mJRuiRWLiMpZBVOM8eSpHTbm98+urat3MRSqNAcO7noShJDNCxba47NmoBoHbaqsHKzGxwHkTlWLxTDInNsJquINWAskcLETBq3PHgII2dS+PYdO7G12z0LN0FIMvY5Tph04PKDeZljDwvyAOUGpGzmuEhW4W7mOM+h6dArJZXNOS7GA1xuApJ3I3Nsv/DLDrM+WbkNjs+gJx4DAGxc3gxZYugfLjTBqvbc3xtvwtDkbMn1ySBzLIJjXfA6mnCvNXNMyxyX/2wSFjfY4lyoZY5dKsYDCtftM3NZW24VXV3GBbFudrojTbMCBcclbF7Ron2pwi5WeptRvkOdSXAsZBUWd+Z2MVqSy9aKrMLkYqr5DuecZ44B5eRtFawqXqhAumRZv5osi7jpsrr4hAJ2q4iGleNpeFLJHLc1GWdLli6JYCKZwa0PH8KxsRl889YduKDX3UI8QUiWDGUVSubY/zkCClZuXgfHokBJnzm2Y+XmtuYYQNW6Yze+p4C7TUAUKzdnY4q67VZRTUFehVZunHMMjic1d4nGsIz1nUuKguNqj52eeBNyeY5Tk3OFYlkjzXHEIHOcSLvWYKOpguDYrMU1oM8c5zCaSKHDZVkFoHjJ27kZufPONzztdLdvH0jTrELBcQkhWdIKidys9DZD6CTNM8fm7YyzZe7M7WKUianGv9ctZDUQBWxkjvPO3SoARRNnlX1mjBku61eTZRGfqWVHviJZhf9ZURFsnpqcgywx0/bkIovy0qlp3L/nfFyyvsOzMYlWzaUoS6LBZI7FcSgK8rySwIRlCfFYRA2Ora3cvCrIE9Z9RrrjpwfGtRsEM5yu8AgistIMplp5h55MLu88cxwO2S78soMIFisryJPnFVVbIW6yRHAMAJtXtuDI8HTBcq9qWYXqWDE+o3XZNNQcG2SOx2bcyxxrsgobHtSWmWP1dSZn05iey7qbOdbJKux8V6++esTTTnd794I0zSoUHBtw9dnL0NXc4FuHPMAoc2zduSkkSUjnuE5z7CRzPF+vpmWuA8gci0AUMNcch7TMsdIExGkx1pqOJVgdb7J8jFEhUDV+0HY0x6GAZRViuW94ahat0bDpcbiuM4aQxHDfB7fjqrOXeTqmkCSBc8wLQhKprKOVEyeIc4Rm5eZC8GdG55IGjJxJaTfSdgry3JRFxdWM2VhJcPzm9Bze/42n8M1fvWH5fDczx8D8IuJqyFVgoWWGuJF0qygvmc5CllhFwWmlbhXCxk1/ztuysgWnp+cworYpr/bGqldn55asIHPMOVdlCwFkjtPmvQLEuUUUGbqpORZzkKmgMNTLTndm2uV61DQHc0WpcW59Wy/+04U9jquq7VDQHM8PTq1OTpEQK6vpsoth5jgXXOYYUILyNMr7HCvto81b6drlW7fvRLlPOywzg8xx5Z0Ew7Y0xwE3AVHf883pOaxuN79puHhdB17882t98WLW3xDJUuH9ZlJZLGtu9Pz9jdA65KWyiIQkSB7eTHa1NBRljs2K//Q+x27WTbTHjDPHhwfGwTnwu2Njls934yYWKHbYcXrcuWHlpgV56RyaXXBoSaZzaArLFV1/GkIysnmOXJ5rx6QVomCuN16cOQaA505MAqher76suRGRkITB8aT2+RitqIht4niens0im+euZWbF69sJjpMp89UnsV10/XOrAQhQnPiohSYgPT2KlMJoe70R/KdRg+gzl15jVpCXzuYtT05CVmF1Z26XiDxfwycKn+ycaL1AaI3LNwHhjttHA8r/s1xgY1Qln83nbT1XT1jLHJf3VQaCcasQx1Mmx9FiUown8KtJiZiv0qK8mVTOcNnWD8RnmZjLmvoOu0XnkgabmmNvCvLiTcaa48PHxgEAvx+ctCyUc7MgD5i/2lYNubwLsooKMpR2mE3nKl4tEs1n7M7J4HgSEgNW6W58hWOFCI6rDdYkiWF1exSDauY4FpENz4+FmwplzG9p3efczRzbcauwklVEQhLCMtNuKNwaH1B8bvdjpbocN9wAlN6TualpXkhQcBwwEZPgOJu3DvhCkqT6HJtruuzSEJ7fiEQEIEF9YbUA0mQOtCxiPu+aRZSdMaWz8wvyKr24appjq883YFmF/j3bXOoG5RS9Q4meIGUV4uZxJp31/Cahs1kJjmfLao4L43Dz5jYakRENyxif1/RlQlvWf2FoyvT5Tpv1CMzsJ6shk3MuqxA1AW4Fx0rH08qOJa3TqU07t8GxGaxojRadg9qaIuhui+ItVVbh5LPqXRrD8fEkZtI5w+54gE5zrB7PojWzW5pjIQ0r97kIxyOrBFOsIVSQVbg0PmWM3nSzrIZ9+4BHHlEK8QSMAbfd5q50Y6FAwXHAFArySmQVWevlvkiIIZ3LI5l23gDBMHMsZBUBfWEjZTTHYrk4lckhz/3pZmg0T5lcvuJVBnvto3VNQILIHOtutsxs3PxG71CiJ5kOzudYs3Kb8yc4TufyWvBSzq3CjYYbpcRjxV3ypmYzePn0ND6wYzUARWJhRjqbd6W9tllCoRwj03P4t2dPguuu/tkqvr+laBlKG4Vfdkimc1oxmV3EvNqdk+PjisdxKVtUaQXgLDHSE2/C4NiM6gJhfZzOqtJAoWV3S9Mb1TL61p/LjI1eAbFISCs49UJzDARjm6rHqBiPc+Cxx4IZT9BQcBwwVgV5VlZymltFKue4m1DEoIV1kB3ygMKJwiw4F/sT6onNjYtuOcKyhIyB5V2lF5GulgZsXNaMTcubTR8TtKxCX9RVK8GxyKbrW0gnUllkcjywMYZ0TUC8agAiEF7HJyaUK5hp5jhU3iqwWtpj4SLN8bPHJ8A5cP3W5VjbEcPTJsFxNpfH4HjSFb3mmg7Fm/fLj71UUTOQv/3JK/jj7z2Pv/jhS1qAbFeja4XrsopMtuLMsZZkydiUVYwli5wqBEJ3zJizVYfepU2YSecwOJ40vT6VFuRpmWOfZRUJNXi2Wn0S+yIhydVVqqhH9QHVQMV4xVBwHDCmmuMyGQ1NVmFxZ25/DDJSBlpaicHTAiMryskqSl0CfMkcG2iOM7l8xdq8pkgIBz5zGc7raTd9jHjNxrC3RV5mSBLTLi5ttRIcq/Og9zoWPswr26KBjEkEEKms8+Kwcojg+OR4EpGQeVZYjMOLG9t4rAHjyUITkMMD4whJDNt72rCzL47DAxOGFmuHByYwkczgqk1djsdwXk87/tuNW/DTI2/is9973paFWjaXx+MvjaA1GsbDvzmG+376KgAhi3KnIE9kIJ1SjazCrLDbiEQqi7GZtGa5pmfLSqV5T9jhqoPISr9y+oxpRrZg5aacU0cTaTBW0LY7JSwrWuFyDVpE3Y6Z/EPZp4y1IxZxdTVGHxwHnTk2K7qrx2I8gILjwGk0WQ7L5Kz1eWFNVmGu6bKLsc+xc3N8J5QrWhMXNOHWEXGhCr78mJiBrIJ7Yncn/t9BZI0FIuNTriDPL8Qxof8MhiaU4Lg7oOBYfwPb6PEx2KVljmcti/80WYUHOvx4UxjjM4UuXYcHxrGluxVNkRB29LVjajaD10YS8553oP80GkISLt/Y6co4bn1bH/70uo34wfPD2Pv9F4qkEkY8fXwC4zNpfPmmbfjAjlX46s+P4hu/fN2lDnn2/XTtMJvOVfy9N0uyGDGoOVXE5u0Tsgqn5zSRlZ7NmK9syhJDJCQVMsczKbQ3RVy97kTDshb8miHkEmZWbso+5f/gpscxoCRBItq1zvr/vW8fcPPNF3nWue7ee1G2wcg99wChkLKyEAopf4uxLbauemTlFjARWflCGnWos7Ry0zUBcZ45nu9znPUo6LOL0Bqb3SCIjLIf/rLaexr5HOfzptltp+8FVN8W3A1E9qpWZBV6hxLB0GSwwbF+6dlraU+nalc3PpPWAmWzMYVl5km9QHssgokZJXM8l8nh+RNTuO3iXgDArjVKZ8RDA+PYqJMMcc7xk/7TuHRDp6vH8z2712MmlcXXfvE6Yg0hvD1mHiAf6D+NSEjC7o2duG7rciTTOfzVj19GWGbYsGyJo3G4LauoKnMcNm4mZcTg+AwAGGqOV7Q2ulKAq3fBsJIhRMOyZuU2lkhjqYvd5wDl/Fnuc9E0x1YFeRERHLs7PkBZeUjPWrumiM51yaRyDhCd6wD3iuXE6+zdq0gpenqUwFhsv+ce4P77C4/P5ZS/X30VeOqpgl7Zi7EFAWWOA6ZQSFH8BU7n8tbthSUJea70ZHdDc2zkc1wbmWOT4Fi4BKgnNi+yZKUYWrlV4VZhh7BOVhEUmqzCpWVOp+h9jgXDk7MISUyTHPiNfmXDa1lFS2NIO87LBeKNIdmyZqFa4k0RJFJZpLI5/OHkFNK5PHb2KUFxT7wJXc0N83THLwxNYXhqDtducb9JzH+5ZiNuv7gPDz15DD98I2P4GCU4fxOXbehArCEEWTSt2dRVldtMKdEKLMPsUE1BXiVuFcKSzEhWwRjDlpUtjosUG8MylrcogZxVoB8Ny9q8udkARNAUkcvKKkTm2KqoV+xz0+NYIFYJrK63fnWus2ow8sADxs/52c8WZ1c9Co4DxsyWqJwLgrjwTSbTjiv1GwyC40y+8kIzNxGBkGn7aHV7UpNV+ONWUeqUUE4bXi2yxCAxyhzrMfI5HpqcxYq2xsD8uPXv63VwzBhDp3pxLifhaAjLnhT4xNXgZTKZ0ZwpdqjBMWMMO9fENd9jwYH+05Alhqs96KDIGMMX3rkZN2xbjn9/PYORM3PzHtM/PI2hyVlcs2W5ti0sS/janvNx03nduHSDM6lHUwXNJsoxm85hfCZV8c1eJW4Vg+NJtDWFTb/XH9ixGu/ZvrKi9zdCBN9W16doRNZkFaMzKddlC8tbG3F8bMbyMTMpOwV5ymfsReZYnGetrre1UCyXq/DwXuiFfBQcB4zZSS2T45aaY7FvajZjaUFjawwhed7753LOq7idoLWPNsl+heTizLFfsor5mWPrDL/T9wtScywuarUSHBv5HA9PzmJlazCSCqBUc+z9MdjVogbHZY6LxrDkyXEpiqXGEmkcHhjH+q4lWltpANjZ247hqTmcnCikkg70v4ldfXGtw57bSBLDn1y7Cbk88PCTA/P2H+g/DYlhXnDeGJZx3we3430XrHL0/kI36kZw/PLpaeR5saWaHTTNsQ23isHxZFFnvFJu3N6Nve/YXNH7GyHewypz3BiWtXkbS6TR4fIxsqO3HUeGp3FmznhVASgkWKx6BYi6ng4XPY4FYuXBSgZVC8VycoWXooVeyEfBccBoy2GlTThy1h3yxFLgZDLjiawik88HakperkghrLPQAvzJHIdDxp0EveqmGJalQBqACAqyihoJjg18jocmZtHdHlxwHPIxcwxAyxyXuxlsDMueHJciwB1NpPDMwIQmqRDsVHXHIqv8+lsJHB1JeCKp0LOmI4ady2U8evA4pmaLA6ED/aexa028KIh3m2hE1vx6nXDk1DSAaoJjY798I46PJdGzdH4xntv02skchyXMZXJIZ/OYms24njneuSaOPAeeHZw0fYywA7Vj5eaJ5liTVZhf7+0Uy5XiVpGceB2zzPFVV1U+toUABccBE5IlyBJDOleqObZ2ixBFYNk8d1yQZ9wEJFhZRVnNsTo2cdfvT+aYzbuJSGfznvlThmVWcWGOm4ibrlrJHGsFearPcTaXx+npucCK8YDibI8f+nCx3G4vc+yBrEINMJ96YwxnUlnsWlNsR7hpeQuaG0I4PDABQAlMARRJGrziHWvDSKSy+O5TA9q2Y6MzePXNBK71+P2bIrIrmeP+4Wm0RsMVH9N23SoyuTyGJmfRE/f+O7PaRuZYyCrGXW4AIji/px2yxOZJffTMpLKQmLUzkLjGuh28A4XMsdX1ds8eRfO7bNkcGAN6e5W/zQreRAHf8eNKIw9RJFdpgKx/HSOuugp4/HFlLL29sDW2hQIFxzVAg2ETjjJWbrp9Tq3cGkIScnlelHXI5gMuyAtZB8dC8qE1AfHByi0iK1mOog5beeftZ80IWlbRFJERCUm+ZETtUOpz/OaZFPI8OI9joDjb48c8damOFeUC8caQ7InbjAiORdBbmjmWJYYL+tq1YORA/5s4Z1WrL59Rb4uM3Rs78fBvBrQiL7+C86iNwi879A9PY/OKloq9dIU8b13kG90AABdHSURBVDSRsnzcqck55PLc0MbNbXrV7LSVC4QoyBt1uXW0INYQwpaVLZadGxOpLGKRkOWci+y3224aQCEol8skWfbsAfbvP2hYLFeKWwV8Rq+j5+jRwtjMCvkWKhQc1wARg+X6TBlZhX6f08zx1lWK8fv/ff6Uts0rFwa7iAu72Q0CY4pdlZ8FeVu7WzGaSOPgG4UTrRvtZ8345JXr8X61LW8QvPf8bvzJNRsDe/9SxDwL3XfQHseAvwV5QCFzXO5m8I5L1uCOS9a4/v6iIcwbb81gZWtjkWWXYGdfHK+NJPDSqWk8f2LS86ytno9fsR7jM2nsP6xUAx3oP41t3a2eHyNNEdmxW0U2l8fLp6YrllQAihb2vJ42/N3jr+E3R0dNH3dc2LgZOFW4zZaVLfjwJWtw2VnmBY/RSAhzmZzWOrrDA9nCzr44njsxaSo5eeb4BNZ1Wdv5XX5WJ+64pK/IotAt7BTkVYpbBXzlHr/Qi+6soOC4BjDMHGfLuFW4mDnefVYnNi1vxv1PHNW6W3mZEbVDoUOetZ2dnz7H//GCVehY0oCvP3FU25b2UH5yy9v68LZ1Sz15bTtc0BvHXZetDez9SwmVuFUE3R0PKP4e+nEMasFxmczxO85ZgXecs8L19w/Jkiaz2VGSNRaIbPKXH3sJADzXG5e+966+OB741Rs4OZHE7wcnfXn/pnBIu1GvlmOjM0hl81oL50qQJIZv3b4TaztiuPORp03beAsbN6PW0W4TliV84V2bsby10fQx0bDSBES0jvbCKm1nXztS2TxeHJqat29ochYvDE2VvYHramnEF9+1xZNEiJ2CvEpxq4Cv3OMXetGdFRQc1wCKW0TxXW0mzy2bS+i/pFadfezAGMM9V6zH62/N4CdHlGXITC7YgjwRFFu20JaZrwV5jWEZH3n7Gvz6tVG8cFI50WYDnqd6QsyzljkOuAEIoGSOxWqsP7IKe5pjLxHSClF8V8o5q1oRkSX8+rVRrOuMYX2X+9k2Kz52xTqcmprDp/Y/BwC4bqv3meuoC5nj/mFRjNda1fPbmiL47kcuxPLWRtzxrcOGweCg2np8WbN5wOon0bCsBsfeaI6Bwk3coWMT8/YdeFG53vl5A1dKNKwkt9xIRoniOSONsN0iOX0hXyIBREw+Er8KAoOCruo1gKmswkLWoM9WuuGF+45tK9C3tAlf+8Xr4JzXTEGelbQjLEuYUzPuVvpsN/mji3rQ3BjSssdBZ9jrCc3nWNUcD03OIh6LBOroARSOUT9lFV63qrZCBMe7TDLHjWEZ565WAjw/JRWC3Wd1YvOKFjxzfAJrfQrO3SjIO3JqGpGQhHWd1euBO5sb8OidF6IlGsYtD/0Or715pmj/4FgSq9ujkAKUzOlpVG8qRmdSiIQkS8eIaulY0oC1nTHDbPqB/tPY0LUEazuddUl0gluyCqviOcaA224rrwUuLeQbG1P+XaouYAo7N78KAoOEguMaoCEkYXq2eEmuElmFVcGDXWSJ4aOXr8MLQ1N48ugocvlgfY4bQkoxmFWRhP5k0uBTJq25MYzbL+7D/+s/jaMjibKFk4R7hErcKoYnZ7GyLfgMmMho++FW0bGkAYwB0Uhwx1w8FkFrNIwNFjpNIa0IIjhWVsLW+fr+dtoUl6N/eAqbljc7LoTuboti350XIiRLuOGrv8a2Lx7Qfn5y5LRWKFcLRMOKx/5b0yl0xCIVFyLaZVdfHE8fn9BkgwAwlkjh8MC4LysLVrglq7AqnuMceOyx6l4jkwGWLFFeI5tV/vWrIDBIgmu/RWhcvG4pHnryGAbHklqhRCZnX1ZhZV5eCTed3437Hn8VX/vFUWTyeSwJB3d4fGjXamztttbe6U8mfgaot1/ch2/++g38r1++rshPKHPsC2IlRfgcD03MYq2DLJtbaJljPxxTQhL+7oPbcd7q9vIP9ohPXrkeo4mUZfbxtov7sKK1Eeesqk4i4JTrt67Af31nCu8+13mnNzs06Tq9VQPnHP3D07jepUCtryOGf777Iuw/fEJbaRG881z3tejVIpwaTk7OemKTJtjZF8f+wyfw6sgZbFquXFd+9tII8jyYGzg9Yg6cZo7dKJ7zupBvIRXwUXBcA9x56Vo88tvj+MavXse9N20D57xsW+Jitwp3PsaGkIy7Ll2Lv/zRS4hFZOwy0RT6Qe/SWNkMh34O/JSALF3SgA/t6sF3nzoOWWKBWt7VE1rmOJcH5xzDk7N4+4aOgEdV0Ar6pQO+cXu3L+9jxjmr2so+ZllLI255W5/3gzFBlhg+8nb33TrMUGQV1RfknZqaw2Qyg80rKi/GM2Nt5xL82Q1nu/Z6XiCypkMTs9iwzDtpg1jJOHxsXAuOD/SfRndbtCp3EDdxK3Pc02PuRyz2V/sa1RTyufE6QUJX9RpgWUsj3nfBKvzL0ycxMq34UAJAxNLKTZc5dlFz+aFdPWhrCmMmnav5oE+Mr6GM/MIL7rp0LRhTTPdJVuEP+g5507NZzKRzgRbjCcRx6IesgqhNohEZc5l80bJ9JYhivM1VFuMtVETW9NTUrOsex3pWx6NY1tKAQ2pzmkQqi18fHcU1W5b5fu0oRVy/rVYgRXHblVdeXlTc5kbx3L59QEeHokt2Usinx25Hv1ou2qOzeY3w0cvXIpvP46Enj2nLxpYd8orcKtxbAIg1hHDHxUrGJUifYzuI8fnhVFHKyrYobjqvu2gchLeIm5BMPo+Tk4qgrSaCYx8L8ojaRAQ41Uor+oenwBhw9gp/nT2CRmRN89wbj2MBYww7++I4fGwcnHP88pW3kM7mA5dUAIXzhtlKcXFxG9OK2+65x3nx3L59wB13KM81otpud6Kjn1XXvFov2qPguEboXRrDO89ZiUcPHsdbZxTPR7uyCrc0x4LbLu5FLCIH7gJQjrCWOQ5mnB+9fB0YczdzT5ij75A3PDkHIFiPY0FBVkGn03qluVHxfn76+Hy7MDscGZ7Gmo6YK85DCwl9B1AvbNz07FoTx+npOZycmMWB/tOIxyLzOjwGgWisY3YdMStue+AB58Vze/cqzzGit9dZt7tyXfNqvWiPzuY1xMd2r8NMOoeHnnwDgD1ZRUhiri/rtzVF8E93X4TPXH2Wq6/rNuIGwY/mC0as7VyC/XddhFsv7gvk/esNWQuO81oDkO72GgiOpWBv0ojguWHrCpy1bAk+9ugzeKaKALl/eLpqf+OFTFFw7KGsAijojn/7+ih+8fIIrj67K1BHJsHOvjgeum0Htq821vKbFbHlTBYpKil6s3qs18VztV60R8FxDXH2ihZcfXYX/unwCQDlMsfKvqaI7Ilm6pxVbVgd976LkhOE7CQIWYXgwrVLPenqRMxHtAzP5DmGJmfREJKwNOZttskOJKsgWpvCePQjF6KruQG3f+sQ+ofnN+AwYzKZxtDkbOCFYUHQqMuWdjR7ex49a1mz6lH/Os6ksjUhqQCU7oZXnW2ufTYrYpNNTjeVFL1ZPdbr4jm3uvh5BQXHNcbHdq9HOqv4uJbrDgcoGuF6JejMMeE/IUlCNpfH0OQsutuigRfTAFSQRyh0tTTi0TsvRHNDCLc+dAhHRxK2nnfklFqM56JTxUKhOHPs7Y2uLDHs6G3H8bEkYhEZl6wP3unGDvfeC4TD87c3Ns4vwGtqAm64wbjIrbT47eqrzbO0kUjlRXiVYrdoLyjobF5jXNDbjovWKss/VtWrEV3muF4Ry9lBZo4JfwnJDJkcx9DEbE3ojQHKHBMFVrU3Yd9dF4Exhj0PHsSTr43i2cEJ7efI8DQ4L3a0OKK1ja7v4NiPFTjR8nz3xq4F9X01ygHMzBQK8ETR2223AY88Mr/IrbR47/hx4Gc/U34vZelS4OGHq9ca28VO0V6Q1G/asYb5xBUbcPCN36GtyfxOWmSVvWi3uVAQmWOyUqsfwrKEbF7RHO/e2Bn0cAAoAbssMcuVHqJ+WNMRw6N37sLNDxzEHz30u3n791zYg798z1Zt1ePI8DSWtzR62gSjVtEnd+I+SKQuWdcB4BXcsK12GqGUY+9eIJ023icK8EZHlb/7+syL98w0ynpkufBafrBnT+0Ew6XUb2RVw7x9Qwce/+PLsKbD3BRdZJXrrbpZj1YIRcvZdUNIYkimcxg5k0J3W21o4kMSQyOtXhA6Ni1vwYFPX4aXVMmE4IlX3sK3fzuAJQ0hfO76TWCMoX94GpvrMGsMFDTHLY0hX1YAz13dhgOfvgxnedhwxG0q6XxXafFetY+rB+iMXqOs72q2rKQNq4FhzGUbt4WEaK9NmeP6ISxLODmuOFWsbGsMeDQKIUlaUEu0hD8sa2nE7o1dRT9ffNdm3HJRL77xqzfwDz8/irlMDkffStSlpAIoyCr8LGreuLy5JmoV7FKuQE2/v9LivVLMpsWqWUctN/JwQv2mHRc4ksQQklhdZ47DkijIo8CkXgjJDANjMwBqw8YNUMZEwTFhB8YY/vzdW5BM5/A/f/oqjo8lkcvzuizGA5Sb3ZDEPPc4Xsjce6+iFy6VSwDzC9iMHtvUVNAiG72GHllWglujZh3iuULHLDDbV6tyCbtQym0BE5JZXWeOhbSECvLqh5DEMKI2yamF7niAMiaS9hB2kSSGv37fNly/dTn+9dmTAFCXHseCaFj23ON4IaMvXAO4Zec7syK3r399/vZGg4W3bHZ+Ew6rZh213sjDCfWbdlwEdLdF0bs0FvQwAqMWfI4Jf9EXvS1vrQ1ZRXd7FAZF3wRhSkiW8Pc3n4fUo8+gf3gKq+O1caMXBKvjTQtKAxwEonDtiSd+id27d9t6bLntkslls1S3XE2zjlpp5OEECo4XMI996lKtKK0eKcgq6ncO6g2xWtDV3FAzcpovvWsL8hQdExUSCUl48NYdSGZyC0oD6zbf//jFdX0dC4qeHkUGYbS9ksfZeY2FCB2RC5iGkFwT7S+DgjLH9Ye4iNaKxzGgHId0DBLVIEmsru04AbqO+YFR0ZzdJhxWj6v1Rh5OoDM6sWAJU3Bcdwhv61opxiMIgqhlREFdaWMQwF4TDqtmHbXeyMMJ9X3LSixoCu2ja2N5nfAecUNUK8V4BEEQtYxV0dzAgL1A1qpZRy038nACpdyIBYvWBIQyx3WDkNKsrJFiPIIgiFqmmoI6wmFwzBj7EmNsiDH2nPpzg27f5xljRxljrzDGrnU+VIIoJiRTQV69IYowu9trozseQRBELWNWHLcYiua8xI2o4j7O+Xb15zEAYIxtBnAzgC0ArgPwdcYYrX0TrhImn+O6Q9wQ1Up3PIIgiFpmMRfNeYlXUcWNAPZzzlOc82MAjgLY5dF7EXWKVpBH7aPrBiGrWNVGmWOCIIhyLOaiOS9hnFdv0MkY+xKA2wFMA3gawGc55xOMsX8EcJBz/qj6uIcA/Jhz/r8NXuNuAHcDwLJlyy7Yv39/1eNxQiKRwJIlZETuF27M988HM/jOkTTuPqcBF6+k2lIrFsvx/Y3n5/D7kRzuv7qp5r1hF8ucLxRovv2F5tt/aM7d54orrniGc76jdHvZiIIx9jiA5Qa79gK4H8BfAODqv/8DwIcrGRjn/AEADwDAjh07eLnuL17xxBNPlO08Q7iHG/N9+tAgcOQFnLt1C3afs8KdgS1SFsvxPd5yEpuGpnDFFVuCHkpZFsucLxRovv2F5tt/aM79o2xwzDm/2s4LMca+CeCH6p9DAFbrdq9StxGEa1ATkPrjveevwnvPXxX0MAiCIIhFjFO3Cn267iYAL6q//wDAzYyxBsbYGgAbABxy8l4EUUqY3CoIgiAIgnAZp0LNrzDGtkORVQwA+M8AwDnvZ4x9D8ARAFkAH+ec5xy+F0EUIXyOKXNMEARBEIRbOAqOOee3WOy7FwCZhRCeQVZuBEEQBEG4DUUVxIJlZ18cH9rVg80rWoIeCkEQBEEQiwTyvyIWLO2xCP7qvduCHgZBEARBEIsIyhwTBEEQBEEQhAoFxwRBEARBEAShQsExQRAEQRAEQahQcEwQBEEQBEEQKhQcEwRBEARBEIQKBccEQRAEQRAEoULBMUEQBEEQBEGoUHBMEARBEARBECoUHBMEQRAEQRCECgXHBEEQBEEQBKFCwTFBEARBEARBqFBwTBAEQRAEQRAqFBwTBEEQBEEQhArjnAc9Bg3G2FsAjgf09h0ARgN673qE5ttfaL79h+bcX2i+/YXm239ozt2nl3PeWbqxpoLjIGGMPc053xH0OOoFmm9/ofn2H5pzf6H59heab/+hOfcPklUQBEEQBEEQhAoFxwRBEARBEAShQsFxgQeCHkCdQfPtLzTf/kNz7i803/5C8+0/NOc+QZpjgiAIgiAIglChzDFBEARBEARBqNRdcMwYez9jrJ8xlmeM7dBt/w+MsWcYYy+o/16p23eBuv0oY+yrjDEWzOgXHmbzre77vDqnrzDGrtVtv07ddpQx9jn/R714YIxtZ4wdZIw9xxh7mjG2S93O1GP5KGPsD4yx84Me62KBMfZJxtjL6nH/Fd12w+OdcAfG2GcZY5wx1qH+Tce4BzDG/kY9vv/AGPs+Y6xNt4+OcQ+ga6L/1F1wDOBFAO8F8KuS7aMA3sU53wbgNgDf1e27H8BdADaoP9f5MM7FguF8M8Y2A7gZwBYo8/l1xpjMGJMBfA3A9QA2A/iQ+liiOr4C4M8559sBfEH9G1DmVxzPd0M5xgmHMMauAHAjgHM551sA/K263fB4D2ygiwzG2GoA1wAY1G2mY9wbfgpgK+f8HACvAvg8QMe4V9A1MRjqLjjmnL/EOX/FYPvvOefD6p/9AKKMsQbG2AoALZzzg1wRaH8HwHt8HPKCxmy+oQQQ+znnKc75MQBHAexSf45yzt/gnKcB7FcfS1QHB9Ci/t4KQBzjNwL4Dlc4CKBNPdYJZ3wMwH/nnKcAgHM+om43O94Jd7gPwJ9COd4FdIx7AOf8J5zzrPrnQQCr1N/pGPcGuiYGQN0FxzZ5H4Bn1QtcN4CTun0n1W2EM7oBnND9LebVbDtRHZ8G8DeMsRNQspifV7fTPHvDWQAuZYz9jjH2S8bYTnU7zbdHMMZuBDDEOX++ZBfNufd8GMCP1d9pvr2B5jUAQkEPwAsYY48DWG6way/n/N/LPHcLgL+GskRH2MDJfBPOsZp/AFcB+Azn/F8ZYx8A8BCAq/0c32KjzHyHAMQBXARgJ4DvMcbW+ji8RUmZOf8z0PnaVeyc0xljewFkAezzc2wE4QeLMjjmnFd18WeMrQLwfQC3cs5fVzcPobBsBPX3IWcjXFxUOd9DAFbr/tbPq9l2wgCr+WeMfQfAp9Q//wXAg+rvVvNPWFBmvj8G4N9UCdYhxlgeQAdovh1hNueMsW0A1gB4Xq2TXgXgWbXwlOa8Ssqd0xljtwN4J4CreMEPlubbG2heA4BkFSpqxe2PAHyOc/4bsZ1zfgrANGPsItWl4lYAlA11zg8A3KzqutdAKZo5BOAwgA2MsTWMsQiUAo8fBDjOhc4wgMvV368E8Jr6+w8A3KpW9F8EYEo91gln/B8AVwAAY+wsABEoxb5mxzvhAM75C5zzLs55H+e8D8qS8/mc89OgY9wTGGPXQdF3v5tzntTtomPcG+iaGACLMnNsBWPsJgD/AKATwI8YY89xzq8F8AkA6wF8gTH2BfXh16gFNfcA+DaAKBR91Y/nvTBhiNl8c877GWPfA3AEytLcxznnOfU5nwBwAIAM4GHOeX9Aw18M3AXg7xljIQBzUKr2AeAxADdAKZpJArgjmOEtOh4G8DBj7EUAaQC3qZk10+Od8Aw6xr3hHwE0APipmq0/yDn/qNU5nageznmWron+Qx3yCIIgCIIgCEKFZBUEQRAEQRAEoULBMUEQBEEQBEGoUHBMEARBEARBECoUHBMEQRAEQRCECgXHBEEQBEEQBKFCwTFBEARBEARBqFBwTBAEQRAEQRAqFBwTBEEQBEEQhMr/BwsYjifzWJsaAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "pJ7kryvdrqcg"
-      },
-      "source": [
-        "We are building a single step LSTM model for training data with dropout 0.3 and we used ADAM optimizers."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "snN_Flr5DWQN",
-        "outputId": "449c5036-923b-4a60-8e6d-dad286ef1c59"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:]))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 14s 226ms/step - loss: 0.2044 - rmse: 0.2723 - val_loss: 0.0922 - val_rmse: 0.1511\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 11s 215ms/step - loss: 0.0574 - rmse: 0.1058 - val_loss: 0.0394 - val_rmse: 0.0519\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 11s 216ms/step - loss: 0.0240 - rmse: 0.0351 - val_loss: 0.0156 - val_rmse: 0.0187\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 11s 214ms/step - loss: 0.0182 - rmse: 0.0226 - val_loss: 0.0054 - val_rmse: 0.0068\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 11s 212ms/step - loss: 0.0164 - rmse: 0.0199 - val_loss: 0.0096 - val_rmse: 0.0110\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 11s 219ms/step - loss: 0.0148 - rmse: 0.0179 - val_loss: 0.0129 - val_rmse: 0.0157\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 11s 217ms/step - loss: 0.0137 - rmse: 0.0163 - val_loss: 0.0071 - val_rmse: 0.0084\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 11s 216ms/step - loss: 0.0138 - rmse: 0.0162 - val_loss: 0.0090 - val_rmse: 0.0100\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 11s 216ms/step - loss: 0.0131 - rmse: 0.0152 - val_loss: 0.0081 - val_rmse: 0.0092\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 11s 218ms/step - loss: 0.0126 - rmse: 0.0144 - val_loss: 0.0081 - val_rmse: 0.0090\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 11s 214ms/step - loss: 0.0121 - rmse: 0.0137 - val_loss: 0.0082 - val_rmse: 0.0090\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 11s 215ms/step - loss: 0.0191 - rmse: 0.0297 - val_loss: 0.0055 - val_rmse: 0.0068\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 11s 218ms/step - loss: 0.0112 - rmse: 0.0133 - val_loss: 0.0067 - val_rmse: 0.0080\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 11s 214ms/step - loss: 0.0104 - rmse: 0.0124 - val_loss: 0.0039 - val_rmse: 0.0048\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 11s 216ms/step - loss: 0.0105 - rmse: 0.0127 - val_loss: 0.0049 - val_rmse: 0.0058\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 11s 215ms/step - loss: 0.0102 - rmse: 0.0122 - val_loss: 0.0029 - val_rmse: 0.0035\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 11s 216ms/step - loss: 0.0098 - rmse: 0.0117 - val_loss: 0.0043 - val_rmse: 0.0052\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 11s 217ms/step - loss: 0.0088 - rmse: 0.0108 - val_loss: 0.0076 - val_rmse: 0.0094\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 11s 219ms/step - loss: 0.0090 - rmse: 0.0108 - val_loss: 0.0141 - val_rmse: 0.0143\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 11s 215ms/step - loss: 0.0092 - rmse: 0.0109 - val_loss: 0.0135 - val_rmse: 0.0139\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Ay5m27doDsTt",
-        "outputId": "803927cb-1be0-4f8b-e31e-2dcb68a7e217"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "6ZFP49W4D2wp",
-        "outputId": "b810ee24-c241-45ce-e60c-c002d81270d0"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8639928a-99de-4dbd-9394-34b651da23ac"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 36s 51ms/step - loss: 0.0147 - rmse: 0.0161\n",
-            "MAE: 0.016090337187051773\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "oLqijoE9W-Gm",
-        "outputId": "ccb080da-2676-4cf8-d3a3-968bc5cb6c94"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "174/174 [==============================] - 9s 51ms/step - loss: 0.0142 - rmse: 0.0151\n",
-            "MAE: 0.016090337187051773\n"
-          ]
-        }
-      ]
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "OwlM7YM2htFR"
+   },
+   "source": [
+    "We are importing the libraries:\n",
+    "- TensorFlow: to process and train the model\n",
+    "- Matplotlib: to plot the training anf loss curves\n",
+    "- Pandas: used for data analysis and it allows us to import data from various formats\n",
+    "- Numpy: For array computing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qlVZPlu-iiYw"
+   },
+   "source": [
+    "We are reading the CSV file using `read_csv` function and storing it in a DataFrame named `df_Ellis`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "06698528-eedb-475b-fa32-e347d03e9980"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/Failure/lstm/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "t5gl1fqmjBdt"
+   },
+   "source": [
+    "`plot()` function is used to draw points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "547a5311-6db3-42b6-d5bd-3bc171446eac"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "KYRyARNcjJkz"
+   },
+   "source": [
+    "Using multivariate features:\n",
+    "- Storing only the multivariate features in a dataframe named `features_3`\n",
+    "- Extracting the Timestamp column from `df_Ellis` dataframe\n",
+    "- and combining it with the dataframe `features`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "8bb3a951-1f2d-4f40-aa40-668e00bdc238"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.system_perc', 'ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-mem.free_mb', 'ellis-net.in_bytes_sec', 'ellis-net.out_packets_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "jO-JgNPQj99-"
+   },
+   "source": [
+    "Plotted features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 437
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "3a6ee243-5136-4614-93e6-8c2f7f4c13af"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "9337b00a-1d3f-4dbc-91d5-2f445eda21e5"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "vOzDoRCrlTBc"
+   },
+   "source": [
+    "We spliited the multivariate data in tarining and validation and printed the shape of that data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "73165ad2-6043-42c9-ed7d-ff050af74e34"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "YU_j8yNblhOO"
+   },
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "QialFchyl9Rt"
+   },
+   "source": [
+    "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
+    "- Creating a source dataset from our input data.\n",
+    "- Applied dataset transformations to preprocess the data.\n",
+    "- Iterate over the dataset and process the elements.\n",
+    "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
+    "Once we have a dataset, we can apply transformations to prepare the data for our model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "08bfc16c-0e6b-43d8-8fa3-97b84c124bfb"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "F-ntkTP2njMy"
+   },
+   "source": [
+    "We used a custom loss function to evaluate the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kTwy7LdqoGpM"
+   },
+   "source": [
+    "We are building a single step LSTM model for training data with dropout 0.3 and we used ADAM optimizers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "f6ec7f52-8cf8-4e81-82c8-8ca59e89f429"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "from keras.utils.vis_utils import plot_model\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "single_step_model.summary()\n",
+    "plot_model(single_step_model, to_file='/content/drive/MyDrive/Failure/lstm/LSTM.png', show_shapes=True, show_layer_names=True)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ch-I96MromT8"
+   },
+   "source": [
+    "We defined the `plot_loss` function to plot the train and test loss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "c8794bd3-d704-4244-8f32-7be7d73f0890"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "06250b6b-9899-4eb1-af6c-14afd3ae70f8"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tBNraVXSqqfH"
+   },
+   "source": [
+    "We defined a function `create_time_steps` to create time steps and function `plot_time_series` to plot the time series data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kX1mtI44q4U7"
+   },
+   "source": [
+    "We plotted the time series and predicted values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "37fe707b-40d1-476b-c668-631789537c57"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "5ghCNUvcrBMi"
+   },
+   "source": [
+    "We splitted the data in the form of training and validation for multistep forcasting:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "4aeabbf6-4ca3-4340-d1b1-e94ad1f78faf"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Rv5mugNBrVdY"
+   },
+   "source": [
+    "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
+    "- Creating a source dataset from our input data.\n",
+    "- Applied dataset transformations to preprocess the data.\n",
+    "- Iterate over the dataset and process the elements.\n",
+    "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
+    "Once we have a dataset, we can apply transformations to prepare the data for our model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "13cf8949-9ebc-4ea9-b5ac-f33c6e146a00"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "gMIQq83Ercb2"
+   },
+   "source": [
+    "We created a `multi_step_plot` function to plot between `history` and `true_future` data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "eadda952-c8bc-4b54-e55f-0500d73115c1"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "pJ7kryvdrqcg"
+   },
+   "source": [
+    "We are building a single step LSTM model for training data with dropout 0.3 and we used ADAM optimizers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "449c5036-923b-4a60-8e6d-dad286ef1c59"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:]))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "803927cb-1be0-4f8b-e31e-2dcb68a7e217"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "b810ee24-c241-45ce-e60c-c002d81270d0"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "8639928a-99de-4dbd-9394-34b651da23ac"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "oLqijoE9W-Gm",
+    "outputId": "ccb080da-2676-4cf8-d3a3-968bc5cb6c94"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "LSTM.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/LSTM_Attention.ipynb b/models/failure_prediction/jnotebooks/LSTM_Attention.ipynb

index 9959bd7..ea2d34f 100644 (file)
--- a/models/failure_prediction/jnotebooks/LSTM_Attention.ipynb
+++ b/models/failure_prediction/jnotebooks/LSTM_Attention.ipynb
@@ -1,1658 +1,885 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "oQvr9zfcPRi-"
+   },
+   "source": [
+    "Contributors: Rohit Singh Rathaur, Girish L.\n",
+    "\n",
+    "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
+    "\n",
+    "http://www.apache.org/licenses/LICENSE-2.0\n",
+    "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "LSTM_Attention.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    },
-    "accelerator": "GPU"
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "cb071d50-8fcb-426d-8fa9-6f7033f783d1"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/content/drive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "oQvr9zfcPRi-"
-      },
-      "source": [
-        "Contributors: Rohit Singh Rathaur, Girish L.\n",
-        "\n",
-        "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
-        "\n",
-        "http://www.apache.org/licenses/LICENSE-2.0\n",
-        "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "cb071d50-8fcb-426d-8fa9-6f7033f783d1"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /content/drive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 521
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "120b11e9-5c7d-4332-d133-9636a8d002aa"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 4
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "92xBt43BnjAo",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "outputId": "2104e011-6066-4e86-e6f8-515dfb9ea715"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd54812ab50>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 5
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "RSo-aa-SIoBR",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "outputId": "ea97c36d-cb27-4fb3-d9bd-e8f1776b098d"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "gggaMJ_2LtFs",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "outputId": "9e21fcc0-a838-4449-ef31-8e7d1df4d060"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "R_ctvXcQL1Xf",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "outputId": "1a35f11e-eb94-4404-bd86-6f6fc2765ba2"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Gkd5ecCmL6Bw",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "outputId": "2396e496-512e-45de-b804-acfb32e79b41"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "EycZrQU0MBSX",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "outputId": "dcf3d389-1ac0-4005-ae48-53e0f96548b1"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YoQA_MIBMknS"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Pi8UMMitMa3Q",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "outputId": "57b8d44c-ad3d-45e0-82da-1787d6d47d55"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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py+jI+Px93dnV69etGyZUsOHTpE9+7dCQ8PJzw8HFdXV5o2bcrChQut65w7l9kHMyMjwzp+IyIiwpoBqFixIjExmXeXWbNmzU33m5SURJEiRQgMDKR///4cOHAAyBy8Xq5cOWbOnEmHDh2AzHEfFouF1q1bM3z4cGvZYsWKcenSJSCz8ZKcnMzevXuBzK5MsbGx/6IGby4xMdG6zZUrV9KwYcO73leVKlU4deoU0dHRAFy8eDHfDBovqGbO+hLPRj54NvJhxYq19OzeEYCnnmzA+XPnOXEi6w0LihUrah2PYG9vj59vSw4d+gOA8BVrefbZpkBmlyonJ6d82dCA+1tvrX2e5ZVXBtMuqA9Xrly17YEY4PD+WNyqlKeseznsHR1oYm7G7vU7spSp/EQVBkwdwrv9p3D+zN995Eu5lcaxUObFlWIPFeMxzxocP5xIQZC4/wilqrjh7F4Wk6M9Nc2N+X191uy7S+W/72RYzaseKXGZjV5n97LWAeEPVSxD6aoVOJtQMO4U9Nf+w5St7EapSmWxd7Sngbkpv6zP2sWn0hOV6TplAJ8NeJuLZ/6+E1xK4mk8nqqJyd6EycGeqk/VIOmPBFsfguF+3/87FapUxNXdFQdHB5qbm7N9/fYsZR594lGGTh3K5P4hnDtT8Ma12Jwlw7YvA9gks+Hh4cHw4cPp168fGRkZODo6EhwcfMf1IiMjCQ8Px8HBgTJlyvDCCy9kKzN48GBCQkJo27YtJpPJOri6aNGiREdHM3PmTEqVKsUHH3wAQL9+/Rg+fDhLliyhRYsW1u0kJSUxYcIEPvvsM37//XfefvttTCYTDg4OTJo0yVrObDaTnJxM1apVATh58iRjx4613i505MiRALRv356JEydSuHBhFi9ezIwZMwgNDeXChQukp6fTu3dvqlWrluM6hcwGw8KFCxk3bhweHh48//zzODk53dW+nJycmD59OqGhoVy9epXChQszb968B64r1asTp7FzbzRnz56nZbseDOnfkw7m1kaHZbjVkRtp08aLQwd/5vKVKwwYMNK6bNfOdXg28qFYsaIsD5tHoUJOmEwmNm3ayuw5XwEwb/4i5n72Hvv2buT69VT69R9u1KHY1L3W24cfhFKoUCHWRC4CYPv2Pbw4dIwhx2ILGekZzA/+jLELJmKyt2fTkg0kxMbTceTzHI3+g90bdtJtXB8KFy3My5++BsCZxFO8O2AKFT0q0WNCXywWC3Z2dqycE078oT8NPiLbsKRnsDZ4Ps8vGI3J3sT+JZs5HXuM5iM7cDz6KLEb9uDZ24cqzWqRkZrOlfOXWDEysyuju+djNB1iJiM1HYslgzUT5nEl5cG7uUdOZKRnsDT4C4YsGIfJ3sS2JZs4EZuA34hO/PXLEWI27CZwbA+ciham76cjAEg5dprP/vMO+1Zvo3rTWoxZ+y5YLBzcvI+YjXvusMf8JyM9g1mvzyTkq8mY7E2sX7yev37/i+4jexD7Syw71m+n3/j+FC5amDEzxwJwKvEUk/uHGBy5PMjsLJb8eS+LG8/tuN9CQkKoUaMGnTp1uu/b/jcSEhIYNGgQK1dmH5iaW1JPH7HZvvKLIhWeMToEKUA6lW9050KSRS2KGR3CAynJTpnwnDiSUTAahvfbyr9WGR1Crrm6Z4VN91e4QYBN9wd58DkbeVlQUBCHDh0iMDDQ6FBERERERPK8B6vPzL+QG1mNsDDb31kmJSWFPn36ZJs/f/58m2Y1REREROQ+KwBPEM+3jY38wsXFhfDwcKPDEBERERH519SNSkREREREcoUyGyIiIiIiRsgw5kF7tqTMhoiIiIiI5AplNkREREREjFAABogrsyEiIiIiIrlCmQ0RERERESNkKLMhIiIiIiKSI8psiIiIiIgYQWM2REREREREckaZDRERERERI2jMhoiIiIiISM4osyEiIiIiYgRlNkRERERERHJGmQ0REREREQNYLOlGh5DrlNkQEREREZFcocyGiIiIiIgRNGZDREREREQkZ9TYEBERERGRXKFuVCIiIiIiRrCoG5WIiIiIiEiOKLMhIiIiImIEDRAXERERERHJGWU2RERERESMoDEbIiIiIiIiOaPMhoiIiIiIETRmQ0REREREJGeU2RARERERMYLGbIiIiIiIiOSMMhsiIiIiIkbQmA0REREREZGcUWZD7lqRCs8YHcID50rij0aH8EBKO7DF6BAeSCVajTc6hAfOt0YHIAXKqxVaGB2C5DXKbIiIiIiIiOSMMhsiIiIiIkbQ3ahERERERERyRo0NERERERHJFepGJSIiIiJiBA0QFxERERERyRllNkREREREjKAB4iIiIiIiIjmjzIaIiIiIiBE0ZkNERERERCRnlNkQERERETGCxmyIiIiIiIjkjDIbIiIiIiJG0JgNERERERGRnFFmQ0RERETECMpsiIiIiIiI5IwyGyIiIiIiRrBYjI4g1ymzISIiIiIiuUKZDRERERERI2jMhoiIiIiISM6osSEiIiIiIrlC3ahERERERIygblQiIiIiIiI5o8yGiIiIiIgRLMpsiIiIiIiI5IgyGyIiIiIiRtCYDRERERERkZxRZkNERERExAgWi9ER5DplNkREREREhC1bttC6dWu8vb2ZM2dOtuWJiYn07NmTdu3aYTab2bx58x23qcyGiIiIiIgR8tCYjfT0dEJCQpg3bx6urq507NgRLy8vPDw8rGVmzpyJr68v3bp1448//mDgwIF8//33t92uMhsiIiIiIgVcdHQ0jzzyCO7u7jg5OeHv78/GjRuzlLGzs+PixYsAXLhwgXLlyt1xu8psiIiIiIgYwcaZjcWLF7N48WLrdJcuXejSpQsASUlJuLm5WZe5uroSHR2dZf2hQ4fSv39//vvf/3LlyhXmzZt3x32qsSEiIiIiUgD8s3GRE6tWraJ9+/b069ePvXv38tprr7Fy5UpMplt3llI3KhERERERI1gybPu6DVdXV06cOGGdTkpKwtXVNUuZpUuX4uvrC0D9+vW5du0aKSkpt92uGhsiIiIiIgVc7dq1iYuLIz4+nuvXr7Nq1Sq8vLyylClfvjxRUVEAHD58mGvXrlGqVKnbbveBbWx4eXmRnJwMZLasILMFNmzYMCPDuifjx4/njz/+AGDWrFkGR5O3TH8/hN8O/MSe3eupX6/WTcusivgvu3etZ/++7/nk42lZUnovDulLzC+b2b/ve6ZNHW+rsPOkCVPep7l/V9r1GGR0KHnOzzGHCZwwG/O4mXwRGZVt+fEz5xjw7kK6hHxBp0lz+fGXzPM1NS2d4Hkr6ThpLp3f+Jydh/60deiGupfzs06dmvy0ZQV792zgu+XzKVGiuC1DN9Sd6q148WLs2rnO+jqR+AvvvfsGAO+9M8k6/8CvP3L65AFbh2+Yu/m8TQ4ZzdHDOzmb/HuW+QP/05O9ezawa+c6Nv+wnBo1qtkiZENVb1GHkRvf5ZVN79NisDnb8ie7t+TlNdN4afUUXvh2IuU8KgJQtGRxBnwznkm/fkHAG31sHHXBYcmw2PR1Ow4ODgQHBzNgwAD8/Pzw9fWlWrVqfPjhh9aB4mPGjGHJkiUEBAQwcuRIpk2bhp2d3e23e99qKw9wdXVlxowZRoeRY2+++ab1/ezZsxk0KPd+DKalpeHg8GD8+X3beFHNowqP12zGU0824JOPp9K0WfZ/mF27DeLChcw7JCxZPIeOHduyZMkKnm3RlABzaxo09Ob69euULVva1oeQp7Tz86ZbhwDGTX7X6FDylPSMDKZ+vY5ZI7ri6vIQ3d+cT4u61ahaoYy1zGertuLjWYPOzzbgcOJphs5YQuQ0D5b9uA+ApZMGkHz+Ei9+uISF4/tgMt3+H3B+cK/n5+xZ7zB69GS2/LiNPr278MqowUyc9I6tD8Pm7qbeLl68hGcjH+v09m2RfPfdagBGvTrJOv/FIX2pd4sf3fnN3X7eVq5czyefzuO3Az9lmf/NouXM+ewrANq29ebdtyfib+5hk9iNYGeyIyCkL5/3mMr5E2d4cUUoB9fv4eQfx6xl9odvZcfCzB+SNVo1wP/1Hszr/Rap11JZ/95SXB+rhFt1d6MOQWysRYsWtGjRIsu8l19+2frew8ODRYsW/attPhCZjfDwcDp27EhgYCDBwcGkp6fftFxCQgJt27YFIDY21rqO2WwmLi4uW/lLly4xduxYzGYzZrOZtWvXApmZkilTpuDv70/v3r2tGZSePXvyyy+/AJCcnJwttQQwd+5cFixYAMCUKVPo1asXAFFRUYwaNQqAiRMnEhQUhL+/f5bG0Y3tv/vuu1y9epXAwEDrOjc71jZt2jBq1Ch8fX0ZNmwYV65cASAmJoYePXoQFBRE//79OXnypHX7b775JkFBQSxYsIDo6Gi6du1KQEAAHTt2tN7KLK8xm1vz1cKlAGzfsQfnks64uWW/1dqNHzIODg44OTlZH8r5wgu9ePudT7h+/ToAp06dsU3geZRnvdo4P1TC6DDynJijibiXdaFSWRccHexp3agGm/ZlvSpqZweXrlwD4OKVq5QtmXkV/kjiaZ58/BEASj1UjBJFC/Hrn8dtewAGudfzs3q1R9ny4zYANmz8kfbt/WwTuMHutt5uqFbtUcqVLcOPP23Ptqxrl3YsXvxdrsWal9xtvW3fsYcTJ05mm3/jcwhQrFhRLPn86c3u9Tw482cSKfEnSU9NZ39EFDV8GmYpc+3iFet7p6KFrHWSeuUaf+46RNq1VJvGXOBkZNj2ZYA839g4fPgwkZGRfPPNN4SHh2MymYiIiLjjeosWLaJXr16Eh4ezbNmyLLfyuuHTTz+lePHiREREEBERQePGjQG4fPkytWrVYtWqVTRq1IiPP/74ruP19PRk165dQOaP/suXL5Oamsru3btp1KgRACNGjCAsLIwVK1awc+dOfvvttyzbeOWVVyhcuDDh4eG89957t9zX0aNH6datG5GRkRQrVoyvv/6a1NRUQkNDmTFjBmFhYXTo0IHp06db10lNTSUsLIwePXowYsQIxo0bx4oVK5g/fz6FCxe+6+O0pYoV3EiIT7ROH0s4TsUK2f+eAKtXLuT4sf1cuHCRZctWAplf0s2aPcnWnyL4fsNSPBvWtUnc8mA5efYibqUesk67upTg5NkLWcoMMj/Dqu2/4vPqxwyd8S1jnvcGoLp7OTbt/4O09AyOnTrLgT9PkJR83qbxG+Vez88DB34nIKA1AB07tMW9UoXcDzoP+Df1BtClcwDffrsi2/yHH65I5crufP/Dz7kSZ17zb+vtZgYP6s2hgz8zbcoEho8Mvt8h5ikPubpwLvHvC2znjyfj7Jq9f33jnt68snk6bcZ0I2LSAluGKAVAnm9sREVFERMTY81SREVFER8ff8f16tWrx+zZs5kzZw6JiYk3/SEdFRVF9+7drdPOzs4AmEwm/Pwyr64FBgaye/fuu473iSee4Ndff+XixYs4OTlRr149YmJi2LVrF56engBERkbSvn172rVrR2xsLIcPH77r7f9T+fLladgw8wpFQEAAu3fv5ujRo/z+++/07duXwMBAZs6cSVJSknWdG8d19OhRypYtS506dQAoXrz4A9Ot6nb82nan0sMNKFTICa/nngbAwcEeF5eSNG1mZvSYUL75WuNhJGfW7DhAQNParHtnKB8P68SEzyPIyLDQ7um6uLqUoFvoPN5ZvIG6VSve9jaABdXNzs8BA0cy+IXebN8WSYkSxbh+XVdRb6Zz50AW3SR70aVzIMvCVpGRh55CnNfNnPUlj9V4mrHj32Tc2JfvvEIBsO2r9bzbYgRrpn2D10vtjA5H8pk8/+vSYrHQvn37bN2Jli9fftv1zGYzdevWZdOmTQwcOJA33niDI0eOsGTJEgDmzJlz1zHcGPhib29vTS/e6JLz/zk6OlKpUiXCwsKoX78+jz32GNu3b+evv/6iatWqxMfH88UXX7B06VKcnZ0ZM2YM165du+tYbhbXP6ctFgvVqlXL8sCWfypSpEiO9mVrgwf1pn//zIbgrl37qOT+99XOipXKcyzxxK1W5dq1a6yIWIfZ3JoNG3/kWMJxvvsuEoCdu/aRkZFBmTKlOH06OXcPQh4o5UoW58Q/shFJKRcoVzJrd7PlP+3n0+GZ9yevW7US13ix5k4AACAASURBVFLTOXvxMqUeKsarXVpZy/WatoBHbnL1ML+4n+fnoUOH8fXvBmRmIf18W+Zu8AbKab3VqVMTBwcH9uz9Jduyzp0DGTYsf9/04l4+b7ezeHE4n3w09b7EmFedT0rBucLf4xQfKl+Kc0m3/u6LjoiiXWg/W4QmN9zhdrT5QZ6/9NakSRPWrl3LmTOZacCzZ89y7NixO6wF8fHxuLu706tXL1q2bMmhQ4fo3r074eHhhIeH4+rqStOmTVm4cKF1nXPnzgGQkZFhHb8RERFhzR5UrFiRmJgYANasWXPLfXt6evLFF1/QqFEjPD09WbRoETVq1MDOzo5Lly5RpEgRSpQowenTp9myZctNt+Hg4EBq6u2v8CUmJrJ3714AVq5cScOGDalSpQrJycnW+ampqcTGxmZbt0qVKpw6dcr6ZMiLFy+SlpZ22/3Z0sxZX+LZyAfPRj6sWLGWnt07AvDUkw04f+58tr64xYoVtfbbtbe3x8+3JYcOZd4pKHzFWp59timQ+WPGyclJDQ3J5onKFfjrZArHTp0lNS2dtTsP0qJu1jvVlC/9ENsPxgFw5Phprqem4VKiKFeupXLlWuYFiKgDR3EwmbIMLM9v7uf5eeOGDXZ2dowb+zKz53xlwyOxrX9bbzd07RJ40zEZjz1WFZeSzkRt25WrcRstp/V2Mx4eVazv/f1aEfvH0fseb16SsP8wZSq74VKpLPaO9tQ1N+Hg+qy9NUpX/rsb2mNe9Tkdl7PGm8it5PnMhoeHB8OHD6dfv35kZGTg6OhIcPCd+1hGRkYSHh6Og4MDZcqU4YUXXshWZvDgwYSEhNC2bVtMJhNDhw7Fx8eHokWLEh0dzcyZMylVqhQffPABAP369WP48OEsWbIky0j9pKQkJkyYwGeffQZkNjZmzZpFvXr1KFq0KIUKFbJ2oXr88cepWbMmvr6+uLm50aBBg5vG37lzZwICAqhZs+Ytx21UqVKFhQsXMm7cODw8PHj++edxcnJixowZhIaGcuHCBdLT0+nduzfVqmX90eTk5MT06dMJDQ3l6tWrFC5cmHnz5uXJrlSrIzfSpo0Xhw7+zOUrVxgwYKR12a6d6/Bs5EOxYkVZHjaPQoWcMJlMbNq01fqjZd78Rcz97D327d3I9eup9Os/3KhDyRNenTiNnXujOXv2PC3b9WBI/550MLc2OizDOdibGNPNm8EfLCLDYiHw6Tp4VCzLp+FbqPlIeZ6tV42RnVoSsmA1CzfsBOCNvv7Y2dmRfOESQz5YjMnOjnIuJQjtn/3uOPnVvZ6fXbu0Y/DgPgB8991q5n9586xsfnM39XZDxw5mzIE9s22jS+dAlnwbbpN484q7rbdpU8fTtUt7ihYtQtyRXXwx72tCJr/PkMF9aNnyGVJT0zibci7ffx9kpGewIng+/RaMwc7exK4lmzgZe4xWIzpy7JcjHNywhya9ffB4uhbpaWlcOXeJb0fNtK7/2k8fUqh4EewdHajp05Avek7LcicruQ/ucDva/MDOkt9vxZAD9evXt2YG8qqEhAQGDRrEypUrbbZPB6eKNttXfnEl8UejQ3ggpR24ecZPbq9Eq/zdnUbkQfdqhRZ3LiTZTI372ugQcs3lT4badH9FX7z7mx7dL3nvMraIiIiISEFQAG7uoMbGTeSlrEZKSgp9+vTJNn/+/Pk2zWqIiIiIiPxbamzkcS4uLoSHF6w+uSIiIiIFQgHIbOT5u1GJiIiIiMiDSZkNEREREREjFID7NCmzISIiIiIiuUKZDRERERERI2jMhoiIiIiISM4osyEiIiIiYoQC8ARxZTZERERERCRXKLMhIiIiImIEi8ZsiIiIiIiI5IgaGyIiIiIikivUjUpERERExAgaIC4iIiIiIpIzymyIiIiIiBjAoof6iYiIiIiI5IwyGyIiIiIiRtCYDRERERERkZxRZkNERERExAh6qJ+IiIiIiEjOKLMhIiIiImIEjdkQERERERHJGWU2RERERESMoOdsiIiIiIiI5IwyGyIiIiIiRtCYDRERERERkZxRZkNERERExAh6zoaIiIiIiEjOqLEhIiIiIiK5Qt2oRERERESMoAHiIiIiIiIiOaPMhoiIiIiIASwF4KF+amyI5KK0A1uMDuGB5FCzudEhiIjcd5dINzoEEZtTY0NERERExAgasyEiIiIiIpIzymyIiIiIiBhBmQ0REREREZGcUWZDRERERMQIlvx/NyplNkREREREJFcosyEiIiIiYgSN2RAREREREckZZTZERERERAxgUWZDREREREQkZ5TZEBERERExgjIbIiIiIiIiOaPGhoiIiIiI5Ap1oxIRERERMUKGHuonIiIiIiKSI8psiIiIiIgYQQPERUREREREckaZDRERERERIyizISIiIiIikjPKbIiIiIiIGMBiUWZDREREREQkR5TZEBERERExgsZsiIiIiIiI5IwyGyIiIiIiRlBmQ0REREREJGeU2RARERERMYBFmQ0REREREZGcUWZDRERERMQIymyIiIiIiIjkjBobIiIiIiKSK9SNSkRERETECBlGB5D7lNkQEREREZFcocyGiIiIiIgBdOtbERERERGRHFJjQx4I098P4bcDP7Fn93rq16t10zKrIv7L7l3r2b/vez75eBomU+bH+62pE4j5ZTN7dq9n6bdzcXZ+yJahG+LnmMMETpiNedxMvoiMyrb8+JlzDHh3IV1CvqDTpLn8+MsfAKSmpRM8byUdJ82l8xufs/PQn7YOPc+aMOV9mvt3pV2PQUaHkifdyzl6w4jhL5B2/RilS7vYImTD3U2dOTo6MvPTtzjw64/E/LKZ9u39AHB3r8CGdd+yc8da9uxej28bL1uGbqi7qbfJIaM5engnZ5N/zzJ/+MsDid7/A3t2r2fdmsU8/HBFW4RsqBot6jJ+43Re3/QhrQYHZlv+XH9/xq1/j9GRb/Piwgm4VCxjXRYwpjtj173LuA3v02FiHxtGXYBkWGz7MkCebGx4eXmRnJwMQP369QFISkpi2LBhd72NsLAwQkJC7ns8tnL48GG6dOlCrVq1+Pzzz+/LNjdu3MicOXPuy7ZsybeNF9U8qvB4zWYMHjyaTz6eetNyXbsNoqGnN3XreVG2bCk6dmwLwIaNW6hbz4sGDb2JjT3CmNFDbRm+zaVnZDD163V88nJnwkIGsmbHAQ4nns5S5rNVW/HxrMHi4H5MG9iOKQvXAbDsx30ALJ00gFkjuvL+ku/JKAAp3rvRzs+bWe+HGh1GnnSv5yhApUoV8G7VnD//TLBV2Ia62zobN3YYp06doeYTz1C7zrNs2RL1v/kv8+3SCBo92ZruPYbw0YwptgzfMHdbbytXrqfJ0/7Z5u/bF8NTjX1p0NCbZWGrmDZ1Qm6HbCg7kx2dQvoxq89UpniPpGHA07h5ZG1gJRyI4x3zWN7yfY39kdsJHNsdgCoNqvOo52NMa/MqU31G8XDdqng0rmnEYcgDLk82Nm7G1dWVGTNmGB2GzZQsWZLx48fTv3//+7bNli1bMnDgwPu2PVsxm1vz1cKlAGzfsQfnks64uZXLVu7ChYsAODg44OTkhOV/v5HXb9hCeno6ANu276FixfK2CdwgMUcTcS/rQqWyLjg62NO6UQ027ct6dc/ODi5duQbAxStXKVuyOABHEk/z5OOPAFDqoWKUKFqIX/88btsDyKM869XG+aESRoeRJ93rOQrw3ruTGDPuTSyWgtG4vds669O7K9Pe+ggAi8XCmTMp/3sPDz2Ued46P/QQx48n2ShyY91tvW3fsYcTJ05mm79p81auXLn6vzK7qZTPvw8eqefBqT+TOBN/kvTUdPZEbKW2T6MsZWKjfiX16nUA4vbGUtKtNAAWLDgWcsTB0QEHJ0fsHey5cOqczY8h38uw8csAhjc2wsPD6dixI4GBgQQHB1t/FP5/CQkJtG2beRUsNjbWuo7ZbCYuLu62+0hISKBXr16YzWZ69+5NYmIiAN9//z2dOnWiXbt29OnTh9OnM6/+pqSk0K9fP/z9/Rk/fvwtv/w+/vhjOnToQNu2bXn99dexWCwcPnyYjh07Ztm32WwGYPPmzbRp04agoCBCQ0N54YUXbhlz6dKlqVOnDg4Odx7Dn5CQQJs2bRgzZgytW7dm1KhRbN26la5du+Lj40N0dDSQNdszZswYQkND6dq1Ky1btmTNmjV33I9RKlZwIyE+0Tp9LOE4FSu43bTs6pULOX5sPxcuXGTZspXZlvft05U1a3/ItVjzgpNnL+JW6u+uYq4uJTh59kKWMoPMz7Bq+6/4vPoxQ2d8y5jnvQGo7l6OTfv/IC09g2OnznLgzxMkJZ+3afzy4LnXc9Rs9uHYseNERx+wSbx5wd3U2Y0unyGTXmPH9jUs+mY25cpldnEJmfwe3boFEXdkFxErFvDy8Px9hf6Gf/NZu5O+fZ7P998HJV1LcTbxjHX67PEzOLveupti487PcWBTZoY7bk8sv0f9yuSdswndMZuDW/aTdPhYrscs+Y+hjY3Dhw8TGRnJN998Q3h4OCaTiYiIiDuut2jRInr16kV4eDjLli3Dze32/2hCQ0Np3749ERERmM1mQkMzu0I0bNiQJUuW8N133+Hv78/cuXMB+OSTT2jQoAGrVq3C29vb2jj5/3r06MGyZctYuXIlV69e5YcffqBq1aqkpqYSHx8PwOrVq/H19eXatWsEBwfz2WefERYWdt+7Zf3111/07duXyMhIjh49SkREBN988w2vvfYas2bNuuk6J0+e5Ouvv2b27Nm899579zUeo/i17U6lhxtQqJATXs89nWXZ2DHDSEtL4+uvwwyKLu9Ys+MAAU1rs+6doXw8rBMTPo8gI8NCu6fr4upSgm6h83hn8QbqVq2YrV+9yL34/+dokSKFGTv6JSa98a7RoeU5Dg72uLtXYOu2XTz5VBu2bdvN228FA9C1SzsWLPiWyo96Yg7oxfz5M7CzszM44gdHt25BeDasy7vvzTQ6lDzDs10zHq5Tle/nrACgzCOuuHlUJLjxYF5vPIjqTWvxaKPHDY4y/7FkWGz6MoKhvyKioqKIiYmxZimioqKsP9Jvp169esyePZs5c+aQmJhI4cKFb1t+79691qxIYGAgu3fvBuDEiRP0798fs9nM3LlziY2NBWDnzp0EBmYOonr22Wdxdna+6Xa3b99Op06dMJvNbNu2jT/+yBxk6+vrS2RkJACRkZH4+flx5MgR3N3dcXd3B8DfP3tf0ntRqVIlHnvsMUwmEx4eHjRp0gQ7Ozsee+wxjh27+ZWIVq1aWcvfyOrkFYMH9WbXznXs2rmO4yeSqORewbqsYqXyHEs8cct1r127xoqIdZjNra3zevXsjL9fK3r2yt/jNQDKlSzOiX9kI5JSLlCuZNbuP8t/2o+PZw0A6latxLXUdM5evIyDvYlXu7RiycT+fDC0IxeuXOMR11I2jV8eDPfrHK1atTKVKz/Mnl3r+eP3bVSqVJ6d29fi6lrWFodhU/+2zs6cSeHSpcssX74agKXLVlK/fuaA6L59u/Lt0syLc9u276ZwoUKUKZM/z9V7+azdTEuvZxg7Zhjtgvpw/fr1+x1unnI2KZmSFUpbp0uWL825pJRs5ao/XRufoUHMGfA2adfTAKjT+kni9sZy/fI1rl++xsFN+6jSoLrNYpf8w9DGhsVioX379oSHhxMeHs7atWt56aWX7rie2Wxm5syZFC5cmIEDBxIVFcXChQsJDAwkMDCQpKS767saGhpK9+7diYiIICQk5F/907l27RpvvPEGM2bMICIigs6dO3PtWmYfeD8/P2uGwc7OjsqVK9/1dnPKycnJ+t5kMlmn7ezsbtk17Z/r5DUzZ32JZyMfPBv5sGLFWnp2z+ya9tSTDTh/7ny2vrjFihW19tu1t7fHz7clhw5lNv5a+zzLK68Mpl1QH2tf3fzsicoV+OtkCsdOnSU1LZ21Ow/Som61LGXKl36I7QfjADhy/DTXU9NwKVGUK9dSuXIt8zyIOnAUB5OJqhXK/P9diNy3czQm5jcqVKqLR/XGeFRvTELCcRo91ZqkpFM2P6bc9m/rDGDlqvU826IpAF7PNePgwcyLYvF/HcPruWYAPP64B4ULF+LUqTPZ1s8PclJvt1Kv3hN8+sk02gf1zbf19U9/7T9M2cpulKpUFntHexqYm/LL+l1ZylR6ojJdpwzgswFvc/HM3xeqUhJP4/FUTUz2JkwO9lR9qgZJfxSMGzjYVAEYs2HoQ/2aNGnCkCFD6NOnD6VLl+bs2bNcunTpjuvFx8fj7u5Or169OH78OIcOHaJPnz507979puXr16/PqlWraNeuHREREXh6egJw4cIFXF1dAfjuu++s5Rs1akRERARDhgxh8+bNnDuXfUDUjYaFi4sLly5dYu3atbRunXkl/eGHH8ZkMvHpp5/i6+sLQJUqVYiPjychIYFKlSqxevXqf1FTBdvqyI20aePFoYM/c/nKFQYMGGldtmvnOjwb+VCsWFGWh82jUCEnTCYTmzZtZfacrwD48INQChUqxJrIRQBs376HF4eOMeRYbMHB3sSYbt4M/mARGRYLgU/XwaNiWT4N30LNR8rzbL1qjOzUkpAFq1m4YScAb/T1x87OjuQLlxjywWJMdnaUcylBaH+zwUeTd7w6cRo790Zz9ux5WrbrwZD+Penwj+xZQXav52hBdDd1BjB23Jt8OW8G7703idOnkun/nxEAvDo6hNkz3+Hll/+DxWKh/4ARhhyHrd1tvU2bOp6uXdpTtGgR4o7s4ot5XxMy+X3emvo6xYsXY9E3swGIjz9G+6C+hhyLLWSkZ7A0+AuGLBiHyd7EtiWbOBGbgN+ITvz1yxFiNuwmcGwPnIoWpu+nmZ+hlGOn+ew/77Bv9TaqN63FmLXvgsXCwc37iNm4x+AjkgeRoY0NDw8Phg8fTr9+/cjIyMDR0ZHg4OA7rhcZGUl4eDgODg6UKVPmtgOtAV5//XXGjh3L559/TqlSpZg6NfNWeUOHDuXll1/G2dmZp556ioSEzBb7iy++yKhRo/D396d+/fpUqPB3yvY///kPoaGhuLq60qlTJ9q2bUuZMmWoXbt2ln36+fnx9ttvs3HjRgAKFy7MxIkTGTBgAEWLFqVWrZvfG/yGU6dO0aFDBy5evIjJZOLLL79k9erVFC9e/I71kx8Ne3n8Teff+GI5efI0TZrevGva4zWb5VpcedUztT14prZHlnlDAptb31etUIYvx/TKtl7FMiUJD739+VRQvfNG/m2g3g/3co7+k0f1xvc1rrzsTnUG8Ndfx3iuZYdsZQ4ejKX5s+1yLba87G7qbczYNxkz9s1sZVr7ds21uPKqA5v2WQd937B6+rfW95/0uPktvS0ZFhaP+yxXY5OC8QRxO0tBuc9gHnDp0iWKFSuGxWLhjTfeoHLlyvTp08fosO6ag1P+f/jR/XZhQ/YvO7kzh5rN71xIsilS4RmjQxCR2xhSoeBd/LofZsQtNjqEXJPcvoVN91dq+Wab7g8MzmwUNN9++y3Lly8nNTWVGjVq0KVLF6NDEhERERGjGDSOwpbU2LChPn36ZMtkLFu2jAULFmSZ16BBAyZOnJht/ZSUlJtmQubPn4+Ly63vmy0iIiIiYgQ1NgzWoUMHOnTI3h/3ZlxcXAgPD8/liERERERE7g81NkREREREDGApAN2o9GhgERERERHJFcpsiIiIiIgYQZkNERERERGRnFFmQ0RERETEABqzISIiIiIikkPKbIiIiIiIGEGZDRERERERkZxRZkNERERExAAasyEiIiIiIpJDymyIiIiIiBhAmQ0REREREZEcUmNDRERERMQAlgzbvu5ky5YttG7dGm9vb+bMmXPTMqtXr8bPzw9/f39GjRp1x22qG5WIiIiISAGXnp5OSEgI8+bNw9XVlY4dO+Ll5YWHh4e1TFxcHHPmzOGbb77B2dmZM2fO3HG7ymyIiIiIiBjBYmfb121ER0fzyCOP4O7ujpOTE/7+/mzcuDFLmSVLltC9e3ecnZ0BKF269B0PUZkNEREREZECYPHixSxevNg63aVLF7p06QJAUlISbm5u1mWurq5ER0dnWT8uLg6Arl27kpGRwdChQ2nevPlt96nGhoiIiIhIAfDPxkVOpKen8+eff/LVV19x4sQJevToQUREBA899NAt11E3KhERERERA+SlAeKurq6cOHHCOp2UlISrq2u2Ml5eXjg6OuLu7k7lypWt2Y5bUWNDRERERKSAq127NnFxccTHx3P9+nVWrVqFl5dXljKtWrVix44dACQnJxMXF4e7u/ttt6tuVCIiIiIiBrBk3H7Qti05ODgQHBzMgAEDSE9Pp0OHDlSrVo0PP/yQWrVq0bJlS5555hl+/vln/Pz8sLe357XXXsPFxeW227WzWCwWGx2DPOAcnCoaHcID58KGN40O4YHkUPP2g83k5opUeMboEETkNoZUaGZ0CA+kGXGL71zoAXW82XM23V/5n36w6f5AmQ0REREREUPczYP2HnQasyEiIiIiIrlCmQ0REREREQNY7vCgvfxAmQ0REREREckVymyIiIiIiBhAYzZERERERERySJkNERERERED5KXnbOQWZTZERERERCRXKLMhIiIiImKAgvBobTU25K51Kt/I6BAeOCVajTc6BClAriT+aHQID5w1tXSO5sTz57cZHcID6dPEn4wO4YE0w+gA5J6osSEiIiIiYgCN2RAREREREckhNTZERERERCRXqBuViIiIiIgB1I1KREREREQkh5TZEBERERExQEG49a0yGyIiIiIikiuU2RARERERMYDGbIiIiIiIiOSQMhsiIiIiIgawWJTZEBERERERyRFlNkREREREDGDJMDqC3KfMhoiIiIiI5AplNkREREREDJChMRsiIiIiIiI5o8yGiIiIiIgBdDcqERERERGRHFJmQ0RERETEAHqCuIiIiIiISA6psSEiIiIiIrlC3ahERERERAxgsRgdQe5TZkNERERERHKFMhsiIiIiIgbQAHEREREREZEcUmZDRERERMQAGXqon4iIiIiISM4osyEiIiIiYgCLMhsiIiIiIiI5o8yGiIiIiIgB9JwNERERERGRHFJmQ0RERETEALoblYiIiIiISA4psyEiIiIiYgDdjUpERERERCSHHtjGhpeXF8nJyQDUr18fgKSkJIYNG2ZkWHe0a9cu/P39CQwM5OrVq4bF8dFHH/H5558btv+7VbdFfd77/hOmb55JwOCgbMv9BgTwzoaPeGvNB4z/OoQyFcsCUKZiWaaseo+pq6fzzvoZtOre2tahG276+yH8duAn9uxeT/16tW5aZlXEf9m9az37933PJx9Pw2TK/JdQp05Nftqygr17NvDd8vmUKFHclqEb6l7q7YYRw18g7foxSpd2sUXIedqEKe/T3L8r7XoMMjqUPKXsc3V57qf38IqajsfQgFuWK+//JOYT3+Bc99Es84tULI3v4Xk8Otg/t0M1XCvv5uzZt5H9v/zAyFHZP0dOTk58ueAj9v/yAz9sXs7DD1cE4DmvZvz48wq274jkx59X0KJFE+s6HTr4s217JDt3rSVk8mibHYtR7ub/2uSQ0Rw9vJOzyb9nmT/85YFE7/+BPbvXs27NYmv9yv1hsdj2ZYQHtrFxM66ursyYMcPoMG5rxYoVDBw4kPDwcAoXLmydn5aWZmBUeZOdyUTfyS/wVu8QXmn1Ek0DnqFitUpZysT9eoTxbUcxus1wtq/eSrexvQFIOZlCcPvRjPUbwYTA1wgY3AGXcgXnh59vGy+qeVTh8ZrNGDx4NJ98PPWm5bp2G0RDT2/q1vOibNlSdOzYFoDZs95h3Pgp1G/Qiu++i+SVUYNtGb5h7rXeACpVqoB3q+b8+WeCrcLO09r5eTPr/VCjw8hbTHbUntqX7d3e4ofmr1ChfVOKV8/+A86+WGGqDGhDyu7YbMtqvtGTk9/vs0W0hjKZTLw/PYSgdn3wbOBDp04BPP64R5Yyvft05uzZc9St/RyffPQ5k0PHAHDmTDKdOg7gqSd9eeE/r/DZ5+8DUKpUSUKnjKWtf3caebbG1bUszz7b1ObHZit3+39t5cr1NHk6e+N1374YnmrsS4OG3iwLW8W0qRNyO2TJZx6IxkZ4eDgdO3YkMDCQ4OBg0tPTb1ouISGBtm0zv/RjY2Ot65jNZuLi4rKV/+ijjxg9ejTdunXjueeeY926dbz99tuYzWb69+9PamoqADExMfTo0YOgoCD69+/PyZMnAejZsydTpkwhKCgIX19foqOjGTp0KD4+PkyfPj3b/r799lvWrFnDhx9+yKhRo9i+fTvdunVj0KBB+Pv7k56ezltvvUWHDh0wm80sWrTIuu7cuXOt82/XoEpISKBNmzaMGTOG1q1bM2rUKLZu3UrXrl3x8fEhOjraWva3336jS5cu+Pj4sGTJkjv/IWzMo141TsQd52R8EumpaURF/ISn91NZyhyIiuH61esA/LH3EKXKlwYgPTWNtOuZDThHJ0fsTPm/T+Q/mf+PvfuOy6r8/zj+YiniQFEDBXLkKJNEwxyZpnxdKYJbM7f5TX+lpmWaRqXmSM3Scn3LmbkHLpyplXuPNFwgGxUxt+B98/uDb7fxBcNI7sN4P33weHDOuc45n3PJPa7zua7r+DVl4aIVAOw/cATnos64uT2VptzNm7cAsLe3J1++fJa7HpUqluenn/cBsG37z7Ru/Zp1AjfYP603gMmTPmHYh5+RnBcmT38MPt5eOBcpbHQY2Uqx6hW4HRrLnfDLJCeZiF6zF7emPmnKPftBB85/sw7T/aRU692a+XAn/DI3Q3J/g9bHpxoXL1wiLCyCpKQkVqxYR4uWjVOVadGiMYu+XwnA6tXBlobDieOniY1J+bw+ffosjo6O5MuXj7LlnubC+TCuXk3pHbFjx278A5pZ8aqs63HfMBOQtgAAIABJREFU1/YfOEJs7OU063fu2sPdu/f+W+YwHu6lsjbgPMacbGPVHyNk+8bGhQsXCA4OZvHixQQFBWFra8u6desy3G/JkiV069aNoKAgVq5ciZubW7rlwsPDmT9/PjNmzOD999+nVq1arFu3DkdHR3bt2kVSUhJjxoxh6tSprFq1irZt26ZqSDg4OLBq1So6depE//79CQwMZP369axevZqEhIRU52rfvj2NGjVi6NChTJ48GYDTp08zYsQINm/ezIoVKyhcuDArV65k5cqVLFu2jIiICH755RcuXbrEihUrCAoK4tdff+XgwYOPvPbw8HB69uxJcHAwoaGhrFu3jsWLFzN06FBmzpxpKRcSEsL8+fNZsmQJ33zzDXFxcRnWqzUVc3MhPuaqZTk+Jp5ibi6PLP9qx39xfOcRy7JLqRJM2PQlX+/7lrUzV5FwOeGR++Y27qXdiIyItixHRcbgXjr918DG9YuIiTrOzZu3WLlyPZDywdyqVUrXs3ZtW+LpUTrrg84G/mm9+fk1ISoqhhMnTlslXsmZHEsV4250vGX5Xkw8jqVSZ16dvcpSoLQLl7cdTbXezik/z7ztx9lJK60Sq9FKl3YjMirGshwVFUvp/3lNli7tailjMpn4/cbNNF0YAwKac/zYKRITE7l4IYyKlcrz9NPu2NnZ4efXGPdc/B73d97XMtKzR2c2bd7xpEKTPCLbz0a1d+9eTp06Rbt27QC4d+8exYsXz3A/b29vZs6cSWxsLE2aNKFs2bLplqtfvz4ODg5UqlQJk8lE/fr1AahUqRKRkZGEhoZy9uxZevbsCYDZbKZkyZKW/Rs1amQpX7FiRZ56KuVugaenJ7GxsRQr9tddd7y8vPD09ARg9+7dhISEsHnzZgBu3rzJpUuX2L17N7t37yYgIACAO3fuEBYWRs2aNdM9poeHB5UrVwagQoUK1KlTBxsbGypXrkxUVJSlnK+vL46Ojjg6OlKrVi1OnjyJq6vrX8abXdVr3YDyXhUY1XGEZd21mKt80GwQxZ4qxuD/DOfAxj38fvV3A6PMnl5r2YX8+fOzcME0GjV8mW3bf6ZP38F8+cVoRnw4iPXrt5CYmJTxgfKY/6233XsOMvyDd2j22utGhyY5nY0NVT7tyrGBM9Jsqvx+Oy7ODsZ0574BgeVMzz1XkVFjPsDfrxsA16/fYNDAj5i/8GvMZjP79x2hXPmnDY4y+3v99Tb4vFiNhr5tjQ5Fcphs39hITk6mdevWDBkyJNX61atX/+V+fn5+VKtWjZ07d9K3b18+/fRTLl68aOkuNHv2bCBlYBmk9At1cHDAxsbGsmwymUhOTqZixYosXbo03fP8ef8/fv9j+XHGYTg5OaW61pEjR/LKK6+kKvPLL7/Qt29fOnXqlOHx/hzT/8ZlY2OTqgvaH9eaXSXEXqN4qRKW5eKlipMQey1Nuaovv0DA2+0Y1WGkpetUquNcTiDybDiVX6rCgY17szRmI/V7qzu9e3cB4NChY3h4PrxT5+5Riqjo2Efue//+fdau24KfX1O2bf+ZkJALNG+R8qW5YsXyvNbcN2uDN9CTqrfYuCuULfs0Rw5tBcDDoxQH92+mzsstiIu7krUXITnKvZgECpR+eNPMsVRx7sU8zLzaF3KkSGVP6q4KBCB/SWdemv8eB7pPomj1CpRqWYsqH72OQxEnks3JmO8nETZni9Wvwxqio2NTddtxd3cj+n9ek9HRcXi4lyI6KhY7OzucixQmPj6lPku7u/HDkln07TOE0NBwyz7BG7cTvHE7AD17dX5k9+yc6p+8r6XHt9ErDB82gEa+bUlMTHyiseZ1mvo2G6hTpw6bN28mPj4l5Xz9+vVUd+cfJSIiAk9PT7p164avry8hISF06dKFoKAggoKCHvsOfrly5bh27RpHj6akspOSkjh3Lu1gvSehXr16LF682DJWJDQ0lDt37lCvXj1WrlzJ7du3gZRZt/6oj39i+/bt3L9/n4SEBA4cOICXl9c/PuaTdOH4OdzKlaKk51PYOdhTx68eh7ceSFWm7PPl6DOuP5N6j+VG/MOshYtbcRzypzSyChYpSGWf54i5EE1uNmPmfHxqNsGnZhPWrt1M1y4p2cBaL9Xgxu830vTFLVjQydJv187Ojtea+xISch6AkiVTvgjZ2Njw4fCBzJq90IpXYl1Pqt5OnfqN0h7VqFCpNhUq1SYyMoaatZqqoSFpXD92gYLl3SjwdElsHOwoHVCH2C2HLdsf3LzL5uf7sr3mALbXHEDCkfMc6D6J349fZE/Ap5b1F/8TzLmpa3JtQwPg8OETPFOhLGXKeODg4EC7dn5s3LAtVZmNG7fR5Y2Uu+2tWzdn166Um0rOzoVZuXIOHwdOYN++w6n2+eM9rmjRIrzZ9w3mz0v/hmJO9Xff1/6Kt/fzTP9mPK3b9OTKlX/+3UPynmyf2ahQoQKDBg2iV69emM1mHBwcCAwMzHC/4OBggoKCsLe3p0SJEvz73//O1Pnz5cvH1KlTGTNmDDdv3sRkMtG9e3cqVqz42Md48803GTNmTIYNnPbt2xMVFUWbNm1ITk6mWLFiTJ8+nXr16nHhwgVLZsPJyYmJEyc+Vneyv1K5cmW6detGQkIC/fv3z3ZdqMwmM/MC/8PwBR9ja2fHzmXbiDwXQbvBnQk9cZ7D2w7y+oc9cHRyZOD0oQDER19hUp+xuFfw4I2RPUlOTsbGxob1s4OICLlk8BVZz8bg7TRr1oiQM7u5c/cuffoMtmw7dHALPjWbULCgE6tXzSV//nzY2tqyc+ceS6OiU8cA+vXrAcCaNRuZNz93fRA/yj+tN0nr/Y/Hc/DoCa5fv4FvwBv0792Vtn55byrqP0s2mTn14TxqLx6OjZ0tEYt3ciskkspD23H9WChxWw5nfJA8wmQyMWTwx6xZuwA7O1sWLljOmTPnGPnRuxw5cpKNG7Yxf95Svv1uCsdP7iAh4Xd6dHsHgH+/1Z3yz5Rh2PABDBueMi2+v183rlyJ5/OJgXh5PQfA+HFTOX8+1LBrzGqP874GMH7cCDp1bI2TUwHCLh5iztwfGDX6CyaM+4hChQqyZPEsACIiomjdpqch15IbGTVo25pskjVlijymzmUCjA4hx1ke8+iB/CJP2t3on40OIcfZVHVExoUkjc439hkdQo5074G6IGXGg8SMe7TkVPtLp32GWFaqFb3KqueDHJDZEBERERHJjfLCHX81NnKohIQEevTokWb9vHnzMpwBS0RERETEGtTYyKGKFStGUFCQ0WGIiIiISCblhTEb2X42KhERERERyZmU2RARERERMYCesyEiIiIiIpJJymyIiIiIiBjAbHQAVqDMhoiIiIiIZAllNkREREREDJCMxmyIiIiIiIhkijIbIiIiIiIGMOeBR4grsyEiIiIiIllCjQ0REREREckS6kYlIiIiImIAswaIi4iIiIiIZI4yGyIiIiIiBtDUtyIiIiIiIpmkzIaIiIiIiAHMRgdgBcpsiIiIiIhIllBmQ0RERETEABqzISIiIiIikknKbIiIiIiIGEBjNkRERERERDJJmQ0REREREQMosyEiIiIiIpJJymyIiIiIiBhAs1GJiIiIiIhkkjIbIiIiIiIGMOf+xIYyGyIiIiIikjXU2BARERERkSyhblQiIiIiIgYwa4C4iIiIiIhI5iizISIiIiJigGSjA7ACNTbksVWloNEh5DjLjQ5A8pRNVUcYHUKO0+zUZ0aHkCOVr9rF6BBypNPXwo0OQcTq1NgQERERETGA2egArEBjNkREREREJEsosyEiIiIiYgCzjWajEhERERERyRRlNkREREREDJAXZqNSZkNERERERLKEMhsiIiIiIgbQbFQiIiIiIiKZpMyGiIiIiIgBzLl/MiplNkREREREJGsosyEiIiIiYgAzuT+1ocyGiIiIiIhkCTU2RERERESEn376iaZNm9K4cWNmz579yHKbN2+mcuXKnDx5MsNjqrEhIiIiImKAZCv//BWTycSoUaP49ttv2bBhA+vXr+f8+fNpyt26dYsFCxZQrVq1x7pGNTZERERERPK4EydOUKZMGTw9PcmXLx8tWrRg+/btacp99dVXvPnmm+TPn/+xjqvGhoiIiIiIAcw21v1ZunQpbdq0sfwsXbrUEktcXBxubm6WZVdXV+Li4lLF++uvvxIbG8urr7762Neo2ahERERERPKAjh070rFjx0ztazabGT9+POPGjftb+6mxISIiIiJiALPRAfyJq6srsbGxluW4uDhcXV0ty7dv3+bs2bN069YNgCtXrtCvXz9mzJiBl5fXI4+rxoaIiIiISB7n5eVFWFgYERERuLq6smHDBiZPnmzZXrhwYfbv329Z7tq1K0OHDv3LhgaosSEiIiIiYoiMZoiyJnt7ewIDA+nTpw8mk4m2bdtSsWJFvvrqK6pWrYqvr2/mjvuE4xQRERERkRyoQYMGNGjQINW6gQMHplt24cKFj3VMNTZERERERAxgtjE6gqynqW9FRERERCRLKLMhIiIiImKA7DQbVVZRZkNERERERLKEMhsiIiIiIgZQZkNERERERCSTlNkQERERETFAsmajEhERERERyRw1NkREREREJEuoG5WIiIiIiAE0QFxERERERCSTlNkQERERETGAMhsiIiIiIiKZpMyGiIiIiIgBko0OwAoMz2w0atSIa9euAVC9enUA4uLiGDBgQJaed+bMmY/cNmLECM6fP/+3jzls2DA2bdr02OX379/PkSNH/vZ58pryDV7grR8n0m/XZOr080uzvUYXX97cPJ4+G8fSbUUgJSq6A1C6Wnn6bByb8hM8lspNfawduqGmfDGK307/wpHDW6nuXTXN9kKFCnLo4BbLT2z0SSZP+hSAyRM/saw//evPXL182trhGyajegNwcHBgxvQJnP71Z06d3EXr1q8B4OlZmm1blnPwwGaOHN5K82aNrBm6IUo2rEbDXybTaO8UKrzd6pHlSrV4Cb/YxThXK59qfQH34jS/MJfy/Vpkdag5xsixX1C/RScC3njL6FCynZcb1mbtL0tYv3c5vd7ummb7i7W9WbplHkcif6Zxy4aW9ZWfr8jC9bNZtWsRK35cSFN/X2uGbbiM3tcKFHBk7ZoFnDq5i+PHfmTsZ8Mt27p17UBM1AnLZ0Kvnp2tGbrkAtkys+Hq6srUqVOz9ByzZs3irbfSfyP/7LPPsvTcfzhw4ABOTk7UqFHDKufLiWxsbWg2ugc/dBnHjdhr9Fo7mnPbjnD1XJSlzKmgPRxZtB2Aiv+qwb9GdmFJ98+5HBLJd34jSTaZKfRUUfoEj+XstiMkm3J/D8nmzRpRsUI5nq1Sj1ov1eCbr8dRt17qhtqtW7fxqdnEsrx/XzBr1mwEYMj7n1jW/1//nng/4kt3bvM49Qbw4fABXLkST5XnX8HGxgYXl6L/XT+Q5SvWMWv2Ap57riLrghZSoVJta1+G9dja4DWuJ/s6jOVuTDyvbPqM2C2HuXU2KlUxu4KOlOvTjITD59IcosqnXbn84zFrRZwjBLzWmNfbtuLD0ZOMDiVbsbW15cNxQ+jbYSBxMZdZvGkOO7f8zMWzYZYyMVGxjBw4mh79u6Ta997de4x4ZxThoZGUdC3Bki1z2bNjPzdv3LLyVVjf476vfTFlJjt37cHBwYGtm5fSrGlDNm3eAcCy5WsZOGiktUPPE8x6qN+TFRQURLt27fD39ycwMBCTyZRuucjISFq2bAnAuXPnLPv4+fkRFhaWpvy0adMYPnw4Xbt2xdfXlwULFvzlOSdNmsS9e/fw9/dnyJAhaY7XtWtXTp48CaRkW6ZMmUKrVq3o0KEDV69e/ctr3LNnD23atKFp06bs2JHyIu3SpQtnzpyxlOncuTO//fYbS5YsYd68efj7+3Po0CGuXbvGO++8Q9u2bWnbti2HDx8GUhol/v7++Pv7ExAQwK1b6b85Xr58mS5duuDv70/Lli05dOgQAL/88gsdO3akdevWDBgwgNu3bwNw4sQJOnXqRKtWrWjXrt0jj2uk0t7PcC0sjusRVzAnmTi9bh+VGr+YqkzirbuW3x2c8lt+f3Av0dKwsMvvQHJeyFX+l59fUxYuWgHA/gNHcC7qjJvbU48sX7FieZ4qWYKff9mfZlunjgEsXbomy2LNTh633np078T4CdMASE5OJj4+4b+/Q5EihQBwLlKEmJg4K0VujGLVK3A7NJY74ZdJTjIRvWYvbulkEJ/9oAPnv1mH6X5SqvVuzXy4E36ZmyGR1go5R/Dx9sK5SGGjw8h2qlavQnhoJFHh0TxIesCmNdto2LR+qjLREbGcO3MBszn1TaVLFyMID035O7sSd5VrVxMoVryo1WI30uO8r929e4+du/YAkJSUxJGjJ3F3L2X1WCV3slpm48KFCwQHB7N48WIcHBz45JNPWLduXYb7LVmyhG7dutGqVSsSExPTvIH8ITQ0lAULFnDr1i2aN29O586dCQ8PT/ec7733HosWLSIoKCjD89+5c4dq1arx7rvv8vnnn7Ns2TL69+//yPJRUVGsWLGC8PBwunXrRt26dWnXrh2rVq1ixIgRhIaGcv/+fZ599lk6deqEk5MTvXv3BmDIkCF0794dHx8foqOj6d27N8HBwcyZM4fAwEBefPFFbt++Tf78+dM99/r166lXrx79+vXDZDJx9+5drl27xowZM5g7dy5OTk7Mnj2buXPn0rdvX959912mTJnCCy+8wK1bt3B0dMywPqytsJsLN2PiLcs3Yq7hXv2ZNOVe7NaYWn2aY+dgz/edH2amSns/Q8uJfXF2L8Had2fkiawGgHtpNyIjoi3LUZExuJd2Izb2crrlO3ZoxfLla9Osf/ppd8qW9eTHHbuzLNbs5HHqzdm5CACjPhlK/QZ1uHjxEgMGjuDy5auMGj2Z4I0/8H/9e1GwYAGaNutk9WuwJsdSxbgb/fD1eS8mnqI1KqQq4+xVlgKlXbi87SjP9G9pWW/nlJ9n3vZjX4exqdaLPIprqZLERT98LcbFXMarxvN/+zhVq1fBwcGBiLCojAvnAn/388DZuQgtWzRm2tffWda1af0ar7xSi3PnQhny3idERkanu6/8fXnhW4nVMht79+7l1KlTlizD3r17iYiIyHA/b29vZs2axezZs4mOjn7kF+IGDRqQL18+XFxccHFxIT4+PtPn/DMHBwcaNkzp91m1alWiov76zal58+bY2tpStmxZPD09uXjxIs2aNWPnzp0kJSWxcuVK2rRpk+6+e/bsYfTo0fj7+9OvXz9u3brF7du3qVGjBuPHj2fBggXcvHkTe/v024heXl6sWrWKadOmcfbsWQoVKsTx48c5f/48nTt3xt/fnzVr1hAdHU1oaCglS5bkhRdeAKBQoUKPPG5OcHjBVqbXH8yP45dQ750Ay/roYxeY3fgD5rT6iLr9W2GX38HAKLOvDh38WZJO9qJjB39WrtrwyEZ+XmRvb4enZ2n27DvES7WasW/fYT6fEAikZIEWLFhO2fI++LXqxrx5U7GxyQM58kexsaHKp1359dPv02yq/H47Ls4OxnTnvgGBSV5V4qnijJ0WSOCgMSTnpXT3Y7Kzs2PRwm/4+ps5hIaGA7B+w1aeqVibGi82Ztu2n5j73ZcGRyk5jdW+XSYnJ9O6des03ZZWr179l/v5+flRrVo1du7cSd++ffn000+5ePEiy5YtA2D27NkA5MuXz7KPnZ0dDx48eOQ5/w4HBwfLlwVbW9tHdv36w/9+sbCxsaFAgQLUrVuX7du3ExwczKpVq9Ld12w2s2zZsjSZi759+9KgQQN27dpF586d+fbbb3nmmbR392vWrMn333/Prl27GDZsGD179qRIkSK8/PLLfPHFF6nKhoSEZHjt2cHN2GsULlXcslyklAs3YxMeWf7XtXtpNqYnMCvV+vjz0STeucdTlTyIORmaVeEaqt9b3endO6Wf8qFDx/DwLG3Z5u5Riqjo2HT3e+GFKtjb23Pk6Mk02zp08GfAgBFZE3A28XfrLT4+gdu377B6dcr4lhUr19OzZ0oGo2fPTrRo+QYA+/YfxjF/fkqUcOHKlXhyo3sxCRQo/fD16ViqOPdiHr4+7Qs5UqSyJ3VXpTTG8pd05qX573Gg+ySKVq9AqZa1qPLR6zgUcSLZnIz5fhJhc7ZY/TokZ4iLuYJr6Yfdf1xLPcXlmCuPvX/BQk588/1kpo2fxYkjv2ZFiNlGZj8PZs74nHPnQ5k67VvLumvXHr6mv5vzA+PH5e7PBGvLC7fyrJbZqFOnDps3byY+PuVD9/r16xlmCQAiIiLw9PSkW7du+Pr6EhISQpcuXQgKCiIoKAhXV9dMndPe3p6kpKRH7ptZmzZtwmw2Ex4eTkREBOXKlQOgffv2jBkzBi8vL5ydnQEoWLCgZfwEQL169Vi4cKFl+Y9xHuHh4VSuXJm+ffvi5eVFaGj6X5ajoqIoUaIEHTp0oH379vz66694e3tz5MgRLl26BKR0CwsNDaVcuXJcuXKFEydOAHDr1i0ePHjwxOvjn4o+fhGXcm44e5bE1sGOKn61Obv1cKoyxco+/Buo2MibhLCUN1Fnz5LY2KX8iRdxL0HxZ0pzPfLxP5hymhkz5+NTswk+NZuwdu1munZpB0Ctl2pw4/cbj0yZd+ron+6YjMqVn6FYUWf27juUpXEbLTP1tn7DVl5tUBeARg3rceZMysDniPAoGjWsB8Czz1bA0TF/rm1oAFw/doGC5d0o8HRJbBzsKB1Qh9gtD1+fD27eZfPzfdlecwDbaw4g4ch5DnSfxO/HL7In4FPL+ov/Cebc1DVqaMhf+vXYGcqU98T96VLYO9jTLOBf7Nzy82Pta+9gz5dzJ7BueTBb1+/I4kiNl5n3tVGfDsXZuTCDh3ycav2fx3f4+TXht9/+/mydkrdZLbNRoUIFBg0aRK9evTCbzTg4OBAYGJjhfsHBwQQFBWFvb0+JEiX497///Y/P6e7uTocOHWjVqhVVqlRh8uTJvPnmm4wZM+YvGy+Po1SpUrRr147bt2/z6aefWrIUVatWpVChQqm6UDVs2JABAwawfft2PvroI0aMGMGoUaPw8/PDZDLh4+PDqFGjmD9/Pvv378fGxoaKFStSv379dM994MABvvvuO+zt7XFycmLChAm4uLgwbtw4Bg8eTGJiIgCDBg2iXLlyTJkyhTFjxnDv3j0cHR2ZO3dututKlWwyszlwHp0XfICtnS3Hl+3i6rko6g9uS8yJUM5tO4JP9yaUq1cVc5KJuzdus3ZwyrTGnj6VqdvfD3OSieRkM5tGzuVuQvYbBJ8VNgZvp1mzRoSc2c2du3fp02ewZduhg1tSzULVrq0ffv5pp5Ds2MGfZcszHteUmzxuvQ3/8DPmz53K5MmfcPXKNXq/+S4A738wilkzJjJw4JskJyfTu8+7hlyHtSSbzJz6cB61Fw/Hxs6WiMU7uRUSSeWh7bh+LJS4LYczPoik8f7H4zl49ATXr9/AN+AN+vfuSlu/pkaHZTiTycTYDyczY/GX2NnZsmbxei6EhNJ/6JucPnaGnVt+4Xnv5/hyzniKFC1Mg8b16Pd+H9o06ELTVr7UqO2Nc7EitOqYMlX1RwPHEPJr2hnScpvHeV9zdy/Fh8MHcua3cxw8sBmA6dPnMmfuYt55uxctWzbhwQMTCdeu06vPIKMuJVfKC535bJLVadEq4uLi6NatG8HBwdjaGv54k0z5rEyXjAtJKh/H7DQ6BMlDVrukfyNCHq3ZKetMdZ7bvFhVnweZcfpauNEh5EgPEnPvYP5JT79h1fO9F552DF1Wy5nfenOYNWvW0KFDBwYNGpRjGxoiIiIi8mSZbaz7Y4Ts1Wcmh5gxY0aaJ4U3a9aMfv36pVs+ICCAgICAdLdlRkhICEOHDk21Ll++fCxfvvyJnUNERERE5J9SYyMT+vXr98iGhTVUrlz5sZ4RIiIiIiJiJDU2REREREQMoKlvRUREREREMkmZDRERERERA+SFKWGV2RARERERkSyhzIaIiIiIiAHMeSC3ocyGiIiIiIhkCWU2REREREQMoNmoREREREREMkmZDRERERERA+T+ERvKbIiIiIiISBZRZkNERERExAAasyEiIiIiIpJJymyIiIiIiBjAbGN0BFlPmQ0REREREckSymyIiIiIiBhATxAXERERERHJJDU2REREREQkS6gblYiIiIiIAXJ/JyplNkREREREJIsosyEiIiIiYgA91E9ERERERCSTlNkQERERETGApr4VERERERHJJGU2REREREQMkPvzGspsiIiIiIhIFlFmQ0RERETEAJqNSkREREREJJOU2RARERERMYBmoxIREREREckkZTZERERERAyQ+/MaamzI3xBn88DoEETkL3S+sc/oEHKc8lW7GB1CjnT41CKjQ8iRrrXvaXQIIlanxoaIiIiIiAE0G5WIiIiIiEgmqbEhIiIiIiJZQt2oREREREQMkJwHhogrsyEiIiIiIllCmQ0REREREQNogLiIiIiIiEgmKbMhIiIiImIAs8ZsiIiIiIiIZI4yGyIiIiIiBsj9eQ1lNkREREREJIsosyEiIiIiYgCN2RAREREREckkZTZERERERAyg52yIiIiIiIhkkjIbIiIiIiIGSNaYDRERERERkcxRZkNERERExAAasyEiIiIiIpJJamyIiIiIiEiWUDcqEREREREDaIC4iIiIiIhIJimzISIiIiJiAA0QFxERERERySRlNkREREREDGBO1pgNERERERGRTFFmQ0RERETEALk/r6HMhoiIiIiIZBFlNkREREREDGDOA7kNZTZERERERCRLKLMhIiIiImIAPUFcREREREQkk5TZEBERERExgJ4gLiIiIiIikklqbEi29lyDaozYPoWPdn7Fv/r5p9nesHcLPtw6mQ+CP+f/Fo2kmHsJy7ZWw7owfMskPtzKk1aeAAAgAElEQVT2BW0/7mHFqLOHKV+M4rfTv3Dk8Faqe1dNt8zoUR8QeuEg16+dTbW+75tdOXpkG4cObmHXjtU891xFa4ScLfyTehs0sC8nju/gyOGtbNm0lKefdrdGyFb3r8b1OXJsO8dP7mDwkLfSbM+XLx/zF0zj+Mkd7Ni12lIPDRvV4+fda9l/IJifd6+lQYM6ln3atm3Bvv3BHDy0mVGjP7DatRjl5Ya1WfvLEtbvXU6vt7um2f5ibW+WbpnHkcifadyyoWV95ecrsnD9bFbtWsSKHxfS1N/XmmFnayPHfkH9Fp0IeCPt36Q8lK/mSxSfv5Di3y/CqfPr6ZbJ/2pDis+dT/G58ygy8iMrR5i3mEm26o8RMt3YaNSoEdeuXQOgevXqAMTFxTFgwIAnE9kjzJw584kda//+/Rw5cuSJHe+vdO3alZMnTz5W2cjISNatW5fFEWV/NrY2tB/Vi5k9xjG28WBebPUybhVSf3mLPB3GRL/hTGg+lOPB+/Ef3gWAcjUqUd6nMuObvc+4JkN4utozVKhdxYjLMETzZo2oWKEcz1apR79+H/DN1+PSLbd+/VbqvNwizfrFS1ZTvca/8KnZhImTpzPp84+zOuRs4Z/W27Fjp6hVuzk1XmzMylUbGD9uZFaHbHW2trZ8MWUUbQJ64FOjCe3bt+LZZyukKtO9RweuX/+dal4N+Wbad4weMwyA+PhrtG/Xh1ovNeffb77Hf777AgAXl6KMGTucli26UNOnKa6uJXn11bpWvzZrsbW15cNxQ+j3+mAC6nemeevGlK9UNlWZmKhYRg4cTfDqranW37t7jxHvjKJNgy706/wuQ0cNonCRQlaMPvsKeK0xM78YY3QY2ZutLYUHDuL6sKHE9+iOo68vdmXKpCpi5+5Owde7cO2d/yO+Zw9ufj3NoGAlt3iimQ1XV1emTp36JA+ZxqxZs57YsQ4cOMDRo0ef2PGelKioKNavX290GIYr412BK5fiiI+4jCnJxJF1e/BqUjNVmXN7fyXpXiIAYUfPUdStOJAyu4NDfgfsHeyxz+eAnb0dN6/8bvVrMIqfX1MWLloBwP4DR3Au6oyb21Npyu0/cITY2Mtp1t+8ecvye8GCTiQn5/7ZMuCf19vOXXu4e/fef8scxsO9VNYGbAAfn2pcvHCJsLAIkpKSWLFiHS1aNk5VpkWLxiz6fiUAq1cHWxoOJ46fJjYmpd5Onz6Lo6Mj+fLlo2y5p7lwPoyrV1NuYO3YsRv/gGZWvCrrqlq9CuGhkUSFR/Mg6QGb1myjYdP6qcpER8Ry7swFzObUPbovXYwgPDQSgCtxV7l2NYFixYtaLfbszMfbC+cihY0OI1tzePY5TNFRmGJi4MED7v34I/lfrpeqTIGWftxds5rkWymfA8nXrxsRquQij9XYCAoKol27dvj7+xMYGIjJZEq3XGRkJC1btgTg3Llzln38/PwICwtLU37atGkMHz6crl274uvry4IFC/7ynJMmTeLevXv4+/szZMiQNMfbu3cvAQEB+Pn5MXz4cBITU76E/jkLc/LkSbp27UpkZCRLlixh3rx5+Pv7c+jQoXSvadiwYQQGBtKmTRuaNm3Kjh07LNf6+uuv07p1a1q3bp0qQzJ79mz8/Pxo1aoVkyZNSnU8s9nMsGHDmDJlCiaTiQkTJtC2bVv8/PxYsmQJAJMnT+bQoUP4+/szb968x6pLgDt37tC3b19atWpFy5Yt2bhxIwCnTp3ijTfeoE2bNvTu3ZvLl1M+7C9dukSPHj1o1aoVrVu3Jjw8PN3jGqWoqwvXo+Mty9dj4nF2LfbI8rU7NOT0zmMAhB05x9m9vzL64CzGHJjFmZ+OE3chKstjzi7cS7sRGRFtWY6KjMG9tNvfOka/t7oTcmY348eOZNDgwCcdYrb0JOrtDz17dGbT5h1PKrRso3RpNyKjYizLUVGxlP6fOipd2tVSxmQy8fuNmxQvnvq1GxDQnOPHTpGYmMjFC2FUrFSep592x87ODj+/xrh7lM76izGIa6mSxEU/bKzGxVzmqVIl//ZxqlavgoODAxFheee9Tf4Z2xIlMF9++LdnvnIFuxIlUpWx8/DAztOTYtO+ptg308lX8yVrh5mnJFv5nxEynI3qwoULBAcHs3jxYhwcHPjkk08eq4vPkiVL6NatG61atSIxMTHN3Zk/hIaGsmDBAm7dukXz5s3p3Lkz4eHh6Z7zvffeY9GiRQQFBaU5zv379xk2bBjz5s2jXLlyDB06lB9++IEePXqke14PDw86deqEk5MTvXv3/striYqKYsWKFYSHh9OtWzfq1q1L8eLFmTt3Lvnz5ycsLIzBgwezatUqdu3axY8//siyZcsoUKAA1/90R8BkMvHee+9RsWJF+vXrx9KlSylcuDArV64kMTGRTp068fLLLzNkyBDmzJljyeKMHj36sery559/5qmnnmL27NkA3Lx5k6SkJMaMGcP06dNxcXFh48aNTJkyhXHjxvHee+/Rt29fGjduzP379x953JzAJ6AeT7/wDFM7fgJAiTKuuFVwJ7B2PwD+7/uRnKl5nIsHfzMwypxlxsz5zJg5n06dAvhw+EB69R5kdEg5xuuvt8HnxWo09G1rdCjZ0nPPVWTUmA/w9+sGwPXrNxg08CPmL/was9nM/n1HKFf+aYOjzN5KPFWcsdMCGTlgdJ7JPIp12NjZYefuQcKggdiWLInLV9OI79WT5Nu3Mt5ZJB0ZNjb27t3LqVOnaNeuHQD37t2jePHiGR7Y29ubmTNnEhsbS5MmTShbtmy65Ro0aEC+fPlwcXHBxcWF+Pj4TJ0zNDQUDw8PypUrB0Dr1q1ZtGjRIxsbf0fz5s2xtbWlbNmyeHp6cvHiRTw8PBg1ahS//fYbtra2lmzD3r17adOmDQUKFACgaNGH6e3AwECaN29Ov34pX4B3795NSEgImzdvBlIaB5cuXcLBwSHV+R+3LitVqsSECROYOHEiDRs2xMfHh7Nnz3L27Fl69uwJpGRWSpYsya1bt4iLi6Nx45TuD/nz5//H9fSkXY+7RtHSD//fi5Yqzu9xCWnKVXrZiyZvt2Fqx094kPgAgBeavkTY0XMk3rkPwJmdxyhXo1Kubmz0e6s7vXunjFk5dOgYHp4P7wy7e5QiKjo2U8ddujSIb6alP3YhN3jS9ebb6BWGDxtAI9+2luxqbhIdHZuqe5i7uxvR/1NH0dFxeLiXIjoqFjs7O5yLFCY+PuW1W9rdjR+WzKJvnyGEhj7MpgZv3E7wxu0A9OzV+ZEZ9NwgLuYKrqUfds9zLfUUl2OuPPb+BQs58c33k5k2fhYnjvyaFSFKLmW+ehXbpx7+7dmWLInp6tVUZUxXrpB05gyYTJhjY3kQGYGdhwcPQnLv56eRcu5t3seXYTeq5ORkWrduTVBQEEFBQWzevJl33nknwwP7+fkxY8YMHB0d6du3L3v37mXRokX4+/vj7+9PXFwckDJryR/s7Ox48OBBps/5KHZ2dpY7P/fv3//b+9vY2KRZnjdvHiVKlCAoKIiVK1eSlJSU4XGqV6/O/v37LTEkJyczcuRIy3X++OOP1KtXL81+6dVlesqVK8eqVauoVKkSX375JV9//TXJyclUrFjRco5169YxZ86cv10HRgg/foGSZd1w8SiJnYMdNfzqcnJr6u5uHs+XpdPYPvynz+fcir9hWZ8QfZUKtapga2eLrb0dz9R6jrjzkda+BKuaMXM+PjWb4FOzCWvXbqZrl5TGeq2XanDj9xvpjjF4lAoVyll+b/Havzh3PvSJx5tdPMl68/Z+nunfjKd1m55cuRKf8Q450OHDJ3imQlnKlPHAwcGBdu382LhhW6oyGzduo8sbKVmd1q2bs2tXynuWs3NhVq6cw8eBE9i373CqfUqWTLmxULRoEd7s+wbz5y21wtUY49djZyhT3hP3p0th72BPs4B/sXPLz4+1r72DPV/OncC65cFsXZ/7uulJ1kr67Tfs3D2wdXMDe3scGzXi/p7dqcrc/+UX8nl7A2BTxBl7D09MMdHpHU7ksWTY2KhTpw6bN28mPj7lg/P69etERWXcPzQiIgJPT0+6deuGr68vISEhdOnSxfKl19XVNVPntLe3T/eLfbly5YiKiuLSpUtAypiPmjVTBhO7u7tz6tQpALZs2WLZp2DBgty+fTvDa9m0aRNms5nw8HAiIiIoV64cN2/epGTJktja2hIUFGS5C1e3bl1WrVrF3bt3LbH/oV27djRo0ICBAwfy4MED6tWrx+LFiy3XExoayp07d9LElV5dpicuLo4CBQrg7+9P7969OX36NOXKlePatWuWgfBJSUmcO3eOQoUK4ebmxrZtKV8SEhMTLTFnF2aTmRWBc+i/4ENGbPuCo+v3EnsuktfebU/Vf70IgP/wN8jn5EjP6e8ydOME3vzP+wAc27iPq+FxDNs8iWHBnxN95hKntltn5rHsYGPwdi6GhhNyZjczZ37O2+98aNl26ODD18D4cSMIu3gIJ6cChF08ROBHgwHo368Hx4/9yKGDWxg0sG+e6UL1T+ttwriPKFSoIEsWz+LQwS2sXjXX6teQ1UwmE0MGf8yatQs4fHQrq1Zt4MyZc4z86F1ea/EvAObPW4qLSzGOn9zB2wP6EPjRBAD+/VZ3yj9ThmHDB7Bn3wb27NtgaWR8PjGQQ4e3sG37Cr6YNIPzubiBazKZGPvhZGYs/pKgnxezZe12LoSE0n/om7zaJOWG0/Pez7H1SBBN/Brx0ecfsGrXIgCatvKlRm1vWnV8jWXb5rNs23wqP593pqb+K+9/PJ4u/36XsPBIfAPeYOW6zUaHlP2YTdyc+iXFPp9E8XkLuL9jB6awMAr27EX+uikTOSQePID5xg2Kz51PsSlfcnPmDJJv3MjgwJJZycnJVv0xgk3yY5x548aNzJo1C7PZjIODA4GBgQwePJgVK1bg4uJC9erVOXr0KJGRkbz11lusX7+e2bNnExQUhL29PSVKlGDy5MmpuhRBygDxP4+ZaNmyJTNnzsTDwyPdc3p7ezNx4kR+/PFHqlSpwuTJk3nzzTcZM2YMrq6u7N27lwkTJmAymahatSqffvop+fLl49ChQ4wYMYKCBQtSq1YtTp06xcKFCwkNDWXAgAHY2try0Ucf4ePjk+bahw0bRr58+Th16hS3b99m2LBhNGzYkLCwMN555x1sbGx45ZVX+OGHHyxf6GfPns2aNWtwcHCgQYMGDB48mK5duzJ06FC8vLyYOnUqYWFhTJo0iS+//JIdO3aQnJxMsWLFmD59Oo6OjvTu3Zvr16/Tpk0bEhMTM6xLSBmz8fnnn2Nra4u9vT2ffPIJXl5enDlzhjFjxnDz5k1MJhPdu3enQ4cOhIWFERgYSEJCAg4ODnz11Vd4eno+8u9gQNmOGf2pyP+YHv2L0SFIHuJony/jQpJK+SKZmwAgrzt8apHRIeRI19r3NDqEHMl1xy6jQ8gyrZ/2s+r5Vodb/9EKj9XYyMuGDRvGq6++SrNmuXcaxselxsbfp8aGWJMaG3+fGhuZo8ZG5qixkTm5ubHh/3RLq54vKPyvH63w008/8dlnn2E2m2nfvj19+/ZNtX3u3LksX74cOzs7XFxcGDt2LO7uf/0AWz1BXEREREQkjzOZTIwaNYpvv/2WDRs2sH79es6fP5+qzHPPPcfKlStZt24dTZs2ZeLEiRkeN8PZqPKKGTNmsGnTplTrmjVrxvjx4w2K6NESEhLSnWVr3rx5FCv26OdQiIiIiEj2kZ1mozpx4gRlypSxdKlv0aIF27dvp0KFCpYytWvXtvzu7e3N2rVrMzyuGhv/1a9fP8uUtNldsWLF0n3WiIiIiIjIoyxdupSlSx/O9texY0c6dkzpJh8XF4eb28Oupa6urpw4ceKRx1qxYgX169fP8JxqbIiIiIiIGMDaT/X+c+PinwgKCuLUqVN8//33GZZVY0NEREREJI9zdXUlNvbhQ1rj4uLSfVTFnj17mDlzJt9//32q5+U9igaIi4iIiIgYwEyyVX/+ipeXF2FhYURERJCYmMiGDRto1KhRqjKnT58mMDCQGTNmULx48ce6RmU2RERERETyOHt7ewIDA+nTpw8mk4m2bdtSsWJFvvrqK6pWrYqvry+ff/45d+7cYeDAgQCUKlWKmTNn/vVxrRG8iIiIiIiklt0ed9egQQMaNGiQat0fDQtImfn071I3KhERERERyRLKbIiIiIiIGCA7PWcjqyizISIiIiIiWUKNDRERERERyRLqRiUiIiIiYgBrP9TPCMpsiIiIiIhIllBmQ0RERETEABk9aC83UGZDRERERESyhDIbIiIiIiIGyG4P9csKymyIiIiIiEiWUGZDRERERMQAGrMhIiIiIiKSScpsiIiIiIgYQM/ZEBERERERySRlNkREREREDGDWbFQiIiIiIiKZo8yGiIiIiIgBcn9eQ5kNERERERHJIspsiIiIiIgYQM/ZEBERERERySQ1NkREREREJEuoG5WIiIiIiAHUjUpERERERCSTlNkQERERETFAsh7qJyIiIiIikjnKbMhju2i+ZXQIOc77pRsYHUKOdBuT0SHkSNOjfzE6hBzn9LVwo0PIka6172l0CDmSy/K5Rocg2YzGbIiIiIiIiGSSMhsiIiIiIgZIVmZDREREREQkc5TZEBERERExgGajEhERERERySRlNkREREREDKDZqERERERERDJJmQ0REREREQNozIaIiIiIiEgmKbMhIiIiImIAjdkQERERERHJJDU2REREREQkS6gblYiIiIiIAZLVjUpERERERCRzlNkQERERETGAWVPfioiIiIiIZI4yGyIiIiIiBtCYDRERERERkUxSZkNERERExAAasyEiIiIiIpJJymyIiIiIiBhAYzZEREREREQySZkNEREREREDaMyGiIiIiIhIJimzISIiIiJiAI3ZEBERERERySRlNkREREREDKAxGyIiIiIiIpmkxoaIiIiIiGQJdaMSERERETGABoiLiIiIiIhkkjIbIiIiIiIGSE42Gx1CllNmQ0REREREsoQyGyIiIiIiBjDngTEbamzkENWrV+fo0aOPVXbatGk4OTnRu3fvLDm+kWo0eJG+n/TF1s6WLUu2sGL68lTbA/oE0KRzU0wPTNy49jtfvvclV6KuGBStcSo1eIGWgd2wtbPl4NId7JqxLtX2l7r4UqdrY8xmM4m377N6+LdcPh+FU9FCvD5jIB4vPMORFT+x9uN5xlyAQZ5rUI02gT2wtbNl79If2TYjKNX2hr1bUKdTI0wPTNy6doMfhs4kIeoqAK2GdeH5RtWxsbUl5OcTrPx0ngFXYIwpX4yiebNG3Ll7l9693+XosVNpyowe9QFvdGlHsWLOFHWpZFk/aGBfevXqzIMHD7h65Rp9+g4mPDzKmuEbJqN6K1DAkaWLZ1P+mTKYTCY2bNjKhyPGAdCtawcmjB9JVHQsANOnz2XO3MVWvwYj5av5EoXffgfsbLm7YQN3Fv+Qpkz+VxtSqHsPIJmkCxe4MWa01ePM7kaO/YKfdh/ApVhR1nw/0+hwJBdSNyrJMWxtbek3ph8fd/+Y/r79aNCqPp4VPVOVufDrRd5tMYh3mr7NLxt20/PDXgZFaxwbWxtajerJ3B6fM6Xx+1RrVZenKrinKnM8aA9fNRvGtNc+5KdZ62jx0RsAJN1PYuvkFWwcu8iI0A1lY2tD+1G9mNljHGMbD+bFVi/j9j/1Fnk6jIl+w5nQfCjHg/fjP7wLAOVqVKK8T2XGN3ufcU2G8HS1Z6hQu4oRl2F1zZs1omKFcjxbpR79+n3AN1+PS7fc+vVbqfNyizTrjx07Ra3azanxYmNWrtrA+HEjszrkbOFx6+2LKTOp6tUAn5pNqVunJs2aNrRsW7Z8LT41m+BTs0mea2hga0vhgYO4Pmwo8T264+jri12ZMqmK2Lm7U/D1Llx75/+I79mDm19PMyjY7C3gtcbM/GKM0WHkWcnJyVb9MYIaGznYjz/+SPv27QkICKBHjx5cvXrVsu23336jY8eONGnShGXLllnWf/vtt7Rt2xY/Pz+mTp1qRNiZVsm7EjFh0cSFx/Ig6QE/rfuJ2k1qpypzcu8J7t+7D0DI0d8oUaqEEaEaytO7AvGX4kiIuIwpycTxdXt5rsmLqcrcv3XX8ns+p/yWN6Cku/e5dCiEB/eTrBpzdlDGuwJXLsUR/996O7JuD15NaqYqc27vryTdSwQg7Og5iroVB1KmLnTI74C9gz32+Ryws7fj5pXfrX4NRvDza8rCRSsA2H/gCM5FnXFzeypNuf0HjhAbeznN+p279nD37r3/ljmMh3uprA04m3icert79x47d+0BICkpiSNHT+KeR+onIw7PPocpOgpTTAw8eMC9H38k/8v1UpUp0NKPu2tWk3zrFgDJ168bEWq25+PthXORwkaHIbmYulHlYC+++CLLli3DxsaG5cuX8+233zJs2DAAQkJCWLZsGXfu3KF169Y0aNCAc+fOcenSJVasWEFycjL9+vXj4MGD1KxZM4MzZQ/F3YpzJfphg+pqzFUqe1d+ZPkmHZtweMcha4SWrRRxLcbv0fGW5Rsx1/D0rpCmXO2ujanX5zXsHOz59vXPrBlitlTU1YXrf6q36zHxlEmn3v5Qu0NDTu88BkDYkXOc3fsrow/OwgYbflqwibgLeaMrkHtpNyIjoi3LUZExuJd2S7dhkZGePTqzafOOJxletvV3683ZuQgtWzRm2tffWda1af0ar7xSi3PnQhny3idERkanu29uZFuiBObLD+vKfOUKDs89l6qMnYcHAMWmfQ22ttyeN4/EgwesGqdIRjRmQ7K12NhY3n33Xa5cuUJiYiIe/31jBfD19cXR0RFHR0dq1arFyZMnOXz4MLt37yYgIACAO3fuEBYWlmMaG3/Hq60bUuGFigzr8IHRoWRb+xZuZd/CrVRrVZdG7wSwfIj66j4un4B6PP3CM0zt+AkAJcq44lbBncDa/QD4v+9HcqbmcS4e/M3AKHOW119vg8+L1Wjo29boULIdOzs7Fi38hq+/mUNoaDgA6zdsZcnSNSQmJvJmnzeY+92XNG7aweBIsxcbOzvs3D1IGDQQ25IlcflqGvG9epJ8+5bRoYnkKWps5GBjxoyhR48e+Pr6sn//fr7++mvLNhsbmzTlk5OT6du3L506dbJmmE9MfGw8JUs/7BZVolQJ4uPi05SrVs+bjm93ZFiHD3iQ+MCaIWYLN+IScC5d3LJcpJQLv8dde2T5E+v2EjAm741t+V/X465R9E/1VrRUcX6PS0hTrtLLXjR5uw1TO35i+ft6oelLhB09R+KdlC58Z3Yeo1yNSrm2sdHvre707p0yXuXQoWN4eJa2bHP3KGUZtPy4fBu9wvBhA2jk25bExMQnGmt2ktl6mznjc86dD2XqtG8t665de/i3+d2cHxg/bkQWRZ09ma9exfaph93ObEuWxPSnrsQApitXSDpzBkwmzLGxPIiMwM7DgwchufN1KTmTUeMorEljNnKwmzdv4urqCsCaNWtSbdu+fTv3798nISGBAwcO4OXlRb169Vi5ciW3b98GIC4ujvj4tF/Ws6uzx89Supw7rp6u2DvYU9+vPvu37k9Vpvzz5Xl73NuM7j2K3+PzRp/5/xV5/AIlyrpRzKMkdg52VPOrw5mth1OVKV7WzfJ75UbVuRr2974c5kbhxy9QsqwbLv+ttxp+dTm5NXU3PI/ny9JpbB/+0+dzbsXfsKxPiL5KhVpVsLWzxdbejmdqPUfc+UhrX4LVzJg53zIwee3azXTt0g6AWi/V4MbvN/5WFypv7+eZ/s14WrfpyZUrOef9KDMyU2+jPh2Ks3NhBg/5ONX6P4/v8PNrwm+/nc/a4LOZpN9+w87dA1s3N7C3x7FRI+7v2Z2qzP1ffiGftzcANkWcsffwxBSTd7qaiWQXymzkEHfv3qV+/fqW5Z49e/L2228zcOBAnJ2dqVWrFpGRD7/cVK5cmW7dupGQkED//v1xdXXF1dWVCxcuWDIbTk5OTJw4keLFi6c5X3ZkNpmZ+dEMRi0cja2dLVuXbiX8bDhdBr/BuZPnOLB1P71G9MbRyZFhM4YDcCX6CqN7jzI4cusym8ysDZxHrwXDsLGz5dCynVw+F8W/3m1H1MmLnNl2hDrdm1Dh5aqYHjzg7u+3WT5khmX/ob98Rf5CBbBzsKdKkxeZ03U8l8/n/vEHZpOZFYFz6L/gQ2ztbNm3bCex5yJ57d32hJ+8yKlth/Ef/gb5nBzpOf1dABKirvKfNydybOM+KtWtyrDNkyA5mTO7jnFq+xGDr8g6NgZvp1mzRoSc2c2du3fp02ewZduhg1vwqdkEgPHjRtCpY2ucnAoQdvEQc+b+wKjRXzBh3Ef8f3t3HhZlufcB/DvjOIjkXrgQqJlUB7RU8ujBOkZuqBCLqJWYS4ILhaakprmh4snjgocM1PdoeirUEAUUlPRVO5Z61MEFckFRVhFjFJR9mPcPX+ZIso7C/Tzw/VwX18U8j+m353pg5vfc9+++n3vODKE/hAAAUlLS4Oo2Ucj/S32qyXWzsOiIL+b74rfL1/Cf0wcB/HeJ2098JmHkyCEoKdFBm30Pkz6eKep/RYxSHXI3rEebr/4OKJUoiD4A3c2bMJs4CSVXLqPwl19Q9J/TUL/5Jtpt/Rb60lLkBn8DfU5O9X93I+O3eBX+o7mAe/dy8K7LOEyf7Al3p6GiYzUapY1gZEOhbwzjN/RMjLR6ctlKqloPZSvREWTpIXSiI8jSxvR/i45AjUSafeWLJ1Dl2u7eKjqCLDV9/iXREepMx9b1u0x6xr2Eev33AI5sEBEREREJoW8Eq1GxZ4OIiIiIiOoEiw0iIiIiIqoTnEZFRERERCRAY2id5sgGERERERHVCY5sEBEREREJUMoGcSIiIiIiIuNwZIOIiIiISMMo0pgAACAASURBVAD2bBARERERERmJIxtERERERAKUcmSDiIiIiIjIOBzZICIiIiISgD0bRERERERERuLIBhERERGRANxng4iIiIiIyEgc2SAiIiIiEoA9G0REREREREbiyAYRERERkQDcZ4OIiIiIiMhILDaIiIiIiKhOcBoVEREREZEAei59S0REREREZByObBARERERCcAGcSIiIiIiIiNxZIOIiIiISABu6kdERERERGQkjmwQEREREQnA1aiIiIiIiIiMxJENIiIiIiIB2LNBRERERERkJI5sEBEREREJwJENIiIiIiJqFI4fP46hQ4di8ODB2LRp0xPni4qKMHPmTAwePBgeHh5ITU2t9u9ksUFEREREJIC+nr+qotPpsGzZMmzZsgX79+9HVFQUEhMTy/2Z3bt3o2XLloiNjcWECRPw97//vdr/RxYbRERERESN3IULF9C5c2dYWlpCrVZjxIgROHz4cLk/c+TIEbi6ugIAhg4dil9//bXaqWDs2aAai0reLzoCEVVhg+gARERUKyVFafX67+3cuRM7d+40vB4zZgzGjBkDAMjMzESHDh0M59q3b48LFy6U++8zMzPRsWNHAIBKpUKLFi2g1WrRtm3bSv9NFhtERERERI3A48VFfeE0KiIiIiKiRq59+/a4ffu24XVmZibat2//xJ/JyMgAAJSUlCA3Nxdt2rSp8u9lsUFERERE1Mj16NEDN2/eREpKCoqKirB//344ODiU+zMODg4IDw8HABw8eBD9+vWDQqGo8u9V6BvDAr9ERERERFSlY8eOYeXKldDpdHB3d8e0adMQGBgIW1tbvPvuuygsLISfnx9+++03tGrVCuvWrYOlpWWVfyeLDSIiIiIiqhOcRkVERERERHWCxQYREREREdUJFhtERERERFQnWGwQEREREVGdYLFBspWXl4fS0lLD69LSUuTn5wtMJA+8blSfsrKycPjwYRw5cgRZWVmi40gefz6Nk5KSgsLCQsPrgoICpKamCkxERGVYbJBsTZgwodybcH5+PiZOnCgwkTzwutXeoUOHMGTIEPTp0we9e/dGr1690Lt3b9GxJG/37t3w8PBAbGwsDh48iDFjxuDHH38UHUvS+PNpHF9f33Jr/SuVSvj6+gpMJG1lv8PKfp+VvebvNqoLKtEBiIxVWFgIMzMzw2szMzM+AawBXrfaW716NYKDg9GtWzfRUWRly5YtCA8PN+wuq9VqMXbsWIwaNUpwMuniz6dxdDod1Gq14bVarUZxcbHARNKm0WhER6BGhCMbJFumpqaIj483vL506RKaNWsmMJE88LrVXrt27VhoGKFNmzZPfHAuKzyoYvz5NE7btm1x+PBhw+uffvqJ91oNnTlzBmFhYQCA7OxspKSkCE5EDQ039SPZunjxImbNmgVzc3Po9XrcvXsX69atg62trehoksbrVnvLly/H3bt3MWjQoHJPT4cMGSIwlXRt3boVAPDbb7/h6tWrePfdd6FQKHD48GG88sorWLVqleCE0nXhwgV89tln/PmspeTkZMyZMweZmZlQKBTo0KED/va3v6Fz586io0laUFAQLl26hKSkJBw8eBCZmZnw9fVFaGio6GjUgHAaFcmSTqfD2bNnER0djaSkJABA165d0bRpU8HJpI3XzTgPHz6EqakpTpw4Ue44i42KPXz4EABgZWUFKysrw/F3331XVCTZ6NmzJ38+jWBlZYVdu3YZ7r3HR9SocrGxsdi7dy9cXV0BAO3btzdcQ6JnhcUGyVKTJk0QFRWFCRMmwNraWnQc2eB1M05AQIDoCLLi4+MjOoJs5efnY+vWrUhPT8fy5ctx8+ZNJCUl4Z133hEdTdLu3r2LtWvX4s6dO9iyZQsSExOh0Wjg4eEhOpqkNW3aFAqFwtBcn5eXJzgRNUQsNki2evfujWXLlmH48OEwNTU1HLexsRGYSvp43Wpu8+bNmDJlCvz9/cutdFNm4cKFAlLJx8WLFxEcHIz09HSUlJQYjkdGRgpMJW3z58+HjY0N4uLiADx60uzr68tioxrz5s2Dm5sbgoODAQBdunTBrFmzWGxUw9HREYsWLUJOTg527dqFsLAwjB49WnQsamBYbJBs/fbbbwCAwMBAwzGFQoHt27eLiiQLvG41V9YUzvnyxpkzZw4+//xzWFtbQ6nkeiQ1kZycjPXr12P//v0AHjWMs7WyelqtFsOHD8emTZsAACqVivdcDUyePBknTpyAmZkZkpKS8Omnn8Le3l50LGpgWGyQbO3YsUN0BFnidas5BwcHADDMZ6baadu2Lfs0akmtVqOgoMAwkpacnFxuUQKqWPPmzaHVag3XLS4uDi1atBCcSh6sra0N9xyn11Jd4GpUJFuco2scXrfa43Qg4/z666+IiopC//79uYpXDZ04cQLffPMNEhMTYW9vD41Gg4CAAPz5z38WHU3S4uPj4e/vj2vXrqF79+7QarUIDAzEq6++KjqapO3evRtff/01+vXrB71ej//85z+YPn0698KhZ4rFBsnWxx9/bJijGxERgZKSEri6uvIDYDV43Wpv6NChFU4HsrCwEJhK+ubMmYMbN26ge/fu5a4bG+6rptVqcf78eej1erz++uto27at6EiyUFJSgqSkJOj1eq7iVUNDhw5FaGjoExtvHjx4UHAyakg4jYpki3N0jcPrVnucDmScixcv8kNLLZ09exavvfYaBg4ciH379iEkJATjx49nYVuN6OhovPXWW+jevTs2btyIhIQETJs2jQtfVIMbb1J94CcMki3O0TUOr1vtffrpp1iwYAGioqJw6NAhwxdVrXfv3khMTBQdQ1aWLFkCU1NTXL58Gdu2bYOVlRXmzp0rOpbkbdy4Ec899xzOnDmDX3/9FaNGjcKSJUtEx5KsrVu3YuvWrbCyssLo0aPxj3/8A0FBQRgzZgy6dOkiOh41MBzZINmaN28epk2bhuTkZIwdO9YwR5eqxutWe2FhYbhx4wZKSkrKjQKx96BqcXFxcHFxgYWFRbmeDU7Zq5xKpYJCocBPP/2EDz74AB4eHvjxxx9Fx5K8Jk2aAACOHTuG0aNHY+DAgVi/fr3gVNLFjTepPrFng2SNc3SNw+tWO0OHDuV0ICOkpaVVeLxsStD9+/fRqlWr+owkeePGjcNbb72FPXv24F//+hfatWuH9957jwVaNby9vdG+fXucOHEC4eHhaNasGUaNGoWIiAjR0YgaPRYbJFuFhYX4/vvvcfbsWSgUCvTp0wfvv/8+TExMREeTNF632ps/fz4mT56Ml19+WXSUBsXV1RXh4eGiY0hKVlYWoqKi0KNHD9jZ2SE9PR2nT5+Gi4uL6GiSlp+fj59//hnW1tbo0qUL7ty5g6tXr2LAgAEAWNhWJjs7G5s3b0ZiYiIKCwsNx7nvEj1LLDZItnx9fWFmZgZnZ2cAQFRUFHJycrBhwwbByaSN1632HB0dkZKSwulAz5iLiwv27t0rOoasjBkzBjt37hQdQ3ZY2FZs0qRJcHR0xD//+U8sXboU4eHhaNu2Lfz8/ERHowaEPRskW9euXcOBAwcMr/v164fhw4cLTCQPvG61t2XLlirP86mpccoWKaCae/zpM9Ucn6tW7N69e/Dw8MD27dvRt29f9O3bF+7u7qJjUQPD1ahItv70pz8hLi7O8Pr8+fOwtbUVmEgeeN1qz8LCosKvMhMmTBAXjhoVFmjG4XWrmEr16Jmzubk5jh49ioSEBNy/f19wKmpoOLJBshUfH4+xY8eiU6dOAID09HR07doVTk5OADjFpTK8bs8en5oah9eNSKxp06YhNzcXc+fOhb+/Px4+fIgvvvhCdCxqYFhskGxxaotxeN2ePT41rdyZM2dw69YtuLu7Izs7Gw8fPoSlpSUAYNu2bWLDyRALNOPwulXsnXfeAQC0aNECO3bsAMCfS3r22CBODRYbAo3D61Z7vGYVCwoKwqVLl5CUlISDBw8iMzMTvr6+CA0NFR1NsvLy8tCsWTMolUokJSXhxo0bePvttw3LU1+9ehXW1taCU0pPcnIyOnToALVajVOnTuHKlStwcXFBy5YtATzqTWjdurXglPIwcOBAHD16VHQMakDYs0ENFuto4/C61R6vWcViY2PxzTffwNTUFADQvn17w2ZiVLFx48ahsLAQmZmZmDx5Mvbt24d58+YZzrPQqNgnn3wCpVKJW7duYdGiRcjIyMDs2bMN51lo1Bx/n9GzxmKDGixObTEOr1vNPP6hmdMOKta0aVMoFArDPZWXlyc4kfTp9XqYmpri0KFDeP/997FhwwYkJiaKjiV5SqUSKpUKsbGxGDduHObOnYusrCzRsWSJ7wH0rLFng4jICCNGjDBMNeBT04o5Ojpi0aJFyMnJwa5duxAWFobRo0eLjiVper0eGo0GkZGRWLFiBQCgtLRUcCrpU6lUiIqKwt69e/HNN98AAEpKSgSnkq5evXpVWFTo9Xour0zPHIsNarA4FGwcXrf/2rp1a4XH9Xo9n9LXwOTJk3HixAmYmZkhKSkJn376Kezt7UXHkrQvvvgCISEhGDRoELp3746UlBT8+c9/Fh1L8gICAhAaGoqpU6fC0tISKSkpho1L6UkajUZ0BGpE2CBOsnb//n1kZGRAp9MZjtnY2ABgQ2Bl/Pz8sHr16kqP8br9V48ePTB58mTDWvSP27ZtG86cOSMglbykpaXh1q1b+Mtf/oL8/HzodDo899xzomNJXn5+vqHXhar37bff4qOPPqr2GBHVP45skGytX78e4eHhsLKyMhxTKBTYvn07AE5tqcwf53/rdDrEx8cbXvO6/ZeNjQ0GDRpU4aaHu3fvFpBIXnbt2oWdO3fi/v37+Omnn5CZmYnFixfj22+/FR1NsjQaDRYsWIC8vDwcPXoUly9fRmhoKJYsWSI6mqTt3bv3icIiPDycxQaRBLDYINmKjo5GbGws1Gq16CiyEBISguDgYBQWFqJ3794AHk0HUqvVnEdfiZUrV1ZafIWFhdVzGvn57rvvsHv3bsP91aVLF2RnZwtOJW0rV67E//zP/2DatGkAgFdffZUjaFWIiopCVFQUUlNTMXXqVMPxhw8fcr8gIolgsUGyZW1tjdzcXLRr1050FFnw9vaGt7c31qxZU25JSKrcSy+9VOm5559/3vC9v78/vvzyy/qIJCtqtbrcwwA27NZMx44dy71WKrlwZGV69eqFF154AVqtFpMmTTIcNzMzwyuvvCIwGRGVYbFBsuXl5QUXFxdYW1sbNrwCgODgYIGppOv69evo1q0bhg0bVm7aVJmyXheqvXPnzomOIElvvvkmgoODUVBQgBMnTuD777+Hg4OD6FiS1rFjR5w7dw4KhQLFxcXYvn07unXrJjqWZFlYWMDCwgI7d+4s1x9UUFCAgoIC9gcRSQAbxEm2RowYgTFjxsDa2rrck7++ffsKTCVdX375Jfz9/eHp6fnEucd7Xaj2uIN4xfR6PXbv3o1///vfAIABAwbAw8OD6/hXITs7GytWrMCvv/4KvV4Pe3t7LFy4kL1U1fhjf9DNmzfZH0QkERzZINlq1qwZxo8fLzqGbPj7+wMAduzYITgJNQY6nQ4jRoxATEwMe4JqISkpCWvWrCl37OzZs+jTp4+gRPLA/iAi6WKxQbJlZ2eHNWvWwMHBody8cE4Hqt7Vq1eRmJiIoqIiwzEXFxeBieSNA8RPatKkCbp27Yr09HR06tRJdBzZWL58+ROjZBUdo/LYH0QkXSw2SLYSEhIAAHFxcYZjnA5UvaCgIJw6dQrXr1/HX//6Vxw/fhx9+vRhsfEUOMJWsZycHIwYMQI9e/Yst2cE+6qepNFooNFokJ2dXW4zyQcPHpTbR4gqxv4gIulizwZRI+Pk5IR9+/bBxcUFERERuHv3Lvz8/CrdLZtQbknNMi1atICtrS3Gjh0LExMTAamkq6ioCGq1GqdPn67wPPuqnnT69GmcPn0aoaGhGDt2rOG4mZkZ3nnnHXTp0kVcOBkoLS3Fjz/+WK4/iNP3iKSBIxskW3fv3sXatWtx584dbNmyBYmJidBoNPDw8BAdTdJMTEygVCqhUqnw4MEDtGvXDhkZGaJjSdqLL74IrVaLESNGAAAOHDgAMzMz3Lx5EwsXLnxiR/bGbsyYMQgPD8fu3bt5bWqob9++6Nu3LwYNGoRXX31VdBzZ+cc//gFfX19DgaHT6TB79uwn+l+IqP6x2CDZmjdvHtzc3AxTMrp06YJZs2ax2KiGra0tcnJy4OHhATc3NzRv3hy9evUSHUvSNBpNuU38HBwc4O7ujrCwMEMBQv9VXFyMyMhIaDQaHDp06InzQ4YMEZBKHpYtW4aioiK4urrC2dkZLVq0EB1JFm7fvo2QkBB4e3ujqKgIM2fOxGuvvSY6FhGBxQbJmFarxfDhw7Fp0yYAgEql4uZXNbBkyRIAwPvvv4+33noLDx484JPUauTl5ZVrdE5PT0deXh4AlNvjhR5ZsmQJIiMjkZubi//93/994jyLjcp9//33SEpKwp49e+Dm5oaePXvCzc0N9vb2oqNJ2sqVKzFnzhyEhITg1KlTePvttzFhwgTRsYgILDZIxpo3bw6tVmtYsz8uLo5PAWvAz88Pb775Jvr06cPNwmpo3rx5+OCDD2BpaQkASE1NxeLFi5GXl8fG+grY2dnBzs4Otra2HGk0QteuXTFz5kzY2tpi+fLlSEhIgF6vx2effcZC7Q8e36B0/PjxWLRoEXr37o0333wT8fHxXJ2QSALYIE6yFR8fD39/f1y7dg3du3eHVqtFYGAgn9JX4+TJkzhz5gzOnj2L5ORk/OlPf4KdnR0++ugj0dEkraioCDdu3ADw6MMgm8KNk5WVhRdeeEF0DMm6fPky9uzZg2PHjuEvf/kLRo0aBRsbG2RmZmLs2LEVjhQ1ZhVtUlqGqxMSSQOLDZKtoqIiKJVKJCUlQa/Xo2vXrtDr9eXWWqeK6XQ6XLx4EadOnUJoaChMTEwQExMjOpZkOTk5YeTIkXB0dISVlZXoOLLm5eVlmPpITxo3bhxGjRqFYcOGoVmzZuXO7d27lyNpRCQ7LDZItlxdXZ/Y6KqiY1TeRx99hPz8fLzxxhuws7NDnz590K5dO9GxJC0tLQ0HDhxAdHQ0FAoFhg8fDkdHR25WR3WibBRNoVCga9eufIBSA2vXrsXHH3+Mli1bAgDu37+Pf/7zn5g1a5bgZETEblqSnaysLFy6dAkFBQVISEhAfHw84uPjcerUKeTn54uOJ3mvvPIKmjZtimvXruHKlSu4evUqCgoKRMeSNAsLC0yZMgV79uzBmjVrcOXKFbz77ruiY8nC/fv3cfnyZcPP6eNz7OlJx44dw+DBg7FixQr4+/tjyJAhOHbsmOhYknf8+HFDoQEArVq1wvHjxwUmIqIybBAn2fn3v/+NPXv24Pbt21i1ahXKBufMzMzw2WefCU4nfV988QWARzsTh4eH44svvjAUcFS5x0c3lEol/Pz8REeSvPXr1yM8PLzc1DPOo69aQEAAtm/fjs6dOwMAkpOT4eXlhb/+9a+Ck0mbTqczbCYJAAUFBSgqKhKciogAFhskQ66urnB1dcXBgwcxdOhQ0XFk51//+hfOnDmD+Ph4WFhYwN3dHX369BEdS9I8PDxQUlKCYcOGITAw0LAqFVUtOjoasbGxnAZUC2ZmZoZCAwAsLS1hZmYmMJE8ODk54aOPPoKbmxsAYM+ePexvIZIIFhskW7dv38aDBw9gZmaGhQsXIiEhAbNnz8aAAQNER5O0wsJCTJw4ETY2NlCp+CugJv72t7/hpZdeEh1DdqytrZGbm8ueoBoo2/zQ1tYWU6ZMgaOjIxQKBWJiYtCjRw/B6aTPy8sLr7zyCk6ePAkAmD59Ot566y3BqYgIYIM4yZizszMiIiLw888/IzQ0FDNnzsTnn3/OBnGqE0ePHsW1a9dQWFhoOObj4yMwkfRdvHgR06dPh7W1dbnND4ODgwWmkqb58+dXeT4gIKCekhARPVt8rEmyVVYnHzt2DC4uLujevTtYOxvH29sbISEhomNI1qJFi1BQUIBTp07Bw8MDBw8e5NPmGpg3bx6mTJkCa2trKJVcj6QqNS0mQkJC4O3tXcdp5CcuLg7+/v64ceMGiouLodPpYGpqinPnzomORtTo8bc/yZatrS0mTZqE48ePY8CAAXjw4AE/0BjJ399fdARJ02g0+Oqrr9CyZUv4+PggNDQUN2/eFB1L8po1a4bx48ejX79+6Nu3r+GLjMf9cCq2bNkyrF27Fp07d8b58+exfPlyfPjhh6JjERE4skEytmLFCvz222+wtLSEqakptFotVq5cKTqWLJmbm4uOIGllm6uZmpoiMzMTbdq0QVZWluBU0mdnZ4c1a9bAwcGhXJO4jY2NwFTyxtHbynXu3Bk6nQ5NmjSBu7s7XFxcMHv2bNGxiBo9FhskW76+vnB3d8drr70GAGjTpg3atGkjOJX0OTg4QKFQPHH88OHDAtLIw8CBA5GTk4PJkyfDzc0NCoUCHh4eomNJXkJCAoBHU1zKcOnbp1PRzy49ehBQVFSE1157DV999RXMzc1RWloqOhYRgQ3iJGO//PILwsLCcP78eQwbNgxubm5cMagGtFqt4fuioiJER0fj/v378PX1FZhKPoqKilBYWIgWLVqIjkKNkIuLC/bu3Ss6huSkpaXh+eefR3FxMbZt24bc3Fx88MEH5ZYRJiIxWGyQ7OXm5iIqKgrBwcHo2LEjPDw84OzsXG71G6qam5sb9uzZIzqGrGRlZeGFF14QHUPS7t69i7Vr1+LOnTvYsmULEhMTodFoOCr0FIKDgzF16lTRMSSpqKgIN27cgEKhQNeuXbm/C5FEsNggWdNqtYiIiMC+fftgbm4OZ2dnnD17FlevXsWOHTtEx5Ok+Ph4w/elpaW4dOkSfvjhB0RERAhMJT9eXl7YtGmT6BiS9vHHH8PNzQ3BwcGIiIhASUkJXF1dERkZKTqaZGVnZ2PXrl1IS0tDSUmJ4TiXvq3a0aNHsXjxYlhZWUGv1yM1NRVLly7lzutEEsCeDZKtGTNmICkpCe+99x6Cg4MNTc7Dhw837CJLT1q1apXhe5VKBQsLC6xfv15gInlioVE9rVaL4cOHG66VSqXiinHVmD59Ovr06YP+/fujSZMmouPIxqpVq7B9+3bDtKnk5GR4eXmx2CCSABYbJFuenp7o169fhec4JahyHPGpuXv37lV5vnXr1vWURJ6aN28OrVZraGqOi4tjr0s18vPz4efnJzqG7JiZmZXrz7C0tISZmZnARERUhsUGyZZWq8WDBw/w3HPPYePGjUhISMC0adO4rGY1tFotvv76a5w9exYKhQK9e/fGjBkzuJJXBcpWntLr9cjIyEDLli0BADk5OejYsSOOHDkiOKG0zZs3D9OmTUNycjLGjh0LrVaLwMBA0bEkbeDAgTh27BifyNeSra0tpkyZAkdHRygUCsTExKBHjx44dOgQAGDIkCGCExI1XuzZINlycnJCZGQkzpw5g8DAQEyePBlff/01du/eLTqapE2cOBF2dnZwdnYGAERGRuL06dPYtm2b2GAStnDhQgwePNjwAfDYsWM4fPgwli1bJjiZ9JWUlCApKQl6vR5du3blwg3V6NWrF/Lz86FWq6FSqaDX66FQKLgTdjXmz59f5Xn2vBCJw2KDZKtsCcg1a9bA2toaTk5OXBayBkaOHImoqKhyx8oKN6pYRdeH16x6Op0OR48eRVpaGnQ6neH4xIkTBaaixigkJATe3t6iYxA1SpxGRbLVvn17LFq0CCdOnMCUKVNQVFTETZxqwN7eHvv374ejoyMAICYmBgMGDBCcStrMzc2xcePGcqNB3HW9elOnToWJiQmsra3ZGF6N69evo1u3buVWi3scp4c+nZiYGBYbRIJwZINkKz8/Hz///DOsra3RpUsX3LlzB1evXuUH52qUTdMoW+lGp9PB1NQUADhdoxL37t1DUFAQzpw5AwCws7ODj48PG8SrwdGfmvvyyy/h7+8PT0/PJ85x1/Wnx1FvInFYbBARUZ1YvXo1+vfvzwcAJJyrqyvCw8NFxyBqlDiNihoUb29vhISEiI4habGxsejXr59hCdKcnBycPn0agwYNEpxMurKzs7F582YkJiaisLDQcJxPm6v2xhtvwMfHB6WlpWx2fgrcrf7p8bkqkTicREsNir+/v+gIkhcUFFRur4OWLVsiKChIYCLpmzNnDl566SWkpqbCx8cHFhYW6NGjh+hYkhcQEIDQ0FCcP38e586dg0ajYaFhhAULFoiOIHlnz56t8tiwYcPqMw4RPYbFBjUobNqtXkVN9I+vFERPunfvHjw8PKBSqdC3b18EBATg5MmTomNJXseOHWFtbW3Y1I+Mw93qq7d8+fIqj02dOrU+4xDRYziNimTLwcGhwg8xhw8fFpBGPmxtbREQEIAPP/wQAPDdd99xpZtqqFSPflWam5vj6NGjMDc3x/379wWnkj5LS0t4enri7bffhlqtNhzn0reV8/Pzw+rVq6s9Ro9oNBpoNBpkZ2dj69athuMPHjzgQxQiiWCxQbIVFhZm+L6oqAjR0dH8AFgDX375JTZu3IiZM2dCoVDA3t4eixYtEh1L0qZNm4bc3FzMnTsX/v7+ePjwYbWbiBHw4osv4sUXX0RxcTGKi4tFx5GFxMTEcq91Ol2ly+ESUFxcjLy8POh0Ojx8+NBw/LnnnsOGDRsEJiOiMlyNihoUNzc37NmzR3QM2bhz5w6nnlG9YJNz1UJCQhAcHIzCwkI0a9bM0NCsVqsxevRozJ49W3BCaUtLS4OFhYXoGERUARYbJFuPP+0rLS3FpUuX8MMPPyAiIkJgKnnhcpA1c/v2bfj7++Ps2bNQKBSws7PDggUL0KFDB9HRZIP3Ws2sWbOGhYURPD09K5xWyxXjiMTjNCqSrVWrVhm+V6lUsLCwweXvFwAAC39JREFUwPr16wUmkh8+a6iZ+fPnY+TIkQgMDAQAREREYP78+eXmiFPVeK/VzKxZs7Bv3z6kpqZixowZyMjIQFZWFnr27Ck6mqTNnTvX8H1hYSEOHTpk2LiUiMRisUGytWPHDtERZM/Dw0N0BFnIzs6Gu7u74bWbmxu+/fZbgYnkh/dazSxduhRKpRInT57EjBkz0Lx5cyxdurRcjxo9ydbWttzrPn36YNSoUYLSENHjuPQtyZZWq8Xy5cvh6uoKNzc3LF++HFqtVnQsyUtOTkZRUREA4OWXX8b27duRk5MjOJW0tW7dGvv27YNOp4NOp8O+ffvQunVr0bEkj/da7V24cAGLFy+GiYkJAKBVq1Zsrq+Be/fuGb6ys7Px888/Izc3V3QsIgKLDZKxzz77DG3atMGGDRsQGBiItm3bYtasWaJjSd4nn3wCpVKJW7duYdGiRcjIyOAc8WqsXLkS0dHRsLe3x4ABA3Dw4EEEBASIjiV5vNdqT6VSQafTGfoPsrOzoVTyrbo6bm5ucHd3h5ubG8aOHYutW7dixYoVomMRETiNimQsKysLM2bMMLyePn06oqOjBSaSB6VSCZVKhdjYWIwbNw6enp5wcXERHUvSLCwsEBwcLDqG7PBeqz1PT0/MmDEDv//+O9atW4eYmBjMnDlTdCzJO3LkiOgIRFQJFhskW/b29ti/fz8cHR0BADExMRgwYIDgVNKnUqkQFRWFvXv34ptvvgEAlJSUCE4lTf7+/lXufr1w4cJ6TCM/vNdqz9nZGTY2Njh58iT0ej02btyIbt26iY4lecXFxfjhhx9w5swZAEDfvn0xZswYNG3aVHAyIuLStyRbvXr1Qn5+vmHFEZ1OB1NTUwCAQqHAuXPnRMaTrMTERISGhuKNN97AyJEjkZKSgujoaHh5eYmOJjnVLdXq6upaT0nkifeacXQ6He7evVtuB+xOnToJTCR9CxYsQElJiWHkLCIiAkqlklOpiCSAxQYRUS1wczqqSzt27EBQUBCef/75cr0akZGRAlNJn7Oz8xN7LFV0jIjqH6dRkWzFxsaiX79+aNGiBQAgJycHp0+fxqBBgwQnkyZfX18EBgbCycmpwvP8MFMzXl5e3JyuGrzXjLd9+3bExMSgTZs2oqPISpMmTZCcnAwrKysAQEpKCvfZIJIIFhskW0FBQRg8eLDhdcuWLREUFMRioxILFiwAADY6PyUOBleP95rxOnToYHiAQjX3+eefY/z48bC0tIRer0d6ejpWrlwpOhYRgcUGyVhpaekTxx6f40zlmZubA3i0shIZj5vTVY/3mvEsLS3h6emJgQMHQq1WG45PnDhRYCrp69+/Pw4dOoQbN24AAF566aVy14+IxGGxQbJla2uLgIAAfPjhhwCA7777DjY2NoJTSVevXr0qXFlJr9ezob4aycnJ6NChA9RqtWFzOhcXF7Rs2VJ0NEnivWa8Tp06oVOnTiguLuZmfrWkVqvx6quvGl6zv4pIGtggTrKVl5eHjRs34pdffoFCoYC9vT2mTp2K5s2bi45GDcx7772HsLAwpKWlwcvLCw4ODkhMTMTmzZtFR6MGjB+Wn46Xlxc2bdokOgZRo8digxqEO3fuGKZuUMXu3btX5fnWrVvXUxL5cXV1RXh4OLZs2QITExPD5nR79+4VHU2SeK89G2X3HRGRnHEaFTUI3t7efFOuhpubGxQKhWEqC/DfZmeFQoHDhw+LjCdp3JyudnivPRt8Flhzfn5+WL16dbXHiKj+sdigBoFvytU7cuQIgEeN9REREUhNTYWPjw/S09ORlZUlOJ20BQQEIDQ0FFOnToWlpSVSUlLg7OwsOpZk8V57NrgYQc0lJiaWe63T6RAfHy8oDRE9jtOoqEH47rvvDI3iVLXFixdDqVTi5MmTiI6Oxv379zFp0iSEhYWJjkYNDO+12nt8MYJTp07hypUrXIygCiEhIQgODkZhYSGaNWtmePCkVqsxevRozJ49W3BCIlJW/0eIpCk5ORlFRUUAYFghKCcnR3Aq6btw4QIWL14MExMTAECrVq246k0lfH19AQBOTk4VflHVeK/V3ieffAKlUolbt25h0aJFyMjI4AfmKnh7e0Oj0WDy5Mk4d+4cNBoNNBoNTp06xetGJBGcRkWy9cknnyAsLMzwpuzg4IDZs2dzhaBqqFQq6HQ6w1z67OxsKJV87lARbk73dHiv1Z5SqYRKpUJsbCzGjRtnWIyAqjZr1izs27cPqampmDFjBjIyMpCVlYWePXuKjkbU6PG3PsnWH9+U586dy/ngNeDp6YkZM2bg999/x7p16/D+++/D29tbdCxJenxzuoq+qGq812rv8cUIBg4cCICLEdTE0qVLERcXh6ioKABA8+bNsXTpUsGpiAjgyAbJGFcIMo6zszNsbGxw8uRJ6PV6bNy4Ed26dRMdS5K4Od3T4b1We1yMwDgXLlxAeHi4YRSIU/aIpIPFBskW35SN161bN37oqwGNRiM6guzxXqudl19+GQsXLjS8trS0hJeXl8BE8sApe0TSxdWoiIgqwc3pqL74+voiMDCw0oUHIiMj6zmRvERERODAgQNISEiAq6srYmJiMHPmTDg6OoqORtTosdgg2eGbMtUXBwcHbk5H9eLOnTswNzdHWlpahefZI1S969evG6bs9e/fnyNqRBLBYoNkh2/KVN8q25zu9ddfFx2NiP6fTqfD3bt3odPpDMc6deokMBERASw2iIiqxc3pqK5xMYKns2PHDgQFBeH5558v16vBkW4i8dggTrLDN2Wqb1zphuoaFyN4Otu3b0dMTAzatGkjOgoR/QGLDZIdvilTfeNKN1TXuBjB0+nQoQNatGghOgYRVYDFBskO35Spvv1xc7qylW6InhU3NzcuRvAULC0t4enpiYEDB0KtVhuOT5w4UWAqIgLYs0EyxBWCSASudEP1gYsRGCcoKKjC4z4+PvWchIj+iMUGyRbflImooeFiBE8vKysLL7zwgugYRPT/OOmYZGvp0qU4f/489u/fDwAwMzPDsmXLBKciIjLehQsXsHjxYpiYmADgYgTG4I7rRNLCYoNki2/KRNTQcDGCp8cJG0TSwgZxki2+KRNRQ8PFCJ6eh4eH6AhE9Bj2bJBsRURE4MCBA0hISICrq6vhTdnR0VF0NCIio3ExgtpLTk5Ghw4doFarcerUKVy5cgUuLi5o2bKl6GhEjR6LDZI1vikTEdF7772HsLAwpKWlwcvLCw4ODkhMTMTmzZtFRyNq9DiNimStW7duLDCIiBo5pVIJlUqF2NhYjBs3Dp6ennBxcREdi4jABnEiIiKSOZVKhaioKOzduxcDBw4EAJSUlIgNRUQAWGwQERGRzAUEBCAuLg5Tp06FpaUlUlJS4OzsLDoWEYE9G0REREREVEfYs0FERESy5Ovri8DAQDg5OVV4PjIysp4TEdEfcWSDiIiIZOnOnTswNzdHWlpahectLCzqORER/RGLDSIiIiIiqhOcRkVERESy1KtXLygUiieO6/V6KBQKnDt3TkAqInocRzaIiIiIiKhOcGSDiIiIZOnevXtVnm/dunU9JSGiynBkg4iIiGTJwcEBCoXCMG0KeDSFCgAUCgUOHz4sMh4RgcUGERERyVxpaSkiIiKQmpoKHx8fpKenIysrC6+//rroaESNHncQJyIiIllbunQpzp8/j/379wMAzMzMsGzZMsGpiAhgsUFEREQyd+HCBSxevBgmJiYAgFatWqG4uFhwKiICWGwQERGRzKlUKuh0OkPfRnZ2NpRKfsQhkgKuRkVERESy5unpiRkzZuD333/HunXrEBMTg5kzZ4qORURggzgRERE1ANevX8fJkyeh1+vRv39/dOvWTXQkIgKLDSIiIiIiqiOc0EhERERERHWCxQYREREREdUJFhtERERERFQnWGwQEREREVGd+D/GK44FtmZSzAAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "rkYwyKtXMvpy",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "f5386858-2a38-4b20-9be9-f841ee5af0d6"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "5oQK-ddinvCM",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "outputId": "a611220f-df65-4d99-9c8f-dc0dd715f93f"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "qbqn755fo81g",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "outputId": "8750fe62-a1e7-40ca-a3c1-4285546f97ff"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fd5476b2bd0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fd54764c5d0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fd5471169d0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7fd54747cd10>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 14
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "xf8WCiykpUzN",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "b43752ab-2ff0-4e21-a4bc-633cd0aff7dd"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Z0CivgkitfgE",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "614149cc-6746-4d02-a608-2957cef79338"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "VBdr2epGu3aq",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "f9dc4c4f-ccfa-4379-add5-cd732dc8a310"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "81S0BbNa7Rce"
-      },
-      "source": [
-        "import tensorflow as tf\n",
-        "from keras.layers import Activation, Dense, Dropout,Permute,Reshape,Lambda,dot,concatenate\n",
-        "\n",
-        "INPUT_DIM = 100\n",
-        "TIME_STEPS = 20\n",
-        "# if True, the attention vector is shared across the input_dimensions where the attention is applied.\n",
-        "SINGLE_ATTENTION_VECTOR = True\n",
-        "APPLY_ATTENTION_BEFORE_LSTM = False\n",
-        "\n",
-        "ATTENTION_SIZE = 128\n",
-        "\n",
-        "def attention_3d_block(hidden_states):\n",
-        "    # hidden_states.shape = (batch_size, time_steps, hidden_size)\n",
-        "    hidden_size = int(hidden_states.shape[2])\n",
-        "    # _t stands for transpose\n",
-        "    hidden_states_t =  Permute((2, 1), name='attention_input_t')(hidden_states)\n",
-        "    # hidden_states_t.shape = (batch_size, hidden_size, time_steps)\n",
-        "    # this line is not useful. It's just to know which dimension is what.\n",
-        "    hidden_states_t = Reshape((hidden_size, TIME_STEPS), name='attention_input_reshape')(hidden_states_t)\n",
-        "    # Inside dense layer\n",
-        "    # a (batch_size, hidden_size, time_steps) dot W (time_steps, time_steps) => (batch_size, hidden_size, time_steps)\n",
-        "    # W is the trainable weight matrix of attention\n",
-        "    # Luong's multiplicative style score\n",
-        "    score_first_part = Dense(TIME_STEPS, use_bias=False, name='attention_score_vec')(hidden_states_t)\n",
-        "    score_first_part_t = Permute((2, 1), name='attention_score_vec_t')(score_first_part)\n",
-        "    #            score_first_part_t         dot        last_hidden_state     => attention_weights\n",
-        "    # (batch_size, time_steps, hidden_size) dot (batch_size, hidden_size, 1) => (batch_size, time_steps, 1)\n",
-        "    h_t = Lambda(lambda x: x[:, :, -1], output_shape=(hidden_size, 1), name='last_hidden_state')(hidden_states_t)\n",
-        "    score = dot([score_first_part_t, h_t], [2, 1], name='attention_score')\n",
-        "    attention_weights = Activation('softmax', name='attention_weight')(score)\n",
-        "    # if SINGLE_ATTENTION_VECTOR:\n",
-        "    #     a = Lambda(lambda x: K.mean(x, axis=1), name='dim_reduction')(a)\n",
-        "    #     a = RepeatVector(hidden_size)(a)\n",
-        "    # (batch_size, hidden_size, time_steps) dot (batch_size, time_steps, 1) => (batch_size, hidden_size, 1)\n",
-        "    context_vector = dot([hidden_states_t, attention_weights], [2, 1], name='context_vector')\n",
-        "    context_vector = Reshape((hidden_size,))(context_vector)\n",
-        "    h_t = Reshape((hidden_size,))(h_t)\n",
-        "    pre_activation = concatenate([context_vector, h_t], name='attention_output')\n",
-        "    attention_vector = Dense(ATTENTION_SIZE, use_bias=False, activation='tanh', name='attention_vector')(pre_activation)\n",
-        "    return attention_vector"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1cKtTAzqyiyL",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "e1863cec-a19f-4419-fe8c-527e549bccdf"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "from keras.layers import Input, LSTM, merge ,Conv1D,Dropout,Bidirectional,Multiply,Flatten\n",
-        "from keras.models import Model\n",
-        "from keras.utils.vis_utils import plot_model\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "TIME_STEPS=120\n",
-        "INPUT_DIMS=4\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "inputs = Input(shape=(120, 4))\n",
-        "lstm_units = 32\n",
-        "lstm_out = LSTM(lstm_units, return_sequences=True)(inputs)\n",
-        "lstm_out=tf.keras.layers.Dropout(0.6)(lstm_out)\n",
-        "attention_mul = attention_3d_block(lstm_out)\n",
-        "#attention_mul = Flatten()(attention_mul)\n",
-        "attention_mul=tf.keras.layers.Dropout(0.6)(attention_mul)\n",
-        "output = Dense(1, activation='sigmoid')(attention_mul)\n",
-        "\n",
-        "single_step_model = Model(inputs, output)\n",
-        "\n",
-        "  \n",
-        "single_step_model.summary()\n",
-        "\n",
-        "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/LSTM-Attention-B.png', show_shapes=True, show_layer_names=True)\n",
-        "\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "\n",
-        " "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Model: \"model_1\"\n",
-            "__________________________________________________________________________________________________\n",
-            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
-            "==================================================================================================\n",
-            "input_2 (InputLayer)            [(None, 120, 4)]     0                                            \n",
-            "__________________________________________________________________________________________________\n",
-            "lstm_1 (LSTM)                   (None, 120, 32)      4736        input_2[0][0]                    \n",
-            "__________________________________________________________________________________________________\n",
-            "dropout_2 (Dropout)             (None, 120, 32)      0           lstm_1[0][0]                     \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_input_t (Permute)     (None, 32, 120)      0           dropout_2[0][0]                  \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_input_reshape (Reshap (None, 32, 120)      0           attention_input_t[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score_vec (Dense)     (None, 32, 120)      14400       attention_input_reshape[0][0]    \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score_vec_t (Permute) (None, 120, 32)      0           attention_score_vec[0][0]        \n",
-            "__________________________________________________________________________________________________\n",
-            "last_hidden_state (Lambda)      (None, 32)           0           attention_input_reshape[0][0]    \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score (Dot)           (None, 120)          0           attention_score_vec_t[0][0]      \n",
-            "                                                                 last_hidden_state[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_weight (Activation)   (None, 120)          0           attention_score[0][0]            \n",
-            "__________________________________________________________________________________________________\n",
-            "context_vector (Dot)            (None, 32)           0           attention_input_reshape[0][0]    \n",
-            "                                                                 attention_weight[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "reshape_2 (Reshape)             (None, 32)           0           context_vector[0][0]             \n",
-            "__________________________________________________________________________________________________\n",
-            "reshape_3 (Reshape)             (None, 32)           0           last_hidden_state[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_output (Concatenate)  (None, 64)           0           reshape_2[0][0]                  \n",
-            "                                                                 reshape_3[0][0]                  \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_vector (Dense)        (None, 128)          8192        attention_output[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "dropout_3 (Dropout)             (None, 128)          0           attention_vector[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "dense_1 (Dense)                 (None, 1)            129         dropout_3[0][0]                  \n",
-            "==================================================================================================\n",
-            "Total params: 27,457\n",
-            "Trainable params: 27,457\n",
-            "Non-trainable params: 0\n",
-            "__________________________________________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "94000u5xIjWD",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "c3f7f857-fbb7-4fc5-b2bf-d860a828d0a9"
-      },
-      "source": [
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 10s 50ms/step - loss: 0.6677 - rmse: 0.6899 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5433 - rmse: 0.5433 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5432 - rmse: 0.5432 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 2s 41ms/step - loss: 0.5432 - rmse: 0.5432 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5432 - rmse: 0.5432 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 2s 41ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 2s 41ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Pgev0dgzzBVx",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "outputId": "a97e1688-da30-4042-c349-fa8971512907"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "EnYf6j4okEoC",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "outputId": "be978504-7501-42fe-c192-4c6b023e992a"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "xFJT1rZDAUVL",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "56ae677f-dadd-434f-f31b-d7cc9ee0eb89"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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q+345+DHqzyaZ27/vWvpfzyyzH27Ytj7doIoqLK9yq/k5OT6dceHp40aNCII0d+5vfff+cf/5hf2XGF0Czf5v7sfno/q375iE2nvyAzNxMXRxdGtR3DlM4v1JiyBxt+0bYydLqvHh+P6lRtc/h3GY1GUlKS6datB506dSEmZhe3b9+mdu06ZGdnmcY99FAnYmJ20r//IHbt2kGnTl2L3WdAwFDmzZtLv34Di33GIISomBb1W/Ju7/d5t/f7pQ9WsRpd+FBQ+tVV9HcZjUbmzZtLVlYmiqIwcuQY6tatyxNPPMncua+yZ8+PzJgxixkzZrNw4TusX7/O9KJtcXr18mbhwnkMGiTTOUKIirHZ77Q1GhVSUwu/R/bq1fN4eja3UqKSVfVbHU+e/J1ly/7Nxx+vtnhftvS2zLL8nmr9rYNVSU151ZQVaujbMkXVW7cukujozTJ3L4SwiBS+CowbF8y4ccHWjiGEUDnb+Hy9EEKIKieFL4QQGiGFL4QQGlHjCt95+VIc9saVOMZhbxzOy5dWUyIhhLANNe5FW0PXbtSbHMTNT6LIM7PGjcPeONP95ZWRkc5LLz0PwI0bqdjZ2eHqWrCmTUTEOuzsLP9A1LRpoaSmXqdWrYJP2gYFTeCpp/qaHZuUdIWEhHj8/ftbfFwhRM1X4wo/r1dvbn4SZbb07y17c/8YlKZ+fVciIz8HCq+MCQXvbc/Jya2UpYzfems+7dt3KHVcUtIVYmK+LXfh5+fnA/JtU0JoTY0rfDBf+paWfXHuLmWcmHiahx/uRO3adQr9QzBu3GiWLFlKkyb3sXPndjZv/oK8PAMdOnTk5ZdfK9MyCQsWvM3jj/cyXen7+T3Jd9/tYeXK/+H8+XMEBz/LgAGDqFu3HidP/s7Mma8CMHt2GGPGjKVbtx74+T3JkCHDOXz4ELNmvcbly5crlEUIoV41bg7/rntLv/a786uk7O+6di2F8PBPmT59ZrFj/vzzHLGx37FiRQSRkZ9jZ6dn164dZse+886bBAc/S3Dws2RkpBe7z6lTp9G5c1ciIz/n6af/XmLG27dv06HDQ0RFrad+/fplziKEqDlq5BX+XXm9enM7aCJ1/r2ErJmzq6Ts4f+XMi5puYIjRw5x6tQJJk0aD0BOzp1i17Qv65ROeej1evr08QHg55/LnkUIUXPU6MJ32BuHc9QasmbOxjlqDXm9eldJ6d+7lLFer0dR/r/4c3NzgYKv8hswYDBTp04r9/71ej1GY8GSR0ajkbw881/WcO84gJycXNOvHR0dC03ZVDSLEEK9auyUzr1z9tmvvWma3intLZuWatLkPk6fPgnAqVMnSUq6AkD37o+ye3csaWk3gIJvyrp6NalM+/T0bMKpUycA2Ls3DoOh4ItcCpZbzr5n3H2cOXMao9FIcvJVTpz4zez+evSoeBYhhHrVyCt8cy/QlvTuncrUp48P3367jbFjR9OhQ0eaNm0GQIsWLZk8+TlmzJiGohjR6+2ZOfNVPD2blLrPIUOG8dprLxMU9Aw9e3rh7OwMQOvWbbCzsyMo6BkGDhzM6NHP0qTJfYwdO4rmzVvQtm07s/uzJIsQQr1q3PLIpb0bp6rerWNLSw6XxpayyvLI1qWmvGrKCra5PHKNm9KxP3a0xDK/e6Vvf+xoNScTQgjrqnFTOrenh5U6pqpevBVCCFtW467whRBCmCeFL4QQGiGFL4QQGlHj5vDvOpfxByuOL2fz6Y1k5WVSx8GFkW1H81yX6bSo39La8YQQotrVyCv82PO76LPhcT77fS2ZebdQUMjMu8Vnv6+lz4bHiT2/q8L77tWrB/PmzTX9bDAYGDy4Ly+//GK59jNyZADp6cWvk1PSmJEjAxg//mmCgsYwY8YLpKZeL9ex77VmzSo+/3xdsfdfv36NN9+cDUBi4ikOHNhb7mNMmxbKyZO/VzijEKJy1LjCP5fxBxN2jue2IRuDUngJAoOSx21DNhN2judcxh8V2r+zszN//HGWnJw7APz880EaN3a3OHd5LVu2iqioL2jfvgPr1n1a6D5FUTAaK+d99o0buzF//hIAEhNPc+DAvkrZrxCi+tW4KZ0Vx5eTl29+rZm78vLzWPXLR7zb+/0KHcPL6wn279/LU0/1JSZmJ337+hMffxwoWKZg0aJ5XLlymVq1nJg9ew6tW7chIyOdt9+ew7Vr13jooYe59/NuFV02GaBz565s3vwFSUlXmDlzGh06PMSpUyd5770P+f777/j++xjy8nLp3fspJk6cAkBk5Gq2bfuGBg0a4O7uQbt2DwJw6dJF/vWvRaSnp6HX2/HPfy7Gzs6O2bPDiIj4D6tXryQ3N4f4+F8YNy6Yxx9/kg8+WMK5c2cxGAxMmBDKk0/2ISfnDgsXvsOZM4k0a/YAOTk5FTrPQojKZdEVfnp6OiEhIfj7+xMSEkJGRobZcRMnTqRHjx5MmTLFksOVyebTG4tc2f+VQclj0+kvKnwMX19/YmN3kZOTw9mzZ+jQ4SHTfWvWrKJNm3ZERX3BlCkvMH/+WwB8+ukndOrUhc8+20jv3k+RnHwVKN+yyebs37+Hli1bAwWFPWzYKD77bCMXLpzn4sWLfPJJFJ9++jmnTp3g+PGjnDx5gu++20Vk5Oe8996HhaZa3nnnTYYPH0VU1HpWrIigUaPGpvscHByYNGkqPj5+REZ+jq+vP2vXRtC9+yN88slali1bxUcfLeP27dts2bKZWrWc+M9/NjNx4hTT2kJCCOuy6Ao/PDwcLy8vQkNDCQ8PJzw8nFmzZhUZN2nSJG7fvs2GDRssOVyZZOVllj4IyMwt2zhzWrduQ1JSEjExO/HyeqLQffHxx01TIN27P8LNmxlkZWVy/PgxFiwouP3xx3tRt249oHzLJt/rxRenYGenp1Wr1kye/DyZmbfw9GzCQw89DMChQz/x888/ERJSsE7+7dvZXLp0gezsbLy9nzKt8Nnr/z6Alp2dxfXr1/D2fgqAWrVqlZrh0KGf2Lv3R9av/wyA3NwckpOv8ssvxxg5cozpXLVq1brUfQkhqp5FhR8bG8u6dQUv+AUGBjJu3Dizhe/l5cXBgwctOVSZ1XFwITPvVqnjXBxdLDpOr169+eijD1m+fFWJX1JSmooum7xs2SpcXV1NP2dm3iq0TLOiKIwdG0xg4IhC223c+HmFs/6VoigsWLCEZs0eqLR9CiGqjkVTOqmpqbi7F7xg6ebmRmpqaqWEssTItqOx1zmUOMZe58CotmMsOs6gQUMICZlc5Oq1c+eufPfdtwAcPXqY+vXrU6eOC126/P/tBw7s49atm4BlyyaXpGdPL7Zt+8q0fPK1aymkpd2gc+duxMX9QE7OHbKzs9i3bw9QsNSym5s7cXG7gYJ1/O/cuVNon7Vr1y60HHPPnl5s3rzB9HrE3ambe8/BH3+c4ezZMxY/HiGE5Uq9wg8ODub69aJv+wsLK7xmjU6nQ6ervC/G1ukKVpu7V3KyDr2+5H+jpnV/iQ2n1mMwFD+P76B34Plu00vdV3H0ejuaNGnCmDHPmn6++/9Jk6aycOE7BAWNwcnJiX/8Y97/3T6Ff/zjDcaNG83DD3fG09MTvV5H69atmTLleWbOnIbRaMTe3p5XXnmN+++////2af4x//V2vd4One7/b/PyepwLF/5k6tQJANSu7cxbb82nQ4cO9O3rT3DwszRo0JAHH+yInV3Bdm+/PZ/Fi+ezZs1K7O3tWbBgSaH99ujxKP/5TxQhIc8yfnwIEyZMZunS9wgKegZFMdKkyX28//4yRowYzYIFb/P3v4/kgQda0K7dg9jZ2Zl9HDqdrsjvs7nzXdoYW6GmrKCuvGrKCraZ16Llkfv168e6detwd3cnJSWFcePGsXPnTrNjDx48SEREBKtWrSrTviu6PDIUvA9/ws7x5OXnFXoB117ngIPegYh+a/Ft7l+mHGVlS0sOl8aWssryyNalprxqygo1cHlkHx8foqOjAYiOjsbX19eS3VUa3+b+7H56P+M7BlPXsS46dNR1rMv4jsHsfnp/pZe9EEKogUVX+GlpaYSFhZGUlMR9993H0qVLcXV1JSEhgS+++IIFCxYA8Oyzz/LHH3+QnZ2Nq6srCxYs4Mknnyxx35Zc4VuDLV01l8aWssoVvnWpKa+asoJtXuGr7huvPDyaVeprBZXFlkq0NLaSVVEUkpMvSOFbkZryqikr2Gbhq2ppBXt7R7KybmKj/0aJclAUhaysm9jbO1o7ihCaoaqlFRo0cCMt7RqZmRV/33tV0el0qvmHyFay2ts70qCBm7VjCKEZqip8vd6exo2bWDuGWWp6uqmmrEKIyqOqKR0hhBAVJ4UvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaIYUvhBAaYVHhp6enExISgr+/PyEhIWRkZBQZc+LECZ5++mkGDRpEQEAA27dvt+SQQgghKsiiwg8PD8fLy4tdu3bh5eVFeHh4kTFOTk4sXryYbdu2sXr1ahYuXMjNmzctOawQQogKsKjwY2NjCQwMBCAwMJCYmJgiY1q0aMEDDzwAgIeHBw0bNuTGjRuWHFYIIUQF2FuycWpqKu7u7gC4ubmRmppa4vj4+Hjy8vJo1qxZqfvW6cDVtbYl8aqVXm+nmrxqygrqyqumrKCuvGrKCraZt9TCDw4O5vr160VuDwsLK/SzTqdDp9MVu5+UlBRmzZrF4sWLsbMr/YmFokB6enap42yFq2tt1eRVU1ZQV141ZQV15VVTVrBeXje3usXeV2rhR0ZGFntfo0aNSElJwd3dnZSUFBo2bGh2XGZmJlOmTGHGjBl06dKl9MRCCCEqnUVz+D4+PkRHRwMQHR2Nr69vkTG5ubm88MILDB06lP79+1tyOCGEEBawqPBDQ0PZt28f/v7+7N+/n9DQUAASEhKYM2cOADt27ODw4cNs2bKFoUOHMnToUE6cOGF5ciGEEOWiUxRFsXYIc4xGhdTUTGvHKDM1zS+qKSuoK6+asoK68qopK9jmHL580lYIITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITRCCl8IITTC3pKN09PTmTFjBpcvX+b+++9n6dKl1K9fv9CYy5cvM23aNIxGIwaDgbFjx/LMM89YFFoIIUT5WXSFHx4ejpeXF7t27cLLy4vw8PAiY9zc3NiwYQNbt25l48aNfPLJJyQnJ1tyWCGEEBVgUeHHxsYSGBgIQGBgIDExMUXGODo64ujoCEBubi5Go9GSQwohhKggiwo/NTUVd3d3oOBKPjU11ey4pKQkAgIC6NOnD5MnT8bDw8OSwwohhKiAUufwg4ODuX79epHbw8LCCv2s0+nQ6XRm99GkSRO+/vprkpOTeeGFF+jXrx+NGzcu8bg6Hbi61i4tns3Q6+1Uk1dNWUFdedWUFdSVV01ZwTbzllr4kZGRxd7XqFEjUlJScHd3JyUlhYYNG5a4Lw8PD9q0acPhw4fp379/iWMVBdLTs0uLZzNcXWurJq+asoK68qopK6grr5qygvXyurnVLfY+i6Z0fHx8iI6OBiA6OhpfX98iY65evcqdO3cAyMjI4OjRo7Ro0cKSwwohhKgAiwo/NDSUffv24e/vz/79+wkNDQUgISGBOXPmAHD27FlGjRrFkCFDGDt2LBMmTKBdu3aWJxdCCFEuOkVRFGuHMMdoVEhNzbR2jDJT09NNNWUFdeVVU1ZQV141ZYUaOKUjhBBCPaTwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhUe2xO8AABC8SURBVBBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCI6TwhRBCIywq/PT0dEJCQvD39yckJISMjIxix2ZmZtK7d2/mzZtnySGFEEJUkEWFHx4ejpeXF7t27cLLy4vw8PBixy5dupRHHnnEksMJIYSwgEWFHxsbS2BgIACBgYHExMSYHffrr7+SmprKE088YcnhhBBCWMDeko1TU1Nxd3cHwM3NjdTU1CJjjEYjixcv5l//+hf79+8v8751OnB1rW1JvGql19upJq+asoK68qopK6grr5qygm3mLbXwg4ODuX79epHbw8LCCv2s0+nQ6XRFxn3++ef07t0bT0/PcgVTFEhPzy7XNtbk6lpbNXnVlBXUlVdNWUFdedWUFayX182tbrH3lVr4kZGRxd7XqFEjUlJScHd3JyUlhYYNGxYZc+zYMY4cOcL69evJysoiLy+P2rVr88orr5QtvRBCiEph0ZSOj48P0dHRhIaGEh0dja+vb5Ex77//vunXX375Jb/++quUvRBCWIFFL9qGhoayb98+/P392b9/P6GhoQAkJCQwZ86cSgkohBCicugURVGsHcIco1EhNTXT2jHKTE3zi2rKCurKq6asoK68asoKtjmHL5+0FUIIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjZDCF0IIjbC3ZOP09HRmzJjB5cuXuf/++1m6dCn169cvMu7BBx+kbdu2ADRp0oSVK1daclghhBAVYNEVfnh4OF5eXuzatQsvLy/Cw8PNjnNycmLr1q1s3bpVyl4IIazEosKPjY0lMDAQgMDAQGJiYiollBBCiMpn0ZROamoq7u7uALi5uZGammp2XE5ODsOHD8fe3p7Q0FD69u1b6r51OnB1rW1JvGql19upJq+asoK68qopK6grr5qygm3mLbXwg4ODuX79epHbw8LCCv2s0+nQ6XRm9/HDDz/g4eHBxYsXCQoKom3btjRr1qzE4yoKpKdnlxbPZri61lZNXjVlBXXlVVNWUFdeNWUF6+V1c6tb7H2lFn5kZGSx9zVq1IiUlBTc3d1JSUmhYcOGZsd5eHgA0LRpUx599FF+//33UgtfCCFE5bJoDt/Hx4fo6GgAoqOj8fX1LTImIyOD3NxcAG7cuMHRo0dp3bq1JYcVQghRARYVfmhoKPv27cPf35/9+/cTGhoKQEJCAnPmzAHg7NmzjBgxgiFDhhAUFMTkyZOl8IUQwgp0iqIo1g5hjtGokJqaae0YZaam+UU1ZQV15VVTVlBXXjVlBducw5dP2gohhEZI4QshhEZI4QshhEZI4QshhEZI4QshhEZI4QshNMt5+VIc9saVOMZhbxzOy5dWU6KqJYUvhNAsQ9du1JscVGzpO+yNo97kIAxdu1VzsqohhS+E0Ky8Xr25+UmU2dK/W/Y3P4kir1dvKyWsXBatllmVrmXm8OuVmwAcuZhOfWcHMm7nlfr/7k1dy7xNecaWtk2uAo46qvw4lbH/XAU6uNWp0kyV+Tjk3NbMc1uebbo3daV3Fa08eW/p3y33mlj2YMOFn3zzDhPXH0cHlPejwOXZpqr3X13b2GKmimwjmapuG1vMVJZtdICjvR3rQmrRol6tcu65bO4t/dtBE3GOWlPjyh5UMKVTkXUfyrNNVe+/uraxxUwV2UYyVd02tpipLNsogCHfyMFzNyqw57LL69Wb20ETqfPvJdwOmljjyh5suPB1gINeh4NeZwqpK+X/drqyb1Oesba8jS1mqimPwxYzafFx2OnAXm9Hzxbml1+vLA5743COWkPWzNk4R60p9d07amSzUzru9ZxYObozYDvzs7Y6FyrzzHJu1XhuyzuH37VZgypbjOyvc/Z5vXrXyDl8WS2zkqhpJT81ZQV15VVTVlBX3qrKWtwLtJa+cCurZQohhA0pqdRLesumWknhCyE0y/7Y0RKv4O+Wvv2xo9WcrGrY7By+EEJUtdvTw0odc3dOvyaQK3whhNAIKXwhhNAIKXwhhNAIm31bphBCiMolV/hCCKERUvhCCKERUvhCCKERUvhCCKERUvhCCKERUvhCCKERUvhCCKERNlH4O3bsYNCgQbRv356EhATT7fv27WP48OEEBAQwfPhwDhw4YLrv119/JSAgAD8/P+bPn091fZyguKwAq1atws/Pj379+rFnzx7T7XFxcfTr1w8/Pz/Cw8OrJac5J06cYPTo0QwdOpThw4cTHx8PgKIozJ8/Hz8/PwICAvjtt9+slvGv1q1bR//+/Rk0aBBLliwx3V7cuba2iIgI2rVrx40bBd/OZIvndvHixfTv35+AgABeeOEFbt68abrPVs+rrfwdMicpKYlx48YxcOBABg0aRFRUFADp6emEhITg7+9PSEgIGRkZVk4KKDbgzJkzytmzZ5WxY8cq8fHxptt/++035erVq4qiKMqpU6eUXr16me4bMWKEcuzYMcVoNCoTJ05Udu/ebdWsiYmJSkBAgJKTk6NcuHBB8fX1VQwGg2IwGBRfX1/lwoULSk5OjhIQEKAkJiZWS9a/CgkJMZ2n3bt3K2PHjjX9euLEiYrRaFSOHTumjBw50ir5/urAgQNKUFCQkpOToyiKoly/fl1RlOLPtbVduXJFmTBhgtKnTx8lNTVVURTbPLd79uxR8vLyFEVRlCVLlihLlixRFMV2z6st/R0yJzk5Wfn1118VRVGUW7duKf7+/kpiYqKyePFiZdWqVYqiKMqqVatM59mabOIKv1WrVrRs2bLI7R06dMDDwwOANm3akJOTQ25uLikpKWRmZtKlSxd0Oh2BgYHExsZaNWtsbCyDBg3C0dGRpk2b0rx5c+Lj44mPj6d58+Y0bdoUR0dHBg0aVG1Z/0qn05GVlQXArVu3cHd3N2UPDAxEp9PRpUsXbt68SUpKilUy3mv9+vWEhobi6OgIQKNGjYDiz7W1LVq0iFmzZqHT6Uy32eK57dWrF/b2BQvldunShatXrwK2e15t6e+QOe7u7nTs2BEAFxcXWrZsSXJysun3HiAwMJCYmBhrxgRsZEqnLHbu3EmHDh1wdHQkOTkZT09P032enp4kJydbMR1FMnl4eJCcnFzs7dbwxhtvsGTJEry9vVm8eDEzZ84Eima3hfMJ8Oeff3L48GFGjRrF2LFjTeVjS+f0rpiYGNzd3Wnfvn2h22313N713//+l969C5b+tcXzCraby5xLly5x4sQJOnfuTGpqqumiys3NjdTUVCunq8b18IODg7l+/XqR28PCwujbt2+J2yYmJvLee+8RERFRVfEKsSSrtZWU/aeffuL111+nX79+bN++nTlz5hAZGVn9Ie9RUt78/HwyMjLYuHEjCQkJhIWFWfXKrqSsq1atqrY/n2VRlj/DK1asQK/XM2TIkOqOVyNlZWXx4osv8sYbb+Di4lLoPp1OV+iZn7VUW+FXtFiuXr3KtGnTWLx4Mc2aNQMK/oW/+zT07pi7Uz+VoSJZ/5opOTnZlKm426tCSdlfffVV5syZA8CAAQN48803gao/nyUpKe/69evx8/NDp9PRqVMn7OzsSEtLK/FcWyPrqVOnuHTpEkOHDgUKzt/w4cPZtGmT1c5taX+Gv/zyS3bv3k1kZKSpiKx1Xktjq7nulZeXx4svvkhAQAD+/v5AwRRkSkoK7u7upKSk0LBhQyuntPEpnZs3bxIaGsrLL79M9+7dTbe7u7vj4uLC8ePHURSF6OhofH19rZgUfHx82LZtG7m5uVy8eJE///yTTp068fDDD/Pnn39y8eJFcnNz2bZtGz4+PlbJ6O7uzqFDhwD46aefeOCBB0zZo6OjURSF48ePU7duXdNTUWvq27cvBw8eBODcuXPk5eXRoEGDYs+1tbRr144DBw7w/fff8/333+Pp6cmXX36Jm5ubTZ7buLg4Vq9ezYoVK3B2djbdbmvn9S5b+jtkjqIozJkzh5YtWxISEmK6/e7vPWATHQU2sjzyd999xz//+U9u3LhBvXr1ePDBB1mzZg0ff/wx4eHhNG/e3DQ2IiKCRo0akZCQwOuvv86dO3fo3bs3c+fOrZanTMVlhYKnyP/973/R6/W88cYbeHt7A/Djjz+ycOFC8vPzGTFiBM8991yV5zTn8OHDLFy4EIPBQK1atXjrrbd46KGHUBSFefPmsWfPHpydnVm4cCEPP/ywVTLeKzc3lzfeeIOTJ0/i4ODA7Nmz8fLyAoo/17bAx8eHzZs307BhQ5s8t35+fuTm5uLq6gpA586dmTdvHmC759VW/g6Zc/jwYf7+97/Ttm1b7OwKrqFnzpxJp06dCAsLIykpifvuu4+lS5eazrm12EThCyGEqHo2PaUjhBCi8kjhCyGERkjhCyGERkjhCyGERkjhCyGERkjhCyGERlTbJ22FqA5paWkEBwcDcP36dezs7GjYsCEXLlxg6NChvP3221Vy3OPHj7NgwQJyc3PJzc1l4MCBTJ8+nYMHD+Lg4EC3bt2q5LhClIe8D1/UWMuXL6d27dpMnDixyo/Vr18/PvzwQ9q3b09+fj7nzp2jdevW1ZpBiNLIFb7QhIMHDxIREcGqVatYvnw5ly5d4uLFiyQlJfH6669z/Phx9uzZg7u7OytXrsTBwYFff/2Vd999l+zsbBo0aMCiRYuKXRbhxo0buLm5AaDX62ndujWXLl3iiy++wM7Ojq+++oq5c+fSsmVL3nrrLa5cuQIUrGDavXt3li9fzoULF7hw4QJpaWlMmjSJ0aNHV9v5EdoghS806cKFC6xdu5azZ8/y9NNPs2zZMmbPns0LL7zAjz/+iLe3N/Pnz+fjjz+mYcOGbN++nQ8++IBFixaZ3V9QUBD9+/fn0Ucf5cknn2TYsGH87W9/Y8yYMYWu8F9++WWCgoLo0aMHV65cYeLEiezYsQMoWIRt48aNZGdnM2zYMLy9vW1ukTChblL4QpN69+6Ng4MDbdu2JT8/37QmfNu2bbl06RLnzp3j9OnTpsWwjEaj6QrenGnTpjFkyBD27t3LN998w7Zt21i3bl2Rcfv37+fMmTOmnzMzM01fSuPr64uTkxNOTk707NmThIQEKXxRqaTwhSbd/RYtOzs7HBwcTAvv2dnZkZ+fj6IotGnThg0bNpR5n82aNePZZ59l9OjReHl5kZaWVmSM0Whk48aN1KpVq8h9trBeuqjZ5G2ZQpjRokULbty4wbFjx4CC9c4TExOLHb97927uvv/h/Pnz2NnZUa9ePerUqWO6goeCrxe898r/xIkTpl/HxsaSk5NDWloahw4dsvqqmqLmkSt8IcxwdHRk2bJlzJ8/n1u3bpGfn09QUBBt2rQxO37r1q0sWrQIJycn9Ho97733Hnq9nqeeeooXX3yR2NhY5s6dy5w5c5g3bx4BAQHk5+fTo0cP09LE7dq1Y/z48aSlpfH888/LdI6odPK2TCFsgLx9U1QHmdIRQgiNkCt8IcrhnXfe4ejRo4VuGz9+PCNGjLBSIiHKTgpfCCE0QqZ0hBBCI6TwhRBCI6TwhRBCI6TwhRBCI/4XSg/yjkNTEIoAAAAASUVORK5CYII=\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Lu7m2Rr4AbMK",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "9436a6eb-214e-47a3-d241-3a5bd056c31c"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "fjXexah9C8yg",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "185bb543-b7ad-4f25-fd89-75be524af04e"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "7mtLZ6S-DPU-",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "outputId": "553066ce-28bf-4e95-95c1-f7f34f907647"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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zOezJw5C2+8sRsA8Prru3Ho0DsAgNNPfx/++MdtGBjoBwAMDw/h8OFDjrbZ3j4Tr7++CwDwv//7FCRJOzOLxeqQSCQMj5uFN998A4qioKfnMHbtetV0e37WQhAEMVERZaMTTcWFBDEZsDI3x8P09MKUdKK1SwCpigfVP/zhc/H44xvx6U9/AiedtBBz5swFALzrXfPx+c9/Edde+yWoqgKeF9DVdT3a22eW3OZFF/0jvv7163DFFZfh/e//AKLRKADguOMWIBAI4IorLsOFFy7HJz5xOWbOnIVPf3ol5s17F44//t2m2/OzFoIgiImKpOQ70QRBTHzWrEnnNYIAKmN6OoVTVXViyHkXiKKMwcFE3m2HD7+N9vZ5VVrR1IM+b4IgJhO/e/kw/u8TbwAA7vnUaTipPV7lFREE4YSJ0J1jxgzz/YVvJ/q+++7DAw88AJ7nsXjxYnzta1/Lu3/Pnj249tpr9X8fOHAA11xzDVatWoUf/ehH+PWvf42WlhYAQFdXFxYvXux3SQRBEASRR35hIcU5CGIiiFMndHZKE3JdgE8R/dxzz2Hbtm343e9+h1AohL6+vqLHzJ8/Hxs2bACgDfL40Ic+hCVLluj3r1q1CldddZWfZRAEQRCELYWFhQQxlanUvIxax1dh4UMPPYQvfOELCIVCAIBp06bZPv7ZZ5/FnDlz0NHR4edlCYIgCMIVeYWFIoloYmpTyXkZtYwvEb1v3z5s374dK1euxKc//Wns3LnT9vEbN27E8uXL82574IEHsGLFCtxwww0YGhrysxxMwnj3pIQ+Z4IgJhtUWEgQGuvXC6ZtfoGJ0zpuslAyzrFq1Sr09vYW3b569WrIsoyhoSH8+te/xssvv4zVq1dj27Zt4LjiP0Imk8GTTz6J6667Tr/tsssuwz//8z+D4zj84Ac/wM0334zvfve73t6IEMLY2DDq6hpMX58oD6qqYmxsGIIQqvZSCIIgHCMZ4hwpkTLRxNSExTgAc500UVrHTRZKiui7777b8r6HHnoIS5YsAcdxOOWUUxAIBDAwMKAXChp56qmnsHDhQkyfPl2/zfjfK1euxNVXX+1y+Tmam2dgYOAoRketR2ET5UEQQmhunlHtZRAEQTjGWFhITjQxVTGLcTAmUuu4yYKvwsLzzjsPzz//PP7P//k/2Lt3L0RRtBwRvXHjRixbtizvtiNHjqC1tRUAsHXrVixYsMDzWnhewPTp1MuYIAiCKEaUVXAAVGhjvwliKmId11Cxbh0VFbrFVya6s7MTBw4cwPLly9HV1YWbb74ZHMehp6cHn//85/XHJRIJPPPMM1i6dGne82+55RasWLECK1aswHPPPYcbbrjBz3IIgiAIwhRRVhAL8QAozkFMXaziGrNnq44F9Pr1AhYtqkNbWz0WLarD+vVTcm4fgBoatkIQBEEQVty89e948o1eJEQZn3jvLFyzeH61l0QQFaewtR2gxTicutB+nz9ZsRq24suJJgiCIIjJgCSrCPIcIkKA4hzElKWzU8K6dSnMnq2A41TMnq24EsDUGi+fqevBEwRBEFMGUVEg8JpvlKaJhcQUxs8EQKtM9VRtjUdONEEQBFHziLKKYIBDJMjTsBWC8IhVpnqqtsYjEU0QBEHUPKKsIMgHEKY4B0F4Zs2aNKLRfME8lVvjkYgmCIIgah5JyWWiKc5BEN7wm6muNSgTTRAEQdQ8kqxCCHAIU5yDIHzhJ1Nda5ATTRAEQdQ8rLBQc6JJRBME4R8S0QRBEETNoxcWCgGkKM5BEEQZIBFNEARB1Dx6YSHFOQiCKBMkogmCIIiaJ7+wkEQ0QRD+IRFNEARB1Dx6YSHFOQiCKBMkogmCIIiap7CwUFWn5nAIgiDKB4logiAIouYxTixUVO3fBEEQfiARTRAEQdQ8xomFACjSQRCEb0hEE0SZeePIKN4ZSlV7GQRBGDAWFgKg4kJiSrJ+vYBFi+rQ2lqPmTPr0dpaj0WL6rB+Pc3e8wKJaIIoM998bDd+8Kc91V4GQRAGJFkFn41zAKA2d8SUY/16AV1dEXR3BwBwkGUOAIfu7gC6uiIkpD1AIpogysxIWsKBwWS1l0EQhAFRyY9zkBNNTDXWrg0jmeRM70smOaxdG67wiiY/dNpBEGUmkZGRyMhQVRUcZ77DIgiicqiqaphYmHWiKRNNTDEOHrQ/HpW6nyiGnGiCKCOqqiIlyhjLyBhKSdVeDkEQAGRF68RBTjQxlenosO9IU+p+ohgS0QRRRjKyCtY5i4oLCWJiIOoimkMkmO3OQZloYoqxZk0a0ai5UI5GVaxZk67wiiY/JKKJmufXO97Bp+97yfXz/t8f38LXf/+aq+ckxdwlYhLRBDExkLJntjzFOYgpTGenhHXrUpg9WwGggudVACpmz1awbl0KnZ109dQtlIkmap7dPSN48+io6+e91TuGPX0JV88hEU0QEw9R0VxninMQU53OTonEchkhJ5qoeQaSImQVkGR3B820pKBvLANJcZ4TyxPRwySiCWIiwKYTahMLWZyDnGiCIPxBIpqoeQYSIgAg5dJ5SksKFBXoG8s4fk7SkLM8SE40QUwIRLnYiXa7PyAIgiiERDRR8wwksyLapfPELvceGXFebJHMaK/RFA1SnIMgJggsE61NLNQy0RTnIAjCLySiiZpnIKE5yW6dp0zWvToy6kJEZ4X6cdNjODScgqJSyyCCqDYskiUEOAR5DgGO4hwEQfiHRDRR06REWY9YeIlzAMCRUTdxDu3AfOz0OoiyiqMunksQxPjACgsFPgCO4xAWAhTnIAjCNySiiZqGRTkAIF2JOIfuRNcBoA4dBDEREA1xDgCICDzFOQiC8A2JaKKmYUWFgHcn+qirOIf2nGNJRBPEhEEvLAxohzxyogmCKAe++0SvXr0ae/fuBQCMjIwgHo9jw4YNRY976qmnsHbtWiiKgpUrV+ILX/gCAODAgQPo6urC4OAgFi5ciO9///sIhUJ+l0UQAPKdaDcTylRV9eVEv2taDBxIRBPEREAqdKKDAddXpgiCIArx7UTfeuut2LBhAzZs2IClS5diyZIlRY+RZRk33XQTfv7zn2Pjxo149NFH8eabbwIA/vM//xOrVq3Cli1b0NDQgIcfftjvkghChxUVAkDaxYQydvkXcJ+J5jmgLsRjRn0IB330ipZkBa8dHvH8fIIgNIyFhYAW5yAnmiAIv5QtzqGqKjZt2oTly5cX3bdz507MmzcPc+bMQSgUwrJly7Bt2zaoqornnnsOH/3oRwEA//iP/4ht27aVa0kE4TnOwVzoIM/hyGgaqsMuG4mMjGiIB8dxmNUY8eVEP/n3Xqx6YAd6XDjhBEEUw+IcAk9xDoIgykfZRPT27dsxbdo0HHPMMUX39fT0oL29Xf93W1sbenp6MDAwgIaGBgiClippb29HT09PuZZEEBjMi3M4d6LT2YPu7MYoRFnN244dKVFBNKj1ofUrogeTElS4G/ZCEEQxokJxDoIgyo+jTPSqVavQ29tbdPvq1atx3nnnAQAeffRRUxeaIKpJf0JELMgjIcounWjtADu7KYK9/QkcGc2gOVY6q58Q5ZyIbohg08gRiLKCIO/+fJWtYSQluX4uQRA5igsLefQnnJ0YEwRBWOFIRN99992290uShC1btuCRRx4xvb+trQ2HDx/W/93T04O2tjY0NzdjeHgYkiRBEAQcPnwYbW1tzldPECUYTIpobwhjT1/CVUsr9tg5zVEAWnHhu1vrSz4vaRTRjRGoAA4Pp/XtuIEVQg6nSUQThB+KCguFALW4IwjCN2WJczzzzDOYP39+XmTDyMknn4x9+/bhwIEDyGQy2LhxI84991xwHIf3v//92Lx5MwDgt7/9Lc4999xyLIkgAGiZ6Nb6MHiXE8oy2QPs7CZN/Dptc5cSZUSD2s9qVmMEgPcOHazTx3CKHDOC8IPEhq0EcnEOmlhIEIRfyiKiH3vsMSxbtizvtp6eHnz+858HAAiCgG9961v43Oc+hwsvvBAXXHABFixYAAD46le/il/84hdYsmQJBgcHsXLlynIsiSAAaN05mmJBRILuqvGZSzWrIYIAB/Q47NCRMGSiO7Ii2muHDrbeYYpzEIQvWLedXGFhdYat3PfCAXzrsd0Vf12CIMYH332iAeDmm28uuq2trQ133HGH/u/Fixdj8eLFRY+bM2cOtbUjxo2BpIiWWBBhl5dv2WOjoQCm14Uc94pOijLa42EAwIz6MIQAh4ODHkW07kS7E9GSrCAhymiIBD29LkHUGkWFhVXqzvHq4RG8cojaVhJErUATC4maJSXKSIoKmqJB7aDppjtH9gAbFni0xsOO4xzJbIs7AOADHGY2hD3HOdhB3m1h4S93vIOVv9gOxWFbPoKodcwmFqYlpeK/EUlW9ZgWQRCTHxLRRM3CphU2R4MIe4xzhPkAZtSHcWTEWZwjKcqICrmf1azGCN7xGufIHmyHXGaiDw4m0Z8Q0etiSAxBjDeyouKZvf2Oe66XE0mPc7BMtHaim6mwGy0qChIZEtFEZVm/XsCiRXVoa6vHokV1WL/eWwihXNupJUhEEzULG7TSHAtlnWjnB8yMzJzoAFrrQzjitLBQUhDLOtGAv17RSeZEu+zOMZo9SB+kkePEBGL7/kF85ZFX8MbRsYq/tqQo4DkgwGkiOpw90a10pEOSVUiKqjvjBDHerF8voKsrgu7uAFSVQ3d3AF1dEdcCuFzbqTVIRBM1S05EB7MtrZw7QCnJKKLDGMvIGC0hZmVFRVpSdJcL0AoTB5OiJ/cp7TETzdbpZ9ALQZSb0Yz2vSz1OxoPRFnViwoBLRMNuOvYU5Z1ZLPZ5EYTlWLt2jCSSS7vtmSSw9q14apsp9YgEU3ULANJLc7gJc7BLvOGhABas4WCR0vEI1jWMRrMd6IBb4LWa3eOMRLRxASEXd2pRkGfqKh6USGQi3NUw4kGQLloomIcPMi5un28t1NrkIgmapZCJ9pNnINloiNCADPqtUmFpSId7MAYC+Z+VnqbOy8iWvQ2sVCPc3jMYhPEeCBKmoCsxrhtUVb0okIgF+eodJs71q86QSKaqBAdHeY1CFa3j/d2ag0S0UTNMpAQEeQ51IV4hIUAUi7iHCz6ERICaMs60aXa3CWzIj1i5kR7ELTMJUuIMiQXGUqKcxATkWo60ZJc6ERXJ84hZeMcSYpzEBVizZo0otF8oRuNqlizxlmdT7m3U2uQiC4jwykRH73tWezoHqr2Ugho3Tmao0FwHIdI0N1whbSkHXQDHIfpdZoTXTLOkWFOdE5EN0WDiAYD3uIcogI+O2HNzejv0bS2DhLRxESCiehqDDmRFEWfVghUz4lmBYXkRBOVorNTwrp1KcyerYDjVMyerWDduhQ6O91d4SzXdmqNqV1WWWbeGUqhPyFiT98YTpvdWO3lTHkGkyKaY5oAdh/nkBHKFiJFgjwaI4LjOIcxE81xnOcOHUlRxoy6EA6PpDGclNCSfS92qKqKsYwEntOcc1FWEOTpXJmoPmxqYFUy0UWFhVXKROuFhdSdg6gcnZ1SWcSu1+2sXy9g7dowDh7k0NGhude1Ir7p6FpGBrN9iZMuxBoxfvQnNCcaQHbst3P3JyMrulsFAK3xcOk4R3b7kWD+z2pWg3sRLckKJEXVixqdOtEJUYaiAsdMi0EFcHh4al9qIyYOrFi3KpnoosLCKnXnoMJCYopR663xSESXkcGkJnQo7zYxGExk0BzTRHRYCECUVciKsyKItKTobbAAoLU+jCNO4xyGPtGAlos+OJR0NWSCOWSt9ZqIdlpcyKIcx8+oB0CRDmLiUM04x0QpLKQ4BzHVsGqN98UvRmpiYAuJ6DKSc6JpBzkRGEiKuoiOuDxopiUFoTwnOuS4sNAY5wA0EZ0UFf374QRdRMe1CIfTqYWsqPD4Vk1EU4cOYqJQ1Ux0YWFhleIcMhUWElMM6xZ4teFKk4guIySiJw4pUUZSVNBkiHMAcBzpSEsKwkJODM+oD2MgKdqOCU6YZKKBXJs7N64wu8zs3onWHveulhiEAFdzTrSiqvjhn/bgMJ0cTDqqmYmeOIWF2Uw0HSOIKUKpFnjJJIcvfWnyCmkS0WVEF9FVOEgQ+Qxk/xYtBU600+LCtKTohYUA0JYVs0fHrN3olIWIPmPtpAkAACAASURBVKYlBgB4s9f5uGO2Ttaj2unAFdYjOh4RMLMhXHMi+vBwGvdt78ZTb/VXeymES3JOdDX6RE+MiYWsTzQ50cRUwaw1XiGyzE1aR5pEdBkZYiKadpBVpz87aKUpqolQt85TRlIQNhQIzsjGKo6OWOei2RWIwsLCuc1RNEQEvHxoxOHqc455XUhAXYh3XFjIphXWh/lsFru2RDT7+41laqOyeyohVjMTXVBYKPABCAGu4q44OdFEtVm/XsCiRXVoa6uvSCbZ2BoPsBbTk3WEOInoMuInzkERkPIyaJhWCHiLcxQWFgL2UwsTGe05AS4/A8ZxHE5qj+NVNyJaH9wSQENEwIjLTHR9SPDcWm8iw+I0bqc4EtUnk51Y6KbVZLkoLCwEtBPrSgp6WVF1CVGO/b3oYgATQQDV65TR2SnhpZfGcNttKVtXejKOECcRXUZYdw63lwif3tOPc378DF477FxkEfYMJDXHuGxxjmyruR6b4sKUJBdFORjvaY9jT98YEg6vUqT0dnk8GiJBDLnszlEfFjCrIYLBpOj4NScD6axwGHExfIaYGFTTiS4sLASybS8raF4YRa/f3+Th4RQ+/KOn8cqhYb/LIqYQVp0yKuUAM1ea52tnhDiJ6DLipU+0oqr47//dC1lR8btXDo/X0qYcA3qcI9fiDnDhRBf0ia4L8YgGA7ZTCxMZGdGQhYie2QBFBXb1ODtR0p1oIYB4RHBeWJgdtBINBnIjx2vIjWZ5WnayQEweqpmJlpTc9E9GpZ1oydBe068T/VZfAhlZxcFB/7/to6NpHKJC3SmBldNbSQe4s1PCj39c7EhP1hHiJKLLhKqqnuIcW18/ir8fHUNbPIwndh+tiktTiwwkRAR5DnVZUcviHGk3TrRBRHMcl+0Vbf0jT4oyokHzn9TC9jgA4BWHkY6UYXBLQ1hwXliYllEXFsBxHDqaogBQU7loFgkYJSd60sGc2GpNLCyc3BkRAhVdiyTnRIPfiYXsilg5jhdrNu7Gv2963fd2iImPldNbaQe4lkaIk4guE2MZWXcanIpoSVFx+zNv49jpMaxZugAjaQl/fqtvPJc5ZRhIatMKuWw+WY9zuCgsNGaiAWBGPIwjJQoLYxZxjqZYELObIo4vvyZ1J5pHQ0RwXFg4mpZQnz1x6GjIOtE15DJRnGPykqnm2G/FPM5RSVecdeYA/DvRuoj2mYseSor428GhKVVjsKtnBC/sH6j2MqqCWaeMajjAtTQGnER0mWAudF2IdxzneHxXD94eSOKf/uEYvG9uM1rrQ9j4Ws94LnPKMJAQ0RwL6f/WCwsdHrzSkpwX5wCAtvpQCSda0V/HjPfMbMCrDnPvKUOnj4aIgOGU6Gji4UhaQl1YKxJpjAqIBfmainPohYUkoicd1c1EmxcWVrLIUTTEOfx25yiXE/382wNQ1FzUZipw57P78f/+uKfay6gKE8EBrrUx4CSiywRrb6dNpyu9gxRlBXc88zZObKvHh4+bBj7A4fwT2/Ds3n70jdmPlyZKw5xoRtiFE62qKjKymldYCGgDV3pH05ajw7U4h42Ibo/j6GjGtjiRwdapOdFBiLLq6IA5lpZQnxXRHMfVXIeOXCaaRPRkgwm1chTzPfTSQWx5/ajjx2t9oguc6CrFOepCvO82qGx6qt3wJyc8s7e/LNuZTCREueL9wScKE8EBrnZxY7khEV0m2HCP9ngYkqJCKnFm/7tXDuOd4TSuPusYPXKwbGErZBXYvPvIuK+31hlMZPT2doC7sd/sMYVOdGs8DFkFBhLmJzl2mWgAeM9MLRf9qoNIR0pUEOI58AEO8Ygmip3kokczsh7nAFCDIpoy0ZMV1iO5HE70w399B4+5uGonKgoE0xZ3FezOkY1zNESEMjrR3rejqCqe3afFGqaSE52WlClZezRRHOCJUNxYTkhElwkW55iZzaHaRTpSoow7n9uPU2c14APHNOu3z59WhxPb6rHxVYp0+KU/IeaJ6LCLCWVsBxsqFNHZ6YE9Fh06kqJi60QvmFGPIM85GrqSlmQ9GtIQdiGiDU40kBPRTqIgkwF2sM84dOaJiQNzO8vxd0tkZH2wUClUVbVpcVd5J7ohEkRaUvK6dbhBVVWDiPb+u97dM6rtJ6PBKSeiM3Jt7A/dYOUA/9u/hSs6fGWiFDeWCxLRZYL1iJ6ZbStm5zQ8svMQjo5m8MWzcy40Y/nCNrxxdAx/Pzo6foutcVKijJSk6O3tAC3a4PTyLTugFBYWtmZ7RR+1iGMkMzJiFi3uAE2Uv7u13pETnRRl/fUbmBOdLj1wZTQtI14gohOijKFkdZ1bUVbK4h4bLztTLtodGUmp6qRH9ruSFNWzgGQkRVkfcV8KWdXmpBWJ6Aq3uGOZaHZlyWukYCgl6ev240Q/vbcfHICz57foVwmmAmlJnlLxFYaV0zswwLlyp/1OPJwoxY3lgkR0mRhMihACHKbXaW6lXS76N399B6fPacTpc5qK7lv67lYIAQ4bX6VIh1dYtKbF4EQDzvvC5uIc+YJ4hs3UQlVVNeFr40QDWqu7XT2jJUVEylCkqIvoEkJYVVWMZSTUhw1xjuyVkYNV7tDxi+f348oHd/jejlE0UKTDHT97Zh/+6Vc7q/b6RqHmR/ypqurKiWbROtPCwkp258iuozH7e/Y6cMVYU+HHQX52bz9Oao+jNR5GWlJq5mpVKdKS4ruryWTE2ul1nk8uRyRkIhQ3lhMS0WViMCmiKRrUM7F2LkP/mIjjZ9Sb3tcUC+Ls+S14fPcR327NVKVfH7QSyrvd6YQyqzhHUzQIDrlBLoXPUQFEBfuf1MkzG5CSFLzVO2b7uJSUG/bSENFOBkq1uUuIMhQVeXGOjuyVkYODSdvnjjc9I2l0D/qPlRgvX5OIdseh4XRV8/EZWXFVm2AF+62NORShTLwXFRZWOs7BnOjs79NrLvqIQUR7/RwHEyJeOTSCs97VohdQV+p4U+2WemlJgVyGqyGTDTMHGDD/DKxc63IVBbIx4D09o3jppbFJK6ABEtFlYygropl7aJWJVlQVCVHWh4CYceFJbegby+D5t6dmL0u/DCbMnWincQ6rwkIhwKEhIuhOtxF25cEuzgEACx0WF6ZEGREh34kudeBhU/zqCuIcQPWnFmZk7aDl9/K50XmjOIc7UqKMsYxUNcdRlBVDlMH794CJz9GM7Oi9sIK+wmErYSFQlmiJU4yZaMB7r2jmRDdGBM+/p+feHoAK4B/e1aybBZXIRcuKii/+ZicefLF73F/LCvaZiVPMjTZzgFta3OWTa60osByQiC4TmhMt6IVlVi4Du4RnJ7bOnt+CxohABYYe6c92z2g2iXO4caLDfPHPozkWNHWi9eEoJeIcHY0RNEWDJScXpiRFv6oRC/EIcMBwyj4TzZxZY3eOWIhHUzRY9YEr7IDl1z02xgCm0oCIcpCSFChqdYadSIoKRc25sH5Optg+VHZ4UsbEqxAozkRra6lMpMPYnQPwF+fgA1r7Sq+f49N7+9EcDeLE9jhCWYe+EjnhjKxAlFXs60+M+2tZkcuTTy0RDRQ7wGvXussn11pRYDnwVYa5evVq7N27FwAwMjKCeDyODRs25D3m0KFD+NrXvoa+vj5wHIdPfOITuOKKKwAAP/rRj/DrX/8aLS0tAICuri4sXrzYz5KqxmBSxHHT6/SJdVZije04jW5hIUE+gHOPn44ndh+FpKhFO3/CHtYpxVhYCLAJZQ4KCy2caABojoVMnWh20mQ1sZDBcRzeMzOOV0oMXUmKsr7+AMch7mD0ty6iC75bHROgzR37TEfTMqabJ5kckc7GXNKS4riwjNBg+6SxjH0/8/GAnUTlRLT3v53RwR3LlK5DyDnR+ftRVvOQlhTUhYqeVnZyTrT2GfhxomfUhRAJ8p7cY1lR8ezefvzDu1oQ4Dg9zlGJjhXprNmwf6A68TJjjGMqFhcWosUoUo57R69Zk0ZXVyQv0jGZiwLLgS8Rfeutt+r/ffPNN6O+vvjoyPM8vv71r2PhwoUYHR1FZ2cnzjrrLBx33HEAgFWrVuGqq67ys4wJwWBSQmM0iEjWPbTaQbIcX12JHf/75jbjtzsPY3fPCN4zs6G8i61xBhIiQjxXFJlxGudgjwmb9Hxujgaxp684z8wEihNxsrA9jqf39Be1ozOSLhg7rk0tLCGis9+twm3Oaoxgd4+zSYnjRaZM47ozsoppdSG8M5TCKDnRrmDf67G0pBdAVwomWMoS58jki+hpdfaPZ5nowsLCiF6/Uhkxxbpz+HWij4ym0RYPI8wHMOqh28qunhEMpSSc9S7NvNLjHBUQlayg78BgEqqqFnWnGvfXN7zHqdTWz47OTslxJtkouru7OfA8kExCz0SX2s5EGPZSbsoS51BVFZs2bcLy5cuL7mttbcXChQsBAPX19Zg/fz56emorpiArKoZTrLDQPhOdyO706sL2Yuv0OY0AgBf2D5ZxpVOD/mw+vXAH7bSwkO1cCycWAtZxDnZAjIZK/6TeMzMOFbAdAZ4SZf0gD2g5ylKFhWO6E53/3ZrVGMGhYetJi5WAuVxeDvp525EUNEYE8AGOMtEuMTrRlabYifYuYPKd6NLfAeYAm7W4A1CxDh1SQZzDjxPdGg877jZUyNN7+hHggPdnZxQE+cploplQT4pKVSbzGq+ATMU4Rzno7JSyRYqALHMAnLfGmwjDXspNWUT09u3bMW3aNBxzzDG2j+vu7sauXbtw6qmn6rc98MADWLFiBW644QYMDQ2VYzkVZyQtQVGRJ6KtxNqog0w0oMUGFsyoq5qIfuXQMJb85Fn0TsIR5IMJEc2xYqct7LiwUNYfX0hzNIjhlFRUjMROmpw50dqVhVdtctEpSdELCwHNwXMc5wgVO9GSouJotjWfoqq445m38dHbnsXhCmWlc5lof4IlLWn9s+NhgUS0S9h31G+v6OGUiPN/+hxefqd0v3NGukBE+8llJwwGxZiD7xOLcwhFhYW5OEclYI54Q1iLaSU8OOCqquLIiOZEhzyK6Gf2DWBhe4MeFwtVUEQbW8sdGKx8xIyc6PLgpUtHrY37ZpQU0atWrcLy5cuL/rd161b9MY8++qipC21kbGwM11xzDf7t3/5Nj31cdtll2LJlCzZs2IDW1lbcfPPNPt9OdTBmcJl7aHWpTs9Eh0qffZ0xpwk73xmuyhnza4dHMJgU8XrP5Bv6MpAUi4oKAefDFay6cwCaE61C68ZiRI9zCKVFdDwi4JiWKF6x6dCRKug53RgRMFKysNA8ztGR7RX9znAKg0kRqx95Bbc/+zb6EyLe7q9MNpE5UH6Fb1pSERICqA/zrosUD1QphzlRYI6rE+Fpx5GRDPrGMtjrojhMzLYmrI+UIROd8eZEFxUWVjjOIRUMW0l6uCIwkBSRkVUtziEEXEcw+sYyeO3wCM6an5uUGxIqV1ho3P9W4/doPHmjTLR3vHTpqNXOHiWV3N133217vyRJ2LJlCx555BHLx4iiiGuuuQYrVqzA0qVL9dunT5+u//fKlStx9dVXO1jyxGNIF9ECAtnJeFZxDrbTt2txxzhzbhMeeukgXjk0bDqYZTxhDvTbAwmchZaKvrZfBhIZzGuOFt3utk+0mYhm7s1AUsQ0Q66UFRZGHfxdAeDEtjhe6ja/8iIrKjKymhfncFRYmJHAc9C7ejBYm7sn3+jFv7/5OvoSGVx+egcefPFgyYhIuWAunNMBGVZkZAVNvIB4WHDlau/qGcFn79+Buy9/LxZO0RoDJha99idmMDfRTYsw5vo1lMWJzs9El8KqsLDS3TnYsJVYkEeQ5zz9HVh7u7Z4GPv6E67dVHb14H1zDSI660RXYmqhUbjur0LveqOIpziHdzo6VHR3F4tfuy4dXp4zGfAd53jmmWcwf/58tLe3m96vqirWrFmD+fPn48orr8y778iR3FS+rVu3YsGCBX6XUxUKu0FEg7xlzi7nRJcWW6fNbgTPVScXfXQ0K6Ir5FSWk4GEuRPtPM5hPrEQAFqyMZHBglx0Ui8sdPaTaomFLFvWse9OYWGhFhuy3uGMpmXUhYWiLHh7QxgcgF/teAccB/z80vfiU6fPBoCS7na5SJepxV1GUhAWeNS7jHOwATy7j0y+KyvlQJIV3Qn1G6lhQshNN4dyZqKNV/mcvBfLwkKBRe8q60QLPIdYkPfkRB8xiGgvmWgm3I37RyaiKzHFL1NlJ5riHOVhyRIJHOdudHetjftm+E50P/bYY1i2bFnebT09PfjGN76BO+64Ay+++CI2bNiA448/HhdffDGAXCu7W265Bbt37wYAdHR04KabbvK7nKpQLKIDJbtzxBzEOerDAk5sj2P7/kHgrDIt1iFGJ3oykRRlpCQFzVHrOEepqnC2ow/xxY9pyh58WC9q4+sCzjLRgFb8lxQVSLJSlNVMmfScbogEoaiagLDq6DGalvJ6RDOCfABnzm1CJMjjmx89Hk3RoO7Il3K3y4Wod+fwn4kOC1rLv94x599N5gJOxpPCcmA8efSbiWbOrZvL4Uxw5+Ic5XKivRcWsu47leqbLRpiJdEg79uJDvHuRbQ+jdWwz2HdOcQKfA7ss55WF8KBqjjRuc+c4hzeWL9ewC9/GYSq5n5PHKfi0ktF204bbtvpTRZ8i2izHHNbWxvuuOMOAMAZZ5yB119/3fS5t9xyi9+XnxAMJrUvARPRkSBvmYkey8gQApypQDPjjDlNuG97NxIZuWQxYjnpnaRONOucYZqJDuYKiex6y7JexGZCm01BHEwWOtEKhABXNBXNCubIjaZlNMUKRLSJE81ylEMp0VZEW/Uf/++Vp+T9OywEEOQr1+Ei1yfap4CTtUw0H+BcRUOYgKlWf9pqk3IZgbCDjV534+RldCfavvDaCcmMNvE1IyvO4hyyeWFhxeMchgLHaIj31J2jZyQNIcChORbUJy7Kigre4SwB3SAw7FsqWVjIXmPB9Dr89eCQrzZ3u3pG8OKBIXz6jNmOn5MX5yAn2hNmBYKqymHLFgHf+569q+ymnd5kgSYWloHBpIiIENCFWTTIW14iHEtLqAvxjnccZ8xtgqyo2HGwsp1Lescy4LL/71f4VBImCuMRcycaKO08pSXFtL0dADRGguCAojZ3KdHdAAsmis1avpk50Y0ORn+P2rjUhXAOB7iUCyZiffeJzv5t3MY5WC52sl1ZKRfJvI4W/nPpgLtMNHtsNMiDD3C+nehokEddSHD0XvQYRdHEwsrGOURZBQeA57RctJc+0ay9XYDj9JoNN+LXrN5DLyysYJzj2Ol1SEmKr+5Pj+86gv/+815Xz8mLc5AT7YlaLRD0ConoMjCY7UvMsHMZEqLsKA/NOHVWA4I8p0U6KoQoKxhMiji+VeuiMpncu5RNNpkdOEq5YGlZMS0qBAA+wKEhIhRNLUxkZMd5aCDXQcNMCDKRb9weE912otcqzmEFy1lXAnaA9ivgtDgHj3hY0OMwTmAi/p2h1JQ8eBprNHwXFupxDueZ6IweqQg47pJjRTJ7Va4uxDuaWpkrLCxocRdkTnTlMtECz4HjOM9ONGtvBxiyzC5OApj7mhfnYE50BYetHDcjBsDfsSUtKdlx8s6/h/mFhZO7oK1a0OjvfEhEl4EiES3YZKLTsqM8NCMS5HHKrIaKimjWBJ8NfJlM7p3u4poUBRrjHHawOIcVLbFQkROdFBVXTjQbiGLmLDORb3wPrLesnYges5mAaEY8HKyIE62ouVG7fkZ1q6rWtYRlogHnRXJMbCsq0D00eU4Ky0XSZW9lO3KFhS6caEMWVyvw9b6GnBPNOzopE60y0RUetiLKil7c6MeJZiKard9NLCEjabEzY/wjWMmx39nvwXHTtTGTfooL2X7STVeRvBZ3FOfwRK0WCHqFRHQZKBLRQd4yMjDm0okGtFz060dGi3oTjxesM8d7OxoR4CZXLpodEM1cYadxjoyk5GUGC2mKBYuc6KToLrOeE4F2cY787hwAbFvSuYlzsG3axUPKhdHh8vN67CAf4gO2cRgzjAfayfR9LhdMcAQ4/4WFKQ8imj02yHP+nWhRRiwYQF1YcJSJZidQwYI4B4tEVMqJlrNONGBffG6Foqo4MprJOdGCeyc9Y3KVTY+FVOBzYK8xtzmGIM/5GrjC3rebWBHFOfzT2Slh3boUZs9WwHEqZs9WsG5dquayzk4hEV0GBpMiGqM58RK1KyxMS64LBM+c2wQVsOwrXG5YTm1mQxizGiMTRnRIiopdPdZT/oCc42buRDuMc0hKXlFfIc3RIAZMunPYFSsWEreNc5g40UxEW5xIqaqadaLd5bIr0SfaKGD9jP1mB71wNg8LOM9Yi4pRRE+eKyvlggnfpmjQd2FhxoN4EQ0xgnCQ993iLpqNczgrLGSt5cwjXpXMRLNcdizEu55Y2D+WgaSoaK3XRHTEg/g1q/eoxtjvSDCAjsaIrw4dXk7m0oZ9PznR3unslPDSS2Po6RnFSy+NTVkBDZCILguuMtEZ2dG0QiMntccRDQYq1i+aiejp9WHMa45NmDjHQy92Y9UDO4oErBE9CmGaic4WEpWMc8iWhYWA1vmjOM4hI+YqzmEdRzBzosNCACGbbhpJUYGsFo/8tqMhXCEnOnuwaowIGEvLrjKMRvRx7DyHeMQ6DmMGE3ENEQFvT6KMf7lgv4tpdSH/Ijr7WXrJRIeymWg/wpX91jQR7b2wENCEaKXiHJKi6GuIeugTbWxvBxidaOfbMbvKJgQ48Jy7kyKvpCQFQZ5DgOMwpynqK87BTsTcnkQAWvtScqKJckAi2ieSrGhtyvLiHAGkRBmqiVgYy7iPcwT5AE6b3VixXHTvaBoBTnNc57VEsX8g6Vn4lJOtb/RCUe1zwUnd6bB2oktnolXbTHRzVMsSSwZ3Mym6KyyMhXhwKOVE57bHcRzikSCGLN47i4W4daJHSwxwKQfs4NxSF4IKeMqCAoaiKCFgG4cxg/UKPnZ63YS5slJJmGgth4hOe3AARcPfTotQ+MhEZ7RMdH1YcJTvFvUoibkTXak4hyir+hpiQc1ocfPb68nG7Nr9ZKItiqaDfKAihXYZOeeEz2mO4sCg92NLLs7hrrAwxHOIBHlyoomyQCLaJ4Op/B7RgOYyyKr5jzuRkVHnQugwzpjThL39CfSOjn94v3csg2l1IfABDvOao0hLij4pq1ocHk7htcNalMPOxcp15zAR0YKzHrVaBwh7J1oF8jLqSdG+93QhAY5DfVgwFYFJkxZ3gL1zzGISbjPRKvz3bi4FcyGnZXtse3095nyG+IDrwkJRUcAHOBzTEsX+CXJlpZKwE7PpdaEydEjxnokO8f5zyElR0btzOHGiRTsn2qYdabmRlPw4hwp3eeYiJ5p3n4m2at8ZFgIVcaIzhqLtOU3asYXV4LiF7cfdfg/DAu9pUA1BmEEi2ieF0wqBnPgpjHQoqoqEy8v+jDPnNgEAth8Y/1z00dEMptdp463ntWitiKrt3v3hzT79v+0KclKiDA7m0wbDTgsLbVrcAUBzdvT3QJ6Idv93jYd5cydaLHaiAU30WmWYmZi0GrZiBhPc492hg102ZZ+b17Z6eiY6O/bbzbZEWUUwwGFecwxDKalobLsb1v/tHTz2Wo/n51cDdmLWEgshJSl5V1Hc4qVPdIb1SA5wiAjWhdelULP7UNYnOiOrJS/LS7ICnoPpQBK/RY5uEGVFd6LZSb6bqzI9w2mEhYBef8NMAbdxBksnugIi2tg+dE5zFADQ7TEX7eVkLpV9/yEhQE40URZIRPtkyERER7M7iUKxx3aYboQOg7UEOliB9ly9YwYRnd3RVTsX/Yc3juouTtLmUnBK0lrNmQ2zyRUW+mtxx0aKG4WY28JCAFkn2iQTnW1DVVgIFY8IloWFepzDTZ9ol0LUK+xg1aI70d4u5TM3NSxwtnEYM5iAmdfi//v8yN8O4d4XDnh+fjVgJ2bsb5DwUeDpJYsqZrO4nM+OGKKsTehjTjRQWoiKsmpaVAjAd7s9NxQ60YC9IVBIz0garfUhfd/mtTuHWeehEM9VxIlOizknfG722OK1V7TXTHRYCCDMBygTTZQFEtE+MXOiczvI/B8pyyJ6Gd8tZPur+u3xmhRl3Pj467j2t69YPqZ3NIPp9ZqInlYXQl2Ir6oT3TuWwV8PDuPs+S0Aij9XI5qYNf9aM+emVB4z7aDFHQD0ZwscJVmBKKuIhdz9nKym7qUs3kOjzXCUXCbaRZ9oBwNcyoGeifbrRBtytXZxGDMkRUWQ15xowN+VlYysYG9fwtfo6kqTynacYTEYr7l0wNgn2k1hoaL3adY6Ynh7/YQhrsVicaU6vhjFayEVjXPIqv4ZeHGij4zmekQDhky0GxEtKQibnFCEhMqISqOIb60Pa23ufIpot5lo5kRTnIMoBySifZIT0TnxYhXnYDtMN26hEactnazY15/Aqgd24NFXe/C/e/pNd+CSrGAgKWJGnbaz5jgOc5ujVXWin3qzFyqAZSe1AbDPNKdssslO4xzajtb6b8TcPPa3Z6LezbAVQGtzZ9onWlJMW/TFI9bDUbyI6AYHo8TLQbET7S8TzURAPMw73pYoa+7+zMYIhADn6/uclhQoKvDG0THP26g07EpJTnh63494aS0myqruQEZ8tLhj+9RYkNc70ZTaJxpjFIVUtLDQ0J0jZnGMsMM4aAXw5kRbGQRBPlCRYSsZQ/tQPsBhdmPUc5s7L3EOVu8S4inOQZQHEtE+YUKqsaA7B1C8g2RFMF6caACOC2nM2PbGUVxx/w70J0R88rRZAGBaYMXa203LOtGAdtmtmqO/n/x7L+Y2R/GemXEA9geepChb9njmAxyCPOc7ztEYCYID9DZ3bD2u4xwWw05SFp0+GiLacAmzPCuLSMRdTSwsPcClHLCDc0s2IuQ1zqG3uMueYNSFBYw4LSzMdkYQAlprLb/jYxTjlwAAIABJREFUhgFgd4me5RMJ5kSzCISf4kIvfaIzBiGrRSi8CRh24h8N5U4ISu0TRUUtmlbIqGiLO0OsJMqiKA5FtKyo6C1wovU+0S7/DlaFhZUQlWlJzhPxczweW1RV1fcHboetRIQAwgK1uCPKA4lonwwmJdSF+DynI2rhMjDHxG2faEZdyNmELiOqquIHf9qDr/9+F46dHsN9nz4NHztlJgDzS9ps5PeMupyIntcSw+HhdFUuXw8lRWw/MIRzFkw3OPw23Tkk+/HbEYG3jXPIijai2uySJ4MPcGiICHphYcLgjrkhHhZML0VbuekswzxqIrxHMxJ4znxSoxUNEe3Eb9ydaFZYGPXnRBtb3AHa5+eqsDArpOY2R33FOZiI3tUz6nkblSadLcaLOXRv7cj1iXbX4i5kiHOkJcW0BWgpjE4024+WirhJslI0rZARFvwNfnGDaMxEs32Zw79D71gGsop8J9pjd46wUPxZBCuUEU4brkgAWoeOg0Mp123uJEUFM87dOOjsKmNICCBdAeedqH1IRPukcNAKAEux5ycTDQB1Yfdxjjd7x3D/9m6sWNiGn33yVLQ3RDCnKQoO5sVVrN3QdIMTPa85ChXwNV3KK3/e0wdZUXHugumWJydGrPLEjEjQ3gVjAsHOiQa0fC9zonNt9VxmokO86fCRlGTuprMM81CquLhwNC2jLiyYFlRaEQ0GwAesB7iUC+YU1YV5hIWAjzhHrk0aYB2HMUNSck7ovBbtErLXDhXsO/L6kckjorUWjAYn2oeIzl1GdzdshX3+EQ8xBEbOiXb+XuwKCyPByk0slIzdObL1E06daNbertUgooM8Bw5eRHTx8SfMV77FHQDMaY54aqFqfM9unWg9zkFONFEGSET7xExEW+XdWEW822Erxu26vQw7lNQev2xhW97l1JkW47z1aYUFTjRQnTZ3T77Ri/Z4GCe21YMPcAjxXMlMtL0TbV/UpE+0KiGim2LBIifadSY626e50ElLiQrCJttqZM6xyXdgNC25ztpzHFeRqYW5HsGa8PE6+psNg2B58fqIcxFtHLk8rzkGSVFxaCjleg2Kqurb2tM7NmmKC9mJWa6jhf/uHG7HfjMHkn23vYjoPCfa4cAd28LCbJzDrSu+fyCJR3YecvUcoxNdF2QFns4+gyMFPaIB7ffrtkDOqjtHkOcq4sgXtg+d06R16HBr0BiNEE/dOajFHVEmSET7ZCgpojmWL6Kjeiu1gjgH6+Xr2Yl2H+dgecHCcdDzmqOm4497xzLatMJYfiYaqHybu7GMhOffHsA5C6brDms0yJfuzmEjgEtdvmX3lXKim6NBffy418JCq17HLL9aSM6JNhfRXlonxiPC+PeJlvOHpIyk/GWimQioD5n32TbDWFzmp80dO2Cf2FYPWdWu9EwGWESIfefKEudwk8WV8jPRgEcn2nDCWu/YibYrLOShqHB9VeKx13rw3S1/d/U82ZDNjro8mSkctMKIuOyqkbEYthISAq66XHglJcp5r8+OLW47dBgjeW6uiKTEXGEhdecgygGJaJ8MJsW8okLAmInO/5GyA4D3TDTvujWVVYRkXksM+wcSRQ5M72gGzbFQnnMTDfJoi4cr7kQ/vacfGVmLcjAi2XG5VqQk+8mBpeIcjkV0LJgrLMx4dKItnLSUKJt257DrpjGakV115jBucyTtffCIE0Qp50TXW+TAnZAxyUSbxWFM12AQMH7a3LHvxymzGgFMnlw0687BvqN+WmUaW4s5zbKKsoJQNovLThC9FBcmDfuzsBAAz/ksLHTYO74Q9hm4uRLBOsQAWiSJ55x35+gZSSMaDBQVDrtxolVVRUZWTTPRoQoNW8nIap4T3hoPI8Rz2D/g7qqQ7zhHhVr6EbUPiWifDCZFNEXyRXRYCIBDcd5tNC1DCHAlowJWaIWF7gSIXsxYMGp8XnMUSVHBkYKRq71jmbyiQuPjzZzr8eQPf+9FSyyIk2c16LdFg/ZxjFQJJzoiBJC2eX7GhRM9nJIgKap+IIy67hOt/U0K3dSkTXcOABg2zUS7j3MAmhAdfyda+0yDAod6F23pirYjaZPnmBCxisOYoRWXaZ9pUyyIxojgyYlmB++5zRE0RYOTpkOHVnCrZeCjwYDnExkg//K5U/cybZqJdi/kE4arPhzHaVfnfBUWelsLE25uTA1JyWWzOY5DNMTr76cUrL1dYc1DWHAufo1XhAoJVSkTHeA4dDRFXU8tNJ70uGtxp2XCKc6RY/16AYsW1aGtrR6LFtVh/XpvJt9UhUS0D1KijKSo5PWIBrI7yCBfJPYSGclzlAPQRJeTMbdGWIa60P3WL2n35wuJo6PpvKLC3ONjeLu/2LkeLzKSgqf39uOcBdPzxvVGg7xtMU6p7hzhEiOHc23USjnRIajQ4jx++kQDxU502sJNZ905zETvWFry4UT7E9HX/+41/OipvZb3GzPRbooBC0kVFEWx9+tEEGrFZbnv0dzmmCcnOld4yuOEtvpJ40Qbr2546fKTt63syQzg3AXMy0QLPjLRBVd9nLT9tC0szK7FrSvO1u60MFBfh2FfFgvyjrtzHB1NY0Z9uOh2N7GEwjhU3nYq5Mym5eL2oXObotjvUkR7caK1tngKwkGKczDWrxfQ1RVBd3cAqsqhuzuArq4ICWkXkIj2AcumFhYWAtplQrMWd35ENCtYdON+jGWy7nfB5Uz9knaBu2wc+Z3/+CjGMjL6EuN76Z/x8qFhJEUF//CulrzbIzaZaFlRswK0RHcOG/cnbRB8drAc/EBSzCt2coPbTLTABxALmueAvcY54j4LC1VVxXP7BvBmr7WYzMgqOGgOcp3FqHMnZAoGRbCTECfrF5X8XOy8Fm9XVoxxnxPb6rGnLzEpDsYpMfe78BILY6iqdhLPvmtO37uWxc3GOTxGKABNtEaEgH5i7eSEwK6w0OkApkKYcHMzLEUq+A6WMgSMjKZl/UqUkbAL8cseZ7ZvCfLcuDuzkqKNbC/ct85pjuLgYNJVmzsvmWhRVqFCe/8hIaCvZyqzdm0YyWT+byOZ5LB2bfEJm19q1fEmEe2DwUTxyG+GWQFcIiN7Kv5iOB1za4QJ98LLgDPqQ4gF+TwnWlJUDCREcxFt4VyPF9v3DyLAAYtmN+bdbhfnYAf0Ut057C7duiksBLTvQFKUwTl4TiE5Jzq3HkW1PxGIR4SiwkJVVbNOtPsTNOZEu+3TyugdyyAhyrZiSsyKX47jXPV2LiRj6DUMWMdhTNcgq3mX9Oc1R9E3lnHtihu7t5zQFoesqHjz6MR2o1VV1bpzMPc27D4WxpAUTYiw/ZgbJ7ochYVJUc6r79C6vfibWOhlLUy4uRHRRU50yL6+wwjLtBcSLrE/M1LYZ71wO+M9sdAqKtfRGEFGVvUZBU7w4kTrv10+oM8BqESEZSJz8KD5yaXV7V6pZcebRLQPciO/zUV0UXeOjOTarTTCIhnunGjzCElunHfOjesfy0CFJrAL0dvcVSgXvf3AIE5sixe5q1GbwkJ2u93I7kiwRJxDZG6N/d+JOdH9iUw2w1x8olKKOhMnOi3Zv36DyZTDpKhAVos7sDghHglCUd19p4ywSISdCNGm1WmfTX1Y647i5eBVOEnSKg5jhmRYA+D9+5wpcKKBiV9cqBUA5hzIWLY/uRfY35l99k6FV8YwZMNrDhnQvqfGk+S6cOm2n3aFhSGPa2Hfg6TDFnWAdgJiXEc06PyKQFKUEbUQv6z1YykyknUmOsgHII+zM2slor10jDHub5w68caonpeR6eUiJcp48o2jFX9dMzo6zP/eVrcX4tRdrqTjXWlIRPvAXkQHinaQYxm5qMDPDV4GJdi53/NaothvcJaPspHfdcVf7LZ4GGEhUBEnOinKePnQCM6Y21R0n12cg43vtRt6Ehbs4xyFHSCsYCJ6MBvnsIuQWCEEOMSC+YV2uRHi5tubUR8qKsJhz/fkRNvkrJ3AivNKiWh24GZC30suunBQRL2Jk2+FqOTnYr1eWWFuXpgPoD0eRmNEwO4JLqILx9LXh9wPbWLkRLS2LacRANFwEhP2mEMGip3oeidxDkNXjEK8Dn5h79tpHENVNYHq1Ym2qvUI8c4L5OyKpivhzLL9c6GIt2oJa7st0ehEOxN8KcP7Z/v3ahQX/uHNXlz/+12uiynHgzVr0ohG8z+/aFTFmjWlh9+4cZcr5XhXAxLRPijlRJtNLIwF/cQ52Bm7cwEyapPDntccwyHDOO/ebKcOMyc6wHGY0xTF9v2DeGuce+P+9eAQZEXFmXOKRXTUZlgK+7xtW9xlL39aFUimHMY5GiNBcAAGElphoduiQkZ9mM9zllMl3sNpHY3Y05fIu/TJ4j2eMtE2bfOc4MyJznVmYK/nJRddOCgibpEpN6MwzjG7MYoA596JNsY5OI7LFhdO7A4d7DvNnEwtE+2vzSD7rjnO4xr+dn5a3Jk60Q4mFpaKc7gtqtMz0Q5PRlg/6aJMtIPn20W8tL73/uMcwQo4s3p3kILXt5rwa4f+nQ46P4kwRvXYSUM1nGh2FWi8uyI5obNTwrp1KcyerYDjVMyerWDduhQ6O0uvzY277NfxnsiQiPbBYFIEh5wwMBIN8vqZNyPh14n20ON1LC1Z9qWemx3n3T2o9ejsHdPOPs0y0QDwsZPbsacvgUvveRFXPrgDv915yHO20o4X3h5EkOdwakdD0X12cQ7Wus7OiY4Eecg2wxUykvWBxggf4NAY1aYWJjOy51Hu8YiQl+lk3xmrNn1nzmsGALx4YFC/jQlSL3l7vW2ex17RzIm2c5FEQwyDfRe9tFjLSArChsvhZnEYyzUU5GJDQgAzGyLY77JDR6Gbd0JbHG/1JSZ0z9lUgRPtpzsHizvFXWaijSdSvjPRRhEdEkrGOewLC711CmERCqdONHNLi7pzOHh+yqb7T1jgXMcZzFvccdl1jqOItihszM1VcBPn0B4bDwsuvoO5zjrVdKLZd208jp1e6OyU8NJLY+jpGcVLL405EtCAO3fZj+M90SER7YPBpIiGiJDXgo1h3p3DX4s7JsDd/PjsOoIUTm7rHc2AA9BiIaI/uagDj/3T+7F68XyMZWT8x5a/44KfPpcn6MrB9gODOHlmg6kbGw1qbf7MsntJB3lmvRrfwvVIW+zozdCmFmbjHCUy1FYUFtqVcqLf3VqP+jCP7Xkimk2l9NYnGhhvJzo/E+319dKSmhfnMIvDWFGYRwVYhw6XcY4CEX1iW71WXDiBJxfq3yl2IhPWivG8tKtMFzrRDkSIorKuDCzOkRXRHkamJ0RZn/YHaK56SlJsJwc6KSwc7+4ckqI93hgp0vpEl35+YRzHSEiwHx5lhGWizfZtTFiPZ3GhlRPuJc7Bfof1YcHxmtOG34H+fqtw8quLaB8DjyYCbtxlP473RIdEtA8Gk5JplAMovlQnKyqSouJPRIfcF2CM2bikcwsmt/WOZdAcC1q6NoDWH/lTZ8zGr644HXdd9l7EwwJ+/tx+x+spxXBKxO6eUdM8NJDLCpsdvJxkonOXku07fDjptNEUC+ot7mIuB60w6sMCRo1xjhJOtBDgsGh2E17YbyKi/TjRHkRtRlJwaFi7imHbncNQVKYXA3pwQtOSXHQAdjq8RZSVol7BLbGQ6/dd2ALxhGxx4UQeupL7XWj7gViQ19tBusVLYSETKoVOtNeJhTHD75tdjbCLp5idQDG8uuJplyLa3IkOIOngZCZpc4UtLPDO4ww2cY5KiEorJ5x9L9303E5LWs5dM1U8xDmyUxurEedgn4OfXu0TAbfuslfHe6Ljq7/I6tWrsXevNmRhZGQE8XgcGzZsKHrcueeei7q6OgQCAfA8j0ceeQQAMDg4iGuvvRYHDx5ER0cHbr31VjQ2NhY9f6IymBJtRbTR7dR7CXsc+a1tU5uE6K6w0DrOEQvxaK0P5Zxoix7RZnAch5NnNeATp3Xgx3/eizd7x3Dc9DrH67LipQNDUAHTPDSQ2+GmxOK+yMyJDtuO/ba/fJuWFb2ncSlaYkG81TsGIRDANIefWyH1YQF7+3JuaCknGgDOmNuEp97qw6HhFGY2RHRB6isT7aHQr3soCUUFZjVGcGgoBVVVTTuUpA1OoF4M6EW0GwoUGfGIgJESjo6saN0pCqfWRWzy9ZZrKDjJmtUQQUNEmNAdOgqLVesM3RDsvmdmsPfProo5EV1iwaQ8juOyXSXcC5ixwkx01iDQ+iib74u1cdvlbXHndmKhnokuGBwlq7Acxc2wi3O4GRqiR9XM4hwViDdYFTZ6zUSHhQBCPOc4zqHXuwQDUKD9PaoR52Dr8Dp0aqKgieAU1q4N4+BBDh0dmoCuFXHsFF9O9K233ooNGzZgw4YNWLp0KZYsWWL52HvuuQcbNmzQBTQA3H777fjABz6AJ554Ah/4wAdw++23+1lOxRlIZPQuDYVEs5XXzGXQx2/7cKK1MbfOK+t199smhz23JTe5rXc0YzoVy46LT25HWAjgVy8ddPU8K17YP4iIEMDCmXHT+6M2O9yUk0x0qTiHqO2cnbSra8rGORIWPVydUDjBz8l7YCcY27Nu9JiP7hyxIA+e8+ZEs+/N8TPqoMK6Sl40DNrIOdEeM9EFYqM+VLrvNDvIFl7SL9Xu0IzCKxUcx+GE1vqqd+h4Zyil960vJFUQc2L7IC9tDZmb6SYTnTH5/CMeRXRxd47SETetsLC8Y7/1FneOnWgW58jvzgGULk60i3NEhEC2haHzKwJmV9lycY7xdKJV09ePGYwR59uSERYCCPIBPabi5Dns9XPOe+UL23KZ6MntRAO16y67oSxxDlVVsWnTJixfvtzV87Zt24aPfexjAICPfexj2Lp1azmWUzEGEiJaYuYOZFQIQEVxEYEfEQ1oO5xShTSMhAPhPq9Zy4WqqoqjLpxoRlM0iPNPbMWmXUf0biV+eOHAIN47u9Eywxi1iXM4y0Sz9lrmO7CMyVhaK5qjQQynJIylvff/jmfjCOxki4k6u/cwf3oMzdGgnoseTUsIcO4nJgKaCIxHgp6caNYe7vgZWqTBShQZOzPEdOfQ/esVjv0GsoWZJU4Acp0Rip3otKS4GjRjVnh6Qlscb/aOVbW48CuPvIwfPrXH9D79O6VPLHTf5YdRHOdw4kQzBzT3+Yc9XAWQZAUZWS1worPvxeJqhJwdDmN1ZUkIcAhw7mMMLMaScNgnOudE53fnAErHGOwiXrqD7GD9tnGO7Mnp+Ipo87HjdhE9620p+uRBt8NWjCI6XQUneqIVFhL+KIuI3r59O6ZNm4ZjjjnG8jFXXXUVLrnkEvzqV7/Sb+vr60NraysAYMaMGejr6yvHciqCrKgYTIrWTrR+dp1/2c8qWuEUbdqYs52NE+E+ryWG0bSM3rEMBhIZTDdpb1eKS0/rQFpS8LuXD7t+rpHesQz29iUsoxyA8dJf8WeQLsh+mj+/VGGh7FxEx0JQoY1/99In+v9n792DJTnrK8GTj6qs531239uiu/VESDKWjRvkh8BgHpIhQMC6AT8iZlcOAsJhJmzcnhkHiFl7jBULI6/WESZiZpeZCBwxHjN4GyEW8IaFsQeQwF4sHubpAYSkbqm71X1ffW+98rV/ZH6ZWZnf4/dl1b11b3eeCIfR7XursqqyMs93vvM7B4jsDX6YLgAGua13HkzDwEuuXcBXntpAGIbYHvpo123tsheGuYZdTole7+NQu558B0RqXtYTbZkG2nVLacHgIR9xB0TvH1WJzm/ps3NJh0AN4yFJM/Ne37bagReE+MGl2QwXun6Ap9b7Sc57Hnkls0zePAN7rzo6nmhOtFmjZmkr0ew7MtZY6Mhfi2gXgoFZS3Z9sJB5ojlKtIpE96XpHHQ7SraxLw+VJ/rC5SH++rsXlM8hQ5LBn3t+M/4MdOwcLDO+ppGTnZJoS2vxMW3MSom+Umu3Zw3lu3jvvffi4sWLhZ+/+93vxmte8xoAwKc+9SmpCv0Xf/EXWF1dxaVLl/Drv/7ruPHGG3HHHXeM/Y5hGKVJwCywNXARhJEvloesyrCAWqKUTKpEd+r0lqsdAnG/bjFK6Pja2S0EoTjeTobnH27jJcfn8bGvPYNfe8kxkp+Yh3+M7QmioUKguDjJIm0sVNs5hJ5or0jURMguoMoq0Z1MTFurbpGUaCB6jx753nN4cr2P7VG5ym+GrlNsQaTgybU+rltqKgfFRrl0hE7OwkLFyON4ogmPxWwmPCUaiM4lqh1nyDmG65ejAd2n1/u4bZVvQ9pNPLs1RBCKE0/ScypN5wBKZnXnlWgCCeGRpzKe6J5bXCSrVHXRLkQWUdayrhJdMp2Do0Sr7BwDzutm0GneE0XMAekiQ7Qo+n++dQ7/8dEncecNS6VmL1TPL4su5YHlZut4orPJS64/exK9l55oVozCcp3PnDFw6lQDwJWRkDFLKL8NH/nIR6T/7nkeHnnkkTGvcx6rq6sAgOXlZdx11134xje+gTvuuAPLy8u4cOECVlZWcOHCBSwtLekd/QyxFvsPFwV2jvwW1U4yWDgZiY4yXmknfUKiJQSLxdyxmDpe0QoFv/xTR/GvP/ltfP77F/GqFxwu9Rj/39Mb6Do2blnpCH9HZucYxH5mXuQgAxs6lKVz6Ng50uMq74kGogvqatfJDBbKjyHri94eFocstY6hpBL91HoPr3rBobSwQnAzG2U80QA9USOLMAy5A1idjB1GtAh3A6ZG5kg025XwfAD8xXAeI875wRZQKiLzHx/9EX7q6Dx+5vpF0nNRcXYz8qaLFPk8CZvEzsEIeacRPRaFwPDU4IZtCr+DIjCyOZ4THS8IFEq0aLAQ0Cf0QRgmCzPtdI6sEk20c8jSORqK714WQz+AaYB7fWRkXPR5MhHowvaw9LVmKChbAaLXptdYmPFEUyPuMnaOoTdLO8fep3PIilEqEj0ZJrZzPPbYY7jxxhtx5MgR7r/3ej1sb28n//vRRx/FzTffDCBK7fjEJz4BAPjEJz6BV7/61ZMezp5hPSbRIiWakWV2YWA+5knKVtjjUuPBUjuH+KJ3pNtA3TISEl1GiQaAn79pGc+bc/DRrz5T6u+BaKjwxcfnpSQ4sXNwbsBRXrP8lFYOFnJ8tyJklehm2bKVDIkGotdgGep0kGMLDax2HXzl6Q1sD71SGdEMc46NywM9P/tGz8XmwMN1iy1lYUVeiaaox3lkt2Kz6ObsMDwkSnTezmGLdzXEx1G0+1Aj2/7LV87gP335SfJzUcHKkoRKtOvDNNJFxCSDhUljYZ3uiU595OOe6NJKNM/OITifRLsQWegeS3aAdqJ0DvJgoTixh6n7FDsK28nhLTYTj7DgcRiRv3C5fDkGywXn2UkanIZf6WMl6RymVtmMGV9byzZVTgPsOfeSRF/JtduzxsQk+jOf+Qxe//rXj/3s/PnzeMc73gEg8j3/2q/9Gt74xjfirW99K17xilfg5S9/OQDgne98Jx599FHcfffdeOyxx/DOd75z0sPZM6z1Iv+hyhPdz3uiJ6j9BqIbIHWwkGIhsUwDxxeb+FGctHBIM50j+zhv/amj+OqZTXzvgn5SwdnNPp7ZHOAlEj80oEjn8NTb8qqc6JE/3oonwxiJLu2JjstH4s+UvQaVtcnI+KIvD71SbYUMZZRoFot43VIztcgIboKuH44Rz8jOoZmGIBiKytphRPBEdo6a/FzgYeiFBRLAHkdGxMK4uvnrZ7dwUeBdLoszG6kSzcscHngBGnZ6Tk3iiWYqWrtuwUC5iDugnIUiiQnNfMdbNUsa+8nIq2xR6th0IgaMq7W66RzZxaS+Ei32RJNsNZJdNlVjYT9+/Avb5c9d0XcY0LdzsCHjmmWQPdEsFs8wjD1JI5EdByBe+O0GruTa7VljYmf5Bz7wgcLPVldX8eEPfxgAcPz4cXzyk5/k/u3i4iL+7M/+bNJDmAkSJbopsnOMXyDZRX5iO4djk0PpqYkg1y228IOLPRgAlgWLAgre+OOr+D8f/RH+2+Nn8b++9hbp757d7KOfmWz/wg+joVKZHxqQt1sNXF9JZpU50V6QqGwqzDdqMACEKG/nyJPAgUZc3h3HF/Dpb53H9tDDTRNkdM81bKUlIg8Wb3fdYguXYlJIVaLbdQtPaN5AkniuHBHO22F4cDltcUA5JZqX3pIkvki+l+y9CQH89+9fxMmffB75OVU4GyvRXhBi4AWFczHyfI/7kS2jnJ1j5AXRTokVJSPQBgs5do6aqfW+A6kQkVWiVbGfqsFCQF+JZr9rmwb5Wswj84kSrUrncH0YGE83YdDxRA85g7nFx+F/noNpKNFe1Fppcq4xunaOrBKt44lm31W2oJ5N2creK9H33Tcc80QDs6/dPn3aviIypqvxzJJY67swDWCuyX8L82RvZ+SjZhnkoTURIiXaJxEeymAhkPqiF5q1AtHQwVyjhtf92Ao+/a3zeO9dNwsf67vnL+Nf/JevFn5+qF3HjfGQlgipEs1rLAyUA3mU2u+lFu09sEwD880aNvpueU90g5HA6PUM4ugmCtiCww9TMlnqGGJLxM6I7q1+cr0H2zRwzXwjyXwWbSm7/rgnupSdwxfbOQD5kI5wsLCUEl20c9imAds0pFvq2X/73D9Pl0SfiT3RQGTpyJ+L/dzCLCKedqna4aEXJtcwKoERRdzpZjPzlGggnhMR2TlIg4V6x8JeD/vuU67FvHMwUaJVg4Xxwoj3HA0NJZo3FMvAfi5UohmJ3i5PunjpOgzNmoWLGio3i7irxQs5ymeQnXdhqSxXSzrHfitGuZIGHSsSXRLrvREWmjXuqhpIL5DJYKGkOVAH7bqFEJGdQaVqU9Xv6+L67zLxdnm84HAHD/nnsN53hcUtT61HN/1Tr7wJq5nnvGG5rbwQ1qxocJBn5+gTlGjbNGAZ0xksBKLhwklINFO9t8eUaNrzr3YdXLvYxFPr/YnSOeb3VrB6AAAgAElEQVQa6TGQSfRaH8cXmmP+Qh4R8VhbYD6dY0RbCDIk8Vyc2m9AbudI1EhBxJ2WEi04Pxo1uZrJFtPL7Tr+8ekNbPTFbac6CMMQZzcGWOnUcWF7hK2hh5WcIs9bmLXrVjLsrIOh5yeEi7qVPkoI5LgarhsrlyjRNc5rEdk5iIOF64KiGh7Y65lv2Li0M4oiHCWNgwDgc9I5qPnIfck1gX0fqJ5osZ1Dbm9g19vnJrBzZM+dPBq2pp0jHixkCzNZtXv6/OOvv64RjzdNzCon+uRJbyKCOk3l+EoadJxKTvTViPWeK616zleZ9kb+xFYOIOtnVJ9oO8OIVMoG9QDg2jjmruxQYRZL8WOsSW5K7Ib12lsP41UvSP/vBoUKzSDa+hu4gbTyG4gUCFlGrTaJju0vZSPu6rYJxzaTobCBq1bTs7gjVqOpFhQeunFdso4v+sn1XrKDIcuq5VUNdx0bfmw9oEJUWTyRJzo+bt6QqghDP+SqaY5tkewcv3jrYfgh8PkfTCcT/1LPxcALkmg93nBhZHOiq7cyZO0s1KGuVInOpnPoe6KZdSJ/HZUlFlEGC3Wqs4H0XGSLIIqlg5fOYRoGmjVTWdjSd4sWHQZVMs7YcUuKpNj7I/o82bl9fgI7x0iyy9asmdoRd45taXmbCyS6ZGvmpGDP6frhTAuadMCU4zNnTIShgTNnTJw61SidNX0lDTpWJLok1nruWMRZHnnbwc7InzgjGlA3dGWxM/LQIpArRobKxttlwTzVbPCSh7XeCJYRbYeWQUswhNLnkAUeorY0cRxbGRJdtmwFGC8MGXhqNT0LNog5kRJNIKJZeEGIMxsDXBvvYMjSORI/7NhgoX5rYZrOkfNE5+wwPLBjKHiiSyjRIjVNVWPNFgw/eXQe18w5+Nv/UczeL4Oz8VDhratRLCTvM+TtbsjUWxmyRITsifaKEYNllGjRgJ3ME00dLNQi0Rk7R/a4ZBAdB2WgjrcIYkhTNdTHILNzRMN2hvDzZMc4mRLNX4AC0ftAPR/YkK5TM5PdDZdQ3523YjkaQ4nTxDBzjd8+IK2FMuW4DK6kQceKRJfEem8kTOYAEA9QpBef3sibDolmkU6ECzeVuM81anjNCw7hzhsmz+lmudlrO2Il+lLPxUKrLrTCqCCKQ6L6iWUZtbpKNFOjyto5AFb9HXuiNYo/AOBnrlvEi47O4cevmSv//DERpSrRz2wO4AVhsviSFdgwFTI7EEhRj/MQRdzl7TA8uJx4sexx6yrivPNDRQrTrGYTr7z5EP7+yfWplC2weLvbjkiUaM6sQGsiEh09FtUTzWssdGwTfhAmdgsKeqOoLTI/JNiJ50R4oAwWNmxLi0yxRQGzQVFi7kTH0apbpHQO0cJaxxM98uRFUrL2P3a93ei7pdVbqZ1DI53D9aMq90bGzlFWid5rJTiI8+6X4vtkmbmEWWDayvF99w3RbI4T5lkPOpZFRaJLYq3nJl8EHgzDiFWGdIhgOp5opkSrb8A9DfX7f7vnx/DqkiUpWSxRlOidkTBfmwKReiNTbLJwapZ4sNAXqzU8sNcxGYlOB+0GnjrreuxvGzY+/CsvwgskBTUqMDJAbS18isXbLRLsHBzy0HHU6rHocfIkIG+H4cETEJhUidZPBcijUZPbObJNlK98/iG4fohHf7hGfl4Rzmz0YQC45XCUzsJXogOOj7i8nYN9BnRPdNHOQc3WzqLv+lzbVLtuCxU9+mChvhK9MC0lmpATLVpYa3miJXYOIHofRIuibPLRcyWHC2XP36yZcP0weZ9kyJam1Caxc2gUtUwLjLQnJPqAKNHTVo5PnvTw4IMDHDsWwDBCHDsW4MEHD95QIVCR6FIYuD52Rr5UiQbGyd7O1D3RNDvHJPnBZdCuW3BsE5ckSnS0AJmERIs90RRbhWjr3QtC+EGopUTffcsK3vlz101kp2hn7RwEX/e0wRIutoikKom3W4rsHLYZ7brwtpTZNmudS6LpF8w04q742WTtMDyIfLF1y4ABPSIn2hJX2TmyN/6fODqH5XYdf/v9yS0dZzYHWO06WIhvyrzFRN/1C+dU21EroDwMvTRHXdcTPR5xR2t5zKInWCS3HbESnSygpthY6GYGCwEaiRaR+VZN/TkMJCVSbFeA8jkMJHaO6NjE70Pf9RP7VtmEDplVrqmxoGW7iI044g4YL8ARIV+kNYt0DnatWW5H97+9TOiYBLuhHJ886eHxx3dw/vw2Hn9850ASaKAi0aWw0Ze3FTJkyd60PNEtncHCkT9Rk10ZGIaBpVYN632xEr3eG0lVfBV4do4wDAtRXrK/59k5GAnUIdHXL7fwjjuvI6dM8NAd80TTI+6mhXbdgmWA3Fr45HoP8w07UeJYeQGPjA45nmhKLJ3ocXjb0Vk7DA+irfRoyFQvnzZS0/ilFxQ7R6NmwjQM/MLzl/HoD9e0npuHsxt9HFtowDYNtOsWX4kWpXOU2EoeZe0cE3qiAT0S3R/53GbQdmyJ8DkqJm+gLw9GonlFNTwMc55o1WAgIE4JadYJnmhO9jdDXSPvWDXvIVKi/SCyILAB9AuXy/miRUO5QJq4QlmQZK1d7LpSerBwjz3R7NiZAKdbOlUWp0/bOHGijdXVDk6caJcaCGw0QkRJ9yGWlg6ucjxtVCS6BFjyxKKCCGbJXm/kTUWJ7ugMFg6n85y6WGrVhZ7oMAxxSWGFUYFn5xhlfHIqiAYLRxm1cC+RtXNE1eV7v/DpOPTWwifX+okqxSBS83gZwaUGC13xZ6PKnZZt6eukRCQDTZw4syjxhWbnAIBX3nwIAy/Al360TnpuEc5uDnB0ISI3Hcfm7ibw0znExFOGYcZXq+OJjnYr0vdN1RzKQ09i5wD4BIwyWKhTWAIAbvx78w19OwdXiVbaOcQ2tSTvmGirkXuiDe57wF4fs2+VtXOoPNHRc9EUdQBjEXeU85Br59hjJZq9v3tp55g0WYP9/fq6CcAAYBSGDK9mVCS6BJK2QoKdg92o+i69CU8GRoopW7HT8mHrYqlVwyWBJ7rn+hh6QbKdVQY8O4esGjcP0WDhcEYkuhOTwCAmaWUrxCfBXENuicjiyfV+MlTIICLRPD9sOlio74nm2TnaSjuHeEtfR4n248xroRItIQDs35jd6MXH5jHfsPG5CVI6dkYe1noujs03AMTNk7mFUBCGAiWabkXIImtnoXqiXc6cgSzRRQSZEg3wF2XUxkKdY0k90fFgISnijinROU80QYmW5UQD9Ii+kRdwvz/Zx+HZIrIZ5+26VTrmjmLn0FOi9T3R2e8BdfExTbCFdkqid1+JnjRZY9rJHFcaKhJdAmxoTu2Jjm7QSdPWFFTherz6Vm0DhWE4NQuJLpZadWFONFOoJ1eixy9+yXY5JZ1DkBMtKvTYbXQcCyM/TPysOukc00K3USMp0dtDD5d2RokqxSB6T3me6IYdZZeXibjj2znkJFqUEx0dCz1aS2YpUXuix61CtmXi5Tct4ws/uESuLc6D1X0fkyjRTGnjKdGA3m4AENtZYkJH9ZRGte/8ZJShRrygSIlmizIeIaEMFiYJF8TPIYm4Y0o0gQh5QQjLNAq2rzZJiRbbOQC6pzu7i8BD3eLbG9i1tlmzsNJxcKFkzJ0s+Sjf8Ct/nNQalXiiS0Tc6eaDTwPs+RJP9BQSelSYNFnjSsp03g1UJLoEUiVaTgSZ7YDdqKZFaFuScgGGUTzpPBMS3a5hozdCwPEYUhcgMvDarQYunyzwIFINRTFquw3mEX5uJ3pv9toTHR0D30+bx5Pr40OFDColOuuJNgwDnbqlN1go9USr7ByxCsgbCKzJFeQsEiLPfRy+z55hwDm3fvb6ReyMfDxxqUd6/jzObEYk+uhCrERz3oe8As7ABo51hwuHGTWzRkw3cDk2gjSdg/78oqi3JPaTQ0Zpg4V6qnjSWNjUGCyMLS15NBURd64fwA9C6XWtTlBUwzBU2zlsM7GqZJHu8pk43KlPYOcQDzbqKNEDN/0uUSPuWLTcrCPu2Dk217BhmcaeKNGTJmtcSZnOu4GKRJfAWs9FwzaVhI0ppqKmrbKgFCUwkr3X6RxAtLjwQ2CzX1SjL8ULkOWJlOhoiCtL0gcZdUKF/WbnYCT6UqzwTFLcUv4YaEr0k2txvB3HzsG7IY04nmggiubTzYm2TINLRDoqEu2HMADwxEhZZnge7PXxFjkUO0fNGj/+OY10Bx5Y0cqx+ViJbhR97f0kyYCvROsOF5b1RBfjBfUHC0Wtr0nsJ0dYoA4WAvSUFjej7js2rWlPVEvdqllw/VASLcdfBGVBUaI9ZkWS2VoEOdEJia5bWOk6uFDWziEh8TqeaJ6dQ3UejjiL2FnYObKL6U7JrHZdTJqscSVlOu8GKhJdAut9Ws4xywBlN6ppEdposl5OQJLnnImdg2VFF0n0eqxEL03kiS4qR/3kZkNL55CpprIbzW6gE5MpFh2114OFQOyJJpBo5od83lxj7OfRjbx4Q+DlRAPRgKzODSSrgObRqkeKqKi4w/UjAsNLUJFlhufBboAiO4cXiHNu81vJ0d/oNyZmcXZzgPmGnZTlzDnFz1CoRGuk/GSRzfoVDaLlEXmix9/7Up5oUcSdZEGQDvRNzxM9zJzTTYIdA4jeg3wyB4DE4y0i4uznsuuaQ7AlUAQCkcc92eWzLax06ri0MyLlOechr/0u54lm30XVjsiA8/pnaedwbBNtR72jPA1Mmsl8JWU67wb2Xqa8ArDWc5XJHEB04+q7fnKRbU/J69p2bOU2bKJEz4BEL7fj1sLeCDehPfZvzBMtq0xXoZG54Cb5opnsUOXf22mwf1YZ5F1o9wIshvDizgyV6Ebkpw3DUBrXt9Zz0a5bhZu6Y5uJzSkL5lXMv6cdxyKXuwDytrWEkPkB17LhBYGQRDVsE89pKtG840iJmA+bM8zLaw3UIQ48nNnoJ8kcQPQZ9lx/7LxOd2jySrTYRyyCH4Rw/TBZzMjKObIYecX3P1F/iQuIIIyGs/npHOIFgWigL4t65rOjwPWjXRHLNNCsTapER8/dG/mYaxSviVkrhez4VWRQZodicGz+YGF2aHul68APo8KslS59sMwLQvih+PlLeaJtE4zLqxRl3iKCYoOZNrKzEWVjJsvg5ElvItI76d9fyaiU6BJY77kkT2+rFg0tbSfWiinaORRfPnZznE06h7j6+1JvhPmGzSU7VPAyRfuanmigeNOUkaTdBFMSn0vsHDNQoh07SZGRQVR37wii4oRKtCNumeNBNpTEfJYif6PIjwqwpkG9gTJRYyE7Th4GnIQFNqCnU/aSxZmNQZLMAWTytzOLk75g4FbmIxbBzb1+5olW5Su7fljwwjY0Xzv7jHh2DtVgoWkAloREy2rreRh5YaKsRwlM6r/z/IDviVbYGLIqsAiUAU9ZWRGDqGyln7HKHe5ExFnXF82utWpPNN3O0ch4olWLOR6JduI0Et7szm4hawmL7BwVMT3oqEh0CURlITQ7B4CkvW+6nmiFnYOR6CkRdx0wksWLuVvruVhql/dDA/wL7oCw7cmQ1j2PX3hn7Ym+OMvBwpjIbykKV9Z6Lhabxc9PHXE3TiAiH7NuyYlIiZYXTri+XIkmp3NIiIhKWR1OWYn2/ADntgY4tpCS6KS+PWP1Eg3c6jSfMuQTUhghUm3tj7h2Dj31t5dRQ/NgP+PaOSSfff5YqENmo0xkX6uuru0GmBJdPA5VZCklupPiiaYkD4l2FrICxWpMos9rJnSoMvgbGt+FZLCwlo24k5+DQ85OZV3zc58G8naOvSpbqbB7qEi0JsIw1LBzMBIdrdqnpQq3CX5SRrJ525+7DTZ5zPNEr+3QFiAy8CpiB4RtTwaR8sS70O4FEhLNPNEz+swAKIf91gWV7UISLUi0UA0D5iGb7Ff5a13BVjrAlGjajUy2yFKVhww4Snr6N/o38XOXh/BD4Oh8audgiuzWGInmD9y2ktKm8jGD1JIS3iJG1xPNiCpPiLBMA62axd3ZkO1ClD2W7IAcr/iJB9cPuWp4spASXM/7hIFpx1Y371HsHCIlejBm54jue7rDhSqBwjYN1CxDe7CQvR5eqgj/b9LzJ/VTz4JEWyQxrML+R0WiNbE9jDyHNCU6enuZwjgtfzIpnWPKw4w6MOPq77UdnhI9WeU3kN5QeHYOylCeKF5ryDKN95hEO3FucmLnmEnEHVOi5Rf1NYGdQ5ST7Pr8wa6uE53D1MY82WS/6mYoUyN1lGiZ3Udl5xhy7By8xSAVZ+JkjqNZJZpj58g3JTLYZtR0p6NEs/eXnZ/UrfQRp+7ZjpNWqO99knAkWGC2Hf41UaQAZ6GbzpH1eLdq8oi6sePgkGi1Eq0emKYMyMl2UdLHMQRKdCpQLDRrqFmGtp2DKcWya2uTuKAdeFHSjWkY5LIVvp0jjsfbQyU6O3dDEcMq7H9UJFoTLOeYQgSzdo66ZSgv5lS0nch/KkojANJt2s4MBguB6P1Z50TcrQmUTB1w7RyehhIttHOMF2LsFQzDQNexM4OFM1SiJSQ6CENs9GVKND+dgw1hZZH6WGlKjMwT7UzkiTbhB+Jkj/wxZJ9v7BgUdg7eYGFEBMqR6LOb40UrQJrywlOiufnKmkpYkk6SyYkG1FvpWftDFtSSECBVanmNhYA4scgVeJGz0K799tOkGErjYHIcnPdApUQPiHYOFRGkWNXqAo97343eQ9syYRgGDncc7dbC5NoquQc2iHGB2aSbqE5evZDjpnOwz32PlWg7vh5SxLArAadP2zhxoo3V1Q5OnGiT68YPCioSrQmWQEAZLGxmUhdaUxzwo0zW90YeLGPvCSHDUquGSzkleugF2Bn5SXpHWfAUvL4b5wgTFiqirfdZRdwBkTLLvKWzqP3ucghYHlt9D0EIrpUpylwtDunw/LBASqKpnkBZZXGdeaKFEXcyJZqluxBINDs/OJ9PahESkaGgoEQbhsFt36TgzMYAdcvA4U76Wcw5RUuOTMnsODYpno0hr8QnbXEKEuJyGgsB8cKLB6USXbexLRgslLUVAiUGC/30MZs1k/QeCpXomlyJptjUKIsRip0jsUbkFkWDXLTgSqee7JpRQRnapn4X8vMFlNIfbjpHsvjeu8HCrBjAxLCyjaUHAadP2zh1qoEzZ0yEoYEzZ0ycOtW4ooh0RaI1kSrRdDvHpZ3RVKPmWoShoJ2Rj7ZjS+PKdhNL7WL1t857JwMvnWMgaDPjQbT1PvQCWAa/2W630cnYbmaSE+1En4lMiV7riz8/5jXMK2K8ZAYgS6LpSrQy4q6UJ5opyPR8Wm5joSLzmZcTDcQlLRqtfQxnNvo4Ot+Emfl+dzm7CbLoR10lLD8cRlVwRwI/u04ySrbwgwdRYpHOYCGV0GfjFqmeaM8PuIUviZ1D5IkmpA5RSkMo6Rx1gTUi3xQZVX9rKtGSZBuGpqL1kyE/X0Ap/eHtMuoOlE4D2etAmZjJWaKMonz//Q76/fHzvt83cP/99HjE/Y6KRGtiLVGi6XaOtd5oaskcQGrRkG3Fbo/8mQwVMiw1a1jrjca2BplHenJPNC+do7hdLoJo6z1SCWbznjFSaRpQKme7gbZjwYBciZbtwoh8pbyMYCA9h6mthdJ0DoWdw/MDrgoI6CnRsoQBpk4LI+44dg6Arr7lcXZzMOaHBiKibJtGIZ3DFuzQtAilTVnk7SxUT7TL8UQDenYORjJF17SOoLiCMljILAGl0jnihYAqJi1SosV2DtG1nFK2wjzRsqhBSjqHyF/cd4Ox52ethapoQ+7zS0g8NXM7b+2ilP4M3eJ3d1Z2jkZCossVHs0CZRXls2f53z3Rzw8iKhKtCUYkFghlISzbMwin601OVrCSrfCdoTeTeDuGpXYdrh+Obdezyu/peaIzSrSnoUQLBwvFaudugw32NWxrJrsHpmFEVdwyJVqygBS1vonsHEw1pdo5ZJ+NShF1/VC4u5Aq0QQSLcuJVqVzcOwc7Pl1PdFhGMZK9DiJNgyj0DzZ5ww0MogsECLk7Sw6nmjeQko0jMqDikSLVHXKYKFhGPGOAN0TnY24C0FJKAm5SrRlGug4lnCgt8+pi88jUVQln0Nq55A9Dn/QLt8UebhTx8gPsalZlpQ9Vh4ifznFzuFrK9G8764qX343kBVq2ND/XhWuTIKyivLRo/xz0jRxxVg6KhKtiTVWFqJQN4DxWKKpeqJZUYLk5tsb+TMpWmFIq79T71xa+T2ZEl2PB7Ly6RzUgTxZTvSsPOQJiZ6BHzp7DDJlmH1+yxIlOk8mXEGqRqdeYrBQGHEnn9CX2jkSJZq2jWyA334ns3OEYYiB53MtFU0NSwPDWs9F3w3GhgoZOrnPUKSAA+XtHPVEiaaREF7tN6BnZemp7BxCJVo9WBgdC78siIehF2Q80XI7BkO+HTWLOcn3buD6yh02SuMiJZ1DtCjKW+VW46ZCnZg7XsRcHlRrTFbNBVjzINUTnT6/MyMlmn1enRJZ7bNCWUX5vvuGaDaLn43vG2Rv9H4fTKxItCbW+y7ZjpC1cOyKJ1pCeHZG/kwqvxmWWWthxhe9lijRk5Fo3kAW5WbDIBokGs2QRHcSJXp2X8m8ipnHWs+FaYBbTyxsgfT5SiBbNFCrvykRd9KyFc5WOqCpRMfnB2+noCGxc3hBiCDkE4hGCU90mszRKPxb/jOUzQq065bWYGF+OIuSsxuGofAcaGgQ177rwzKKpT0MzBOdtxhQBguB6HHp6Rxh8h5QC3MiMs//HLqNmlCJpuywsWuGbDFDIbFiT/S4QJG2FtKHCylKODWzPW+7qwmi+bLgpnPMQInO+rnbmglFs4RIURb9nOHkSQ8PPjiAZXHq5AlK9kEYTKxItCbWiJXfwPgwyDQ90ZSBhJ2RN1MSvdQuKtFswHIaRLWRUy36gu1yHlJPdNHOMTsSHX1Ws4i3Y+g6tjQner3nYqFZ45ZGyO0cvMHC6HVSq78pEXciEuT5MiVabsPIQrbIqkseZ5AkZPCH63Q90Swj+tg8X4neynmiReeUSL0VIT8cRvFEs8SZSSPueiMfzbrY6tSObRX599ITRMvl0ajRCX3WntJUDAYmxyEh813HEi4mKTts6bknPn5KOkaaziG3c6zEiTDnNYYLKUp406YlnQy98Wt9FM2njvizc1GbM2ksdDMkOhHD9r8SzVOUm80Q992nPgdOnvQQCN5ilZJ9EAYTKxKtCWrlNxBtj7Ev7TStFZTK3p2Z2zmiCy2rPAeiBcik8XYMzZyXNFJsNAcL8+kckuG13UZq55gdiZ5v1rDRF6tLoqIVQEKiPf5Wvm2ZaNimstwFiPKpXT+URNzJb4ZuICZSjsDaw4PMl23Gvlpu45skIaNh0xsTGVhG75G54o1kLtcEKbKRANF1xPVDMonID4dRPNGM3Igi7qivve/KB6VFqp7r86PleMdSbrDQTI5PBpmtpNuoCQd68wSWhyQZR0IkEyVYosqzf8u/D/ndjEPtOkyjnJ1DWbZC+AwG7rgnmhpxl7+2s89wb+0c6bFTAgL2C5iifOxYAMMIcexYgAcfHODkSdqxl1WyD8JgYkWiNbFOrPxmYBef3bBz9CRfvp2hP9PBwvlmDQbGleg1jQWICnw7B+10NgyDO9Qkq5bebbBBu1naOVa7UYmCaOpedu47gpQLWUbzQrNGGk5SqWjs5i8bLBSnc9CVaNUiq2GbXDI+SJIBeOkctESCLPquD1OQAd9tjO8mSJVozZt4fjiMEhEmqn0HImWerkQHUjLZEah6svMvCx1VPB9xB6hJtGzAcc4R26go0Z11xU5M9G8h6pYhHVoW2XP67vh7b1smllp1rdbC9NyRe6KHXqBsMc0T4rplEGq/ixGTM1Gis+kcmln5s8bJkx4ef3wH589v4/HHd8gEGiivZJcl33uJiaTKd7/73XjiiScAAJcvX0a328XDDz889js//OEP8Tu/8zvJfz/99NP4rd/6Ldx777340z/9U3zsYx/D0tISAODUqVN4xSteMckh7So8P8DmwCPbOYDowrA9ZUJrGvK2oyAM0XNn64m2TQMLccwdw9qOi+uXW1N5/IZt5dI55DfZPFa6Dn601hv72dALMN+YjXrf2QeDhUe6DkZ+KPT9r/dd3LrS4f6tiFCN/BDzTQmJ5rRa5qEqimDpCsLBQlnZiq4SLSFkokE5Rm5Edg4qeWMYxKSGR4jYcGgYhjAMA33XT9oo88jawhYJX8v8YoZSucwUwho34k7PEy2zxLUFg6qygb7xY6EXv4wy5TFpbbf8dciOo9sQDxb23SBZYItA8UTLZgoYROUjPc68SRRzR/dEp7sYMk90uqCV7aIWPdEmdkby60h+GBHIRGPu8WAhu1Y2bBOmcTCU6EkREe4B7r/fwdmzBo4ejQi0iojfd98Qp041xiwdVBvJXmEixvAnf/Inyf/+wAc+gE6neIO98cYbE2Lt+z5e/vKX46677kr+/d5778Xb3/72SQ5jz7DR149oY8Ru2pnNLUG5AJD682Zp5wAiX/T62GDhCCeOz0/lsfMKnizKi4efvW4Rn/zmubGL2mwHC2NP9IxyqgHgyFw0qHZua8gl0Zd2Stg5BJ5oICLRGwQSTa0sFnqipekcaj8pg+r8EBHi1M4xHSV6IChuASIS7Qch+m6AVj3aHlcr0bTnH8SpFKzgheKJdiU2Ap1YuZ7C1sBeS17Vk332+WNZ76nPRSBaGLBzWlXbnRyHIOIOiIZBh17AtRz0XR8rXbn/k+KJHnq+cpeNN1gYhCGGXlBQw1c6dTy13pc+XhYs6lKmhKeqfgCZ649ftkJRr8fPH92692kgexyGYaBdtw9EOsc0cPKkp6Ves78pQ773ElNhDGEY4q/+6q/whje8Qfp7X/rSl3D8+HEcPXp0Gk+759ApWmFgF4a2M11CGynR/BOJfSmnOcxYBkuteuKJZir+8qsWe1YAACAASURBVITJHAxFOwc94g4A7rxhCQMvwFfPbCQ/E7XK7QX2Q8Qd89ie43gdWWW7KFlFVHstqnwGgPmmrUeiZW1rCiValIyQkGhKKoDCzuEo7BxcJdq2MPJD5RZ2FrJhs6S1MFY2pekcLCqTaufw8yUXdE80v+VRXRLC0B/JlehDgmE3lzhYKFuEZeEH0WeVt3OIaruT4wgk6RxJUk3xuzDgKKh5UG01qsfhpVWwcze/gNFtLaQUWTWTXSHxexnGpL6ROw8pg4VFTzTfA76byB9Hu25pZbVfjZjERrIXmMod+ytf+QqWl5dx/fXXS3/v05/+dIFo//mf/znuuecevOc978Hm5uY0DmfXwJSKJULRCgO7gU2b0MqKEthNcZZ2DiBS7JmdY52p+O3peKIbGQXP8wN4QajlJ37x8Xk4tolHn1hPfrYfcqJ1LCnTxpFY8Tq3NSj8G8uILjdYOJkSrbJzsOeXeqIFRN62opY/iiI6dOV2DlF5iExJz25hUyEjxnO56m9ZTnSLUNqURf6zpJA3N7YG8Ow0onOGB5USfWSuAcs08HROHdUZLKQch5tbFLDrukyJDsNQmhDDPjPecOGAMFhIUVSHHr81MosaK1vJEFJRY+LhTh3bQ58ckUixkzQJQ5q871LdpkXc5b9/hmGgbhlkO8e/+eS38cef+z7pd0XIL8Tbjl5raIX9ByVjuPfee/GGN7yh8H+f/exnk9/51Kc+pVShR6MRPve5z+G1r31t8rNf/dVfxSOPPIKHH34YKysr+MAHPjDBS9l9rPXlRIIHdvGZZmMhIM94ZTfFaavfulhu1xMSvbYznYxohmwwPyNAOgS0UbNw4tg8HntiLfnZLAcLmSd6ViQeiG7mzZqZpD9ksa6wMjGVqWjnEN+8F5o1bA99ddsYwc7hWPx0hTAMlVv61NZAWfU4Oz5uxJ3EzqHjyU4fT0yM2XmUVaLFjYV6do78Tg3z+NJSITgkmr12AnlVpXPYpoGj8w08vZEn0bTBwmhHgGDpyS3oHNuEATnx80MgBL+kB8jsHnCGCyk2tcQTrfgcVNc2ttPjckh0wc7BCleIanRUliRfzDQydg7Z4wDpuQMQ0zlc/ne3rjFQ+q1nt3D668/i4g7dC56FF+9ijCvRV4+d40qFkmV95CMfkf6753l45JFH8PGPf1z6e5///Ofxwhe+EIcOHUp+lv3fb33rW/Ebv/EbqsOZKdZLlIWwC//UlWjHxqVej/tvjFxPm7jrYrFZQ98N0Hd9XGJthVNM52DEI1VL9AjoS29Ywh//7Q9wZqOPYwtN0pbjbqFVt9B1bByaUgRgGRiGgSPdBs5tFW+MKiuTKDbQVXiiAWCz7+JQR+z7pNo5REUnAF8JZaBGa1E80Rc5BRQyOwdFfSs+nphYJarmwIMfREUnIutHh5Dyk8XQGycATMmTLYJkEXei0iMeWE60DMcXmgWfrt5gIYVEs9zr6DHNuPhJZufwkvdAnM4BoBD3GIZhMkQqA/t+qXKiVQt0dnzDDCEV2TmyrYXXL6mnUrOJJiJQkk64SjSh9nvo+VhoFukOJWOaYXPgwQtCPPT1Z/GOO68j/U3+GAAU7Bw69ekV9h8mlr0ee+wx3HjjjThy5Ij09z796U/j9a9//djPLly4kPzvz372s7j55psnPZxdxVrPRc0ykiEwCtKIu+mqwrLBwtTOMevBQpYVPUoU6ekp0ZGdg91oop/pEeA7b4hSYR57Yi1uVgvgSBq1dhOmYeC//s8n8Lafmu28wOqcw/VErysWQZZpwDaLrW8jiRLISPRGX34ToWTMitI52MCRjEg1iHnFQ8+XHoPIzqHKiY5+R0OJlhCrbhKb5UmfF8hmK9OV6PyCSKUC5u0PWVDtHGEYxkq0/HZ1fLGJMxv9MY+1zmAhiUR7RULcrMvrqtlCTpYTDaCQ0DH0AoRQX9cotpohwU7BHicbF5cq0Xk7h15rIc0TrZ5PSJJuxjzRhtLXLHp+aj74wPWT5/6/v/6MkrSLjiF6zmyTsV3ZOQ44JibRn/nMZwrk+Pz583jHO96R/Hev18Njjz2Gu+++e+z3HnjgAdxzzz2455578OUvfxnvec97Jj2cXcV6b4TFZk06YZxHY5eU6I4k4m57nwwWsiHC9Z6bqvhT80RHDWVDL0iVaE0rxPHFJq5dbOLRJ9ak1cx7hSNzjZnaOYDIF833RDMlWvz55YlIGJekiGKt2GOpfNEUT7RIiXYVKiBAj5kb+mEpO4escpkyTJWHrECFkeitoZdRwPnndMM2YRlF8iYCz86iIiGyiDvqUOfQCxCEajJ5fKGJvhvgUma7nTxYSBxyZOdidlekWZM37XnsPRB5ogVKtMhKkQeJRBOsaqkSzfNEF9M5AD07h+r5dewc2fPfsSlKdACH8z5GA6XqwVb2HfmF5y9jrefis//8nPJveMcAjB97xxHfxyscDEwsVfJ8zKurq/jwhz+c/Her1cLf//3fF37vgQcemPTp9xRrPX5+rgxJOscueKJ3RmkebBY7ScTdjAcLM9Xfl3ZcOLY5tai/VsZLylS8Mm1/d96whIe+8WxyA5s1iZ01jsw5WOu5hSHLtZ7688tn7TIVWER+55s0Ek2JuHMsk6vouIGcwADikpTicchjwoQRd9Lab3Psdyjou8GYJzSLTibpgRF6EQkzDCNqyyNuJ/MsAapkBGnEXY3vo8+DETmVKHB8MYpofGqjj0MdB368MKYOFrJjkV1HkkWZnSXR8up2N+48FpH5jsATzR5TFXtJGSyk2DmsuBZ73BPN3+Vr1CzMNWxyayFll49i5xgklohxT7QfRskpluCz5uVEA/JUnyyY5eKuWw7jiUs9fPTxZ/DaW1e0BLWhW7yORZ7oSok+yLi6GYMm1nqu1lAhAPzc9Yt444+vkoZbdNCu2whC/oWTkYmZk2hW/d1zsdYbYbmlp+LLkFxwPb+0JxoA7rxhEUMvwJd+FA0YqrY8r3Qc6UZEJD9cSNmFydsZRgoVeEGXRJeIuEv8qIJ4MSAic5R0DBUREUbceT4sg7+d3yAQh8LjuT6aguOwzKiI6fLQJ5Gw+YaNTYWdJnlejq+V7okWK9EqEt0TWAryOL7QBIAkoYOyC8FAtZakDYzpZ9lSeaIVdg47/szy6RyJHUdxXTMNAzXLkNZXq4ZiGerWuCVrIHnvl1v1ZFZChSHJE10ynYMzEMn7O97rp9o5tuL4wYVmDb984ii+fe4yvvnsZeXfqY697UQLMJ2Iywr7C1c3Y9DEeona6p++bhH/9hdvmfqxMFWGF3PXG0VT9JRtzN0Ee6/WYk/00hSH5hqZC25ZTzQAnDi2AMc28bl/vgigUqKTrOicpWOt5yo/v3wDnSyZAQAWYgVOaecgeqL5do6YwEyoREeeebmdoxEr8XlLAMsw5y1AdMpeksdTqKVdx8blgYshYXE516glBEGFiIgVCytkxJNF3Mk80aoFTH8UPb5KiT4y14BtGnhqPTp3VeQ1C0rCRfTvxdfTrFtSS4qrsHMA6WeWhUgF5kHl6aYmD+WLS2SWkm7D5sby8cA7d/JoZnYXRRhwiCh7X2WfnagDoG6Z0sUHw1a80Jxv1PD6H1tFu27hv331rPLvxo89VtEz72U7Ge6tLB0HFVc3Y9BAGIaxEj279IQskqIEzkVsZzTbym+GmmWi69hY67nRe6eRr61Ctt1qkHii9V+zY5u449oF/P2TUV60TO28GsCm7vPDhes9V7mAzN/IeapdFrZlouNYZE+07LMRRdyxrXSpJ9pWK9FpbbHczuGHKXnL/q2IfFO2sLMIOGUTeUQ10j4p+nG+aZPTAaKc6PHPUtUWN5LYORqCWMQ8qEo0i7k7E8fcqbzIWYgiGvPgLQxbNXHcKAB4zM4h2Q3pNuyCrUamAudRF5z/yXETlGCguKPTl1jl5ho2N5aPhyHn3MmjZpmwTKO0Ei0acPX8AH7IF0jqVCU6vs92GzZadQtvuv0IPvvPF8l2FtGxd+Lh/+3K0nFgcXUzBg303aiWdVoRbZOCJW/whhJ2Rt6+INFApEav90YkJVMH2YEslfdThTtvWEouwFe7Er3ScWAAOJ+LuVuL7Rwy5GucVZ5ogFa4kmbDlhksjImULJ2jplaiEyKv8IQDRSVNNgio64keEogxUzUpA7fzDZusRPMWAypPtMzOQbVQsCITyjzF8cVmkhWt8iLzjkW1I5Ckc2Q90Yp0Dso5ONewCwOe1MFCoDiPUDhuop2jliPjMiLPU8+Fz0/wZEfPYypIdLH8RWXnYEozN52DGHHHFjgsQvKtL3oegiDE6W88q/zb9Ng56RyJGFYp0QcVVzdj0MCaorFtr5EWJYiU6NnG2zEsteu4uDPCRuyJnhay/jnqAI4Id96wmPxvGVG7GlC3TSy36zh3ObVzhGGI9b56F6Zum8nwDKD2RAMRiVZ5ctnNR/Y4orxXVUYvENs5CBFZAKSFEaLq84FkEFA3nWNAsmjESrQinSP6XfX7z8CLCVN5ol3J4pRKXBMlmiAMHF9o4un1fpIMA9AGCynDeUBK1MbSOWxFOkegthR1naIS3Sd8fgwRiRbvCAyIdg4nl7ncd32YBn8nYU7DzkHN4M/m//Mw4AznJU2Lgs9OtotELVvZGriwjPS+e2yhiZ+/aRkPff1ZclkLb7ZDdh+vcDBwdTMGDawryib2GmwbiHfx3hl6yQp31lhu1fDEpR78cHoZ0cB4HBKFWMhwdL6J65eioaRZNRbuJxyZc8YKV3ZGPlw/JNo50vNRtpXPQFGiR36Q5FALn7vGjygjeaJrck8rQM2q5mc+y5Roqi+YgUKsIkLmkgbT5ps2eq66NRLg+2pVJISiRKve+ySdg6hED7wAz22PSg4WKs4DTnlMS5UTTRhulSnRlOtaFNXGPwZeU54ItdxgYT/OJOf5+buOje2hTxqKozQmAuNNtDzIBwv5x8GLlkv+lhCPB0RK9FxjfLD65E9eg/W+i398ekP596Jjbyd2jkqJPqioGAMRaz157fFeo5WsYHl2jn2kRLfqiedyN+wcfddH3wtgYDIrBite0c2avhJxpDteuLJGyIgGOOkcBAV5nmjnUH0ujmUiiGOuskg90YrBQkVG8EiyJZw8To2vrMqO3zQMOLYpjUjLQlWgAkS+zW1iOsdcXPShirkTlRGpPNGuH8AywI0eYwsBpSd6RFeir2UJHRv9UoOFSiXaK1qUmjULIz8seOGTvyEs5LpOMWpQZ2DakdSWJ+o54doWZS6PDxaKFmysrnxboUaHsY+fUmTVsFV2jiIhriWeaIESzVGvGRyLpkRv9r3EysFw43LU1Mgrp+IeB6+xUDLbVOFgoGIMRKx267jpUCuJUZo12Jdvm+Ol2hn5My9aYciWq0xzAZJtt2I1yJPE573uthUcW2jgefONaR3igcVqt4Hzl4cJqVS1FTLkWwNlW/kMCw0aiVapWMl2fO5Gmm7pywcC2fPIjgFQDBay4TSXbueI/o7WmMgeK3vMPHSdSF1m5EY6WBgTg02Ft9UXlBEpPdFeKFxE1S0DBugkmqpEA1HMnd5gYUzEygwW1uWWnHSwUO6JHnoB2Y+ch2MX20IZKOcuQy2XVjFwfaEnm5FKVVkPO3cog43NmpUMM/LAiGh9TImO3lehJ1qSM0/Nid4auMmCk+FQuw4DwEVi4QwvWUQ221ThYKAi0UTcutrFR/+XlyRlBrNG+uXbv+kcwLj9ZZp2jvF0jqC0H5rh1tUuHnr7T+8bu84scc2cg6EXJOR2jWhlEkXcyT3RNgZeICWRlGQBEQmixIulzXnydIPoeSSWEoHHV2bnANTEIQvKsBlrLbwYVzLLFjHzTIlW+KLZa9LNiXYlddOGYaBOiBfcHnmwDNqA3WrXQc0y8PRGX3OwsHw6B7sWiXzRqRIt3z0AMOYxZp81TUEWt25SIiIZ8vYGZufgHrND28WQDfbl0VRYq9hwq5kRTFRKNC9ajkGVasKwNfAw3xy/99uWicVWDRc0qs+BPIkW7ygfFJw+bePEiTZWVzs4caKN06f3B0faK1Qk+oCibkUeUXE6x/44kbPDhNNUoh3bhIE4J9oTqyUV9MGyop+NfdE6SnT2Ri5rq2OgFK5QkgXYsE6eSHgEIpXaMChezHJ2Dmm+dM0sqNciJO2ckuNghOzC9hB1yxC2uAHAXJOmRI8ElgCKJ1o11KnyIW8PfbQdm7TTZMUxd0+t9zUHC6PfIadz5MpWAAgLV5jNQ5rO4RRbC/tuZAMyCa9b9jmIPjvu4+TsDX3XF55rc4KmxTx0lPCGIp1j4Ba/S6qIO5kS7dgGRn6orHuPlOjiPXWl4ySLVRV4x9GqWzBwcO0cp0/bOHWqgTNnTIShgTNnTJw61biqiHTFPA4oDCNqucqrHyMvgOuH6OyTwUKmPtumwb0IlYVhGMkFV1aDXEEfrLWQef2YEr2gGXFHSdVgjylLiFCRUECcrkCKuGMDgRJFlDZYGB8Dx84hs1+oaqPHjoMwbJYo0TsjpRWAKdGqrGhRayTFEy1bRKlKQoBIFOho7KwdX4hi7vQGC2lKNC+2UdU6yY5D6olmSnRmMROJA7TXnbdSZTHQILH5nQWZnYOnnvNA2cVhUH0XeNeChEQr7Cy8BbCKgDNsDb2CnQMADnXquEC0c7Bjzy4GTcNAq24dWCX6/vsd9Pvjn2u/b+D++50ZHdHeoyLRBxjtulWwc+j4B/cCzBO9NMXKbwYWhxRd6PfH670SsJprLVzvRSqMiow4tgk/SAesEsJBINEyJVrHE50nEhQiRVGiKWpeo0Q6R/R3pnY6h+x8Z4vVC5eHysXHXELeiGqidk602BMNxMkoCuLKlGgqji82cWZjkNoopjhYOPQD2KYxpg636tHfiuwcqRItT+cAxv3FfQmBzUM2IDeSKLF5RB7h7GCh2M6RqufEnPcp2DkGnOZBFnFX1hMNyL3wXhBie+gnrzcLHSValJXNu48fFJw9y/9uiX5+JaIi0QcYbccuhLSz5qP9E3EXKdHT9EMzNOI4pIErJykV9DDfsNGwTZzPKNGUtsl8TFjiH1WUrQBqOwfVE11QogOKJ5quREtbE0WeaIUS3dBQoinpHGxu49LOSJkx3K5bsEwDm8TqdZ6dYyRJNnEV0WYUJXp7qK9ED70Az8SLQJ3BQpW1xOVYi5hgITp/PFI6R3ExoxpIzcKxxd5eHU90vmyl7/rCVBTqAoxyHWBQ2TmkSrSCRPO+M8nnLlkIbueKVrI41Kljve+SfNWiHbW2Yx9YJfroUf73XvTzKxEV8zjA4K1g2Zdxv3iiGzULrZo1ltIxLbB2q4EnVksq6MMwjLGs6PX+iORnz2+J63ii12UkmmDnEHqiCRm9Op5oGRFgj5M9Bi9W5uWeaHVONQOtQCX67vuhOtnBMIy4tbCcEl23DIQoRgsyRJ5o+VCn2hPtaSvRAPDDizsAaIOFkbpMSOfwih5vRjLFnmh2DsrTOYC8J5q+w1aXFAYlg30ly1ZEarhjm6hZhjKdg7IAZWC7i6JFWRQXWUyIAWSeaPGApsoKAqTzAnPN4jl4OI5tvdRTq9E8FR0AOnXrwDYW3nffEM3m+PvebIa47z56HfpBR0WiDzDa9eIKlpHq/ZLOAQA3HWrj+YfaU39cdsHtxxF3FaaHI93GmCeaklqS3xIfJckY8lQCA3IleuAFyhuw2M5BKFshKNGULfH0cdLv5JCgHDdr9Ig7SpV3N0M4KTs0cw2bPljI8URH/y4g0QorjkNI59BNG7qWkehLPQC0wUIjzutWDhZyPN5Mie6r0jkkC7lEiR5mlWgNO4dkR0BXic4uAgcSO4dhGNymxTzSBRjNEx1CbKsZcJXo2M4h+RtA3popI9Fp5XdRSDjcjaxvFwhZ0UIlum4nO8gHDSdPenjwwQGOHQtgGCGOHQvw4IMDnDx5MF9PGVTM4wCDN5DAVrQ6ys1u4//65Z/Ab77shqk/bmrnkG+XV9DH6pyTeKLXdqhKNBusi0k0YaDJigdOpXYOSsSdQFGieKIdQapGFjJfJUMtzj0e5EgIIFeOG7baF5w8nhd5cmXqKlMIo+dVX+LnGzX6YCHHEw2It9JHfoiaQoUn2Tk0rmerXQd1y8ATjEQTW0jzyRQ8jPywcC6yz1aVziFbyNmWiVbNKqRz6AwWhuC39unYKRw7HSwMw1BatgJECzBV2QqlqIghW6LFA4+IKstWCIOFMjsHI9HzHDsHU6Iv7qiVaFH1eduZvRI9SUzdyZMeHn98B+fPb+Pxx3euKgINVCT6QKPNIdFsuKW9j0ilbZnSmK2yaNosnaPyRE8bR7oO1noueiMfmwOP5GnP+5LTnGj5Z7/QrEk9uRN5ognDZWlOtMTOwckHzoMlxgwzyirFw6zygWYxIOy6MIUQoBV1zDVsbBEKbwCOnUOh5KnSOZo1S0g+gYjIbY98LRJtGgaOzjcTixBlsBCg+bNdTmRfS0H8knQOxXF0G3YhJ5qaf58oqhwyqGOnqFkm/DAi/kMvQIjoOis8Zk7TYuH5XfrzM+VdNCMw5FgiKLXfBvi2MspgYWLn4CjRK51YiSYMF4qV6NkOFlYxdZOhYh4HGO26XciX3Nlng4W7iWY82V95oqcPlhX9zxe2Aagrv4GsohuRCUagVKksC4rqb0rttzDiLhDXTjMwpU2mBo9iBVi1GHRsa8xbTVGwGwofaBay7fUsGImmJDLMNdVK9EhAxBgxESvRcjtH17GlOcNDL4AfhFqDhUDqiwZog4UATRXnJcXU4ixuEYlO0jkUJLLr2MkQG6CXzsGOiXcOU87B/OO4fkCqHe82LKUnWkcJL6dEy8/BYbyTxbsOyRYfDFuSwcL5po2aZZBaC2V2jlkOFlYxdZOhItEHGG0nIpFeZqhnvw0W7iaatUiJp5CsCnpgWdHfPn8ZAK0op6hEy+PNGBZbNWwocqLLR9yFysEykhJNGG5kj5X3lAJyO0cz3opXEThAHZfHwG74FJtTNFhIjCmr6amAruIc6Dg2Lg894QJie1TOnnZ8IUui9XzFMvDSRgzDQKtWzOxP/iYIYUC+kAOKSvTAo9vUZN5e3cZC9jd9T107vhueaED8XeQNFhqGgZqkOVN2f0jsHJLPnS3yupxz0DAMHG7XyUo07zjYjnJAWETvBqqYuslQMY8DDPal/v5z28nPtkc+DNAqcg86GjUzUTArJXq6YEr0t89FJJoyWMhL56AUPMwrlGiKnUOU8+sq0iGi41Z7olWKanIctfFBOZqdQ62EJ49H9P93NOwc840a+m4gJZAiO4vSE+3J7RxzDRteEApfO/Pb6pZHXbvYSP73NO0ckT+/+HhNiSXH80OSGj6XU+V1BwsBPhnUayxMVd1kiFVyDHONGlmJpniiGwo7R3T+81M2ZOkcotdOtXN0HVu4CDrUcYhKNP842AJRtAjbbVQxdZPhymdaVzBe/YJDONyp4189/O3kS9wb+Wg71tSLTfYjmjUridaq0jmmC+b1+855DTtH7kY+9NQEFkjtHDw1MghDuH6oTucQ1n6H0ng7IPYyK1IieKkAPOTtHOwxZX/LiBIloYPqk02UaA3VWqZGy3Kis/9e+DtF7Xc3JsciSwfbWeto7qwdK6lEq+L2RLsrrbqF3kiQEx0E0mQOhm5mR8APQoz8cCpKNKU5lCG7o0Mp9uk2IuIvU1F1I+4AmZ2DT0RruWi+/POLvn+OYhEIRHaOrqRtd6VTx3MTeqIBKC0dIy8gpYDoooqpmwwV8zjAONxx8OCbX4itgYtTn/gW+q6PnaG3b9oKdxvZi3uVzjFd1G0Ty+06nlrvAyDaOXJE1iUoyEBEor0g5N5EqG1riS+yhBINsOY8SWMhISEEKNo5kqIHRToHII/YY4i2+NXHwZRoUjpHU139LfLVqjzRrh/KPdHxsJaoOpop0bozHizmjmKjYKhbtIg7HhlsxklBPJCV6IadqLrssXRyogF+1vnID2CZBkmRT3OTw2RRJ23HdGyEgDRdgpKxziAj0UEYLSz4ec+GtPZbpIKLZimy2Bp43GQOhkMdh0yied+FlETLFf3/+o9n8Ob//A94/MyG8rl0UMXUTYaKRB9w3Lraxf2vvw3fu7CNf/vp7+KyZjHBQUaWIFSe6OnjSJyBapkG1w+YR7GxUE6gGBbiEgOepYN6A2Y5v2U80QCr3pYPFtKU6PJ2jj6h+pvazsnUZWo6BwBpVvTQjxIO8kQsO4jGA1WJ3hYp0czOoalEr3Sdsag/Cqh2Dt7rkaWMuEFAIvJdx0bfDeD5QYbA6tk5ROkcFBUYGG//6xOOgSm0W0P1LobM1sOQ7sqIvd3cqDrOd59BpkSLZimy2Bq43KFChpVOHT3XV5LggYDMswWvKubu3OUhXD/Ev3n423hyrSf9XV3MOqZukoi9WaNiHlcAfv6mZfzuK2/Cf//BJXzhB5e0J9kPKrIEofJETx/XxL7opVaNZA/Ke4upnmjWWsiLudPLuC2SINcPSWUbUTTdFAYLa9aYJYCUEy0hDnlQk2jYoodCuBeYGiwZ7mSLiPx5kJIQSe23ZKBMrUTHdg5NYSCKuWuQrRwAPeKO93padXHrpEccsE1sNUOPZKXIwskoyHlQz10ASab3yAsSj640J9opNi3mMfL55w4PssxtWWlKZOcQR9yp7Byyz31z4HHj7RgOdaJ5kecui9XoMIwiA/ODuQBdid7su1hq1WAaBt790Dex0ZMPAx8UHPSIvYpEXyF4208dxa+eOAo/vDqSOYC8naM6laeN1TihY7FJq2zP+zJFql0ejETzEjoSOwQxnqvoiaYdg6rwZEhcEORb7yjxYiofaBaUnGggQ6IpSnSTeaLldg4ReQH4XlwvCBGEci8uI2Giwg7W5KY7WAhECR3UoUIgOgdkiiQg3l1pKtI5KMeRqLoDj9RMmUU61Mu3RFEWocC4R5gWcUc7Rg1vOQAAIABJREFUdyjfnexz8b4LA8l7Eg0WyiPueKAMFm4NPIUSHYkNz+2IPcRskclN52BKtMITvdF3cXyhif/9zS/Ec9sj/O7D3yIl+ux3HPSIvYp5XEH47VfciF/6iWvw8zctzfpQ9gTZbcZKiZ4+jiRKtDqZAygOFqpUSIaUREvsHMShKJ6dg+aJlldvU+0cxYg7gp2DkA6SPB4n4osHnYg7ip1DRMTqksEsZvFQ5UQDYhLGtrhbJYSB1962gtfetkL+fZKdQ7CYak3DE+1E34PLAy85F6izHom3l/M5MCWYAnacLtHOwc4dWUKHjMTmUbcMmAZ/yFYUs8j+rkzEnSpjOghDbA1cuSc6bi2U+aLZ4ob3ObCdY5WdY3PgYaFZw+3Pm8MfvPYWfOOZLfy7//d7M4vGmxYOesTe1SFZXiWwTAPvuevmWR/GniF7g6E2e1Wgg3miKckcQOpLTtI5/BBzBBIgI9Fadg6rmPPr+rRkhIZtJaonDzp2jiwBkG1BM6iycbNQ1TAzdDXSOVo1C7ZpSAcLB4JUhHqGdOXBPgsZgewoSNj2yEOzZmopygyvueUwXnPLYfLv18kRd8X3oVEzJbXf9HQOILJzsNerU/sNYKwtk0FHCU4H7ULScKNqEQTokXjDMOIhTVlpTPF4aiUj7sw4Y3rIscEAUdpVEPLbChkOMyVaSqLF1wG2cyy7/gDR9fG21Q6A6Nx+ZnOAP/3CE7jj2gX8Tz9xjfRv9ytOn7ZhmoDP+eoclIi9ikRXOLCo7By7C6ZEU0k0MK7muYIkgzzadQuWafBJtEY8Vt5KAURb6VQl+uLO5DnR+WMYuJEKJvODNogRd14Qxf1RzvWffN483v6z1+LEsXnl7xqGgbmGrahe59sYsqQrD4oSbZtRUYkw4m6oV/k9Cdi5G4ah8PMS1Zi36hb6I5/7tx7xHMz6i5n6Sx4slOwIUHLWGbKDon0vGiaVEWBGLlWtk9TBRiBaiPJUfRkRrVumkISqFsAyK4isrZChVbfQrlt4TpIVLTv2FkGJDsMQm30X8xky/y/uOIZW3cILVjrCv9vPYF5o3+fkrh+giL2KRFc4sMjeYKqIu+njyFwDBlLPHwVZEk31RBuGIaz+1qos5jTOeX6Q3KRUxy2LuBu4YjUri0aOiMlUMIbUBypXQYeEpA+Gum3iN156vfL3GOabNbmaKCAisnQOpgyqFh/5pr4stkdeMni128jakXjXEy8I4Qs83s2aBT+MI/1yFqZoN0TPE81uzdp2DkFOtENMKamPeaIj/71sAdismbBMQ/j5seenknj2mDISzTv/ayUj7gB5UyXL7ZYp0UB0jaQp0cXjsEwDzZp4EQBE14aRHya7dkB03XzLi54nPa79DJ4XGgAsKzxQEXsTy3ff+c538La3vQ1vetOb8Eu/9Ev4xje+wf29hx56CHfffTfuvvtuPPTQQ8nPv/nNb+Kee+7BXXfdhT/6oz8S1r9WqJDHeDpHpURPGwvNGv7D234Cb7r9CPlvsmSU6omOnsueKOKO/Q7fE63+22bNkqZjjPyQnBACpMdNqW5OPdFyJVo3sUEHqupvWckFIFZAAfVn13VsYcTd9tDbUyUaECc1sIUCV02UpEp4AS1mMfUXu6VzormNhQoSyXuckRd5olXPbxhGoWmR//w6JJr/XZTFRdZtcTqHqiipbplcLzmQZqfLlGggSugoq0QDkaVDNljI5hXmm1eO7inyPAcBDgyBBqZAoh944AG8613vwsMPP4zf/u3fxgMPPFD4nY2NDXzoQx/Cxz72MfzlX/4lPvShD2FzcxMA8Ad/8Ad4//vfj7/+67/Gj370I3z+85+f9JAqXCWoPNG7jxcfX9AiMWNKNJHAAhFhnzTiLj/UB0QZvRQVkFK2QvVEAxkS7YqHmhhsK/L8qpToZEhxFxaMc42aomxFYOeQeKJTO4f8/Zcp0TsjXzsjuizY5ySrMAcESnRdnCrh+rR0jpplomGbY+kcVHHANg1YpiFUonUG+4C0sZDqv1d5onWU6IatsnOIPNHF155Ey8lItFSJppFoVWuhmkRbUjsHExgWiElJBwFXSt34xFdjwzCws7MDALh8+TJWVorT0F/84hfx0pe+FAsLC5ifn8dLX/pSfOELX8CFCxewvb2NF73oRTAMA29+85vxN3/zN5MeUoWrBOwGU7cMcitZhd2FY1sZEk0faIrsHOKIO4qnkhdxR1WiVbXfFFsGexwgHSgceLRBQFU6SPYxd2PBOK/0RPOJiCEZzGJ2DtX733VsccTd0NNuKyyLNCZOXBwD8BcFiRLNUROpnmggbi0ceBnrAv21NwSFIzrfw2zu98D1SSQ+alqU7WLoeaIjO4dssJCezsHOQdl3l2LnkKVzAHFr4c5ImJShsmK1HVuaE82+m/MKW8lBwpVSNz7xEv+9730v3v72t+ODH/wggiDARz/60cLvnD9/HkeOpFvCq6urOH/+fOHnR44cwfnz5yc9pApXCdgNpvJD7x/kPdE6JHp9Gp7o3I3UI9d+m/CCEJ4fFLbemReWNFiYGxKkpnqo7CTZx9wNO4daiRYvIuqWyVeiifGE3YaN710Ql63slRJdzy2A8pDtisjyjakJMUD0XlweRkq0ZciTTfLgLSIBtoui54lmEXfUYh+eFYtB3xNtca8FqrIVXjqHLFqOQWbnYEp0V+mJrsMPQmz0XW4kqOo61nUsqZrPBIYrSYmOLBsD3H+/g7NnDRw9GhHog2TlAIgk+t5778XFixcLP3/3u9+NL3/5y3jPe96DX/zFX8RnPvMZ3HffffjIRz4y7eOsUKEAy4wi1arK7/0DxzYTf6SOJzoabHPhB+HYrkJSGVw24i4IUSNG3AHRjbqTI30jDSLfsIt2Doqa11AMNrLHAnbHzjHftDH02DBZkTjJCjtEW+nsZzXFObB/lGi5J5q1AXLLVurRzyZWoh07tnNEVgpKyx+DKOd6SPTzA2mt+9Cj2znmGjae3ugL/10n4g6Izu8y6Ry8hRylrElm59jse2jYpvL4D7GYu8sjBYnmv5/L7TqeWt8UPn6iRBM80adP2weGmJ486e3bY6OCRKJlpPj3fu/3cN999wEAXve61+F973tf4XdWV1fxD//wD8l/nz9/Hj/90z+N1dVVnDt3Lvn5uXPnsLq6Sj32ChXQrFmVEr2P0LBNXPQC+JIkAx4WmjUEYZQXnFVbRpJhrjxEtd82UYkGYhKdCyOhqFnZY2CPE/1/nxQR2BBk42YhG6yaFPOZvGbe90k2nCXaSneJ6RxzTjRU5eWa/bwgjD+PvR4s5C9mkkWBoGwF4CeseMR0DiBSPJ/dGpBV4CxEOddDzyfvCLGsd6ZEq2wMQLQImmbEnTAnOpkJoHuiVeQViBbfomSMrYGr9EMDkRINRK2Ft6AYOafKi19q1bHWc4XxipsDFwbUijiLjWOpF2fOGDh1qgHg4KRdHDRMfDVeWVlJCPKXv/xlXH/99YXfednLXoYvfvGL2NzcxObmJr74xS/iZS97GVZWVtDpdPC1r30NYRjiE5/4BF796ldPekgVriI0a2bVVriPEBFZn5QRnMVCrLDkt4V1GwuLJJpe+w3Im9Iox8DIOCNi5JIW21J6ovuJEr07dg4gUt54kPlqReRNRjqzYIUreTV6J/7vvYq4ayiUaLeknYOazgGkQ3pUP3IWIm+vTjoHgNjjHsTHQFOiLw89oR9Yp3YcYNYmTu13nFvN86RHC7mwcAyUsiNZyc7loYd5goWCtRZeEAwXquwcy+06hl4gTOjY6HvoNmzlYuygV2gfRExMot///vfjgx/8IN74xjfiwQcfxB/+4R8CAP7pn/4pUagXFhbwm7/5m3jLW96Ct7zlLXjXu96FhYUFAMDv//7v433vex/uuusuXHvttXj5y18+6SFVuIrQqFmVnWMfganB7KZB3cZm6nN+uG3oBUnygArME52NyfSCEDVSOofYDyurGy48TkLGmZ3DJ52fomGqLHYznYNtE4uqv2VErGbx48WoC6lsyUgWTB3cayValjcMCAYL6+KIO2o6B4AkLo5qpciCtxMThiFGfkj2RAPMGhGi7wY0T3Qj2kXiWVkAvcZEIM2JzsfdMm81T6llJD1/HlJmKuocGxjD5sAjKdGH2nUYAC4KYu7UJDq6/l3c4ZPwzb5L8kPPukL79GkbJ060sbrawYkTbZw+Tfvulv27/YCJj/QlL3kJPv7xjxd+fvvtt+P2229P/psRaN7vfepTn5r0MCpcpVhs1kgXuQp7A5bOIcvU5UFU/a3jp3QsE0EI+EFq4XCpg4XMy8whQYmlhNhYCKRkXFTcUXh+wTBVFruZzpEo0Zxt+UBBxESNb6kSrY64A4rV3yzya+9ItDydQ7YoSJRokSeabOew0XN9bA897c/ZsYsDctTCmyzYoF0/LltRYS5T/Z3/rCISH5AWoAyNmoUgROGcG3riuEi22+HmrhcUK5ZjG5LGQhfHF5rKY7YtE4utmkSJlluxmI96rTfC9Uutwr9v9F2Stebo0RBnzhTPtb2IjStrJTnoFpRKwqtwoPEHr7sF//pVz5/1YVSIUbei2mtqvBnDooBE66hYeQLrByGCEKStdJkSnQ4W0qLqouP2k8ejKtHKiLtdTOdgN+gtSfW60M4hGOpS/R1DV6FE75Wdgw3BitM5YkLK+TzZQomvRNMsRUBKSJ/bHmrbOXjpHDqDucnj2CZcDTuHaBEERAuIIKQtQBlE1hh5Qkyab50FZShYZufYGnjkWLmVjoOLEjuHZYivRcuxHeTSDn8hvTmg2UpmGRtX1kpy0C0oFYmucKBxzVwDK92D8WW7GuDUohsSlUAxpEr0+I1Yp+0szbiNnpsRO5KdgxFwblMaIyLqx3Eydo6AUPSQPr8lJG/Jcbh66r4O2A2aF7OVKPECQlW3+ZXLOrXfAAqFK9v7TImWla3YcVIQbyGUH5iUgb0XF7ZH2oslnid6qLkjBESf187Ihx/SFmxJ0yLn3NFpHGVo5mIis48l2tVJmjNzr79HaPkU7aQA0feButN5qFPHBYmdQ/YeHGoxEs0n4Rt9l0SiT5708OCDAxw7FsAwQhw7FuxZhXZZK8msLSiTotoHr1ChwtTAyOhOfANUtdUlf1ez4NgmX4nWsHMA6Y3UC+hqOCOIvJi5kcaQZHY4jR0HtWyFN5SWxSBW4najWKhhm6hZBtcTnRbe8J+3Zpm47BZv0skihhBxB3DsHMwTvU8GC1XnQbNm8SPuiJYiICWkEWHUHyzMJ4voJMsw1CwjKRmhHAP7/HitkzrpOgxNQdLJwJUlxPA90Ru9iJTKEnJEA5kD18fQC8gkeqXj4FvPXub+21Ax3DnXtGEZkZ2Dh02inQOYTWzc6dM2TBPwOZcwlZVklhaUaaBSoitUqDA1sJvcdqxKUbexAdZaOIEnOkeCXKInF5Ar0QkZptg5EkuJn+Y6E+vCVWUrfUKFeFkYhiEsXFGpiY7CE60cLBQomUyJbu+TiDtVjXm7bhUWAkEYRT2Sy1Yyr7WMEl20c+h7oh3bTM4DPSVatgDT80QDPDuH+FpQE9g51nrquux6XNSSH2RMKr+JBSeHOnWs910+IVfsSJmGgaV2natED1wfAy/Yt0UrzNPs+8XvBcVKctCbCysSXaFChamB3SgYmdC5eedJdBhGDWC6lcUpiaYr0Q2JEq2zJW1bkVI89II015mg5jUzjYkiDFxa9XhZiKq/VVm7NUG6AbNzqKwMjVhdzxNQFnm3V0q0bRowDVk6h9gTDUTnb34R4rH3gKxEp0RJOyda4onWU6LN5DzQ8UTzrECT2Dn0PNHpYGEW670o51l2DchWnWfBXg9VAT7MfM0cNXkoUdEZllp1rieanVMUO8ekKJOSwfM0A4BlhSQrySwtKNNAZeeoUKHC1FAg0Ro3z4XmOIn7i8fP4mtnt/DOn7uO9PcFT3QwHSU6JQJEa4ptYuAGmYxaioItbkxkGHi0yLGymI8zivNQKcp1W1C24gWoW4aydc8wjCTaLYvtoZ94jfcChmEkg7E8qCL7Fpq1wnY8Owd1PdGAfpThatfB5sDD5YGXPA7zROt8Dx3bTL6/lOHGVs2CZfAHC8sMNrJzPP9dHHiB0JZRExDhtZ6bDC2LwM6vfLLH1jC6FlHtHIfj2ZwLl4e4Zq4x9m+yBQDDcrt4/gDpsPVuK9FlUzJE3uUgAJkIH+TmwkqJrlChwtTACON2okTT/btZJfrv/sdF/Mnf/RCvuvkQ3v5z19Ke2xIo0aTa79SGkQel9WzsOOIK76GGnUOkvmXRF1RyTwtR9bqYCMnixfLkBYjIN9XO040LO7LYGUWRaTrV15NCVJ0NqBcTC027YEfyNFNq5iawc9y6GjXlffdC6svVHfAFomONxwlI55thGOg2BOdOCU+0zM4hslQ5IiW6P8KSojG0nrtuMGzFQ85zxHQOpkTzsp5l8XwMyy2+nSOp/N7lKNeyKRki7/JB8TRPiopEV6hQYWpgN8ut0p5oD986dxnv+8x38cJruvh3r7sFJpFEOTklOiUw6r+3LRO2afA90Ro50UBEAnTtHA2B+pYFNS6vLOYaNnewcKBQEx1BxJ3rh2TyxquO3h56exZvxyAl0YoCoXmOp98NaJYWhrptJuex7oLp1tUuAOC757eTn5VL50iPlUrk5xr86u8ynuiWgETLfMUyT/RinHwhQn4Hi0HXzrHSicjmc5yYO8psx1I7qv7Oty7ulRLNG+6T/ZyB52k2jBB33XUwlWVdVCS6QoUKU8Mknuj5Zg2Xhx5OPfRNLLdq+OM3vVCLSCSeaHfczkGtXG7U+Fv5lNazLBxm50iUaFrZCiBXoofE3N6ymBOpiQoSXeN4cQGmRBNtDA5Pifb3LN6OgS2AeBj5odSestCsoe8GY9FsnsZwKwMbLmxqLpgWmjVcM+fgO1kSXcITnf3OUrOqu47NTeeYzBOdi+uTkOiECHvjZG6950qTOYDiDhYDW1B2iSR6vmmjZhl4jhNzp0rnAKKsaC8IC9/BvfJEW4LDE/2c4eRJD7/yKy4MI33vw9DARz9aO1DNg2VRkegKFSpMDUwpZXYOVbxZFkxpcf0Qf/JLtycFBFQkEXdJTjRdiQbirGYOidWtMG/EambiiSbVhTM7iViJjqqgd3ewcOgFhfdAtSUv9ET79HhCrp1j6KHj7L0SLRosVNlTeK2bXqJE0z83RtrKLJhuXe3iu+cns3NkPzPqMXQFSvSohBKdeqLpg4U1jp3DC0Js9l0sU5XovJ1j4MEyjUQZV8EwDBxu17lKtCqdAwCWY7Kft3QwO8eChp2jzIAgL55O9vMsHnnERhgWrSDvfa9zYOu8qahIdIUKFaaGvBKtc/O8cbmFdt3Cv3/jj+GG5WL1rQrFdA5WtjKZEs0KX6je3EbNijzRSdWv+iYsamnLYkAYTpoELMornzCh2pKvWSb8uG49i5Ef0r3AHBK2PfLRru/tTVdm53B9eXsmG2DbzBQG6ViKGJgvuoz//bbVDp7eGCSL2DLpHNnXSD2GOc5OAlDOE+3YJgyIIu4EhT+5BTQQLWZCyDOiAbmdY76h58k/1HEkSrRqsDCt/s5io++iXbfIO2psQPDMGRNhaODMGROnTjWUBPbYMb6HWfTzLETDhevrhvZxHDRUJLpChQpTA7vJXR5EN0AdT/SLjy/gb951J15y7ULJ5x4n0boERqRE62RVs+MYs3OQPNHidBCGgbv76RwAkqINBkpONFAc6lKRziw6sR0gm9W7PQMlOoqJ4y9kRoriH54SrZvOAWSVaP3bczJcGFs6yqRz1MrYOQTJLio/PQ+GYcTlQ+n55AchXD8UzgQwH3f2HFyPyahqsFBk59gauORkDoaVDl+JJpHoFr/6e3Pgafmhyw4ITpLXLB4iPLh13lRUJLpChQpTQ6pERzcCnZsngIna+PKDhaU80YLab53t8NTOQW+La9r8Lewsdj2do1FUUgG1r7Zm80nIKI64o2DOseEH4Rhx2hn56MxAiRZZaka+/PVI7Rwa5w8jbqWU6JVouPA7saWjjJ3DyViwKLsoANtJcAuFJWUi7oBoZyablMPOLdGCNKn9zqTEsKKVsoOFmwOPnMzBsNpt4NmtQWE4kBJxt9Tm2zmold8MZWu0J8lr5hFw3eM7qLiydPUKFSrMFCmJ1leiJ0U+qiqNuNPId+bVfmtUjwOZiDudpkOmRAtU0Ojfdj+dAygq0SpLAE8FZP9N/fw7rPVu6KFVtxCG4cw80bLBQl1PtEssnMkiGSwsoUQvtGo40nUSJbqMnYK9Rp2K+a5jww+BnjtuwWHPr3veNmrWmJ1DVV/OK1tZT0g0TYnOe6IvDzwc6ujNZVy31MTID3Fua4jnzadZ0ZTBwq4TDSbm7RybffVwZBaT1GiXzWuO/maAf/kv+c2FusdxkFAp0RUqVJgaktrvoQfT0CMPk6JmGTCQ3gzT2m96NJ2obEU35zYa0KMTmDSdg0/gPD+AH4S7a+dgJDDviVaVrXBUQPbfVAWU+YCZL7rvBvBD7DtPtOyz7DZsGMgr0frpHHMTDBYCkaXjuxciEj3wAu3vIXuNOs/fzX1+DMMSSnj03Ca2Bh42ei42em5ikVBG3GU+uzWinSM/S8GwNXC1s5mvW2oCAJ5c7yU/U1lRGAzD4GZFb/bdZJeIglnVaJ886SEQu9FKHUeZAcm9xv47ogoVKhxYNDI3pN1UTXkwDAP1DAliW+k6qRpcJdoPtAYk08ZCH3XLIKl5aWMiX4nua/iryyLxRPeLnmjbFL+OukDJG+mkczipEg1ERSsA9lyJbthWYVufYejJlXXLNDDXsAVKNP1zW2rVYQClrSy3rnbwd9+/hO2hF1tq6EOxQLro1FHC010MD0fm0p/rJtswdB0bX/zhGu76D18a+7loUcXOMzezkFvvubBMIzm3RGBNpNOwc1y3GA1EP7nWx89dj7HHpSyml9rF6m9dTzRThe+/38HZswaOHo2I6140Ai4uhlhb433WIY4d0zuOsg2Ke42KRFeoUGFqsC0TlgH4ob4PchpwbDMTcac31OVMSYl2bAvD2M6h03JoAOgLVNCkuGUX31PHNlG3jMKA2Ejx+tPKZd5goV7dNXvu7dgOtNc50ep0DvnrYYVBDLoLOQB4/QtXcXyxiQWNLfwsWOnK9y5sKz87HtiCUceT3W2ML4IYdJNtGP7Vq56Pr5/dHPtZ3TLxshuXuL9vGtEib5Szcyy1asrn5tk5PD/AzsjXHixcatXQcSw8uZYq0UONHanlVg3nLqdKrRsfx3xTfRynT9szIc7Z5xVhcTHE44/vaD2ubECyItEVKlS4YuHYFnquv6d+aIZ6pvjD1axcbgiGyvTtHFEN9s7IJyvHLJFApESnSR+7p8wahoH5Zq3QWqh6/SJPtE7EHVMLWTQb+/97beeoS0j0yA/RUjQoLjRr2Mi8f57mQg6IbBQ/c90i+ffzuC1O6PjO+W0MNXYDGFi2u46dY86JCH9hAaaZbMNwy0oHt6x0tP6mbo2T6LXeKIkdlKHt2LBNA3/3/Ut40+3XwDKNZDGgS6INw8C1iy08ud5PfqYzYLzcruNb59Kc77TyW/46ZqXa5p9XhI0NfVtf2QHJvUblia5QocJUwW7aVBVymhhTorXtHIKIO10SHf/uZt/VUo6bAiUcSDNzd5NEAxFpyBOhoSKqTuSJ1om4S5RoRqJnZOdgSnQ+ZQJAYo2QYaFZS4gPUC6dY1IstepY6dTx3fOXScecR72EnSNRonPnjm6yzSSoW+a4naPvYkmRzAFE37vffeVN+NKP1vHg3/4AYRgmWem6dg4AuG6xOa5EaySULLXr2Oi7SeY629VQ2TlEqu1737u7cXK85+WhzDCh6G/222BiRaIrVKgwVTDCORMlOuuJ1h4sjJToPIEqY+cAIi+jDukVebKBNG93t33m841aoWxFlU7C80Sz+mKqHYP93nb83DuxnaM9AzsHUBwyA9SNhQCzc0yWzjEN3LbaxXfOb2v50hlSEq2hROcWQQw/vNjTbh4ti5pl5pRoeqrFW170PPzai4/iY197Bh/96jPJQlJXiQai4cIL26Nk4TvU+O4ut+oIwnQ4le0KqewcsrKT3RzGo6jCZYcaZzUgqYuKRFeoUGGqYERkN9v1hM/Ns3NoRNwBRQKlUmJFj7PZd7VTPUTpHEwh3810DiAiDZucwUJdT/TT630MvQDPP0xrnrRNA+26lSrR8f/vKOwT04aMRFNqzOdjEs0WYmXSOaaBW1c7eGq9j7We3m4IkJJoakY0ALTqFkwDuJyxsjy13sc/PbuFu285rPX8ZVG3jELZik403G+/4kb8wvOX8X/87Q/wqW+dA4D/v717D46qTNcF/qzu1ZeQKwlJB0kCKnIHkVFnz96UzOFyInJinMTL3qeYEYddTnGwZjAzypBoMaWGqQQOs63aW0dqhkPpH1ozolLngOVRHJQ9hwxDoTsMooNuESKTxJCQG0lf1/lj9VrpJN1Jf6s7vVY3z69qqqaa7s5Ku9L9rref7/2Ep3MAI4sLL4YjHSNz1id/PWeMmRWtFdOTdaIn2uwk3s1NjEzCiPVzJUkBoP4v3vnRYyUytzqVWEQTUVKZ3YkeO+Iu3lm3Wtd4bC5adE60loPuHQ4IFTDqiD3zpnMAaidadGFhtEz0+W/UEWu3FMefa82J2Dp6wGfOwkJ3lAsCjTeOzWMKsmT4gwquhf87GpnOkQwLw4sLP2nvF49z6CPu4n+cTVKnYESeO4c/6YBNAtYvKhH6+UY57Db4AurrPeQPYsgfiivOobFJEp69ZwEWlubizVa1iDYU59DG3IUjHZNtVhRJO15tPF+8mWi1Oxu9WI2nW2x0q/Bo3WKHQ4HDAai7FUro7ja+3XdtbQCnTw+io2MAp08PWq6ABlhEE1GSaYWIWZlovRMdUtQL2TdQAAAgAElEQVTZ0XFOBog1Zk50XJ/Wceob9gvFObImWFjo1adzTG1nNj9LRm9457m+YT9+//FlfNY5MEkRPT4T/VnnIGSbhJuK4utEA9qud1qcIwAJmHQhX7LFmhkMqAVxPJloYKSDaGQ6RzJo2397BS8AgZG/W9FvPXLdIxdBIUXB25904M6K6SjOSc02z86I9RDxbrQyltthx/+8bzFm5qnHbCTOUV6QBQnQFxeKFNFa9EUbc6dFqybbsbC2NoDCQuMZYqNbhUfrFufmKvD5Mn+7bw2ncxBRUpnZiXbJNj0K4A+G4BDoAMbsRBuMc4QUsQyzW7aP261Moy04NLKLnYg8twP+oIL6//Mpjv/nFXgDIcwrzsb3by+P+Rh92+TA6E70jUXThM6BXJesxwEGfMFwRCC1xad2ARRtSks854FeRF/zY1Z+lvCYxWQpylYXF3YO+IRjVdp/T9FFrLkR3yR81NaLv/V58T9W3ij0HImIzET3xLnRSjQzsp34t/uX4cSFHqHttjVuhx2lea6ITnT80znGbv19dciPLIctrsc2NnrHTcqIN0OcyCSMsbscejzRv32y2lSNZGERTURJpRUiqVqVHylyxF0gqAh1APVMdEQuWVEUQyPuNCKPy3LYRm11HEmfzjHFneji8DbHLV91o2qxB9VLS/W5w7E49E50ZBE9iDtnFwj97FyXjK97hwGomejsFHehgdiZaEVR4AuE9Px3LCOdaLWoCIbExiwm0wJPLjoHrgj/HRrZbAUY/U3C4bMdyHba8d25RULPkYjITHS33ok2tqixfHoWyqdnGT6W2dOnjWSiBTZbmeawwy3bcCUizhHvRiuJbLKSyFbhU/lc6YBFNBEllfZhYfpmK6GQ0GixLL0TPVLIahEFkd8l8sNSpJsXa7MX9ZhSk4leO68YxTlOLJ2ZF/exu8YU0d3XfOga9AnloQE1DtDXoRY/g75gyvPQQGQRPfpiJhhSoACT7lw5Ns5h1nQOAFhQkoMPv7iSkukcAJDrcqC9z4shfxBH/9qFtfNnTPlIxkgOu03/+9HiHEY60ckwuzAL//svfepFuMBmK5IkoSjbGdGJDght+T22KxyvhgbjXeypfK50wEw0ESWVXkSbkImOHHHnDypxT+YARgrUyELWJ5Bn1J8nolss1ImWY3eitaz0VE88cco23FExXaj4cegLC9WC8XynujPZvOJsoZ+d65L1nQoHvPGPx0umiSa0AJNnm8dnos2JcwAjuWjRcyY/S0a2046yArfQ4/LCmehjn3fhmj+IDYs9Qo9PlDoneuRCDkBcm61MhYrp03DNH0TXoC9ixF18f1OF05x6J713OP5OdCKSOQkjXaZqJAs70USUVKZmou2jp3OIxTnGd6JF8oz680R0i4Wnc8TYLW/Iry5uFN0+ORXGZqL/Gp7MMc9AJ/qaP4hAMIQBbyAlxcNYrjG/i8YfnvowWTQix2WHXRrdibbb4l/cmkzazoWTdc/HynbKeGfLd4QvgnPDG/UcPtuBG/JcWD4rX+jxiXJE7FjYM+RXoxEp7IRHmj1dm9AxNLKwMM5vkYqyHXoU5OqQH7PyxS5mjDLaxY71XAD0aIm2qDDa85u1XXmysBNNREk10ok2ebOVkCIU53BF6URrHUiR38VonCPLoR57KMpuecOBoGkFwWRskgS7baSAOf/NIIpznCgQ/Cp9ZOvvoGlxjljTObTfbbJohLZ1euR0DpFvQ5JpRo4Lq24uwrIb8oQf6zJwwZbnkhEIKfjTV1dxzyJPyheFju5Ex7/RylTQx9z1XBOazgFgVJyjd8ici8lExTsyz+hoPStJ6FPu3LlzePDBB1FdXY2amhq0trZGvc9DDz2EDRs2oKqqCkeOHNH/7ec//zlWr16N6upqVFdX49y5c4kcDhFZgLawMNVjvdSfrWai9YVgInEObcRdZCY63IEU3TQl8nji//nq46KNVxsOhKZ8MkciXBGTEc5/MyjchQZG73qnxjnMW1gYbUILEN/FVOSuhf5gCLIJfweaPfctRuXC1Mxpzo0YB3fPotRGOQBtxJ3699o96BOaEZ1sJbkuuGQbvuoewnBA/UYs3ouKomlO9A4HMOwPot8rlom2inhH5hkdrWclCZX7u3fvxtatW7Fq1Sp88MEH2L17N1555ZVR93G73WhqasKcOXPQ0dGB2tparFy5Enl56tXxk08+ibvvvjuRwyAiC9GKUVN2LJRtCClqB1CdE21gxF1kJ9pAnMNoJ1q775A/OG5R17A/OOWTORLhsEvwBULwBUL4svsaVt5UKPwcWue53xtQO9FOMxYWRr+Q8cWZiQbU2cS9ozrR1r34SSbtIujWG/ISmmxhVGQnumfIjxvyUhODiMYmSaiYnoWLPUMoK3ALvX8UhcfcfdWtRjom2/LbiuIdmZfIaD2rSOivW5IkDA6qi0j6+/tRUjL+ivfGG2/EnDlzAAAejweFhYXo7u5O5McSkYWZumOhfeTr+IBgJlorXL8Mz3fVngcQm85hkyQ9TyqWiR4fJ9EM+0NTPpkjEU7ZBn9QwZdXriEYUnCL4KJCQI0DAGoX0RsIIduETnSshYV+gW8k1E60mukMBBVTO9GppMUO7knxgkJNZCba7DgHoI650+Ic8Wz5rdE66F9cUWurdIxzxBpnN/b2eO9nZQm9K9fX16O5uRmrVq1CU1MT6urqJrx/a2sr/H4/Kioq9Nt+9atfoaqqCrt27YLPF32jASJKH2ZnogG1c+gPCmaiZRuql5bi4H/8DYfPdujPo/2bCO1DU6SIzoroRI9l5Uw0MLLRhdFFhQCQE+5ktvero7DM6URHH3E3Mp1DLM4RCIlFitLZrbPy8fR/nYcqk4potROtIKQouHrNZ9p4O83swixc7h3GgDco2IlWi+j/vKJezKdjnCPaduDRxtxFux+g4No16LnogwdlrFiRDY8nBytWZFsuLz3p0WzatAldXV3jbt+2bRtaWlqwY8cOVFZW4siRI2hoaMCBAweiPk9nZyeeeOIJNDU1wRb+equurg7FxcXw+/14+umnsW/fPjz22GOJ/UZEZKqRTrQ5mWhA7ST6QwqmCRYw29fMxde9w3ju//4VpXmukUVBghcEbocN/V519nPcj4mx7TigTufIN7AFcaq4wl+ln/9mEC7ZZujrfK0T3d6nbrhixsJC2SbBJkWZziGQic7PcqB32I+QoghfyKUz2Sbh3qWlpv18h6xO5ukbCiCoGN9oJVlmF2YhpKgdZSNF9Bdd6duJjnfjF+1+9fUu9PRIANT/dXdLqKtz4+RJP157zaHnptva1NsB64zMm/RdKlZRDADbt29HQ0MDAGD9+vV46qmnot5vYGAAP/rRj/D4449j+fLl+u1a/MPpdKKmpgb79+8XOXYisiBtyoUZnWhXRJxDHXEnvltbc9UibH71Yzxx6BNsvL0MgPjGMVpBbKQTHW3M3bA/CE+udRfbOOwSvAG1Ez13RjbsBrqvWqb2cq/arTJjx0JJkuC022IvLIwzzhFSgP7hgDoh5jrpRJvNaZegAPhmUD1/TO9ET58GAPiq+xrml8T/zYx23F9qneg0zEQD8Y/Mq60NoLFRK6JHDA1JePllB4LB6AsPrVJEJ/QpV1JSgpMnTwIAWlpa9OxzJJ/Ph61bt6K6unrcAsLOzk4A6paq7733Hm655ZZEDoeILEArZM3YsTByZrHott+aXLeMf6lZAoddwq//eAEAhDKNkfc3komOHuew9nQOLRN9/ptBQ3loQP0WQbZJaO83rxOtHce4hYVaNj6O86kgXPRcHfKr0zlYRKeEdtHeEY4DmZ2Jrgh/GxNSxBoKbocd2U47Lveqfwfp2IkWFWshYTD63lOWWniY0Lvys88+i6amJtx7773Yu3cvnnnmGQDAmTNn9A7122+/jVOnTuHNN98cN8ruZz/7GaqqqlBVVYWenh5s2bIlwV+HiMymFZCmdKIjM9Eh4wXMDflu7L1vsV6Ui248oRXEQnGOKNNBNFafzuG029DWO4S+4YDwdt8aSZKQ55bxt75wJtqEhYVAjCJaYPv3yF0LA4ITYsg4x7gi2tw4R45LxoxwNEN0TUVRtlPdZl62mbIWItU55FgLCe0xfnUrLTxM6JW5/fbb8cYbb4y7fenSpVi6dCkA6IVzNC+//HIiP56ILMgymehgYgXM4pl52PXfFuJ3H32t5xRFj0OoEy1P0Im2+nQOuw1tV9XO2fwSY51oQC08tN3ask1YWAioFzOxO9EiRXQAfsY5Uka70NWKaLPjHIDaje4a9IkX0dPUXQvNWAehbYCSyhxyQ4N31M8E1IWI//iPozPR2u1jFyiaybrvykSUltwmZqKd4zLRiRUwd91chH+9f5lwMa51jcV2LIyeiVYUJQ2mc4y8znMNxjmAkVw0YG4neuzCQp/gdA4AuDrkQzAJ5yDFJ7ITLcEaUy20nQtF42DaRXu+CVGOhoboG6Bs2eKesq50bW0Ae/cOo6wsBElSUFYWwt69w2hq8ka93Sp5aCDBTjQR0VgLSnLww7+rwB2zC1L+s0dlok3c6EK7kDA2J3p0J9oXVBBSxJ4r1bTXfVa+O6EOcmQO2qxMtNM+Ps6hTeeIZ0rL2E60SKSHjIvMRBdkOQwtbk02bXGhS/BbJG1WdCJ56IMH5UmnY0R7THd3rNdNmtKudKyFiPEuUDSLdd+ViSgtyXYbtvzDHFO+jh+ViTZxy2VjcY7omWitqB67i6GVaAWM0UWFGm3MnUu2mZYlznLYMOgbMyc6XFQ75MnPJ7dsg0u2hRcWMs6RKg55pIg2e1GhRutEi14A651og910LZLR1maDokhoa7Ohrs49aRdZ3W574vM13bblnmosookoY2jF63ASMtGJcMt22G2S0Ixgu03d6XBsJlqLd1i6Ex3+PecJjPKKJjcc5zBjvJ2mYvo0fNk9CEUZWbzk1xYWxvHfU5Ik5Lvl8MJC8TGLZIyWie7s91oiDw1EdKKFi2j1+AsMjrdrbIweyaivn7j4jXfqhZWmY5iNf91ElDFGbfsdUkzbLa4k1wlPjvh0gCyHfVwmWiuq0yETPS/BTnRuuBNtVpQDABZ4cjDgDeoLJQH1mw0JiLurrO1ayE506mgXK76gYvpkDs3MfDfy3TKKc8Q6t1qcw2gmOlaR29MjTdiNjnfqhZWmY5iNRTQRZQyt43Mt/HW8WV3A799ejpc3rhB+nEu2jetEe8PxDqvPiQZgeLydRiuizexEL/Sov8O5jn79Nl8gBKdsgyTFX0T36iPuWESnQuS3BFbpRMs2Ca8/cgceuu0GocclurAwdpE7cRQj+jbcY55BstZ0DLNZ912ZiEiQVkQPeNWFKGYVME7ZZugDMMthH5+JDoQ70RaeEz2/JAdLZuZiZl5iWUk9zmFiJ/rmGdlw2CV82jGg3+YTnLKhdaID3GwlZSJnuVslEw0ABdMcwhfzFdOzUFbgxiKPsYtStciNXgxPFMWInJIBKJCk0c8hSQo2bfJbeqFfqrGIJqKMIdskSIC+MEwkk2wFapxjdCd6JM5h3d/lnkUe/K//flvcndpY9DiHiZ1oh92GuTOyca5zpIj2BxWhkY1qER3gZispFPk6WyXOYVSOS8abm+/ErbPyDT2+tjaAwsLoRfRkUYza2gBOnx5EZ+cAXnhh9Hi5F15Qx87RCP51E1HGkCQJTtmGQV+4E51mXUC3wzZuxJ3WmbZyJjpZtE60mZloQM1Ff9YxoC8u9AZDwkV0vzeAYT870akyKs5xHWyVPZnGxvHRDNGNSrSCuqNjAKdPD7IDHQWLaCLKKG7ZhkGvlolOrwLG7bCPG6+WDtM5kiXPAtM5AGCBJxf93gC+7lUXF/rDmeh4aVGea/4gZJNmlV9vIscPWinOYZZYG5iwEE4u/nUTUUZxyjYMaJ3oNPsq/aaiafiia3DUZh/pMJ0jWawwnQMYWVyo5aJ9wp3okeM3a1b59Wb0wsL0jnMkS21tAA0NXsyapeDrr9VFhVOx42AyHTwoY8WKbHg8OVO2Q2IypdcnDBHRJJz2kU50un2Vfnt5AXxBBWcu9+m3aZ1oK0/nSBZtpzmzi6Cbi7Ih2ySciyiiRRcWatItUpSuIi+YC7PZiQaMb7pilnQ7XoBFNBFlmFGZ6DTrRN9Wlg+7BPz50lX9Ni0jbeXpHMmS45Kx/5+W494lHlOPwymriws/DY+58xlYWKhhJzo1tP8+LtmGadfBtzbxiLXpSqp2HBTtKpt9vEak1ycMEdEk3PLIts3plonOcclYWJqLUxdHF9E2Kf1+F6MWleZaIroy35ODTzvVxYU+wUx0ZCbXwUx0Smgj7qZnORKeEpMpYo2zS8WOg0a6ymYer1H86yaijOK020bmRKdhAXN7eQHOtvfr3fThQAhZDjsLgxRb6MlB33AAl/uG4RfMROe72YlONXt4vCUXFY6INc4uFTsOGukqm3m8RqXfJwwR0QScsg2+oPqmm44FzB0VBQiGFHzcpuaih/0hfRMZSp0FnlwA6uJCX1CsE+2UbfqEEU7nSA1tvKXZeXoribYDoeiYO6OMdJXNPF6j+NdNRBklsuBMt0w0ACy7IQ8Ou4Q/hyMdQ/6gJeIN15u5M7Jht6k7F/oCoVE74sVDG3OXjhdy6cppt7ETHcHMMXdGu8putwJ1t0UFhYXWH8tn3SWPREQGjC6i06+AcTvsWHZDHk6FFxeqcY70uxhIdy7ZhpuLpoU70eI7DxZkOXC5d5jTOVLokW+XY1FprtmHYSm1tQFTitCGBi/q6tyjIh0TdZW1DHXk/YeGpvwwE8Z3ZiLKKJHZ1XTMRANqLvqvnQO4OuTHsD94XUzmsKKFnlyc6+iHLyAeqdFmRbMTnTrfv6Mc3yovMPswMkKi85pFu+DpOJkDYBFNRBkmMruargXMHRUFUACcvnRVLaLZiTbFAk8OeocD6BnyG+pEA+l7IUfpLZEi+OBBGT/+8ejJGj/+sfi8ZpFtw9NxMgfAIpqIMow7zeMcALC4NBdZDhv+fPGqPp2DUk/buRCAcCZaK6LTbcMfSn+JblpSX++C3z/6vPX7JdTXT11XOB0ncwAsookow2RCnEO223BbWT5OXbqKYX9o1IUBpc7c4hzYw0WwyIg7IKITnYaLWym9JRqN6OmJfuEX6/ZkSMfJHACLaCLKMM4M6EQDai76QvcQ2vuH4WIn2hQu2YabiqYBgNCIOyBiOgc70ZRi6RiNMHOSSCI4nYOIMkq6j7jT3FGhLpAa8oeQxU60aRaU5OD8N4OGM9Hpmsun9DVrloK2tvHnXbzRiMJCBd3d4x9fWDi10QqzJokkgu/MRJRRIovodO4C3lKcgzy32ufgnGjzaJuuiMY5ls7Mxe0VBbi5KHsqDosopkSjEY2NXjidox/vdCpobLR2tMIMLKKJKKOMykSncSfabpOwoiwfAJiJNpG2uFB0YWFxjgsvPrAMBdz8g1Is0WhEbW0Azz8/+vHPP5+6aEWi4/VSybpHRkRkgJZdtUnQF4WlqzsqpuPY51c4ncNEC0tz8c9/V4GVNxWafShEcUs0GmFWtGLspittbRLq6twArJmPZnuDiDKKK9x9TucutObOcC46x8Ui2iyyTcKP/mEOZuRYe9MHokyQbpuusBNNRBlFy0Sncx5aM6doGp6vWYJlN+SZfShERFMu2oJIwLqTRRIuos+dO4edO3fC6/XCbrfjF7/4BZYtWzbufgsXLsS8efMAADNnzsSvf/1rAMClS5dQV1eHq1evYvHixWhubobT6Uz0sIjoOqXFOTKhEw0Af38jYwRElPkOHpQhSYASZQiIVTddSfhTZvfu3di6dSsOHTqEn/zkJ9i9e3fU+7ndbhw6dAiHDh3SC2gA2LNnDzZt2oR3330XeXl5eP311xM9JCK6jrn0ItqanQsiIhqvsdEFRRn/vi1J1t10JeEiWpIkDA4OAgD6+/tRUlIS92MVRUFLSwsqKysBAN/73vdw9OjRRA+JiK5jehGdAXEOIqLrRazIhqLAkosKgSTEOerr67F582Y0NTUhFArhtddei3o/r9eLmpoayLKMRx99FGvXrkVPTw/y8vIgy+phlJaWoqOjI9FDIqLrmDbiTs6QOAcR0fUg1iYxZWXWjHIAcRbRmzZtQldX17jbt23bhpaWFuzYsQOVlZU4cuQIGhoacODAgXH3/cMf/gCPx4NLly7h4Ycfxrx585CTk5PwL0BEFMnJOAcRUdppaPCOGm8HiG0SY4a4iuhoRbFm+/btaGhoAACsX78eTz31VNT7eTweAEB5eTnuvPNOfPLJJ6isrERfXx8CgQBkWUZ7e7t+PyIiI0biHOxEExGlCzWyMYzGRhfa2iTY7cDQEPTxdlaMdCT8KVNSUoKTJ08CAFpaWjBnzpxx9+nt7YXP5wMAdHd34/Tp05g7dy4kScK3v/1tvPPOOwCAN998E6tXr070kIjoOsaFhURE6am2NhDethwIBiUAEtrabKirc1ty50JJUaINE4nfqVOnsGvXLgQCAbhcLuzcuRNLlizBmTNn8Nprr6GxsRGnT5/Gzp07IUkSFEXBD37wAzzwwAMA1BF3jz/+OHp7e7Fw4ULs2bNn0hF3fn8QV69eS+SwiShDDXgD+C//+v9wW1k+9j10q9mHQ0REAlasyEZb2/geb1lZCKdPD5pwREBxcW7U2xMuos3AIpqIYvEHQ/j7f/l33FlRgH97YPzMeiIisi6PJyfmqLuOjgETjih2Ec3QIBFlFNkmQULmbLZCRHQ9ibWxihU3XOGnDBFlFEmS4JJtzEQTEaUhNRM9umC26pQOFtFElHHUIppvb0RE6aa2NoC9e4dRVhaCJCkoKwth795hS07nsN5SRyKiBDllG2TuWEhElJZqawOWLJrHYhFNRBnnB3eUY05hltmHQUREGYzTOYiIiIiIYuB0DiIiIiKiJGERTUREREQkiEU0EREREZEgFtFERERERIJYRBMRERERCWIRTUREREQkiEU0EREREZEgFtFERERERIJYRBMRERERCWIRTUREREQkiEU0EREREZEgFtFERERERIJYRBMRERERCZIURVHMPggiIiIionTCTjQRERERkSAW0UREREREglhEExEREREJYhFNRERERCSIRTQRERERkSAW0UREREREglhEx/D2229jw4YNWLBgAc6cOaPf/sc//hE1NTWoqqpCTU0NTpw4of/bX/7yF1RVVWHdunV47rnnwOmB8Yv1egPASy+9hHXr1qGyshLHjx/Xb//www9RWVmJdevWYd++fak+5Ixy7tw5PPjgg6iurkZNTQ1aW1sBAIqi4LnnnsO6detQVVWFs2fPmnykmeOVV17B3XffjQ0bNqC5uVm/Pdb5Tonbv38/5s+fj+7ubgA8v6dSU1MT7r77blRVVWHr1q3o6+vT/43n+NTgZ6IJFIrq888/V7744gtl48aNSmtrq3772bNnlfb2dkVRFOWzzz5TVq5cqf9bbW2t8tFHHymhUEjZvHmzcuzYsZQfd7qK9XqfP39eqaqqUrxer3Lx4kVlzZo1SiAQUAKBgLJmzRrl4sWLitfrVaqqqpTz58+b+Bukt0ceeUQ/X48dO6Zs3LhR//+bN29WQqGQ8tFHHyn333+/mYeZMU6cOKE8/PDDitfrVRRFUbq6uhRFiX2+U+IuX76s/PCHP1S++93vKleuXFEUhef3VDp+/Lji9/sVRVGU5uZmpbm5WVEUnuNThZ+J5mAnOoabb74ZN91007jbFy1aBI/HAwC45ZZb4PV64fP50NnZiYGBASxfvhySJOG+++7D0aNHU33YaSvW63306FFs2LABTqcT5eXlmD17NlpbW9Ha2orZs2ejvLwcTqcTGzZs4OudAEmSMDg4CADo7+9HSUkJAPX1v++++yBJEpYvX46+vj50dnaaeagZ4dVXX8Wjjz4Kp9MJACgqKgIQ+3ynxP3yl7/EE088AUmS9Nt4fk+dlStXQpZlAMDy5cvR3t4OgOf4VOFnojlYRCfgnXfewaJFi+B0OtHR0YHS0lL930pLS9HR0WHi0WWGsa+rx+NBR0dHzNvJmPr6ejQ3N2PVqlVoampCXV0dgPGvP8/r5Lhw4QJOnTqFBx54ABs3btSLCJ7XU+O9995DSUkJFixYMOp2nt+pcfDgQdx1110AeI5PFb6u5pDNPgAzbdq0CV1dXeNu37ZtG9auXTvhY8+fP489e/Zg//79U3V4GSeR15sSN9Hr39LSgh07dqCyshJHjhxBQ0MDDhw4kPqDzCATvd7BYBC9vb343e9+hzNnzmDbtm3sGiVootf7pZde4nv1FIjnPf3FF1+E3W7Hvffem+rDI5py13URbbRIaG9vx2OPPYampiZUVFQAUK/6tK+rtPtosQ9SGXm9x76uHR0d+usa63aKbqLXf/v27WhoaAAArF+/Hk899RQAnteJmOj1fvXVV7Fu3TpIkoRly5bBZrOhp6dnwvOdJhbr9f7ss8/Q1taG6upqAOo5XFNTg9///vc8vxM02Xv6G2+8gWPHjuHAgQN6jIbn+NTg62oOxjkE9fX14dFHH8VPf/pTfOtb39JvLykpQU5ODj7++GMoioK33noLa9asMfFIM8Pq1atx+PBh+Hw+XLp0CRcuXMCyZcuwdOlSXLhwAZcuXYLP58Phw4exevVqsw83bZWUlODkyZMAgJaWFsyZMweA+vq/9dZbUBQFH3/8MXJzc/W8NBm3du1a/OlPfwIAfPnll/D7/Zg+fXrM852Mmz9/Pk6cOIH3338f77//PkpLS/HGG2+guLiY5/cU+vDDD/Gb3/wGL774IrKysvTbeY5PDX4mmkNSFM5hi+bdd9/Fs88+i+7ubuTl5WHhwoX47W9/ixdeeAH79u3D7Nmz9fvu378fRUVFOHPmDHbs2IHh4WHcddddePrpp0ctYqHYYr3egPp14MGDB2G321FfXz/xfAMAAADiSURBVI9Vq1YBAD744APs2rULwWAQtbW12LJli5m/Qlo7deoUdu3ahUAgAJfLhZ07d2LJkiVQFAXPPPMMjh8/jqysLOzatQtLly41+3DTns/nQ319PT799FM4HA48+eST+M53vgMg9vlOybF69Wq8/vrrKCws5Pk9hdatWwefz4eCggIAwK233opnnnkGAM/xqcLPxNRjEU1EREREJIhxDiIiIiIiQSyiiYiIiIgEsYgmIiIiIhLEIpqIiIiISBCLaCIiIiIiQSyiiYiIiIgEsYgmIiIiIhLEIpqIiIiISND/B2HMX/n/WzKsAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "snN_Flr5DWQN",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8c9fb49d-7743-4966-845b-f56a06bbe9e6"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "inputs = Input(shape=(120, 4))\n",
-        "lstm_units = 32\n",
-        "lstm_out = LSTM(lstm_units, return_sequences=True)(inputs)\n",
-        "lstm_out=tf.keras.layers.Dropout(0.6)(lstm_out)\n",
-        "attention_mul = attention_3d_block(lstm_out)\n",
-        "#attention_mul = Flatten()(attention_mul)\n",
-        "attention_mul=tf.keras.layers.Dropout(0.6)(attention_mul)\n",
-        "output = Dense(1, activation='sigmoid')(attention_mul)\n",
-        "\n",
-        "multi_step_model = Model(inputs, output)\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)\n",
-        "multi_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 5s 50ms/step - loss: 0.5863 - rmse: 0.5965 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5432 - rmse: 0.5432 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 2s 39ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 2s 40ms/step - loss: 0.5431 - rmse: 0.5431 - val_loss: 0.5431 - val_rmse: 0.5431\n",
-            "Model: \"model_2\"\n",
-            "__________________________________________________________________________________________________\n",
-            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
-            "==================================================================================================\n",
-            "input_3 (InputLayer)            [(None, 120, 4)]     0                                            \n",
-            "__________________________________________________________________________________________________\n",
-            "lstm_2 (LSTM)                   (None, 120, 32)      4736        input_3[0][0]                    \n",
-            "__________________________________________________________________________________________________\n",
-            "dropout_4 (Dropout)             (None, 120, 32)      0           lstm_2[0][0]                     \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_input_t (Permute)     (None, 32, 120)      0           dropout_4[0][0]                  \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_input_reshape (Reshap (None, 32, 120)      0           attention_input_t[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score_vec (Dense)     (None, 32, 120)      14400       attention_input_reshape[0][0]    \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score_vec_t (Permute) (None, 120, 32)      0           attention_score_vec[0][0]        \n",
-            "__________________________________________________________________________________________________\n",
-            "last_hidden_state (Lambda)      (None, 32)           0           attention_input_reshape[0][0]    \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_score (Dot)           (None, 120)          0           attention_score_vec_t[0][0]      \n",
-            "                                                                 last_hidden_state[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_weight (Activation)   (None, 120)          0           attention_score[0][0]            \n",
-            "__________________________________________________________________________________________________\n",
-            "context_vector (Dot)            (None, 32)           0           attention_input_reshape[0][0]    \n",
-            "                                                                 attention_weight[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "reshape_4 (Reshape)             (None, 32)           0           context_vector[0][0]             \n",
-            "__________________________________________________________________________________________________\n",
-            "reshape_5 (Reshape)             (None, 32)           0           last_hidden_state[0][0]          \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_output (Concatenate)  (None, 64)           0           reshape_4[0][0]                  \n",
-            "                                                                 reshape_5[0][0]                  \n",
-            "__________________________________________________________________________________________________\n",
-            "attention_vector (Dense)        (None, 128)          8192        attention_output[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "dropout_5 (Dropout)             (None, 128)          0           attention_vector[0][0]           \n",
-            "__________________________________________________________________________________________________\n",
-            "dense_2 (Dense)                 (None, 1)            129         dropout_5[0][0]                  \n",
-            "==================================================================================================\n",
-            "Total params: 27,457\n",
-            "Trainable params: 27,457\n",
-            "Non-trainable params: 0\n",
-            "__________________________________________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Ay5m27doDsTt",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "e9e4b8ea-77d6-438f-9698-91b95180e6f2"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6ZFP49W4D2wp",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "41c0548f-3fd9-41eb-b2c8-045ec24f59c3"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "error",
-          "ename": "ValueError",
-          "evalue": "ignored",
-          "traceback": [
-            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-            "\u001b[0;32m<ipython-input-41-ff89c8e0e80a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mval_data_multi\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mmulti_step_plot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmulti_step_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-            "\u001b[0;32m<ipython-input-38-27efd3ecf8d8>\u001b[0m in \u001b[0;36mmulti_step_plot\u001b[0;34m(history, true_future, prediction)\u001b[0m\n\u001b[1;32m     10\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mprediction\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n\u001b[0;32m---> 12\u001b[0;31m              label='Predicted Future')\n\u001b[0m\u001b[1;32m     13\u001b[0m   \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'upper left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m   \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2761\u001b[0m     return gca().plot(\n\u001b[1;32m   2762\u001b[0m         *args, scalex=scalex, scaley=scaley, **({\"data\": data} if data\n\u001b[0;32m-> 2763\u001b[0;31m         is not None else {}), **kwargs)\n\u001b[0m\u001b[1;32m   2764\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2765\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1645\u001b[0m         \"\"\"\n\u001b[1;32m   1646\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1647\u001b[0;31m         \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1648\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1649\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    214\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    215\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m             \u001b[0;32myield\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_plot_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    218\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_next_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[0;34m(self, tup, kwargs)\u001b[0m\n\u001b[1;32m    340\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    341\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 342\u001b[0;31m             raise ValueError(f\"x and y must have same first dimension, but \"\n\u001b[0m\u001b[1;32m    343\u001b[0m                              f\"have shapes {x.shape} and {y.shape}\")\n\u001b[1;32m    344\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (72,) and (1,)"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YXcsNZ8yu9Ay"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "uCFgbZEOvZ9A"
-      },
-      "source": [
-        "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
-        "\n",
-        "plt.figure(figsize=(10,5))\n",
-        "plt.plot(y_pred_test)\n",
-        "plt.plot(y_val_multi)\n",
-        "plt.ylabel(\"RUL\")\n",
-        "plt.xlabel(\"Unit Number\")\n",
-        "plt.legend(loc='upper left')\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1Pdu1pZyZExX"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 521
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "120b11e9-5c7d-4332-d133-9636a8d002aa"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "2104e011-6066-4e86-e6f8-515dfb9ea715"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "ea97c36d-cb27-4fb3-d9bd-e8f1776b098d"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "9e21fcc0-a838-4449-ef31-8e7d1df4d060"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "1a35f11e-eb94-4404-bd86-6f6fc2765ba2"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "2396e496-512e-45de-b804-acfb32e79b41"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "dcf3d389-1ac0-4005-ae48-53e0f96548b1"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YoQA_MIBMknS"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "57b8d44c-ad3d-45e0-82da-1787d6d47d55"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "f5386858-2a38-4b20-9be9-f841ee5af0d6"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "a611220f-df65-4d99-9c8f-dc0dd715f93f"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "8750fe62-a1e7-40ca-a3c1-4285546f97ff"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "b43752ab-2ff0-4e21-a4bc-633cd0aff7dd"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "614149cc-6746-4d02-a608-2957cef79338"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "f9dc4c4f-ccfa-4379-add5-cd732dc8a310"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "81S0BbNa7Rce"
+   },
+   "outputs": [],
+   "source": [
+    "import tensorflow as tf\n",
+    "from keras.layers import Activation, Dense, Dropout,Permute,Reshape,Lambda,dot,concatenate\n",
+    "\n",
+    "INPUT_DIM = 100\n",
+    "TIME_STEPS = 20\n",
+    "# if True, the attention vector is shared across the input_dimensions where the attention is applied.\n",
+    "SINGLE_ATTENTION_VECTOR = True\n",
+    "APPLY_ATTENTION_BEFORE_LSTM = False\n",
+    "\n",
+    "ATTENTION_SIZE = 128\n",
+    "\n",
+    "def attention_3d_block(hidden_states):\n",
+    "    # hidden_states.shape = (batch_size, time_steps, hidden_size)\n",
+    "    hidden_size = int(hidden_states.shape[2])\n",
+    "    # _t stands for transpose\n",
+    "    hidden_states_t =  Permute((2, 1), name='attention_input_t')(hidden_states)\n",
+    "    # hidden_states_t.shape = (batch_size, hidden_size, time_steps)\n",
+    "    # this line is not useful. It's just to know which dimension is what.\n",
+    "    hidden_states_t = Reshape((hidden_size, TIME_STEPS), name='attention_input_reshape')(hidden_states_t)\n",
+    "    # Inside dense layer\n",
+    "    # a (batch_size, hidden_size, time_steps) dot W (time_steps, time_steps) => (batch_size, hidden_size, time_steps)\n",
+    "    # W is the trainable weight matrix of attention\n",
+    "    # Luong's multiplicative style score\n",
+    "    score_first_part = Dense(TIME_STEPS, use_bias=False, name='attention_score_vec')(hidden_states_t)\n",
+    "    score_first_part_t = Permute((2, 1), name='attention_score_vec_t')(score_first_part)\n",
+    "    #            score_first_part_t         dot        last_hidden_state     => attention_weights\n",
+    "    # (batch_size, time_steps, hidden_size) dot (batch_size, hidden_size, 1) => (batch_size, time_steps, 1)\n",
+    "    h_t = Lambda(lambda x: x[:, :, -1], output_shape=(hidden_size, 1), name='last_hidden_state')(hidden_states_t)\n",
+    "    score = dot([score_first_part_t, h_t], [2, 1], name='attention_score')\n",
+    "    attention_weights = Activation('softmax', name='attention_weight')(score)\n",
+    "    # if SINGLE_ATTENTION_VECTOR:\n",
+    "    #     a = Lambda(lambda x: K.mean(x, axis=1), name='dim_reduction')(a)\n",
+    "    #     a = RepeatVector(hidden_size)(a)\n",
+    "    # (batch_size, hidden_size, time_steps) dot (batch_size, time_steps, 1) => (batch_size, hidden_size, 1)\n",
+    "    context_vector = dot([hidden_states_t, attention_weights], [2, 1], name='context_vector')\n",
+    "    context_vector = Reshape((hidden_size,))(context_vector)\n",
+    "    h_t = Reshape((hidden_size,))(h_t)\n",
+    "    pre_activation = concatenate([context_vector, h_t], name='attention_output')\n",
+    "    attention_vector = Dense(ATTENTION_SIZE, use_bias=False, activation='tanh', name='attention_vector')(pre_activation)\n",
+    "    return attention_vector"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "e1863cec-a19f-4419-fe8c-527e549bccdf"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "from keras.layers import Input, LSTM, merge ,Conv1D,Dropout,Bidirectional,Multiply,Flatten\n",
+    "from keras.models import Model\n",
+    "from keras.utils.vis_utils import plot_model\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "TIME_STEPS=120\n",
+    "INPUT_DIMS=4\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "inputs = Input(shape=(120, 4))\n",
+    "lstm_units = 32\n",
+    "lstm_out = LSTM(lstm_units, return_sequences=True)(inputs)\n",
+    "lstm_out=tf.keras.layers.Dropout(0.6)(lstm_out)\n",
+    "attention_mul = attention_3d_block(lstm_out)\n",
+    "#attention_mul = Flatten()(attention_mul)\n",
+    "attention_mul=tf.keras.layers.Dropout(0.6)(attention_mul)\n",
+    "output = Dense(1, activation='sigmoid')(attention_mul)\n",
+    "\n",
+    "single_step_model = Model(inputs, output)\n",
+    "\n",
+    "  \n",
+    "single_step_model.summary()\n",
+    "\n",
+    "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/LSTM-Attention-B.png', show_shapes=True, show_layer_names=True)\n",
+    "\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "94000u5xIjWD",
+    "outputId": "c3f7f857-fbb7-4fc5-b2bf-d860a828d0a9"
+   },
+   "outputs": [],
+   "source": [
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "a97e1688-da30-4042-c349-fa8971512907"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "be978504-7501-42fe-c192-4c6b023e992a"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "56ae677f-dadd-434f-f31b-d7cc9ee0eb89"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "9436a6eb-214e-47a3-d241-3a5bd056c31c"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "185bb543-b7ad-4f25-fd89-75be524af04e"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "553066ce-28bf-4e95-95c1-f7f34f907647"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "8c9fb49d-7743-4966-845b-f56a06bbe9e6"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "inputs = Input(shape=(120, 4))\n",
+    "lstm_units = 32\n",
+    "lstm_out = LSTM(lstm_units, return_sequences=True)(inputs)\n",
+    "lstm_out=tf.keras.layers.Dropout(0.6)(lstm_out)\n",
+    "attention_mul = attention_3d_block(lstm_out)\n",
+    "#attention_mul = Flatten()(attention_mul)\n",
+    "attention_mul=tf.keras.layers.Dropout(0.6)(attention_mul)\n",
+    "output = Dense(1, activation='sigmoid')(attention_mul)\n",
+    "\n",
+    "multi_step_model = Model(inputs, output)\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)\n",
+    "multi_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "e9e4b8ea-77d6-438f-9698-91b95180e6f2"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "41c0548f-3fd9-41eb-b2c8-045ec24f59c3"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "DNKMjVoAVqZP"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YXcsNZ8yu9Ay"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "uCFgbZEOvZ9A"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
+    "\n",
+    "plt.figure(figsize=(10,5))\n",
+    "plt.plot(y_pred_test)\n",
+    "plt.plot(y_val_multi)\n",
+    "plt.ylabel(\"RUL\")\n",
+    "plt.xlabel(\"Unit Number\")\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1Pdu1pZyZExX"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "LSTM_Attention.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/LSTM_correlation.ipynb b/models/failure_prediction/jnotebooks/LSTM_correlation.ipynb

index 4eb480b..3090cf8 100644 (file)
--- a/models/failure_prediction/jnotebooks/LSTM_correlation.ipynb
+++ b/models/failure_prediction/jnotebooks/LSTM_correlation.ipynb
@@ -1,1533 +1,793 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "RW6MfrDdMIP7"
+   },
+   "source": [
+    "Contributors: Rohit Singh Rathaur, Girish L.\n",
+    "\n",
+    "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
+    "\n",
+    "http://www.apache.org/licenses/LICENSE-2.0\n",
+    "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "LSTM-correlation.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    },
-    "accelerator": "GPU"
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "cb34bd5a-8e52-43cc-90d1-954431091e6b"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/gdrive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "RW6MfrDdMIP7"
-      },
-      "source": [
-        "Contributors: Rohit Singh Rathaur, Girish L.\n",
-        "\n",
-        "Copyright 2021 [Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n",
-        "\n",
-        "http://www.apache.org/licenses/LICENSE-2.0\n",
-        "Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "cb34bd5a-8e52-43cc-90d1-954431091e6b"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/gdrive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /gdrive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "V4G3MxsJMN4m"
-      },
-      "source": [
-        "We are importing the libraries:\n",
-        "\n",
-        "- TensorFlow: to process and train the model\n",
-        "- Matplotlib: to plot the training anf loss curves\n",
-        "- Pandas: used for data analysis and it allows us to import data from various formats\n",
-        "- Numpy: For array computing"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "W46t-S6TMZVG"
-      },
-      "source": [
-        "We are reading the CSV file using `read_csv` function and storing it in a DataFrame named `df_Ellis`"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 521
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "94530f09-ebe1-4361-9b23-e21ec5f0f649"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 4
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "727ad3d1-e00a-4d6e-9ce8-6859b01fa6ce"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9828b56310>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 5
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "c4a79b59-30eb-41ba-9d34-2c7cad07d9f2"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "f96a17fc-a509-4c29-e57f-1dfda73d8df6"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "4a3a36e3-c071-4353-cd86-0ab6b1afba0e"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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ZO8Jt0dKn5Okjcn2SfJ7yWZmOThJBcm+ada67XdzAkAAADAyOo6eKq1npzk5C77zslavoys1nrH2p6v0ffrGfoZUAAAAAC0pO1vtQMAAABgAyV4AgAAAKARgqcNVK1tVwAAAACMdYM5XJwe9evHF+cv/+2Xue2BJ7Lf1BdnnykvbrskAAAAYAwQPI0B7//Wf+UX9z+eJPnhbQ/nh7c93HJFAAAAwFhgq90G7tGnlq4KnQAAAABGkuBpA1VK3/XJJc+2WwgAAAAwZgmeAAAAAGiE4AkAAACARgieNlDX3Dmv7RIAAACAMU7wtIE6/ap7MnveorbLAAAAAMYwwdMG7JD/e3Vunruw7TIAAACAMUrwtIH7wL/+ou0SAAAAgDFK8AQAAABAIwRPPaTW2nYJAAAAAF0TPAEAAADQCMFTDymltF0CAAAAQNcETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwxo6bIVbZcAAAAA9DDBEwN65amX5apZj7RdBgAAANCjBE8M6Kmly/Phf/tlVqyobZcCAAAA9CDBE2s1f9HS3PrAwrbLAAAAAHqQ4Il1enrp8rZLAAAAAHqQ4AkAAACARgieAAAAAGiE4IlG1epgcgAAABirBE806u5HFrVdAgAAANASwRONOvOa2W2XAAAAALRE8MQ6lfUY+/jTzw5bHQAAAEBvETz1kLbOS5px32OtzAsAAAD0NsFTD2nrmO7P/+jOlmYGAAAAepngqYesz5a39bFsxdAjr9JW0QAAAEDrBE8AAAAANELwBAAAAEAjBE806ke3P9x2CQAAAEBLBE80Zv6iZ9ouAQAAAGiR4InGfOun97ddAgAAANAiwRONuf/Rp9suAQAAAGiR4AkAAACARgieekhtuwAAAACAQRA89ZCZDz7RdgkAAAAAXRM89ZDTr7qn7RIAAAAAuiZ46iELFz/bdgmtmP7SrdouAQAAABgCwROj3ote+IK2SwAAAACGQPAEAAAAQCMET4x6pbRdAQAAADAUgqceUtsuYJCGKy+qvfbBAQAAgCSDCJ5KKUeVUr5cSrm2lPJEKaWWUs4d7ISllDmdsf39PLSWcQeUUi4ppTxaSllcSrm5lPLnpZTxg62hZwlgAAAAgB4yYRB9/y7JXkkWJZmbZNp6zLswyRf6aV/UX+dSypuSfDvJkiQXJHk0yRuSfD7JgUneuh61AAAAANCAwQRPJ6UvcLo7ycFJrlyPeR+vtZ7cTcdSyhZJvppkeZLfrrXO6LT/fZIrkhxVSnl7rfX89ainN4zZs44s9QIAAIBe1PVWu1rrlbXWu2od8RN3jkoyOcn5K0OnTj1L0rcKK0n+1wjXBAAAAMA6DGbF03DaqJTyriQ7Jnkqyc1Jrqm1Lu+n7yGd6w/6eXZNkqeTHFBK2ajW+kwj1QIAAAAwaG0FT9slOWeNtntLKcfVWq9eo323zvXONV9Sa11WSrk3yR5Jpia5Y9grZchskAMAAICxreutdsPorCSHpi982jTJnknOTDIlyaWllL3W6L9l57pwgPetbH/R8JYJAAAAwPoY8RVPtdZT1mi6Ncl7SymLknwoyclJ3jxc85VSjk9yfJLsuOOOw/XaVixdtqLtEgAAAAC61saKp4Gc0bketEb7yhVNW6Z/K9sf7+9hrfUrtdbptdbpkydPXs8Sx66RP1N+9blbmxoAAABYD6MpeJrXuW66RvusznXXNQeUUiYk2SnJsiSzmyuNWQ8/OegxpYE6AAAAgN4xmoKn/TrXNQOkKzrXw/sZc1CSFya5wTfaNeufr7qntbkteAIAAIDe1EjwVEqZWEqZVkrZeY323Uspa65oSillSpJ/6tyeu8bji5LMT/L2Usr01cZsnOTjndt/HqbSGcDipctbm3uXbTdrbW4AAABg6Lo+XLyUcmSSIzu323Wu+5dSzu78Pr/W+uHO7y9JckeS+9L3bXUrHZ3kQ6WUazrPnkyyc5LXJ9k4ySVJPrv6vLXWJ0op705fAHVVKeX8JI8meWOS3TrtF3T7Oeg9E8bZtAcAAAC9aDDfard3kmPXaJva+Un6gqQPZ+2uTF9Y9MokB6bvPKfHk1yX5Jwk59R+TrGutX6nlHJwkr9N8pb0hVR3J/mLJF/qbwwAAAAA7eo6eKq1npzk5C77zkk/Z0vXWq9OcnW3c64x9vokRwxlLAAAAAAjbzQdLg4AAADABkTwBAAAAEAjBE90xSFaAAAAwGAJnmhM8WV0AAAAMKYJngAAAABohOCJrli8BAAAAAyW4AkAAACARgieaEx1IjkAAACMaYInuiJDAgAAAAZL8AQAAABAIwRPAAAAADRC8AQAAABAIwRPAAAAADRC8ERjShme9/h2PAAAAOhNgicAAAAAGiF4AgAAAKARgicAAAAAGiF4AgAAAKARgicAAAAAGjGh7QLoTfcveDpn3XBvnli8LEfv8xt59U4vbrskAAAAYJQRPNGVWpOzrr83F9/8YDbfeEKumjVv1bPv/fKB/Nt7989ev/GiFisEAAAARhvBE135zzsezn/e8XC/z5YuX5F/vuqenHHMq0a4KgAAAGA0c8YTw+IHtz30vLaS0kIlAAAAwGgheKIxNbXtEgAAAIAWCZ4AAAAAaITgiWHz5JJn2y4BAAAAGEUETwybV576o/zjJXekVlvsAAAAAMETw2jZipozr5mdn977aJLkoSeeabkiAAAAoE2CJ4bdZ344K0ly3V3zWq4EAAAAaJPgiWF318NPJknGldJyJQAAAECbBE80Ztw4wRMAAACMZYInGjN+mFY8OaocAAAAepPgicZY8AQAAABjm+CJxthqBwAAAGOb4InGdHO4+HEHTmm+EAAAAKAVgieGXekETuO7WPH0kd9/WT7y+y9ruiQAAACgBYInhl2tfceBryt32n/qpJRS8iev2WkEqgIAAABGmuCJYdfJnVatfBrIhPHOgAIAAIANmeCJYffkM8uSrHvF05//zq4jUA0AAADQFsETjVnb4eKv221y9tphyxGsBgAAABhpgicas7bg6cxjpmfCeH/8AAAAYEPmb/40Ztxa/nS9YII/egAAALCh87d/GlPi8HAAAAAYywRPAAAAADRC8AQAAABAIwRPNKamtl0CAAAA0CLBEwAAAACNEDwBAAAA0AjBEwAAAACNEDzRmJIyLO+pjooCAACAniR4ojFleHInAAAAoEd1HTyVUo4qpXy5lHJtKeWJUkotpZw7mMlKKZNKKX9WSvn3UsrdpZTFpZSFpZTrSil/Wkp5Xj2llCmduQb6OX8wNTA67Tf1xW2XAAAAAAyzCYPo+3dJ9kqyKMncJNOGMN9bk/xzkgeTXJnk/iTbJvmDJF9L8nullLfW2u/mql8m+U4/7bcOoQ5Gmb/83Wk59hs/y6JnlrVdCgAAADBMBhM8nZS+wOnuJAenLzgarDuTvDHJ92utK1Y2llL+JsnPkrwlfSHUt/sZe1Ot9eQhzEkPeNVLt8oN/+eQvO/c/8p1d89vuxwAAABgGHS91a7WemWt9a4BViN1+44raq3fWz106rQ/lOSMzu1vD/X99LYtNp6YA35zUttlAAAAAMNkMCuemvZs5zrQXqvtSynvSTIpyYIkP6613jwilQEAAAAwaKMieCqlTEjyR53bHwzQ7X92flYfd1WSY2ut9zdXHUM19LVxAAAAwIag6612DftkkpcnuaTW+sM1nj2d5GNJXpVkq87PyjOmfjvJ5aWUTQd6cSnl+FLKjFLKjHnz5jVROwAAAAD9aD14KqWcmORDSWYmOWbN57XWR2qtH6m1/let9fHOzzVJDkvy0yS/meTPBnp/rfUrtdbptdbpkydPbuhTAAAAALCmVoOnUsr7k3wxye1JXldrfbTbsbXWZUm+1rk9qIHyAAAAAFgPrQVPpZQ/T/LlJLemL3R6aAivWbl3bsCtdrSnlLYrAAAAANrUSvBUSvnfST6f5Kb0hU6PDPFV+3Wus4elMAAAAACGTSPBUyllYillWill536e/X36DhO/Mcmhtdb563jXb5VSnldnKeXQJCd1bs8dhrIZZhY8AQAAwNg2oduOpZQjkxzZud2uc92/lHJ25/f5tdYPd35/SZI7ktyXZMpq7zg2yalJlie5NsmJ5fn7sebUWs9e7f5zSXYppdyQZG6n7RVJDun8/ve11hu6/RyMnNp2AQAAAECrug6ekuyd5Ng12qZ2fpK+kOnDWbudOtfxSf58gD5XJzl7tftzkrw5yT5Jfi/JxCQPJ7kwyT/VWq/tonYAAAAARljXwVOt9eQkJ3fZd0762Wk1mHesNubrSb4+mDEAAAAAtG8wK56ga6/51BWZ+9jitssAAAAAWtTKt9qx4RvO0Kk6LQoAAAB6kuCJUaX4LjwAAADYYAieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieGP1q2wUAAAAAQyF4YlQppe0KAAAAgOEieAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheGLUq20XAAAAAAyJ4IlRpbRdAAAAADBsBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANKLr4KmUclQp5cullGtLKU+UUmop5dyhTFpK2aGU8o1SygOllGdKKXNKKV8opWy1ljEvK6VcWEp5pJSypJQyq5RySillk6HUAAAAAECzJgyi798l2SvJoiRzk0wbyoSllJ2T3JBkmyT/kWRmklcn+WCSw0spB9ZaF6wxZt8kVySZmOSiJL9KckiSjyQ5tJRyaK31maHUAwAAAEAzBrPV7qQkuybZIsn/Wo85T09f6HRirfXIWutf11oPSfL5JLsl+YfVO5dSxic5K8kLkxxVa31nrfV/J9k3ybeTHNipDQAAAIBRpOvgqdZ6Za31rlprHepkndVOhyWZk+S0NR5/NMlTSY4ppWy6WvvBSXZPck2t9bur1bMiyV91bt9bSilDrQsAAACA4TfSh4u/rnO9rBMcrVJrfTLJ9elb2bTfao8O6Vx/sObLaq2zk9yZ5KVJpg57tQAAAAAM2UgHT7t1rncO8PyuznXX9RzDBmQ9FtkBAAAALRrp4GnLznXhAM9Xtr9oPcfQo2yYBAAAgA3HSAdPI66UcnwpZUYpZca8efPaLgcAAABgzBjp4Gnl6qQtB3i+sv3x9RyzSq31K7XW6bXW6ZMnT+66UAAAAADWz0gHT7M614HOY9qlc139PKehjAEAAACgZSMdPF3ZuR5WSnnO3KWUzZMcmOTpJD9Z7dEVnevha76slDI1fYHUfUlmD3u1AAAAAAxZI8FTKWViKWVaKWXn1dtrrfckuSzJlCQnrDHslCSbJjmn1vrUau1XJ7kjyUGllDeuNse4JJ/q3J5RffUZAAAAwKgyoduOpZQjkxzZud2uc92/lHJ25/f5tdYPd35/SfrCovvSFzKt7n1JbkjypVLKoZ1++yZ5Xfq2y/3t6p1rrctLKcelb+XTRaWUi5Lcn+TQJNOTXJ/k891+DgAAAABGRtfBU5K9kxy7RtvUzk/SFzJ9OOtQa72nlDI9yanp2z53RJIHk3wxySm11sf6GfPTUso+6VsVdViSzTvznZrkk7XWZwbxOQAAAAAYAV0HT7XWk5Oc3GXfOUnKWp7/Kslx3c7dGXN7krcOZgwAAAAA7Rnpw8UBAAAAGCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMET4x6tbZdAQAAADAUgidGlZLSdgkAAADAMBE8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8MUB5o/UAACAASURBVOI+fNiubZcAAAAAjADBEyPuhNf9ZtslAAAAACNA8MSIK6W0XQIAAAAwAgRPAAAAADRC8AQAAABAIwRPAAAAADRC8AQAAABAIwRPAAAAADRC8MSoV9suAAAAABgSwROjSiltVwAAAAAMF8ETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETo16tbVcAAAAADIXgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGDCp4KqXsUEr5RinlgVLKM6WUOaWUL5RStupy/G+XUmoXP7+xxri19f3JYD4DAAAAACNjQrcdSyk7J7khyTZJ/iPJzCSvTvLBJIeXUg6stS5Yx2vmJDllgGd7JvmDJLfWWn/Vz/P7kpzdT/vcdRYPAAAAwIjrOnhKcnr6QqcTa61fXtlYSvlckpOS/EOS967tBbXWOUlO7u9ZKeVfO79+dYDhc2qt/Y4FAAAAYPTpaqtdZ7XTYelbsXTaGo8/muSpJMeUUjYdShGllK2TvDnJ4iT/MpR3AAAAADC6dLvi6XWd62W11hWrP6i1PllKuT59wdR+SS4fQh3HJtkoyb/UWh8foM+LSil/kmS7JAuT3Fhrdb4TAAAAwCjVbfC0W+d65wDP70pf8LRrhhY8vbtzPXMtffZK8vXVG0opv0xyTK31liHMCQAAAECDuv1Wuy0714UDPF/Z/qLBFlBKOTh9wdattdYbBuj2uSQHJpmcZPMk+yS5KH1h1BWllJes5f3Hl1JmlFJmzJs3b7DlAQAAADBE3QZPTTq+c/3KQB1qrR+qtd5Qa51fa11Ua51Ra31rkm8n2TrJh9cy9iu11um11umTJ08e3soBAAAAGFC3wdPKFU1bDvB8ZftA5zP1q5Ty4iRvSd+h4ucMZmzHGZ3rQUMYCwAAAECDug2eZnWuuw7wfJfOdaAzoAay8lDxC9dyqPjarNw7N6Rv0wMAAACgOd0GT1d2roeVUp4zppSyefrOX3o6yWC/ZW7loeIDbrNbh/0619lDHE8PqKltlwAAAAAMQVfBU631niSXJZmS5IQ1Hp+SvhVH59Ran1rZWEqZVkqZNtA7SymvTbJ71n6oeEopryilTOyvPck/dG7P7eZzMPqVUtouAQAAABgmEwbR931JbkjypVLKoUnuSLJvktelb4vd367R/47OdaAkYZ2Hinf8RZI3lFKuTfKrJM8kmZbk8CTjk3w1yb92/zEAAAAAGAldB0+11ntKKdOTnJq+0OeIJA8m+WKSU2qtj3X7rlLKVkmOSneHin8nyRZJXpHkkCQbJ1mQ5NIkX621frfbeQEAAAAYOYNZ8ZRa66+SHNdl3wH3THVCqk26fM930hc+AQAAANBDuj1cHAAAAAAGRfAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMET3TlrD/eJ9O227ztMgAAAIAeIniiK/vvPCk/+POD2i4DAAAA6CGCJwAAAAAaIXhi1Ku17QoAAACAoRA8MaqUtgsAAAAAho3gCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgia7U2nYFAAAAQK8RPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPNGVUtquAAAAAOg1gicAAAAAGiF4AgAAAKARgicAAAAAGiF4oiu1jsw8zpICAACADYfgiUE55Y17tF0CAAAA0CMETwzK61/xP7LT1puuut/9f2zRYjUAAADAaDah7QLoLVtvtlG+874Dc8Wsh7PxhPHZb+qkvPJjP2q7LAAAAGAUEjwxaFu+cGLe/ModkiRLnl3ecjUAAADAaGWrHevFYeAAAADAQARPAAAAADRC8MR6KbHkCQAAAOif4AkAAACARgie6EpN7bfdGU8AAADAQARPAAAAADRC8NRD3vqqHdouAQAAAKBrgqce8u6DprY290CHiNtpBwAAAAxE8NRDdt1287ZLAAAAAOia4In1UpwuDgAAAAxA8AQAAABAIwRPrBfrnQAAAICBCJ4Y9WqtbZcAAAAADIHgia7UjEz4YwUVAAAAbDgGFTyVUnYopXyjlPJAKeWZUsqcUsoXSilbDeIdV5VS6lp+Nh5g3MtKKReWUh4ppSwppcwqpZxSStlkMJ+B4eVscQAAAGAgE7rtWErZOckNSbZJ8h9JZiZ5dZIPJjm8lHJgrXXBIOY+ZYD2Zf3MvW+SK5JMTHJRkl8lOSTJR5IcWko5tNb6zCDmBgAAAKBhXQdPSU5PX+h0Yq31yysbSymfS3JSkn9I8t5uX1ZrPbmbfqWU8UnOSvLCJG+qtX630z4uyYVJ3tKZ/5Pdzs3wKZY8AQAAAAPoaqtdZ7XTYUnmJDltjccfTfJUkmNKKZsOa3V9Dk6ye5JrVoZOSVJrXZHkrzq37y0SEAAAAIBRpdsznl7XuV7WCXxWqbU+meT69K1I2q/biUspR5dS/rqU8hellN8rpWw0QNdDOtcfrPmg1jo7yZ1JXppkardzAwAAANC8boOn3TrXOwd4flfnuusg5j4/yT8m+b9JLklyfynlqBGaGwAAAICGdRs8bdm5Lhzg+cr2F3Xxrv9I8oYkOyTZJMm09AVQL0pyQSnl8OGcu5RyfCllRillxrx587ooDwAAAIDh0G3wNGxqrZ+vtV5ca/11rXVJrXVWrfVvknyoU88/DvN8X6m1Tq+1Tp88efJwvhoAAACAteg2eFq5qmjLAZ6vbH98PWr5WpJlSfYupWw+wnOzDhtNGN92CQAAAECP6TZ4mtW5DnSO0i6d60DnMK1TrXVJkic7t6t/O17jc7N2f3LgThk/zpcGAgAAAIPTbfB0Zed6WCnlOWM6q5MOTPJ0kp8MtZBSym5Jtkpf+DR/tUdXdK5rnv2UUsrU9AVS9yWZPdS5Wbu/ff3ubZcAAAAA9KCugqda6z1JLksyJckJazw+JX0rlM6ptT61srGUMq2UMm31jqWUnUopL17z/aWUyUnO6tyeX2tdttrjq5PckeSgUsobVxszLsmnOrdn1FprN5+Fwfmd3be12gkAAAAYkgmD6Pu+JDck+VIp5dD0hUH7Jnld+ra5/e0a/e/oXFdPLQ5OckYp5br0rVB6NMmOSY5I31lNM5L81eovqbUuL6Ucl76VTxeVUi5Kcn+SQ5NMT3J9ks8P4nMAAAAAMAK6Dp5qrfeUUqYnOTV9296OSPJgki8mOaXW+lgXr7kxyflJXpXklUm2SN/WuluSXJjkzFrr0n7m/mkpZZ/0ra46LMnm6dted2qST9Zan+n2cwAAAAAwMgaz4im11l8lOa7Lvs/bn1VrvSXJHw9mztXG3p7krUMZO5btuu1mOepVO+Txp5/N6Vfd03Y5AAAAwBjS7eHijHL77vS8o7OSJFu98AU5/qCd81eHT+v3OQAAAEBTBE8biOMO3KntEhrj1HgAAADoTYKnDcSEAb55rvTYF9KVXisYAAAAGJDgCQAAAIBGCJ5Yq2nbbd52CQAAAECPEjwxoPHjSv5o/5e2XQYAAADQoya0XQCjz2YbTciWm0zM3xyxe7bZYuO2ywEAAAB6lOCJ53jJizbJNX/1uowrDvoGAAAA1o+tdj3mhNft3Oj7/+rw3TJ+XBE6AQAAAOvNiqcec+z+U3LalfcM2/vesNf22fMlW+Te+U/ld3bfNofuvu2wvRsAAAAY2wRPPWagM5d2336LIb1vk4njcvxBza6iAgAAAMYmW+160MfetMdz7g/adXJe8qJNWqoGAAAAoH9WPPWgY/afkhe+YEKumPlIdt5ms7znoKkD9t1p681GsDIAAACA/yZ46lFvedUOecurdnhO2z/+wZ75P//vlue0Hb+WUAoAAACgSbbabUCOetUOectv7ZDx40o2fcH4nPLGPbLT1puudcxLJ639OQAAAMBQWfG0AZk4flz+79v2yilv2iMbTRiXieOfmyv+7RG75x8uuWPV/fhxJe949Y4jXSYAAAAwRljxtAHabKMJzwudkuTYA6bkyL23z8TxJZM2fUE+f/TeefGmLxjR2koZ0ekAAACAFlnxNIa8YMK4fOHtr8wn3/KKvGD8uIwbN/Ip0KUffO2IzwkAAAC0Q/A0Bm08cXxL847LtO22aGVuAAAAYOTZaseIec1vbj2kcbUOcyEAAADAiBA8Mao4AwoAAAA2HIInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInRkwppe0SAAAAgBEkeGLEjBc8AQAAwJgieGLEjPOnDQAAAMYUUQAjxlY7AAAAGFsET4yYcYInAAAAGFMET4yY8XInAAAAGFMET4wYK54AAABgbBE8MWKc8QQAAABji+CJETNO7gQAAABjiuCJETNe8gQAAABjiuCJETPUrXY1dZgrAQAAAEbChLYLYOzoZsGTNVEbpkeeWJILZ/wqTy1dnj945Uuyy7abt10SAAAAI0DwxIjxrXZj06JnluVtZ/44cxY8nSQ59yf35TsnHJidJ2/WcmUAAAA0zVY7Rsz0KVu1XQItuOy2h1aFTkny5JJl+Zcb5rRXEAAAACNG8MSIOfzl27VdAi34yjWzn9f2zR/f10IlAAAAjDRb7RgxG00Y38q8dzz4RL5949y88AXj8/ZX75jtX7RJK3UAAADAWCN4YkRM3nyjVua9+5FFeesZP86iZ5YlSf7fL36d75/42my5ycRW6gF6z/IVfd+sOb6bb0gAANiALF66PP/+i1/noYWL87sv3y57bL9l2yXRgwRPbNC+ecOcVaFTksx9bHEuveXBvP3VO7ZYFdArzrj6npxx9T1JkvcevHPee/DOLVcEwEi5b8FTefiJZ7LXb2w5Iiv3lzy7PBf8/Ff51aNP53++bNvsO3VS43PC2tRa82f/8vNcf/eCJMmZ18zOt969b1710he3XBm9xhlPbNDO+cnzzxL6+nX3tlAJ0K1nli1ftcqoTT+799F88tKZefzpZ/P408/mk5fOzM/ufXStY26ZuzDHfP2nOfwL1+Rr185Ore1/DgAG79M/mJmDP3NV3nbmj3P4F67Nw08saXzO/3Xujfnod2/L1667N+/46k9y+R0PNz4nrM3tDz6xKnRKkmeWrej3/FZYF8ET0IorZz7SdgmMMitW1Jz6vduz1ymX5ZWnXpazr283JP7MD2c+r+2zP5z1nPvVA7KnnlmWP/zaT3LtXfMz86En8/Hv35H/uOmBxuvs1j3zFuVffjwn1989XyAG9KQVK2ruW/DUkP/PiSXPLu+q34MLF+f0q+5ZdX/v/KfyjYb/nTRn/lO5cta8VfcravKly+9qdE5Yl3//r18/r+2HtwlEGTzBE2NOcUzLqHDc2T/Pd385ev5S3muWr6hZumxF22UMq0tufTDfuP7eLHl2RZ5Ysiwnf+/23Pnwk63V8/M5jz2v7Wdz+lY83XjfY/mdz12d3T/yg5xw3n9l8dLl+e4vH8gTS5Y9p/+pF9/+nPu2VnLdcPf8/N4Xr81H/uO2/OHXfpo3nXZ9Fi/t7i9g6/KrR5/O+T+7Pz+dvWBUBFq11sx78plRUQtsCFasqLn11wvz09kLWv33zsyHnsj+n7w8B3/mquzzD/+ZX9z//P+OHsjdjyzKYZ+/OtP+/gd502nX58GFi9fa/9x+VsyfeXWzqzyumvX8/0Pul3MXNjrnWDYaVlbDWCJ4Yr0df9DUdfYZTf/7f6RrWbEB/Ytt8dLlw/p5PnfZrHV34nnOvv7e/NbHfpS9/j979x3fVNXGAfx3u/fee1Pa0hYKLWVvBBSQIYiiqCwFHKC+qIg4ECcqiiioTFkCgkwRKLulQBd00b3pnulIk9z3jzShSW6SmzRd9Hz/4UNy781Nmtx7znOe85yPz2PTmdTHpoO94Z9kmce2RmXK3V4goFHF4QIQTs/ris+BooSN1SV77iCzrAFcngCn75Xg+wsPcDtXdhqe6Pzqm1uxZM8d9F9/DlN+uIbUkrpOP9f2dlzLlugwJhXWYsjGC8gqb+jQce/mVWHSd1ex9tg9zNseg01nZbPEulJBVSMmfXcVQzZewNBNF5FYUINWvgB3cquQVd7w2PxWepKGFh5+v56DjadTEKdCIEAZgYDGL1ey8Mwv0XjvWBIqG1o0dmyCPb6AxqoD8Xjyx+uYtz0Gs7fdRG1Ta7ecy/rjySitE34PqjhcvHfsHut93zqUgAelwutdYkENPvj7vsLt66UGEYjHR2pJHab8cA3915/D4t13UN/cPd/nnkgUZI7NqXrsBjeJ7keKixMdtnCoOw7cykd9S+fcpPfF5MPTxgRzB7vAzKB3rEZH0zQelDZg9eEEZJY1YKSvLb6bFwLTXnL+0ppb+VhzOBHnkh/CwlAXn80MwpQBjgCA5OJaHL1bBGN9bcwPd4OzhSHr4+ZWNnbWKXepJi4fJxKKUFLbjMmBDghwMuu010oprsOGk4+yaH69mo2BbhZ4Isix016zM9E0DaotDbGigSvzfEoxc4AmJrsSK/fHSexjb6aPT2YEYXKgg/gxflsjitPCQ5iHJavisFUcLm5lV8p9/npmhTigJPLr1WzMGuQsd59NZ9PwX4owNT21pA7L9t7FlXfGiN+7uuqbW3EprQxcngAT+tvD0liPcbv20zdEGlp42BqVic3PhOJ2bhVic6oQ7GKOkb62rF9/x9UcNLWbuvL79RysGufTbde6j/5JRkaZsHNZWteCl3bdhp2pPtIeCjPnFg51xyczAkFRFI7FFeJiahm8bI2xbLQ3TPRJk0hVNE3jpZ2x4uzAXTdzsfvlcAzztunwsX+5moWvzgkHJ2Jzq5BaUo/jK4Z3+LiEau7mVeP0vRLx/+8V1eJ4fBFeHObR5ecSKxXcT3tYD04LD8ZKfru1ja24VySZOXSJTPfvk2iaxrK9d5FfJWx/Xkgtxedn0rBp1oBuPjPV7Y3Oxd6YPJga6OKtCX4Y4dux6y5fQOP1g/E4nST8vQe7mGPvKxEaOFOCEFKplUVRlAuATwA8AcAaQAmA4wA+pmla6TAXRVHGAGYCmAZgEABXAAIA6QAOAPiRpmmZngdFUYqGKG/RND1UlfdBaJarlREOLB2KvdF5qG1qxbnkhxp/jU9PpeBkYjGOvToMWh1c0rwzp9qV1TdjzeFExOVVg9NuGsuF1FKsOZyIAc7mqORw8VSIE8LcLTvvRDTs9+s54oZnJYeLVQfiEedrg4e1zXjml2jxez0WV4Szb47sNQFCTaBpYfbL9cwKAMJV0PYvGSrx9+ULaKSW1MHZwhCWxnoor28BX0DDwdxA5ddjygD65GRKpwaeuDwBbudWoZUvwFAvaxjodnxln4YWHt49koirDyrga2+Cb+aGsN6Xpmm8fiBeJlBVWteClfvjcGfdRJgb6oLHF2DVgXicvS+8JgU6mWH/4qEwN5L//cworcf87TGo5MgGwQCAAlBULWeKhpw71U+XMrD/Vr7EY/lVjUgtqe9QkJLTwsP87TFIbgvOedoY48jySFib6LM+xrG4IkR4WuF/Rx9lDrz7RD+8NsaH1f7S13u+gMaltDLMCJUfhOtM0p3JKg5XIki4NyYPLw5zx62cKomMh/j8GuxbTBrYqkoqrJWYktrKp7HtcpZGAk+ioJNIQkENsssb4GVr0uFja1oVh4s7uVXwsjWBj53w/Jq4fFzPrACPL8BIP1tWgc1jcYXYG5MHE30dvD7eF0M8JFeNomkat3KqkFPBwXBvG7hZG3XK+2nvW4bM5I/+Se6WwBMTPossxiaWdZ2Ix9+2K1nioJPIgdj8Xhd4ikorw4cnHmWJv7L7Nq6+Oxb2Zqq3K0Xu5lWLg06A8Pp+IqGIlCghNIZ14ImiKG8ANwHYATgBIA1AOIA3ADxBUdRwmqblDxELjQSwD0AVgCgIg1aWAKYD+AbALIqixtM0zbRsRB6AXQyPF7J9D0TnCXI2x5dzggEAHmtPyzyviYtWQkEN4vKrMViqIZZf2QgDXS3YdeBiq46imiY8eFiPUFcLcZbBO38l4VpGBeP251NKcb4t42H/rXwcWDq0S4NPZfXNOJlYApqm8VSIk0o3p6+lCirzBDSO3ClERlmDRICtqKYJZ++VYN4QN7XOsaGFh5xyDvo5mEJPp3fMBE57WC8OOgHC1T5+u5aNMPcwAMICpQt23EJOBUdm36dCnLD5mRDoarN/r9KjtgBQXNt5K+00t/KxaGcsYrKFI83BLub4c3FEhzNaNp5OxZl7wqBFfH4Nlu29K3fbRi4P55NLUd3IxaRAB5TXt6CsnnnaTSufxl93CrB4pBfi8mvEQScASC6uw9/xhVg03FPua/1+PUdu0ElEoOJ0rW/OP2B8vJKjeOpQNYeL9f8kI6mwBhGeVtgwPRBGeo9u21cflIuDToCw+O3Z+w/x/FB3lc5vy0XJYObPUVlYPspb7SC/qP5Y+sN6eNkaK81GECmpbQKnhQdvW5MOZ4Ip8uuVbJn6ctczK1BQ1QhXq87vyD9O1p+Qna4k7x6oCZlligNPLTw+Cqqa4GVjzPj9vVdYi49PJqOopglPBjti7ZT+0O7gYFZSYQ2e++2WeGrWumn9sSDCDc/9dgvx+TUAAH8HUxxaGqkw6H0jswKrDyeK/38ntxpX3hkj0bb54lyauM6Qga4W9rwcgXDPzl3SvCun1WWVN2BfTB54fBrPhrupFZjnC2iZvyktb1Sgh+kdZ9k71TRy8dRP11FQpbi2V2/x0q7bEv9v4QnwZ0weVk/qp/Yxv/tPtq2y/kQyloyU32Yi2MsorceppBJYGeth5kBnmBv2nUF6EVUynn6GMOj0Ok3TP4oepChqM4C3AGwEsFzJMR4CeB7AX+0zmyiKehvAZQDDAKwA8C3Dvrk0TW9Q4XyJx9DxhCJx4Km5lY/X/owTj3AvGuaBj54KULvDcj75IW5mVSLQyQyzB7ko7HQdjM3H2na1BY6+GokwdytceSA7nYUJly/AtstZ+O3FwczP8wSo4nBhaqADY30d/JdSit+vZ0Nbi8LSUd4Y7ad8KkxZXTPyqxoxwMUcnBY+Zm+7Kb7h7ryRi+MrhsPWlH1mhDTposki/zt6D4Z6OojwtFIpuPVv8kOs2h8PLl8AGxN97F8SAT97U7XPr6v8HS+72kf7YMfPUVmMQScAOJlYjClBDpg6wBEltU3IqeAg1NVCIrigCZwWHq5lVEBXm8JwHxtxxtKRu4XYG50LY30drBrni0hva5l9rzwoFwedAOEI2IAN5/Ht3BDMDnNR+5wOxEpmAGWWMdca4gloLPrjtniKxY+XMrFqnOJsnLy2KZzSK9ABwIaTKZgR6iwzJY2maeRXNeLg7QKl595VdYJePxgv7sTnVTaCJ6Cx+ZlQ8fOv/hkns8+64/dVDjwV1Ug2xBtaeKhpaoWVnGl7yqSW1GHj6VRUcrjQ09HCL88Pwjh/e7nb0zSNj/5Jxp5oYTHf4T7W+O2FITDU63hmHZO65la0MNSuSC6uJYEnFdA0rVbh4/rmVghoqNXoVnR/v5xehtf+jEMjlw8XS0PseyUCHjbG4ue5PAFe+OMWqhuFgZQd13JgZ2qAJSzqVCry46VMiXpA35xPh62pvjjoBAgHKM4ll+CZwa5y34P0AE9TKx/7Y/Px5gQ/AG21tK49WlWtuVWAHdeylQaeahq5+C+lFNpaFCYE2PfYjOSy+mbM2XZT/PfZG5OHH58diKdCnFjtz+ML8OGJZJxIKIKtqT42TA/E2H52AISrw/VmiQU1KKtvQYSXlcp/v7/jC3Esrgj2ZgZ4fZxvl2TJaUJ+ZSNOJhXDQFcbM0OdYGWsh0oOF9bGenJ/Q82tfERnVaK5lY8RvjYSA2Q/Xcrs9UGnRi4PZ+49xJl2U1/bu5FVidUdOH51o+JBN2lXH5RjFIv+CCFcGGHOtmg0tJWlOXK3EEdfHdZrBtk1hVXvpi3baRKAXABbpZ7+CMBSAAspilpD0zRzDwsATdMJABIYHq+nKOpbAH8CGAPmwBNBQKvdzeafxGKJaRW7buZiRqgTBrqpnkW060aORN2c5OI6bJgeyLitQEBLBJ0AYPa2aORsmqrSa15IZV6K9EFpPV77Mw6ZZQ2wMdHH4pGe+PrfdPHqG7dzqnH2zZHwVjDq2/79OJobYNoAR4kbblFNE04nFSvM/OiI1w/Ew1hPG3tYzA0/crcQb/+VKPFYRUMLJn13FWP62cLH1gSrxvtKdFIEAhpbozJxKb0MPrYm+N8Uf9wrrEViYQ3CPawwzEe9aR65FRwcuJ0PgYDGvCGu8LHreOBrL8PKOO2tPZqE8voWfNRWWNvGRA8Hlw6Fj50p+AIaR+4WIO1hPUb52Yob0aqobWrF/O0x4mLWYe6W2PdKBOLyqyU+97j8alx5RzZN+6MTsgW/AWDNX4lY07b/1gWDMHWAg0xjkKZp/HEjF2fulcDF0hDvTO4HF0vVGr05FRyJwF0Vh4uPTzIHPaXVySkY+sahBOx5OVziPNefSFb6twKEHd+u6MQ0cnkymSPH4orw5ni/Luk4dCQHZEe7zjGXJ8AHf9/HzbV2cjsLiYW14qATANzIrMTf8UVYEKFe5qS6Sjoxc5Ct+0W1uJ0rrLUV5t65mSwdlSEnWCwPTdP4/Ewq/riRC5qmMW+IGzbODFIps07eljRN490jSWhsy8AtrG7C52dSsf2FR4M7F1NLxUENkY1nUjsceBLVbhNpbhXgjYMyTV387+g9fHkuHc9FuGH1jfULXQAAIABJREFURD+Z30NCQY3MPhdTy8SBpyvp5eBJXXykX1taNYeL2dtuIrvtGurvYIq/lkf2yHqTf90plPn7rDoQj0mB9qxq8+26mSse0MirbMSyvXdxd90EmBro9thFXnh8AWJzq1DF4WKEgnbLjK03AADOFoY4tGwo6/vo2XsleOvQo/t8dFYlot4e0+M7uwVVjXj65xvi7OPPTqfA2lgfFQ0tcLE0xO8vDkE/B8n2mXR2tq+dCQ4vixQPMv12PQe9GY8vwKKdtxGbI7uISWeTd+9+61AC7n44sYvPpufLr2zE0bhCUBQwJ8wFLpZG2H0zTxx0AoSzF2KyK/tc4I7tsPrYtn/P0zQtMUzYFjS6AWFgaiiAi2qei+huI69CtQVFUS8DcABQC+AuTdMxar4W0Uu1v/S9eyRJ5vnvLmRg56IhyCirh5MKRa6/OCe5EtOum7l4b6o/Y2MnoVC2cdgRqSV1WH/iPuPS7RUNLfhCapUoLl84lWvTrGDG43FaeBLZSCW1zYw33A0nUxQGnkpqm7DrRq7aqxRxuHxsu5yldDvpoFN7l9PLcTm9HPeLa3FwaaT48R8vZeK7C8KU4Pj8Gvx1V3LG7aczg7BQxayPsrpmzPklGhVtKyftuJYjzmTrTHXNPHx+JlX8/4oGLn68lIkf5g/EuuP3cCBWmIGz80Yuvpw9QOVpq+ful0isoHY3rxpXM8rxs9TfprlVmIXXPuD6b/JDPKxT3hlfsT8Oq8b5YI1Uive+W/n4tO27eDevGkmFtbi4enSH67R11NUH5RIFaVNL6lkFnURUnWqnDk4Lc02SmT/fwPHXhnd68ElLg1PdSmqF2Zfu1sYSj++8kYOjcYW4XyRbQP79v+9BQNMIdjFHsIuFxs4FkL+y6ccnU1DN4XZoqgIbXJ6AseP3d3whVh9OFJ/fYHdLvDzCExMD7LH7Zi6uPCiHj50J3pro1yOyVjgqLigSk10lEZQ8EJuP2JxKXFg9mnWmsrzN0h7Wy0y/PS8VlEkvrWf1GmV1zWjk8uFubaTxKZ9VHOH13dfeFNNZZvIAwk6nvCwHRc4lPxQHnQDh5xSVXq7Sa3fVQpA7rmUzPn4+uZRV1tNnp1Ml/s/lCfB3fBFeiPTQxOlpHE3TeONQgkRNHWWKapqwLyYfa6f4s9pe+jMpqmlCVHqZxAIcbLXw+DgYW4Ds8gaM62/PKvNeXQdv50tMeadpiNtmhdVNePdoEk5ILTQQnV0pkZ2dUdaAU0nFWNhD//7ypBTXIS6/GqGuFghyNhc/nlBQ0y1BJ0UqOVyU17d0aPZEezy+ANczK1BW14LR/Ww7VK9KVa18ATadScPFtFJ425rg4+mBamVAP6xtxqxtN8Xf1+8vZMDeTF+8Gmd7u2/mksCTHKJWGHOhCiADwsCTH9QPPL3c9u85Oc+HAPi9/QMURSUCWEjTNPv1VIleTVkjMD6vGhM2X0FOBUelug3NrbLTLkprWxg7d1lyRnnVaZzxBTQW7YxlvCAp8k9CMTbNCganhYeC6kb42pmK3+9LO293OCOjicvHvF9jZAowqupCain8HTqeNRSTXSVRf0UUdJLnhwsZeC7cDb9dz8bnZ9LgYW2EXS+FS0y7kHYkrlB8oxCZvS0atz+YAFtTfaQU12Hzf+koq2/BnDAXjTZmpaf9nEgoxmczg8RBJ5Fvzz+QW9hbVFst1NUCR5ZHQqetblT7otEiHx6/z1gjadfNXFzNKMf2hWEorG7C8n3y6y5J+/FSJib0t0egk5n4tT85KZktlVPBQWxuFYZ6yU7p06S9MXnwdzQVr2TGpH3gialguzwU5E/bOMYw7VJd8q5fVRwu3j6SiHXT+mvstRi1vfyVB+W49qAcfg6mmD3IRe16ONLLMh+PL1KaubbuuLB+0KczArus87DlUiarwJNotcSY7ErUN/MwwMUcQz2tcflBGfR1tDHazxb6Olq4X1yLSg4XEZ5WqGlsxfO/3RIHAkb42OC1Md4orGnCxdRS/JssGSi5k1eNO3mSgf9rGRV4UFqPPxf3vjVVnt0hO1aYVc7ByaQSmUCI3KkkmZXYdjkLDS08vBDpIc6Ka+R2vHg0TdP4+GQKdt3MBQCM8rPF9oVhGllMQdqGf5JZBX9ETZ53jyZJrCzH1nvHZK//a48mKX3t8voWXEorhZmBLpp5nVOYO+1hHb44m4aHtc2YOdBZbhvqAcuAIZPscuFvTdFgwZUH5dgbnQs9HS0sGeklzppn26ZraOHhg7/viUs1fDErmNXCIeml9SoFnUR+uZKFopomlNc3Y/YgFzwV4gQBTTNO0ZeeRg0Is54mBzrgQWk9TiQUgaaBxSO9lE6tXn0oUfwd3B2dhx/mh3baIhJboxQPWiYW1KCVL5Coj/kpQ/mHD08k4/mh7p1aM1CTpAcfNs0agGfDhde4364pz9hq0sB1UFV8JR2ORi4PHx5PRky28Pfx2dNBsDOV/X3QNI03DyXgVNtvwtJIF4eXRcK3i0pu/HAhA3/cEH7GeZWNyKvkqDQoInLkboFMX0LVPt7jjG3gSRRylTeZX/S4WsOSFEWthHClvAQAfzBsshnAUQgDX80A/AH8D8AcAJcoigqlaVpzLX6i+yj5gYtG4Ru5zCOt9S081LeNwsq7GFIsJ5HIm6YjrwHTvq4PW5+eSlHrgkRRFE4nleCtQwng8gVwsTTE/sVDQVGyyw2r42JaaYeDTpr2oLQeDuYGCjOkRCoaWvDr1Wx82ZbJllvZiDHfXEbW51Pldpy3XMxgfPyfxGIsCHfDc7/FiKcBJBXWwtxQFzNCnXFKqkixpjwolQ1wltW3wE3JCExCQQ1WHYjHz88NknvDZKpvI5JdzsGaw4kQ0KoHU2dsvQEbEz3sfjkc3rYmaOXLHuBeYW2nB54ASKxYxoSGcITrXpFwiiZbPAGNr6QyJDuDovhObE4Vpv90Q+kxaJpGVHoZUoplM4qUiUorw9f/pkt0XOLzq+VmWqpKXo04JlsuZSrsPNQ2tsJQT1tj00cEAlphVl5zKx+v7L6NG5ny11MZ7G4JJwtDmSLm7V3PrJBYmICtG5mVKKltgqM5+6ze7sbUARZhCsL8eoW54ynqGADCrDhnS0OFmRdRaWW4mVWBACczuQHjhIIahLpaIKGgRhx0AoSZkcfjizA/XPNTPkUrLSr7rtG0sPbRsbiua+IWVjdizrZoVtmu6mrh8fH8b7fEK5NKZ3ZriuiSIe9eFrD+nETQ8kp6Of5bPZp1xrxAQGPDP8k4kSD8nV9OL8eC32Jwac0Ypftuv8qc4cXGybbrSkx2Fd45kgRdbQrPRbhj/ZMBSjOKKQpIf1iPyd9fFT/28+Us3Fg7Ds5t75umaZxPKcXtHOFqtjYm+jKBz2/PP+i21UuZtDAMIAPAgdgCtaZtN3H5uJlVAV1tLUR4WbGa7ikPTdP47kIGjsUVwtZUHx9M7S+zUBIgrEPV/rv606VMzB8ivy6ctJQS2Xt9cU0TLI305NZMrGtuxZmkEjS08ORepzsStvvoRDKOxglnJRTVNOF8Silyv5gms11OBUccdAKA6sZW/HkrX27ZE037SWoAMqucg5SSOgQ6mcvZg5m8xWSY9MwJwJ1LsxVs1UBR1CwA30NYeHw2TdMyvX2aptdIPXQHwFyKoo4AmA3gbQgLnDMdfymENajg5ta19SIIzaMooLKhBfO2qz/LsryBXaDn8J0COFsYyhQhltd4XbFfttCvMu0buargCQRYeywJXL7wRltY3YRv/0tXqVirovvY3xps5CrKOlGFFkXhREKxuIGnzJcMwYFDt+U3QOQ1TD89lQJzQ12Z2hOfnkrFjFDnTltRbvVh2RohAFgFBM/ef4iRX0Xhg6nqZcWoUzBYpKKBi2lbrsNAlzkIsPFMKp4Z7Kr28TWlsoGLF36PZT39pj1FgTtVKArssQ2QK7L5vwf48RL7bK723jwk+/07EFuAD6YFoKaRi9icKviqUANt4ndXEeJijo1PD0CQs7m4481GeX0LKhq4Mun8za18vHEwHudTSkHTwCsj2NWsk56CJU1ZG/98SqnCoBMgzFZCnnrTlNnIKeeoFHjiC2jsjc5FUmEtwj2tMNjDCutP3EduBQcTAuzx4ZMBKq2uyeb12gf597ar4SWtSmJKDY3fr+ewvga9+EcsTr8+AvKa8NIrPzHZfjULPz8Xhh8YBh/WHrsnDjzx+AJoa1HiTmB9c2uHPrNpW64ho6wBo3xtsXleiNztpDPhOtuxuKJODToBwtpUoqBTZxJdR+UNGEpnynG4fOyLycO8Ia4Kp183cfl492gS/kt5KJMxn13OYbVCpnQWaEe08mnsupkLCyNdcU0webQoijHoNfWHa0j8aBIAYVBsk5JgoKK2SEFVIy6mlsLKRB+TAuxhoKuNzLJ6/O/oPWSWNWBsP1tsmhXMGAy5znJVTNFAtEBAo7Re/vf1k1PJrAJPTVw+Pvj7Hv5LLYWVsR6qOFzxogERnlbY/XK42tmPh24XiAc3C6ub8OIfsbj1wQTczavGjcwK9Hc0xYwQZ2SVS5ZJLqppQnOrQK2FNqKzKiWyTAMczXBi5XCJa1ZzKx/jv72CcjmrBLOhbMVI6VIYALAvJk9mERSm39uum7ldFnhiUlDVqHLgSRW9Iw9Ps9gGnkQtAHmfvuhxlYrfUBQ1E8BBAGUAxtI0rWr4/xcIA0+j5G1A0/R2ANsBYPDgwX0xuNirKPsRclp4OBpXKHcFLDaqOFylo4wAsCc6D3ui8xDpZY1fFoaJgzrSxT27Q3OrQKaxcyKhGMMYViWTp30NF5qmcTSuCFFpZfC2M0FTa9en6ypFAe8eUZ7tpMj7f9+TH3hSsF9sjmwns6KhReHqZk//fEOlzrU00cps6iqsbsLKA/EdOkZHME1fFZm3PboLz0TOOfwaLc6O7C5MWZll9c1482ACbmYpDmwoUlLbBGtjfZWmELK1JzoXWy5mKPz7ypNYWItFO2MR/d54lfdlylTcF5Mn0Sn/XUPFY2lacfDpfYbpSz3dhn8eFc+XnhK6JzoP5oa6MjXalFE0Cn8qqVgiG+JEArvBjBMJxTJ1aZSZtuU6IpSs7KbImXvCbOWSGubOq0BAY+OZVByMzYeJgQ7emeyPW9mVOBpX2KHAU3JbJuKF1FJsOqPae9aEu3nVOHy7ADmVHIz2s8XcwS6wMzXAZoYl1Zl8fDIZ/3vCH/XNPMTmVMHDxoh1Jy0hX7O1MuWhKCCvkoNzyewz0n++nCVTA1Ha9xcfiLOOmByPL8Kq8b4Kj6GpQbn2vr+QgVXjfBVOiZZ3naxtejS4pizoJHI3rwqhrpYSr5dRWo+5v0ajpm2wbqSvDXa/FI5Xdt8Rt2uOJxTDwkgPG6YHgqZpZFdwYG9mgH0xeayz3ygIF2NYvPuOwkBpc6sAp5KUD1huOpsqvja2X6USAG7lVOF6RgUmBMhfnVUR0bRxEQ6XjzFfX5aYkpVYwBxsV3WWoEBA42pGORbtlAy6p5TU4ckt1/HvW8Iuc0FVI0Z+FaXawTWEafXdnroAAKFZbANPojVe5YXRRVdX1vllFEXNBbAfwkyncTRNM89zUUy0dr38wi3EY+Vc8kPxzawjYrIrMczHBlFpZUqLZ0dnV+LHixlY92QALqaW4sPjiqfwdCdVih63b5fsjcnDejmrl/UU9wpre9ySyEzT4UTiu6hhrYiyuffdpTMa3Krq7qATIMzG+G5eCIz0dBDmbgkbE328d/Reh4JOABC56RKG+1h3yu9lW1SWWkEnkYoGLpbvZV87TISpH6VqgEJTGnrAd0eVP20rX6C0eP6PlzIlAk+F1Y3YE52HuqZWzAlzYZwWosgbBxMwPcSJ9RSRFh4fNY2t+PikevehW51YdPd4QpG4s87h8iWme2sq+1G6np+qmlv5rLMxGrl8HLqdL1H/LzanCl//m45r745VsKeknTdyEZ1ViaKaJomO+uIRnpg72FVm1bHucDSuEH/cyNF4gfRfrygeJ9984YFM4KmsrhkfnriPtIf1GO5j06EBVEUupJZicqAD8irlLjKuMbO3RWNigD22LwwT/9b3x+ZLtNOvZVTgr7sFMoNpu27mYuU4Hyz8PVZiARS2KAp450gSq+y8lfuVD8LtUZCVCQAf/ZPMGHh6UFqPHVezweHy8Gy4G0b6yk79ZRqwlq4DJG8GxJl7JZg1yEXhubWXV9Uo9/uZXlqPnAoOtl/NFq8A2d1omkZxbXOXtu+Ti2txLaMC3rYmGO9vpzARQSCgkVhYg9K6FkR6W6s0s0SZXlJ6TKPYBp5EIdFJFEVptV/ZjqIoUwDDATQCYDX/iaKo5wDsBlAE9TKdRETVNdWfKE30KpoIOgHCwFNSUS3rkZXfrudgzaR+eGX3HY28fmdpv6KHMu3r73RXB04VhdWdXHNKwU1P3gpjqhTfJggmoqWujfS08dOCgbiYVqaR4yqbCqYuTQTs1HmP/yQWd+nqVJll9dgTnYdTSSUwNdDB5EAHjPCx0WijsyPad6QFAhrJxXWo5LQg3NNKpsjwbZZ1/0TFehtaeJj3a4y43sfB2wVwsTTEL8+HSayypMyVB+UY08+O1bb91slbV6bryJsywlSguys1NCv+zS3YEYPo7Eq4Whphy7MDEeqqvNwq06ITAFTOgGAaRPjteg4O3SnAiRXD4WVrotLx1CUv+1hTbcb20h4qD5Iwnc6rf8bhbtv027zKzuv0L2sL7M8apHr9JS5PgBsq1p37L6UUWeUc+NgJ/9Y7b+TKbCOvjflzVJZaQSdAOAVV3X3VUVTThK//TYO7lTFmDHSCvo42qjlczN8eI85uP59cir+WR4oL1GvCh8eFq16zzdoT0DSis+Xf/+dsuymxYiAbvyqoRxa56RIyN04RLyqjipwKDhbtjO1whr8yXJ4AApqGga42otLLsGT3HXEw8IVId3wyI4hxv6xyDj44fl8iSDehvz2+nD0A1iaaWcmvr2H1LaFpOgvAeQAeAFZIPf0xhBlHe2maFofXKYrypyhKZr1PiqJeBLAHQD6AUcqCThRFBVMUJdPSoygqGMDGtv/uY/M+iJ6vq6K/XD6NHy6olmQX/PG/nXQ23SezTNho1GStgc6iyeXdmYjqZTGRt5pQTkXnjygSfUMjl4+Xd/XswHZ3Wn8iGR5rT2P14QQkFtR0aBqrMvtu5WHC5qvYE52HKg4XeZWN2H41Gy/8EYsZW5UXde8KovoqNE1j7bEkPPXTdSzaeRtTfriG0nYZAPmVjViw4xarY47+KgopxXXYfTNXpshsYXUT5v0ajYJ2dV0KlNSbk57q0VtpKqtJHakldYz1Ctu7mVUJmhZ+J17bd1cchOnOqSv1zTzsi9FMcEXZnX/utmjEdWGGsbIV10T+ji8UT18rq2sWB526ijoF6V/78y6rumjSPvpH8UwA6alrIu0XC1BVdwz8bY3KwrtHk9Bv3TmsOZyIg7cLJO5FPAEt/n7w+AJEZ1XiXxWmeTLhcPkazU5SNejEBlMdJzY2/JPc6UGnrVGZCP3kPEI+Po9NZ1Kx/Uq2RAbanug81DQyfyZf/5su89lfSC1F2GcXWE3fVK7vpTypUlz8NQA3AWyhKGo8gFQAEQDGQjjF7gOp7UXhbfGnSlHUWAhXrdOCMIvqJYY07Bqapr9v9//VAJ6iKOoagAIALRCuavcEAG0AOwAcUOF9EN1A02nOHdXKF6hcx4hpha7ebsLmq5jQX705612tff0BTSuplb/i0uOoMz9LguhMx+KKcO7+Q/z83KBOe42ePu0YEE6PXhDhhsyyBhy+86jRn1fZiD9v5WP1RGFlhAO32XdYimubMXXLNbnPc7h8cUZMiIs5alhcR748l4ZRDFNPCHZUrSlZXNuM5OI62JnqY8Fv7AKOneWPGzlY/1QAmrh8tYojizS18nEqqVhu8CK9tB6zt91U+/iqUlTbqb23DiXCx84Efy2LRKGCVR17kgup6mXciuoTKap7+bgRrdQm7UJqKeZvj1ZpBkJv996xe+LM0P1LIjDM24bVflcelCvd5lJaKcI9rWGizy5kIRDQ4HB5MDXQRVx+Nb7+N138nLzMrdWHVa8fu3J/PIz1dTC2XVavotVbCSHWgSeaprMoihoM4BMIgz5TAZQA+AHAxzRNswnlu+NRltXLcrbJg3CVO5HjAMwABAMYB8AAQCWAswB20DT9D9v3QPR8mljJiY0+dG9U6kJq166Yo66z9zs2aqTIS4/JyDxB9AWNXL7aK4I+LgQCGnH51Zj1s2yHe8vFDDw90BmeNsbYpqRIsrrYrjq37XJWp52DJi3dcwe5FZ08nbuLFFY3dngRFk2ZuPkKMsoaMMDZHL8sDIOzBfuVGEV2XNPMogHdIbOsAZv/e4C/7nashldPJwo4nUxizg7va7oz6NTdwb8FO24h+/OpShdwqmS5wvjLu+7A1coQh5dFwtHcEK18Ae7kVqOplYehXtYSU8vPJz/E2mP3UN3Ixdh+dqwHWS+pWeLgq3PpEoEntuVb+jJVMp5A03QBgJdYbivzjaNpeheAXSq+5nEIg09EL9bTCqipUoSbeDyV1DYhNqcKApruEcWuCYJg73K68pHSx1l6aT1j0Elk0c5YfDgtoAvPqHc7n9I7BmDYWL4vrrtPQSyjLfh1r6gW7x+7h90vh3fzGXU9ZYX9HwccLh8Lf7+Faxmq1YciNG/C5qvdfQr481YeFkZ6KAwuhX12gfXxCqqaELnpEuaEueBEQpF4Bko/e1McXDoUlsZ6aOLysfJAvLh0iLrBJFVI1xhjmw0p0tP6xl1BpcATQXS2rvoRnuvE7Bmi57udW4UXfo9VebolQRBEb5BX2YjFe0jNMKLnYDOthui9SNCJEPnwRDJ+uZKNSg67rCa2jkjVkkovrcfAT//DrffH4+qD8m6pV7t49x21Z470xbIXJPBE9Elsll8lHl8/R2WSoBNBEARBdIMS0gYjiMdaV9Y7ivj8Ype9lrSOlCvhKVjU6HFFAk8EQfQpHmtPd/cpEARBEESfM+WHazDV10Fsbt8pvEwQBMGkLxZ9IYEnokfpg9NdCYIgCIIgHnvSNVEIgiD6KhUXLX0saCnfhCAIgiAIgiAIgiAIguio7l6BsDuQwBPRo/TFCv8EQRAEQRAEQRBE39AXV1gngSeCIAiCIAiCIAiCIIguIOh7tcVJ4IkgCIIgCIIgCIIgCKIrkIwnguhmFCkvThAEQRAEQRAEQTym+H2wujgJPBEEQRAEQRAEQRAEQXQBPsl4IojuxeuD0V+CIAiCIAiCIAiib+iDcScSeCI0L9LLWuax8f52rPaNSi/T9OkQBEEQBEEQBEEQRI9AptoRhAasnuQn8X8dLQpLR3mx2vdWdmVnnBJBEARBEARBEARBdLu+GHjS6e4TIB4/Qzys8O3cEPx+PQd6OlpYMdYHXrYm3X1aBEEQBEEQBEEQBNGt+uKqdiTwRHSK2WEumB3m0t2nQRAEQRAEQRAEQRA9Rl8MPJGpdkSP0vd+ggRBEARBEARBEERf0Ren2pHAE9Gj1DfzuvsUCIIgCIIgCIIgCKJT9MWV3EngiSAIgiAIgiAIgiAIogsISOCJIAiCIAiCIAiCIAiC6Ax9MO5EAk8EQRAEQRAEQRAEQRBdgdR4IgiCIAiCIAiCIAiCIDoFn6xqRxAEQRAEQRAEQRAEQXQGUuOJIAiCIAiCIAiCIAiC6BQCkvFEEARBEARBEARBEARBdIY+mPBEAk8EQRAEQRAEQRAEQRBE5yCBJ4IgCIIgCIIgCIIgiC7wRKBDd59ClyOBJ4IgCIIgCIIgCIIgiC5gYqDT3afQ5UjgiSAIgiAIgiAIgiAIoguQ4uIEQRAEQRAEQRAEQRBEp+iDcScSeCJ6lnmDXbv7FAiCIAiCIAiCIAiiU5CMJ4LoZgsi3Lr7FAiCIAiCIAiCIAiiUwj6XtyJBJ6InkWLorr7FAiCIAiCIAiCIAiiU5CMJ4LoZjT63o+QIAiCIAiCIAiC6BtoEngiCIIgCIIgCIIgCIIgOkN9M6+7T6HLkcAT0aP0weAvQRDEY2egmwWuvTsWW54d2N2nQhAEQRAE0aNcy6jo7lPociTwRPQoj1PcycJIt7tPgSAIKRP623X3KfQoswY6d8pxwz2s4GplhOkhTp1yfIIgCIIgCKL3IIEngugkF1eP7u5T0CgPayPYmup32evteyWiy16rN/v7tWFwsTTs7tPoEmHulho4hpUGzqRr/DA/FFOCHPBksGOnHH9asCM2zwvFH4sGa/zYOtpkoQiCIAiCIAhCiASeiB7lcSm09sxgF1ib6CPQyUyjx31jvK9K26uySOCJFcMxe5CLxGO2pvrwszfB6+N88O9bo/DmhEevr61F4deFYSqdD1sbnw7CCF8bXHlnDN6f6g9PG2NYPsYZZO7WRsj9Yppa+w50s8Q3c0M0fEYdQ1FAf0fNfve3LwzTSDBy/hBXDZyNch0NFs0a6IwZoc7Y9nwYflowCLMGqZaZZGWspzS7K6DtbzTO3x43146Dv4Op2ucrTVtL9eZFzqapGnv93srNyggTA+zhZWPc3aeiEWun+CP3i2lqX9+Ijon0sn4sXoMgegpni74x0MdGyieT8e+bo7r7NIhehASeiB7FzLD3Bxd+eT4Mm2YFAwD+94S/Ro/91kQ/uFsbMT4X8954cWff0kgXB5YMxeW3x+Cr2cFKj7v5mRCEuFrgm7nB+OX5MCwf7Y3fXxyM2x9MwPm3RmP1pH7Q19HGcxHuOPvGSHw9Jxj/vTUKkwMdNPr+AODy22PwXIQ7AMDd2hhLR3kj6u0xiF8/Sa3gkyj4pqPVNRkYp1aNwOIRnirts/ul8A69ZoCCAKeOFoVtzw1C7hfTcPntMSofe4CzOUb72Srd7tu5Ifh0RiCWjvLCgSVDcWrVCKwa5wNPDXWgR/rawlBPm/G5maHsp3NZGuubA4wiAAAgAElEQVRp5HyU+fDJAAxys1C4zcmVI/DmBF9YGevB2cIQIS7mmBRgjzUT/bBp9gCJbb+cHYx+9uwDQ38ujsBvLw7B+beYG4U6WpREEM7JwhAbnw5Selw7U32sfzIA2Z9Pxfm3RuEVOd91dX5uFEXBUJf5b6xJr47xZnz89XE+Sve1MVH+/flPzmfOxlAvK+x4YTAuvT0G0zop062r+NqZYNkoL/H/332iXzeeTfd68NkU5H4xDSmfTMaLke5d8pofTw/E/iWdnzl8YOlQ7H2lY/cwQkh68K83MNHX6ZLXGeJhiQ+m9u+S15JnpK8NotRoR4nMCet5f9/kjyerPeijRVHo52CKO+smaPisei8yyKJY11wtCIIlLxtjuFkZIb+qsUtfd/4QV0wd4IgQFwtEZ1cit5IDQ11t7L+Vj/TSepntZ4Y6wdPGBN9deCDx+Kczg/BE0KNgzCg/W3w6IxAfnkjW2LnKSwpzMDfA2TdGoqy+GTbG+tBq6/m5Wxsj1M0CW6MyUcXhYk6YCx7WNmPLxQxw+QLMCXPFjFBhNgVFUXgiyEHiPUjr72imdjaLFgUI2p2/kZ42XhnhiWWjvVFW1wxPG2NQCtK0Pps5ACv2x0k89t28EIz2s8Oe6FzczatGUmEtHM0N0M/BFOumBcBEXweGetqgaRo0DXi9f0atc2/PzEAHE/rb41h8kcTjSRsmwcxAF4FOZpg1yAWF1Y34O74IZ+8/lHusXxeGwaMtOBPqaoGEghqJ5/e+Eo78qkZ88Pd9Beeji2cGu+DwnULxY9/MDcGTwY7Q19ESf6YCOV+eBRFu2H8rn/G5Q8uGwkhPB8fiCrH6cCLjNp/NDMJshgbVmkn9sGZSP6zcH4dTSSVyzx8AFo/wxCB3S7z2Zxzj86Kg05sTfPH9hQzx40tGeuKtiX44nlAssf2MUCeckHpMlZFKMwMd1DGsOOJiaYhx/nbYE50nd9/5Q1xhb2YAHW35YzsT+ttjgIs5BriYizMZFX33dbW1sHSUF9b8xfw3aG/7wjDxb9TP3hSnVo3Aj5cy8G9yKQDhtNkPpgXA2kRy6qyjueLPx9PGGJfWjBafp5+9KRaP9MTv13NktrVSM8B39d2xGLLxglr7siXvGvp8pDu2XMpUuO/MUGf8xvB+vWyNceGt0eLrriaM9rXFaSW/G1UMdrfEnbxqjR1PETtTfRxcOlTiO/3qaG98dS69S15fkf6OZkgtqeuy19vy7EDo6QivBUZ6Ovh4RhB2K7h+dNSmWQMwb7CrRr+L8iwbLQwsjvS1xapxPvhRye+HUOyrOcE4Glco8/iaiX749r8HDHto4DVnB+Pdo0lq7XvstWEY6GoBz/dUa1c5mRuguLaZ1baLhnlg5Tgf2LTdr8b1t8P4b6+w2jfU1QJ/Lo5AZlkDZmy9wbjNKyM8ce7+QxTVNCk8lq42hSUjvaCno4Uf5ofijYMJrM5BZNloL7w3pT/yKxsRm1vFah87U33UNbeiuVWg0mupQluLktv28LIxxqczg5BYWCNz7fZ3MIVB20CRjYk+Fo/wZLw3EkR7JPBE9CgURWHrgkFYsT+uU4NPBrpaOPP6SNiY6sPMQDKLpn3Q5cVhHriWUY6Fv8eKH7Mz1ceq8b7wtjWBk4UBNp5JBaeFhxmhzozTeBZGemBhpAc81p5mPJfFIzwxP9wVT3x/DTxBx6ca2pkayDzmZ2+KH+ZLri718ghPtPIFMNLrmsvA3DAXfDQ9EHdyq+BkYQhPG2PQNMQNchNbE6XHGOtvizB3S9xt6zyFuFpgYoADTPR18OYEP4X7UhQFikKHA4E/PzcII3xtYGagi+eGuiEmuwpBzuYY5WsjvnlTFIUAJzMEOJlhUqADqjhcHIjNx9f/yna6Rvk+yiZ6c4IvXtp1W9wx9rUzwTBvG4z0pXDkbiHi8yWDUktGPso2+fzpARjkZokHpQ0Y5WeDMf1kp1k5yQm8fP70AKwa54PITZfkvu+pAxzx3rF7aOFJNoDMDXUxXUnGkbxv9Sg/W+RVcjA50AHvTu4HHW0tTB3ggDP35Afq3hjvCxdLI9zJrUKoqwWeaetgZX0+Ffti8pBUWIsITyvMHeyCioYW3MisFO/LNuPCxkQPp1aNxLWMcjS18rHxdCpaeAIY6Wlj06wBCPe0gr6OFqKzKxHoaA4nC0NxENrJ3ACvjfFR/MalKAo4sbF1wSBs/i8dnBY+XhzmgYkB9hLPBzmb49eFwjpOAgEtt0PqZGEo8fuStv7JAJlzdTQ3lAl66mhRmKli0fLVE4W/X1tTfRxfMRwzGToJutoUWvkdv0bScv4wdqYG+GRGID47lQoun7mhP2ewC2Pjev/ioRKfq562ltxjKKLbLlg5LdgRm86morqxVeXjMPlzSQT6rTun0j52pvooq29Rul2AoxkOLBmKlJI6cFp4iPS2hrFUJgRFUcjcOAXXMitQ2cDFmH620KIoDPviYqd2rKSdfWMkDt8uwNbLmeALaBRWK+5wyrNstBd+vZIt8dgQD0sM8bBCbE4VAp3MMDvMBcEuspmPo/xscfVBuVqvK7Jz0RC8tOu2zOPPhrtJ/N/BzAAP69h18lX1zqRH19QXIj3kBp5G+trgemYFDHS00dTKV3hMYz1tcLjM28wa6IzlY7xx9UE5tCgKO65lo4RlAKM9VQI5WxcMgr6OFrS1KHx/MQOJUoNDAPDbC4OxeM8dlc+jPS9bY2jLuTY/EeSAny9nKf3smEzob48LqaWMzx1fMRyhrha4mlGudHBI2oxQJ4S4WKh8//J3MMWhZZGY+sM1pcEeR3MDbJgeKPGYt62JOKskKq0Mqw7Eo6GFB187E3w5JxifnExBYmEN/B3M8N28UBjr6yDE1QKxH4zHxtOpoADMGuSCUe0yuZtb+fiTYfBNT1sLr431hr6ONkb72Yqzy2eEOoOmgTcPsQs+OZkbiLODl4zykgk8WRjpoobhOv/F7AEoqmnGh8flDzx2hKuVoTh4xIgChvvYYLiPDUb42ODFP2JR3dgKUwMdfDpTMkN6YaR7twWevGyNkV3OUWtfRW0eJimfTEZxTRMmbL6q1utJ2xqVidfGeHe4HdhbkMAT0eMMcDHHlXfG4FJaGV7Zrf6NPNDJDOaGuriZJex4zgh1wrdzQxRmITAZ6WuL3C+moby+BXmVHAQ5m4sv1HMHu2LWIBdweQK504AUMdbTxtuT+8FAVxu/LgzDz5ezwOUJ8PxQN6w/kSzRyReNLGoqrVlXW0uik9PZpoc6wURfhzEgwpaRng7+XByBWzlVENA0Ir2sFd80GSyM9ECwiwWSCmsYA1D+DqZwtTLCWxP8cCevCuvbbfPMYBdMHfBo+kuYuxWrYtVWxnpYOsoLJxKK8KC0Qfz47y8OlvjejOlnh52LhuCfxGLYmQobKqKG6B8vDsHULdfEjWwzAx08P/TRlA0dbS3Ml+pwSDPQ1caLke4So+0bngoAoDzbxUBXGz8+OxDvHk0SN5BG+tpg7RR/meCttHH97GQyN/wdTLHnZdnpGSvH+soEntpPAaMoCnPCXGRS1rW1KLw4zEPise0LB2PnjRzkVDRiUqA966mhn8wIgoO5AeYOFgaSF4S7IaucA3drI/H37YNpARL7PBvuioLqRgQ5m0NfR7iNvAAH2p5VlbxMw2nBjqynZSnLgvjl+TB8eioF94trJRpy00OcMNLXhnGfdyb7I7GgFuml9dCigA3TAyW+E1OCHGSy/vS0tfBUiBM4LTwM97GW+C6Hulrg2GvDcDy+CJZGenguwg2WxnrQ1dbC2G8uI6dCvQamiKJaVi9EemBumCtqm1rxU1QG9sU86ox42RrD38EMHz0VgI9PpgAA9HW0sHPREDiYSwb8N80awCo7TdpLwx8Fk431dXBg6VD8cCEDlQ1c2JrqI720HpllDQqOwGzNRD/oqlh366/lkRjiYYXmVj4yyxrgY2cC/w+ZA1eHlg2FqYEuIr0V1/vR0dbCWKl7wJV3xiLi84sSj3nbGmPvKxHQoigs2hmLtIeymccAsHKsD5aP8UZUWhnSHtZha1SWwtePfX88AOCZIa54pm2g6JcrWfjibJrC/dytjeBmZSRe/vrdJ/rhpWGeiM+rEXcig5zNsOulcJmAG5PPZgRh1NdRSrcDgPem+GNTu/PT09HCrffGo7xBeUAQADZMD8DyfcyZpGyZGujg7rqJaOULcD2zAib6OhjqZS0RKLE11cfXc4LxzhHZ7Jm9r0SgkcuDoa42ssobZDptU4IcsHy0N4KczaFFAb9dy8HGM6kyxxndzxZ+9qbwa5t2/EKkO/zWnYX0mN04fztcSitjfC/+DqZ4cbgHLqSWIrGwVuH73vNyuESAYtsV5u+XvZnsgJ+qVimY6quvo41tzw/Cop2ygUZFZg1yxuZnQlHN4YKG8O/Y3MqHqdQ9++Ppgahs4CI2twq+dib4ak4wSmqb0coX4NDtAvH33sxABx9M648BzhbwdzBVej95eqAzPG2MUcXhIruCg5E+NnhlhCfrbLx1UvdZaWP97RC/fiIe1jbDxdIQFEXh+IrhaG7ly7QN7UwNZAZgRZaN8pYJPIV7WGHPK+Fy25gzBzorDTxteCoAPAGNJ4OdxIPCEwPs8d28ELx1SHh/0Nai8OmMIAS7mGP015fF+w5ys8AYPztoaVEw0tXGxbRSeNmY4F5RLa50IGgtmnlAUcAb4xUP2BroPHrvwS4WiP1gArLLOfC0MRYPGnfUO5P7MQ7KsrVuWn9kV3AYA09j+tnicnrHAvzSjPR04GNniiBnM9wvksycbT8YzNbX/6ajv6MpxvnbK9/4MUACT0SPRFEURvraItxTOHLI5OTKEdhyKQP/pUiO5Kye6Ac3KyNMCrSHoa42MsoaoKetBXdrow5FlG1N9RlXddPWotQKOgHAt8+EiG9q4/vbY3z/RxceCyM9/K+tkz/S1wYrxwobJe9N9ZfIwALAqjZLZ1k7xV9pox2A0uAEWwa62qxqDikS4mqBEFcLjOlnh5FfPWr8x384UaIGUICTGexM9XEtowL+jmZ4tgOFqXW1tbB/yVDsi8lDRUMLpoc4I9xTNmg1pp8dY3DO0lgPfy2PxKHbBWjhCTA3zAXu1qrXT1r/VCACnc2RUlyHSG9rlep0TQp0wIT+9qhv4cFchXpsUwY4YNPZNFS06yjJyz7q72iKV8d445crWaBpYQdC3boXxvo6WDlOtiC/tbEeKjlcxn30tLUwSSpjSEdbC/2UFN62MzOAnQqdj/YBBrb6O5oiwNEMKe2mCWm65oWtqT62PPuocZ5XyYEWRcHVirm2nGifs2+MRFZ5A+zNDWR+629P7oe4/GqU1gn//s4Whtj50hBx55HJIDdLDHKTXcXwf0/063AnekqQI9YfT0Z9y6OplOumPfocDfW0Yainjfem9EdNYyuuPChv64wJi/i/NNwTw7xtkPawDkM8rBgzCZ8MccTZ+w/FmQbPRbghsbBGpqHa3sxQJ3jbSv6m/R3MsO15yUUcSuuaMeOnG+IsFksjXcwPd8PyUd54+ucbyJYKzC0a5oFXx3gr7Oz52ZtIBMUDncwQ1vb5G+hqI8jZXO6+lka6Mh1ZVdibGWD3y+FYuucOWngCmBvq4rt5oeLP9cTK4bibVw1zQ13UNrXiRHwxrE30sGiYh/g391SIE54KcWIMPJ1cOQKWxrpwtjBkbAPMH+LKeA+jKOG0TC1K2K6YEeqM5lY+tLUo8aDN3sXhuJNbDQFNY4iHFeuBEDdrI2RunII1fyXiUloZ7Ez14WplxNhJWjrKCxwuH4dvF8DKWA9rp/jD0lgPFka6cDQ3kMj4eYLhei49pVbk5tpx+ON6jsIsBV1tCo7mhvhydjD0dLSgp6Ol8J4xd7ArhnhYYcbWG6htaoWXjTH+XjEcAMTZ1T52psj6fCqSi2tRUtuMga4WMtfOJaO8GANP1saS70VHWwuHlkXipZ230dD2e940awDmD3FFeUMLPjmZghuZFeKsQQczA3wzNwRmBro4+uowJBbWwkRfB7am+njnr0TE5lQh2NUc38wNYRyMWT3RD/O3x0g89sZ4X+jqqN62fH+qP1wtjZD6sB7Dva0RoaBIOw0aY/rZIWfTVHx/IQM/XMyQu63ITwsGYkqQcECifbuGacDR2kQfB5YORStfIH4+uO22+0SgA25mVaKsvgWj/GwYs+qZrJvWH4tHesl9fvFIT3EAX6S/oxnMDXVQzWnFvCGurAZUdLW1ZO5Pqg5Iulkb4ZMZgfjibBpaeAJMD3HCV3OClQ7OulsbIa+SeXbGB1P7Y5Gc+/zTA10wJcgRKSV18LYxgXlb/dLcL6Yhp4IDc0Ndienqs8NcxOUMVsgpR6CMvo4W/lg0BPZmBojPr0aIq4XEPXjDUwHYIPX3eG+qZJ1aXRZtIVW9NsYbLpaGuJVThRAXc0wOdEDoJ//J3X7LswNRUtOErPIGDPexwfQQJ5y7/1CmXISblRG+nRuCsM8UT92fG+aiUsaTyM5F4Ziw+Qpqm1rFr7d2inrtsU1n0vpM4Il6XFYRY2Pw4MH0nTsdS4UlulYTl4/L6WWob+ZhXH872JjoS9wY0x/WY8GOGFRyuNCigO/mhYrrFfU0TFPtfnk+TGE9Jb6ARkMzT3xTAgAuT4Ble+8gqq2BGuRshj8XD1UpEKBJZXXNePLH6+LpGPZm+jDW15EYfTDR10H8+oldmmFFqI7pO5r1+VS56f+qyCxrwNaoTFQ0tGBOmIvS32k1hwsOlwcXS/kBD3UduVuItxmyUaYEOWDrgkEaq42yYn8cY42eEFcLHFkeqdbvoayuGV//m46cCg4mBthj6SivXpGi3coXIK2kHh42Rh0KUgDAqaRinEgohqO5gcJaW0xeHu6J9U8F4G5eFTb8k4KS2mbMCHXC+1P7y/2e0zSt9mecX9kIfV0t2JsZYPpP15HEkGHx6hhvjPGzxWAPK5V+a/XNrTDR15E4t7K6ZuyNyUMVh4unBzpjsIdkcFvelO/0z55AfTMPl9PLYW2sh+E+Nowj2odvF8jUg/n5uUESmaDqauTykFnWAD97U5U7jiIfnbgvkdHpZWOMS0qKAbfw+IxTEC+tGY3EwhqEuFjAi8VUcHWJvl+/XcvGZ6dlgy2KitXezKrAq/vixEGe3S+Hy3TCeXwBBn7yn0Sgdby/HX5fNASAMJCZW8HBkj13JOraHVw6FIPcLNXObOjI7wYA1h2/J5FxaGGki7vrJjL+Rppb+XhQWg9fO1PGgUCaplHe0AJbE32F56TsnLk8AZ77LQa3c4UdVVtTfRxdPgwuloYYsvGCxIDGSF8b7H0lgvE3l7NpqtzXYdo++ePJ4ky6zLIGTNgsW+Po14Vh+CehGHZm+lg+2lsjWVhsrT9xX+JaTFFA3LqJChfzqOJw8cT3V8VtR2M9bZxYOQI+dp33W1OmlS9gzAiT58y9Epm6lCEu5pgc5IBXR3fO9KnX/ryrsByBSJCzGTY9HQxbU32klNQi2MVCXCeLSRWHi2d+jRZn1I7wscHviwaLM7iVyavkSGRssSV9fattakXIx+flbp/26RMy9wcuT4BRX0VJTCkW3Zfu5lVj9rabco93c+04DPtCfpkJRedL0zRyKjiwNzOQyHSVd59le9zejqKouzRND2Z6jmQ8ET2aoZ42pkg1aNt31vo5mOLG2nFILq6Fl41Jl61YpQ5PG2OZKSKD3BWveqWtRUkEnQBhmv2OFwYjvqAGza18lUZZO4OdmQGOvjoMx+KEhbZnDXJGVnkDlu65K65xsmKsDwk69QIrxnpLZAwsGuahkaATAPjYmeC7eaGst7c01uu03/OcMBfo6Wjh3+SH8LA2wsvDPWGkp6N25qI8r43xlgk8+dmbYO8r4Wr/HuzMDPD13BBNnF6X0tXWwgAX+Vkzqngy2AlPBgvrirEJPEV6WSOjrAHj/G3FmXZh7lY4uWoEq9frSOfBTc4qpO2pu/opU+fIzswAaybJr2X2zdwQmaDrnpfDoa+jDX0TbaWrLk0OdMAfN3LEU99CXC06nIEqYqSnw1gPSRVrp/RHXTMPUell8LUzwRcsVnWlIKewrq1JpwacxK/fge/XMG8b3F03AaX1LXAyN2A8lo62Ft6f1h/vHbsHQDjdqn1NRHszA9ibGeDA0qHYdjkL9c08PBvuhqEKMnDY6Gin++1J/ZBZ1oCY7CrYmurj+3mhcu9HBrraCr87FEWxytRRds56OlrY/XI4/kspRV1TKyYGOIin2a5/KgBvHUqAgBZ+xm+3/Q7fGO8rkaG0YqzigMTKsT74KepRrazpIU6spm9ODnTolJWG2Vg6yguX0srE9dJWT/BTev+2asvi3n8rH82tfMwd7NqtQSdA9RIUUwc4YuuCQTiVVAxHc0MsH+PFOiNMXfKyjycF2ONSWhnszQzw9dxgDPN+NDVeeio4EytjPRxfMRzXMypgpKeNCC8r1kEnAHIHCd+f6o/Zg1yUZh6xxdTf0dPRwsGlQ7HlYgZK65vx9MBHZTHC3C1xfMVwHI8vQm1TK/5utyjQmddHwtHcAM4WhkrrjQHCtkR7FEVp7B6x80aOWpnwvQ3JeCKILnIysRirDsSL/z8tWHjDelzlVnBwK6cS/RzMEOrasc4E0TUEAhoHbxfgTp6wcPdzEe4aCzz1RTRN47PTqeJV3yI8rfDHoiGsOhEEO2xGFnvKSKK8jKeuPL9GLg8v7byNW21T2CcH2uOnBYNU6mw1tPDExZ1H+dl02QIVnYXLE8Bv3VmZx7v6e5NV3iCzWleIizlOrGQXIFWmuKYJGWUNCHW16LYMaXXUNbfCVCqzr6cqr29BRlk9gl0sxPU4aZrG8YQi3M2rxkBXS8wa5KzwvQgENP64kYOY7EoEOpnj1THeEp3t5la+TK01XW0KGRunds6bYqm5lY/Egho4Wxp2SqYyIVRS2ySzEIxoWmMLjw89ba1u+61sOpOKX69KLrhw6/3xsDczwOivoxinJaqa8aSJ67J0DbDTSSV4/WA8+AIaBrpa+HRGEGOtOlHdQ2WW772Lc8nKs9KknXl9pLiAfW9GMp4Iogd4KsQJFka6uJRWBi9bE8wbrH69oN7Aw8YYHjaq1yAiuo+WFoUFEW5YEKG4SDnBDkVR+PDJACwd5YX65lZ425r0is5Tb/LFrAFY25bJwcTSqOd0sMf42coEnoKcu7aRaaSng/1LhuJ+US10tbXQ39FU5e+kib6ORqbWEZK8bU0kVrvTooDXx8vWqFOXk4Wh3JVNezJN1YfsCky1QCmKwtMDXfD0QHa1CrW0KCwe6SW3PpKBrjaei3CTKIatbtakJhnoaiusU0VohqO5IT6dGYTPT6eiqZWPyYH24sU5VMlQ6gxrp/hjgIs5vvk3HaGuFnhvan+Vp3zqdcHsCOmsqWnBjhjsYYmUkjqEuFjAylgPJvo6eLXdNMof5oeyCjoBwBsTfHErp1JcW+6zmUFYx2JlwqlbrvWYgbLOQjKeCIIgCILolWqbWrFgRwySi5mLdn8/LxQzB/aMun+ldc0Y/XUUmlsfrVYqvWoW0fVomsaIL6Mkplq4Wxvhyjtju/xcmrh8HLydj/yqRkwKcFC6SiDRN/EFNA7ezsf9ojoM9/l/e3ceZ0dVJnz89yTsCGGRzQEMO4wOqESBICMJijoqi7uyj+uouIz6usyrA867OKPgAjqiIqAoKrggyqZAAGEEUdFxBYSAbAJhEQgkgs/8cU6bm8vd+nbfe9Od3/fzqU/drjrn1OlbT6oqT1ed2vCvjx5r5bHkkUdZvOTRFXqIkUa93vEEsP/xP2z5xsnGsemGpd+x6h5Y8ghX33Qv22y8NpvNWrPncZ+Of/VTp/y/Z+94kiRJ086sNVfljDfO5Uc3LGK1mTOYOSP4+A+u4a4HlvLyOZuz/1NWnAu4TdZdg5MOfwafvOBaHljyCAfvvqVJpxVARPCmedvwL99a9hfpN+29zUj6suZqM1eKcT40MTNnBAft9sRRd0MjtPoqM0d+h9N4zNthY06+fOFyy9oNw/HRl+3CoV+4crk3dq46M3hTfbv3MPV7l/rjVl+FZ273+O4Fm7zlKz+b8omnTrzjSZIkSSu1n910D1f/4V6etuX67OK4hJI0aW5atJj5xyzgkb8syzt85bW7MXfb9smZ397+J77101u4+8GlvGTXzSf8woNRGs+b7qb643be8SRJkiS18dQt1+epW64/6m5I0rSz5YZrccIhu3Lchdfx0NJHOWLP2R2TTgA7brou7/uHqT/YtpYZV+IpIjYHPgQ8D9gQuA34NnB0Zt4zjnY2AD4IHABsBiwCzgU+mJk3D3LbkiRJkiRpOPbZaRP22WmTUXdjJFabOYOlj/6le8FprufEU0RsA1wObAycCfwWeAbwNuB5EbFnZi7qoZ0NazvbAxcCXwV2BI4AXhARe2Tm9U11JmXbkiRJkiRJGp7xvLPw05TEz1sz84DMfG9mzgc+BuwA/N8e2/l/lKTTsZm5T23nAEoSaeO6nUFtW5IkSZIkSUPSU+Kp3nG0L7AQ+FTT6n8FHgQOiYi1u7TzOOCQWv6optXHAzcCz42IrSd725IkSZIkScOSrDwvc+uk1zue5tX5+Zm53AOKmXk/cBmwFrB7l3Z2B9YELqv1Gtv5C3Be0/Ymc9uSJEmSJElDMXNGjLoLK4ReE0871Pk1bdZfW+fbD6Cdydq2JEmSJEnSUPz7S3buqdxG66w+4J6MVq+Jp1l1fl+b9WPL1xtAOxPadkS8PiKuioir7rzzzi7dkyRJkiRJmrj5O27cU7nPHTpnwD0ZrfEMLj4lZeZnM3NOZs7ZaKONRt0dSZIkSZK0ElhnjVW5/L3zO5b59EFP4ylbdLuHZ2rrNfE0dlfRrDbrx5bfO4B2JmvbkiRJkiRJQ/OE9dbk5x/cl2dtv/yNMGusOoOL3rU3//B3mzHECwIAABjOSURBVI2oZ8OzSo/lflfn7cZR2q7O243DNJF2JmvbkiRJkiRJQzVrrVU55R+fMepujEyvdzxdVOf7RsRydSJiHWBPYDHwoy7t/Ah4CNiz1mtsZwawb9P2JnPbkiRJkiRJGqKeEk+Z+XvgfGA28Oam1UcDawNfyswHxxZGxI4RsWNTOw8AX6rlj2pq5y21/fMy8/qJbFuSJEmSJEmjF5nZW8GIbYDLgY2BM4HfALsB8yiPuc3NzEUN5RMgM6OpnQ1rO9sDFwJXAjsB+wN31HZ+P5FttzNnzpy86qqrevp9JUmSJEmS1F1E/CQzW76er+e32tVk0BzgZErS553ANsAngN17SfzUdhYBewCfBLat7ewGnATs2px0msxtS5IkSZIkaXh6vuNpOvCOJ0mSJEmSpMk1KXc8SZIkSZIkSeNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQMRmTnqPgxNRNwJ3DjqfkySxwN3jboTmpKMHfXL2NFEGD/ql7Gjfhk7mgjjR/1aWWPniZm5UasVK1XiaTqJiKsyc86o+6Gpx9hRv4wdTYTxo34ZO+qXsaOJMH7UL2PnsXzUTpIkSZIkSQNh4kmSJEmSJEkDYeJp6vrsqDugKcvYUb+MHU2E8aN+GTvql7GjiTB+1C9jp4ljPEmSJEmSJGkgvONJkiRJkiRJA2HiSZIkSZIkSQNh4mkKiYjNI+ILEXFrRCyJiIUR8fGIWH/UfdP4RMSGEfHaiPhWRFwXEQ9FxH0R8cOIeE1EzGgqPzsissP01Q7bOiwiroyIB+o2FkTECzuUnxkR74iIX9R+3R0RZ0fE3A511oyIoyPidxHxcETcERFfj4id+vuG1E39998uHm5vU2du3Zd31337i4h4e0TM7LCdF9aYua/G0BURcViXvg085tSfiDi8y7EkI+LRhvIee1ZCEfHSiDguIi6NiD/VfX1qlzrT5vhiXPVvPLETEdtFxHsi4sKI+ENELI2IP0bEmRExr02dbsewN7apN+59GhEbRLnOXhjluvvWKNfhm3eo47V6n8YZO9Pu3NRPvGmZccbPyV3iJyPigqY6HnsmyDGepoiI2Aa4HNgYOBP4LfAMYB7wO2DPzFw0uh5qPOrB6T+B24CLgJuATYAXA7OAbwAvy/oPNCJmAzcAPwe+3aLJX2bmGS2281HgncDNwBnAasArgQ2AIzPz+KbyAXwdeCklrs6qZV8BrAG8JDPPbKqzOnABsCdwFXAhsAXwMmApMD8zr+j1u1FvImIhsB7w8RarH8jMjzaV358SVw8DXwPuBl4E7ACckZkva7GNtwDHAYtqnaWU2NgcOCYz39WizsBjTv2LiKcAB7RZvRcwH/heZr6wlp+Nx56VTkRcDewCPEDZhzsCX87Mg9uUnzbHF+NqYsYTOzU58Arg18APKXGzA7AfMBN4W2Z+sqnO4cBJlGvhq1t04buZeVVTnXHv04jYkHLdvX0t/+P6u+wP3AHskZnXN9XxWn0Cxhk7s5lG56Z+4k3LG2f8HAA8pU1ThwBbA+9uvJb22DMJMtNpCkzAeUBSDoqNy4+tyz8z6j46jWt/zqdclM9oWr4pJQmVlJPZ2PLZddnJ49jG3FrnOmD9prYWUf6DMLupzqtqncuANRqWPx1YQjngrdNU5321zumNvw/lAJnAr5p/T6dJiaGFwMIey65b990SYE7D8jUoJ6oEXtlUZ3aNkUWNcQKsX2MqKSe/ocec08Bi6r/qvtivad957FnJJsrF6nZAAHvX7/PUNmWn1fHFuBpq7BwOPLXF8mdR/lO2BNisRZ0EDh9Hn8a9T4ET6rpjmpa/tS4/t8V2vFYfXuzMZhqdm/qJN6f+46dDG+sBi+u+fXzTOo89E91Ho+6AUw87CbapQXNDi+Bch5LZfRBYe9R9dZqU/f3+ur+Pa1jWzwn2i7XOES3WfaiuO7pp+SV1+bxe2qsH9xvr8q1a1GnbntOE42QhvSee/rHuh1NarJtf113cS4x0am8YMec0sHj6u/pd3wzMbFjusWcln+j+H8Bpc3wxroYbO13qnk/TH+Hq8sMZx3/++tmnwOMo//l8gMcmFWZQzr8JbN2w3Gv1IcbOdDo39RNvThOLnw71jqz1TmuxzmPPBCfHeJoaxp5zPz8z/9K4IjPvp2Th1wJ2H3bHNBB/rvNHWqx7QkS8ISLeX+c7d2hnfp2f22LdOU1liIg1KH8NWgxc2ksdysFuS+CazLyhxzqaPKtHxME1Ht4WEfOi9XgqnWLhEso+n1tvCe6lTrv9OoyY02C8vs5PzMxHW6z32KN2ptPxxbhacXS6FgJ4SpQxxN4bEYd0GPukn326O7AmcFm9zv6reh1+Xv2xcRwqr9VHYzqcm/qJNw3G6+r8sx3KeOzp0yqj7oB6skOdX9Nm/bXAvpRnQS9oU0ZTQESsAhxaf2x1YnxOnRrrLAAOy8ybGpatDfwNZayf21q0c22db9+wbBvKmArXZ2arC71WdXqJzeY6mjybAl9qWnZDRByRmRc3LGu7nzLzkYi4AXgS5Zn23/RQ57aIeBDYPCLWyszFQ4w5TbKIWBM4GHgU+HybYh571M50Or4YVyuAiHgisA/lP/yXtCn2tqafH42IzwNvz8yHG5b3s08HVcdr9ck3Hc5NHndWABGxB+Xu72sy86IORT329Mk7nqaGWXV+X5v1Y8vXG0JfNFgfBp4MnJ2Z5zUsXwz8G7ArZQyM9SljIFxEuZ30gnpSHdNPzAyrjibHSZQL802BtSknyxMot5+fExG7NJQd5L6d1TQ3fqael1O+43Mz8w9N6zz2qJvpdHwxrkas3hn3ZWB14KjMvKepyA2Ux2F2oJz7nkA5hi0E3gB8oam8sTM9Tadzk7GzYhi78/tzbdZ77JkgE0/SCiIi3kp508ZvKW9U+KvMvCMzP5iZP83Me+t0CSWDfQWwLfDaoXdaI5OZR2fmhZn5x8xcnJm/zMw3UgYSXBM4arQ91BQydrF1QvMKjz2ShqU+Kv4lyhugvgZ8tLlMZl6cmcdn5jX13HdbZp5OedzkHuBVTX940TTkuUmTKSJmUZJIS4GTW5Xx2DNxJp6mhua//DUbW37vEPqiAaivlf4E5ZXC8zLz7l7q1Vt/xx6N+fuGVf3EzLDqaLA+U+fDiof7mubGzxQSEU+ijGFxM3B2r/U89qjBdDq+GFcjUpNOp1JeM/514OCso+P2ot6tOXYM85i0kpqi5yZjZ/QOpoyD9M3MvGs8FT329M7E09Twuzpv92zvdnXe7tlOrcAi4u3AccAvKUmn28fZxJ11/tdbijPzQeAW4HERsVmLOq1i5veUMV62rmNN9VLH2FzxPCYe6LCf6r7eijKA6/U91tmstn9zZi6GocacJle3QcU78dgjmF7HF+NqBCJiVeA04JXAV4BXtxlTp5txnf+qyYoDY2fFMdXOTcbO6I0NKv6YO7975LGnByaepoaxAc72jYjl9llErEO5JXkx8KNhd0wTExHvAT4GXE1JOt3RRzNjbym4vmn5hXX+vBZ1nt9Uhjog3uWUjP9evdShnJRvAraPiK16rKPBahUPnWLh7yn7/PLMXNJjnXb7dRgxp0lS39hzCOXC+sQ+mvDYI5hexxfjasgiYjXgdMqdTl8EDukjCT5mtzpvPCb1s09/BDwE7Fmvsxv7O4PyOBcsuz5v/Oy1+uhNtXNTP/GmSRIRuwG7UAYVX9BnMx57epGZTlNgorw+MYEjm5YfW5d/ZtR9dBr3Pv1A3XdXARt0Kfs0YEaL5fsAD9d25jatm1uXXwes37B8NrCo1pvdVOdVtc5lwBoNy58OLAHuANZtqvO+Wuf0xj4C+9flv2rVd6cJxc5OwNotls+mvL0igfc3LF+X8teYJcCchuVrUC6qEnhlU1tb1RhZ1BgnlAE8r6t19hhFzDlNWhwdUr/7szqU8dizkk+UgXoTOLXN+ml1fDGuhho7qwPfq2U+38v32hhjDctmNOy3Oydjn1LufEjgmKblb63Lz23RD6/Vhxc70+rc1E+8OfUfP01lT6xl39mlnMeeCU5RO6UVXERsQ7mA2xg4k/JK4t0oA5pdQzm4LhpdDzUeEXEYZfC6RymP2bV6E8HCzDy5ll9AuVXycspYLAA7A/Pr5w9k5v9psZ1jgH+udc4AVgNeAWxIOTgd31Q+KGMrvJQyyPlZtewrKP+JeElmntlUZ3VKtn4uJYl2AbAl5a+XS4H5mXlF1y9FPYuIoygD0V8C3AjcT3nt7wso++ls4MDMXNpQ5wBKDDwMfBW4G9iP8naOM4CXZ9MJISKOBD5JuSD7GmV/vhTYnHJCfFeLvg085jQ5IuJS4JnAfpl5VpsyC/DYs9Kpx4sD6o+bAs+l/CX30rrsrsZ//9Pp+GJcTcx4YiciTgIOB+4CPk35D1KzBdlwF0JEJGVogp9THp2aRfmL/pMpf9U/MDPPb+rTuPdpRGxIOe5tX+teSfmjz/6UZMPczPx9Ux2v1SdgnLGzgGl0buon3rS88Z63ap11gVuBVYDNs8P4Th57JsGoM19OvU/AFpRXqN9GCdYbgY/TkLV3mhoT5Y1j2WVa0FD+NcB3Ka/sfIDyV5abKBfre3XZ1uHAj4EHKQmKi4EXdii/CvAO4L8pt3veQ0lkzO1QZy3gQ5S7bZZQsv6nA3876u96Ok6UVwafRrkIuhf4c/3Ovw8cCuWPCi3q7Vn35T113/533dczO2zrRTVm7q8x9GPgsFHHnNOEY2inepz5Q5f977FnJZx6OEctbFFn2hxfjKvhxA6woEvZBI5qav8jdZ/fSkl0LqacC48Htp7MfQpsQHnxy42U6+7bKK9M37xDHa/VhxM70+7c1E+8OfUXPw11/qmuO62H9j32THDyjidJkiRJkiQNhIOLS5IkSZIkaSBMPEmSJEmSJGkgTDxJkiRJkiRpIEw8SZIkSZIkaSBMPEmSJEmSJGkgTDxJkiRJkiRpIEw8SZIkSZIkaSBMPEmSpBVSRCyIiIyIHHVfJEmS1J9VRt0BSZI0PUTEbOCGSWruiElqZ9qKiKPqx4WZefIIuyJJktSWiSdJkqSp6V/r/GLg5BH2Q5IkqS0TT5IkabLcARzYYf184Mj6+SLgkx3K/tS7eCRJkqY+E0+SJGlSZOZi4Nvt1kfEeg0/3pSZbctKkiRpenBwcUmSJEmSJA2EiSdJkrRC6vZWu4g4fGx9RBxel82JiFMi4oaIeCgiboyI0yLiyU11Z0bEqyPiwoi4LSIejohrIuLDEbFuj/1bLSJeExHfiYg/1DbujYhfRMQxdbD1bm08ISI+FBH/FRF3R8SfI+KeiLg2Ii6NiGMjYq+mOs3fybMavofGae+meutGxEERcWJE/Kz29c91uz+tfd6mhz4vrO0vrD+vERFvj4grImJRRPwpIn4SEW+JiNWa6m4dEZ+IiN9ExIN12+dFxLO7bPPkht9rdl12UET8oGH/LYyIz0fE33b7HSRJ0vBEpm8oliRJg1eTQyfVH0/JzMO7lF8APAsgM6NLe0cAjwM+RuuhBJYA+2fmeRGxDvA14PltNv1b4O8z884OfZsDfB3YqsOvsBR4a2ae0KaNFwBfrf3u5L7M/Otjiu0ScS3My8wFtc5qwJ+A1bvUeQR4e2Z+ql2BmnB6InAjsAfwPeCpbYqfR/nel0TE/sCXgbXblD0yM49vs82TgcPqjzsA/w4c0KadpcCbMvPEdr+DJEkaHsd4kiRJ08ELgRcDdwKfB34JrFmXvYCScPlaRGwFnEJJOl0GnA7cRkmkvLnOd6QksA5utaGI2AP4AbAWkJTkyvnALXWbewCH1PWfiYglzQOlR8TfsHzS6XvA94FbKXekbwzsAjwHmNXUhbEB3L9V578C/neLrv6y4fOM+h3cWrfzC+CPwF+ALYC5wH6Ua8PjI+LWzPwWna0KfIOSdDobOAu4m/L9HQk8Hngu8P6IOBs4A3gI+ARwVW3j+cCrgACOjYgLMvM3XbY7lnS6EfgC8Dtgg7psX2A14HMRcWdmfqdLW5IkacC840mSJA3FgO94ArgSeF5m3tNU7rPA6+qPPwF2Bd6XmR9uKrcxcDWwGfAosEVm3tZUZh1KomcL4F7ggMy8uEXftgUuALYEHgRmZ+ZdDevfBXyk/viezPyPNt9BAM/MzEtbrBu7iLs4M/duVb+h7ExKEuu8bHPxFxE7U5JomwLXA9tl5l9alFtISdBBSbwdmpmnNpXZjvJdrgXcR0kIAszPzD80lf0A8KH6439m5ptabPNklt3xBOWtiPtl5gNN5d4CHFd/vL3+DsuVkSRJw+UYT5IkaTpYCry8OelUHU1JkEBJOp3TnHQCyMw7gLFHvWYCrcYdeh0l6QQl4fKYpFNt6zrK439QHi17fVORbRs+f65VG7WdbJV0Gq/MfDQzz22XdKplfgG8v/64NeUuqG4+25x0qm1dC4wtn0X5fQ9qTjpVHwHur5+f28M27wNe2SqhVB/V+1r9cVPgoB7akyRJA2TiSZIkTQdnZeaNrVZk5i3AwoZFbccvAn7Y8LnVINWH1Pk1mXlWpw5l5oWUR9ugPALWaHHD5yd1amfILm/4vFsP5VuOyVRd1vD5qsy8slWhzHyYZY/ebRURa3TZ5qk1SdjOMQ2fD2xbSpIkDYVjPEmSpOngii7r/8iygcBbJkAayo1Zv3FFRMwCdh4rFxHtBrduNHZXzk5Ny78PvKN+/mZE/H/g9My8uYc2+1bfCHcYsDdlLKb1gHaJns27NPcg5bHDdhq/y07feWPZqH26vUPZC7q0dRVlIPV1gad3KStJkgbMxJMkSZoOFnVZv6THso3lmhMyW7DsbvG96tSr5ZJYmXlORHwFeDWwEXAsZXDtayl3HV0CfLfLnT3jEhFvBz5M9zfbjVm3y/q7Oz26R+/feXPZbnc8XddpZWZmRFwPPAXYICJWz8wlnepIkqTBMfEkSZKmg8cMgt1OqwGze9T8drnxWLXFsoOBCyl3Po09brddnQ4DHo2IrwPvbB7kfLwi4iDKm/rGXApcTHkE8X7KGFlQ3qZ3Qv08s0uz4/ke+/3OW1ncvQgPNnx+HMsntiRJ0hCZeJIkSepN42DWX8zMw9qW7EG9W+hE4MSI2Bp4JmVA7/mU5NNM4FXAMyPi6Zn5x7aNdfdvdf4I5W1w57QqFBEr0nhT7azVQ5m1Gz77VjtJkkbIwcUlSZJ6c0vD527jH41LZl6fmV/MzDdm5vaUt+/9rK7eAnh3v23XpNbY+Fbfbpd0qp7Y73aGaNtOKyMiKG/lg/I4oHc7SZI0QiaeJEmSepCZdwG/rj/uHhHdxkCayLZ+yrI36EG5G+oxxeo8ujS3ScPn33cp+9wu61cE87us35Vl41P9eMB9kSRJXZh4kiRJ6t0pdb4W8N4Bb2thw+dWwyOMPUK2dot1jRrHRNqmXaGI2AI4oqeejdbBEbFRh/X/3PD5m4PujCRJ6szEkyRJUu8+BdxYP783It4dEW2vpyJiVkS8NSKe3bT8gxHxnE51gTc1fP55i/U31PmOEbFmh3Z+w7LBtvePiGe06OcmwLeBdTq0s6JYDzgtIh6TcIuIN1LGxQK4HfjKMDsmSZIey8HFJUmSepSZD0bEAZQ3wq0L/Afwhoj4BuUxvAfq8q2BZwB7A6ux/GNzUB4XOxq4PSLOA66mJEpmAE8A9gP2qmWXAMe26M4FwM6UO57OiohTgLtY9gjelZl5d2YujYgTKHcCrQpcEhFfoDyG9mfgaZQ7ndYDvggc2teXMzzfBg4AfhkRJwLXUvp+IMseFUzgDZnpwOKSJI2YiSdJkqRxyMyr611DpwFPpTy+9r86VFlCSQgt10ydbwocVqdW7gIOysxftVh3DHAwsBGwT50azQMW1M//Uvs6D1gd+Kc6NTqBkkhb0RNP76F8fwey7G19jZYCb87M7wy1V5IkqSUTT5IkSeOUmb+LiF2BFwEvBvagJJHWBu6nPI73c+BC4DuZeU9TE/sBzwaeRRkMe1tgQ0pC5W7gV8A5wImZeW+bPtwSEU8D3kVJOs2u23/MYOOZ+XBE7Au8jnL31ZMpd2LdDlxRt3N+RMwe/7cxdEsz88URcRDlTq0nA+tTfpcfAMdk5q87NSBJkoYnMrN7KUmSJGlEIuJklt0VtlVmLhxdbyRJ0ng4uLgkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsK32kmSJEmSJGkgvONJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkD8T8LpXtnoHpMJQAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "385a467a-5cb2-49e9-ba49-dd68c7cfb6c6"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "73cb3b63-1038-48d3-ff11-1a2dda4941df"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YoQA_MIBMknS"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "548bd638-42a5-4cc4-c073-01f07ad9a4cd"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "05a92d00-674b-4e12-c9d4-4a70b2d19768"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "fd00e983-d38e-4d4a-f1e1-23ab6525ecc8"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "c9204a3a-f6a7-44de-a499-32280bf3e02b"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f9828364c50>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f98280c8750>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f9828121350>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f9827cb6e90>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 14
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "ef830bbd-5c4e-4dc7-c1ea-3d112d7d809e"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "8057191e-6d36-429f-d649-12689677409a"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "42891ad8-9f74-4c75-a750-776d3d6b8ceb"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "e8cbfcc9-59f0-459a-a451-fd2d49c31973"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "single_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 9s 45ms/step - loss: 0.1683 - rmse: 0.2196 - val_loss: 0.0219 - val_rmse: 0.0226\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0866 - rmse: 0.1100 - val_loss: 0.0134 - val_rmse: 0.0140\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0560 - rmse: 0.0704 - val_loss: 0.0052 - val_rmse: 0.0057\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0487 - rmse: 0.0611 - val_loss: 0.0041 - val_rmse: 0.0046\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 2s 33ms/step - loss: 0.0458 - rmse: 0.0576 - val_loss: 0.0109 - val_rmse: 0.0111\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0432 - rmse: 0.0542 - val_loss: 0.0084 - val_rmse: 0.0086\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 2s 36ms/step - loss: 0.0401 - rmse: 0.0504 - val_loss: 0.0080 - val_rmse: 0.0082\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0383 - rmse: 0.0481 - val_loss: 0.0129 - val_rmse: 0.0130\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0363 - rmse: 0.0456 - val_loss: 0.0074 - val_rmse: 0.0075\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 2s 33ms/step - loss: 0.0349 - rmse: 0.0437 - val_loss: 0.0116 - val_rmse: 0.0118\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0322 - rmse: 0.0405 - val_loss: 0.0081 - val_rmse: 0.0082\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0439 - rmse: 0.0573 - val_loss: 9.7213e-04 - val_rmse: 0.0014\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0297 - rmse: 0.0377 - val_loss: 0.0026 - val_rmse: 0.0029\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0267 - rmse: 0.0336 - val_loss: 0.0077 - val_rmse: 0.0078\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0242 - rmse: 0.0305 - val_loss: 0.0028 - val_rmse: 0.0031\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 2s 35ms/step - loss: 0.0222 - rmse: 0.0279 - val_loss: 0.0035 - val_rmse: 0.0036\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 2s 36ms/step - loss: 0.0200 - rmse: 0.0252 - val_loss: 0.0033 - val_rmse: 0.0034\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 2s 36ms/step - loss: 0.0181 - rmse: 0.0227 - val_loss: 0.0044 - val_rmse: 0.0045\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 2s 36ms/step - loss: 0.0160 - rmse: 0.0201 - val_loss: 0.0085 - val_rmse: 0.0086\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 2s 36ms/step - loss: 0.0140 - rmse: 0.0176 - val_loss: 7.0871e-04 - val_rmse: 9.2643e-04\n",
-            "Model: \"sequential\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "lstm (LSTM)                  (None, 32)                4736      \n",
-            "_________________________________________________________________\n",
-            "dropout (Dropout)            (None, 32)                0         \n",
-            "_________________________________________________________________\n",
-            "dense (Dense)                (None, 1)                 33        \n",
-            "=================================================================\n",
-            "Total params: 4,769\n",
-            "Trainable params: 4,769\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "21b2a7ee-356f-4ea9-b8e7-ba034e91c36e"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "b9f0c285-968c-4ada-828c-15f7d3a025c9"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "xFJT1rZDAUVL",
-        "outputId": "b91b2190-3709-431b-bf10-226a10d5b1ce"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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s/PD4C6devSrl079u7di4eHB0eOHCE0NBTIH+YKCQlhw4YNBbbt3r07kydPLrFGPz8/Tp48aXt98uRJ2z5FRKTilOueSufOnVm9ejUAq1evJjg4uFCbjIwMsrOzATh9+jQ7duwgICCATp06sWXLFjZu3MjGjRvx9PS0Bcrhw4dt2yclJVG/fv0S6/D19cXb25tdu3ZhGEaxtYiIyM1VrnsqkZGRREVFsWrVKurUqcOcOXOA/Ce6VqxYwbRp0zh48CCTJk3CYrFgGAbDhw8nICCgxH7j4uLYunUrLi4uVK1atcDQV+fOncnMzMRqtZKQkEBMTAwBAQFMmjSJl19+mcuXLxMUFERQUFB5Dk1ERMrAYtzmb+jIyzNIT8+s7DJKxZHGesGx6nWkWsGx6nWkWsGx6rXHeyp6R72IiJhGoSIiIqZRqIiIiGkUKiIiYhqFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYhqFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYhqFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIal/JsfPbsWUaPHs0ff/zBXXfdxZw5c6hWrVqhdvfeey+NGzcGoHbt2ixcuLDA+qlTp/LJJ5+wc+dOAJYvX86HH36Ik5MTXl5evP766wQEBHDmzBlGjRrFzz//TO/evfmf//kfWx8DBw4kLS0NDw8PAGJiYqhVq1Z5Dk9ERG5QuUIlOjqawMBAIiMjiY6OJjo6mnHjxhVq5+HhQXx8fJF97Nmzh4yMjALLwsLCePrppwFITExkxowZLF68GHd3d1566SVSUlJISUkp1Nfs2bN54IEHynNIIiJSDuUa/kpMTCQ8PByA8PBwEhISbmj73NxcZs2aVSiIvL29bV9funQJi8UCgJeXF23btsXd3b08ZYuIyE1SriuV9PR0fH19AfDx8SE9Pb3IdllZWfTp0wcXFxciIyPp0qULAHFxcQQHB9v6uNoHH3zA+++/j9VqJTY2tlT1TJgwAScnJ0JDQ3n++edtYSQiIhXjuqEyePBgTp06VWh5VFRUgdcWi6XYX+LffPMNfn5+HD16lIiICBo3boy7uztfffUVy5YtK3Kb/v37079/f9asWcOCBQuYOXNmiXXOnj0bPz8/MjMzGTVqFPHx8barqJJYLFC9utd129kDZ2cnh6kVHKteR6oVHKteR6oVHKtee6z1uqGyZMmSYtfVqlWLtLQ0fH19SUtLo2bNmkW28/PzA6Bu3bq0a9eOvXv34uHhwZEjRwgNDQXyh7lCQkLYsGFDgW27d+/O5MmTr3sgV/bh7e1Njx492L17d6lCxTDg7NmL121nD6pX93KYWsGx6nWkWsGx6nWkWsGx6q3MWn187ihyebnuqXTu3JnVq1cDsHr1aoKDgwu1ycjIIDs7G4DTp0+zY8cOAgIC6NSpE1u2bGHjxo1s3LgRT09PW6AcPnzYtn1SUhL169cvsY6cnBxOnz4NgNVqJSkpiUaNGpXn0EREpAzKdU8lMjKSqKgoVq1aRZ06dZgzZw6Q/0TXihUrmDZtGgcPHmTSpElYLBYMw2D48OEEBASU2G9cXBxbt27FxcWFqlWrFhj66ty5M5mZmVitVhISEoiJiaFOnToMGzYMq9VKXl4egYGB9OvXrzyHJiIiZWAxDMOo7CIqU16eQXp6ZmWXUSqOdFkOjlWvI9UKjlWvI9UKjlXvLTf8JSIicjWFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYhqFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYhqFioiImEahIiIiplGoiIiIaRQqIiJiGoWKiIiYRqEiIiKmUaiIiIhpFCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYppyhcrZs2cZMmQIoaGhDBkyhIyMjCLb3XvvvfTq1YtevXoxYsSIQuunTp1Kq1atbK+XL19OWFgYvXr14umnn+bAgQMAbNmyhT59+hAWFkafPn3YunWrbZuff/6ZsLAwQkJCmDp1KoZhlOfQRESkDMoVKtHR0QQGBrJ+/XoCAwOJjo4usp2Hhwfx8fHEx8ezcOHCAuv27NlTKIzCwsJYs2YN8fHxDBs2jBkzZgBQo0YNFixYwJo1a3jjjTcYP368bZvJkyfz+uuvs379eg4fPkxycnJ5Dk1ERMqgXKGSmJhIeHg4AOHh4SQkJNzQ9rm5ucyaNYtx48YVWO7t7W37+tKlS1gsFgCaNWuGn58fAI0aNSIrK4vs7GzS0tLIzMykZcuWWCwWwsPDSUxMLM+hiYhIGbiUZ+P09HR8fX0B8PHxIT09vch2WVlZ9OnTBxcXFyIjI+nSpQsAcXFxBAcH2/q42gcffMD777+P1WolNja20Pqvv/6aZs2a4ebmRmpqKv7+/rZ1/v7+pKamluoYLBaoXt2rVG0rm7Ozk8PUCo5VryPVCo5VryPVCo5Vrz3Wet1QGTx4MKdOnSq0PCoqqsBri8Viu6K41jfffIOfnx9Hjx4lIiKCxo0b4+7uzldffcWyZcuK3KZ///7079+fNWvWsGDBAmbOnGlbl5KSwuzZs4mJible+ddlGHD27MVy91MRqlf3cphawbHqdaRawbHqdaRawbHqrcxafXzuKHL5dUNlyZIlxa6rVasWaWlp+Pr6kpaWRs2aNYtsd2XIqm7durRr1469e/fi4eHBkSNHCA0NBfKHuUJCQtiwYUOBbbt3787kyZNtr0+ePMnIkSOZOXMm9erVs/V/8uTJAm2u7FNERCpOue6pdO7cmdWrVwOwevVqgoODC7XJyMggOzsbgNOnT7Njxw4CAgLo1KkTW7ZsYePGjWzcuBFPT09boBw+fNi2fVJSEvXr1wfg3LlzREZGMnbsWNq0aWNr4+vri7e3N7t27cIwjGJrERGRm6tc91QiIyOJiopi1apV1KlThzlz5gD5T3StWLGCadOmcfDgQSZNmoTFYsEwDIYPH05AQECJ/cbFxbF161ZcXFyoWrWqbegrLi6OI0eOMH/+fObPnw9ATEwMtWrVYtKkSbz88stcvnyZoKAggoKCynNoIiJSBhbjNn9DR16eQXp6ZmWXUSqONNYLjlWvI9UKjlWvI9UKjlWvPd5T0TvqRUTENAoVERExjUJFRERMo1ARERHTKFRERMQ0ChURETGNQkVEREyjUBEREdMoVERExDQKFRERMY1CRURETKNQERER0yhURETENAoVERExjUJFRERMo1ARERHTKFRERMQ0ChURETGNQkVEREyjUBEREdMoVERExDQKFRERMY1CRURETKNQERER0yhURETENAoVERExjUJFRERMo1ARERHTKFRERMQ0ChURETGNS2UXYI9yc3M4c+ZPcnKyK7uUAlJTLRiGUdlllJo91Ovi4kaNGj44O+u/ukhF0E9aEc6c+RMPDy+qVPHHYrFUdjk2zs5O5ObmVXYZpVbZ9RqGwYUL5zhz5k/uvLN2pdUhcjvR8FcRcnKyqVKlql0Fitw4i8VClSpV7e6KU+RWplAphgLl1qDvo0jFUqiIiIhpFCp2KiTk4QKv165dw+zZbwCwevUq1q37othtd+zYzp49P93U+kREiqIb9SbZffwcPx49S5u61Wlep+pN3Vd4eN8S1+/c+SOenl488ECLUveZk5ODi4v+O4hI+ZTrt8jZs2cZPXo0f/zxB3fddRdz5syhWrVqhdrde++9NG7cGIDatWuzcOHCAuunTp3KJ598ws6dOwFYvnw5H374IU5OTnh5efH6668TEBDAli1bePPNN7Farbi6ujJu3DgCAwMBGDhwIGlpaXh4eAAQExNDrVq1ynN4AHz5Syqf/3yyxDaZWTmknLqAYYDFAo3urIK3e/Gntuf9/nS/z6/MNS1evAhPTy+eeWYgH3+8gvj4T3B2dubuu+9hxIgXiY//FCcnJ9avX8fo0ePw9fVjxowpZGScpXr1Grz88iT8/f2ZNm0ybm5u/Pbbfpo3b8GWLZtYsCCGGjVqkJeXx9NP92HhwvepUaNGmWsVkdtLuUIlOjqawMBAIiMjiY6OJjo6mnHjxhVq5+HhQXx8fJF97Nmzh4yMjALLwsLCePrppwFITExkxowZLF68mBo1arBgwQL8/Pz47bffGDp0KJs2bbJtN3v2bB544IHyHFKZZGblcOXtGIaR/7qkUCmNrKwsBg9+xvb63LkMHn64Y6F2cXFL+Pjjz3Fzc+P8+fPccccd9OrVxxY6AOPHj6Zbtx5069aDL76I5+23/5cZM94E4M8/01i4MAZnZ2eqVPFmw4Z19Ov3DNu3byMgoJECRURuSLl+8yUmJrJs2TIAwsPDGThwYJGhUpzc3FxmzZrFm2++SUJCgm25t7e37etLly7ZnuBp1qyZbXmjRo3IysoiOzsbNze38hxGibrf53fdq4rdx8/x/Me7ycnNw8XZide731vuITB3d3eWLPnQ9nrt2jXs37+vULuGDRsxZcqrPPxwJx5+uFORff3yy26mT/9fALp27c6CBXNt6x55pAvOzs4AdO/ek5dfHku/fs/w5ZfxPPZYz3Idg4jcfsoVKunp6fj6+gLg4+NDenp6ke2ysrLo06cPLi4uREZG0qVLFwDi4uIIDg629XG1Dz74gPfffx+r1UpsbGyh9V9//TXNmjUrECgTJkzAycmJ0NBQnn/++VI9TmqxQPXqXgWWpaZacHYu/TMMrepWZ+GTLWz3VFrcVXgIsCyursHJyWJb5uRkwckpv8Z//Wsuu3btYPPmZJYujSEubmWB9fksODvnvzYMy/9/7YTFYsHLy8vWrk6dOtSsWYudO7ezb99eXntt+g2dh+sdQ2WxWCyFvsfXcnZ2um4be+JI9TpSreBY9dpjrdcNlcGDB3Pq1KlCy6Oiogq8tlgsxf4S/+abb/Dz8+Po0aNERETQuHFj3N3d+eqrr2xXOtfq378//fv3Z82aNSxYsICZM2fa1qWkpDB79mxiYmJsy2bPno2fnx+ZmZmMGjWK+Ph4wsPDr3d4GAacPXvxmmXGDb8T/H7/O7jf/w4A095FfnU/eXmGbVlenkFenoHVmkNq6klatmzD/fe3YMOGr8nMvICHhxcXLlywbX///Q/w9ddf0bVrd9atW0vz5i3Jzc3DMAzy8vIK7KdHj15Mnvwqjz76GGAp17FU9jvqrzAMo9D3+FrVq3tdt409caR6HalWcKx6K7NWH587ilx+3VBZsmRJsetq1apFWloavr6+pKWlUbNmzSLb+fnlDx/VrVuXdu3asXfvXjw8PDhy5AihoaFA/jBXSEgIGzZsKLBt9+7dmTx5su31yZMnGTlyJDNnzqRevXqF9uHt7U2PHj3YvXt3qULFkeXl5TFlykQuXMjEMAz69n2KO+64g7/97WEmTvwHmzZ9y+jR4xg9ejzTp7/G8uXLbDfqi9OhQ0emT59C9+4a+hKRG1eu4a/OnTuzevVqIiMjWb16NcHBwYXaZGRk4OnpiZubG6dPn2bHjh0MGzbM9jTXFa1atbIFyuHDh7n77rsBSEpKon79+gCcO3eOyMhIxo4dS5s2bWzb5uTkcO7cOWrWrInVaiUpKcn2VJij2rBhU4HXjz0WRlhYL3Jz8xg69Dnb8gULFhfatl69+sTGriiwbO7chYXavfLK5ELLDhz4jYCARtSvf3fZCheR21q5QiUyMpKoqChWrVpFnTp1mDNnDpD/RNeKFSuYNm0aBw8eZNKkSVgs+TPWDh8+nICAgBL7jYuLY+vWrbi4uFC1alXb0FdcXBxHjhxh/vz5zJ8/H8h/dNjT05Nhw4ZhtVrJy8sjMDCQfv36lefQbkvLli1h9epV/M//TK3sUkTEQVmMyp6bvJLl5Rmkp2cWWHby5O/4+9evpIqKZy/3KErLXuotzffTkcbRwbHqdaRawUVStXsAABTySURBVLHqtcd7KpX/aI6IiNwyFCoiImIahUoZec6bg+vm5BLbuG5OxnPenAqqSESk8ilUyiinVWuqDo8oNlhcNydTdXgEOa1aV3BlIiKVR9PSlpG1QxDn3o2l6vAIzr0bi7VDkG3dlUC5dnlpZWSc5aWXngfg9Ol0nJycqF69BhYLREfH4urqWu76R46MJD39FO7u+RNwRkQ8yyOPdCmy7YkTx9mzZzehoV3LvV8RubUpVMqhqGApb6AAVKtW3Tbv19UzEl95msqsaeonTZpK06bNrtvuxInjJCR8dcOhkpubC+iTF0VuJwqVcro6WC5FDMUzdnG5AqU406ZNxt3dnf37f6V58xZ4eVUpMBPxwIH9mDVrDrVr1+Hrr9eyatUKrNYcmjW7j7Fj/2mbNPJ6+3jooQ62K5aQkIfZsGETCxf+m99/P8Tgwc/QrVt37rijKr/+upcxY/4BwPjxUTz11ABat25LSMjD9OzZh+3btzFu3D/5448/ylSLiDgm3VMxgbVDEJcihlLlX7O4FDHU9EC5Ii0tlYULY3jxxTHFtjl8+BCJiRtYsCCGJUs+xMnJmfXr1xXZ9rXXXmXw4GcYPPgZMjLOFtvniBEjadGiFUuWfMiTT/YvscZLly7RrNn9xMYup1q1aqWuRURuDbpSMYHr5mQ8YxdzYcx4PGMXY+0QdFOCpXPnkOv+lf/jj9vYv38fw4YNAiAr63Kxn4lS2uGvG+Hs7EynTp0B+OGH0tciIrcGhUo5XXsPxdohqNz3VIrj6elp+9rZ2RnD+L93q2dnZwP5M/J269aDESNG3nD/zs7OttmQ8/LysFqt120HkJWVbfvazc2tQPCVtRYRcUwa/iqHom7KX32P5XrvYymP2rXr8NtvvwKwf/+vnDhxHIA2bdqRlJTImTOngfxPjDx58kSp+vT3r237ILDNm5PJyckBwMurChcvXryqXR0OHPiNvLw8UlNPsm/fL0X217Zt2WsREcekK5UyKukpr5IeNzZLp06d+eqrLxkwoB/Nmt1H3br5HwNwzz0NGD7874wePRLDyMPZ2YUxY/6Bv3/t6/bZs2dv/vnPsUREPE379oG2K6OAgEY4OTkREfE0jz3Wg379nqF27ToMGPAE9evfQ+PGTYrsrzy1iIhj0oSSZZxQ0nPeHHJatS4xMFw3J+OycweXXowqts2NsJcJGkvLXurVhJKVy5FqBceq1x4nlNSVShmVJihu1g17ERF7pXsqIiJiGoWKiIiYRqEiIiKm0T2VcjqU8V8W7JrHqt9WcsGaSRVXb/o27sffW77IPdUaVHZ5IiIVSlcq5ZD4+3o6ffQQcXuXkmk9j4FBpvU8cXuX0umjh0j8fX1llygiUqEUKmV0KOO/PPv1IC7lXCTHKPjO8xzDyqWcizz79SAOZfy3TP136NCWKVMm/l+fOTl069aZ8eNv7PHkvn3DOHu2+Hm9SmrTt28YgwY9SUTEU4we/QLp6aduaN9XW7x4ER9+uKzY9adO/cmrr44HICVlP1u3br7hfYwcGcmvv+4tc40iUn4KlTJasGse1tyipzG5wpprZdFP88vUv6enJ//970Gysi4D8MMP3+Pj41umvspj7txFxMauoGnTZixb9n6BdYZhkJdnzvtQ7rzTh6lTZwGQkvIbW7duMaVfEalYuqdSRqt+W1noCuVaOYaVj39bwRtBb5ZpH4GBf+M//9nMI490ISHha0JCurJr1w4gf8qTGTOmcPz4H7i7ezB+/CsEBDQiI+Mskye/wp9//sn99z/A1e9tLeuU+AAtWrRi1aoVnDhxnDFjRtKs2f3s3/8rs2e/zcaNG9i4MQGrNZugoEcYOvQ5AJYseY8vv/yCGjVq4OvrR5Mm9wJw7NhR/vd/Z3D27BmcnZ14/fWZODk5MX58FDExH/DeewvJzs5i9+6fGDhwMA899DBvvTWLQ4cOkpOTw7PPRvLww53IyrrM9OmvceBACvXq3U1WVlaZzrOImEdXKmV0wZp5/UZAZnbp2hUlODiUxMT1ZGVlcfDgAe67737busWLF9GoURNiY1fw3HMvMHXqJADef/9dmjdvSVzcSoKCHiE19SRwY1PiF+U//9lEgwYBQH4o9O79BHFxKzly5HeOHj3Ku+/G8v77H7J//z527drBr7/uY8OG9SxZ8iGzZ79dYFjqtddepU+fJ4iNXc6CBTHUqnWnbZ2rqyvDho2gc+cQliz5kODgUJYujaFNmwd5992lzJ27iPnz53Lp0iU++2wV7u4efPDBKoYOfc42F5qIvTqU8V/GfzuaBu/ehd871Wjw7l2M/3Z0mYfJ7ZGuVMqoiqs3mdbz123n7eZd5n0EBDTixIkTJCR8TWDg3wqs2717l224qE2bBzl3LoMLFzLZtWsn06blL3/ooQ7ccUdV4MamxL/aqFHP4eTkTMOGAQwf/jyZmefx96/N/fc/AMC2bd/xww/fMWRI/uesXLp0kWPHjnDx4kU6dnwED4/8jyvu8P9nFrh48QKnTv1Jx46PAODu7n7dGrZt+47Nm79l+fI4ALKzs0hNPclPP+2kb9+nbOeqYcOA6/YlUlkSf1/Ps18PwpprtY1yXHmw56P9y4l5dCnB9UMrucryU6iUUd/G/Yjbu7TEITAXiytPNH6qXPvp0CGI+fPfZt68RWRmnitzP2WdEn/u3EVUr17d9joz87wtKK70O2DAYMLDHy+w3cqVH5a51msZhsG0abOoV+9u0/oUqUhXP9hzrRzDSk6OlWe/HkTSk/9x+LciaPirjP7e8kVcnV1LbOPq7MpzLV4o1366d+/JkCHDC/0V3qJFKzZs+AqAHTu2U61aNapU8aZly/9bvnXrFs6fzw+i8kyJX5L27QP58svPbVPj//lnGmfOnKZFi9YkJ39DVtZlLl68wJYtm4D8afR9fHxJTk4C8j8H5vLlywX69PLyKjDVfvv2gaxa9ZHt/tCVYa6rz8F//3uAgwcPlPt4RG6Gm/1gjz1RqJTRPdUaEPPoUjxdvHCxFAwXF4srni5exDy6tNx/dfj6+vHEE4Wvdp59NpL9+/cREfEUCxf+m1deeQ2AIUOG89NPOxkwoB/Jyd/g5+efX+9V09BHRDxFVNQLnDpV9keEr2jX7q+EhHRlxIghDBr0JK+++g8uXrxIkyZN6dIllIiIZxg7dlSBT5icOHEKq1atICLiKUaMeLbQo8qtW7fl8OFDDB78DImJ6xk8eCg5OTlERDzFgAH9eO+9hQD07t2XS5cu0r9/X957bxGNGzct9/GI3Aw38mCPo9PU92Wc+v6KQxn/ZdFP8/n4txVkZmfi7ebNE42f4rkWL5h+GWsvU8mXlr3Uq6nvK5cj1Qo3p16/d6phcP1ftRYspD6fUep+NfX9Leieag14I+jNMj82LCK3vop4sMdeaPhLROQm69u4X6Fh8muZ8WCPPVCoFOM2HxW8Zej7KPagoh7ssQcKlSK4uLhx4cI5/UJycIZhcOHCOVxc3Cq7FLnNVdSDPfZA91SKUKOGD2fO/ElmZskTMVY0i8XiUEFnD/W6uLhRo4ZPpdYgAhBcP5SkJ/9TYQ/2VBY9/VXE01/2Sk/R3DyOVCs4Vr2OVCs4Vr32+PSXhr9ERMQ0ChURETGNQkVERExz299TERER8+hKRURETKNQERER0yhURETENAoVERExjUJFRERMo1ARERHTKFRERMQ0t02orFu3ju7du9O0aVP27NljW75lyxb69OlDWFgYffr0YevWrbZ1P//8M2FhYYSEhDB16tQKnRyxuHoBFi1aREhICI8++iibNm2yLU9OTubRRx8lJCSE6OjoCqv1avv27aNfv3706tWLPn36sHv3biB/xuCpU6cSEhJCWFgYv/zyS6XUV5Rly5bRtWtXunfvzqxZs2zLizvPlS0mJoYmTZpw+vRpwH7P7cyZM+natSthYWG88MILnDt3zrbOHs+tPfz8lOTEiRMMHDiQxx57jO7duxMbGwvA2bNnGTJkCKGhoQwZMoSMjNJ/cuRNYdwmDhw4YBw8eNAYMGCAsXv3btvyX375xTh58qRhGIaxf/9+o0OHDrZ1jz/+uLFz504jLy/PGDp0qJGUlFTp9aakpBhhYWFGVlaWceTIESM4ONjIyckxcnJyjODgYOPIkSNGVlaWERYWZqSkpFRYvVcMGTLEdp6SkpKMAQMG2L4eOnSokZeXZ+zcudPo27dvhddWlK1btxoRERFGVlaWYRiGcerUKcMwij/Ple348ePGs88+a3Tq1MlIT083DMN+z+2mTZsMq9VqGIZhzJo1y5g1a5ZhGPZ5bu3l56ckqampxs8//2wYhmGcP3/eCA0NNVJSUoyZM2caixYtMgzDMBYtWmQ7z5XltrlSadiwIQ0aFJ5aulmzZvj5+QHQqFEjsrKyyM7OJi0tjczMTFq2bInFYiE8PJzExMRKrzcxMZHu3bvj5uZG3bp1qV+/Prt372b37t3Ur1+funXr4ubmRvfu3Su03issFgsXLlwA4Pz58/j6+trqDg8Px2Kx0LJlS86dO0daWlqF13et5cuXExkZiZtb/meu1KpVCyj+PFe2GTNmMG7cOCwWi22ZvZ7bDh064OKS/+kaLVu25OTJk4B9nlt7+fkpia+vL/fddx8A3t7eNGjQgNTUVNv3HyA8PJyEhITKLPP2Gf4qja+//ppmzZrh5uZGamoq/v7+tnX+/v6kpqZWYnX5rq3Lz8+P1NTUYpdXtAkTJjBr1iw6duzIzJkzGTNmTJF128v5PHz4MNu3b+eJJ55gwIABtl9u9nI+r5aQkICvry9NmzYtsNxez+3VPvnkE4KCggD7PLf2WFNJjh07xr59+2jRogXp6em2P958fHxIT0+v1NpuqQ/pGjx4MKdOnSq0PCoqii5dupS4bUpKCrNnzyYmJuZmlVdIeeqtTCXV/d133/Hyyy/z6KOPsnbtWl555RWWLFlS8UVepaR6c3NzycjIYOXKlezZs4eoqKhK/Qu1pFoXLVpUof8/S6M0/4cXLFiAs7MzPXv2rOjybkkXLlxg1KhRTJgwAW9v7wLrLBZLgavYynBLhUpZf3mdPHmSkSNHMnPmTOrVqwfk/6Vy5XL9Spsrw2RmKUu919aVmppqq6u45WYrqe5//OMfvPLKKwB069aNV199FaiY81mckupdvnw5ISEhWCwWmjdvjpOTE2fOnCnxPFdGrfv37+fYsWP06tULyD9/ffr04eOPP7bbcwvw6aefkpSUxJIlS2y/7Crr3JbEHmsqitVqZdSoUYSFhREaGgrkD9mmpaXh6+tLWloaNWvWrNQab/vhr3PnzhEZGcnYsWNp06aNbbmvry/e3t7s2rULwzBYvXo1wcHBlVhpvs6dO/Pll1+SnZ3N0aNHOXz4MM2bN+eBBx7g8OHDHD16lOzsbL788ks6d+5c4fX5+vqybds2AL777jvuvvtuW92rV6/GMAx27drFHXfcYbtkr0xdunTh+++/B+DQoUNYrVZq1KhR7HmuLE2aNGHr1q1s3LiRjRs34u/vz6effoqPj4/dntvk5GTee+89FixYgKenp225vZ1bwG5+fkpiGAavvPIKDRo0YMiQIbblV77/gF38nrptpr7fsGEDr7/+OqdPn6Zq1arce++9LF68mHfeeYfo6Gjq169vaxsTE0OtWrXYs2cPL7/8MpcvXyYoKIiJEydW2KVlcfVC/nDCJ598grOzMxMmTKBjx44AfPvtt0yfPp3c3Fwef/xx/v73v1dIrVfbvn0706dPJycnB3d3dyZNmsT999+PYRhMmTKFTZs24enpyfTp03nggQcqvL5rZWdnM2HCBH799VdcXV0ZP348gYGBQPHn2R507tyZVatWUbNmTbs9tyEhIWRnZ1O9enUAWrRowZQpUwD7PLf28PNTku3bt9O/f38aN26Mk1P+9cCYMWNo3rw5UVFRnDhxgjp16jBnzhzbOa8Mt02oiIjIzXfbD3+JiIh5FCoiImIahYqIiJhGoSIiIqZRqIiIiGkUKiIiYppb6h31IhXhzJkzDB48GIBTp07h5OREzZo1OXLkCL169WLy5Mk3Zb+7du1i2rRpZGdnk52dzWOPPcaLL77I999/j6urK61bt74p+xW5EXqfikg5zJs3Dy8vL4YOHXrT9/Xoo4/y9ttv07RpU3Jzczl06BABAQEVWoPI9ehKRcQk33//PTExMSxatIh58+Zx7Ngxjh49yokTJ3j55ZfZtWsXmzZtwtfXl4ULF+Lq6srPP//MG2+8wcWLF6lRowYzZswodoqV06dP4+PjA4CzszMBAQEcO3aMFStW4OTkxOeff87EiRNp0KABkyZN4vjx40D+zNFt2rRh3rx5HDlyhCNHjnDmzBmGDRtGv379Kuz8yO1BoSJykxw5coSlS5dy8OBBnnzySebOncv48eN54YUX+Pbbb+nYsSNTp07lnXfeoWbNmqxdu5a33nqLGTNmFNlfREQEXbt2pV27djz88MP07t2bv/zlLzz11FMFrlTGjh1LREQEbdu25fjx4wwdOpR169YB+RNTrly5kosXL9K7d286duxolxMniuNSqIjcJEFBQbi6utK4cWNyc3NtnyfSuHFjjh07xqFDh/jtt99skwPm5eXZrkSKMnLkSHr27MnmzZv54osv+PLLL1m2bFmhdv/5z384cOCA7XVmZqbtg9OCg4Px8PDAw8OD9u3bs2fPHoWKmEqhInKTXPk0SScnJ1xdXW2TkTo5OZGbm4thGDRq1IiPPvqo1H3Wq1ePZ555hn79+hEYGMiZM2cKtcnLy2PlypW4u7sXWlfZn7Uhtz49UixSSe655x5Onz7Nzp07gfzPykhJSSm2fVJSEleeq/n9999xcnKiatWqVKlSxXYlAvkf43v1Fcy+fftsXycmJpKVlcWZM2fYtm2bXcxmLLcWXamIVBI3Nzfmzp3L1KlTOX/+PLm5uURERNCoUaMi28fHxzNjxgw8PDxwdnZm9uzZODs788gjjzBq1CgSExOZOHEir7zyClOmTCEsLIzc3Fzatm1rm3K+SZMmDBo0iDNnzvD8889r6EtMp0eKRW4TevRYKoKGv0RExDS6UhGxM6+99ho7duwosGzQoEE8/vjjlVSRSOkpVERExDQa/hIREdMoVERExDQKFRERMY1CRURETPP/AFTsXO3EKnJ4AAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Lu7m2Rr4AbMK",
-        "outputId": "c9d7e6dc-0bc7-47c7-d46e-b3995916a961"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "fjXexah9C8yg",
-        "outputId": "589003e9-f035-4c9b-bcf9-3377d047f0ef"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "id": "7mtLZ6S-DPU-",
-        "outputId": "7d37e336-cbae-4183-95c3-421271831727"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAssAAAFwCAYAAABO7TbwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9e5QcdZ33/65LX+eWmVxmQhKiQBYfEFjxsquCaCQIhMs+DCgiKj6KR37rJUZX1kVd4BBFXTm7PvuAynJH4yrhCBrucQVF5SJIEAiIJpAJySQzmWtf6/b7o/pbXd1d1V3fqp6qrpnP6xzOITM93dXddfnU+/v+vD+CYRgGCIIgCIIgCIJoQIx6AwiCIAiCIAiiU6FimSAIgiAIgiBcoGKZIAiCIAiCIFygYpkgCIIgCIIgXKBimSAIgiAIgiBcoGKZIAiCIAiCIFzo+GL5y1/+Mt7+9rfjjDPOCPxcv//973H22Wdb/x1zzDF46KGHPP3tY489hje/+c3W3/7nf/5n08dfddVVeNOb3mT9e/PmzTjzzDNx9tln44Mf/CBefvll63ff//73sW7dOrzvfe/Dr3/9a+vn09PT+OxnP4tTTz0Vp512Gp5++mkAwI4dO/CBD3wAZ555Jj71qU9hdnaW52Nw5Pbbb8e6detw5JFH4uDBg4GfjyAIgiAIYj4gdHrO8hNPPIFsNotLL70Uv/jFL9r2vJOTkzjllFPw8MMPI5PJtHz8Y489hhtvvBHf//73Wz722Wefxa233oqHHnrIKnBnZ2fR3d0NANi2bRt+9KMf4YYbbsDLL7+MjRs34o477sDo6Cg+9rGP4f7774ckSbj00kvxlre8Beeddx7K5TKKxSJ6e3sxPDyMSy+9FG9729twxx13YGRkBBs2bAj0eTz//PPo7e3FRz7yEdxxxx0YGBgI9HwEQRAEQRDzgY5Xlt/61reir6+v5mevvvoqPv7xj+Occ87BBRdcgL/85S/cz3v//ffjxBNP9FQo86BpGr71rW/hn/7pn2p+zgplACgUChAEAYBZOK9fvx7JZBKrVq3C6tWrsX37dszMzOCJJ57AueeeCwBIJpPo7e0FAOzatQtvfetbAQDvfOc78cADD1iv/c1vfhPDw8M488wz8eMf/9jzdh911FFYuXKl/zdOEARBEAQxD5Gj3gA/fPWrX8UVV1yB173udXjmmWdwxRVX4NZbb+V6jq1bt+JjH/sY19/88Y9/xFlnnYVly5bh0ksvxZo1axoec/vtt+O9730vli1b1vC7H/7wh7jpppugKApuueUWAMDo6CiOO+446zGDg4MYHR1FOp3GwMAAvvzlL2PHjh04+uijcdlllyGbzWLNmjXYtm0bTj75ZNx3333Yu3cvAOCOO+5AT08PtmzZgnK5jPPPPx/vfOc7sWrVKq73SRAEQRAEQZjErljO5XJ4+umn8bnPfc76WblcBgA88MAD+O53v9vwN4ODg7jhhhusf+/fvx8vvfQSTjjhBOtn3/nOd/A///M/DX/73ve+F5///Odx9NFH45e//CW6urrw8MMP4x//8R8tRZcxOjqK++67D7fddpvjtn/oQx/Chz70Ifz85z/Hddddh29+85uu71NVVTz//PP46le/iuOOOw5XXXUVfvCDH2DDhg3YtGkTNm3ahGuvvRZr165FMpkEADz66KN48cUXcf/99wMAZmZm8Morr+CQQw7B2Wef7fg6X//613Hssce6bgdBEARBEMRCJnbFsmEY6O3txV133dXwu1NOOQWnnHJKy+e49957sW7dOiQSCetnX/jCF/CFL3zB9W/sNoqTTjoJV1xxBQ4ePFjj7X3hhRfw6quvWttQKBSwbt06PPjggzXPtX79elx++eUAzEJ+37591u9GR0cxODiIoaEhDA0NWarzqaeeih/84AcAgMMPPxw33ngjAGDnzp341a9+ZX02X/nKV3DiiSc2bH87/d4EQRAEQRALhY73LNfT3d2NlStX4t577wVgFog7duzgeo6tW7di/fr1XH9z4MABsF7I7du3Q9d19Pf31zzm3e9+Nx599FH88pe/xC9/+UtkMhmrUN61a5f1uF/96ldYvXo1AGDt2rXYunUryuUydu/ejV27duHYY4/F0qVLMTQ0hL/+9a8AgN/97nc4/PDDAQDj4+MAAF3Xcd111+H8888HAJxwwgnYvHkzFEUBYBbS+Xye630SBEEQBEEQVTpeWd64cSMef/xxTExM4F3vehc+85nP4Nvf/jYuv/xyXHfddVBVFaeffjre8IY3eHq+kZER7N27F29729u4tuP+++/H5s2bIUkS0uk0rrnmGqtJ7+KLL8ZVV12FwcFB17+//fbb8bvf/Q6yLKO3t9eyYKxZswannXYaTj/9dEiShK997WuQJAmA6c3+4he/CEVRsGrVKnzjG98AYKrEP/rRjwAA69atw/DwMADgvPPOw549e3DOOefAMAz09/fj2muv9fT+br31VvzXf/0XxsbGcNZZZ+Gkk07Cpk2buD4jgiAIgiCI+UbHR8cRBEEQBEEQRFTEzoZBEARBEARBEGERuFi+7bbbcOqpp2L9+vX41re+5fiYRx55BO973/uwbt06q0mNIAiCIAiCIDqdQJ7l3//+99i2bRvuvvtuJJNJq/HMjqZpuPLKK3HTTTdhcHAQ5557LtauXYsjjjii5fPrug5NI5cIQRAEQRAEMXckEpLr7wIVy5s3b8YnP/lJK+d38eLFDY/Zvn07Vq9ebQ3GWL9+PbZt2+apWNY0A5OTlOZAEARBEARBzB1Ll/a4/i6QDWPXrl148skncd555+HCCy/E9u3bGx4zOjqKoaEh699sQh1BEARBEARBdDotleWLLroIY2NjDT/fsGEDNE3D1NQUfvKTn+DZZ5/Fhg0bsG3bNitSjSAIgiAIgiDiTMti+eabb3b93ebNm7Fu3ToIgoBjjz0WoihiYmKiZqqd24Q6giAIgiAIguh0AnmWTz75ZDz22GP4+7//e+zcuROKojRMtTvmmGOwa9cu7N69G4ODg9i6dSu+853v+H5NTVMxMXEAqloOsumEB2Q5if7+pZCkjp9dQxAEQRAEMScEGkpSLpfxL//yL9ixYwcSiQS+9KUv4e1vfztGR0fxla98Bddffz0A4OGHH8bXv/51aJqG4eFhXHLJJZ6eX1G0hga/sbG9SKez6OrqJbvHHGIYBnK5aRSLeSxZsjzqzSEIgiAIgpgzmjX4dfQEP6died++VzA4eCgVyiFgGAZGR1/F0NDqqDeFIAiCIAhizpizNIyooEI5HOhzJgiCIAhioRPLYjlq1q07sebf99zzc1xzzTcBAD/72R24995fuP7tU089iWeffWZOt48gCIIgCIJoD9S51Wb+4R/Obfr7p5/+AzKZLI455jjPz6mqKmSZviqCIAiCIIiwoQqszdxww/eRyWRxwQUfxk9/+mPcddcWSJKE173u9fjUpz6Du+66E6Io4oEH7sXnP/9PWLZsEN/4xpWYmprEokX9+PKX/xVDQ0PYtOlyJJNJvPTSizj22OPw6KO/xnXX3Yj+/n7ouo4PfvAcfO97NzWkjxAEQRAEQRDtI9bF8tbnRnH3n/a1fiAHZ71xCOuPbp4DXSqVcNFFF1j/np6ewgknvKvhcbfffjN++tO7kUwmMTMzg56eHpx99jlWMQ0AX/rS53HaaWfgtNPOwC9+cRf+4z++jW98w4zWO3BgP773vRshSRK6urrx4IP34v3vvwBPPvk4jjhiDRXKBEEQBEEQcwx5ln2QSqVw880/sv77xCc+5fi4ww9fgyuv/Aruv/8eSJLk+JjnntuOdetOBQCceup6bN/+R+t373nPydbfrV9/Fu67bysAYOvWu3D66We18y0RREdRUnWMTBai3gyCIAiCiLeyvP7owZYqcJR8+9v/jmeeeRqPPvoIbr31Rtxyy4+5/j6dTlv/Pzg4hP7+xfjDH57A888/j6997ap2by5BdAx3bt+L7/1mF7Z9+h2QRUplIQiCIKKDlOU5Qtd17N8/iuOPfwsuueSzmJ2dRaFQQDbbhUKhmh39xjcei4ceuh8A8MAD9+LYY9/k+pxnnnk2rrzyq3jPe97rqlQTxHxgPFdGXtGganrUm0IQBEEscKhYniN0XceVV34VH/nIB/Cxj12Ac889Hz09PXjnO0/EI4/8Dy666AI888zT+Pznv4R77vk5PvrR83H//ffgc5/7outznnDCSSgUCli/niwYxPymqGgAAEXr2JlJBEEQxAIhlhP8FupEuR07nsd3v3sNrr32v0J7zYX8eRPRcdUDL+GuZ/fh/kv+HgPZZNSbQxAEQcxzmk3wi7VneSFx220342c/u4O8ysSCgCnLZZVsGARBEES0ULEcEz784Yvw4Q9fFPVmEEQolCpFsqp37MIXQRAEsUAgzzJBEB1HUTGLZfIsEwRBEFFDxTJBEB1HUWUNfmTDIAiCIKKFimWCIDoOS1kmGwZBEAQRMVQsEwTRcRRYdBw1+BEEQRARQw1+HExNTeJzn/v/AAAHD45DFEUsWtQPALj++luQSCQCv8anP/1JjI+PIZUyp/d99KP/B+95z8mOj9279zU8++x2nHLKqYFflyA6iaLKlGUqlgmCIIhomffF8pYtMjZtSmHPHgErVhi47LIShodVX8/V17cIN9/8IwDADTd8H5lMFhdc8GHr96qqQpaDf6T/+q9X4Q1vOKrl4/bufQ0PPXQfd7GsaRpNACQ6GhpKQhAEQXQK87pY3rJFxsaNaRQKAgBgZETAxo1pAEXfBXM9mzZdjmQyiZdeehHHHnscstmumiL6wx9+P771rX/H8uWH4P7778Edd/wYiqLiqKOOxhe+8M+eitZNmy7HO95xgqUwr1t3Ih588Nf43vf+E6+8shMXXXQBTjttPXp6erFjx/PYuPFSAMCXvrQB559/IY4//i1Yt+5EnHXWOXjyycexceOl2LfvNV/bQsSLa3+zE38Zy+M7/3B01JvChaUsU7FMEARBRMy89ixv2pSyCmVGoSBg06ZUW1/nwIH9+N73bsRnPrPR9TG7du3Etm0P4rrrbsTNN/8IoijhgQfudXzsFVd8BRdddAEuuugCTE1Nuj7npz71aRx33Jtw880/wgc+8KGm21goFHDUUW/ELbdsRl9fn+dtIeLNnw/ksHM8F/VmcKEbhi1nmWwYBEEQRLTMa2V5zx6B6+d+ec97Tm6pyv7hD4/jxRdfwCc+8REAQKlURH9/v+NjvdoweJAkCe9+91rubSHiTUHRYjfYwz61r0zRcQRBEETEzOtiecUKAyMjjYXxihXtLR7S6bT1/5IkwTBsF/tyGQBgGAZOO+0MfOpTn+Z+fkmSoFcKHl3XoShKy8cBQKlUtv4/mUxaBX2QbSHiRUHRY2dlYLFxANkwCIIgiOiZ1zaMyy4rIZOpvdhmMmaT31yxfPkheOmlHQCAF1/cgb17XwMAvPnNb8OvfrUNExMHAQDT01PYt2+vp+ccGlqOF198AQDwm988AlU1/dbZbBfy+bztcYfg5Zdfgq7rGB3dhxdeeM7x+YJsCxEv4qgss4EkAKCSskwQBEFEzLxWls0mvmLb0jC88O53r8V9923FhRe+H0cddTRWrToUAPD61x+Giy++BJ///KdhGDokScbGjZdiaGh5y+c866z/jX/+5y/gox/9IP7u796OTCYDADjiiDUQRREf/egHcfrpZ+D9778Ay5cfggsvPA+rV78ef/M3Rzo+X5BtIeJFoazFzvdLyjJBEATRSQiGYXTs1UhRNExO5mt+tm/fKxgaWh3RFi086POONyf/v9+ipOr49edOiHpTPLNjdAYfvv1pAMDnTjoMF75lZcRbRBAEQcx3li7tcf3dvFaWCWKhU1A0xMyFUacsx0sVJwiCIOYfVCwTxDxF0w2UKzYGwzAgCO1NgZkr7J5lKpYJgiCIqJnXDX4EsZApKNWiU4uRvEyeZYIgCKKTiGWx3ME263kFfc7xxl4sxykRo6hSsUwQBEF0DrErlmU5iVxumgq5OcYwDORy05DlZNSbQvikYFNoY1Us1xT5ZMMgCIIgoiV2nuX+/qWYmDiA2Vn3MdBRMF1UkZBEZBKxu/9wRZaT6O9fGvVmED6pUZZjpNAyZVkWBVKWCYIgiMiJXbEsSTKWLOm8POAP/b/f4sTDF+PyU52zjQkibArleCq0TFnuSck07pogCIKInPkjg0aIbhiYLak0bYzoKAr2VIk42TBUHQKAbFKiNAyCIAgicqhYbgP5spllGydfKDH/qVGWY2RnKCo60gkRSUmkY4ogCIKIHCqW28BsyRyfHaeChJj/xLbBT9WQliXIEnmWCYIgiOihYrkNzLBiOUYFCTH/KcQ0VaKoVpVlsmEQBEEQUUPFchuoFst0YSc6h7jmLJcUU1lOSAIVywRBEETkULHcBmaKZlFCS8ZEJ2EvluO0bzJlWZbEWG03QRAEMT+hYrkNzJINg+hAaj3L8VFoC4qGdEJCQhRileJBEARBzE+oWG4D01QsEx1IbIeSKDrSsogEeZYJgiCIDoCK5TYwW2RpGHRhJzqHuHqWi6qpLCclIVZFPkEQxHxnyxYZxx/fhcHBbhx/fBe2bIndbDtfLIx3OcewBj9aMiY6iXw5psVyRVk2ACgxso8QBEHMZ7ZskbFxYxqFggAAGBkRsHFjGkARw8NqtBs3x5Cy3AZYsazFqCAh5j9FRUdKNg/xOK16sAa/hCigrMZnuwmCIOYzmzalrEKZUSgI2LQpFdEWhQcVy22gOpSELuxE51BQNPSkzMWjeCnLLDqOJvgRBEF0Cnv2CFw/n09QsdwGaCgJ0YnkFQ096RgWy0xZpgl+BEEQHcOKFc7nY7efzyeoWG4DM5UGP7qwE51EUdHQy5TlmOybqqZD0w1z3LVIaRgEQRCdwmWXlZDJ1F5LMhkDl11WimiLwoOK5TZAOctEJ1JQdJuyHI+is1jxKKcTIpIy5SwTBEF0CsPDKq65poiVK3UIgoGVK3Vcc838b+4DKA2jLcyUzNSBuBQkxMLA7lmOy6pHsRJ3l5ZFJEQRmm5ANwyIwvz3xBEEQXQ6w8PqgiiO6yFlOSC6YZCyTHQchmHEssGvqixLkCWzQI5LoU8QBEHMT6hYDkiupMEAkEmIUDQDhkEXdiJ6SqoO3UDsGvyKlRHdbIIfAPItEwRBtJGFOlgkCFQsB4QlYfRnkwAAEsGIToAVnb2x8yybNoxUQkJCNJXluDQnEgQx97xyMI/33/QkDubLUW9KLGGDRUZGRBiGgJERERs3pqlgbgEVywGxiuVMAgBlLROdQaFSdHYn45WGUaMsVwaq0BQ/giAYz4/OYOfBPEYmi1FvSiwJOlhkoarSC+NdziGzlrJcKZZjstxNzG/YqOtMUoIkxidVginLaZuyXKYbUIIgKkzkFQBkz/JLkMEiNO6a8A3LWK4qy/EoSoj5DUuVyCREyKIQm/3S2bMcj20nCGLumSqYxXJczmmdRpDBIjTumvBNvWc5Lt5QYn5TqBSdmYSEhCTEZr+sKsvmBD+ALooEQVSZLFSGgMXknNZpBBksQuOuCd/MkA2D6EDylrJsTsKLy35ZVZbN7QbookgQRJWJirJcpptoXwQZLLKQx10H9izfdttt+OEPfwhJknDSSSfhS1/6UsNj1q5di66uLoiiCEmScOeddwZ92Y6BeZb70vEa/kDMb4o1xbLAXSxf/7tXsDibwDnHHTIXm+dK/QQ/gI4pgiCqTFo2jOhuoi+/70WccuRSvOP1A5FtQxD8Dha57LJSjWcZWDjjrgMVy7///e+xbds23H333UgmkxgfH3d97C233IKBgXjuWM2YKWnoSkpIVTr346LgEfMbq8GPeZY598t7nx/F6oFs+MVypchPyRISIuUsEwRRCyuWo7qJnioo2PrcKAYyidgWy34xC+wiNm1KYc8eAStWmIXyfG/uAwLaMDZv3oxPfvKTSCZNv+7ixYvbslFxYqaooCclQ5ZYsUwXdiJ6CmrVsyxLArcKM1lQIylSi6qOhCRAFgXLs0zFMkEQjMmI0zB2TxYALFxhbHhYxVNP5TA6Oounnsp5KpTnQ9xcoGJ5165dePLJJ3HeeefhwgsvxPbt210f+/GPfxznnHMO/vu//zvIS3YcMyUNPWkZMhugsEAPIKKzsNswEpyeZVU3MFNSI1FuioqGTEICAOsGlGwYRFRc/7tX8Ms/j0W9GUQF3TAwVawUyxFda1mxTDfx3pgvQ1Babu1FF12EsbHGk8WGDRugaRqmpqbwk5/8BM8++yw2bNiAbdu2QRBqOyM3b96MwcFBjI+P42Mf+xgOO+wwvPWtb23fu4iQmZKK7lS1WKYLO9EJ5MsapIo6ayrL3vfLmWJ0y5xFVUe6YmliOctxyYgm5h8/274XRw31YO2aJVFvCgEzqpWdDiJTlicWtrLMS7O4uTjZN1oWyzfffLPr7zZv3ox169ZBEAQce+yxEEURExMTDd7kwcFBAKZNY926ddi+ffu8KZZnSyqW96ZtyjLdbRLRU1A0ZBIiBEHg9iyzaKYo9uWioiFdUZZZzjJNxSSiQtUNjOVorHKnwJIwgOgiJV+lYpmL+RI3F8iGcfLJJ+Oxxx4DAOzcuROKoqC/v7/mMfl8HrOzs9b/P/roo1izZk2Ql+0oZooqetKy7cJOB1Cc0A0D3/mfv2DneD7qTWkrRUWv2hlEvpzlqQgbaIqKbjXLVj3LdEwR0aDqBg7MUrHcKUzZiuWoJnvurozZpmLZG/Mlbi5QsTw8PIzdu3fjjDPOwMaNG3H11VdDEASMjo7i4osvBgCMj4/jggsuwFlnnYXzzjsPJ510Et71rne1ZeM7gZmSajb4kWc5lkwVFPz4qT145C/uSS5xJG/3/ooCV8E5aeWYRtHgpyEt1yrLNO6aiApVM5Vl3Yj/eX0iH//3MWkrlqOwZxmGUbVh0HnJE0GGoHQSgRzWyWQS//Zv/9bw88HBQVx//fUAgFWrVuHuu+8O8jIdi6YbyJU19KTMxAGAVLC4wb6v6aLS4pHxomArliVJRFnlUJaL0eWYFhUd6QQpy0RnoOo6NN3AZEHBQGVKaxyZLak48/rH8a+nHol1Ry6NenN8M5G32zDCPz9NFVRrEBkJY96YL3FzNMEvALmy+WXbG/w08izHCjYdbroYrwO3FUVFQzZRbZTjObFPWeNko27wozhGoj386s9jeOjFA9x/x46bsZhbMSbyCkqqjgOz8VLz6mHKMu9qWbtgSRhAfIvlKGLc/MTNdRrxyu7oMNgdZk9Ktl3Y43kALVSqynL8Dt5m5BXdmiopi3w5y1GG/tc2+JGyTLSHGx97FZIo4GQOVVU3DCt54UCujL+Zo20LAzakiGeFqROZKChIyyLSCSmSNAxWLPem5Vj2J7EYN5ZOMTIiYOPGNABv464XMqQsB2CmWC2WmQ2DiuV4wU5406X5daIo1OUVcynLxehC/2uUZYkm+BHt4bWpIndxY3/8WMwV2ZxSWS2KYYFnZ6qgYFEmgYQkRLLy9epEAaIAHNqfsVYl40SzGDeiOVQsB8BSltP2nOX4HUALGcuGUYjOs/zozoNtbzAslDVkkvY0DH4bRhQ3fnZlWRIFiAIdU0QwZksqpooqd3Fj3//jnohhKcsxP5YmC6pZLHOulrWL3RMFDPWmkU5IsVSWg8a4zYdJfH5ZOO90DpgpmSegbkrDiC2dYMO45fHdGJks4MTDBhoG+viloGjIVBRa/zaMaJVlwFSX466GEdGyZ6oS9cWrLNuK67hnLc+XYnmioGBRNoG8okXmWT50UQYQgEIMr/UrVhgYGWm8xniJcVvoFg5SlgMwW2PDoJzlOMIKwpkIbRhlVceB2TJ27J9t23MW1WrOckLiVJYrNgzdMBNfwkI3DJTUahoGUGnkieFFiegcWLHMux/Zj5m4N/jlKsVy3G88J202jLALf8Mw8OpEAav6M9yrdZ1CkBi3hW7hoGI5AKzA6k2TshxX2PeVK2uR5Wayk/4jL7fHiqHpZtFZtWFwepYL1RuHMNVl1nzEcpYBpizHWw0jouU1S1nmtGHYCssDMVeWc/NEWbY8y5zntHYwWVCQK2tY1Z+J7XlpeFjFNdcUsXKlDkEwsHKljmuu8aYML3QLBxXLAZgpqRAAZJMSeZZjiv2CGJW6zLbh13892JbnKyjmhbF2gp+3C4tuGJgqKpYVIswLUlGpFMs2ZTkpCbRaQwRiTyXBgFdVZfu+JMS/wS9fiTmNcxpGWdWRK2vozyQiKVbZmOtDF8VXWQb8x7gFmcTHLBwjIyIMQ8DIiIiNG9OxKpipWA7AbElFd0qGKAhVG0ZMD6CFiv2EOxWRb5mpPS/un8W+6WLg5ytaxXLFsywJni8ssyUVugEs6TYHMIR5QSqq5nbblWVZEmPZdU50DpZn2acNY2l3CuMxn+JXtWEEP5ZueuxVfHbLs4GfhxfWS7EoI5tpGCHfRLPYuJWL0rEulv2y0C0cVCwHwBx1XencFwABVCzHDbuPcSaiYlnRdByzvBcA8Js2qMv5ikLrR1lmFowlXaxYjlZZTogCyiodUzw8/PI49s/EWwltJ8yGwVsosga/5b0paEbt9Li4UW3wC34sPTUyhT8fyAV+Hl6sYjmbjKZYnihAEoAVfWnupun5QJQWjk6AiuUAzBRNZRkABEGoKHh0YY8T9gtoVIkYimbgb5Z1YeWiNH791+C+5QYbhiR6tjKwC9KSLvOOP0xVlynLqTrPMk3w845hGLj0589jy/a9UW9KR6AbBl6b9tngVzlmhnrTAOLd5NfONIx908VI7IYTNcpy+OeFVyeKWN6XhiyJlddfONf6LVtkHHlkFy65JI2REQH9/Xwjq4NYODoFKpYDMFNS0ZOuem5MBS9eF/brHt2Fqx/6c9SbERn2IpKlQIRNWdORkESceNhiPPHqpHVh80uh8vdZm7JswFuyBfsMqjaMiJVlugHlQtMNaLqB3DwbsuOXA7NlKJqBgWwCmm7A4LBSsGJoea9543ggF1+1Pq+0x4ZhGAb2TpciKRSnrGI5Ecm4692TBaxalAHAn10fZ7ZskfHZz6YxMSHCXD8XcPCgiM99zokUw2sAACAASURBVLvnOIiFo1OgYjkApg3DXiyLoUZttYNnX5vG73a2p7GsXTy/bwYvj4WzzGdXTqOyYai6gaQk4F2HL4aiGXjslYlAz1dg3t9ENWeZvU4r6m0YYTbXVT3L9TnL8boBjRKmnrLVhYUOs2C8biALgM8mxx47H5RlKw0joKVpsqCgpOqRpGqwVS/W4BfmNhiGgZHJAg7trxTLC6jxeNOmFBSl0S5RLnv3HA8Pqzj/fAWSZAAwIEkGzj9fiVU+MxXLAbDbMAD+PNtOoKzq2D/bOc0rB/Nl/OMd2/Hdh/8ayuvZT3hR2DAMw0BZ1SFLIv52RS+6UxJ+HXCaX8HBswx4U5XYBWkpU5bDtGFYyrLdhkE5yzyw/TlfphsMANgzZTZlrR4wixweNZKtEi7rYcpyfIvlfJsa/PZOlyrPw6fSt4OJvAIBQE/azFkO0zN8MG/Gxq20lOWF03jczFfMExv34x8noGmmMq1pAm6+OYFly+ITI0fFcgBmS1qdsuw9daBTKGs6VN2wiqSo+e4jOzFb0lAMKeJIscVDTUewdK3pBgyYEWmyJOKdrx/Ab/56MNAKhWXDSFY9y4BHZbmoQBLMpU4gZBuGWlvkA0BCJGWZB3YBJ2XZ5LWpIgTAWj7n2ZfYjUcmIaI/k4i1smxFxwU8luxpPWGvok4WFGumQUISQ72J3l2JjVu1AJXlZr5ir55jpzQMwzAL57jEyFGx7BNVN5BXNAfPcrwOoFKlQOmE7vk/jkxh63OjAPgHCPiFXTwXZZOYjsCzzE74CdE8FE88bDEmCgqe2zfj+zlZocQU2gSnDaM3nUCyUmCHGh2nNNowqGmWD0tZpmIZgBkbN9iTsm7A/NgwZFHEku4kDsQ4a7ld0XFMWQb4GyaDMllQrZv4RMie5VcnqxnLAF8fSNy57LISEonG95lMevcct1Kg4xAjR8WyT2ZL1VHXDJ7UgU6BKQ37I1ZNVN3AN7e9jKGeFN68qi+0EyH7vgayiUhsGGxIQKJSIL799f2QBASyYhTqc5ZZsezRhsHGyZp/E76yXNvgR8oyD0xZLlKxDADYM1nEIX1pa3/mUpatYlnAkq4kxmJsw8i1KTpur01ZDvu4nCyUq8VyyOeF3RMFSKKA5X2mf30hTewdHlbx3e8W0d+vAzA9xwMDOv7jP7zFxgHeFOhOj5GjYtknjsVyDJXlcocoyz95eg9eHsvhC+85HD0pOTQ/mKLrkASgLxNNsczUmWTlYt6bTuBNK/vwSBuKZTbcQ5Y4lOWigr5KNJO5fVEoy3YbRvyOqShRLM8yFcsA8Np0sZKLyz80yl4sL+2Ob7Gs6oa1ghh0gt8+u7IcsjBUoyyH3B+0e7Jg5Subrx/+yluUDA+rePHFHPbvn8X+/bPYscP75D/AOQ2jnk6PkaNi2SdsNHJ3zD3Llg0jwiXGA7Ml/OC3r+Cdrx/ASUcsrqgG4Rw4imZAlkT0peVobBiV/YXZMADgxMMX46/jeas5iZeCoiMli5AqJ3aeQmGqoKIvnbApceEqy6IA67UBU3GP2zEVJSqlYVgUFQ0HZstYsSjta39mKzEJScSSyhS/OC67F2w3ToE9yzP2YjlsZVnBoqxZLMsRKMsrF6Wtfy8kZbkd2AeaAAYEIX4xclQs+4TFjPWka0fzxu3g6QQbxn88/Fcomo4vrj0cgiCE2umsaDoSkoDetByxDaNaIP7d6n4AwDN7pn09Z0HRrIxlwG7DaL1vWjYMMXzlpKBoSMsSBMFWLItCW6aOLRTYcUOe5aq/9pDKIAkAXDn4NcpyVxK6AUzk46cu5yrNfX1pOfDxvG+6aJ1bwrzWGYZhnZsA87ygG+F4hg3DqMlYBqhY9sPwsIqnnjLV6Wuv9TcJMEo6u/2wg5lxsGHEcck4ahvG9temcf+OA7j47YdasTwJMbybDlU3kBBF9KRMG4ZhGDXF2lxT3+AHVPepks8l04KiWX5loKrUtioUDMOwbBhyBMpySdVr/MpAZYIfKcueYd9XoayFvi93GixjeUVfxhpowRcdVymWJcGKUjyQK2NJd2c3ItXDbpz6MglMBTjH5csapooqjlzWjRf3z4Z6bsiVNai6gX6bZxkwb+YlUWr2p4EZz5VRUHQrYxng6wMhGhkeVju+OK6HlGWfWMpyTYNfdMVyvqzVxPp4QdUNsPNdVJ3eL+2fBQCcc+xy62dhJiComoGEJKAvLUPVjdAi6xiKbamXETSJoqDoNVnFXm0YBUWHohkVG0Y0aRj2JAyAJvjxwr5jzQjezBV3mI3JVJaDN/gB/geTqLqBVw7mff1tUJh/namyfq9RrLnPTwxfUCZt0/sAhGoTY0kYq2zFcoIjjnM+smWLjOOP78LgoP+c5HY8R5hQsewTN89yVHeaNz72Kj7x42e4/oapyqIAjM6UQg+ZB6o2kNpBFOEFviu6ORCERQBOhZw3zU72SZsNI6iqWyhrVsYy4N2GYb8gWRejEC8GRVVHKlGrEi2k8P92YC9gCgu8yW/PVBEpWcTibNVWxNXgp9mK5e5gg0nue2EU59/yh0j6IlgSBlNl/fqWWXPfof2mdzfMc8NEvr5YDq8B2cpYdrJhLMAb0i1bZGzcmMbIiAjD8JeT3I7nCBsqln0yW1IhCkBXslbBi+pOc2SywN2tzYrlwZ4UCopunVTDxPLs2pTVMDM0Fc1AQjSVZaB6ExQWTg1+QVXdgqLVKsse0zCmKhfyvowciWe5qOgNynKyoixHcSMXR+wFzEL3Lb82ZSZhsD4IgK+4YbYlWTQLbgHAmM8VuN0TBai6EUlfRL2yrPgceW0pyxWFNUxhyLqRz1Y9y0A4yvLuySIkUbDGngN8CUPzDacBI7w5yW7P8elPd27BTMWyT2Yq0/tqmpEitGGwTm2eE1ip8ljmFQ6aiOHH98xUjqRU9zmG2OAnSwJ60+ZJOOyLWdmyYdiUZTGYqltQNGTsgz2s52v+mbILkj0NI9yc5doiH6jeOMQxhSAK7N/XQi+W90yZGcuA92PAjmbzLMuSiP5sAgd82jDY3/ntQwiC1eAXUFneO11CQhIw1FNRlkM8N1RXvcxCKkybGGssZPsQYG/wi9eqVzusD255yDw5yW6P1TShYxVmKpZ9MlNSaywYALNhRHNRZ6pyQfF+8DJVly0vBWnye3H/LNb/4DG8MMo3ea6kGkhKQs1NhyyJ0ELqdLYa/JgNI+RiuWrDqB6KkihAEvwrNwXFnw1jqmC+90WZhJUeEG7OcqOyzIr2he6/9Yr94r2QbRiGYVjKMlAd+e6rwa9y/AQZTMLsG2H3RAB2Zdk8x/m3YZjTENm5Ksxzg5tnOYzrraobNWIO4G9/ipp2WR/c8pB5cpKbPbZTp/lRseyT2ZJa09wHmEVOVP7KcatY9n6BrCrL5gUlSHzcnkrnOfN3ecWMbqsrkEKM5WHRcZYNI2RPoZMNAzBPxn4LxIYGP4/NKMyv3ZeRIQmAgLBzlhuVZXmBhf8Hxf59LeSs5amCilxZs5TlhI9lc7tnGQCWdqd8N/ix83NJDf87ydXbMHwe03unSxjq9ZdZHZTJgoKkJFixdWHezKuaXqMqA/GMjmuHfQJwHjDCm5PcakhJJ07zo2LZJzNFFd3pOmU5onHX+bJmKco8F0imLDP1JYiyPF0ptCY5G+TKmjlAw06YS2yqbtQ0+IVtw2AXnESdcpEMELpvRsc5KMstTuzsu+tJJyyfZ6jFspOyHNCSstCoUZYXcLHMkjBW9FXjKAG+cwqb7slWvZZ0J303+EVpw8iXNUhCtRndt7I8U8TynlS1WTJkz/KiTML6Lth5IYwVJza4yk4cbRjtsE8AtQNG/OYks+eQpOAqdVh0njEkJsyUVKzuytb8LKqc5XHbCbzow4bRnZLRn0kE8iyzIpO3WC6puhWVxghziU3RDKRlEdmEBEkUIvQsN34GfvYlwzAqQ0kaPcutTuxTRRW9ablmpGuYF4OiQ84y2zcoz9QbCnmWAVRXulYsYjYMHw1+dUXS0q4kDubK5g226L3AKKu6dV7kOT+3i3xZQzYpW/YJPyOvFU3H2GwZQ72pSDLYJ/LVgSSA/Rox95+noulWcc6Io7K8YoWBkZHG/dZPYdqOnGTz74vYuDFdo3h36jQ/UpZ9Ytow6mOuohl3bS+W/dgwUrKIpd1J380rQDVJgUX8eEXR9Bq/LuCvGccvzAYiCAJ6U+FP8VMcGhwB//tSWTOgG3BMw2h1cZsqKJYdpboNYSrL5gQ/O1FcmONMjQ1jAXuWWbF8SCXBIOHjnFJfFC/tTsIA/xS/cdvjI2nwq/QwJC3/P/82jM6UYAC1NoxQPctqXbEcnmdY1Q0HMSNenuUtW2TkcgDQWWOm26FShwUVyz6ZLjo0+EU07tp+Mi5weOKYwpCURSzrSWE0gA1jqo3KcpjNE+aJ0Dz5myOvo8lZdjoZ+3n/rEDK+hhKMllQrI756jZEqyyzz8Xv0vFCw74SkI9AxewUXpsqYiCbsBpdLd8+Z4OfvVhe3FXJWuYUFeyPL0ag9ufLrFj2b29jsXHLe1M2S0uYnuWyc7EchqBiu0Yw4qQss8a+iQkRZicKABgYGOjcwrQToWLZB4qmo6jqDQ1+cgfYMLjSMGwWgGXdqWDKcqVInvDhWa4/EVUbSMJRltmJrzediExZdrJh+CqWKzdLmZohLx7TMIr16o0QmldY1XRoutGgLCc8JnkQJiopywBqY+MA2zmFp8FP1yHVKcsAf7FsT9CIxrOsojsp2W48+Y+lvZWBJMsja/BT0Z9ttGGEIqg4NfiFaAMJilNjHyAgm0XkhXKchpNQseyD2crgit66Br+ocpbHcv6UC3biTkkilvUkMVlQfJ/MWZHJa8Moa0Zjgx9TLkJJw6j6Ek1lORrPcr0Nw6+qy2w4aT+e5TobRkISQ7sYsEgtN2WZpvh5wx53ttA9yytsxbLso8FP1RptGAAwluNbgbMPMokqOi6osrxvuggB5gCr6qjncN6LqumYKam1q14hNhk6N/jFZ9x1uxr72gHLeV62rBvLl3fjkkvSbUnoCAMqln0wUzIvQk45y5oe/rSx8VzZUkB4iuUaGwYb5+qzyY95lrnTMJo2+IXbvNGbljEd+gQ/c1+RRIdi2cfFyLJhJBttGK1yq+ttGGF6ltl+W5+GQZ5lPlgh1JOSF2wahqobGJ2uL5b9TPCrLZL6s0mIArjj4w7MVs/PUUXHZZOyLbPcT7FcwpLuJBKSWO0pCemYnCxW898ZYZ4XnBr8ohja5JdmucjtGFLiFbuKDAjQNAFVW0gtFB03T2AjkRttGNHcbY7nFCzvNYtdPzaMlFQtlv0mYjBFdqqgQOe4WSirDg1+ETVvRONZ1huGsgD+R36z798pOq7Z85VU01pU7wsMy7NcVZZrbRhB1LCFCPNXZpKSNYxioTE6U4RmoMaGYQ36CdDgJ4sC+rP88XEHcmUs6UoiJYsRTfCrKMtsmIiPcdd7Z0rW5D6/0Z5X3vcirn7oz9yvzQSYfoc0jFBylh0a/OIUHeeWi7xunRqqBcLZDuJMJ0bHUbHsg9miW7Ecjel/PFfGykqeKFcaRl2DHwDsn/HnW54uqkjJ5uQ9HitDWXNQlkNMw6hv8JstaaGOVla0xhMx4H/kd96yYTSmYTQ7sVsDSWpsGOF5llmkVuO4a1KWeWDWgWxCWrDK8p7JSmxc5ZzIkDmbZp0i4pZ2JbmV5bHZklUsRxUd15Wwe5b92TCYICOJAkSBv1jesX8WfxnLcb/2VN30PqBqwwgjZ9lpPwjzWq9qOu7cvtf3dcktceLBB+VQLRBe1eKoEzrcoGLZB0xZbhxKEs3SzHi+jGU9SSQkwZeybBbLph/Pz2CSoqKhpOrW2OxJDt9y2SE6LsxYHrPBjynL5sl4JkQrRtlhgiFQubD7ODkyO4M9DUMUmKrm/nz142SBSm54aMqysw3DzzCJhYyqm/tTZgEXyywdaEnFY8yQRb6bP6fGriXdSW6r2liujKXd0SjLhmEgX1YDRcfphoHRGXN6H8NPWk+urPm6WWB9MPZzU5j562zKq50wr1F/2D2Fbzz4Z+zYP+v7OYaHVTz1VA6jo7N46qkchofV0L3MrdViio6bd7SyYYTZjKQbBg7myljclUQmIXF7liXBvIh0JWV0JSVfNgwWG7d6wCyWeRIxTM9ydH4wU9mtKstAuFP8mA2jnqQk+hoewAqkTKLR2tLs82Se8xrPss/4Oj9UlWUXz3IMGmk6AYUpy0kR+fLCvMFgNgOnyaA8xVW9Zxkwm/zGOG0YY7OmDSMti9ZNYViUVB2agboGP75jaTxXhqIZlrIM8N94AECupPq6WbBu5LNReZabTfCb+9dnFjWOOTieaOZlnguajbjOZAxcd13RKuQ7ESqWfTDrVixHoCxPFhRoBrA4a56M+WwYRo2qu6w7hf0+4uPYMtnqfh/FsmY42DDCURMNw2iwYQDATIi+ZacTMeDfApF3sTO0ijWcKpj7dF86WHTc469M+FudsJTlehsGKcs8qLqphi5kZbnZVEy+6DgnG0YKE3nFc9FdUnVMFVUs7U4hJUuhK8vMltVlj47j3AZ7bByDt5/BMAzMljVfDY5WsVyX1AOEc15QdaPJBL9wlG2gcX8OipuXea4sEHY7CGBURl13tppsp/PC7GLAbFmDAAf1LgLPMstYXtKdrFwg+WwY9kJ1qY8lRqCqxK4eMMd/T3JMuHJu8Avnc6zGbJmvz25+pjpAWZZ9WiCcbBjs+ZpdWKo2DNsFSeRv8Punu57HmW8cxBfXHsH1d27KcjJGXeedAPPAZ5PSgo2Oc4tj5D2mnIrlxZUpfuN5BYM9rb2dLGZuSXcS6UT4nuW8LR1HEgVIosBtw9hXGUgyZFOWzZ4K78dkSTVz1P1E500WFPSk5BpRoTrlNaQ0jLpClaWbhLL6WSnI6wv2oLBx05s2pbBnj4AVK8xCeS6L1naMyY4KKpZ9oFZ8tg0JBiEVeXZYsbw4W7FhcE7wsy9VLutJ4fFXJri3gSVIWMVywfvBUHJq8AspW7c6Pc/83piqOhNqsezW4Odzgp+iQRLQ4LGTWinLDjYM3guiYRjIKxpeq4wa5sFNWZZD2hfmC8xWlElIkQ0lue2J3Xh5LIcrTntDJK+vWsd1sKmYqmY0CCJLuypZy7Mlb8VyZaWumoYR7neSKzNl2bzUJyX+YtlVWeY4Jtl2+LVh2G/iAVu6SUjKcv1NkyAIvqwofmC2onpRqR3EuXgNG7Jh+ID5AuvxE3wflPGcWeSYnmVOG0Zdc92ynhTGcmXuYp/lYC7pSqIrKXm2YWi6AU03HBr8wvGjsSU0ayhJJnxl2a3Bz7cNo6whk5QcbuSaj2KfKqjI2jrmAdZk6H1fZhfCfb6aRF2GkoisKSkeyrKqG3h058EIX99sWM0molOW/7hnGvc8vx+vHMxH8vpuNgzeCauqrlurXAyWX+71s2X+5qXdSaRliVtZHc+V8dzeaa6/sZOvy11P+rgJ3ztdRF9arslu5422ZNZF/8VyouHnYfVUODX4AWylovOV5XZkKYeZx9ypULHsA6dlGSBaG8biriTSvDaMuoEgy7qT0A3gIGcDy7QtdmxRJoEJjzYMdlORcomOm2vVwFKW2VCSig1jphSmZ9nZhuHHAgGYRWemzoIBtC4UnNSbpCRw+RvZhXDvNL+ybE0edPEsx2GsLAD8budBbLjzT3gpQOd6EJgHP5OUrKXvsGHF6i+eGw39tQHzmBIFNAgavD5bU1GstwXxNcmx0dhLu1JmdBxnsfijP4zgkp9u9/095stVzzJgfgb8NoxGFZ33s2TKsloRSHiYyDsXywkfKjkvmm5AN+DYVyJLQiie5bLLSokX2jFOOk4jqecSKpZ9wIL/64nEhpEvI5MwPYrcaRhanQ3D52CSqUrGcjohoT+b8DzFjxVXiYiGklQbJwTrdbMJKeQ0DLcGP//jrl2L5RZpGH11F6RWanQ97MI1W9IsJckrrIhoTDCIV84yS8rxO9wnKEol7ox51qNo8mP77T3Pj0ZSrLtZm7ij4xyW33mH5ByYLUMWBfRlZF/RcbMlDQVFx74Z/htQAMiVzf2xqiw3711wYu90scaCAVQsWhyfJdsOgF9drp8sykhynp/8wJ7fSdWVxbl/faAqFPgplp0GgfBmKbfjOeYDVCz7wGn8JWAfqRqmDcOMjQNQaSDhG0pSoyyzwSSciRjTRcVKkjCVZW/FclVZdvZ+z7UfzDoR2j6DnrQcug3DUVmW/E3wy7sVyy1UkKmCWpOEAfCPu7ZfBHnV5aJifg71Y7+r0wfjoSwzJf5gLtxJkAwWd8a8tlEUy2XVLDL3z5bx+Kv8PRCBX99l2Zx30I/mNIxC4rMFjeVKWNqdhCAI3Odn83XM7X3lYIHr7xhM0WU3TwlJRJljgp9hGNg3Xapp7gPMQpHnmJwtVd83r2+7qOqWMl67DfyFPy/s+d0Si8KwYbg1rHqhHVnKYecxdypULPvATQ2MYtz1WGWUKgD+NIy6JIpl3f4Gk0wXq4VWf4ZDWbYNRbETVnQcKwTtF8TetBxqg5+qN0bnAVXlxuAYHQ6YaRj1TUlAaxXEVG9ql9V41e3aYplvHyqpWkPcHWA20oQ5STAo7DM4yJEI004UzYy5yjBvbQRNfmVNx5tX9aEvLePnfwrfiqE4xFEClaxx3qEkUjBlmWUsA/AVHcde59UJf8Vyvr7BT+Y7pqeLKvKK5qgs89xIB1GWy6pbX8fce5ZVrZmyHI4Ng73HeiHBC+3IUg47j7lToWLZB80M/4D3OBndMPDVe3bgmT1TvrelRlmW+bJV620YizIJJCSBu1ieKlSV5f5sAhMFxVORZ3X51jfihBQX5qQa9KZlK90jDMqq3uCLBGxeXc4iMa/ojkVnKxVkqtjoC+QtUu0XwX0+lOX66X3Wdvj0b0dBtViORllWKgUeUxKjGK9c1nRkkzLe94ZlePjlsVCPJ6BqRamHd6XEyYZRtQV5tGHkylhSsbelfXiW2f7kt1mSFcsZn55l1qy7vLfes8xZLNuUZd590rWvw+fqG9drs+Y6twa/kKLrkpLQ0LTthXZkKYedx9ypULHsAzOk3FkNZL/3Qr6s4b4X9uORv4z73pbxnILFWaYsmydj3aMaWW/DEAShMpiE37PMPGWLMgkommEt/zV9fWt5qfazFAVzOX7Oo+Mc/Gi96UT4E/xk9xsv3otBQdEaMpbZ87mpIKqmY7akNdgwEqJYaXDxvj8xeJXloouyDIRzUWwXUSvL7NzErDhBEjEKioaRSX5Fk13cz3zjIMqagQd2HPC9DX4oa43Z7QBLcAjW4GcN9vBqw5gtW3FzKdk8nngKLLbfv+JTWc6VNaRk0Tqf8HqW2Sqbcz8Dhw3Dp7Ks6QY0lwY73m3wg5XF77KSHE6x7OzB94J9EIgg+BsA0o7nmA8srHbGNuGuLPMt0bHH7eMsLBglVcdMSbWUZXaBLKnOiQj1OF1UlnUnuT3LU0W1xrMMmMv63anmuxfzd7pf2OZ6ia1RNTCV5RCLZd35RJi0Lso6smj9XTLcbRjuKsiUywXRrvA7FfT1lAMqy/XNfdXtiI+yzJTD8YiUZbWSs8wbcebEj5/ag9ueGMEvP/0Orr9jKTtHLuvGmqVd+Plzozj3bw/xvR28NM0uD7HBr6homCmpWNLNekrY+VmDnPR26S0FtWEoao3fNyHxNRk2i+HzrSxzeJYVF0HFzzb4wcmqZ71+SDfxbvGiXmlHljLlMZOy7As3z7LEqSwHyaUFqurV4i6zyElzdsCXVb0htm1ZT4prip9hGJguKuiz2TAAeGryKzc7Efro2ubFqcGvNyVbiQZhUFadm0WtVQrOzyBfdkvDcFdB2ECS+ug43uEwrFDsTcv+lGXZRVkOKfy/HbDmJa/xie1G1XVIlXHXAAINJjmYVzBTUrmPQ0UzrKFNZxw9iOf3zeAvYznf28GLWwN2QhK40jlUzWjwLPOks9gzloFq0guPDUGpHFOjMyVfzZr5slaTj5yURK44yGqxGiyGz77SyFOs1w+OCrINfmg2ajoszzK7AQ5Kp2Qld8p28ELFsg/MBpImnmWPJ2R2IuBV4Rj2jGUA3B3wZa1xIMjS7hT2z5Q8N5YVVR2KZtQ0+AHwNJjEKpYdleW5X+KyPMt1DX4lVefuWve/DY3fAWCfXMfZ4OeyqtBMBZm0crLrbRh8VhD2fa7uz/hKw6gfSMJIymJscpYtG0ZEaRj2cddAMGWZFf68HlO7Enba/1oGSRRCzVx2Paa4bRiN3ueEbcWnFfbpfUC1WPaj7AL+1OVcWbOa+wDzWOLxLLtl/PL2M9ijJNuhbFvbMNeCStMGPzG0NIwgyjLQOVnJnbIdfqBi2Qeq7j51jf3eC+xE4GdqHtB4MrbUJI8Xt/qhJICpLJc1A1MeR1ZPVQoty4aRrdowvLw+0DiUBAjnRKg4XAjY+wjLiqHobg1+/J5lTTdcLTjNVBD2XTs1+AHe1W1WXK0eyOJgXuG6KBZV9wY/WRRiM8GPvefJghJqKg6DZcC3Q1lm74Vn2RyojUPszyZx4mEDuOf50dBueNyKC96Jb042DJ4xywcqYoa9wQ/g+zzLmo6Vi8wkCj/FcqOyzHdedbNBJES+G1jmnQZ4lWX32DReW40fVN29WJc5s6b9whJugtApWcmdsh1+oGLZB63HXXtVls0DUTeAMR9DDMbz9coy64D3djIuaTpSdV7UQRYf53F76v2u/Rnz7yc92TAqxapTg1sIsUBWg1+NZ9l8H9M+rBh/2D2J//vIX60biFYYhuG6SuEnPo+tKGQcM0ndVRC2vfXRcbzqNrsIvm4gC4BvxaSoNGvwC9+zXFZ1fGvby9ZSulfYZ2DA2w1ju1G16rhrIKiybL4XnjhKtk/bi4szjh7EwbyC3+3iy1wuKhqufujPns4ldtyKRE90bgAAIABJREFUiwRHeoFuVCa3uSTVeLl5Y3a2pbboOIDfhnD44i4A/hIxTGW51rPMc+PJBI16GwCvXzdXVrG4IqT4s2FE09dieZYdz9HheJYVl4ZVHjolK7lTtsMPVCz7oF3jru0nLT9NfuO5MgRUrQ9sGdvLsikbO+pkwwA4iuU6ZTmTEJGSRW82DNVZtQDCbfCzXxCryjJ/ofOL50Zx6xMj+MAtf8DDL4+1fv3KfuJoQ+GMqAKqN0mODX5NVJDZivpY35DJq26zi+Dq/gwAvn26mbIcNPx/qqBwT5J7YXQGP/3ja3jy1Umuv7MvcUfhW2bjrhOVAS9BhpJYyjLHc7B9xd6s+Xer+wEAL3P6lv98IIctz+zlHmziVlzw3HSpzYokj88zNltGUhKscwo7P5c4bj5Kqo6etIyhnpSvRIx8Wa1Jx0ly3niya1RDFr4kcqUVzZY0DFRuGniGkjTra+G9idZ0g/u8zt6jW4NfKDnLDnYgXtwykUURoXqH45zZTMWyD9zGXfN7lm3pAT6a/MZzZjYuUwB5GvzcltdYM8oBj4kY03XKsiAI5hQ/D8Uy6/R2SkEIIxbIqXmEXdj8DCYpKhoGsgkMZBP44l3P4ytbX2iqipU19xOx1VzHUSTmKxdhdxuG83Oxi1fDqGlOdbteWebxLTdVlgPECBYUDf/7hidw5/a9XH83Wjke/UwbY19nFL5lpaIsC4KATEIMNJSkaNkwgnlMU7IIUeArus3XNR/PO1HT1YbBoSxbkWEujYJeG/yWdKesfFw/Ngwzhk/Eof0Z357lbI2yLHB5lt1tGPzK8kAl4pRnf6o22LlMZOS4Cb5/x36cdf3jvm7+nPencKLjyi5DdnhwykoGDGiaEKp3OM6ZzVQs+8Dstm4ySMLjych+0hr1VSxXB5IAfA1+rLCpL5BYM4hXRYolKbA0DKAyxc/D0qmiNl5YGWFk66oOqgGzYfgZeZ1XNAz2pHDLh96ET75jNR56aQwfuOVJvDg66/h4t6EsgH3ktw8bhkux7Fb0lioFntsABq+qLlspWLEoDVHguwE0GxPdlGX/lpzn9s5gpqRyL2FXi2XOIRKKjsHK2PjxiJRlpoZmE3xDiuphCijPczh5TM3CXbJu5jy/vs3/zYOZNe1W5HpUlivHndPUtKTHwR4HbNNVAVhpLzz7VKkyZXX1QBavHMxzT/R0SsPgOZbcGux4R4fnypqV2tQuGwZvpOToTAm5ssZ1XKoOVj0Gb7HuF9UlqpaH+qxkSTIAhO8djnNmc6DbiA0bNmDnzp0AgJmZGfT09OCuu+5qeNwjjzyCTZs2Qdd1nHfeefjkJz8Z5GUjR3GIFAJ82DAC5NIC5sV4SU2x7H1ql5sFwloq9HhCY8pyry1JYVHWm7JcbqIsyyFMbWvW4OdHWS5UpuclJBEXv3013n3EYnz49qfxwIv7ceRgd+PrN5kOleD0vwMtbBiie2xWSdWRlqWGCVFVz7J3ZTkpCUhIIpZ2pzzv07phWNvgREISfcf5/bEyHXOc03vMLCTcxbKqYag3jb3TpdCn+JkDZKqd+5mExOU3rsdPGoZbekLGR+HOPnuvPQDWNqg6Ei4JM7phfk6tRgdXlWX/zcdjsyUcvqTL+rev6LhKs+SyvnSl0FNqzvnN0HQDRVWv9SzLZnScYRieJsK5KbuyJELz+FkahoFcScWiTAIC/K1UtMOqV7ZuvlSs6PP2N1YWv8N+IIt8Nwx+KWuGp7kJrbBnJQ86XI+AcLzDcc1sDlQs//u//7v1/1dffTW6uxu/AE3TcOWVV+Kmm27C4OAgzj33XKxduxZHHHFEkJeOFFfPMq8SZ7MB+LFhjM2WsXpVxvp3RvZuw3CLbZMr3d5el6qmCirSstgwNvtVD0peqZWyPNfRcQ6qQVdSgiT48ywXFc3KmQaANUu7kUm4DwFoFYsE8I38bqYsm7YW92LZ0QrjIzqONTEt7015zlpmFzG36LggqwzPvDYNgH9ICDse/YwnPrQ/iYQkhO5Zrs+EzSaDKcvsvXN5TF1uwrNJiTuZwyqWfdgwWkV7tiyWW3qWvTT4lS2/NgCkOIUIwzCsJfhDB8zz/KsTec/FMvvus/boOEmAAbPIdXpv9ZQrzexiXWGd4Pgsi6oOzQC6kzJSssjl2W5uw/Dnv+ZZqWg6lCTEcddBo+PqWbHCwMhI43uKg3c4KtryDRiGgXvvvRdnnHFGw++2b9+O1atXY9WqVUgmk1i/fj22bdvWjpeNDLdlPlEQIAreo+PYgb6iL81twzAMA+P5WhtGug02DEEQkJIlz0XCVFGx1FhGv0fPsqLpkByW/4HgTV1eUB2KVUEQ0J2SfdkwCkrjQJC0LLkqSexE7DyUxXueK6PEbB0uGbNuJ/aiorn6xs3t9LYNRVvRPdSb9qwss88n5aIs+11l0HQDz7JimVtZNredX1nWkUqIGMgmQ5/iV++zzSSkQJ7lahoGf0NWfXHjR1kuWkqgHxtGsP25mWfZiw2joGjIlTWrYRrg9yxb5wdZxOp+sw/glYPefctsEEi9DQPwPq6beabr4fksc5VVoa6UZBbLXA1+TdIwOG+i2XfGs1JhNfi5TOwNq1h2uvkLQpy9w1HRlmL5ySefxOLFi/G6172u4Xejo6MYGhqy/j04OIjR0fAC6ucCt3HXQHMFrx6mwqxalOEuls3JWkZNsZySRQgACh4u8M2Wt9JN1NB6potqw5jk/mwCBaX1YI+S6jw8AAi5wa/ugtiXSQSyYdhJyaLrxbGZasIzVpfRaiKi25Khq7Js+aa9p2Gw73N5bwqjs2VPKRRFq8HQ7Zjyt8rwl7EccmUN/ZmENe3SK749y5WpmAPZBA5yFuhBUbXalZKgynI1DYNfCazfnzIJkb9Yrjzelw3DZdke8LZa08qr2uq4ZBn4rGEa4I+Osx/Pgz0pJCWBq1hmN0rdddFxADxP8Supztc6nrQeK22HKcscx5Ta5JzGm8hR9nHz1dwzHVZ0nPPE4CDE2TscFS1tGBdddBHGxhpjsDZs2ICTTz4ZAPCLX/zCUVWejzBfoNvOyzOvnt01H9qfxa//ehC5slozbakZ45VO+8XZ6smYNdJ4sVBYy6UORVJaFjlsGEpNcx9QHW4xWVAw1MRrVXZRLQC+z9Ev7ERfv4zYm5Z9DSUpKlpNTBOApheHVqoJ4N3/Drh3rgMVz7Jh+oPrl1SLbsWyyNmwWqcsa7qBA7MlDPWmm/9dk88BMN+PH2/gH/eYqvJJRyzGz57d53pTUE9B0ayVBZ7RwED1xmNxV9JzoowbG+78E45Y2oVPn/h6T4+vj7kKrixXPMtcHlN3zzLvMeXXhmFGxzUZIe+hwKo2/7pFljU/Lg/kzJutejED8P552m1akihgVX8Gr054b1TNl83PrX4oif25W+EWw2f1M3g4R9uV5XRC4pzg1+SmpXKN8Oq/9qMsN7tpCmvc9Vwoy0B8vcNR0bIyu/nmm5v+XlVVPPjgg7jzzjsdfz84OIh9+/ZZ/x4dHcXg4CDfVnYQzQoSgM/HxJ7r0H6zmBidKeGwxV6L5dqBJIy0RwXHsmE4vI9UwrsNY7qo4rAl2Zqf2UdeNyuUyk3C1sMYRKFUJnTVn2h7Atkw6hsm3S8OahNlWRa9KzcMtwEC5vOxwtdoKCRKaqMiDlSXHnlyltn+tLzXXH7eN+2lWG5xTPlUcLa/NoVl3UkcPdSDnz27DwfzZSxvsS0AMGrzWvNGx5VU09LSn0ngpf3OKSheeXksBwN8E+eAaiETJA3DqDRdArw5y87fZSYhcfdl+Gnw03QDmuHWkOV9yI7axKualETkys3PD07KsiSa+ddelfqq/9vchtX9Wa6sakcbhsxn7yrXDZhhWP0MHopFpix3+VCWm/d1mD/z7L+2Nfh5xVr9c9mfwhh3XT/kh4iGwN/Ab3/7Wxx22GE1Vgs7xxxzDHbt2oXdu3ejXC5j69atWLt2bdCXjYxmd5qAeULkHXe9chH/EAdWLNc3e5jKMocNw1VZDuBZrjS5TbTwbDqN22aE0eCnas552aayzLf0q+lmM46zDcNPgx9/GkazdJFmSrW7DYMzDUOrPs/yHrMo3TvT2rdc35jmtB083m3GH/dM49hD+qwbSq+2iH22beZaMq4UailZxEBXEgfzCnfUl52ComGm6CcTtqIsJyXfE/zUygqauR1+ips6z3LS24qXHfbZ58qa55vGZtYmnpu/Zp5lWWo9fp2tKiztqo3iSsuS5xuw+oEgh/ZnsGeq6HmVhRXLXQl7gx/fecVN1eQ5P+WsoUcS0r5tGE2sIJ6HgPHbMJo1eoY17totN3y+sWWLjOOP7wp1SAoPgb+Be+65B+vXr6/52ejoKC6++GIAgCzL+NrXvoZPfOITOP3003HaaadhzZo1QV82MtjJ2Gl5Dqh4bTlzaVdVJp7x+JbrR10zvCrLLW0YHk7ohmFgqqjWxMYBtTaMptvQxIaREP0tvfOg6s4nod50gnvJ2C2JopmS0qzBj/dCADS3M0ii+xK0e4Mfp7KsVIvlQZuy3HK7rX3RxbPso+t833QRozMl/O2KXmty2JjHISHsOOxNy1wWBPtwl4FsAqpu+LLzAJW4rbKGWY7IvPpzUyYholDWfBXs9n2WZ4iG23klI/MPSLFvg9eVHqWuwLRj5eB7smG4F0lepuAdmC0jJYvoTnm/ea6nfsVl9UAGmm5gz5S3xtm8g7JseZY5rFVB03rYPlxVltvT4Fe1gvB9nlyeZRbv2WR8epAbYi+4BQrMJ7ZskbFxYxojI2KoQ1J4CLwlV199dcPPBgcHcf3111v/Pumkk3DSSScFfamOwGnqmx1Z9K6Isliepd0p7iEObJRq/cnYq7JsTc9zsWF4uUjnFQ2abjR4lpmy3LJYVt1tGGE0TyiVz7+e3rSMmaLq6O91wy3jOC2LOBCkwc/HtCtnzzIrFJyVZadR0wlOK0hJ1dCXYWPPJSzKJDxN8Wt20wDwDZNgPFPxKx+3ote6efPa5LdvugQB5ooP7wAJwGzkYsfEwbzS0ADrBUUzx9Hz5Etbq142z7JmmOcZt+ZJN4o1xXJwz3I26d3aZb2u7aZ/suAtX1hp5jXmiEJ0GlhkPY+XBr9cCUu7kw0WLx4bQv2Nh5WIMVHA6oGs698xmqVheFfqnafH8aw6WQp3UkJKlriabZUmK6Ds+/Sa7OGnwY/dDDjF47EbKa82EL8omnNueNRs2SJj06YU9uwRsGKFmaTh1wO9aVMKhYLzkJRO8VV33jfQ4TQbJAGwoHK+WB5WMI9yDCZhsXH1J+O0R59i6wa/1ifBqYr3q69OWe5JyZAEDzaMZsoyZ6ezH9zyK3vTMgwAuZJ3BaTgMmo61eSz9KSa+Oj25l2CdrNh8DTxAOb3aS+6vWYtN7OjsJ+zYRJeeea1aWQTEo5Y2m2N2fUaH7dvpoQl3Ul0Jfmakdhj07Jo3TDypnAwmH2Cq1iuz1mu7Iu8+cZArVfbj2e5/iacefd5vsMaZdljgVPv87VTzcH3oCxbnmXnQrFVgTZWN72PkU54b56un4Z4aGUF0us0Stbg11U37hrg8Sy72TC833hUG/wCeJZdvOOA9wZkFq3JpyybVj2nBsJmAkS7YHaoIMryXNgb2q0Euw1DCWNIileoWOaEjSh2MvwDzMfEcSJi6QE9KS5luX7UNSMje23wM9+Hk7KcTkiell6Zr5epiQxBENDnIWvZVJbdl97nXFnWnT3L3ZVEktkWTTx22Gde71k2PYpuNgz3IlESzGGkvJ7lpOuJ3d2G4dbgxxMPxZ7HfvPlNWvZrcCqbgd/jN4f90zhjct7IIsCkrKI3rTseaLevpkShnpS3Bf2kpUXLVrWD79T/NgSeknVPSdyNOQsV4qkAmeTIntdBtcEP5cbNqtw5yi82Rh2oE02DI6pmK1ylr3YMJZ0NY4OTjU5H9RTqhM0+jIJc+DThLf4uLyiQRRqexiqK1beBR3nBj/vx+RsSUNaNkUhHhuK+fwGBDRXdnn814C5L3m1Tiia7rgPAPwTe/3QLDrPC3Nlb2imBPvBbRhKJw1JoWKZk1bKcoIjqNzePDHUm+LzLOeUmtg4RsZjkkWzBr9maqidKYdR14z+bAKTLZVl5yU+gA0lmWPPssuJkFlbePyiBTcbRpPM6nrlyI4gCD5C9927ppt5DN0n+PEpJ/XPw5TlVhcmS2FvkrPMsx2zJRV/Gcvhb20zbQey3rOW98+UMNiTrjQj8RV3gHn8LGbKss+sZXtjntebNmvaGMtZrhSofuLj7Mc/l2fZpVjNcAxMYpRU3VJnvSrL9fF5dmSO/aiZZ9nLcTk2W65JwmDwNLg52ZNW92fwitdiuawhm6wdY8+W83nSMJz93949y7myiq6UWZzx3oCy6DonAcBPAzJgrlDlPB4Tqodz6lymNrHvya/No91FLaPdSnAchqRQscxJ9YLURFnmyFlmB+Jgj1ks6x7veMdzZSxxOBl7nZTVjgY/dgGrV5YBb1P8ypp77q0sidA4l955cYvkYVnXsxw2DFZcZGTvQ0la5QvzDmZxm7YFuC8ZGoaBotqqwc+7EmafwjfUm0ZJ1Vsue7aOY+S7wD+7dxq6ARy7otf62eKupCcbhmEY2DddxFAvv7LMvuekLKIvk4Ao+Ldh2K0TXgfkVG/kKw1+SX41l8HetyQKXGkYrtFxSf7CvaRqWNZjXtS9Lp0zxdQtaxzwVlw1U5ZbpbOUVB15RbOsOHb8NPjZzw+H9mc82zBy5cbc9yTnMe2WxMBjE8uVNWswip8GPzdll8eDDpjXPPZMXvcnVXd//TCU5Vb9HK1wK15HRoRAlox2K8FxGJJCxTInzZqyAL6gcnt02mBPGopmeFq2VTWzAHFSlj3nLGvmEqfTicBrcPx0E2V5USbpqcHPrVAMZYnL5UQYTFluLJZZs1Y9XvYlnqEY9TaI+ucCGj9P5olzKpYFQeAcslNbrC+vFDqtfMvVpftWCo637XhmzzQkAXjj8h7rZwPZpKdja6KgoKwZGOxJcS2ZA7XKsigIWJRJ+Ldh2JVlj/thfTZwEGWZFTR9aZnLs+zmP2c3kTyWjqKqoy+dQEoWrf4Iz6/fdHy7l5xl90bBZIsGv7JtP6jHPLd6jI5zyMJfPZDFwbzirQG7rFmKLoN9BiWPxbJrdBxHoTpbsivLfMdUMwHASjfheC/Muuj55qtJbFsYnuVW14hWuBevwSwZc6EEDw+reOqpHEZHZ/HUU7mOKpQBKpa5qXacuyuinsdd28ZmD1Witrw0+R3MKzAALO5qLFJNZdmDDaNJxnG6UuC1eh9TzLOcdlCWswlvDX5NhpIAc7vE5XYiZCd2Ls+yyjzL9WkYZpHgpES1Ug2SssgVHdds0pNbsWxPcHDCqxVE0w0omlHX4GdmLbfy4ltL964j5PnUsGf2TGHN0u6aaZhelWVmhfLlWbY1+LHXDOpZBoBpj8Uy21cSdTaMIMryokyCLw3DxbNsKcsc28ImS/alZetc04qmUV88DX4tlOVmDadW0lAAixtgL/yr22A1+XmwYuTLWk1zH8DvWXaPjvN+fs7ZtiPdRDxwQtGcx20D/oYmMWuM52K5mbLMYUXxS7Nx215wKmrteLFkODUIxkEJbjdULHPiRQ3kCny3NfgB3rKWmb1hkYtn2Sxcmp/E7KOJ62HNXq0UkOmiimxCcjyQ+zMJzJTUphcm+8S3etjFbk5PRG4NfpViuV1pGIBzokDLYRwin2+7mWfZLQmgWFfgNWyDRyuIkwd+yMpabn4D2OpzqHa9e1ME/7R3BsfZLBiA6VnOlbWWKinLhR7qTSHps3Of3Xjw+KTrsRe4Xm0YVhoGy1n2UaAy2PvuyyQ4lWWzuKiPXMz4bPBLySIWZRJtsWHwePCbDaNoVShWEzmci2XP0XEOja+rB7wnYuTKqqsNw/u4a7foOO8rf7myWi2WE+3xTNu3watnWamsGAEcNoxmxTqHrccvrZKCWmEvauEyDbSZz7hZg2A7leBOH0gCULHMTas7PZ5x1/YGN3YQe0nEYBevbKJxG9jJqJV6UWqi6lYLvObPMVVonN7HWOQha1lxmaAH8J8I/aBquuMKAfPX8dgwik1sGIDzJDilYoVx6vQGzFUKrga/JqsF7spydZCG29952YaSw9Jzb1pGNiG1tmG08ixz+CNfPJBDUdVxnK25D4BlWRpvUbzus5TlNFKyuUrkVQWr/wwGskn/DX5lHzaMuqY0dn7wEx3HbqJMGwbfsrnTvuQ3DSNV8X+3w4bBN8HPvVGwVfxaUxuGx34Q8/kbrzUr+zIQBXhKxMhVGvzs8I+7di4WrULRYxpGt63BD6gmx7RCcTlHA9Xzhdec5ZKmY2k3K5a9N826CxDeb+L9orZYdfMCK2pXruT3Gc9Vg6CdOAwkAahY5qZ+qbMeHs+y3Y/Vm5aRSYieJp5V1cDGpfO0x4tSKxsG0HrU71RRdR240F/5ebMmv1YNfgBfdBoviuYcJp+qxBzNchQZrLhpTMOoeDUdPstmSjDAP/K7qa1FdD6xFxX3C7u5Da1jsgDnYlkQBAz1pjiU5eaNPF4uis/smQIAHHdIrbJcHXndXFHaN12sFGiy5+OAUXQqln3aMGqUZY8rHNUJfubnxfa9PEexy6i1YXifAujWEJZJ8qdhsMmSfekEhw2jdjCLHZ4Cr1V0nPk8zW0Yzsqyd8+uU9GdlEX0pGRP6SBNbRgcq5/Ozb/en8euLFtCjMcbhqaCinVOa/15apWb3v5MApIoeE5XibrBr5qGEbxU8+MzDiP/OIyCvB1QscxJ/VJnPbzjrtmJQBAEDPWkPSrLlWLZQVn2GtHUrLCqFnitbRhuyjLrBHfzLRuGYTakRRjLo+jO0XGCIKA7JXM2+JnPVX9Sa6akNPPjAeY+xvP+m3qWXZZNPXmWPVwM3NS05b1pD8qye/A/2wbA20XxpQM5LO1OWikKjIGKv7+Vb9mMjUtBEATbqoC3C3ujsmz6ff002OXKGgSYF2Svg0nqV70ygYaSVG0YusFXXDntgxmr2ZDPA55OSOjLeCsOgerEy+ZT53hylt0tCC1tGI4Nft49u25L8Cm5eRoHI69oyCadG/y8/L1hGK439NWVv+bvwzAM5EpaTYMf4P0GtNl1imelwMpy57X1NG3wCyENQ2f7c/Di1I/PuB2pF80sFlu2yBgZmfuCvB10ls4dA+qzTOvhG3ddeyIY9Ji1zC7eTsqy167zZn5hpqh5sWGsWdrl+Ds2YtjtpMROMK2UUB5llZdmS2zdKW8jvxlFRWuwYADNlRQ3PyDDq6rLKGuG4zYA7kNJrKY0hxsvoJIb7lNZBkzv75/2Tjf922Yd7wCfilVUqku+dpgNo5WHmA0kAZpbaJwoKbWWFlagH8yXkU1mPD0Ho6CYS+hJSeS3YVS+a6kyBMKfZ7mahsG2x+1Yrf075+KC2TC8+p813WwwNld5EpguqtB0w9WyxHBqimPw+Gy9eJbdVjrKmvOxANSu2tVbJOpRNB2SKDS8Zy9eesMwHG0YkihAEvjU9WY3Hq3ODXlFgwHURMcB3o8p04bhdhPt3Z7FXi8hi1iUkdvS4BeKoNNiCBovw8Mql7f4sstK2LgxXaP88qReMIsF+/uREQEbN6YBmKuN5v87f76dNJAEIGWZm1bNSDJHU1b9XftgT+sla6CVssxhw3BVlr0tlU03sWG0KpZLTRQggE9N9Ivq0uAHmFnLXoPrAfPzrrdgANXP0s2z3NKGwelZdvceOxec1Rsvd/XGm2e5kjFc936W96YxVVSbqqvNIgQB/oui003gQGWlY7yFLWLfdMlqTGQqmNc0CCfPMuB9zLadfNm8+epJy95zlh3OTVmPuev1FBUdklBtdvX6GbjdAKZkEQK8Nxvak0X6MgkY8Db6u2rDcPAscyzbe7NhuCjLLWwYgLfVCnPlzfn1W1mSyhX1ut6GAVRyoj2kYVSVbf/RcaxJuqvOs+w5a1r9/9l7lyDLkrNM8Duv+4zIiIzIqiwps0qlKgnRSMP0pEG3WbchbDCgbUbAghys21jBMOxmIcvZddnspmy0GCtjMTs2aEWzSGagMTBrrLvN6IHZYEU3LRmDQBItZVFKVeU74j7PYxZ+/By/ftx///9zIzIiU/c3wyhFRpx77nm4//759+CEgvC/yzBRlo5sGgYp8Kufp+eALLs4+GdRIWHdtq4XFMXC9W+6LlsgCbBDlsXVii782919EvwA5YjxcLb2JqrpaqKVnZzlmoYRGIyp7a0hA52uqgpPF36Bn26ifTQMKkEQeD6cZZ/AD5Ajy/O1OzKa2nb0iWd0ZUkk2rb28UUBjnUcwVnmNKkeNO3VfdUwfv/ZEm8eT5x/qxos+jro3wuVbxGYJsqCjGpc10WJB6erRmwrRpbzzbjxFs2W85Z1+treMGXTMFwN3njQr1nWATNjISLse6ajKGIHJqnPb1F63bA/nq+bRbivaBrG2Qr8+rhhjATNIrXwCDXbs9r20nbDAGpLSsaCgXIWSZj8bw04dJFlZoJeWWKQuueY1jFJ5tZzOM7wrY95wS4KULk4GkbTbwR2VPoUhfqazbAUjTarH+e5upQ2dDtkWVh54+Pp37bmqudtRE0jWt8PUDEagR+JLG9Pw6CahNNVgaICDhyBJIAaSA5GqVfg104otKjrvNORfHSavUEqS/DLQzQMF7IcEvj1SfALcZY3j9cK/Dyc5S3cMIB2sqaeJarJV+dAI3n2sXwLsKOA7/H3T5aooJwwgPa7cINh7ATDlrffA1leq/S1fcGizUUdmGRJz1AStWDnUrJ0+QRhAD8wCdgUS+oGmYMGUjQMHxXJVXlZIYlAxiz70N1m18zjswzw3CB8C79hGgefSd2kToceZFnQYLpQzSiKWHoG/exqZFkqmiUBAAGgsjIa/4ORhLMcpmGcrxsGvQO7TT0PYR3GeeIUAAAgAElEQVTFefb9282b1aVrlIFdsyyuNQNZ5othqo2JRU/SId7ywuJGmsVFgrYV+Gl1ug9ZBkAKKZogiosMJSn9A/HeMMGpJJRkXbit/AgkheLjATLPbvUZjAS/Dg0jhCzzaEU+gZ8+HyoxLMRZlgh5qEVgKJhEO9Fcv9IfWTa/P5f64ar5usB4kGB/mDZJmaFal4rjanocS9Bcs5Z1BDqXkqWLcniZDHiBSUDbTI7SpNmlesK4DlRolCSRMi8qrwMBm4bhaNgl19PXKA6SGMsAjUIvkGyBn/p7OoHQ/Hz9+67iCJD1GNoiyzKB37qoCM4y3zPaRPsPxymeLtYoGQ4v66J0ijwBk4ZxfnNU64Zx9sjy83C6oBw4ziMF8Dxr1ywLq7FnIn2W+62aW69lmre8yEuM0tiJerDdMDx8OIAn8NO+pz7OMkCn+LmiXM3iqq23KWogVm4YslASFw2DQlLWhOE+wEeANo4X8gS1rie1S6H/jnMPfK4aocYCaN0wfCUR0lCLwONASIiZ3gf0aJYtVFVTP/p4Lc9WNbI84tMwXCjYZBCLqDy6dOPfLr75yLLvGRxnCduZw1zEaZEhBw30JQjqYjfLWwi7qLFN8kytCvfCb8Bww2iQZceYlDGabSCcMKoW0gHOsj6PgeWzLLDP8/F1B54xzXkcg4ZxMM5QVDz/cl9wFeAHIM6yQvdgmzoLp4tQUZznFy0FcMdZFta6rBAB8M3t3FCSslJqb7Nh1XZXIa/lxbpwNmaA6bPMoGEEBX7+Yzwloq51HY4zbyxrKJlI4qHZt/Ki9K7Yp8MUp6scVVV5Lc3Mmq+Lpskyi+J/U8g2oBAdWYJfmLNsN76hUBIuDWPRbD1vXivO5Eg1uIDRcDMt7HyLwKMJE1nuNMv8Bs++jn29lmerAjcPFbIsccPoxExnCR4EvKVdtaht27QugotOr/IS2dgj2skStsBPI6/DTErDCNkQ8qhNdLMcoGEQu2YjgWjUtBbdPAaHs6yRZQdnmemyExqjU8ZiXj+7e8PNBD+2YLT06xkkvtmm6LIVn+e44qER6iIFfgJ3lb4V8qDfprZ1uuAWxXnehg/9vGuHLAtLvzy+wThNYpQVgrzlFgFpb8EwjXE0yYJeyxpZdtWITcPwo5Btg0fQMGpkmRpsDkaZV8lPeZECsq33PlVWFYrKzz3fGyQoK756f+Fxw6CaxVXuR7YBPqoLKMElyVn2iGHCPsvMiTWALFMcy6AriGDhRC0Cj6cDzNelt/G7/2yJw3HWvENyN4yi89lqd0WOLM9rzvLeMMWqqFhInCvtbDLgN6hm6es4FDY31MJnnMVsoaCJLE8HiQqSYNEw/KJdoEZDWT7Lpdemro1flwv8hsyEVcAf2jRgcZZrgZ/TDSNi7VitC//3AOqFdOBabossUwl+ElqNySMPOTWZxRP4nSNVMJAYvE29aMjuRdcOWRZWSJRlKmQpT1Df9sprV0YMznLp3zaPlfAihCxT1nGDJEIEekDTE9fB2P8ITQZ+cRGVcgXI7ML6FOWjCrSWWSfLohnoqfLRMLIkQhz5OcvU9eOiuoBanJVVmAPuomEkcURuOXOaC9Pqy6w2kpZAlvMKk8HZcJapRWDDIT5d4eZh1/f4e88WG7sDfTjL9vc/mgzwjY9OWH9v1szgLAPKNm2YDsi/ycuuYFVCfTCrS8PYnrM8zhJ8zKSkLIzFVxQpsTCXhkGhcKq5YiDLhLBLX2OvzzIVSiKwjvNdy0ESN+i1r2ZNk+oWHcuQZWJsCNFBlpsId8NZluxUnIG9ZhNKksRIBc0yJfB7Ho5NIXR/23qRkN2Lrh2yLKwQCsZdbfpeguv7Q9wP0TDywmkbp2ucJcHJzeZXmhVFEUZZTKIfmoZxxREA0ZxHbVvlElI0qAUhLFO/dz4DUeNf6bmXepLhboHPPaEkOgnO6YbhSRDUJQklWQW4bZR1nG+XAqjRbeE2p1kDJg2D47PMFfJ4OctT2vfY9FgG+gr8Np+B4ynNk3ZVVVU1ZzlumuUTDqrqEIxKqA9mddwwBEigT4egxIb8awm0iy+uN25IB6CeZyZnOSDw8z2Py3r3MXbsPkp8hn38b44bhr7nbmQ57NMM0NZxAO9anqxyTLKkAY44QMzGOZSVUyipi0uraUNJogag4DXLlMDv/GkYeYMsnz0NY1ey2jXLwqII/4AhpAoMIm385uaxXtsf4nvPFqgIpa7iE/pv3SilLZryUhnWU6KBUZoE3DByTAcJmVk/zRJUcG85BgV+Ag/NPtVsbxECP4DXLJd1dLeLhgEoNMUr8AuiJvztb/U37uMlsZqkus1ylzqwcQ4CznKE7qCuGxcSWQ65YQiENNQiMOR7fL+OutYltbnycZZPlgX7GPo4ZaWcDPZGLbIcqrXDwWGSqWePa2fZnkOBURobGggJEuh+pyYDicBvk0t/MM5YNIx1STvMcJ9nirOsqU6+sYkSOUoWYD53mwGDK3xKumEIkWVSzxBGlk37uiiKWAmEQE2VI2gQAF+w6eIssxZfHIHfufosdx1udnUxtWuWheVCb8xqko1CnGUPF+n6/hDzdUlOjst1GFmmEJy2USea5cyNhup6uliT4j6gRTVmDgu2ZdPcXcwWVx74/KZZZkzuejHgi5oeeZBlSumtzk0hN9TCyTwW4EfqgTowx8FZppBlCWd54HBo0YshanJcB8JZmojeAIIUWgQeT1sahl0nyxynq2KjWW5RcT7P1r7+fbyWdWM6zjZpGKFyNXjjQdgG0lWLtWr8NRIoSvDzcpYloSSbyDKfhnE23uVUs5w2yLLfZ9n3DDYCN8Z18GkQhnWzSY0Ls1VRR4W7Q1VknGW/0DHMWc47VBDfeGhXo+s5g903fa+GaYxJliBLIjye0+9U1TTrtNDzXO1NA4FNu3p+tWuWheVCb8zyCans8m1b68mRiloOIcvjjEaFQ1HTQD0gBwR+lG0cYDTLLieIvB28XHXe1nH6uL57qdXbp4wmpUlU9DTLvmu5LmmBX5ZEqABw1gshT1TA7dTiog7Y58AV0Lia7gZZpmgYRHPRnkd4yze0CDycDBABTlqEdsJ47cqo+VkcRRgkEctmC1ANkAtZBmQpfu0WukHDYCHLXTqL9v6W8pb1c6GT92QJfoTALy9Z/ra28JRPw6CdVbhuRXnhp0gFfZYJKpDEZ9h3nHa3hm6WXXxlQCPLPP4/QDgWMTjLJ6uiAR50cRIIAUPXQzrl8Bp/U1AfRbzI68azW0htO8sK0T539fxqdxeEFYoo5trJuNwwgBYJolK3XJPyxjECSVkhvjCgaRg0skwFkgBtehuFLHs5y4LUtj6lB2LfhLg34CPLLRLo33p1J/jRTaLEBYLjx5klcYfKoBFEX6UxM+46LzxbxuHggBDPFOAhSKFFYBqrSdJlpaa9zW37vwFzYtefb19LjWZLeMtmoMR+/Y5xgklcW8ZjYsFKlfldQvoFXS47zI1zEXg2t8mSmzSM0C5LWAfAFPiRnGVaT+FzsQDUM5jGEdNn2Y2Sc5IlT1e5k68MKFoFJ5XSB+jo4nCWT5ddZFkj46EK6Ur0ObB8lvPN54kKzGo+PzBH+KhtZ1kue9G7d1PcujXF9et7uHVrirt3dz4Nz6N2zbKw8rIirYnaVB8eCmaLF8aMbTrtgeqrUYCGEUptU8egt8qeLMIelXqwdqHklL0SYCw6BDSM/+m3/yN++/0PWL/b+lf6kOUa4WcgekEaRubjLPt9ngGhCwRjt8CNLAc4yzWyHGpSfJZtUY3OUihYSOBnngdVHCrKkUdwZ3ss6/LxzZ2f72iSGmRZ4HXcNMuGwK8vDUMvWOXIcvtcqG1zhnuDBwDQpd8PjuBwmReIo3aH6WCUoigrcscNoN1QAH5zRdEwtFjNK/AL7JT4Fs92eUNJNLWJaPpnK7fgWP392dAwBpy461XXTYj7TrVj2vYcdFvTwaH1hALI1L+Fg1m2qZUVnHX3boo7d0a4dy9GVUW4dy/GnTujXcP8HGrXLAsrxK/k5sX7Vu2cCWWxpnmmIW5gCDEAFLJM0TBOlnkzkftKN8uucwmdQxzxeKq6Tlc5/tPfP8XXP3zK+v02FteHgsVIIt72N4eG4RQ5BgV+YXFceyxajAO40yWXAUqPfp5DAjHK3zjkC0v5Q+viWH7pa0A1/yqYpDtJ3n+2RBJHjWOGLi4KVtUiz651nBxZNjnLmjfMeQ5VyI58PHEdp6hgIMsJCw1eG7xQV+nxgEPpWNTPk+bAc71x1yEdwBkI/PQCkIq7JnftsoRnHeexTeOE5SzykmiWecmgQRoGJ+56mTeUNl3cxQLHY5jPWS6RRC1KzEGWQ3OE+jceB75v5daz9O67w40QEQCYzyO8+243EGtXZ1u7ZllYbM5y0DrOvW0+btTn/r9f5P4EP0BvmxLNMgOBCw1op6vCu82na0JQSkKxtADf5gkA7j1W2+gPmNzQPIAsR1GEKTPyesagYdgTm1Z6U81yu90r2TINecx2fZZJzrKmwwQFq340jZqcq6oivXmb82CIiThc/OPpAA9cyPKzJa7vDTre6NxmOa99ru1rOcoSTLJEyFlWn6ffn70hL/LaFd/e6gb4zXIbgZ40/58jzAs5soyyMMVMl82l1/qIkCNGSAeQcmkYhL8uQHPoV3mJIfEe+hbPdq2LsuOWpP9efQ7hmETQqzj8f0AtPADa3pMTd20jy6OM905xPIYzBroNdMW3BywaBmeOOn9k2XwOP/jAfS6+n3NqR+vg1a5ZFpZrQjKLTcPwTOyhbdO8rLAuqiCyTA3GDQ2DQpaJAS0vFYrmE5Do0t/FScOo0UQqSlpinfbdOlb7ITP0oOGjEQPhdJDgxMG3tmthIIGuGjm2HTmf7wsScVUobUt9VncLmkKEzfPj8IV9z+QgoZ+l0Hnrf2eLZklkOcPD01WHVvLB43mHggHoaGEOZ9uPavuoH76aWelr+8MUzxbhBtOFho560DDs78J1Lwht2zdiQxYNY/O51M47nAYnpAPgJvhR7ya1AFzmNAefswDLyzphlKBhULs12vrPVYMkwirgpgHw4q6pnb+yqupmuR9nOW8AJRpQ4Wo6zOficJzh2TInd8z0c+LzWVb/xhOM9i37eb5xw/1Zvp+Hakfr4NeuWRZW7iDcm8X1hG23zd2CHN+EohFKEllOmTSMkMDPcww9mU+3omEwRF3MiQ0AvvtYNcuPmAheKx7xD8R7TGRZ7wKMPQjt0LHwYDW32oaQ5UYRVo67BvaQWLS1Rwqjut5ESIKGEUoJ05UKOMvUIvDadIBFXm4grd97usDXPnyGH3vjsPP7XOX+gmqWJwP2jgcAzFY1sly/4/ujdAs3DDmybDfLXDeM0LZ9u2vGs2M0mz2uNy4n8Y2DBKqFR4jLT9AwSIpbuFmkxofG0pBoEimXm0EaK5cdhq4mjvwCtxClRe8gdN0wmDQUBmeYzVm2xqfDcYayorUALQ0k5DDEp2H8yTcfsJ1l1Dls0j7feWeJ8Xjz+47HFd55hw4y89WO1sGvXbMsLBV3zRBlMRP8ujQM9b99k5tGjGlkmbZoWjEaK0rgd0pEqZqlDfF9Ar+wXRgfWf5OjSw/nq+ZSKzmo/nPYW+QCDnLnu1nBzIXEhia/8a5BpzjpbHbZ5lqlrlUEGpyHqZ+FC6UEqYrY/AsGxpGgLMMbAru/uDr91EB+NLnrzvPnYcsb4ZomMW1PdM1t3YquDSM3OGG0UfgZ3sch8S+ukIi05Y/zbueG8iyhIYR8Ozm6CAozjIQoGGEOMsMwST1LHPcMBZ5iaFnPGoTCMNZANvwhfXY2RdZ5lDLuPzrpbWA4XDgeQI/PlXwe08X+F/+76/j3/z1R6zfV+eweQ9u387x3nsL3LxZIooq3LxZ4r33Fr0jq8+D1vGy1g5rFxY/7rpfKEnIXmmR042ZeYylR+ShEQkKgRsSyPJpjbbuBZrlNFZRz07OcgB9AWQDkaZhVFAD4DVLqGUXi4YxTPHRSXj73G5u7HKhkysGaiHxmuaINn00DCrghksFIQV+BA2DI0wEagSJwZsG6GbZDCZ5/eoYVVXhD75+Hz/2+gFuHIw7vz9MeXxjioYxZnI0dc1WOeKoPdb+MMXfP1kE/87lDTzuxVnebPxHKa2B0BXatm/HNjlneX+YIsIZ0DCYY0oRaJapFLwQEDDMwotwitLCSQGkaFGmcHgC/7sf+h5ZQlMQGlDF6bMsoWFsv1Ng+2/ryGtqEcsR+EloGPp6PBbsMq2LsqMNun07790c23XjRoV797rfry+t42WuHbIsrDOLu/bY4mSJSl0KI8u0dRzg3+7kCPxGaYxVUTm36k4tTiVVPmcOyrhfF3eLDVA0DO37zOEt660zElke8ra/OQl+duIWh4bRiOvOyGbJHti1g4MPgdJ/o843TIEgaRjElnXovAFeAAKHhtGGhKhn5C8+eIIPnizw8194zfn7Q6YnLdUsh2hRds3WaoLUfP4rXBqGwxt4kChXGcnW79LyOOa7Yei/8zjMMDzkm3OwnsskjnBllDJpGGfgs8ywdfQhsyxkOXA9KWSZYx1HWUJyd4uCmQIBN4zThobhSPBjPE8cgV+IN63LtvOTIMthGgZvjtL3lBPb3p5DWPy8TZ01reNlrl2zLCwVd30WyLJ/MJwMEu+2aatUp2kYAKNZJgYBfXxXk3PS0DDCGxOTQeIV+FHb/wA/mvZkmePhbI0f/eQVADybrpyBLEtoGEkceQfVYZqgrDYbTg4fTvPZOZNB464S4iwb93NdVKhAU3q4VBAKyRom/oaTE6aizyPIm2Yhy6pZ/rimYfzrr93HdJDgv/3sNefvD7g0jDXRLDNDPXTNV0VDnwDUou0pJ5DD4eAQRRHGg0QUSmKn56mAorNAlmUCP/t5OhhneBKIKFZUFHoBGuLq6uNsgyzTu3ZhHjz1XoRSMauqIu1FuZaUYZSeBjNaGkbfBL9ws8oFVOzvwmmW2QI/JlVQv1fPlnxkmeNBv02dNa3jZa4dDUNYyjqOsXUeHIj8g+Eo9SfwaYSIQpZD9nMNDYNUbLdbpjZiqoM6psMwsjwdJF4aBieIgrNqv1eL+/7rT17B//Oth6xtc7bAb1WgqirStWO+LjDOYu/v6IWHKYJj2SI1KYZn5IYRRxvPhL3d7jwHJhWECmIYpDEezkICP06zzEOWqUXg4ThDHKkF1WxV4N9+4yP87OdeDe4KhMpuMDeOEYift2tmvXP7w7RxoKGEvT7x8STzL75dZYsVdbMfeg98dpi69JjFEvg53BwORhkeLwLIcogmx4xvDwn8KJ9lSuwKhNNRAZpWFeIsN4tgwmcZaPUC/nOgRdh6fPY9Fz5ty7DetSyrCjHjeToTn+V804avFYxSAj9Gs86wtDTPAQCeCZBlKhHzrOosaR0vc+2QZWEFB2OmdVyj9HWgF5OBf9u2oWEwOMu+rVcWDUMnCToG5JkAWR5niZNSEvIiBcLbfLq0uO8f3jgAAF6zzBH4DVVqWKhZWqz9AQCAO0SARcOQJPgxBYPmc2kLuZx/w4zcXhI7BQMCFeZErwM8P1WOI0hSR14/nK3wb7/xEebrEj//ha6wTxdb4EcsQEep+v7c7dqZ5WG+Xy9KQyI/n62l7x30lS1WHNXuCUEHh4DAL4mjGgjgLT7sa3k4pmkYVVXVFmEB6gBT4Bei27loGMo3nG6WOc9U40NPCPx8DXcooTWzFuy+Cgdw0XOdBlVcbhgALVDUnw8wOMscn2WLzjBKYwzTmIcsh0TTzPda3y9OdL2uVd4NGtrVxdTuLggrD5nec2kYud9neEzEVS841nEhGgZD4KcbKNf2MdcNA1CNvwtZDnmRAryIY6C1jfvc9T0MkojFWebQIPT3C1Ex5g703SzX5MYRGDb8dw4NowdnmUJD23MIN+x5qbjtvsl5mEZefiWXsyxJ8AtROo6nKsXvX3/9Pt64Om7oO67ibhnTAj++sA1QyLLZLO8xI6/z0r3rRS2+XeWyjgP8zZkunx2mWaF0UfMc7OfyIOAq0giyGIKwEKUlL6pOQI1ZPhpGocNpenrY66Lei9bNgp4jzoKzvI215QmBLKvz5DXL2/CmzWOZ1yOKomDkdQuo0Nz1gk3DUNeD42zTnMNzQJZ3xatdsywsdtw1A1mmVOPbWMeNAo4ay1z5Z1KTQUPDcDQKEoGfomF0B4eQqwggaJYfzfHq3gDjLMHVyYDHWW5oGDSyDCDotTxf+wMAgHb72ZwcOI2dHqS50bRZIOTFTpuivIGbc9BbtkTDvgohWRRnWWAdF3oW1gS6a9bRJMNf3X+Gv7j3BD/3+evkNRumMYqKgawTDQq1S+Oq+cqiYdTCVWr7VidCunZKxpl7weqrZsehSfDTC2f6GJxnesxs3F3I8sEoI8VRHM/uLImUx3BgWMnLkuGz3D0IhzevkWWftSewHQ2j3TFyj8/6naYEguocwtZxgL/pPl3miNCdJzhuHvrzzc9x1SDlzREumlgoxa+1jgvFXcsEfhJkeR3QSO3q+dXuLghKowasuGsGZ5nyI/VNTBxkmSPwGyR+jq06fj2geZDlSZaQfLP2XDzI8hkK/L77eIHXryrbr6NJJqJhUCIereIOpfjNPRZ9ulyTQ85AtvWE20fA4qrU8pgNbdea50edA9Uo6p+H3DB4C6ewyDACfU8BhSx/dLJCHAH//Y/4KRiAuWgMfzbgXsSO0h7IssVZBuhFGyVY5aK5ujo+yym9+NYV4iyrc3FbSdq18NAwlnnpvY6chVfKpBX5UHpdPt/vkNc00F5PioZAeeGncYQI/mY3tAjmcpbX9e6nr0J6htOaTmTPE6aGg/x8pmOQipoP7+TalJbDcYbHBGe5tY7bngMPbNEs72gYl6J2d0FQzbbQGcRdU7w2CgnihZLQkxvHiaKhYbiQ5WXBEvcBNbLss47jNHdMZPn1Q9UsH08HzGZZowYEsqxDVQLIsksEaVaz7WhcB57Aj7fw0sfjXM8NZHnNEPgxmotloEGgfJY5E6L+dxa1KaUXgUBrH/ePPnXVGXFtFhcFoygt4waZ5SHLNmeZQ8NolfsezvI2cdeZf5fJrBBnGVBiw9B1yIsSRVl1dBkHAQcDjmiXs/grqxoUIWkYbheEdsFA71YA9PNAIctRFJGWhsvAe63PLbRjFdLnhMaGk2XupOrpd4TvCBIOAeMk5trUmMNxhieEYJQDaPSxjjtZ5sHmXpfeMdzVxdeuWRYUhxPHfXkVEuh+CSYDwg1DI8tUsxxQnYfU2gBN5ThdFSy+MtBylm2OIAcJ5SidT5Y5Hs3XTbOskGUODaNCBIAahxoaRghZXhek4FJfS7PhYrlXNNucDIFfwF9WH88p8CMafQ5nuWmufIlh9cTu4olywlkAHjeRswgEWvu4n3ck9tnVbHkzUG3Ak7jGbDZ1zde2wC/cLFMJjtR44qplXmzEHLcaiO05yyOG2HDhWXgcBBwMWL68DZjh/y45Y9cp8wj8ZOJp/3UIjQ+USDBkL9ruWPXf/QTascHnN326KjqBJICEhqH+naILcmhi+lj2PTkM0TDKMKAiibvW37dCWAcDtNSq0Dx5kXX3bopbt6a4fn0Pt25Ncffuy2uw9vJ+s3MoVkSxFj0EX14/H4wU+K1VShf1AnMEfqEXsEWWXc1yznLCABSSVFbo2F5xGnaOA4J2wtA0DMVZXgdtiXRsOYVCNjSMoMBPTsNg+SwLE/xC19Mv8GPQMIjnOSQUHNZuCi6HAU7qnj6PUDwvZV9n1j/99BG+/eAUP/kZt7eyWfo9cNGRzFrUFBDXAlgfg9OwVlWFmc1ZbmgYRLNc+p8nqRuGpkDod4PaZdo4BwYNY5IlwRQ+33N5WKeu+ezjWDQMpmAVCDfLrmZTZMtJ0jDo92JAIcuB97H1We6/+2kex8tZXuXN7pxZI2azrAElaozOAiJDXVpQb9bhOMWzRe711OZQ9VypqL4ykfSnixxXRhn5+xwR+EXW3bsp7twZYT5X53fvXoQ7d0YAXk6f5su7ZLmExWlwkmbrnIMsU82yP5SEQjEBNVBHUFxaV3HS81x2Z7qkyDLQjdvlNOxZHAcpCN+1muWjSYairIJelj5PWrO4Aj82DSOX0jB4CJA6XhiBsFEQVrPM8HoOuas0iWOO55GzAFX/HtWaAfo8Qs81AHz6eIL/9Z99joVCU+du1nLtp4CEaFFmLfISFbDBWR7UNlcU11G/J34rSjey7yrbiYJ7/kviHHSNsjDK7XsuD0YaWd6ChsEAM3IGougT+HE4yxxkNeQSM0hiL2c59F6H3DR0UbufgEkT87hheOh6HBqK+vxwel0jqCe+i7Lz646PB6MMFYBnvsUXy42Dz1k2F0ccRwwuRe2i6t13h02jrGs+j/DuuzS17UWty3kXLmlxBuMoipAweEzLnHbDyMvK2SQt1gUZSKLPgRIJchA4moaRs5wwAKNZXtnNcoUBsV0L8MQT36lt424ejAAAx02cMY1eudLO7JoIrONIGoYDneQsvFoULNxk8QR+m44SSwalhyfwC0zOBJWBw/FU56H5kUSznNPJaX1qyNgyB9S19F1HiRuGfk/s92t/mLI4y64xZZwlKMpKNKmb91LCWQ4hgT4ryc3Pdz+XLWfZR8PghVgA2yPLg5DAj0HDoJtl2jOc4iyHqHp86zimG4Zn4aGQZX+zHOIsc4KrGqoaMd+uPdfyMPA8sQR+As6yeb+eBpIoAV6zfpH1wQfu8/L9/EWvXbMsKE6QBcB7gdZF6W0WxwM/55iDLAM0grM1DWPp5qK5alJvw5kTpPblZXGWA3SWe4/nuL4/bCb0o6kaAEO8ZY7KOI4iTAdJ4xfqqrKOlqWQ5VHaj7McRxEbuVgRiy9dqWXgrxdCLOs4jsDPN7FrJMuFLDOQuI3zCNBBOMiypCT8St91lLhh6HfW1SyTNAxiy1ij1FwqxnMq5Y4AACAASURBVHJtNcsNjWQ7QRignX76iSUPaws9nyiL8yxxrD15nOXI6cKwDOyyAG7Br10hhJriLFPR6+rceTSM0AI8RGnxc5Z5DjMhZBvgLeZ9YslQ5DXlMKOrT9w1ADxlIcvhxd9F1o0b7mvu+/mLXpfzLlzS4qhj9b9zVu1eGkY9yLkQGA6yDNC8Zzv601XUgD5bF07EwFWTrPtduNtLGaNR/O6jeUPBABRnGQAeBIJJ1h6eml3TQUI2Kct625ykYTiQJJllGtM6LnBPs1hRGfR2PEvgF4dRKD6y7BL4Ma8Dg5vIWQRKa+hY6LjK5QusiyuQA9r3xH6e9oYpSS2iqAN68X0aEKrqWubFxnfhhqqsC38wjXms+bor+N34fI/jT5rEmA6SIA0j1NwA9LY9l7OsjrP5PVjIMuOZohJeAR4NwzdPNAK/0AIwsADPAgi13w2DuwAN0zA4lBKfLiLULK/LEkkckdoXOxWVqmVeNs+0j/rhOu/Liiy/884S4/Hmdx+PK7zzzvKCzuh8a9csC6oZwBjb3Sxk2XOcSYMsO2gYAmTZS8Mowul5UaSiae3Vf1VVOPUMgq7SyPKpaZvGmFAAHaJBD6jfeTTH64ej5n8fT9QA+ChAw8gD4TK69gKInkYCx8Q9cXGW+Qsvntf0ksNZrj+rKDebZV4oyRnQMDyc5SQQkKPOI9y0cxaB0pJYx/kEVePGDSWM7DY0DKtZ3h8lATcMf9rYUf1OPDwNT9DqPMuNRpXri8tFlqvAsajniQqS4Pg8cxxm2phjmoahPnPze3AEq5wEu5Ulsux8PknDqK+fZ0zKGA0mEF6AN3oGx9hQlBXm69Ip8OO+UzmTWqZ/11e+dNMDLRj1NcsMqp7UOu7V2qqS47WcM57ni6zbt3O8994CN2+WiKIKN2+WeO+9l1PcB+zcMETF5RBxXiBq1a6RPheNYhlIi9NFbXdyPI4B91bfMi9RVOC7YejGf9UVtwUdEGKVnlaU7ujZp4s1nizyxjYOUJNpEoVpGCp0IHwN9oZpE+/tKn2PKHQ2jiIMkqiDLIdQC4AvIOFylgH93dWkmiX0Oahz5E1GIV9XFxLGQY8AXpOzLCocMhdx3OIq910hGrq4giagpUq4aBhazOoqamy6VlvlfcyIgQe6KHkaR0iisJsHZ9t8bFBCfO8M1ewpb1z3ZMyiYUgEfoEEP6C7eGsafYZbEbV4WgUW88M09u40hEKC0vqdpprloqxQVOHocMA9NuhFn0vgx32nVgUdDGOeA0dT4UOWvTsVDECFA+iY53FllCJLIpbAjwvOXWTdvp2/tM2xXZf3LlzC4hD+ge05yxOiWV5YFmy+GhGOGlw/2pFDJHjiESD5quFLGg3n0rPSt6vxrPZcS908vGHQMOIowuFkgAcMgR8VLqNrb0jTMDT6T9EwALWdb1vHcT7flxRmF4uzbFEZ7O126hyoyYibGOZCwjjOLOoceMjy2dMweGIkioYR1yESHOu4Zqdi4KBhUAl+DXWgew59mmVzjImiqB4Ltt82D6WLqs/3N3sHo5SgYYQRYY5QlGMZ5hMK6mecbnTD7iIhShHJWa6FliH6wIpI8NvWB15TflzI8oD5TrEckxjWlvr87AXMKEswTGNS4MeZ64sKrJARPd7uD1MWsqyf59A8uavnU7tmWVBcZDljrDaXpM+yf0JZrEseskxMzlw/WhcN47RuHLkJfrqpNmkYHD9WICwu004YJmcZqINJQpxlxpYxoAZ7ClleMGgYgJrcFhtuGLwmccDgvwN6ARRGqYEWOaOoA/bfUTQMKm0MMII9XM0y8z40Eb2B8+A0/5JqmmWOxzPJU+2+S6469dAwroyUG4aP60vReq5OBoij/sgyUC+cQ80NY1xpd5r816IJ1XA8mwfjjEQCgVDcddi7nOuGAbhoGHVjFngWgLAbBvU9KM7yYh1+rwcen+j288NzXftOdo+j7TZd84RePHJ9lqniWFsum+/i3qnw+XbnjPQ8zuJLl959OhhlvGZZL7wCDfuunk/t7oKgWpPw8+Usjz12a4DivQ4ZyPI4S7yTMxfNcyHLejLn0jCmzXdpB4fQtr2ukI/nvUcLRABuHDia5RCy7AjIcBWfs0zfk1EWd3yWufQDDieOg+rZTgCLnLfwCiUphizoGiTJcQzOhAjwuIncRaCkGp/loDcwTY9yvUuumhPWcUVZed/pRtzmaPCSOMLVyQAPTrjNcnfHYZTGZ+aGAYSQZf/4cGWYep0EOKgux5e38azuEZvNoZhxmuV1YIwOhZKEdC0q5Idu1gGes4gUWQZoZFyXzGeZtpQE3PfkysgvnF2XJYuzDNDuKrr0+LQ/8j/D9ucDdCLmrp5f7ZplQTUpWaEXKInCWfXExD7J/Nt0bGT5DGgYQwca1nDRmDSMLImRxhFmBpJErfQ3/5beYvvO4zleuzLsfJejyQCPQpzlomRylnk0jBA1xp4c1iWThnFOnGWApg5snEPgeV7lSqTnu54kDYPJWWZZRF2gdVzoWnKaTcDgLDvcMAC/MCgPLOSvTQdsZNnFv6YEw7rWjN0Nk7PsK6pZpgJW2hTDMHWAtI4TuGHYi8gGCAicQxLRvtVBGgZBz1ow6FXDlF4Ac1D6FsxwIMsEZ1l/Psc6ju2zzEDJXfdklPoXsesirGtJrN06qvQYQTXoZjW+4Ttk+VLU7i4IKmcMIMD2nOURMaEscp51HOWzLKFh2E1CCDFw1XSQbCDLemALDeihie27j+a4eTju/Pyo5ixT9lQcpbM69xSrovIrzz3NjV3DdBPpDyFHukKori5Oo5haKAybsxxHJCdwEfjshobhRZb5zXLIIuqsaRgRc8s41CyPGTQGQCGuSRx10FEdee0TBlFx14CsWXbRc6idKl2chU8LBIQ5yy5QYDLwB6yIaBisUBKaBmF+ZnPuRYmY4e4yypIADSMs8KM4y8FduyQmfZYblJ5Y/JCcZU3XI5Dl0OIrdA0AJj2r+S6OZjnzN+05Y/fRBiCoWhUlRmmiAoYY1nHcfuOi6+7dFLduTXH9+h5u3Zri7t2X0zfict+FS1bcrHaVlNZfaewT+FV1AAbHOs7ns1yUFfIybB0H0DQMrsBP/67Z+LcCPyay7BnUv/t4viHu03U0ybDMSxK9WhclW+AHACcej1qOdRzQXXhwJgKA59mtjxcUTFpOALZFmPfvAgK/EPeZRpaZ16GhYdDncR4TC6dZXgWuATUpmzVbFZhkSccyTDfLJz5kOeDgsDWynMZBKgpn4aPHLurdXKz9OxUUkCChYVDvFAdZTpvFW1fgN0j8lm+6bA2DXatAwzuon0kXIKDoVdtxljm6knbnr3sOJ4EdSC4Ngz9H9EWW/U27miO2m6PMMpFlDg1jxew3LrLu3k1x584I9+7FqKoI9+7FuHNn9FI2zLtmWVCtwC+M4FErzRACkiVuq6ZVUaECHU+sq4243RxE1sTAYZdLlEQJN6hzMfnXoXQqXa14ozsQPp6v8dSyjdPVpPgRvrIKNeDQMOomxeNE0JeGwVFaA2EnCn2sMmDzBJiBDCYNI3wfQw37Kqcb9VDcNQtZ1kEKHoRbsgiUFmdip6zjAHq716zZqnAuRPdGAWQ54Nt9vKeoSUUAAdPpmi6BX5CzzHBkoTzkddluHBt/T4ifOTQMyhtYFye5zYcsh5pcXWrxTNEw6PFJf4ZrbOAhyyHOcniuo8ZnyjoO6LoDuYpl3cYITaJ45CNix4Qj8LNF01SZzfLJsgi+i9zwrousd98dYj7fvEbzeYR33x1e0BmdX13eu3AJK7TVqStEw1gGEJAoijAedCcnPdnyrOPck0oomtg+RhdZprfXXKVoGD18lgnxxj2PEwagaBgA7bXM2WID2u/pSz/jCvzsbUdOYwHUjeoZDao2rYW7SzEIiAyp5gageb/rvHRuj9oVSvCTLAKlpfiV/samqqowZzmjkURd83XhpPSEaBh6y9a3W3JtOkBZIcjl91EgRinDDSMQYgEYAj/CYYa6lpRAkBNwwxGEFYRYUtfAgygumS43Ni3LriCyTASLLNZhetUgQMNox5Qwuu66lpqG4RsXWbs1LIGff9HQHIewKh0TXHyWwI/xPAGbY8T+SIE5Ia9lrvvWRdYHH7jPzffzF7l2zbKgmod3S59lTnMzzpLOhNIEYDApFOpvbGsjfrPsWv3PVgXSOBJ5P9o0jPYcQgORH038jvZYdiDLx02z7EeW1wKBHwCvyG+xLhBHYS9Mm6PIdePIApQegL8AspXbXM5yiFYU4gpTiWEc+oh5DN95SBaB0gpN7Cy7MCZn+XRVdDyWAWA/8ByGeLZcr2WfuI7T7HOaG4pG0Z6D/7l0hRw1n5+HP7/lmHJoGGGhYMc6jkkFCj9T9GJ6QCxAQ4tXQO3UUHHXHGQ5jiIkHj3D6arAdJB4vZ751nFMGgS5mK8pJS5kmVi0cAR+GZOzbL5XV/TCNyDya3eLLm+bduOG+3v7fv4i11bEki9/+cv49re/DQB49uwZ9vf38Xu/93ud3/upn/opTKdTxHGMJEnwu7/7u9t87IVVaKtTV0iU1djyBARBNnrS+I+yrOPUse1VMydhSpfTZ7keBEOcvM1zSfCRYVvFsSUCaDTx3uM54gj45MGo829XdbwvgaLxQ0nCNIyxg2NqV8cNo3BHwdoVcqLQxwIYIS9On2Umuh0IJQmJqpLIF3fNpGEEuIGSRaC0QlvGocQ0QHMjuchy9zhBgV+AOrB1s0z4trfnUAbHFb3QpgV+YWTZ1WznZXi3hsMxlfgsd2gYTMFqiMMeslSkdms47/UgiXC6ZMxRjDHadS1n9Tzhq1Ea4+MzcMNofY77OXtQQvi8rLDHHVMZPuwAMMwS7NeUqhBvmeN1fdH1zjtL3Lkz2qBijMcV3nlneYFndT61VbP8G7/xG81/f+UrX8He3p73d7/61a/i6Ohom4+78NIvXdhnmUaWQyEOQM3ztRvdJi2OwVn2pERJmopRphq8sqoahOB0lbNt43R1aBhsgR/FWc6xP0yd3+NoEuYss0NJAojenIjtNWtkbeWv8hLZmOEvTFhENccScOmBfpzlGREiwZqc07hBeMxi+00HuImSRaC0hil9DyirM11UoqZZs1WB1650F4BpEmOcxXi28IuRAP8zcG2vbpYDXst6jLEFYiw3DCa1yNYw2LUgnstJ49veTyzKsRrjcJa9PstMl5thGpPXICRW1c+5awHKa5bpZ5oTHQ74gaHTVU6KwIcBzjagdypCoSQMS0myWU6wLpTewV4ccQR+bcosb/dvE1mmHTFy5oLlIktFXS/w7rtDfPBBhBs3VKP8MkZgn4lksaoq/NEf/RG++tWvnsXhLm2tywoRgNBCL40jkrzPQQInjhXvouET8kJJAIdIkDkImp+zMrb1TpcFpkPZYzMZpJs0DEZzAdBbbNRgnCYxDkbpmXKWTzwT23xdsBYvnbhrpsBQITehJiVMAwDabWV9PSWhJHnpH/xWedmgJb7yTc7cUJJm4eR5r84VWU5irxsKwGuWx0w3DOp52icCckJoqKYmbUPDsBfOdlF2mGaNswRz4lpQzyXFWeaIRZMIiBDyWQ5zln3UIjaynCYBmhgtVqWCfhaBgBwgLBxuFuCB+5l5xOxqB9I/JowCuzVlpYSmwfsZR4hAL34ojVAbEFMgtc43LyqG8xUvlMRczF8Z057pulZMcO6i6/bt/KVsju06k7vw53/+5zg+Psabb77p/Z1f+7Vfwy/+4i/id37nd87iIy+k8hq5CG25p4G46xWDi+RSny8a5wUeKgwA89xDw2BMaqOGytGeRx9kueOGwQ0lIVLbfK4Buo4mgzBnmUPDGIQ4y2VQ3AeoQXldVM0iiqP0BtSkGBqI2ciysWXIEaWZfxeyjgtNzsPUnTjGDSXxbXs3xxEsAqUV4lcumneK2nZW7jTUuACoJsP3XO8R6XXrsiL9fQepWkA+CDTLekE+tMYYvXD2XYc8YIdp1njQ1WOYtVz7n8sJRcNgvFNRFCEN0Ip4NAw/sswZWzmcZTLuWjvMeJHlkHVc5PWOB3jWcYAeG9yc5TCyTAscgTAFIYqi2tmDBqeGqdvOz6ftAXgCv4YG0oOzHGqW9TvNmad2df4VhAh/5Vd+BR9//HHn51/+8pfx0z/90wCAP/iDP8DP/dzPeY/x27/927h+/ToePHiAX/3VX8Vbb72FH//xH9/itM+v7j9boqoq51YoJ34TqEVZFLLMmNgngwTfe7rJ++mHLG8j8IuNz1XUhtNV0bhNcGs6SJCXVbNFuSpKJHEUNO5PCX7h6arAJPM/vlcnWRBZ5qzY0yTGKI1pGgbjfpjBHOM4YT9LoUYV4Lth6ImnKEsWGtr+3XYCP6CmYZxBKImPGyhZBEorNLHzaBj14nVdYp/4voqz7H6u94cp6YYRep6OGV7LCwJZBpQGwrU4lNhcUemigEL5Dsfua0AK/ATj87YCPx9FbFlUOGSACaFExBA9aWSMJ2bpwBYOsrytdZz+dx9nWdPhXBVK8NP3gOcYRN/PZe5fRPm0PYC2juMBEEERdtG+V2w3DCat6SLr7t30B4KCATCa5d/6rd8i/z3Pc/zxH/8xKdq7fv06AOD4+Bg/8zM/g7/8y7+8tM3y//Hv/hbzdYH/83/40c6/cdHIUNx1E/dMTOxOgd9aiwR4E5L6m65XM8AV+NXHMAa101WB1w9lyHLLMywaM33O57db725keZ+ggxxNBvjGRyfOfyu0LzFzxb43THFKCvz4SL9uNvhNYtgNgysEMdOmTMFJ+Bxo+7rFugh+F18IApfn6nMfaI5zrgK/QGPD5CwDauG57xl2y6rCfF1iMvDQMEapl3Ps4lzadW06CCLLSw9K3p4/jexzdktcFDP7HHzIKOWmIVl4UeMzj7PsoWGw3TD8NISyUg0vtfDTn2HfD33M0O7jMKVpGFzRsE/8G9qB1AvQqqqciC+3WQfCgAIlInbNcc3fsRL8uDSMVgSs/4+DLF9mcZ8OJNHivnv3Ity5MwKweCkb5q1nlj/7sz/DW2+9hddee83577PZDCcnJ81//+mf/ik++9nPbvux51ZFWeGRZ/ueyzPlWsdRDaPbDYNvHTf2+Cw329VMgR/Qin6AmosmCCQBuluna4ZwA6CV67PAeRxP/cgyN1xG194wIX2WOTQMW70uSvAL0TCYKLE5sIuQ5Tgm6QMcOocPneXyXDXX1MtZzvmLQGmFkeXwe6n/jXLEWDQCXj8Ng3LDCDbLe2FkmXLDANxcYfX5/OfJly6qa5GXXkBAu2m4kGUutclnd6aLQ8Pw7XRwI9cpZJVjGeajYXCcWfSxaWSZh+z6BX40Z5ly8wBob2TuOehaEvdkRCLLJbm7ABgABNcNoz4PFXkd9lnmBFddVP0gBZIAZ9As/+Ef/iG+9KUvbfzs/v37+PVf/3UAwIMHD/DLv/zL+IVf+AX80i/9En7yJ38SX/ziF7f92HMrSvWdM8VIYV/a8EBEIcu8UBIPDaOHwM90cThd5iT9wVUmsqzPgdek6QnJo7YmrsPRZICTZeEcjNstPj6y7LeOK1gc8qGFYEgoPQoJp8Q4vImtpbW0NAxe3DWN3KwYQQyDpMtZDsW+m6W5ib6mfXmuyHLIOo6PLFOI6qxekPm4npTAj+PuoiOvXRHJuryhJM1OlQ/Z52+bh2kYNAfe9/dsGkZA3MYR+MVRhDTupuBxI9dHqT+umrPw8LlhcBfBg0AqJzvoyLHwqKoqCKroHS3fe9VwprnWlpT7FLF7NSaeaw6o07phBJply2VmnxF5zV38XVT5gkfu3Yteyrjrrb/RV77ylc7Prl+/jt/8zd8EALz++uv4/d///W0/5rkVZWvEMSkHGHHXjIZ1nKmEJXN7dSFocHyT81KAANkCv7yssMhLObJcT/4aneWmXLU2Tw5keU0LSLTX8qPZqsM/bywAmav2vUHqdUPgIsuN6nqtm2WuC0SLrvu2ZSUTG6DvI3+XIktiLxKnhYJBjqTDfk0a50o1Oecq8MvoLWMfdcGshhtJNN2z+tnwNssjhSy7zoNDwzieDrAuKjxd5DgYu/mkvmarPX/32Mixw2yONQhzlqnxaeL5e4l3OWkdV1ZqJyMg5HZFRkus4wB3gEjr3kA0y3rXz/r8hcf6r3vuMcrK/9xwaTWud3KZlyjKigQzQsjymrFgMc8h5LPsRZZT/3OdlxxkWTs2BTjL1nt1MErxNGAdx138XVTduFHh3j3X/Xk56RiX905cUFEm5VwOkaZh+BAcji2PnjDN7SH931wHg8xh/i+hYbQCP/U3sybquh8NY97QMITeutbCo6qqoOm9FiE+cFBquOEyuvaGydZuGEOj2dCcac7CK5RcB/DT6zJjy5DT4LV/50eW9XcJHWeYdKkMUtN9aruVS0XpU6M0RgW/l6tPFLd5DLeGwCxNLfA1GfvDFGXl5+uGriMnmMRPw6CRZS7HFaABCc7iS3nQu5HAkNUX0O7W+CpngiKDJHbSMHihJH5klUPT059h/z0fWabHFe1xzFkw2I2qfj4pi9FRqFnWqXtMDnrIrcd3nKEHWa5q3jgbWWaHkrQ0jBBnOWc+S2dRd++muHVriuvX93Dr1pSFDL/zzhLjsft7v4x0jF2zbNU4S7BYF97tMQ6HSDd5vveHg6g1QhZjUtH+o9z0vOPJAPefbTpqSBCg1i6q2DgXDnpjlk3DEAv8HFudZaX8m311PG2RZbskqAWgvJZdNIyqqgQ+y+3kIEFUQy4QgCDBz9gylLlh+JG4BbNRHziQZU5MdOc8PE1OI5o9J84y4BcXchYrphuGr07XavL0Lb505LWL66gQwgANY0/SLNsCPz+3EzCRyPD1n9ROEK4xNmcsviYe6zluo8qxjuMimk6f5R5AhFkNskyAKc0zaf29z/rProywngP419Ll/KTF0CGBH0BwlhtAiXkOAWcP39jo0/YUFVBBJpqmyl5QXxmFOcsr5uJv29JCvXv3YlRVhHv3Yty5Mwo2zLdv53jvvQXUleqWj6bxotauWbZqnCUoKjeKxOUQhSI4lwx+n43GAmqi4vCVdb15PMHfPZxvfragSbJpGDqYoz8No+UsS5Blu1HUxwn5LAPuFL+ccf3NmnqQ5WVeogKTQ25wliWIakNFIbb52JzlDRoG/zlI6y1bFxqnvwuHI2lPzFKhZebgPTfncY7Iss95QBeH/20vPF01XwVoGET0OidAQQeTUI4Yi7xEhO7Cq+F2epsbPhI4qsdYlzcux0velW4K8MdnF8/WLH6zvLmIbFwsWNfA3yxyPI71v9nNOve91vfXtwBk7/45Fh4aFKHjrun3Qd8fjmNRCFle5f6AF58bhp67QwvQzAAgqNLfU9+3/VEWto57TsjyNkK927dz3Lzp/u43btDX5EWrXbNs1ciz0gQEnOWAncyaMaC5VrzcxDVdnz6a4L88nG2Iw1b1ZMiZDGyB3+mSFiD5Sg+aJg2D44ebxBGSqNsonjIGY+3x+cCJLMsFfou87Cx+Qu4FZm0iywIP0Zie1AC+E4HpCcq1mDLPwYXecGOmXY4SUp7xhBCGSXZMpNXeO/dncxwIxtbC01W6AaRCSQDg6dJBLSoZAj9G5LUOBLF3r1o3j8D1Z4xPDRDgQIc519L3HLBFswyBX8gD3nUcGcXN3ywuGc9ylqjkOh8Ng8NZBggrxpyfrGmPCycBoSpAI+uAjIaREpoKgEbJfTsmXKoe12dZX2f9Hl0ZpjhdFUGu9bYCPw69wocAc5FhFx1jPFaeyy9T7Zplq6g41XVRsVa6PkRUF8dD0hUqsliXrOZG15tHYyzycoOKobcJOVQOG1lum1QZDUN/F/33y0CUq1mpY2JrXAOIJnWUJZhk7khZLmqgSzcpduS1TkekzkOX2XBJ+J0tFYXm5Jm/66vERJYb/jvHZ9m/1agFixyOpI0ktggab1CeDJLmGeqch8DnV1qhLeNlXgaTtlzOMnaFOMt7IWQ5MDZNBynGWUzSMBYecR2VdAbIOctAN11UfT4DSBi4Oc8in+UQZ5kxztsR7r0Cn1zca8YiMoqixrPeLDFnOffPUdzFvH0tOfPE2dIwQsiynxrj4+K3jighAEL9O8WBB9T3TKJ2p/DKSF0bCl3mLv58xaVX+BBgLjKs6Rg3b5aIogo3b5Z4772XS9wH7JrlTlFWMjkDvQFMbqh/YglNrvo8ZhvIMi8tTtebxxMAwLcfzJqfcSOOgXbQ1wMaB9F11TCNkUSb1nF8BwT/YBxCuI+mGR46GgOxwM9y89ClF1S8+PH2uZLYbOnmg8NZZkX91pOblLNsfo5ZXHeVQdpFoCTBA4C63z5hmLYj5PL5JdWigP5mOfTZPM6y+m6+nYqpxf03iys+vhZI8fOND5RrACC0jiO+B0d46kOWud7laey3IAT46Z729n9DBWKcAyVw49oguiLkuSLwMA3DH+RhlkvPwKFhBN0whIBCmLPs/i5J7dttP9dSZJkTd20+0/ujcOQ193n2FZdecRbI8O3bOd5//xT375/g/fdPX7pGGdg1y51q6A+OSYEdphFrnqlv1R5eMeoJZW4L/ATI8qePVLP8dw/bZpkr3ACUl6gyz9cCv35uGFEUYTJImwlOcg4u8QZnMAYUb/nh3L1lDchoGEAX0ZsLaBjm5Cjh6nI5y2kcIWY0iqpRkDXLlIUf14nDRcOQWsdNB/5wGMkzJS3b9s8uKnFOV4skMpBlz3Ot3QVc1yBnio85zbKLg58mMdI48rthCCg1VMQw57n0uWmcHQ2DL/AzxyaJ1ze1+OA2ioOkGyHf0qt4NAy/Gwbf3tO+lqeMeWIYWHw1zSrjmQ7tFIS+yyhLOs81VwSeEkCCWfYilIMs5yVvweIrLr3iBwUZ3rZePufoLYsKD1gzEn2AsJ0MZ7vQJfBbrulUJLsOxxkORulms8z0AdU1UafQRgAAIABJREFUSuMODWOPsATy1TiLNwR+3HNwRdPOmHSQo0mG7zyad34uGYgBZR0HoCPyWwSQQLPcbhgyn2VfcUNeAO0BLgslaTjLjoadK6wbJDHyskJRVg0dhGOhaNaEsBxbCp9rSXFoGKHvH0WRepdIn+UCWRJ5G75mh8NFwyh5yvnj6dAbAw/Q34Wy1VwK7qVr10wXx/97nKnrWFbVxgKR611+VgI/O9hjJeDZUqEcjViS4zDj5SyH/9b8LLu419IVY9+Mz8Q8MQwsQCVjQzAELLCTOUq7zzVXVxJHSlfDccMw3yst1iWR5ZzXb/jK54Psolfcvp3vmuNA7ZBlq1xcYV0Sn2XA/wJxtle8Aj8BshxFEd48muDvNmgYPLW2LhNZ1pM0pzm0azpIWxqGAAV0iTdOA0IoXUeTgYezXMfZbo0s6+vBWEDVYsVFXjQDMWurV+9SBLYZuVSGNI5rGkatzmaGkqhz8CPLnLhrdQyT48lvLgCas7wqStb2d59qPbL7N8uAWojTCX5FMMghjtzIMifuGqgjrymBHxEIMkr96aaSXQJqjOU8T60Hffv32nKOiyxTtCYVc8xzqlk5aBjcBD/ATffj2vANHXaMC4ZA0jxHr8CPjdJ3Ud2TVYE44rrDbP88DVJGwmjAprXjhiEQgaeB5wlohbO6royUAJ2yj1uXFQZMIMFVPyjCu+dVu2bZKmqLkGsS3jbLfqVxaDBzC/zoZCtXvXk8wbcN+zju9pouc4vqZJVjnMUspbhdk0Fr9yQ5B5d4Y8blLE8yPJmvO4N53tgScbf/3dvf88bmKrx4iKKoiU1e9UKWadU0VySnaRiLevDmUDcor2eOe4E6RhedlXjzAmpbd+7x55XumEgq7IbBa5Y1IuqrWSANMooiTAepc8HAtfq6Nh1gti5IhN73Xca1P7KrJAsf0g2DkUDnQqY1B5lrSUnFI+clr1G0UdU+NAzXM8V1dnEF/TRCssAYPQiMK1yxpAvVna1UuirF4R8S1nmAjAMf9FnOS7LpVLunm/dBIgJPHSJHu+xFqKZhPKGaZSa1ylc7esXZ1o6GYVXIDYODRlIcT4C3ah+mMSLYAj83n5CqTx9N8Hvz7+HxbI3DSSYS1+nzMAV+UicMXaaCXSbwcw3GPAu7o+kAFYDH83WTXgbAQHa5yLKbhjEX0DCA9lrKQknoZwlQz5OI1lLTMNjUjYaDTwn86GvQbvu2x5BylicDlWC3yLupiSumIKlPhVC4UDyzrlGaYBngLIee6akHXedSB8wUvzcG486/L/OyiYq3y8Xt1NVwlgX+7a4xVoIsz1cFMFU/k3iXu1LnzJLRMNr3kmvhqH7H71vNtaDzuWEMU7pRBUzrOH98fDbmexybEeynyzzoEMQV+PGQXT+ynJcViiocADbv6CkEyHJMx6cDXV1Dy1n2R15zNVJU7egVZ1c7ZNkqyiKJ42UKMHyWGat2JYpLNla883Uh8lkGgDctkd+S6XGsS229tjQMqbhP17Tmm1ZVVTc2vHPwuWGMszAqqr2WbUeMVuDH5CwP3DSMhYCGAWhKSwkRDUMjQJSAJZfQMFo3DElyHuChYax5KPnQhSwLJkSgG25jloS3La1QNC+fhhGTbhizNaNZHrqbZa4na9ssu7diF4RYcWRQsuySOJs0iZ4EZ5lKoHMhyxJkO6v5877i8r9TyzquEbtyOMvEM8XdefJxljnPYmsdR7hhMJ1yKmym1Z6uCpKvDCiub5ZEBK1Hdj99HHTOAmacxZ1FrCTlNQ08T4C+L+2xsiTGKI1JzjJ3t2hXz6d2d8IqvSJ2bTeKfZZ9NAzmxDayBE3KZ1nWrL55rNCjb9fNsljgl7UCv9k6Dw6CvtI0jGYQFKCa9qr9dFWQUde6NEL2yHLEkFrHDdIYgyRyIMt8NwxAXcvlWuizrONUe1oj2aU5yz4/Xec5EFu2rdm+HFmWcpYp67SlkF4kKa51XKioZhNQ3yv0LE0HaRMOZBaXOnAcCCZZ5v7gIxJZZthh6qLsOTkCNReNI5cgkQFfXr7Psi3w46PrWRIhjgLIcuB+jlyc5XXBCxqqGzfbTaM5B7bPcnd8mq2KRoxKldppoxdfLFcS4n5yPOhdXHxJyiuHhrEquovQUOQ11SxzwkZ2dba1a5atohP8mD6eATcM7pbxxFCf50WJvKzEyPInrowwTOMGWZZabJkK/m2QZe2Ry41H1uWKMp2teOdxOFbN8hOrWW4mVgH3em/Y5YrO1wUi8L/LsB6UJW4cKYHq6pLEouotS9UU8e5lOyH2t45rqAzGpCSxGwPMZrk7wUjpRZIKbRlTaKxZVLMJqOcptH3tEzn2oWG4inTDINw8uIIwQDUgaRw5kWWOz/LYgUxLOK4h94S85LkQdBL89NjGOIdI23J6QBmA907Z90OMLJOcZf5cZ16H01XOSnkd1RoO9+crCgLHN52i1XAWMCMHF1+S8hqyrgO6bhiA8lr2WcfpHVjX53PDRl7EusyLgF2zbJX2Fra3S4tabS1yMCDirjnJREo9r85DD4pSJ4o4ivDG1XFLwxBzlpNm9X/KbFJdpWy/cnbanC5fs8xJzdPN8mMPssy5l7r2hmnnOPMaxeEGYWjOssQWKRRLC4QFLGYpFKR0Dt7+c/Bbx3ES19S/10iWi4bBtY6jaBjF+dEwdLSwt1E8SzeMwPu15/Ga5tpaHoxSZEmEB55mmRIRU+cvXazYFLPm8zmcZYeuRBJ3niVhgR/XZ9lJw2A+h75mcVW7cYRoZi4aBnfhFuQsCzyrgc2xgattcXmv65IBADGKyp2ix1nAmPOsrhZQYSLLQp9lQDli+GgY+ru4rgE3bORFq8u+CNg1y44aOyaFtQCNDCPLJQt9MJOq9CQisY7T9WnDPm4bGsbpKt8KWV4VVfN9uPZ1il/YFfhxkIsrowwRgEeWfZyeKDkToq4feW0f7997sjEgzwPuBXZpz2qRLRLHZ1mA6qVx3ISS8Jtlv8hQeYFGQYcU/cxtCqKk1nFq0PQlv50XsqxRQDqUhEvDCCDLQYFfSgRyhJ/nKIpwPPEHk1ABK7QbhixtbJTG3vsYep7GA3WtZz1pGFkSoSgrp6sKwOcsd2gYAjcMoNUw2MXd/RsmLus4P43GrDBnmRkdHruQ5fBzDNDNssQOU5+nC93l6CJc9Cj9fRIWrYfLWbaa5WHqbZbbnZLu53PDRl60uuyLgF2z7CjXpND6LvIFfsWWnGWzadfnI4m71vXm8QQfPl1isS7ECNwGDWMLNww9eGp0ls9Z7iLL3ME4jSNcGXURYUmCnq6feOsIj+drfO3Dp83P5kIOueboydKp9ERwRpzlpI/Az79lyz1OI/BzNBfcRcs0owV+58VZBmh+JcXzNWucudFUXacczrJD4FdVFRsNBfxey0VZkVQvettcNq5MBm6UmmOP6UaWZTQMwC/ALkQJfm3T3VBImO+i0jC4OcucZ9kp8FtzaRibwUCdc+Bylh1jAxdUGTqaVF0SO0xSU8HYqaAS/LgaJal1HKBoGE8XbjcMao5yhYpQP39R6rIvAnbNsqNc2zIiK5smSMLnhsHjLJt2a9sgy28eTVAB+C+P5mIEblRP8FVV1Srn/jQMwGiW2QOhwzpuzaeDHIwzPJ5vrt7zHsjyP/n0EZI4wp9882Hzs8W6YDthAJrSIqNhpA7kxi7JFnjrhlGwG/3GZ9mD3LAmZy3wMznL9YTIpbFMKM7yOdIwABoFY1vHZf5jFPUChmsdVxqoaCFYyAOKt/xg1m2WQ7ZtVIKfZHcD0ECAe/EVei5dHvQyO0b6neKGkjROEPX1b33DubSsxNksrpiNouuZ5D6LSawEhq4Gs6qqeo6Se7BXVcXWlIxIGkbFpsmlRHATJw1xnClk2KRSSAR+rpRZu1w7NlcIzjLVb7ysYSOXfRGwa5Yd5aZhyO2+vAl+TM7yxEC4l1sgy5/W9nEPZvJQkhpZXuYlirLaGlnWlAiJL7DNL5wJEO6r4wyP55uNQV4o435JuMreMMWtmwf4D9980PxMTMOoQymaXQoBshwMJRFxlmXIctuwuznLEr9os1mWNlgUZ/k8aRiAWjS6ULiyFuJwaRi+UBU93oQFfl0qipRWdDx1I8uhgJlRqqhULm6ohGMKqDHWJ/DjpEHaHvQyX176nVIoPZ/KoBsyKQ3jysi9Dc99L7TPsvk8cb34oyiqOdeue8l3LGquZdlqa8oKTM4yvVMhR5bdNDEg4LPs8LyWCPxC8elFqRYf9o7N/jDFfF06+c5rYgH8IoWNSAR7l30RsGuWHeWiYUi3ZQDaOo4zEIyyBDNL4NcHWX7j6hhxBHzrwSnWhTzuGmjt1zj0B1d1aBhcznIcdwYTLg0DUCI/G1mWoBZm/cTbx/j2wxnuPVaJiP1oGKUIgaIQIF0yzrLiWS6Y27XqPGnOMi+EoUvDkDZYLbLsQePOEVkeONLSAGHEcZagrNzXUX+nMQNZBjYXDNL49mvTAZ4s8s4zxUGWzd8zS8pZ9lFSOM2y9qA3reNkiW80mMHlLNsLWe1ewEnFBJQP/CMHws+lYQyTGBU2v4dkEWwnEDafL6Cp2Zxl/VxydiBpzrLEXcUvQF4ydhz0c20+j22CH2OMTui4a58DlI68fupAl0NzxO3bOd5//xT375/g/fdPL22jLBHsXfZFwK5ZdpRri1AiRgqHknCt40zOct0s92gIBmmMGwcjfOOj0+Z/c0s3g1o9v43AD0DTuEqtznTlzO1qXapZ7gr8+iQj/cRbRwCAP6nR5fm6wFhwLTXvVU+qXPqBbVFl15opGAVaA30uz1Z9vj8YRWpVtYEs57IGK44ijLO4g0iW9baxZBEoLZ8Yq3FvYCya9Lvk2nqfMZHltlluJxBpyI62j7MdMdrv4muW/emmUjeMseUhr0vC/3Yhy5LxmUaW+RSEplkWXoOrkwEezrqcVa4GQY/jZsMpDRty7ZaIfOCta6A9wJ+nwC8jaI+cZEmNLG/Ses7OZ7kJbuo0y6ppfDp3uNsQbhgvSvUR7F3mRcCLeyfOsUZpl4bRcpi25yxzB8NxljT0hzbZql+z+qmjCb7x/RMAwma5/t22We5Hw5hm6u80JUIk8DMQA40mcZv2w4lqls2tynVRsigQdt08HOOt4wn+w7cUb3khpmEkjRuG5PNDVlfLXDKxRDU/VhJKUguinAI/3nH072yGksjR4Omg63ctCYPoW76JnRPPrEu/Sy6ubkPDCCb4dWkYDbIsEPgBXa/lkMexPn83z7ZiUct0jT38Z25Yjo0sSyLsW9Gsj7NcsShatv2alDd/NMlwuio6zxV3x8X1Ti3WBZuqN/DQMEQovbXrpBcwXOs4n+A170HDcKG7HEtBrTsxn2uJriULNcseZHlfN8uukKEG2faf92X2JAYuv2BPWrtm2VGugbyJv+SsNAnOclVVbM6y3pJd5MVWyDKgeMvfr3mKQ4nFk0aWawRkr6fAb2wjy4JGzTa8B8IInK7DcYa8rDrb1twta7t+4u1j/MW9J3i2yDFfl2LruApqQpEgqlkgREHEWa7trlZFJQgl8SvnuTQMPVmZjcFayFkG2nCbjXMQckX7VKhZ5qKhgDsdVH+n0HOtk9FOjej1Flnm0zCAbopfqPGnkvckuxuAdsPwCPwYz6WNLEt9lgG/tSc3lMQO9pDy5q/WPvA2FYPrm25HyFdVrUVgUvUGaey0juuF0pcaWeaDGWdHw9jkTZvVel/7r+fQ8VxLHJNSD53FPgeXdRwAZ4pfK0x0n/dl9yQGLr9gT1q7ZtlR46wbfymJSG5oGI4XqCgrVOBtcekV73xVNKteady1rjePJ81/b4csP2fOspXOpJtePg1DI9rtdue6LEXpfWZ98e1jFGWF//fvHioahuB66MHy2SIXNYmU2jovKxQVfws+jaPmGnJRsMTiJZq1YPIr9XuzKfCTi/Kmrma5sew6P8TCZx0XEsWZ1SKz3XGBz1lWz/MGDUNgRQj4U/xae0qas+zzBhb5LHsCTrg0gokFaEioA3aDZxefs7z5XkjtC69O1H2wqRjchFebhrEu1NwioVc5F8Aiz+pNZFk/lyw3jCwk8BPSxJxiRT02UDQMveOzKZqNmSLwIA0jd79XLbLcpeK0uQ7u877snsTA5RfsSWvXLDtq5ODThR5es1Jim69ZMTJpGIDatt0WWX7zyGiWJQK/eoJ8WE+sk740jE6zzNxii1U6k7bKmq3423wAcHWsJiQzmCTvKfADgM+/to+r4wx/8s0HYus4fe+eLXP29wdq5MIzsXMmg41jxTFO6m0/brOslPNdv2tAbz3z1PfDdHPbV6J416WQ5U0kZnmByDLHx1WXS0iki++Gof79ZOXYMmZey6uTAeLIT8OgfJYB9/lzdRi6JlmCvKycIkPOtRxbiyaJW1FqNXhmNUmtIhpG2fx/CQ3jeKqRZbtZlnGW9TO4ECzcAE3DcCDLOX+OalH6GlluwAx+gp/LHYYbsqPOYRPhN2vJoJQ0OybG+821DwQ4zbKb3nQw8iPLIXeX50Vx2IbqcdkFe9K6PJj9JSrTd9G2GWI5GNS/4uKZSpTG+iWerQ1keQsahi5ZKMkmDaMvsjyq7Z50s8y2LTO2TAdp1G5Xb4Us9xP4AQpp+KdvHeHf/83HKCpZ/LgeLE+WQmQ5jrDK/TaEANh80TSOoB9LyXOQxd0kRUCuvt/kLPegYWQJ7j/bRCZWgsm9b/kCObhx3/oYgJvGwH2u3W4YYX6jWUkc4aojxS/EWW64nZ4gDQlnea/egn4yX+PaXouGcUJJAPUc/P160fzvfj7L3e8h4aoOrOOIaRgT1Sw/dNAwOO+FzVmWUIIAHddNzFGcHSNLn3Mq0JQMa1rauh7b7XOQ7Japc3A1/uH30+mGUcrcOKi4ax8NY1+/A85mmW7yb9yocO9e9xk9S4qDpnpoBPvevQh37owA8Bve27fzF7Y5tmuHLDvKbXrPRy40EufaOpdsF04MjuNirVa6fRHR/VGK43r7VRp3DWxPw9B2T9pXtC8f7ZQphNJ1WE9IG81yT4Gfri++fdxMClLrOEDeLA9Sd6MKyJ4nYBN95HIbAXiR5WXO56raiWNS6zhA3XefwO8iQklCDaZZLYK1vRvGzEXDECwAjyeZmLM8JM6fa4ep682jMQDgmw9mnXNgIcvW7t9K8B5kRIKffs8kyHJDwxBeg6NJd9dLH2fYg7MseRaBOq7bQ6nR/x4qPZ7o8XkmbJYB9/Mk81n27xQsGeCU02e54CdihuKufQvqNIkxyRISWfaNj8+D4vAiUD2eZ+2aZUc1XGGLwwTwfJYBvTVDDESCbVuFLJe9PJbN+nQ9QYkS/OqB5OFshSSOtmpIzAaX7cRg8WVnAk4coAR+wGaznAu2+Fz1jz91tfl7iXWcvn/PljKBnyvyW5eE1qOO1f6eJODGJ2LhCvwANfluxF0LreMARb+xKVIXScOQuGEMm3Gle5wnixxxFF4EpkmMYRpvCPz6JFK+cXWCbz043fhZOJSkOy7qkvLPP/vKFADwzY83z4EbqmHrSvT7weWYAm6BXy4ARTo0DCFneZwlGKWxk7PMDSUB2mdQI/4SlxvaOo5/DUzOchLJOPxu324+VY6ytlzlJZI4Ip+LsQNZXguRbR4No3u8/VHqdMMIubs8D4rDy+ZmsW3tmmVHufxEcwF9AlBNiSvpSrJlrCdOxVnmWwL56lM1FUNEw2g4y2vsDRK2N7CrTNSMO7HbnDgJcqE/M0uijsCvL0IPqPvyY68fApDSMFrOskzg51dbS0IxAAtZFtEw3PZ1XIEfUNMwrAZH2uBOBt3kN+k16FOutDTAmAg5oSRpd1LW9fB0hcNxxmr2pha6LlHu6/rCJ/bx4dPlBhUjRCmh3TBknOWrkwGOJhn+5qO2WW7cHHpxlvnR6VSIRT8ahkaWZdcAqINJ5l0aBmvxZXmXN0IyJqgyTN3+7TLrOBvMKDAdpqz7oBFwV7OcSwR+eqfAI1YMvZsjlxsG02sbUGMqFUpCLUKvjFKPG0Z4TDtvT+KXzc1i29o1y45yTQrSrU5KEKX+nc9ZVm4YZ4Esq2ZZJPBLW3S7b3qfLv33wzRmN91tnOomJ44rNIyiqI68NmkY/IHQV198+xiAlIahfrcoK9F2LeWzLOEXAptNgKhZdvDytA0iG1m2aBgSXqKuyUBxhzdSyzw+pmdZLT/Ubpa1/zn/fXa5STycrRuaVKhUs2yGkshpGF/4xD4A4OsfPm1+xk3ws89fYodp1mdfmW4gy/racjnLpkBQlGJJbNtLmmVbzyJ5F3S5gkm470Uj8Cu0wO8CkOWG0qL+5mRVsG09WxrGdu4qWep3w+Cg/S46SC74/DT2C7CBNpTE3yw73DB6vNNnXS+bm8W2tWuWHeWkYQjiL/XvuWgYkoFoQ+B3BsjyT37mGP/sh1/BG1fH7L8xP7NvIIku3SxLmnUXcpHEkajZPBhnG7zAtdDmylU//blX8NM/9ErTdHDKFN7IBH5+ZFnuhtF+b4lYNE26KJS2quJOzsM0dsRdS2kYXc7u80CWm7hui18pCiUhfJYfzVaN726o7GAWaSgJAHzu1T0kcYSvffis+VmQs5x2d9wAmR2mWW9fm+JbD2bNDpzEhm/cPAfqbyTb5s1u1Zac5SaVUgvseoTsXJ1sjk1VVdW+6Qxk2aIx9OIsb20dtzk+ny5zVtS1Ok+ahiFFln3fJfRcxrVTj0mPUvaB/N26PnHXgBL5OWkYTdz1xbVoL5ubxba1c8NwVIPo5l3OsiR5zm0dxx+IdHO5OCPO8mtXRvjfvvQPRH9jvuB9xX26NOIgDeQAjDjVVYGpkA6iIq/bFzwvq60EfvqY//vP97+WkkHQjvw2ayl4nuzP5U6qQE3DcNh8qeP0o2H0ccOYGk3SlZFqLp9Hgp+PXym5BoMkQgRg7mgOHszW+NFP8hax0+EmDSMXBCbpGmUJfuiVKb72vc1mmdr1SWMlXLZpGFLevK7PvjLFMi/x3cdzvHk0EdljTgxA42CciRZeKdFc5QGuqFn68/TfSOOuAUXD+Os6WRVores436XDWT4jN4zGOo7ln755LWerApOM11b4FqBlVaEQOBY1Hu4eSglLH5TGFme5EumTKqh756JRUYuYK6O0Eb2bdRmQZeDlcrPYtnbIsqNGTjeMuilhNllpErvdMASc5YYCsSqwXBe9beO2KRPF5SIGvjJpGNyy07Zmq5y9zafr6jjDk8XZCfz6lvm9JSjcgOAsS54nwEKWRW4YcYcKIqU/DNLNbd9+bhg6lKOd2J4PDcPNr1wI0LwoipQwzcNZPpoIkOWlK5RE9kx//rV9/NX3nhnIbphGMM6STnOz6omCfeaaEvn9bc1bbqzPmAI/oHURkSW+EQK/hoYRPlZqIctSn2WgpWFoLrxk4TG0ke0ePss0shw+ThJHiKNNmty2yHLINs2uNr7cLUDmXMtRRzAq2KmI/TsVAE2P2R9m7mZZsAO9q+dTuzvhqIljuzQXcpZTjyBK4oYRR1EdvV1ivuapxM+jdCNwETSMlrPcIstS7vShTcPYUuDXt8z7J07wu4ScZT05c+/nsIMs9+MsA9i0DXuONAybX6nV9lwKxCjrumrMak3C8UTCWXYhy7Jm+QufuILTVYFvP1T2bQvGgnxvmG7w/wGZ1ZhZnz6eIo6Av/14s1lmcZa1+Lm+DhKOaeOwc0YCP9PnuA+yXJQVntWLH8mzbCPLFDfWVVniCdoR3s8siTcE2NwdSD0eLtd2sywULRMJo1yXlnFmIcsigZ9/pwJQ9yf1OHIcjFMs87KzgJbSPnd1/rVrlh3lto6TbXWmsduonKNy3TwXFQu7yC8GWQZaBHJ7GoZqtiXb5V3rOP5grOtwnOHZMm/uh2SL7Sxrk7MssI6j3DC24CxLmmUXZ1k7u/RBlhU3s2L5yZo1zRzN8nMU+LloGJL3cpTGHc6vDqW4ykSWba9pady1rs9bIj8Osnx9b4CPLH9mCQBg1jCN8cbVsYEsCzjLWyDLaeOesJ3AT4/heVE1IkfpNTiyIq8li9+mWbdpGExQZZC6OctrIa3GtLY8XeX8ZllbEdo7FUJ3FyrBj3tPRukmslyIBH40sky9V1cd1qaAfp557i67ej61a5Yd5aJhrIoKEdp0vlCliduoXMJZBoxmeV02oQDPu/Sgtr0bhjqOTOBnceJ6uHLoYBKdlCTZYjvLGmw0y7IFg4uPB8ifp03rOCFn2aZhNM0Nd3JukWXpVqsufe9PjYZz2ZMGIClK4Cdp0odZ0uH86kbpiO2GkW66YQh4tma9cXWMK6O0Efmp70Lfy1f3h/j+yaYaXtpcmfWZa3sNsixxc2h3GFoKhNQ+0bXz16QhsgI5WhpE3ogcpTSMzchryeJXR8jbAj8JZ7msuk1en2Z1U1PC24E8qDUHT+abNASp85RNBTFrxRRLjlzIshCA8DfL/lTKq9Ziqfn8LYOzdnX2tbsbjmoT/LpWMmzLMw8NQyKe0OcyrwV+kgCMsyy9eNjbmobRA1m2JjbJYKxLB5M8qlfvuWCL7SxLq64BKQ0j9sapSp8nPQBHkG2bu7ye221z3nGGSYylkXYGyJuLplleutwwzu+eNtZxHWSZF8+sS4VpWMhy7XV8zESW94YJ1kXVnIumYUgn1ziK8COv7ePr3zObZfoYr+wN8f1nyw2/aWlzZdZnXpnggycLnK5yEf97bFHlRDQMAokUWcfpJq0om3dBjizrZlk9A9LFrxkh39CimOcwdbxLQE0tingBL/pc12WFsqqUwI8JZlwZp4ijdlzW1Yev6xsjFTUm/D1GadJJ7OXuPtpZAK5z8C1gmsVS5xpcjK5mm7p7N8WtW1Ncv76HW7emuHv35fKP2DXLjtKito46VsgzLbYUTwAmslxcGGdZv+hnJfATNWmW4bxkMNZ1OFYv7ZN6QFoXpRiFO6sc3WrlAAAgAElEQVTSzYjYZzmALEtRNYnXtT4He9taalWVJVHT4PVtsKYuzrIgkKJvUTQMWSJm3Enw0zSMIwFnGWivgVRPYdYXXtvHNz8+VSJiRuP/6v4Qq6JqdmmA7cRIn7m2BwD41sczETK6HQ2Dso7jC/wAvYisel8DG1lc96A2mQl+wzRGzHwPNEf+waxLq5FS5fKixHxdoAKfrhdHUa0ncdN6RK5JnjGSG5YzyuKNRayaI4S0HpKG4b4m9mLJ/PyLtI2T1t27Ke7cGeHevRhVFeHevRh37oxeqob5xbkbz7lUk7qpjpWgkSHrOG6zNM7iRgB0UZxlPXCflXWcTOC3PWf56lhNCo8NZPmiBqK+yLLP9F7cLMdtsywptVPiRpa5E+vQ4Cz3RYP17sTMomGcp20cQLthSBMxbTHPg7pR4nKW9c7KSU3F6BN3resLn7iCsgL+6v4z1nd5dU+9S99/1lIxWhqM/PM/84oKSvqbj09FnOWJtfsncVbR2/YuJFB6LbMkwspAlqUc/GbXq34GlsJFpPlOSSlBOgTnwandqMmSCLWeQZquCnR9poF2wXAWXvRch5KRRY9S9qJCzrLP3pMYn+z7r0tihXgZEN133x1iPt883/k8wrvvDp/7uZxX7ZplT41qRFfXWthgpbGbsyzl900GSYPiXBiynJ2tG4bMhaHeMi1V1PBslfdGlh/VFk0XJfADzGZZgq4r1MSOWgZM2y6Zx6y0WdYI2sZnS63jkjYyunkPhOcxSJSq/LSDLJ93s6yOb7thcHi+Zo0tiypAPZdXRil7fGmoKEYgB8DfNjdLi/y+9uEzVrP16p6a/Eze8jbI8ieujDAdJPjmR6ciNwctwm5DSWTb1q7nGZD5LAPafq1qLd96LEIPRmmD7q6F75TpMNO/We6XIKhL0zBOl7pZ5s8TV8eOZrnsQ8NwI8vLnPddbOGtKMGPCLnR5+C7L9NBgkESOZplHmf6siC6H3zgvla+n7+ItWuWPWVbyUheHmBTIWyW1JN0nCXNNu2FuWGckcBPIw6yRUeLLC/zEkUFsc/ygaE41p6yF4Us60TEPiLHglp8Ca3jpAuvzJH21aBpzO+iz1E1F/1oGFEUYW+QdKzjztMJA6BpGJyoa12jNMbS4YbB9VgGDK5pjSyvy/7K+cNxhtcPR/jah095zfK+bpZbNLJvowiorfi3jqc1sqxpGOFnM01iDJKoaXCkDZ5PU1IIEvyAlsu/Er4LZh1NBi2yLJwfBmncLL6kjknXvMiyLFlTo7padCuZJ65OBh2+bh8aRurZfVszkWXlH27sJIsEfpqG4ecs+84h0lQUxzXgzBGXBdG9ccO9UPD9/EWsXbPsqS4NQ85ZdpqkF8qXlYsCjbMEJ/WKfdsEv741bJDl7ZplzTPsI/DLi7JB0iZChDtLYuwNEzyery88GUkPmhKfZyqhalnTg7g8RZOzLKmBw91FmuDXiOSK0kAj5fdhMkg24q6XuWzbuE+dmXWcNa4AOpCEx1cGgOmwDmZZtpzlbQSrn//EFXz9e8/q70K/48fTAeJok4axbYDCZ1+Z4psfnxrWZ3wgwYy7lgpWaRoGl7Nc0zB62ucBmoqwiSxzv8uggyzzx+i9oUI17WZ5lfeY64qqEQpKtC1OZFkYtAS0u292cTUFmh6ld+/WgnfKpgq6zoEaI83Fkq6cmWB4WRDdd95ZYjze/P7jcYV33ll6/uLFq12z7Ck3DYP/ACYEZ1kyqI8NBJCDuJxHtQK/M6JhCLloAHpz4nSpyOt1a/Z+wZxlyTNAmd5LU/AaZFm8XUy5YfBpGIB6B3Tj3wfht32GpYKkPtXGXXfT60Sc5bTrhvFgtu6FLDcCv3I7MdAXXtvHRycrPJytgt8ljSMcTwf4yKBh9EECzXr72hRPFzm++3gOgN9wTgaJwVmW0uTcyLKcsxxvOJP0WTAcTbJG4CfXAUTN9Zfy56NI3Utb4LcWvk8a1W3HZwENY6I88M2xpZ/Az89Z5tEwEhSGjZ5EYMexjqPG28OJA1lm0kcuC6J7+3aO995b4ObNElFU4ebNEu+9t3iporJ3zbKnVHLepjpWYs3kjbsWiifGBspyYchy/aLvXQQNw7COm63k23y6rjbNcn8x1FmUvoeSazAwroFdalCVN95yznIXuRE3y4b92jZo5CRLnzsNI01iJJELWZZZxykEq9zgnz+arUXI8p5Nw9gSWf7CJ68AAMqKN8a8ujfE95+1DZbUvtCuz76iYq+//uEzDBL+Lsk4SzBba99uOc/WiSz34iyXWzbLLRVBqmkZpi19YLkuxHPE8XSAjx0hM2If+LxqFrBSgR+wGcqx7kGVc6WcSoKPRlYQWS+BXw8aBqAWSx03DCY4d5kQ3du3c7z//inu3z/B+++fvlSNMrBrlr01ttWxQgEJFXctGQTMxvDCkOUzEvhplFyiGNfXKi9KnK7Vy9enWT4YZ3g8bxGMixP46QVDf/s8s9RkIEeWJdu1QDsZlaa/rhQFS1oqwzZo5HSQbLphPAeBH7DZmOgSu2GkMSq0TfcqL/FsmeNoKkCWNQ3DQJa3aZZ/6JVpsyDjfJdX9ga4byDLUgcHu96+phwxvvXgVPRcTgZJE3e9EmpKvAI/MWdZLSK3pWE8XaixSepus2Ed12PReDzxIMtSSktZNos3WbOsFokmDWHdY+HhQpYlu1ejxre79i7v4dvdxzoOQG2f5wglYZz3DwKie1lq1yx7qkvD4PsuAq33pF3SgcgUYl0Usvz28QQ3D0dnkOCX4I2rY7x5PGH/TSPwK7enYTyarZoB7aKt47axzzNr2UPYZJ4Ht9pFS3sOixrV5iKBDbJclE1Udp/mokPDeA7WccBmYwIo3u6TuQwVbsI06uNIPZYB1XDHEXCy6kdBsCtLYnzuVeV3zGlWr+8PN2gY2/DPAeDKKMP1/SHKSvZcKmS5vQaSd8pHk+tDw1iZyHKP5/DIQFelCPUgiSzrONnYeG1v4HDDkHOW10XVS1Ny1WGdpr+PxAvftfO1Eux8aZrEIi9RlBWKik/VM0XoruJwlhd5ae1k85Ht27dzvPPOEjduVPjggwj/8l8O8cM//PKGg1xU7a6ip8aWlcwqrzYoEaHyxl3nlWhAnVwCzvLP/vCr+NkffnXr48RRhLv/44+L/iaJIyS1J2ofTpyuq+MMTxa5OEr1rEsPylwBEdA2qivv4qsHZ1m48GoXLSUG9Rr7dJWLmpuGs2zQMHpzls0Ev6Ls5UIgraHVLN/9yw9RVsDPff46+xj6ui/WBTBuuaoSznIURRvX4CzSvj7/iSv4zx8+Y93PV/eGOFkWOF3lmA7SrSgIuj5zbYr7z5ai53KSKdFuWVVsQZQuJQjbXuA3SCLMVi0i3Oc5NINJVkKEepj2t44DFLL8eL5GboRwrIsS+wJ9itYznK4KpHWgF7dcCXZ6R1Ym8Is3IuABmQe9mdorXTCFOMshxN9cMIwPkubcuc+Ato/TrhiPHrXnfe9ehDt3RgB2aPO2tUOWPWX7oUpFNFQoieQ4ZoMusah6mUqb3p9uwVk+HGdY1lve+pgXUQ2yLKGiEKb3UlRVP3t9kWW92FgXJf7933yMH635rpzS33nZY7vZrA4N4zkhy2azvMxL/F//6UP8xNvHuHk4Zh9DL3j1du+jplnmI8uAWjDONmgY233//6r2W2bRMPbVuX70TDs4bMdZBoDP1LxlKf97vi6MBbBw296FLAs5y7Z13DbI8qPZShxaZVKD+gRXHdf0n4cWsitOz6t3/qaDRGRhqBvFhzOTAy8fG1IXsiwYY8xFbBMfz0WWibjrvKxQlDRAdtWR4pcLQtBc9nFmvWzhIBdVP5jdF6O072LRqGPlnGXXyyMNUBhvcJZ/MG+XORgD/WkYAJrt44vmLItQE+1P7LEiFDlrbMFZBtoJ4Y//+iM8nK3xL27dYB/DhSz3t44zbZ6ef7P8b/6/7+PRfI1/ceuTomM0k3LtiKH5ohLOMqDegZazvD2y/A9vHGCUxrhxMAr+rh1Mou0wuXQcV33mmm6WZZzl2aroJRZ1CcKALWgYZ4YsV4gjfsCMDvoB5GJTwAgmMZtVIaVFiyXVToNsXNkfpUjiaEPg1+gZBIDCOEuaREtdEmeRZhGbl+3ii/sMEHHXehFFzd0udH0luAccm7iXKRzkouoHs/tilK2OVXHXsgGkqNBJXZNylsepyVm+GBrGRZc2vdfN8rjHdTic6GZZTQoXRsPINA1Djiw7Q26kllk9fZYbC79SJQn+q/c/wKeujvGPP3WVfYzWq7gSiW/smmQJygobKO/zoGGM0hjLvGi+/9vXJvix1w9lx7CERA9rj9vjHshy64axPbL86v4Q/+5//if4R4z76WqW+/KVdfVBlse1rqSl9GwPZkgFfoO66ZZavpmlkeWHs3VjGcZFZ7V1XFVVvTjLulk2HTFWedks0DmlxZKzVSG2F43rUA4T2W6bVf45vH44wodPFhv3tFlECRIhF+uiOYY4wc/p8xyOcL866aL7EncXjk3cyxQOclG1a5Y91QhxdLMsRG9Sz2pTavi+Q5YN0/uV8qvsE+vbIstqUti2uehbo4aGIadOnKXPsrRZNkWG//nDZ/ir+yf457duiNBEU+C3jXWc7QbxPHyWgRZZ/o8fPMU3PjrFP/9vbohT8/T9n9eT6MPZGpMsES+EbWRZIobyFXdcemWvpmGctDSMbd1I3rw6RhpHoudyUge8SFPvgJbaZVdeVkhifhpiWoeCSLnGZk0HCbIkwqPZSvw+D9IYZaUWzeui6mUdB2ym+PXZrVqXJU5WhThdFahtPa1GEZAtft64OkFRAfeeLJqftVx6hnWcQY9aC3nrlHUcx17z6ljdg8fWgoH7/V32cWZJrOTu3k1x69ZOHOiqH8zui1Et4V9uJQP4Sf/SLWNz8DlvL9nLWtr0/nSV93bk0M3yx6c1DeOCE/wkqEmW+JFlKV93nCXYH6b45JXwdvvmObQN+++8/wH2hgm+9CN8YRvQNsYmx7OvdRzQhnKsmCld25bmh/6r9z/AwSjFf/cP5KLXDrI8WzXIkqSmw6RJ8JMo58+iRlmCg1GK+3WKHzdAgar/v71zD46juvP993RPz0uSrZFsScYPGRzwA4uYZ8Li4mEQhvXaZm1DbvY64eFdbgG5FdbZhMJOKlWAScmkqLpVFBRU4nWRP8iFGMjdQG4qgetgU3YoyrA2jnFMbsAIkHyNbEmWNO++f3SfntZoRppzTkutnvl9qqjC4/FMz5kzp3/nd76/7y+ka+iY04C2hsq1lXwt4HUI4h3fSvssi5z6cDeKdDYPncn5tzPGkLCzq6IbP55JHkxagZawZjnuhQzDrilJZYW693EScaNIMy3evr29yaob+KRvZNTrAIKa5WxOWLc+XoFf0gmWy49LzNAQCWnSmeVi+7hEIo+mpjwAE7puYmTE0jVPFPjyQsHubg2mydDdrWHr1igFzDa1GX1VQGyMDEPuuHus96OgZtm+jmio8qO5aoO3MuUFJDIkijPLPhX4RRV8lstnlsU8Uf/Xv1yFW5eJBXo8GPu8P4k3TpzGuuVtwhsXd8tolaIwvoHkuuV0hY0HVImENHwxkMLej05jfcccKVlUwTqukFkWLe4DeGa5IMOYaivEloaI0/LaCxkGAPyPjR34/qqvVPx8Ppb9I9Y4iPosl9MsiwXLmi3DULPva66zWh5bGz+x9weAAXvDINzGPqRhRjQ0yj5OuCmJrVkeTucQN+Scis6OuIN1sQZgALAgYQXLJ88MO48JWce5kmMZwQK/8XyWK8ks881S8RiIzAN3Q5Djx4ewY0cKsRiQyzEAlQW+pQoFqTiwAAXLZYi6rGQAq7hKzA2jjAxDMEPNZRi1qlcGChXnw5mckIenm/qIDp0VtHl+FfhdfX4C37xsrpCDAi90Kd3kRvwmXR8JCRdj8ff45aHPkM+buH2FWGEbMLrAT6UojAfpQ5msUPZIlUhIw9mRDBiA21fMkXoNx8/VlVluFizuA7hm2SXDmOL53FIfcckwvJHBxAxd7NTNngf9dlbVC7ci0bEMaQUZhsrJn5VdTQsVdgGFBk8D9oZBxl60OR4eJcMQ3oBrGnKmleGXzSyfGZF34wAsr+5EzMAnZwqZZZFmOYXfpctdRdA6rtzJHzBxwO7Orov6PJdCJvDt7i79eak40IKC5TLEi45LRY86y4n+RY+M+eJXq3ploFC5PpTOScswGGOYGTOcoiS/mpLMro9g6w2LhHTXE2aWp2Bu8Pn8zsmzuFbQLo3DbxjcPUA2G+mWYahYdonC3+P6C2ehTVDGwikuHO4bks8sD6dzlsewBz7LorQ0hF0FfmpZVVmczHJSQoahl/NZFms+FQ4xR1akMgcTcVdmWcS73H4uHwOZgL25znCCZatLp6j+mznXIHPyl4gbOJcq/JazObFeBJz2phhO9hUyyyIFfnzcktm8q8DPC83yxAV+gDUGZ52W5+q+5eUC3HKP79kTQrm8BRUHWtRuBDYBsaLMsqxmudjuKyO4EOh20Ytf3fumAyGXG4asDAOwFiSejfNLsyyDUWbjBUydXtc9Xt8QtEsrvMZoGYbsdfPThaFUzskeTYWen29Yv3Fp5XZ5xfB1hdtSnh3JSGmW42EdJngThbxU0asKs+sjjnuDqLTMK3hCY8AOMkSKHMsW+Alqlg3dyqomszmlMWiKWdlV0dbt3AVmMGWNgVywHMbpocIpASDeahqwMqJywbJd4GZ/j6IyEE57Ij46s8yzuhW8FmMM0ZBmFfhxzXKF84D/9kq7YUxsHQdYY8Azy4Uus/K/6XIBbrnHd+yIwDTHvh9jlRcHVjvKK9yxY8dwxx13YP369diwYQMOHz5c8nmvvPIKbr75Ztx888145ZVXVN920nEyQNmc1LFIuQBHZiGIGbpv3fumA7yV6bCEj6cbXuQHyBXi+IXTWauMz/JUBP48uy1jl8bRNQZdY05mWTYbWZBh5DzpHlcp139lFv7p8rlYMbfyRizFhOyOlMlMDmdHMjAh3pAEcDmCpHLK7a5laLXt404PpYWP7b0iFlbILHskw+CnjUPpnGJm2Wqa1D+SERpLXjg2YI+BTFKluc6SYZimWSi8FerMWbhe2e6qQKFBj6VZFp9PCxIx9A1ncM7Wb4sWEVuNyFwd/Cr8d4wx2xGkvM/yRHPD0ixn7BoM+e6mnFIOGeO5YpTLOJsmqPOfjfIK+8QTT+CBBx7Ar3/9a3z3u9/FE088MeY5Z8+exVNPPYUXX3wRL730Ep566in09/ervvWk4nbDcKxsBLVsQBk3DMEbS9yo7cwyD5ZVZBhAUbDskwxDBj7v0qUyyzlzSrKqM6LWTfCbl4nbpbmJ2E0UVAKsUjKMqRiDKxY04l+vX6T0+RljiNqWZ7xrmYxmuZ5vGNI5YVtLL+Bd/E4Npjxxw5CBFz8P2JplIbszuw6iGOECP3venUtllby++YapZyAlNJa8K+aAI8MQXx9n1YWRzFo1ITLNgtxrqcz67HQwHHFZEUrKMADgE1uKwdfLSteGqKFZmmXBAj+A+3bLuWEAVrCccr4DMc10KYodMubNy+PJJ8u3vC6XcZ43jyQYHOUVjjGGoaEhAMDg4CBaWsZW2e/fvx/XXHMNGhsbMXPmTFxzzTXYt2+f6ltPKm6f5cKxiNiPBxgdLPPKfdEsWFTCh7WasCrX5autOe5g2a8CPxmcauuim3vObqU6FYFKe1McL9x5OdYtb1N6nXDILohScA+IOW4YWUeG4YcMQJZISEMym0PfkFyra6CQwRtOZ+3WuFPshuFqTJKWDG5UKXbDEDr5Gy+zLOiqAXiTWQasLm5CmmXuhqGkWeZeyxmpZkHutVSluyqXIajIMAA4UgxR7+toSB/dwU9ow8CkfZYBd8vrjJDWuhi3T/KOHRFs355Cb+85HDo0NG6GWDQTXYsoG+ht27YNW7ZsQVdXF/L5PH75y1+OeU5vby/a2go32dbWVvT29qq+9aTito6T7RAFoKijkJxd1j9c3Opk9mqRkMaQzOaRzOY9k2H4VeAnA8/yFGssvSgEEYG3JFaB+9KqFCbqGkPM0DA0xQV+XhEzdCQzecfbVspn2f4dnEvnPGl3LUprAw+W0/5plovcMGRaNBcjuvHggeK5VBYzY+LfI6fJNQfE3DBGZ9elZBjxQmMSPhdlNMuAnAyjqUizLHvqNLcxCp25gmVBiVbU0KwagJxYF0fAkqnJWscBo4PleltiJSoV5D7J3AWju5th69YogPIZZY7190ns2BHBZ58xzJ1rorMzix07Irj//ijmzrUC51qWZFQ0s++66y6cPn16zOMPPvggDh48iIcffhirV6/G66+/ju3bt2P37t1eX+eUE9I1hDRmyzBM57FK4Tdv3tQEgLQW6VtXzhd6frUR0jT02wupigwjMSpYDk5mmReQlPLsBoL1WXgXPBXNMmAV+Q2nc84YBKlhD78pc42maKtrwKXbTuc8aXctSl1YR8zQcGowZfs8T/0cjBe5YYh2WM2Z1umMuzhSXoaRU5JhJFxzQKYpiTeZ5TTqbes3Me92tcxyfURHSGOuzLLcSYWhazhvZtRxxEjn8mCoPOiM2ptY5yRZ4DcV0kvLMEQK/IDRJwuiG9Dx7OIqCXI3bsw6z1MJvKuVir6N3bt34ze/+c2Y/2666SancA8Abr311pIFfq2trejp6XH+3Nvbi9ZWse5ffmBlgFwaJoFFdFGzdSR0/NQ55zEZPRhhLcb8ZuCZZjlAMgzGmKXbHuPZLabJmw6EQ5YLgWpRGLdOS01hgZ9X8OPevuE0DJ05AYoI3M92KJX1rN21CIwx22s5NWWOLMVEQhoY4GykZezOirOBwgV+jgwjq7RhcG/khZqS2JrlwZS8Zplr5k8PpaVkGO6Nmsz6zBizrNOG1TLLgCUXc2eWwwLNvKIhbZQMQ8hdRSsnw7Dclyop8AOAM8NpYes6jqhd3HjINiip5nbZyitcS0sL3nnnHQDAwYMHsXDhwjHPWblyJfbv34/+/n709/dj//79WLlypepbTzoxOwOUkVhAZtVH0NYQwQdfDDqPySxERMFnGZDLXHB4sBzSxFqpTgcMbWxBUqHaOzjzKaxrthuGmtY6bugYzgRVhqEhlcnhS7t7n8xc5Mfdg6ms5Yvrw+avpSGC3sG0dEGWKowxxMO6s5EW7WQJjD2tEdYs2+OeN9U2reGQhgb7+F3GOs5xw5C4hpkxA7rG8OVQGhmJzeeozLLExg+w1mZe8KpiK7kgEcPJMyPI264SYt1y9SLZpWCBXxkZRlifuPmSW4aRltBMA+J2ceMhE3hXe7ts5RXu0UcfRVdXF9atW4cnn3wSjzzyCADgyJEj2L59OwCgsbER999/PzZt2oRNmzbhgQceQGOjnP3UVMKr1rOSk3f5nAYc7Rlw/jzVGtNqwb1oKWWW7QUpSLIFDncEcZMO4HziMoyMos41HtYtzTKXYQRoDBw3jKH0KK2qCHzTKJNV9YqW+rBd4OePGwZgBTgyBdhGiQJsQMJn2RWcqv4OHb2wTFMSex7IBMsaY2iOW41JHGmXQPv40TIMucCoydWUI60gK2pPxJDK5i2XFsG6iKi9ieUneEKdHMu0T09l8xVl+y17WA1nRjJSwTrgbZGeTOBd7e2ylUP+K664Ai+//PKYxzs6OtDR0eH8mQfKQcLZaUpYyQDAxXNm4A9/OY3TQ2nMqgsLV+cSFu5FywsZxlTrO72At/x2o1I17Rdh2zoulVXTucbDOv7fuXRBhhGgMYjabhhnhgt6UVEMXUMkpDl6XT9kRS0NEZweSoPBP2lZPKwDlhmTnAxjTGY5j5BW+W3R/blV52BT3MDJMyNCQTd/7rlUFjqTt8Rsrgvjy+F0oQhdaOPhLvCTzyx3n00C4F1J5WUYAPBJ3wjS2TwiAvOy4IYhV9BfqslNMlt5G/SmuGG7YfDvoPL337MnZAergK6byOUs2zfZorzt21OjNMvAxIG3lzKQ6Uhw7jA+EOO+i5KZ5Y45DQCAo19Y2eVMVvxHQBRVW3tgHRfYzHKxZjkbPA18OKQV3DAUMnF1YR1D6WwgN6C8kKhvWD6zDFhjcNbJLE/9HJhdH0EubyKblz82VyXmstQUGQOnhbyqZtkVKKrWDvAiLxk3jJwpp1fmWI1JMlJF6HzcwzqTPmFoioddbhjyEq0FCdtr+cwwUoL2lLzwNidpFVtKsyzSvrwxHh6VWa504+OWPwAMuRyDYQDDw8D990eltMOiPs2AtzKQ6Uhw7jA+wI9LC01JxIZrcUs9dI05uuWU5PFKreOFJg6wbixxQw9UcR/H0LUxWbAgauB5ZjmdM4W6hBUTLyrwC5QMI2TdlPuGM2iSzCwD1hicdVo9+yHDKByv+rVZidtWaSFtYl2oG55ZLs4GCmuWPZRhNEnIxBhjzmZZpXFVc9zq4icjFeRzLy4pwQAsCcqQ/XtW2UjPqgsjbug4eWZE2J6Sb2KdDYNgE7JybhiimWVReV0p+UMmw9DXp6Yd3rgxi0OHhiryaQaq36s5OHcYHxgr+BcLsqKGjgtn1eGDHitYJs2yHIZitbWbxlgoUMElJ6SxMR38gqhZdmeWVQLcuBEKrM9y1NDRn7RcLNQyy6FCQw4fNoCtDYVA36/fFG/WJLo2O41+irKBOVHrOA9lGNwRQfR1+PNVMtvNdVaBXTIrfq/jz1Upvna7QaQVrAgZY2hviuGTvhGkcpUHqoC1iTVhdQYFMMpScCLcRehuUtl8xTryxphhuWHkKzvJ5s4T3d0TX+dUaIdlstFBIjh3GB8olmHIZG8untOAYz2DyOXNQPriTgfcmZ64YifDmTEjkONfSrMcxEAxotsd/BS9eevCOlLZPEYy1o0tSN9pzJUBlOnex5kOMgyOr5pliG8YQ1rpzLLlWS0pw1Au8BOXYbifr9ZGeHoAABetSURBVBYsR5A3rfblotfAx0DJA9/VwVBFhgFYUoxPzgwLt2Hnkp7BVFbYMamcZjmVzYlllkcyFbkcFUsvKkFEOyxrASeajQ4SwbnL+kCMyzAck3LxG0LHnBkYSufwt75hpLlmOUDBzXSALxo6U9cFNteFlbR9fmGUML0Pom932HHDUNO5cjnO2RHL31bkCN5voq75p6pZ5t3rRCViXpCIG05g6acbhsz7883F2AI/U6yDX8i7zHKThBsGUHDAiCqsa7Nsr+WegZTwNfCxrFcKlq2NQt9QxtbAy/+e2xNx9AykMJjKCm1g+DgOJnPCm8/x2l1Xes9qjBnI5MyKNsClpBcTUal2uNot4GShqG0coiF9VPtLmRvCxa4iP5JhyME3KfFwSNkf+b5rFuLfbljkxWVNKYauOa4snKBqltO5vJX1UdEs20HSmZFM4H5Pbm2pima5LhIqnHr5IMPQGENLvVw21CvisjIMXuBXrFnOiWmW3Z9bddMq02oa8EqGYX2PXwwkha/BE82yLcM4dc4K1lXWtPamGEwAn/QNC2uWActZRPT9Q2XaXScrtI4DCqdMp85ZftPjfQeiDhMi2mEVCzhqSlKjxAyro09KQsfFWZCIoSESwgdfDAZSYzod4OOuqlcGgIta6rFi3kzl15lqjBLHfEFs9RwJMSQzeZhQCy74XDg7nA7U5we8zSxz/NowcSmGX6dlsbBcZtmzDn6uLLTqGCxsiqMpbmBhU0zo33kjw7ACtR5HhiHemEVJs2z/DnoH1YNl7oiRzollqJ3Msi3DEGE8zXLFmWV7DLgUZrxrqNxhQlw7LGsBV+0Z6WDdZaYYfsR3zhb8y2RvNMZw8ZwGHO0ZdGmRgnNkPB0oZC6CJ5/wivE0y4HKLNtFNIDappE3PwhyZlljwMyoN8GyXw4vLQ12sOyXZtlQ1Czni2UYebHCLrcMQ3EeNteF8bv7rsaS1gahf8eDsahCPYc7s8wgWtxmvb+KU1FdWIehM5dmWn4+LUjEnf8X2cAUa5ZFCGlsjKQHEHfDACrLrpdyngDGOlE880xSWDssawFX7U1JgnWXmWL44jOg2CVreVsD/np6yGkgQJplMbyotg4643fwC87myx1QKLW7tufCmeFM4H5PfF1ptNsMy+LuliYiHfCS2bYMwzfNclhShuG0uy6VWa78s7jns18nHBEPZBgxQ0ddWHdal4vI3ZyTPwUPfMYYEjHDExlGPKxLyYP4JlZOhqGeWeZSlN7BFHQ2/oallPPE3XdnnD8nEnnEYqaUz7KsBRw1JalheNX6YMoKcmUzwsvnzEDeBA5/bjUnCVomzG+camtFJ4wgE9JKdfAT77blN15pPHmwPJDMBlCGYV2vbPc+znSQYbQ6mWW/NMvW+0oX+JVqdy3YuY3j16bNC80yUJiPwsVtGkNrQwTnN4vJR4pJxMM4NZiWuoZiuBRDKFgOFdYU8TEorVlOCxb4AUDfcKai+VzsPNHVlcKhQ0N4+ukkkklxn2WuN77//iiiURNNTWIWcNSUpIZx35AB+RsCL/J7/7N+AME6Np8OeKlZDirh0Dgd/AIULLqvVeV3wANFS/scnM8PFI57eSZJFvext28yDL81y44MQzy4AUa7YeTyJkyIjSVjzNXBzqdgWeduGIrBsmSBIWMM//EvV2Hd8jal90/EDEezrDqWvO21WIGfPSfy4tZ1oRJuRYCYdVzU0F0Fq/KfX0YOUaw3PnNGw8gIw9NPVy7joKYkNUzUpWEC5LtkNcYMzG+MuoLu6jiWmCpCjiauOgoFZDC0Uh38LH1lkGzT3DcOlRuie+MUpM0CULgpqzhhAKPdB/yqg/i785vwz19fgKWt9b68P58HomszHy+3DINnBkU3Hl4U2KlQkGGoJRMKmWXxz8GYmC9xKRJxA8OOb7raWDqZZQk3DEB8DoQ0Nlb/nsvbbcgrv4aERBfHYmTkEF7ojau9KUntRh8VwGUYA8msVfSgsBZcPGcGPj2bhKGrLyq1hlNtXcsyjDKa5aBtvEZplj2wjgOC1eoaKBz3qjhhAEUyDB98lgErWP1v1yz05b0Bd2ZZ7PPzfzeQKtzIuU+uTKAkcw1e4QTrCu2ugUKw7NeaknD9HlQ3f+12kZ+MGwYAId06f35xZpl3QxTZxCTiBj7rTyptFubONUt29RtPDuGV3njjxmzVBMfFBOsuM8U41bG2hkklyF3eZkkxgnZkPB3gC0ctyzAM25/YjWpjDz8Ij8osy/+eIiHNKYAJWmaZb8KbFbr3AaObQPhV4Oc3sjKMpriBpriBv5w65zyWlezUyuefX/PQccPwTLPsz+dwy5JUr6G9SVyzHDPcNQDq1nGprLi1p9PyXOH3LCOHqHa9sRcE6y4zxcTsHWF/sjLB/XgsP28GANIry0CaZSu7XrwYp7P5wAWK7iywym+BMeZkVoO2YWiuC+Oer83HqotmKb3OKDcMnzTLfsNPGEQDXMYYlrY24FjvoPOYrAyDz2PfMsseF/j59TncmWXVazhvZhT3fH0BrvtK5b8xqxNo4f9F4G4YpllYo6WCZXsMZCWfgJwcwmu9cTU2Jwn+J5hEoi43DFUnhotm1yGss8Adm08H+BFzLVvH1UdCSGXz+GIgiTkzogAsGUbQNl9hjzTLgBUoWW4YwfpNMcZw38rzlV/HXeAXtHngFbGwXGYZAJa01uPAx31IZnKIGrp8sOzzCUfVZJZdJy2q90mNMdwnKA9ijCEa0jGcyUk3ucnlC24qPFgW+V74GKiujaJyCOu5SezYEcFnnzHMnWsFyjKSCl4syDXQ3d0MW7dGAQRbv1ybK2yF8GOZTE68OrYYQ9ewuKW+Zm9qKuiUWcbfL2uBoTPsOnjSeSyTywdOr+uVDAMozIegZde9Ij4NmpL4jYp7wNLWBuRN4LgtxZDVLDuZXb/dMBQTOrN4oObT5tMtw1DJrKrAE2TiuvWCkwYnlbWKFWVkGH4U7BZb0ckGttXanKQ27zIVoqJhKsW3rpyPOy49T/l1ao32RAzrO9pw1YKE35fiG20zoli/vA3/cbQXn/WPALAyF0HrBumVDANAYGUYXhEzdPBvv1Y34TFJn2UAjoPHsV47WHY0y5IyDN/dMFQzyzxQC74MQxa+4RAt8Cvl260iwwjy77lam5ME9xuZAgydOQ4YXkzeGy6chX+6fJ7y69Qahq7hhzdf5LTWrVXu+toCaAz494OfAoDTbStIeCrDsIPloDUl8QqNMWcMgrZp8oqQriERM6ScRWbXh9FcF8aHtm65IMMQDJQcNwx/vgOvguXGeBgM00Oz7Nd85pIJGc0ygFGNo1ISPvhOsBzgk6JqLRaszbtMhTDGXDvN4E5eojpobYjgHzvm4Dd/7kX32RHbOi5YP2F3QGEoHvdyn+GgjYGX8Ox6La9Pz2++FN+8bK7wv7OK/OrxZ55ZltUshzSEfbQELTQlUZNhhDSGRNzwLeiPG7oT8Pv1m44ZcptPPmdKZ5YFrOO4G4aPCQDV4rxSxYKAiQsuyJd8flCo3btMhcQ86KhDEF5x19fmQ2fAv//pZDCD5UnILActu+4ldZEQdK22vdvbZkSl9bpLW+vxSd8whtM5haYkzNc56JUbBgDccel5WHXRbOXXkYEx5rR89i2z7GiWxX2WAS9kGGH79fz5/MWd/Cptle1m48YsrrwyB6u/Kofhrbd0PPRQcE+Ha/cuUyEFTVzt3oyI6cPs+gj+8ZI5eO1oLz7vTwZuXoa91CwbtS3DACyv5SAf2frNErvI7y+nzjkdMoU1y5rm66aVB5gzFdunA8CWr7ejc7E/wTJQaNTjV3KKZ+dF11UeZH85lHYek3LDiMm1HPcKr4rz3n5bB1A8hgzPP68+R/2idu8yFRKlzDIxzbjzqvkI6Rr6hjOBy6p61e4aKFinBS277iXxsF6zDUm8wCnyO3VOyWfZzzn49YUJPL/5UqfFc5Bp9DlYlM0sf609gUhIw6uHe5zHZNwwwiENdWHdtySIV8V5uZzY40Ggdu8yFeLIMCh7Q0wTeHYZCF6gGNKYk29Qto4zSIZRFw751uq6GphdH8Hs+jCO9QxKF/itvKAJNy9pmYzLqwjNbrBSDTQ5TTn8kmHIZZZnxgysWdaK//3hKZwdzgBwt7sWm0/rlrfh6oVNQv/GK7wqztPLqKLKPR4EaJWdABVrIoKYLO68ch4idhYiSDBm6TsZ4LSrloUX+AXNa9pLEnFjVHMSQpwlLfU41lsIlkUDpTUXt+K/X6veZIYAWhoiqAvr0HzS4Mu6YQCW3juVzeOVI18AkCvwA4CtNyzC6qX+bL686uT37W9nMFqzDACm/XgwoQ5+EyBbHUsQk8ms+gh+/l9WON6oQYJnWlSL0uqowA//fHU7Nq0g73YVlrY1YP//7cNA0rqR17KziN/818vn4YYL1drAq8A1y6KnCwCwaFYdrlrQiF+9/zm+dcW8gnVcgGIHrzr5dXVZwfXzzxvI5ayM8re/nXEeDyIULE+ArEk5QUw2i229ZdAI6xryprrnJrlhALPqwphVF574iURZlrbWwwTw5x7LQo7Wev+YGTM8KVSURbWg/xuXzcX3Xj2K//PRl0hn84iEtMA51Yi2yi5HV1cq0MFxMbQqTAC5YRCEt4RD3hREzYxZe/06xTa/RG2zxNb7Hvl8AABllmsZJzkmuT6tvKAJ8xqj+J+HPkPKDpaJ6oC+yQkgGQZBeEtYZ57UAKyYOxM71y3DJXNneHBVRK0yqy6Mlvowjp+yM8u01tcsjmZZcsOkMYbbV5yH//x8AP/5+QAFy1UEfZMTQNZxBOEtYV3zRMenMYYbLpzlWzEQUT0sbW2Qto4jqoeYBx171y1vQ9zQcfzUuUkPllW77RGVQxHgBMSp3TVBeEokpNHmk5hWLHHp/2mtr12iHrhf1UdC+IeLWwFMbsMkL7rtEZVDd6wJIOs4gvAWrzTLBOEVS9sKPsVU4Fe7RCQ7+BVzx6XnjXq9ycCrbnteU63Z7ur4FJOIrEk5QRClWdxSj6F0gFs5EVXHUndmmdb6moUnx2QL/DjtTXHcsrRlUjPLXnXb8xKe7eZBfHc3w9atUQBJTxw2/ISC5QmIkWaZIDzlX69f5PclEMQomuJhtDZE0DuYIhlGDePYUXqwYXr075cov8Z4zJ1rort77HWKdtvzkvGy3UEPlikCnABHhkELKEEQRNXCs8sULNcuS1sb8G83LMKVCxJ+X8qEeNVtz0umY7bbKyhYngDKLBMEQVQ/f3d+E9oaIspt2IngomsM37hsbiAs3zZuzOLJJ5OYNy8PxkzMm5fHk0/6K3col9X2M9vtFSTDmADSLBMEQVQ/t3W04baOtsB1XCNqF6+67XnF9u2pUZplwP9st1dM/+2Tz3gl+CcIgiCmL4wxCpQJQoHpmO32CsosT0BzPIxoSMOcGf7asRAEQRAEQUxnplu22yuYaZrTVkySyeRw9uyw35eBZCaHSEijrANBEARBEEQVMnt2Q9m/I21BBUQNnQJlgiAIgiCqnmptLKICjQBBEARBEARR1Y1FVCAZBkEQBEEQBIHLLqtDd/dY0cG8eXkcOjTkwxVNHSTDIAiCIAiCIMalmhuLqEDBMkEQBEEQBFHVjUVUoGCZIAiCIAiCmJZttKcDFCwTBEEQBEEQVd1YRAUq8CMIgiAIgiBqGirwIwiCIAiCIAgJKFgmCIIgCIIgiDJQsEwQBEEQBEEQZaBgmSAIgiAIgiDKQMEyQRAEQRAEQZSBgmWCIAiCIAiCKAMFywRBEARBEARRBgqWCYIgCIIgCKIMFCwTBEEQBEEQRBkoWCYIgiAIgiCIMkzrdtcEQRAEQRAE4SeUWSYIgiAIgiCIMlCwTBAEQRAEQRBloGCZIAiCIAiCIMpAwTJBEARBEARBlIGCZYIgCIIgCIIoAwXLBEEQBEEQBFGGmg6Wf/vb32LNmjVYsmQJjhw54jz+9ttvY8OGDVi7di02bNiAAwcOOH/3wQcfYO3atejs7MRjjz0Gct4To9yYA8Czzz6Lzs5OrF69Gvv27XMef+utt7B69Wp0dnbiueeem+pLrhqOHTuGO+64A+vXr8eGDRtw+PBhAIBpmnjsscfQ2dmJtWvX4ujRoz5faXXxi1/8ArfccgvWrFmDnTt3Oo+Xm++EOrt27cLixYvR19cHgOb4ZNHV1YVbbrkFa9euxQMPPICBgQHn72h+Tx50T/QBs4b56KOPzL/+9a/m5s2bzcOHDzuPHz161Ozp6TFN0zSPHz9urly50vm7jRs3mu+9956Zz+fNLVu2mHv37p3y6w4y5cb8xIkT5tq1a81UKmWePHnSvPHGG81sNmtms1nzxhtvNE+ePGmmUilz7dq15okTJ3z8BMHl7rvvdubr3r17zc2bNzv/v2XLFjOfz5vvvfeeuWnTJj8vs6o4cOCAeeedd5qpVMo0TdM8ffq0aZrl5zuhzueff27ec8895vXXX29++eWXpmnSHJ8s9u3bZ2YyGdM0TXPnzp3mzp07TdOk+T2Z0D3RH2o6s7xo0SJccMEFYx5ftmwZWltbAQAXXnghUqkU0uk0Tp06hXPnzmHFihVgjOG2227DG2+8MdWXHWjKjfkbb7yBNWvWIBwOY/78+Whvb8fhw4dx+PBhtLe3Y/78+QiHw1izZg2NuSSMMQwNDQEABgcH0dLSAsAa+9tuuw2MMaxYsQIDAwM4deqUn5daNbzwwgu49957EQ6HAQDNzc0Ays93Qp2f/OQn+P73vw/GmPMYzfHJYeXKlQiFQgCAFStWoKenBwDN78mE7on+UNPBciX87ne/w7JlyxAOh9Hb24u2tjbn79ra2tDb2+vj1VUPxWPb2tqK3t7eso8T4mzbtg07d+7Eddddh66uLmzduhXA2LGnee0dH3/8Md59913cfvvt2Lx5sxMw0LyeHP7whz+gpaUFS5YsGfU4zfHJZ8+ePbj22msB0PyeTGhs/SHk9wVMNnfddRdOnz495vEHH3wQN91007j/9sSJE/jpT3+KXbt2TdblVSUqY06oMd7YHzx4EA8//DBWr16N119/Hdu3b8fu3bun/iKrjPHGPJfLob+/Hy+++CKOHDmCBx98kLJAiow33s8++yyt1x5TyXr+zDPPQNd1rFu3bqovjyCmhKoPlmWDgZ6eHnznO99BV1cXFixYAMDawfFjJv4cLtcgCsiMefHY9vb2OmNb7nFiLOON/UMPPYTt27cDAG699Vb88Ic/BEDzWpXxxvyFF15AZ2cnGGO45JJLoGkazpw5M+58J8an3HgfP34c3d3dWL9+PQBrHm/YsAEvvfQSzXEFJlrPX375Zezduxe7d+92pC80vycPGlt/IBlGCQYGBnDvvffie9/7Hi6//HLn8ZaWFtTX1+P999+HaZp49dVXceONN/p4pdXDqlWr8NprryGdTuPTTz/Fxx9/jEsuuQQdHR34+OOP8emnnyKdTuO1117DqlWr/L7cQNLS0oJ33nkHAHDw4EEsXLgQgDX2r776KkzTxPvvv4+GhgZHz0yocdNNN+FPf/oTAOBvf/sbMpkMEolE2flOyLN48WIcOHAAb775Jt588020tbXh5ZdfxuzZs2mOTxJvvfUWfvazn+GZZ55BLBZzHqf5PXnQPdEfmGnWrvfZ73//ezz66KPo6+vDjBkzsHTpUvz85z/H008/jeeeew7t7e3Oc3ft2oXm5mYcOXIEDz/8MJLJJK699lr86Ec/GlVIQoxPuTEHrKO8PXv2QNd1bNu2Dddddx0A4I9//CMef/xx5HI5bNy4Effdd5+fHyGwvPvuu3j88ceRzWYRiUTw4x//GMuXL4dpmnjkkUewb98+xGIxPP744+jo6PD7cquCdDqNbdu24cMPP4RhGPjBD36Aq6++GkD5+U54w6pVq/CrX/0KTU1NNMcnic7OTqTTaTQ2NgIAvvrVr+KRRx4BQPN7MqF74tRT08EyQRAEQRAEQYwHyTAIgiAIgiAIogwULBMEQRAEQRBEGShYJgiCIAiCIIgyULBMEARBEARBEGWgYJkgCIIgCIIgykDBMkEQBEEQBEGUgYJlgiAIgiAIgigDBcsEQRAEQRAEUYb/D+GtZulOTfWvAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "snN_Flr5DWQN",
-        "outputId": "3c40a98f-b700-41e7-bc8e-36454edaf950"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:]))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "WARNING:tensorflow:Layer lstm_2 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.\n",
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 24s 409ms/step - loss: 0.3414 - rmse: 0.4277 - val_loss: 0.1861 - val_rmse: 0.2886\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 20s 400ms/step - loss: 0.1268 - rmse: 0.2198 - val_loss: 0.0671 - val_rmse: 0.1290\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 19s 384ms/step - loss: 0.0474 - rmse: 0.0985 - val_loss: 0.0481 - val_rmse: 0.0667\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 19s 388ms/step - loss: 0.0288 - rmse: 0.0438 - val_loss: 0.0330 - val_rmse: 0.0363\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 19s 386ms/step - loss: 0.0228 - rmse: 0.0275 - val_loss: 0.0358 - val_rmse: 0.0367\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 20s 393ms/step - loss: 0.0210 - rmse: 0.0251 - val_loss: 0.0314 - val_rmse: 0.0319\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 19s 380ms/step - loss: 0.0198 - rmse: 0.0234 - val_loss: 0.0297 - val_rmse: 0.0307\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 19s 375ms/step - loss: 0.0187 - rmse: 0.0224 - val_loss: 0.0242 - val_rmse: 0.0263\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 19s 388ms/step - loss: 0.0179 - rmse: 0.0211 - val_loss: 0.0238 - val_rmse: 0.0248\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 19s 388ms/step - loss: 0.0171 - rmse: 0.0198 - val_loss: 0.0231 - val_rmse: 0.0240\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 20s 397ms/step - loss: 0.0163 - rmse: 0.0189 - val_loss: 0.0237 - val_rmse: 0.0245\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 19s 387ms/step - loss: 0.0187 - rmse: 0.0226 - val_loss: 0.0082 - val_rmse: 0.0103\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 19s 379ms/step - loss: 0.0154 - rmse: 0.0181 - val_loss: 0.0078 - val_rmse: 0.0094\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 19s 383ms/step - loss: 0.0148 - rmse: 0.0175 - val_loss: 0.0050 - val_rmse: 0.0064\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 19s 378ms/step - loss: 0.0136 - rmse: 0.0164 - val_loss: 0.0052 - val_rmse: 0.0060\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 19s 381ms/step - loss: 0.0138 - rmse: 0.0168 - val_loss: 0.0067 - val_rmse: 0.0081\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 19s 382ms/step - loss: 0.0135 - rmse: 0.0160 - val_loss: 0.0059 - val_rmse: 0.0070\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 19s 381ms/step - loss: 0.0133 - rmse: 0.0160 - val_loss: 0.0035 - val_rmse: 0.0041\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 19s 387ms/step - loss: 0.0128 - rmse: 0.0155 - val_loss: 0.0097 - val_rmse: 0.0117\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 19s 384ms/step - loss: 0.0128 - rmse: 0.0152 - val_loss: 0.0044 - val_rmse: 0.0051\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Ay5m27doDsTt",
-        "outputId": "b8ae8544-0723-4816-b0c7-4ad689b10506"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "6ZFP49W4D2wp",
-        "outputId": "faebe156-06e4-4b1d-fa8e-e6fbe45d95b5"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "099fdbb3-cc5c-4831-b140-9732b75ff81d"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 22s 30ms/step - loss: 0.0048 - rmse: 0.0058\n",
-            "MAE: 0.005751027259975672\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "oDXXSFLy07gH",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "6152b870-f63b-4142-9ec3-c774ed9b481c"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "174/174 [==============================] - 5s 31ms/step - loss: 0.0043 - rmse: 0.0052\n",
-            "MAE: 0.005751027259975672\n"
-          ]
-        }
-      ]
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "V4G3MxsJMN4m"
+   },
+   "source": [
+    "We are importing the libraries:\n",
+    "\n",
+    "- TensorFlow: to process and train the model\n",
+    "- Matplotlib: to plot the training anf loss curves\n",
+    "- Pandas: used for data analysis and it allows us to import data from various formats\n",
+    "- Numpy: For array computing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "W46t-S6TMZVG"
+   },
+   "source": [
+    "We are reading the CSV file using `read_csv` function and storing it in a DataFrame named `df_Ellis`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 521
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "94530f09-ebe1-4361-9b23-e21ec5f0f649"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "727ad3d1-e00a-4d6e-9ce8-6859b01fa6ce"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "c4a79b59-30eb-41ba-9d34-2c7cad07d9f2"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "f96a17fc-a509-4c29-e57f-1dfda73d8df6"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "4a3a36e3-c071-4353-cd86-0ab6b1afba0e"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "385a467a-5cb2-49e9-ba49-dd68c7cfb6c6"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "73cb3b63-1038-48d3-ff11-1a2dda4941df"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "548bd638-42a5-4cc4-c073-01f07ad9a4cd"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "05a92d00-674b-4e12-c9d4-4a70b2d19768"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "fd00e983-d38e-4d4a-f1e1-23ab6525ecc8"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "c9204a3a-f6a7-44de-a499-32280bf3e02b"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "ef830bbd-5c4e-4dc7-c1ea-3d112d7d809e"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "8057191e-6d36-429f-d649-12689677409a"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "42891ad8-9f74-4c75-a750-776d3d6b8ceb"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "e8cbfcc9-59f0-459a-a451-fd2d49c31973"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=False, input_shape = x_train_ss.shape[-2:]))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "single_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "21b2a7ee-356f-4ea9-b8e7-ba034e91c36e"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "b9f0c285-968c-4ada-828c-15f7d3a025c9"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "b91b2190-3709-431b-bf10-226a10d5b1ce"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "c9d7e6dc-0bc7-47c7-d46e-b3995916a961"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "589003e9-f035-4c9b-bcf9-3377d047f0ef"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "7d37e336-cbae-4183-95c3-421271831727"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "3c40a98f-b700-41e7-bc8e-36454edaf950"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:]))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(16, activation='relu'))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "b8ae8544-0723-4816-b0c7-4ad689b10506"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "faebe156-06e4-4b1d-fa8e-e6fbe45d95b5"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "099fdbb3-cc5c-4831-b140-9732b75ff81d"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "oDXXSFLy07gH",
+    "outputId": "6152b870-f63b-4142-9ec3-c774ed9b481c"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "LSTM-correlation.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb b/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb

index 3401b39..75c301d 100644 (file)
--- a/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb
+++ b/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb
@@ -1,1587 +1,833 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_EvHebagXgW4"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "stacked-LSTM_Correlation.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    },
-    "accelerator": "GPU"
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "d11aafe6-20e9-4719-a751-0da58234f8c2"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/gdrive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_EvHebagXgW4"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "d11aafe6-20e9-4719-a751-0da58234f8c2"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/gdrive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /gdrive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "8c28f578-4405-4a27-81e4-c0fd00475b96"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 3
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "179123d5-8aec-4dda-a400-9096dec19dd8"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f910537d0>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 4
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "75071f5e-5942-4939-a33b-2dc8780e260c"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "af5ce749-d888-4cae-ddcd-9a5a5ce6e558"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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xqRM0EQ8NiKOGR0DW0+kFMDgwF48DcTVI6MiIhIG9jjh6iHLSkVeH97FvJr2xBf1IDHvzmKpnaL2mERSY55HyLSi9SyJkfSp9vbW9JVioaISBmc1IvEYOKHqIe3f+7dUOyw2LA+vkSlaIiIiMibpJJGp+eMFhawJyIi6sbED1EPdW1mp+cSOEyKghjvBhERUagRBAG7M6uweP9xpJc3qR0OEZHqWOOHiCgECcwIERGRTs3bmonlBwsAAP13GrDk0Wm48cLTVY6KiEg97PFDpDO8nifSL9ZmIiLyrM1kdSR9AMBqF7BoH2c3JaLQxsQPERFRkGhksXkiIo/iCut9eo6IKJQw8UNE5IEgCCisbUNZY4faoRChusWkdghERKQQQRBQVMc2CLlm57h9EoE1foh0hiNBpGOy2vDsd8cQlVkFALh/2nh8cO+l6BfGT5mIiIjkY7ba8ez3iYjM6GyD3DdtPD5kG4R62JtVjXNGhasdBgUJ9vghTcmvacWi/ccRkVCKDrNN7XAoxO1Iq3QkfQBgQ0IpjhTUqRiReALvBhGRzunpMFdU14bF+49jfXwJ2kxWtcMhFe1Ir3QkfQAgIqEUh/ODqw1C8pq3NVPtECiIsMcPaUZ6eRNmLD6M1q6GzsaEUnz31BUI450NUXTU/lXdKxtTnZ77cHsWNv/9WhWiISIiPcutasF9i2LR1NFZy2v90RKs/euV6N+P92lD0X9+dG6D/HdbJrY+d50K0RBRsOOZhDRjdWyRI+kDALH5dUgta1IxIgp1HRbnXmflTUYVIpGewBRhUDrj5CFqh0BEMvnuSLEj6QMA8UUNSChqUDEiUlOrix5fFTppgxCR8pj4Ic1Ye7TE6bnVh4tUiISISJuGD2ZHXSK9WhlT6PRcz2nJiYiI/MXEDxERERERERGRTjHxQ0RERERERESkU0z8EHlhYG1pCmKs5ENEesfzNIUK7upE5C8mfoi80NM0sRQ4NrqIiLSF52kiIiLPmPghIhKB1xekJl7gEhEREZFYTPwQEYUgJhCIiIiIiEID54UlIiKv7HYBWZUt6BdmwPmnh8PAohpERLLjoZaIiKTAxA8REXlktNjwl1XxiM6tBQD8fsrp+OqhX2NAP3YaJSIiUgoTgUTkL7baibwItpMsh/BQT1LsDzvTKx1Jn87HVTjY4zEREREREWkXEz9EXjCRQj0FWR5QEv/+MdXpuXd+yVAhEiKi0MI2CBERSYGJHyIiEUKxDd5utjk9V9tiUiESbRAEAXa7OnuCEJJ7IJFnArMj1EMo3qAhIvKGNX6IdCbYhqYRidFstMBqE3DqsIGqbH9DfAk+i8xBh8WGx66aiOdvPo+FromIiIhI05j4ISIi8RTOdQiCgI92ZmPJgXzY7ALumXoGPrrvUvRXsMB0XnUrXopIcTz+Yncupow7CbdOGaNYDEREFMrUudFQ2tCOorp2TJ1wMoYO5OUjUTDiUC8inWGPd9KjYyWN+Hrfcdi6hlj9eKwMW1MrFI1h0f7jTs+9u5W1johIPuxQSGpbfrAA1364Fw8vO4LffrQPedWtaodERH5g4ofICza6KJjppSbMZ7tynJ57fVOaojEkFjc4PVdS36FoDERERErpMNvw4fYsx+PaVhMW7s1TMSIi8hcTP6Rp7L1CWsM8YCelP4f8Guc7jM1Gq8JREBERhY7IzCqYbfZez/14rEylaIgoEEz8EHnB5BORM6V/Flr4Gda3mdUOgYhcYIF1InkYLc6zehJRcGLihzSNbTnSGi0kIEKRFhKwje0WtUMgIqIQxnYxEfmLiR8iohAUaCJF6banXmoVEZH0BC1khomIiDSMiR8iIiIiIiIiIp1i4oeISIRg62Wtlxvhevk7iIiIiIiUxsQPkRccT03kTOliqsz7EBERERH5h4kfIiIiIiIiIiKdYuKHNE0Lwzu0EIM4QRcwERERkSTYCiIicsbED1GIazZasDe7GlmVzWqHEhTYoCQ1BV8imoiIiIjU1l/tAIg8YX0deWVVNuO2z6Mdj/912wV45vpzVYyoU1ZlM/Zn1+CskcNwy0Wno1+YtDuCzS4gMqMSRXXtuOHC0Tj/9OGSrj8YcHp0ItILHs2IiIg8Y+KHKIT934JDvR5/EZWLx6+eiKED1Ts0HMytxayVcbDYOpvyf778THxw76WSbuNfESnYmFgKAPg0MgffzvoNrjpnpE/vZS6yE5OyREREyuKp1z92u4AfjhYjuaQR0yeeivunjVd8kgoitXGoF5EXWj8vVDcb8a+IZMxYHIvlBwtEvddosfd6bLLacTi/TsrwRFsSne9I+gDA2qMlaGgzS7b+mhaTI+kDAGarHUsOHJds/URERFIx8FJfNH5i1Ne8rZl49ac0rI8vxb8iUvB5VK7aIREpjokfoiAmCAIeXRGH9fGlOFJQj3d/ycDKmKKA1plc0iRRdP45kFPj9Nze7GrJ1v9zcrmL9Ttvk4iIiIiCm80uYMWh3jdGv9jNxA+FHiZ+iIJYWlkzsipbej23xUViQwwtngyl7HW1M71SupWFMK3cUT3nP9uQX9OqdhgUpCw2O9LKmtBitKgdCgVAK8cjObAeG1Fg2sxWtUMg0gQmfoi80PIsOmnl8vTOaTNp6yQp5XcQV1Av3cpIdTa7gH9FpKgdhmI0fDgKOvk1rbjuw72488uDmPpOJH5JCSxpTkRE2qPnxDCRGEz8kKZpOemiBRJPduXgajiUmvr2anKlqtmIFQcLsCq2EHWtJvmD6lLdtd1vYwpRq+B26YT4ogYIPFiQSJ/sykZlsxEAYLULePWnNNjs3I+ISLu0XndSi1jEmagTZ/UiApBS2oh1R0vUDkM0uYo+ljd2yLJefy05kI///GGy29erW4y4Z2EMyrriXnmoED89cw1GDB0ga1w1LSb8qed2YwqxSYHtiuEuH6K3PIkgsEFM4mxL7T3ss6nDgoSiBvxm0qkqRUT+0tnhjIgkxKYBUScmfijk5Va14M9LDqPdbHP5utYuJgVBwJID+diRXoljxY0ybUOW1crm56RyR/IFAPJr27AzoxIPTD9T3u0m995uQW0bdqRXYMblE2TdrhRe3JCMiiYjbp48Gs9cfy7C5Oo+ppAg22VJo4wW1+cBIiIKTlprxxOphUO9SNOUOFh/G1voNumjRSsOFeL97VkBJ33MVrvb14KtmOS8rZnOz/2SIft233WxjXe2iN+uIAiol3DKel9sT6tEUkkjPtmVg6/3i5/OXs6u0w1tZjz17VFc+tZOzFx+BFVdw3E8sbvIVgqCgOM1rbB7GL7D9iBR4GKP1+EPX0Rj+rxIvLc1w+NvjsThdO5EgXH3G7La3LeDldLUbtFEHBQa2OOHQt6aw8VqhyCKq2SDP/ZkVbl9TQ9t9mD5E44VN2D2mgRUNZsweexJWPH4dIwdMUTRGD7emY1nbzhX0W168sqPKYjKrAYAROfW4vm1SV7f0zfvsz+nBo+tiHM8fv+eS1y/z/8wSYMEQUBBbRtsdgHnjg4XnaDk/iBeq8mKJ1YeRUdXb6ml0QU489ShePSqieoGRkQE9zeRjVY7wvuFod1sRWZFM84/fTiGD1ZmqH6byYpnvkvE/pwaDB/cH//90yW467JximybQhd7/BB5EWzDnnx1xMPsVnr9m7Xo+XVJqGruLAqdWdGMt3+Wv6eS1u1M752UjM2v8zoEp28vtZ5JHwD494+p0gRHmmW12fGXVQm48dP9uOV/BzBj8WHRQ7eO5NfJFJ1+bTpW5kj6dHtjc7pK0RDpG3uASUcQBCQUNeCK93bj3q9jMW1eFPZlVyuy7cUH8rE/pwYA0GK0Yu7aY2jV2Iy6pD9M/BCRk2Ab6uWSTH+ClCOcCmrbUFTX3uu5HemVbpbWFqWbnhYvXaF7Jisrm7wPDQtWnL3MvajMakRlnkgaxhXWIyKhVNQ6Shu0Vdg+GGRWNKsdgmRyqlrwRVQuvjtSxIswIp0TAPx3WyZaun7rZqsdb/sxXN8f83fn9npsF4CfEsWdr4jE4lAvohDl8fpRw9eWZY0dWB5dgMZ2M+6dNh7XnHuaotuX8rq71Sj/hYVcSTwN7yJoN/OCLRTNXpPg9Nxrm9LwyJVn+bwOFgENXamlTZixJNZR8++nxDKs+9tV6Bfkhe+JyDVBABKKGno9V1DbhsZ2M04eOlDxeOIKGzCTQ2RJRuzxQ5qmhZvboXgh4KpQrhZ0mG2YsTgWKw4V4MdjZXhsRRzi3AxZ0+ZfQP4yWnzv8RMWij9aFeix9xH3ndC14lBBr4ke4osakFTS4OEdytBFD1wKXnre/dz8bTaVCl1uSS5XZbsUOpj4IdKw6majbCcgTxdtLUarJru578qo7DUUw2oX8OWeXA/vUJ6Yb0uqBn2z0aL496W1y+OeyUo9X7vLOZuarxKK6nHb5wdw6Vu78HJEiscZAomUIEUO8qdjZU7P/RBXEviKiSTk6RRgtdlR3aLfoc5SY1KVQg2HehFpUHWLEU+sPIq0smacNLg/5j84FddfMFrSbbR5mMJ+7dESRCSU4slrJ+GV2y/UxMUmAGxJrnB6Ljq31uWywdAbIdCcnt0u4K0t6VhzuAhhBgNmXTMR//nDZM18X0rq+VGy14Z8zFY7Zn1zFM1dwxTXxZfgjFOG4LmbzlM5Mmlw1yGtYTFf8sWu9Eq8sD4ZLSYrpk44GcsfuxynDpNvuJIgCEHf1ghzM4xT+63H3ubvztXNOZjkxR4/RBr08Y5spJV1FsxsNlrx/LokyXv+tBgtHl+32gUsPpDvcfYvCkygyam92dVYFVsEu9D5fS2NLkCsQrMSaa29J4RIjx+17c6sciR9un0WmaNSNNLjRXZw4m+eQpnJasPctUmOIsXHihvxeZS8x+UguLfm1cB++rgM/iwyB2llTWqHQUFAH3s86ZYWGnNqnNw29JmJprHdgtjj0l7Q+9or4pOd2ZJuVymuvrbyxsBn7JFynwx013ry23in5z7cEZzfV6B6fpbBfhdSywr7zEKnN9x1iEjLBKHzRseW5HK8tzUDkRlV2JtVjQ5L717cq2KLVIqQ1PDVnjy1Q6AgwKFeRBKpazXh633HUdrQgdsvGYO7f3WGpOt/bu0xJL5+i2Tr8zXxk1PV4vJ5QRCw5kgxDuTU4PzTw/HsDedi6EC5DymBpUr6NozUFkhS0d2U5SmljZJtI5j0Lu6sXhxy89RLTBAErDtagj1Z1ThndDieuf4cDB88QMHo1HXS4P5OvZHE0vO+IxcpDzFljR1Ysv84alvN+NPUM3DzRadLuHbxtLA79D2mk3d6T/5/uisHX+3tvNBfGl0g75AuN79wPTctgnHvKahtUzsECgJM/FBIs/swfKpv+8FmF5ymdxUEAY+uiEN6eefwrB3plRAE4P+mSpf8qW8zo9nL8CwxfG0XuWtALdqfjw93ZAEAIjOqkF3ZgmWPXS5VeLKQ4mQuNpFiswsIM7j7HP1rOlltdjy49LDL10Il0eOkx98dqsN1vo0pxFtbMjofZFQhtbQJa566QtJtaLkYphSRheq+owUmqw1/XhKLkvrOnpnb0iqwctZv8LvzR6kcmbrK3ST5KTTZBcGR9OlW32ZWPI7OmxDBfbxsczMphnbPckSB4VAvCmkxIoZP2ewC3tychsve3oVrP9yDnemVjteSShodSZ9uH3UlRaSU0WcbgQj0xPZhn78vKrMata2mANfqTWCNDCnuAhp97DUkCAI+3JGFqe/swtUf7MFPx0pdLONfDNG5tbq9u+Nv3aO6thP7npheG3Wy77PKefuXjF6PD+bVorRB30OztKS8scPn4wM525tV7Uj6AJ3Hx892hebQVSJ3mjqkuwEY6rIqXfdo90d1i9Fr7UwitTHxQ5omd++F+bt9nwr8h7hifBtbhFaTFaUNHfjb6gTHXRZXBZDluEsn5eeRXOJb93ExuRK5khEnYvD9A3D1WUkxjKPZaMX6o+6n+O3e7paUCny97ziajVZUNBnxz/XJKO5TH8Xfr3NfdrWf79Sv4voTn62YBJ8v0zVbbXY8v/aYX3EpydU+n1UhXcNWKwRBQG5VCw7n18FklTbREuZHq6ip3YI/fBGNqz/Ygwtf34GIBOckbyj6JaVc1PK7Mqqcnksu9a1gacj2dKSQo5VdXStxqM1ktWH26uwemB4AACAASURBVAT85r3dmPpOpOxFtYkCwcQPhbS4Qt9nrHptU5rTcwu7uts2tiuT5Q90mEVWZTO+jSlEXEE9ShsCL3QcbKQaxvHKjylo8vKdv/1zeq/HggAsO5jv9Jw/GjVxx09bXbxHDhvk+Hdute/JjoN5NV6X2ZpagU1J4i5i9UrsPlvZZMT3R4qxK70SZqtdgu0LeH1zGm753wH8eclh3DH/IGpapOu15U+vwFc3pSKj4kRvzBc3JKPVzRCCUPLC+mRRPaC0OMxOK6VivJ1vSLz6NjM2xJfgl5Ryt0N+NEnhjIu7Yz6TrZ1+TCzDjq4RAFa7gM+jcpFVKV3vfCIpscYP6Vp2ZQs2JZUhfFB/3D99PEYPHyzp+pcdLMBrd16EDfHeew2obWd6JZ75LlHyaeF70lJDwFUhZ6ka8XYBiEh0fVe/ext1Lsbcp/S5e+1uWFNJfTvOPHWo2+1vFpGE0NBX4hN/d8+R4SeKWy7an+9hSfFe+8k56Uve5VW34oHFsY6ekTdPPh1LH50W0JDL4zVtWHO4uNc2vj9SjLk3n6fazv5LSoXTc0sO5OOft5yvQjTaYbLaEZlRhbsuG+fT8lpJsrhTUt+OiIRSCIKAe6eNx1kjhym27Q6LDSMQOoXa5VbdYsR9X8c6eopOnXAyfvjLlRg8oJ/KkZEWmKx2fBtTiKK6dtx80Whcfc5pvV632wX8ZVU8dme57n29cO9xzH9wqhKhEonCxA/pVm5VC+79OsZx53VjQil+ee5aWWaecnWRL4sALmwW7T/uV9JHTFvcLlPmR0sJpW5S1DNy92dd99FeHH31ZowaPsjNEvKqaOrAgr15qGg04o+/8u2iTSruZpHzpudnWVLve10bX/atFg3dDRb7U1Dzp/NDXHGvoqNRmVXIrmrBhWNO8nudSw4cd3ruf1E5nYkfCUg1q9dXe3JDPvEDiOudqOW8T02LCfcvikVlc+cQ7u/jirFlzrUYO2KIZNtIKPK9BzIF5uek8l7Dg48VNyL2eB1uuHC0ilEFFy0X+g/UM98lOsohfBNTgMWPTMOtU8Y4Xj/7P9s8vp+19UirONSLNM3fO4B2u4Bb/negV3f7/No2RGVqrzaKIAiw2HwbAhHIafZYsfxTwvr6d4h1/7TxsqxXaX2/P09Jh5nLjzj1CDJb7XirzxAyqdnsAh5aegRrDhdjd1Y15q5NcrmclHfnew4B8ncfEgQBX+7OxU2f7hNVa0qLSUW9WH6wwOm52z6PxuzVCahu8a8GWkuA07V7I9VwIxk7VmqOVIcCLfb46d4fNieVOZI+AFDbasb6o9LWcvp6n7Q9FdVkttphsdn9LtYvt3lbM52ee3drhosltUcrCRdXX63VZvdptlyt61kDUxCAz6NO1AP1ZciyFBOJEMmBPX5Il/70dYzL5785VIA/+tjtvNv2NGlqU7iyI60Sb/2cjoZ2M/542Ti896dLMLC/+3ysGm0oMSewI/n1uO486afeHX+K+2FPYnj6UwRBgMFgQJvJitpWEyZ4GGrlr4xy34Z6AZ2zTSQWN2LaWac4nvssMgcrYwolj6unmOO+zRgmxb7Ybrbin+uSsTurCmNHDMHH913qd1f7tXElTlPc+oLtM+XtSK9EXZsJG2ZfLfq9ch8DpdofHpiuj2S1L6T6SrRY46fbJy5mF5OypxnQ2SPOnWA5TmWUN2POD4k4XtN5DhnQz4D377kU9wXBzZuexxZBEFBc347Twgdh2CBtXSop3Q70ZXOCIOCzyBx8c6gQA/oZMPem8/D4NZNkjy1Qvv6setZw8+WmhVQ9R8UIlmMEqUtbRzMiibibscrfE+bKGOc7193KG/0rktzYbsacHxJhsXUGtSGhFBeMGY6nrjvb7XseWX7Er21JrdnNlJX7c2rw4u8vkHx7Up3QPCWxBKFzaMqbP6c5vhNP/NmXLDbBkWDyRUJRfa/Ez6L9zsNcpBZzvM6n5aQY6vbF7lxHUcTi+nY8vOwIwvz8sv1J+gBAh5nTb6vhaGEDalpMooczyn2329/9ry+p68lpSUObGYnFDThnVDgmnqZcnRs1dO9vUu0XevfMdwko7DF7pcUm4KWIZFwx6VSPdeuk5k9Po+73NLab8dg3R5Fc0oj+YQa8+ccpmHnlWT6vx2S1IaGoAYMH9MNl409GP4mzAFrsT7Mnqxpf7jlxDn5rSwYun3QqpowboWJU6lEjia3RznWKqG8zI7GoAeefPhwTRip3nAlGTPxQSGls968Wz3+3Zbl97bqP9vq1zs1J5U4JhnlbMz0mfrTC3XALrXRBdsfTqbipw4LXNqUGPESj3WzzOANLVmULJo/trHHibVN6PJE3tVuwK6MSdkHA4j5FmK12AUo3a/NFDAsLRlIPtZCy92NDu1l84keHv4lgklLaiIeXHXGcA9666yKVI1IGEz/e5VW39kr6dBOEzmGfb/1xigpRibf4QL7j5qHVLuCNzWm469KxOHnowF7LxRXUI7mkEdMmnoJfT+i8QdNstOCRZUccEzncPHk0vn5kGgb0k66yhtLD59zt+T3DcDV07svdeVg0c5pkcTS0mRGZUQUYgFsvOt3p+9AUPw8Xp4Vr+G/SqMTiBjy6PM5R2uO9P12Mh6/wPVEbavxO/BgMhkcArO56+BdBEJZJExLRCWLOb6mlTfhoZxaic2vdLuOqURIof2fJElOHRE2uzl/ubmC1ylR/Q6omt6fG+8bEUlFJH09TSN+/2PVQQ6Cz8dLNWzFsKZp3zSKnfpfz8qapw4L7F8cgp6pVxq0Ev6iMKuzNrsa5o8Px0BUTMKi/dmaaiTnu/vjaU1yB90K1jZyiOujM353XK/H/0c5s3HHJWEnWfbxGe8eF7jv3zPt45+nGWs+hMlr39b7ePWsFAYhIKO11U+6bQwV4e8uJmkAf3nsJZlw+AVuSy3vN3hmVWY24gnpcc27vWaGCiS/tEFft2eRS6epKNrabce+iGOR3DSFcMjocG2dfjRFDlZ/pzpce2/4eLgLJ6YXqMWr+7txe9Vw/2J6FGdPPRH8Jk6164lfix2AwnAngKwCtAMIljYjID2llTbjrq4NqhyFKUV1wJH66tZms+F9kDtLLm3H2KNfd+wvr2kUNZeqr3s3saJ9G5qDZaEG7jMNyalvF9Qbb6GY6dwA+JzasXjJNUtzY2+2hboQrcjYe9mZVM+njxYb4ErwUkeJ4HF/UgAUP/VrFiHo7Wtjg03IrXBR27isyoxK/mXSqqO27+0k8uOSwJLOvSdWzQ0DnsM7lBwuwJ6sa54wKxwu3nq/tu9Q+6FuHpt1sw9FCaWajii/ybd9SUndynj1+9M/T6bauzYwOsw2fR+UgubQRh/N77/Nf7zuOGZdPwKs/pTm997/bMrH1ueski1Pp2snu2iHeenhL2TFpZ3qlI+kDdPYui8qswr0arR3l7+EikMNMqPaG3Zdd0+txi9GK5NKmXmUS6ATRiR9D5xXdNwDqAPwI4EWpgyISa1l08MyGYbN3zuK1t8/Bqtuz3ycqHJFv/rEuCbsyOhv9sfnu68BkVDSjpsWEj3dmo7HdgieunYQnr/WtyN8rG1PcvrY02vuFZCCU6j7dcyulXqYdt/aY4Sqv2veEyZbkctzVVcT89c2+zQJ255fR+MfN8k4//e8fU2Vdvx58tLN3EdmtKRV4+48mnBbeNSRKo407o8XWqzB3d+0mT5ZGF+BoYQNunjwae7KqUdtqxn3TxmPOjee6TR67qy3l6ZgkhtiGt7sen20mG5YcyMf72zuHCcccr0NWZbNfBa21zlsC2xfbUisCer+33pP+SizuTEbJXazVWxuGaSfPOsw2DB4QJutsSi9GJGNriuv91FNvcrlnIpSbu49UyUTDyxud2w4vb0xRJfHjyx7mf6LY//3XaLUFdONVT/wdiREK/Onx8xyAGwFc3/V/ItVtSir3eVm7XUCYGiX30Vk82NvFr7uGhZpajBZH0sebH+KKseZwsePxu79koN1kxRPXTsLA/mHIq27FpNOGOc3eVNdq8nkbYuIePti3rsByXTh44m2LB3JrMOem8yAIAh5bEefzet/bmokLxwzH09/5nkRMK2vG7DUJCJdwBhOT1Yb8mjacMyrc42x1dIKrIYSpZU244YLRfq1Pqb364jd34o5Lx+Lj+y4T9V0nlTQiqUcx/s8iczB2xGDcP/1Ml8sfK5Zu+IArYs8MsW6Kof+SUu7Ui/BoYQOK6tpw1kh9FUSW4tD5323ONUJ8telYmcsaI1Lonp1Kzh4/icUNXuMP9ssYuT69NpMVc9cew56saowePhgf3Xcpfnu+fzOLetqPO8w2v9tmFU3+TQBCCpBpx1Qj91JU144r39+Nj+67DL/z8zdA+ieqJW4wGCYD+ADAF4IgHJAnJNIKk9WG6NwaxOTVyjaduRqkuDvpj2PFDUHZ48FgEDcMqmfSp9unkTmY8uZOnPfqdtz+RTSmvRvpVCvk+yPO7wvUJW/t8nlZpXaLno1Lb3cluofVxBc1oEzE7HGVzUbMXZskqpcQ0DkDS4OfdVfyqluwPbXCMdVpQlEDLp8Xhdu/iMb0eZGOO+ekT1a7gM1J5fg2pjDg3nOvb3YeLqEUsTcFfk4uc/m8u2NmLoc6ulTa4N/FcXWLEc+vS5I4Gmdy3kX/1MVU8X1lVbbItn2pePrVy3V6/XJPHqIyq2EXOs97T69JgMkq/ZBwsbXyevJlltBgpIe/KseP35UvhwI1ZvUCgKpmk2y/AdIHnxM/BoOhPzqLORcD+I9sEZEmtJms+POSw5i5PA4PLTuCmcuPwGhR/kCipx6Lf1rovuCvtkl/Cmsz2/Dapt4Xd3ES1Ynoq+cJ8EiB++Egy32oSSI1b8mmKeM6Z//ypxC4EsU0m7oaw98cKsDNnx3A098l4vqP9yGhqB5vbE5Dc1cX92ajFfcsjEGHCscQX4hNkCltXVwJvo0pRHWzUe1QvHovgJ4b3YwW9W40iD3Wia0NRtJaE1ukyHbk7CR8KM/7MMUyEYkxu13ArvRKLNyXh7SyJu9vCGKL9vcuxNxmtmFXurQ9h0Od2xo/Oigqs6BPIW+pBFrjJ6O8GV/vO44daRWwi7wr2W62YSd/A+SGmB4/bwCYCuBxQRB8PgMZDIa/GgyGeIPBEF9T47qmCWnProzKXl3qjxTUY192tYoRScffKd1DldlqkyUBl1/T1muGK7msO1oCAFhzuAhz18p/Z9ibngURvTWcbrqwc3jPgRxtHjsfWnoYzUYLPt2V43iu3WzD51G5SC8Pnllc1Ej6ibEjvRJv/pyO/1twCFUikz/BmjtX7aIiWD8wFZWrOJTluEKzY6p9ievpHGy22rEsOh8vbkjGz8nleGtLOv66OgEf7cjG3QsOYU+WMheBnn46Sv6sKpo6/Oqh5bFYMY8LTvRQRsXT7Kzu+HIr1N8eggYA+3NqcPeCg/hwRxZmr0nEq5vE94Ct5PBCcsOnxI/BYLgCnb18PhUEIVbMBgRBWCIIwnRBEKaPGsUxh8Hi5QjnIUl9e2gEq5+Tfa8HRJ29Nfzthu+NxX7izr5c13ndF/UL9ubJs4EAePub+4V1HqJ/0WDdJwBIL2/GV3vyek2lCQDRub5N+a0VP8RJP8xQDuVNRrSJnNkuWNvm/g45DJRaXfSDmQ5u/HvlzwWilDztlS9FJGPe1kxEJJTiuR+OYVWPXlA2u4BF+4Jn8gsp2PzsMCjXfjxyWHDP5Ocuh5FT5XmYlLdZvwKl5REBgYS25MDxXsMDf4grFn3DmrOnkjteEz9dQ7xWAcgB8LrsEZEmmF2cOdWYmUCOE7FJR/WKlPLwsiPyrFjo+U95Ggnd9akqmrQ3TMaXgtJiu/kqbcmB0LqoEKPZqE7yQg/E9mySipYvJvxlswtOydmeBEFwDNskbXK3Xza1W7DZy+QWcg2j1io1yhJ4cmqQJ37cNVPuXxSL97ZmyDKDktlqR4fImxxK8anGTwDnEVdDP8XeTItIKPU/ANI1X6ZvCQfQPcev0U33taUGg2EpOos+Py9VcERy0MO4ZL3o+U3YQzAf563Q+Pa0CnwTo+1hSOQsr7oVf10dj/yaNpx/ejiWPjpddzM5yS21rAmTx56k+HbFtte1nifamlKBVzelornDgpsmn475f56KIQNPzKiYVdmMv61OQFFdOyaPPQlLZk7DmacOVTFicsVdT7S8Gu3c2ddKy6qx3RxQMWZXAmk26jGZ3G1pdAHGjhgi6ToX7M3DV3vyYLMLeOiKCXjjzoskXb8SpJ4FUCu/LQp+vgz1MgFY7ua/Y13LHOx6LGoYGGmTVuuJSIV5H+3I6FEHpl2mu3QTNXbB3b3/lTV24OOdnmdzyapsQaNKQ15IHJtdwNHCemxLrcBfV3UmfYDOLtcvb0xRObrg03OKdyXp6SKt2WjB3LXH0NhugV0AIjOqsDS6dw+9f65LRlFdOwAgs6I56IZ0+zvFtq/kLOosilbi8JM/ExT465RhA/FZZI73Bfvw1DbcnuZ9Pyvu+h1JpVKDvZRdeeeXDMnWlVLaiI93ZqPDYoPZZsfKmELsyqiUbP1K2Zddjc1JZciqFFfrUOqEEVFfXnv8dBVyfsrVawaD4S10Fnz+VhCEZdKGRmp5Q8GpdM1WO7amlqOkXrlCZNF5tZhz03mKbY/c61kUNFmmC72bJo+WZb2B+mqP9moOkX8EQcBLEcn4MdH11N6H83sPtSipb8fW1AqED+qPuy4bhxFDBsgYm2yrllV5ozrFKfXU8P4xodSpV+FnkTl4ruv819RucZr9b38Q3fiRY4hJX3f/6gzZt+GL5JJG2O0C6trMuP3iMTh7VLjaIYlSrWCNJAMMkieafJlp8PPd4pNNnvxzvfqTUSjt86hcp+fe2RJ4Yknp4X92AY7JRN686yLMumZSQOvjSAWSii9DvSiE1LWaUCjxXQtP5q49hu1pymbz4wrqsSq2EI9eNVHR7ZI6BvYXM3mh/LpP38FSUJi8K6htc5v06WtHWiVmr0lwPP4hrhgbn74agwf08/Cu0NNfpa4Wcm9VybxSmZfkmckq/8VQVoV8s/sp0StsaNewuAH9DL0KrirtuyMnzheL9h9HxOyrccGY4ZrqoWbxUD9RyTjlLirsjrtzgD8F4+12ATHHnWu96F2Gi9lAy930fPLlc/0lpRxRGVXY5KUOlhjeilr39VlkDmZeeRb69/PeFr10/AhUZgRHTy8KTtq6IiLVeao5InVR5JL6dsWTPt3m73a+q0DKU+LueqvJqqlij0aLjXdvdObGT/f7tFxJfXuvpA/QOTOa3LOg5VW34pnvEnDPwkNYHVuIqmYj/rEuCXcvOISv9uRqsoB4P7USPyKPSbuzqmWKRH5KfOs9ExZSMyl4XD9lqHYK9LYYrVgVWwhA/R59Pc9lRwrcF5FWO041eUtEuWoPfLgjS5ptS/DB+5tIEwT32//pWCkeWBSLp76NR2ppk+N5Xya88NXKQwX4+/fHJE36AMDM5XGilm8xWpFZ4Vuy6KyRrK9G8goo8SMIwluCIBg4zEs/lDw5b031PmZarrxAbau4qREB4LzRwdW1OhgocWm3PbUSb29JV2BLvjEA+CGuRO0wSAWrDxe5fP6rvfIN+7PY7Hho6WFsS61EYnEjXt+cjiv+uxs/HStDckkjPtmVg8USz8wmxXnEXeJn2lmnBL5yD8Scc9SqQ+QrT0kss9XudiavdUddJ2uqW0LvTnT3R6i1vIWcCTVfNLab8dS38bj07V14eNlhlDd2ONWPkltetbSFra12O15XuMbVioMFuOaDPfjdx3t7zcQk1TF5+UFxk0MIgoDaVpMkCaPqFhOu/XAvVscWAujcZyw2O/ZlV+Mf65IRV1iPqMwqPLTssGO6cil/Z29JMERMKjWtRk3eYAk2giCgpkWa/TNUcagX9SJlF9miuja0GK24aOxJCHPRiA+23+3wwfy5SE2JXSC1rAmpZU3eF1TQWz9rJxFFymgzWbHEXWNexoNhZEaV1/oaH+7IwtPXnyPZNr+JKQx4Hf3CXN+XGiLRkDh3DUcxwzK03nPU3V+yeP9xvL/dfY+ClzemYsq4Ebj4jBG9nl/LhLXmqDXU69VNaYjKrALQOf303LXH0C7T9Nsmqw0/JpZh4shhuPLsUx0JzaMST1Nf1Wxym5yXw6G82l6FkV+KSMbFZ5yEC8dIN5vhvK2ZeOq6sz0u02y0ILuyBWEG4LkfklDW2IGzTxuG5Y9fjkmnBTY5RlljB17fnI5PI3PQ2G5B+KD+aDVZey3TYrRiY2IZnrx2kmSnQi318gaAJ1bGY9TwQVj48K9x+cRT3S7n7u8PtuslORTXteOJb48ir7oV40YMxpJHpzudo8g7DvWiXqQ4uNjtAl7akIzffbwPd355EDf/b7/TgV7JeKQidggAkTtmWwjOXR/ipry50+1rch7mArk4stkFxOTV4qdjpaht9b0467sSzPIyQMKhXtXNvXuqGC02PLrCdXd9MYf5PX4M85LrnNZqsmJ7agUiM6ocFz3uzlmekj7dXCW1gnF2Hanw7N9b39nUjhY2yLKdvOpWXPDaDvz7x1Q8uPQwJv17G6xd508ttQ89cZdM/qjPrJ6CoPykD/uyqzF9XhTuXxSLe7+OddQFy69tw6s/pUq2ne7ZSd1dC+zL7j6WSvOldsiUhAwkoVTTYsLcH46xt4qfXtuc5ujlV95kxAvrk1WOKDixCwNJLrm0ERt6dFnNr2nDf7dlYvKY4ahrM+OOS8bivNOH+927qLHdjCUH8rE6tgh/uGQs5t7MGbqCFRvTRNq8gBEEAS+sT3LURzgtfBDW/+1Kxba/T8LZpZYfKsC/b5/seByZUeW2rpLcx6SsymbcfNHpkq6zsd2MGYsPI7ur6Oi0s07BmievCKg3yKE8eetOSUKBE0j3RbsGf6IA9H8OveV/zvXTIjOqcPslY922IbV4PHXF1UymsQoXdH57SwbMbup3xhyvw6G8WnzcJ0Elh+jcWgiCADGjocw2OxrbzTjZRf0tue7TmnyY3c2T8iYjcqpaccGY4aLe525Ybig50KdNkF3Vgvo28WU7Qh0TP9RLs1H8wWVzUhl2pVdhwsihmP27c/D0mkSnZb7vMR596YF8bJh9tV8nZ6PFhtu/iEZFV5X/dfElWBfP7ucUPJ7+zvn3QdqSVdmMb2OKYLXZ8fCVZym23YX7pL/b6+9FUEFtW6+imLWtJkXrirhr0PnToF+8P79X4uc/Hu5ky92xc8He4/j7jdLerNiWWulI+gBAQlEDonO1Oy17Smkj1hwuQr8wA2ZeOTEoLmq0epdem1FJQxAEl8evp79LROEHd7h9n6eaaU+vSfA41CaUVLcYvU57//CyIwpFA0z69zacMnSAqPf86p1IZM+7DYP69x4C7M9Mar6QohxGq0n88e5NlgdwyV3Sktxj4od6+cnHKYm7RSSU4sUNJ7rbHS2oR2Wz5wKQbWYbvo0pxAQ/qtdH59Y6kj5ad/7pLAbtzeSx0o1lDxY2FvjTpPu+jsGsayZh2lmnYMbiw46L0Z69F+WSWtaEmcuPyDK7l7fjcbeYvFos2JcHk8WOx6+ZiDgXM/SILRSqVS1G90OP5R7S2+FhqMCq2EJEJJTitPBBeOHW8zFlnG/1C1wlst7YnI57fn2Gv2GizcVQCbsEbezC2jY8uOSwY/1aL3S/+nARRgwZ4NeEEHqVXSluOmtPjBYbPtiehcP5dbh0/Ai8esdFGDGk8+Lf39p8ns6x29MqFZ9NVswhpa7NjKZ2+ROhgiDgN+/tln07YjX48bdHZVTjjkvH9n5SpsO4FM23p9ckYuPTVwe+IiI/MPFDvXibSWD26gR88sBlCB/Uuet80KdWQHyRb+O818WXYM6N53pdru8sIksOHPdp/VogVRFSPRvc4zM64+QhjvHlREqLL2pAQnEDrjtvlCo9EOSe0t2bWSuPwtR19yyhuEET01e3mawYNkjZZopapdy2JJfjjc0n7uomFjcg5pUbMXSgf39/ZbMRC/cFdr4UBKFXIqzFjzvVfX1zqMBlUknL5Jx1L1Bq7K5ui9T74a2f07H2aGfyL6uyBXWtZix//HIAwEYvSXeNdsLyqrrZiOfXJbl9fe66Y7JtO6uyGS9uSEZaWbNs21DayxtTnBI/ch3HpbhxV91iwszlrntSBekuTUGExZ1JlB3plXhva6bjsZiCn3196UMRu+jcWuRVtzi6WQfriZ68mzIu9Hr/kLYIgvM48mCxI63C+0IemHp0mRYE90OtlFTVbITNLiCltBGZFc2KDLeRa4iAN+/0KYjd2G7BL8mBfaeBkmM2xG9jlZs1ieSxMVGaXpB2u+BI+nTbnVXtKMzr6ddeVNfmslei1rWarLj2w72I8VDLZ1+2tOegHV09nARBwFPfxusq6QO4HoYp11H8s0hp6h0V1rW7fL6iSVs3P1uMFsTk1QZ0rUfawsQPifZDnHJ1HgDg5s8O4N8/psJuF2BXMfOj9yKKauh5V4aTphH5b7aL2mrBrt1sw8PLDuOPXx3C7V9E4+k1ibDIPCOeWg3vmhbnhnWcxNNVi/XOlgwkuShA6y+ph7mKSdJ1mG3YkVaJTcfK0NiuflKzW2aFvi7Cxdjvpg5Vu7lzKGZOlfshZb/7eB9+Ti53+7qWZHUNjUsuacRV7+9WfFbPf6xLgslqQ2pZE0obtJVYkItcQ3blHpq6LVU7MyceK27A1e/vwUPLjuCK/+52msmPghOHelFQWHu0BDOvOgsWm3qJH7FbZuck71iYjYjcufPLg70e70iXv1G8KrYID0w/Exef4Vt9HT2LL2rA/y04hNfvvAhPXjsp4PUlFssz5bc3RosNj6444phy/KyRQ7Fh9lUYPXywKvH09Oku+WdM0or18SXIrWrBb88fhf5hYZj1zVGPy+uprlJlkxGf7Mr2WF9MLh0WG/ZkVqN/P33erG1G3QAAIABJREFU63fV1uZ9xMB9tCMbLabO/dVmF/DOL+n4wyVjZK+DJwWtFuPXAn0eBUiXvtqTJ0vXc1LPcz/IN5adiMgf3xwqVDsEANoZ2vzuLxl4YuVRlNQH1ltA6iSHL9cfm5PKcKSg3pH0AYCiunYs8GGouRKiMqvVDkEx/4pIwdLoAsxcHocHlx5WOxxFrTlcpGodt3oN9XKj4BCb33s4YlWzCcX1roeoqSUIclCawx4/5JfKJiPGjFD2bpnaU77y+CK9/No2lDa0Y/wpQzVzkUNEoW1jYik+feAyx2ObXUC/MAM2JpRi+cEChA/qjzk3eZ+cQIo48mtb8bffnoPbLh4j+/Y82ZPlf4Ji4itbA9r2gZwaXHPuaegXJv4sPHet6yK638YW4eXbL/S7eLYUmo2Bt2mUuvtuswv4JaUcKxSY2S+5tBHLDxYgr7pV9m0pZdlB6Qpi+0vvvSCyKpvx/rYsVDR14NaL1D1e6tXDy45g2MD+uHvqODz9u3M02/tHq3FpARM/5Jc1h4vwwq3nK7pNnZ+zQlZ0bi0e/M0EtcMgIp3LrmwR1cvwSH4dHv/mKGyC4DQsdebyOMnisnqo+XGsuBHPfp+IX+Zci8ljQ7MA/qMrOj/rS84YgS/+/CucPSocHWYb/rwksF4j21Mrce+08VKEKJrNLmCHhup5uFPTYsJzPxxzuvsvpydWxiu2LaUYLRzWLhdB6Cwb8MiyI47hgTlV2ujRpzfdNaI+2pGNU4cOxJ/Zdg86HOpFfvlqbx7uXnBI7TAUxbwTEVHw+v3nB5DtoWBsTxsTSjFjyWF0WGyy1iKLK6jHtHlRHpex2QUs0PCU4kpJLWvCbV9EIyavFpe9vSvg9W1PUyfxklTSiAte245/bUxRZftivPpTqqJJH5KPntuwUZlVuqoJFQxe35ymdgjkByZ+yG8ppay3Q4FjTy4ikltBbZuo5V/YkCxTJL29FJHs0zDmX9zMqCL1TFlaZ7ba8dCyI4rPjCSlVzamwCrB93YgR9ppv13ZlVEl+zZIfoKg77YWr0eUp+ZkO+Q/Jn4oaAhBdr9CzydZIqJgUtVsVDsEJ2WNHSiqC6xY5jGVZsoi/7SbrY7pvQPVPQSOyBs91UvqS4DAIr86IwgCfk4uxxub0/BjYqnu61MpiTV+iHzE84o8uhN6PHETkVy02DPGZLGJWl4QBKeilZ/uypEypJCSUFQf8DoEQcDKmELsza7BuaPCMffm8zBiyAC3y0vR04dIrDaTFXod7GWAge1zlcxenYBHrjwL1553mqTrXbA3D590ndtWxRbpOnGpNPb4oaCh9qFdn6dM7WBCn4jkEpFQqnYIAUsvb3Z6Tu3ZLoNZQ3vgn92SA/l4e0sGDuTUYMWhAsxeneByOUEQYLKKS/T5ghe8FOoECAjjnUNV7EivxKyVcUiVeKjdJ31uaCzcd1zU+9lDyD0mfihoBNtQLyIi0oafjpWpHYITsVPOPrzsiNNzPCuq6/3tWb0ex+bXobSh9/C9qIwqTH5jBy54bQf+4WZ6ebXZ7ALyqltkSU6R+gTo9+aaILDHuJosNvUmH6jzoaB3u9mK/JpWJoO6cKgXEamKx2IiCkVir1WaOizIKG/GReNCc1p3OVQ0dSCltAmXjT9ZsnXmVrdi/ClDAQAtRgueWnVievLdWdWSbUcquVUtmLk8DpXNRoQP6o/FM6fhmnOlHbpB6tqSXI4bLxytdhiyECA+iR4qBEFAbnUrSurbcfmkU3HSYPfDUAOxI733DIm1rSYkFjXgwjEnYcLIobJsEwD+MD/a5fPd+8PGhFK88mMKLDYBF44ZjlVP/gajhw+WLZ5gwMQPBY2aFpPaIRAREanmq725WPjwNMdjLRatDiZXvb8HABAm5XVjj5sZH+3IlnDF8pi3NROVXftRq8mKf0Wk4ODLN/BiWkdMVjssQTwTnidmq13a36+OfLorB1919cY5LXwQ1v71Spw7OtxpOavNjqjMapQ2tOOGC0fjnFHOy/gqrqAej62IQ0dXDbsP770EMy6f4Pf6/NVhtuHfP6Y6Zh/LqmzBV3vy8M7dFysei5ZwqBcFjeM14qbj9cW4EcplfsefMkSxbQUTdvgholDkz3V132mLecEjDblqLq8+XCTPiiW0v8+08GWNHShr7FApGpJL3+9ZT9SuAapFDW1mLNh3YghWbasJy6LzXS77woZkzF6TgHlbM3Hn/INIKPJ/tsj/ReY4kj4A8MH2LNhVKGq/Pa0C5j7JzlWx2j8ey42JHyKZ9K1JxOJzRETUfeddiouV008K7W7rWqRkPUK5mhXdd8lJP5o7rGqHIBs2r51tSipzKqWw9miJ03LljR3YnFTueNxhsWFlTKHf243Nr+v1uKHdglwVZuVqlKB4vx4x8UMhjU0bDeg6M/G7IKJQ8N9tmQG9v9184gKONdK0R8nv5NnvE2VZL3uS6Y9eh3oBnN3OFZPVt+/b1cQHW5LLXSzpP7uGTlRWmx1GS+gWsWfih4iIiEgh3xwqBODfXerShg5c/OZOPLYiDi1G3tEMdSX1vg3Jyq1qQV2r73USDTDgeI3yd+lJPo0d+j1ehDFT6URDuRbF2ewCsitbXL429d1IXPb2Lrz1c7oqQ9DUxuLOFLI4tZ9GsI8uEZHP7EJnvY7Po3LVDoVc0GLT4pb/HQAA/POW8/HcTed5Xf7h5Yd9TipRkNDijkmycTfktM1kxbBB+r78f3DpYbevtRg7e8yujCnE1Akn4+5fnaFUWJrAHj9EPmKiSCZdnyvTP0QUSkzWwLqbLz9YwFm9SJTPInNQ2tDudTkmfSiYsIamM3eXLD3r+QChfe/19U1paoegOCZ+iBSiZMFHIiLStsiM6oDXUddmliASkpLWz/TdQw0ptOh5VEsoJy/EKmvsnfgN5Xvaz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BlSY/Mm4IGImNNkGes9QyQdnuPhc5LGqnpMjXqxcAPpmI/Jt6Q2U6bWcW1HzFnf+GSeT4mIVyuWu+2xKp3UtjimVi31roUAdlIaR+rLko6oM/ZFK8f1XcDawE35Ovs1+Tp8ev5aHIfI1+r9oxPOTa3Em/WNo/P8h3XyuO1p0Zr9XYEBYts8f6DG8geBfUnPAs6okccGAElrAkfmr1UnpvflqVhmFjAxIh4ppA0D3kga62V+xXoezPNtCmlbkp6pfzgiqi60qso0E5vlMtZ7NgV+UkqbI+moiJhdSKt5nCLiFUlzgLeRnmm+r4ky8yUtAraQtE5ELG5jzFkvk7Q2cDjwKnBujWxue6xKJ7UtjqlVhKQ3A+8h/Yf7hhrZPlf6/qqkc4ETImJJIb2V49pXZXyt3vs64dzktmcVIGl30t3PD0TE9XWyuu1pke/4ac7wPH+hxvKu9A3aUBfrW6cD2wNXR8T0Qvpi4OvAzqRxEDYkPQN/Pel2xhn5pNallZhpVxnrHeeRLow3BYaRTlbnkG5/vkbSjoW8fXlsh5fmjp+B52OkfXxtRDxaWua2x+rppLbFMbUKyHeH/RQYApwSEc+VsswhPY6xLenctzmpDZsLHAP8uJTf8dOZOunc5NhZNXTd+fyjGsvd9vSQO37MMknHk9408FfSiPKviYinI+JrEXFHRDyfpxtIPbi3AFsB/9b2Slu/iYhTI2JmRDwVEYsj4p6IOJY0kNvawCn9W0MbQLouds4pL3DbY2btkh9V/gnpDTgXA98q54mI2RFxVkQ8kM998yPiUtLjDs8Bh5Z++LAO5HOT9SZJw0mdOMuAqVV53Pb0nDt+mlP+9ausK/35NtTF+kB+te13Sa80HRsRC5spl2897Xo0492FRa3ETLvKWN86O8/bFQ8vlOaOnwFE0ttIYxg8BlzdbDm3PZZ1UtvimOpHudPnQtJrji8BDo88Omkz8t2KXW2Y26TV1AA9Nzl2+t/hpHFwfhkRz3anoNue5rnjpzn353mtZzu3zvNaz/bZKkzSCcCZwD2kTp8nu7mKZ/L8tVtaI2IR8DiwrqTNKspUxczfSGN8jM5jDTVTxrG56lkpHqhznPKxHkUaQPPhJstsltf/WEQshrbGnPWuRoM61+O2xzqpbXFM9RNJawEXAYcAPwM+XmNMlUa6df7LeisWHD+rjoF2bnLs9L+uQZ1XuvO5SW57muCOn+Z0DTC1r6QV9pmk9Ui3xC4G/tDuilnPSDoJ+DZwJ6nT5+kWVtM1SvvDpfSZef6BijIfLOUhD0h2M6nHe69mypBOio8A20ga1WQZ61tV8VAvFt5NOuY3R8TSJsvUOq7tiDnrJfmNJUeQLmyntLAKtz3WSW2LY6ofSBoMXEq60+cC4IgWOqG77JbnxTapleP6B+AfwB75OrtY3zVIjxPB8uvz4mdfq/e/gXZuaiXerJdI2g3YkTSo86wWV+O2pxk9eRf86jSRXt8WwHGl9DNy+tn9XUdP3T6mX83H7nZgowZ53wGsUZH+HmBJXs+Y0rIxOf0hYMNC+khgQS43slTm0FzmJmBoIX1XYCnwNLB+qcxXcplLi3UE9s/p91bV3VOPYmc7YFhF+kjS6P0BnFxIX5/0a8RSYJdC+lDSRU0Ah5TWNSrHyIJinJAGUHwol9m9P2LOU6/F0RF530+rk8dtz2o8kQZJDeDCGss7qm1xTLU9foYAV+U85zazb4txVkhbo3DsnumN40r65T+AyaX043P6tRX18LV6+2Kno85NrcSbp9bjp5R3Ss77xQb53Pb0cFKulDUgaUvSRdQmwBWk16LuRhpQ6gFS47ag/2po3SFpImnwsFdJj3lVjcQ+NyKm5vyzSLfq3UwaiwNgB2Bc/vzViPjviu1MBr6Qy1wGDAYOBjYmNQ5nlfKL9Gz9QaRBpqflvAeTLuQ/EhFXlMoMIfVWjyF1Ys0A3kT69W4ZMC4ibmm4U6xpkk4hDQR+AzAPeJH02tEPkY7T1cABEbGsUGYCKQaWAD8HFgLjSW8nuAz4WJQaZEnHAd8jXRBdTDqeBwFbkE5IJ1bUrc9jznqHpBuBPYHxETGtRp5ZuO1ZreS2YkL+uinwftKvmDfmtGeL//Y7qW1xTPVcd+JH0nnAJOBZ4P9I/0EpmxWFX+ElBenR+LtIj+4MJ/2ivT3pV+0DIuK6Up26fVwlbUxq97bJZW8l/eiyP+k/+2Mi4m+lMr5W74Fuxs4sOujc1Eq82Yq6e+7KZdYHngDWBLaIOuP7uO3pBf3d8zSQJmAE6RXO80nBMg/4DoVea08DYyK9cSkaTLMK+T8B/Jr0ysCXSL8yPEK6YN6rwbYmAbcBi0gdBLOB/erkXxP4PPBn0u2Gz5E6EsbUKbMOcBrpbpOlpF7vS4G39ve+7sSJ9MrSi0gXIc8DL+d9/hvgSEid6hXl9sjH8rl8bP+cj/WgOtv6cI6ZF3MM3QZM7O+Y89TjGNoutzOPNjj+bntWs6mJ89PcijId07Y4ptoXP8CsBnmD9Er34vq/mY/7E6TOxsWkc+FZwOjePK7ARqQXb8wjXXfPJ72yeYs6ZXyt3p7Y6bhzUyvx5qm1+CmU+VRedlET63fb08PJd/yYmZmZmZmZmXUoD+5sZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmZmZmZtah3PFjZmZmlSTNkhSSor/rYmZmZmatWbO/K2BmZma9Q9JIYE4vre6oXlpPx5J0Sv44NyKm9mNVzMzMzGpyx4+ZmZlZa/4rz2cDU/uxHmZmZmY1uePHzMysczwNHFBn+TjguPz5euB7dfLe4btYzMzMzAY+d/yYmZl1iIhYDFxea7mkDQpfH4mImnnNzMzMrDN4cGczMzMzMzMzsw7ljh8zMzOr1OitXpImdS2XNCmn7SLpfElzJP1D0jxJF0navlR2kKSPS5opab6kJZIekHS6pPWbrN9gSZ+QdKWkR/M6npd0t6TJebDrRuvYXNJpkn4vaaGklyU9J+lBSTdKOkPSXqUy5X2yd2E/FKd9SuXWl3SYpCmS/pTr+nLe7h25zls2Uee5ef1z8/ehkk6QdIukBZL+LumPkj4raXCp7GhJ35V0n6RFedvTJb23wTanFv6ukTntMEm/LRy/uZLOlfTWRn+DmZmZtY8i/IZWMzOz1UHunDkvfz0/IiY1yD8L2BsgItRgfUcB6wLfpvpR8qXA/hExXdJ6wMXAB2ts+q/AuyPimTp12wW4BBhV509YBhwfEefUWMeHgJ/netfzQkS89phcN15vPzYiZuUyg4G/A0MalHkFOCEivl8rQ+7weTMwD9gduAp4e43s00n7famk/YGfAsNq5D0uIs6qsc2pwMT8dVvgf4EJNdazDPh0REyp9TeYmZlZ+3iMHzMzM+sN+wEHAs8A5wL3AGvntA+ROjwuljQKOJ/U6XMTcCkwn9SR8Zk8fwupA+nwqg1J2h34LbAOEKTOjeuAx/M2dweOyMvPlrS0PFC1pDeyYqfPVcBvgCdId0RvAuwIvA8YXqpC1wDav8rze4H/rKjqPYXPa+R98ETezt3AU8A/gRHAGGA86drsLElPRMSvqG8t4BekTp+rgWnAQtL+Ow54HfB+4GRJVwOXAf8AvgvcntfxQeBQQMAZkmZExH0NttvV6TMP+DFwP7BRTtsXGAz8SNIzEXFlg3WZmZlZH/MdP2ZmZquJPr7jB+BW4AMR8Vwp3w+Bo/PXPwI7A1+JiNNL+TYB7gQ2A14FRkTE/FKe9UgdLSOA54EJETG7om5bATOANwGLgJER8Wxh+YnAN/PXkyLiGzX2gYA9I+LGimVdF1GzI2KfqvKFvINInUjTo8bFl6QdSJ1YmwIPA1tHxD8r8s0ldZBB6vg6MiIuLOXZmrQv1wFeIHXIAYyLiEdLeb8KnJa//iAiPl2xzaksv+MH0lvhxkfES6V8nwXOzF+fzH/DCnnMzMysvTzGj5mZmfWGZcDHyp0+2amkDgpInT7XlDt9ACLiaaDrUaNBQNW4M0eTOn0gdXis1OmT1/UQ6fEzSI82fbKUZavC5x9VrSOvJ6o6fborIl6NiGtrdfrkPHcDJ+evo0l3ATXyw3KnT17Xg0BX+nDS33tYudMn+ybwYv78/ia2+QJwSFWHTn5U7OL8dVPgsCbWZ2ZmZn3IHT9mZmbWG6ZFxLyqBRHxODC3kFRz/Brgd4XPVYMEH5HnD0TEtHoVioiZpEerID2CVLS48Plt9dbTZjcXPu/WRP7KMXmymwqfb4+IW6syRcQSlj/6NUrS0AbbvDB30tUyufD5gJq5zMzMrC08xo+ZmZn1hlsaLH+K5QMxV3ZAFPJ12bC4QNJwYIeufJJqDS5c1HVXynal9N8An8+ffynpf4BLI+KxJtbZsvxGrInAPqSxeDYAanW0bNFgdYtIj73VUtyX9fZ5Ma9ynZ6sk3dGg3XdThrIen1g1wZ5zczMrI+548fMzMx6w4IGy5c2mbeYr9whMoLldyvvladmrdCJFBHXSPoZ8HHg9cAZpMGNHyTddXMD8OsGd7Z0i6QTgNNp/GavLo1ea7+w3qNjNL/Py3kb3fHzUL2FERGSHgZ2AjaSNCQiltYrY2ZmZn3HHT9mZmbWG1YahLiWqgGLm1R+u1Z3rFWRdjgwk3TnT9fjXlvnaSLwqqRLgC+WB5nuLkmHkd5U1uVGYDbpEbgXSWMkQXqbWNfr5wc1WG139mOr+7zK4sZZWFT4vC4rdiyZmZlZG7njx8zMzAaK4mDCF0TExJo5m5DvlpkCTJE0GtiTNKDyOFLnzyDSq873lLRrRDxVc2WNfT3PXyG9DeuaqkySVqXxhmpZp4k8wwqf/VYvMzOzrFdlXgAAA2tJREFUfuTBnc3MzGygeLzwudH4N90SEQ9HxAURcWxEbEN6+9if8uIRwJdaXXfuVOoa3+jyWp0+2ZvrLFtVbFVvoSSR3koG6XE03+1jZmbWj9zxY2ZmZgNCRDwL/CV/fZekRmPg9GRbd7D8DWKQ7gZaKVueq8Hq3lD4/LcGeZt5nXp/G9dg+c4sH5/otj6ui5mZmTXgjh8zMzMbSM7P83WAL/fxtuYWPlc9Ht/1CNOwimVFxTFxtqyVSdII4Kimata/Dpf0+jrLv1D4/Mu+royZmZnV544fMzMzG0i+D8zLn78s6UuSal7PSBou6XhJ7y2lf03S++qVBT5d+HxXxfI5ef4WSWvXWc99LB/seH9J76yo5xuAy4H16qxnVbEBcJGklTq8JB1LGhcJ0ivhf9bOipmZmdnKPLizmZmZDRgRsUjSBNIbsdYHvgEcI+kXpMfAXsrpo4F3AvsAg1nxsS1IjyudCjwpaTpwJ6mjYg1gc2A8y18Xv5T0uveyGcAOpDt+pkk6H3iW5Y+A3RoRCyNimaRzSHfCrAXcIOnHpMegXgbeQbrTZwPgAuDIlnZO+1wOTADukTQFeJBU9wNY/qhaAMdEhAd2NjMz62fu+DEzM7MBJSLuzHfNXAS8nfT41L/XKbKU1CGzwmryfFPSq9trvSHsWeCwiLi3Ytlk0ivhXw+8J09FY4FZ+fN/5LqOBYYAn8pT0TmkjqxVvePnJNL+O4DlbysrWgZ8JiKubGutzMzMrJI7fszMzGzAiYj7Je0MfBg4ENid1IkzDHiR9DjYXcBM4MqIeK60ivHAe4G9SYMRbwVsTOrQWAjcC1wDTImI52vU4XFJ7wBOJHX6jMzbX2mw54hYImlf4GjS3Ufbk+5EehK4JW/nOkkju7832m5ZRBwo6TDSnUrbAxuS/pbfApMj4i/1VmBmZmbto4honMvMzMzMVluSprL8rqhRETG3/2pjZmZm3eHBnc3MzMzMzMzMOpQ7fszMzMzMzMzMOpQ7fszMzMzMzMzMOpQ7fszMzMzMzMzMOpQ7fszMzMzMzMzMOpTf6mVmZmZmZmZm1qF8x4+ZmZmZmZmZWYdyx4+ZmZmZmZmZWYdyx4+ZmZmZmZmZWYdyx4+ZmZmZmZmZWYdyx4+ZmZmZmZmZWYdyx4+ZmZmZmZmZWYf6f6OMJMBlK1bnAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "8beab52c-ffb7-415c-c84c-04ed39cd70cf"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "a6c042dc-999a-456c-b233-a1e05612e15f"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "6f325187-ee1b-4122-97f7-80ffdbf149d2"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YoQA_MIBMknS"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "a44c4d8b-e9d2-4978-fb9e-ae179758e6bc"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "c3e3d463-1089-48f7-da23-01a7b92423a5"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 11
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "7e9b0a07-d2de-4e42-d45f-572a8abeae9e"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "f8c5d0a8-c26a-4aa5-a530-957480984106"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f1f90fe5fd0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f9075bb50>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f903483d0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f906632d0>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "4dca8628-c567-41b0-f262-bc6a3dddb5a7"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "7747f2fc-9d3d-4e46-9148-39708b9ae947"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "f3dccf5d-76c2-4c9a-898b-9a221f5a491c"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "XkGTfQ46NAlo"
-      },
-      "source": [
-        "## Why Increase Depth?\n",
-        "Stacking LSTM hidden layers makes the model deeper, more accurately earning the description as a deep learning technique. It is the depth of neural networks that is generally attributed to the success of the approach on a wide range of challenging prediction problems.\n",
-        "\n",
-        "As Stacked LSTMs are now a stable technique for challenging sequence prediction problems. A Stacked LSTM architecture is defined as an LSTM model comprised of multiple LSTM layers. An LSTM layer above provides a sequence output rather than a single value output to the LSTM layer below. Specifically, one output per input time step, rather than one output time step for all input time steps.\n",
-        "\n",
-        "We created Stacked LSTM model using Keras which is a Python deep learning library. "
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "eed7670c-b3b2-4a20-82bb-7ff2b5f4a0eb"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:]))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "\n",
-        "\n",
-        "\n",
-        "single_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 12s 96ms/step - loss: 0.0990 - rmse: 0.1509 - val_loss: 0.0124 - val_rmse: 0.0135\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 4s 79ms/step - loss: 0.0433 - rmse: 0.0542 - val_loss: 0.0210 - val_rmse: 0.0211\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 4s 79ms/step - loss: 0.0397 - rmse: 0.0498 - val_loss: 0.0055 - val_rmse: 0.0062\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 4s 78ms/step - loss: 0.0341 - rmse: 0.0429 - val_loss: 0.0114 - val_rmse: 0.0114\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0325 - rmse: 0.0408 - val_loss: 0.0138 - val_rmse: 0.0138\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0299 - rmse: 0.0376 - val_loss: 0.0076 - val_rmse: 0.0077\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0286 - rmse: 0.0360 - val_loss: 0.0161 - val_rmse: 0.0161\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0282 - rmse: 0.0355 - val_loss: 0.0040 - val_rmse: 0.0040\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0270 - rmse: 0.0340 - val_loss: 0.0036 - val_rmse: 0.0036\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0264 - rmse: 0.0331 - val_loss: 0.0100 - val_rmse: 0.0100\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0253 - rmse: 0.0318 - val_loss: 0.0046 - val_rmse: 0.0046\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0271 - rmse: 0.0342 - val_loss: 0.0057 - val_rmse: 0.0057\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0236 - rmse: 0.0295 - val_loss: 0.0090 - val_rmse: 0.0090\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0226 - rmse: 0.0284 - val_loss: 0.0048 - val_rmse: 0.0048\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0218 - rmse: 0.0273 - val_loss: 0.0051 - val_rmse: 0.0052\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0208 - rmse: 0.0262 - val_loss: 0.0017 - val_rmse: 0.0018\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0200 - rmse: 0.0250 - val_loss: 2.3304e-04 - val_rmse: 3.1191e-04\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 3s 70ms/step - loss: 0.0192 - rmse: 0.0242 - val_loss: 0.0069 - val_rmse: 0.0069\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0182 - rmse: 0.0229 - val_loss: 7.9341e-04 - val_rmse: 8.1912e-04\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0178 - rmse: 0.0223 - val_loss: 0.0040 - val_rmse: 0.0040\n",
-            "Model: \"sequential\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "lstm (LSTM)                  (None, 120, 32)           4736      \n",
-            "_________________________________________________________________\n",
-            "dropout (Dropout)            (None, 120, 32)           0         \n",
-            "_________________________________________________________________\n",
-            "lstm_1 (LSTM)                (None, 100)               53200     \n",
-            "_________________________________________________________________\n",
-            "dropout_1 (Dropout)          (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "activation (Activation)      (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "dense (Dense)                (None, 1)                 101       \n",
-            "=================================================================\n",
-            "Total params: 58,037\n",
-            "Trainable params: 58,037\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "25c66158-969a-47c4-d35b-9c34abba211e"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "0a474737-67b6-4ff1-d6b2-37b7623a44ce"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "xFJT1rZDAUVL",
-        "outputId": "8e38f8da-d7ac-40ce-eec9-eee2320fd828"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Lu7m2Rr4AbMK",
-        "outputId": "7b932e10-bb78-4eac-8757-4aa2d915b96d"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "fjXexah9C8yg",
-        "outputId": "72c81185-3db8-4d45-f1f2-9bf5861c3a3e"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "id": "7mtLZ6S-DPU-",
-        "outputId": "a4a392fe-73a5-44f7-ae77-003e7c46a1ad"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "snN_Flr5DWQN",
-        "outputId": "8b881aff-b91b-4394-bc3d-e52261e546db"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:]))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 9s 100ms/step - loss: 0.1700 - rmse: 0.2356 - val_loss: 0.0285 - val_rmse: 0.0316\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 4s 77ms/step - loss: 0.0805 - rmse: 0.1018 - val_loss: 0.0161 - val_rmse: 0.0170\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 4s 75ms/step - loss: 0.0621 - rmse: 0.0782 - val_loss: 0.0116 - val_rmse: 0.0121\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 4s 75ms/step - loss: 0.0527 - rmse: 0.0661 - val_loss: 0.0261 - val_rmse: 0.0263\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 4s 74ms/step - loss: 0.0465 - rmse: 0.0582 - val_loss: 0.0140 - val_rmse: 0.0142\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 3s 69ms/step - loss: 0.0426 - rmse: 0.0534 - val_loss: 0.0165 - val_rmse: 0.0166\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 3s 67ms/step - loss: 0.0387 - rmse: 0.0485 - val_loss: 0.0203 - val_rmse: 0.0204\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0362 - rmse: 0.0453 - val_loss: 0.0142 - val_rmse: 0.0142\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0336 - rmse: 0.0421 - val_loss: 0.0165 - val_rmse: 0.0166\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0321 - rmse: 0.0402 - val_loss: 0.0166 - val_rmse: 0.0167\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0304 - rmse: 0.0380 - val_loss: 0.0190 - val_rmse: 0.0190\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0289 - rmse: 0.0361 - val_loss: 0.0196 - val_rmse: 0.0196\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 3s 65ms/step - loss: 0.0274 - rmse: 0.0343 - val_loss: 0.0220 - val_rmse: 0.0220\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0266 - rmse: 0.0333 - val_loss: 0.0118 - val_rmse: 0.0119\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0254 - rmse: 0.0318 - val_loss: 0.0094 - val_rmse: 0.0095\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0243 - rmse: 0.0304 - val_loss: 0.0093 - val_rmse: 0.0094\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 3s 67ms/step - loss: 0.0236 - rmse: 0.0296 - val_loss: 0.0110 - val_rmse: 0.0110\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0225 - rmse: 0.0280 - val_loss: 0.0157 - val_rmse: 0.0157\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0221 - rmse: 0.0276 - val_loss: 0.0118 - val_rmse: 0.0119\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0210 - rmse: 0.0263 - val_loss: 0.0047 - val_rmse: 0.0047\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Ay5m27doDsTt",
-        "outputId": "70f65cf2-a2fd-4a1e-b9e0-049430410a1d"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "6ZFP49W4D2wp",
-        "outputId": "f2d25889-8aa1-4405-d607-1ed72a0df675"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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YzKXu8K1m2MhgaNyl5vSbhubm7W22+/qW9/+zuSpA8//EDPPPNfmjRpsgoLX9CoUaP0xBPPqLGxUbfddovmzLlMH310SEePfqpt255XTU21liy5UfPnL+xw35qaGuXkZOuRR3I1adJknTpVpzFjxiopaVGHQHvffVlKTb1JM2bM1IkTJ3Tnnbfr97/foaefflyXXjpTy5Yt15tv/kkvvVTo8T385Cf/R0FBNo0YMUKPP/47t31GjBihW29doQ8+OKhVq9ZKkp588jGP9zx2rFxZWet1ySXT9e67b6u8vFyPP/47maapu+5apffeK9XMmbN79VkDAAD4A+G6naDjx3rV7i2Hw6H09MWSWmeub7ghSWVlf9W0aRdr0qTJkqQ///ltffzxx3rttWJJUn39GR07Vq733tuvq6++RjabTeeeG6nZs/+ly/0PHCjTjBmzXPcaM2as23Hs2/eujhz5xPW4vr5eZ8+e1Xvv7Vd2do4k6TvfuVyjR4/x+F5+85vHNG7cuD58Cp5NmDBRl1wyXZL07rtv689/flvLlt0kSWpoOKtjx44SrgEAwKBAuG6nZfIU2Y6Vu233RVvNdWd2u931a9M0tXLlan3723Ed+vS2brk7ptmixx57WqGhoZbd02YLdtVJNzY6uulnk2n+s566sbHR9euwsLB2YzS1ZEm6kpNTLBsjAADAQGFBYzv1Wetktgu8kmTa7arPWtfvrz1nTpwKCna4FjcePfqpGhoaNHPmLBUXF8npdKqyslKlpfu6PPfii6frr3/dr88+Oy5JOnWqTpI0cuQoNTScdfX7l3+5TPn5/+V6/NFHhyRJM2fOUlHRTkmtYf706VNej3vixIk6dOgDSdJrr+1xtY8cOVJnz55t12+SPvywtd+hQx/o888/c3u/b387Ti+//D+u537xRYVqaqq9Hg8AAIA/Ea7bcaSk6vTDv5VzSoxMw5BzSoxOP/xbyxYzdmfBgmSdf/7X9KMf3aSlS1P1y18+IKfTqSuuuEpTpsRoyZIbtWHDva7yifbCw8O1evXdysparbS0H+ree38qSfrXf/2uXn99r9LTF+uvf92vzMzV+uCDvyst7QdasuRGFRTkS5KWLVuuv/51v5YsSdXrr+9VdPQEr8f9wx8uVUHBDi1btrjD9n2zZ39LR458ovT0xdqzZ5fmzp2nU6dOacmSVOXn/5diYr7i9n5z5lymhIRrtWLFMt1887/pnnvWdgjpAAAAgcwwe7M1RIBranKqtrZjEDtx4lNNmHCen0aE/sLPFQAA+FNk5Gi37cxcAwAAABYhXAMAAAAWIVwDAAAAFhkW4XoIlZVD/DwBAEDgGvLhOjg4RPX1pwhkQ4RpmqqvP6Xg4BB/DwUAAKCLIX+ITHh4pGpqvtCZM7U9d8agEBwcovDwSH8PAwAAoIshH65ttmCde+5Efw8DAAAAw8CQLwsBAAAABgrhGgAAALAI4RoAAACwiE/hura2VsuWLVNiYqKWLVumuro6t/2mTZumpKQkJSUlacWKFV2ub9iwQbNmzerS/uqrr+qCCy5QWVmZL8MEAAAABoRP4To3N1dxcXHatWuX4uLilJub67ZfWFiYCgsLVVhYqC1btnS4VlZW5jaUnzlzRs8884xmzJjhyxABAACAAeNTuN6zZ4+Sk5MlScnJydq9e3evnu90OpWTk6PVq1d3ufbrX/9ay5cvV2hoqC9DBAAAAAaMT+G6qqpKUVFRkqTIyEhVVVW57edwOLRo0SKlpqZ2CODbtm1TfHy86x5tDhw4oBMnTmju3Lm+DA8AAAAYUD3uc52enq7Kysou7ZmZmR0eG4YhwzDc3mPv3r2Kjo5WeXm50tLSNHXqVIWGhmrnzp3aunVrh74tLS36xS9+oQcffLA37wMAAADwux7DdV5ensdr48ePV0VFhaKiolRRUaGIiAi3/aKjoyVJMTExmjNnjg4ePKiwsDAdPXpUiYmJkqSGhgYlJCTohRde0Icffqibb75ZkvTFF1/otttu0+bNmzV9+vTevj8AAABgwPh0QuO8efNUUFCgjIwMFRQUKD4+vkufuro62e12hYSEqLq6WqWlpbr11lsVGxurkpISV79Zs2apqKhIkvTOO++42pcuXao1a9YQrAEAABDwfKq5zsjIUElJiRITE/Xmm28qIyNDUusOIFlZWZKkw4cPKyUlRQsXLlRaWpqWL1+u2NhY30cOAAAABBjDNE3T34OwSlOTU7W1Z/09DAAAAAxxkZGj3bZzQiMAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARn8J1bW2tli1bpsTERC1btkx1dXVu+02bNk1JSUlKSkrSihUrulzfsGGDZs2a5Xr8wgsv6LLLLnM95/nnn/dlmAAAAMCACPblybm5uYqLi1NGRoZyc3OVm5ur1atXd+kXFhamwsJCt/coKytzG8qvv/563Xvvvb4MDwAAABhQPs1c79mzR8nJyZKk5ORk7d69u1fPdzqdysnJcRvIAQAAgMHGp3BdVVWlqKgoSVJkZKSqqqrc9nM4HFq0aJFSU1M7BPBt27YpPj7edY/2du3apQULFugnP/mJPv/8c1+GCQAAAAyIHstC0tPTVVlZ2aU9MzOzw2PDMGQYhtt77N27V9HR0SovL1daWpqmTp2q0NBQ7dy5U1u3bu3S/6qrrtINN9ygkJAQPffcc1q7dq2eeeYZb98TAAAA4Bc9huu8vDyP18aPH6+KigpFRUWpoqJCERERbvtFR0dLkmJiYjRnzhwdPHhQYWFhOnr0qBITEyVJDQ0NSkhIUFFRkcLDw13PvfHGG/XLX/6yN+8JAAAA8AufykLmzZungoICSVJBQYHi4+O79Kmrq1NjY6Mkqbq6WqWlpYqNjdXcuXNVUlKi4uJiFRcXy263q6ioSJJUUVHhen5xcbG+/vWv+zJMAAAAYED4tFtIRkaGMjMztWPHDk2aNEmbNm2S1LoDyHPPPafs7GwdPnxY69atk2EYMk1Ty5cvV2xsbLf33bp1q4qLi2Wz2TR27Fg9+OCDvgwTAAAAGBCGaZqmvwdhlaYmp2prz/p7GAAAABjiIiNHu23nhEYAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAiPoXr2tpaLVu2TImJiVq2bJnq6urc9ps2bZqSkpKUlJSkFStWdLm+YcMGzZo1q0PbK6+8ouuvv17z58/XnXfe6cswAQAAgAER7MuTc3NzFRcXp4yMDOXm5io3N1erV6/u0i8sLEyFhYVu71FWVtYllB85ckS5ubl69tlnNXbsWFVVVfkyTAAAAGBA+DRzvWfPHiUnJ0uSkpOTtXv37l493+l0Kicnp0sg3759u2666SaNHTtWkjR+/HhfhgkAAAAMCJ/CdVVVlaKioiRJkZGRHmeYHQ6HFi1apNTU1A4BfNu2bYqPj3fdo82RI0f0ySef6Ac/+IFSU1P1+uuv+zJMAAAAYED0WBaSnp6uysrKLu2ZmZkdHhuGIcMw3N5j7969io6OVnl5udLS0jR16lSFhoZq586d2rp1a5f+TqdTn376qbZu3aoTJ05oyZIlevHFFzVmzBhv3xcAAAAw4HoM13l5eR6vjR8/XhUVFYqKilJFRYUiIiLc9ouOjpYkxcTEaM6cOTp48KDCwsJ09OhRJSYmSpIaGhqUkJCgoqIiRUdHa8aMGRoxYoRiYmJ0/vnn68iRI7r00kv78BYBAACAgeFTWci8efNUUFAgSSooKFB8fHyXPnV1dWpsbJQkVVdXq7S0VLGxsZo7d65KSkpUXFys4uJi2e12FRUVSZKuvvpqvfvuu67nHDlyRDExMb4MFQAAAOh3PoXrjIwMlZSUKDExUW+++aYyMjIkte4AkpWVJUk6fPiwUlJStHDhQqWlpWn58uWKjY3t9r7f/e53NW7cOF1//fVKS0vTmjVrFB4e7stQAQAAEMBC87crYvbFOjd6rCJmX6zQ/O3+HlKfGKZpmv4ehFWampyqrT3r72EAAACgF0Lzt2v0qjtkNDS42ky7Xacf/q0cKal+HJlnkZGj3bYTrgEAAOBXEbMvlu1YeZd255QYVZce8MOIeuYpXHP8OQAAAPwq6PixXrUHMsI1AAAA/Kpl8pRetQcywjUAAAD8qj5rnUy7vUObaberPmudn0bUd4RrAAAA+JUjJVWnH/6tnFNiZBqGnFNiAnoxY3dY0AgAAAD0EgsaAQAAgH5GuAYAAAAsQrgGAACApKFzSqI/Bft7AAAAAPCv0PztOufuNTJqqmX8o812rFyjV90hSYNyYaG/sKARAABgGHN39Hh7gXxKoj+xoBEAAABdjMpe7zFYS4PzlER/IlwDAAAMYz2F58F4SqI/Ea4BAACGse7C82A9JdGfCNcAAADDmNujxyW1REQM2lMS/YndQgAAAIaxtvA8Knu9go4fU8vkKarPWkeo7iN2CwEAAAB6id1CAAAAgH5GuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAwKAQmr9dEbMv1rnRYxUx+2KF5m/395C6IFwDAACgg0AMsaH52zV61R2yHSuXYZqyHSvX6FV3BMTY2uMQGQAAALi0hVijocHVZtrtfj8KPWL2xbIdK+/S7pwSo+rSAwM+Hk+HyBCuAQAA4BJoIbbNudFjZbiJraZhqPJk3YCPhxMaAQAA0KOg48d61T5QWiZP6VW7vxCuAQAA4DJQIba3dd31Wetk2u0d2ky7XfVZ6ywdl68I1wAAAMOAt2F2IEJsXxYnOlJSdfrh38o5JUamYcg5JcbvdeDuUHMNAAAwxPV2kWJo/naNyl6voOPH1DJ5iuqz1lkaYgO1rrs3WNAIAAAwTAVamA20xYl9wYJGAACAYSrQFikOlsWJfUG4BgAAGOICLcwOlsWJfUG4BgAAGOICLcwOlsWJfUHNNQAAwDDQ34sUhxsWNAIAAAAWYUEjAAAA0M8I1wAAAIBFCNcAAADwSm+PLB+Ogv09AAAAAAS+zqc8th1ZLomFke2woBEAAAA9CrRTHv3N04JGn2aua2trtXLlSh0/flyTJ0/Wpk2bNHbs2C79pk2bpqlTp0qSJk6cqC1btnS4vmHDBuXn52v//v2SpAceeEDvvPOOJOnLL79UVVWV9u3b58tQAQAA4INAO+UxUPkUrnNzcxUXF6eMjAzl5uYqNzdXq1ev7tIvLCxMhYWFbu9RVlamurqOZ8jffffdrl9v3bpVBw8e9GWYAAAA8JEZHi6jurpL+1A4stxKPi1o3LNnj5KTkyVJycnJ2r17d6+e73Q6lZOT4zaQt3n55Zd1ww03+DJMAAAA+CA0f7uM06e7tJuSgo6Vs7ixHZ/CdVVVlaKioiRJkZGRqqqqctvP4XBo0aJFSk1N7RDAt23bpvj4eNc9Ojt+/LiOHTumyy67zJdhAgAAwAejstfLaGrq0jajm4AAABiPSURBVG78439tixvdBezhtsNIj2Uh6enpqqys7NKemZnZ4bFhGDIMw+099u7dq+joaJWXlystLU1Tp05VaGiodu7cqa1bt3p87ZdfflnXXHONbDZbT8MEAABAP/GmrtpoaNCo7PUddg4ZjjuM9Biu8/LyPF4bP368KioqFBUVpYqKCkVERLjtFx0dLUmKiYnRnDlzdPDgQYWFheno0aNKTEyUJDU0NCghIUFFRUWu573yyiu69957e/N+AAAA0I3Q/O0alb1eQcePqWXyFNVnresx6LZMnuJ2p5DOOofwUdnrXcG6jbsQPpT4VBYyb948FRQUSJIKCgoUHx/fpU9dXZ0aGxslSdXV1SotLVVsbKzmzp2rkpISFRcXq7i4WHa7vUOwPnz4sE6dOqVZs2b5MkQAAAD8Q9tMsu1YuQzT7Laco736rHUy7fYe7995caPHHUb+Uac9FEtFfArXGRkZKikpUWJiot58801lZGRIat0BJCsrS1JrSE5JSdHChQuVlpam5cuXKzY2tsd7v/LKK7r++us9lpoAAACge53rnc/JWuNxJrk7jpRUnX74t3JOiZFpGGoJj5AZEtKhj2m3qz5rXYc2jzuJGEavA/5gwSEyAAAAQ1DnemepdXcPd9OWpmGo8mSdmyvd37+tvMQcFy4ZklFT06HUxO0YDEOGm/g52A6j8XSIjE8z1wAAAAhMbuudPfTtbq9qT7t9OFJSVV16QKcffVzGlw0Kqq7uMhPdecbbOSVG8jCvO1QOo2HmGgAAYAg6N3qs2xnizrPXpt2u0w//1u0CQ7czz536ezoWve2VW6bEyJFwjUKLXm0N0EFBMpzOLv2ZuQYAAEDA8jQbbYZHtM4kSzJtNukfNdfuap672+2jjacZ5/Z7YNuffsJVY204neoc+d3Vaw/W/bEJ1wAAAEOQux0+TElGTbWMmmopJESG09ntITAed/to1+7N8eedy1EMtQb7tlKRzjPnfd3VJBBQFgIAADBEheZv1zl3r2kN1F7071ya4anko30/d6Uj3uhuEaU3r+tvlIUAAAAMM46UVJmjRnkVrKWuM9VuZ787lXC0LVo0e3midncz3t7MmAcqwjUAAMAQ1ptA2jnwutvtw93iR0dKqk4/8phXB81I7musuxvHP59oBnz9NeEaAABgCPOmJlryHHjbttyrPFmn6tIDrv2rOy82dM1ge7q/1G1Ab8/TiZDd1YcHCmquAQAAhrDQ/O0a/ZPbZDQ1dWg3bTaZY8d2OfjFq/t1sz2fVfXSrkNqjpW7LWvxd/21p5prwjUAAMAQ135hoySZERE6k53jVZjurKfw7M3e2L3hcb/uPpwqaSXCNQAAAHzmTdhtfzR6b2bF3QnUnUPYLQQAAGCYs+JgFk813O3b3dVp93U83uxYEkgI1wAAAMOAVQezWBV2vR2PtzuWBArKQgAAAIYBK8srrCj78GU8Vpad9BU11wAAAMNYoC0M7Ot4rF4w2VfUXAMAAAxj3tRKD6S+jmdU9vouR60bDQ0alb3esrH5gnANAAAwDATawsC+jifQj0YnXAMAAAwDvV0YaMXOIlaOp02gzcB3Rs01AAAAOhjIuubeLk4M9JprwjUAAAA6GKiDW9wGZfV8giS7hQwQwjUAAIDvBmpnEU8hXmqdjW74wU0KLXrVryHaE3YLAQAAgFcGqq65u0WIRkOD7HlP+nzozUAjXAMAAKCDgdpZpKew3nn2PJC23POEcA0AAIAOvN3Joy87irR/jlFfLzMkpFdjC5Qt9zyh5hoAAGCI6s+Ff33ZtcPtc0aMkBkSIqO+Xka7vqZhuK37tnpRZV9Rcw0AADCMtAXZnmqW+7qfdV9OSnT7nKYmmeEROr35iQ4z5Q3ptwTUoTfeYuYaAABgCPJmOz1f9ozuy44ivX1OIGy55wkz1wAAAMOIN8eE92X2uU1fdhTx9jlts+mjf7xcknT60cdVXXogYIJ1dwjXAAAAQ5A3QdabAO5JX3YU8eY53pazBCrCNQAAwBDkTZDty+xz+1llM8yuloiIbncUac+bXUh8mU0PBNRcAwAADFE91Sz3tubalxptbw3U6ZC+4vhzAAAAdOEK4MfKJZtNcjrVMiXG7eJBT4skTZtNpx95zJKA7c1CzEDAgkYAAAB04UhJbS0VsdtlOJ0yJI91zp5qsQ2n07K66IE6HbK/MHMNAAAwzHk7W+ypn6f+fRXIW/C1oSwEAAAAbnlb5zxq7SrZ855029dd/6GMshAAAAC45c2uIaH522V/7vceg3V39xlOCNcAAADDnDd1zu62yOuu/3BFuAYAABjmvNl/2tNiRlPyao9rX7TtrX1u9FhFzL44oA+UoeYaAAAAPfLXFnkDsbd2X1BzDQAAgD7z1xZ5g+3ERsI1AAAAeuRN6Uh/8FSO4qnd3wjXAAAA8IojJVXVpQdUebJO1aUHehWse1s33dZfHiqYA3VnkmBfnlxbW6uVK1fq+PHjmjx5sjZt2qSxY8d26Tdt2jRNnTpVkjRx4kRt2bKlw/UNGzYoPz9f+/fvlyR99tlnWrt2rU6fPi2n06n/+I//0JVXXunLUAEAAOAnneum206AlOQ2oLurs24vkHcm8WnmOjc3V3Fxcdq1a5fi4uKUm5vrtl9YWJgKCwtVWFjYJViXlZWprq7jZuObN2/Wddddp4KCAv3qV7/S+vWBWVMDAACAnvW2btrTtn8DsTOJr3wK13v27FFycrIkKTk5Wbt37+7V851Op3JycrR69eoO7YZh6MyZM5Kk06dPKyoqypdhAgAAwI96qpvuXDIS5OmIdcPodTnKQPMpXFdVVbmCb2RkpKqqqtz2czgcWrRokVJTUzsE8G3btik+Pr5LeL799tv14osv6oorrlBGRobuueceX4YJAACAPrJij+nuToBsKwGxHSuXYZqt2/0ZRq/uE0h6rLlOT09XZWVll/bMzMwOjw3DkOHhg9i7d6+io6NVXl6utLQ0TZ06VaGhodq5c6e2bt3apf/LL7+s733ve/rRj36k/fv3a82aNXrppZcUFMT6SwAAgIHSm1rp0PztGpW9XkHHj6ll8hTVZ61z9anPWud2r+r6rHXuS0ZMU6ZhdDhqPZDrrNvrMVzn5eV5vDZ+/HhVVFQoKipKFRUVioiIcNsvOjpakhQTE6M5c+bo4MGDCgsL09GjR5WYmChJamhoUEJCgoqKirRjxw498cQTkqRZs2bJ4XCopqZG48eP7+37AwAAQB91VyvdPlz3FMLb+o7KXt9a8mGzSf+4j8cSENOUc0qM27AeyHyaCp43b54KCgokSQUFBYqPj+/Sp66uTo2NjZKk6upqlZaWKjY2VnPnzlVJSYmKi4tVXFwsu92uoqIiSa07irz11luSpMOHD8vhcHgM7gAAAOgf3u4x7c2CRUdKauvMs90uw+mUIXVfAvKPkx/7su2fP/m0FV9GRoYyMzO1Y8cOTZo0SZs2bZLUugPIc889p+zsbB0+fFjr1q2TYRgyTVPLly9XbGxst/e96667dM899ygvL0+GYegXv/iFx5ITAAAA9A8zPFxGdXWX9s61zz6F8EFcAuKOYZoeduYehJqanKqtPevvYQAAAAx6ofnbNfont8loaurQboaE6PSvH+0wkxwx++LWWehOnP+YfW5zbvTYDiHadU+1zlQPphKQyMjRbtt9mrkGAADA0DQqe32XYC1J5qhzugTf7hYsttcyeYrbEN7SKYQPZmy/AQAAMAz1tMWep1IPo7amS5sjJVWnH/6tnFNiZBqGx4Ne6rPWybTbO7QN5hIQdygLAQAAGGbcHS9u2u0dArG3pR59ee22LfvMceGSIRk1NYOmHKSNp7IQZq4BAACGGW929+ivWWZHSqqqSw/o9KOPy/iyQUHV1a7DY0avuqNPh9QEEsI1AADAMOPN7h7elnq06VxmMmrtqtbHUWN07sRwnRs1pkP5iTcBfzCiLAQAAGCYsbrkw22ZiSR3Gym3lZ+M/vFy9zuHGIYqT9b1egwDjbIQAAAASOq+5KOnhY7uuJ2F9tC3bXa6817ZbTy1DxaEawAAgCHMXVj2VPIhSaNX3SHbsfJe1UF7KjPprn9fa7r7Ev4HEmUhAAAAQ5Q3u4K019dyEU/P86Ttfu13DmnbLURSl7a2sfb2/fQnT2UhhGsAAIAhqqew3DncBh0rd18n3UMddK9qrt2c8NjtfdqF5/7aHrAvCNcAAADDjMfjxg1Dpx99vGuQNQy3/b0Jr52DulFTo6D6M136tYRHqOrQEbf36Ck8d/d+BnoRJAsaAQAAhpnuFg26XYRomjKNjvPN3u5t3bZ/deXJOlWXHpBxtt5tP3cnPLbpaYvAwbAIknANAAAwRHW3aNDjIkTTVEtEhFd7W3enL0G4p+cMhuPTCdcAAABDVHcHwXgKsoZat8s7/ejjqi490OeFgm6D8IgRMs7We9zpo6fw3NuDbfyBmmsAAIBhyN3iwfasWCTYvg7bHBcuo/6MjMZG1/XOO32E5m/XOXevkVFT3Xo9IkJnsnMCKjy3oeYaAAAALm2zwJ5mWXu7d7Wn12irwzZHjeoQrKWOx523hf2gmurW2fN/XB9sCNcAAADDlCMlVS1TYtxe83aRoLeHuvS0WNHtAst24bu3r+cvhGsAAIBhzJdFgm2zzd6c6NjTYsWewndvX89fCNcAAADDmC+LBL2dbZZ6DvHe7C7Sm9fzFxY0AgAAoE96e6iLu+POe3O0+WA4RCZ4QEcBAACAIaNl8hS3Jyp6moV2pKR6nBFva/cUvvvyev5AWQgAAAD6xOpDXTqf8tg5iHOIDAAAAIasgT7UhUNkBhg11wAAABgIHCIDAACAHgX6PtKBjgWNAAAAkNR1x462faQlBVTpRSBj5hoAAACSrNlHerjPfBOuAQAAhhlPAdibUxJ7um9/naA4WEI7CxoBAACGke4OaxmVvd7tPtLOKTGqLj3Q470jZl/s0/P7MmZ/lat4WtBIuAYAABhGugvA9VnrfAqx/XWCYn+Fdl+wWwgAAAC6Lf3wdR9pTycl+nqCoq/lKgOJcA0AADCM9BSAezolsTv9cYJiaP52Kch9ZA2kY8/bEK4BAACGkf48QtzqExRdtdZOZ5drgXbseRtqrgEAAIaZ0PztGpW9XkHHj6ll8hTVZ60LyH2sPdVamzabTj/ymF/HzIJGAAAADCr9tUDSCixoBAAAwKDSXwsk+xPhGgAAAAGpP+vD+wvhGgAAAN3y1+mIVi+QHAjUXAMAAMCjQDwdMRCwoBEAAAC9FoinIwYCFjQCAACg1wbT6YiBgHANAAAAjwbjjh3+5FO4rq2t1bJly5SYmKhly5aprs79foPTpk1TUlKSkpKStGLFii7XN2zYoFmzZrkeHz9+XGlpaVqwYIGWLl2qEydO+DJMAAAA9NFg3LHDn3wK17m5uYqLi9OuXbsUFxen3Nxct/3CwsJUWFiowsJCbdmypcO1srKyLqF848aNSk5O1osvvqgf//jH+s///E9fhgkAAIA+Gow7dviTT+F6z549Sk5OliQlJydr9+7dvXq+0+lUTk6OVq9e3aH98OHDuuyyyyRJl112mfbs2ePLMAEAAOADR0qqqksPqPJknapLDxCsu+FTuK6qqlJUVJQkKTIyUlVVVW77ORwOLVq0SKmpqR0C+LZt2xQfH++6R5sLL7xQu3btkiQVFRWpvr5eNTU1vgwVAAAA6HfBPXVIT09XZWVll/bMzMwOjw3DkGEYbu+xd+9eRUdHq7y8XGlpaZo6dapCQ0O1c+dObd26tUv/NWvW6P7779d///d/61vf+paio6Nls9m8fU8AAACAX/QYrvPy8jxeGz9+vCoqKhQVFaWKigpFRES47RcdHS1JiomJ0Zw5c3Tw4EGFhYXp6NGjSkxMlCQ1NDQoISFBRUVFio6O1iOPPCJJqq+v165duzRmzJjevjcAAABgQPlUFjJv3jwVFBRIkgoKChQfH9+lT11dnRobGyVJ1dXVKi0tVWxsrObOnauSkhIVFxeruLhYdrtdRUVFrn4tLS2SWhdNpqSk+DJMAAAAYED4FK4zMjJUUlKixMREvfnmm8rIyJDUugNIVlaWpNbFiSkpKVq4cKHS0tK0fPlyxcbGdnvfd999V9dee62uueYaVVZW6rbbbvNlmAAAAMCA4PhzAAAAoJc4/hwAAADoZ4RrAAAAwCKEawAAAMAihGsAAADAIkNqQSMAAADgT8xcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFc99If//hHzZ8/XxdeeKHKyspc7SUlJVq0aJEWLFigRYsW6a233nJd+9vf/qYFCxYoISFBGzZsELsfes/T5y1Jjz32mBISEnTNNdfojTfecLW//vrruuaaa5SQkKDc3NyBHvKQ8ve//12pqalKSkrSokWL9P7770uSTNPUhg0blJCQoAULFujAgQN+HunQsXXrVl177bWaP3++cnJyXO2evu+wxlNPPaULLrhA1dXVkviO95eNGzfq2muv1YIFC/Tv//7vOnXqlOsa3/H+wd+JfmCiVz7++GPz8OHD5pIlS8z333/f1X7gwAHzxIkTpmma5qFDh8zLL7/cdS0lJcXcv3+/2dLSYt5yyy3ma6+9NuDjHqw8fd4fffSRuWDBAtPhcJhHjx414+PjzebmZrO5udmMj483jx49ajocDnPBggXmRx995Md3MLgtW7bM9X197bXXzCVLlrh+fcstt5gtLS3m/v37ze9///v+HOaQ8dZbb5lpaWmmw+EwTdM0KysrTdP0/H2HNT777DPzRz/6kTl37lyzqqrKNE2+4/3ljTfeMJuamkzTNM2cnBwzJyfHNE2+4/2FvxP9g5nrXvr617+ur33ta13aL7roIkVHR0uSvvGNb8jhcKixsVEVFRU6c+aMZs6cKcMwlJycrD179gz0sActT5/3nj17NH/+fIWEhCgmJkbnnXee3n//fb3//vs677zzFBMTo5CQEM2fP5/P2weGYai+vl6SdPr0aUVFRUlq/fyTk5NlGIZmzpypU6dOqaKiwp9DHRKeffZZZWRkKCQkRJI0fvx4SZ6/77DGgw8+qNWrV8swDFcb3/H+cfnllys4OFiSNHPmTJ04cUIS3/H+wt+J/kG47gevvvqqLrroIoWEhOjkyZOaMGGC69qECRN08uRJP45uaOj8uUZHR+vkyZMe29E3d999t3JycnTllVdq48aNWrVqlaSunz/fa2scOXJE+/bt04033qglS5a4wgXf6/6ze/duRUVF6cILL+zQzne8/+Xn5+uKK66QxHe8v/C5+kewvwcQiNLT01VZWdmlPTMzU1dffXW3z/3oo4/00EMP6amnnuqv4Q05vnze8F13n//bb7+tn/70p7rmmmv0yiuvKCsrS3l5eQM/yCGku8/b6XSqrq5O27dvV1lZmTIzM5llskB3n/ljjz3Gn9cW8+bP9M2bN8tms2nhwoUDPTyg3xGu3ehreDhx4oRuv/12bdy4UV/5ylcktf4rse0/e7X1aSsfQau+fN6dP9eTJ0+6PldP7XCvu89/7dq1ysrKkiRdd911uueeeyTxvfZFd5/3s88+q4SEBBmGoUsvvVRBQUGqqanp9vuOnnn6zA8dOqRjx44pKSlJUuv3eNGiRXr++ef5jvugpz/TX3jhBb322mvKy8tzleLwHe8ffK7+QVmIRU6dOqWMjAzdeeed+uY3v+lqj4qK0jnnnKP33ntPpmmqoKBA8fHxfhzp0DBv3jy9/PLLamxsVHl5uY4cOaJLL71U06dP15EjR1ReXq7Gxka9/PLLmjdvnr+HO2hFRUXp3XfflSS9/fbbOv/88yW1fv4FBQUyTVPvvfeeRo8e7arHRt9dffXVeueddyRJn3zyiZqamhQeHu7x+w7fXHDBBXrrrbdUXFys4uJiTZgwQS+88IIiIyP5jveT119/XU888YQ2b94su93uauc73j/4O9E/DNNkX7jeKCoq0v3336/q6mqNGTNG06ZN05NPPqlHH31Uubm5Ou+881x9n3rqKY0fP15lZWX66U9/qi+//FJXXHGFfvazn3VYOAPPPH3eUut/VszPz5fNZtPdd9+tK6+8UpL0v//7v3rggQfkdDqVkpKi2267zZ9vYVDbt2+fHnjgATU3Nys0NFTr1q3TJZdcItM09fOf/1xvvPGG7Ha7HnjgAU2fPt3fwx30Ghsbdffdd+uDDz7QiBEjtGbNGsXFxUny/H2HdebNm6cdO3YoIiKC73g/SUhIUGNjo8aNGydJmjFjhn7+859L4jveX/g7ceARrgEAAACLUBYCAAAAWIRwDQAAAFiEcA0AAABYhHANAAAAWIRwDQAAAFiEcA0AAABYhHANAAAAWIRwDQAAAFjk/wEGhp+KMkAGXQAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "d853fe0e-6ca4-411f-aa83-248f61309efe"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 17s 23ms/step - loss: 0.0047 - rmse: 0.0047\n",
-            "MAE: 0.004736608359962702\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YXcsNZ8yu9Ay",
-        "outputId": "0b7ee485-e356-4c5b-8a9c-257d8803d189"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "174/174 [==============================] - 4s 24ms/step - loss: 0.0047 - rmse: 0.0047\n",
-            "MAE: 0.004736608359962702\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "uCFgbZEOvZ9A",
-        "outputId": "46302cac-3d92-4970-c100-e5c3a13847f0"
-      },
-      "source": [
-        "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
-        "\n",
-        "plt.figure(figsize=(10,5))\n",
-        "plt.plot(y_pred_test)\n",
-        "plt.plot(y_val_multi)\n",
-        "plt.ylabel(\"RUL\")\n",
-        "plt.xlabel(\"Unit Number\")\n",
-        "plt.legend(loc='upper left')\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "No handles with labels found to put in legend.\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 720x360 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "8c28f578-4405-4a27-81e4-c0fd00475b96"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "179123d5-8aec-4dda-a400-9096dec19dd8"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "75071f5e-5942-4939-a33b-2dc8780e260c"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "af5ce749-d888-4cae-ddcd-9a5a5ce6e558"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "8beab52c-ffb7-415c-c84c-04ed39cd70cf"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "a6c042dc-999a-456c-b233-a1e05612e15f"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "6f325187-ee1b-4122-97f7-80ffdbf149d2"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YoQA_MIBMknS"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "a44c4d8b-e9d2-4978-fb9e-ae179758e6bc"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "c3e3d463-1089-48f7-da23-01a7b92423a5"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "7e9b0a07-d2de-4e42-d45f-572a8abeae9e"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "f8c5d0a8-c26a-4aa5-a530-957480984106"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "4dca8628-c567-41b0-f262-bc6a3dddb5a7"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "7747f2fc-9d3d-4e46-9148-39708b9ae947"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "f3dccf5d-76c2-4c9a-898b-9a221f5a491c"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XkGTfQ46NAlo"
+   },
+   "source": [
+    "## Why Increase Depth?\n",
+    "Stacking LSTM hidden layers makes the model deeper, more accurately earning the description as a deep learning technique. It is the depth of neural networks that is generally attributed to the success of the approach on a wide range of challenging prediction problems.\n",
+    "\n",
+    "As Stacked LSTMs are now a stable technique for challenging sequence prediction problems. A Stacked LSTM architecture is defined as an LSTM model comprised of multiple LSTM layers. An LSTM layer above provides a sequence output rather than a single value output to the LSTM layer below. Specifically, one output per input time step, rather than one output time step for all input time steps.\n",
+    "\n",
+    "We created Stacked LSTM model using Keras which is a Python deep learning library. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "eed7670c-b3b2-4a20-82bb-7ff2b5f4a0eb"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:]))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "\n",
+    "\n",
+    "\n",
+    "single_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "25c66158-969a-47c4-d35b-9c34abba211e"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "0a474737-67b6-4ff1-d6b2-37b7623a44ce"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "8e38f8da-d7ac-40ce-eec9-eee2320fd828"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "7b932e10-bb78-4eac-8757-4aa2d915b96d"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "72c81185-3db8-4d45-f1f2-9bf5861c3a3e"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "a4a392fe-73a5-44f7-ae77-003e7c46a1ad"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "8b881aff-b91b-4394-bc3d-e52261e546db"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:]))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "70f65cf2-a2fd-4a1e-b9e0-049430410a1d"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "f2d25889-8aa1-4405-d607-1ed72a0df675"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "d853fe0e-6ca4-411f-aa83-248f61309efe"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YXcsNZ8yu9Ay",
+    "outputId": "0b7ee485-e356-4c5b-8a9c-257d8803d189"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "uCFgbZEOvZ9A",
+    "outputId": "46302cac-3d92-4970-c100-e5c3a13847f0"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
+    "\n",
+    "plt.figure(figsize=(10,5))\n",
+    "plt.plot(y_pred_test)\n",
+    "plt.plot(y_val_multi)\n",
+    "plt.ylabel(\"RUL\")\n",
+    "plt.xlabel(\"Unit Number\")\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "stacked-LSTM_Correlation.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/models/failure_prediction/jnotebooks/vIMS_Visualization.ipynb b/models/failure_prediction/jnotebooks/vIMS_Visualization.ipynb

index 91347b4..5ccc615 100644 (file)
--- a/models/failure_prediction/jnotebooks/vIMS_Visualization.ipynb
+++ b/models/failure_prediction/jnotebooks/vIMS_Visualization.ipynb
@@ -1,4104 +1,1033 @@
  {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "pRQZOrAplLuo"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "6rUjno0va6DX"
+   },
+   "outputs": [],
+   "source": [
+    "#import some necessary librairies\n",
+    "\n",
+    "import numpy as np # linear algebra\n",
+    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)<\n",
+    "\n",
+    "\n",
+    "# To plot pretty figures\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.rcParams['axes.labelsize'] = 14\n",
+    "plt.rcParams['xtick.labelsize'] = 12\n",
+    "plt.rcParams['ytick.labelsize'] = 12\n",
+    "\n",
+    "\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "import warnings\n",
+    "def ignore_warn(*args, **kwargs):\n",
+    "    pass\n",
+    "warnings.warn = ignore_warn #ignore annoying warning (from sklearn and seaborn)\n",
+    "\n",
+    "\n",
+    "from scipy import stats\n",
+    "from scipy.stats import norm, skew #for some statistics\n",
+    "\n",
+    "\n",
+    "pd.set_option('display.float_format', lambda x: '{:.3f}'.format(x)) #Limiting floats output to 3 decimal points\n",
+    "\n",
+    "\n",
+    "from subprocess import check_output\n",
+    "#print(check_output([\"ls\", \"../input\"]).decode(\"utf8\")) #check the files available in the directory"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "K4CRikWVbT1d"
+   },
+   "source": [
+    "# **X.npy data /all data stored in the npy format**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
      "colab": {
-      "name": "vIMS_Visualization.ipynb",
-      "provenance": []
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "geh5BNM3bhmT",
+    "outputId": "0f5af44d-de19-438b-e4de-5f703c59a687"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/gdrive')"
+   ]
    },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "pRQZOrAplLuo"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6rUjno0va6DX"
-      },
-      "source": [
-        "#import some necessary librairies\n",
-        "\n",
-        "import numpy as np # linear algebra\n",
-        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)<\n",
-        "\n",
-        "\n",
-        "# To plot pretty figures\n",
-        "%matplotlib inline\n",
-        "import matplotlib.pyplot as plt\n",
-        "plt.rcParams['axes.labelsize'] = 14\n",
-        "plt.rcParams['xtick.labelsize'] = 12\n",
-        "plt.rcParams['ytick.labelsize'] = 12\n",
-        "\n",
-        "\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "import warnings\n",
-        "def ignore_warn(*args, **kwargs):\n",
-        "    pass\n",
-        "warnings.warn = ignore_warn #ignore annoying warning (from sklearn and seaborn)\n",
-        "\n",
-        "\n",
-        "from scipy import stats\n",
-        "from scipy.stats import norm, skew #for some statistics\n",
-        "\n",
-        "\n",
-        "pd.set_option('display.float_format', lambda x: '{:.3f}'.format(x)) #Limiting floats output to 3 decimal points\n",
-        "\n",
-        "\n",
-        "from subprocess import check_output\n",
-        "#print(check_output([\"ls\", \"../input\"]).decode(\"utf8\")) #check the files available in the directory"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "K4CRikWVbT1d"
-      },
-      "source": [
-        "# **X.npy data /all data stored in the npy format**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "geh5BNM3bhmT",
-        "outputId": "0f5af44d-de19-438b-e4de-5f703c59a687"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/gdrive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /gdrive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "PanwhFGBbDV7"
-      },
-      "source": [
-        "# we are here loading the all dataset and showing the all features and sort them per server\n",
-        "X = np.load('/gdrive/MyDrive/LFN Anuket/Analysis/data/X.npy', allow_pickle=True)\n",
-        "dframe = pd.DataFrame(data=X,columns=['ellis-cpu.idle_perc', 'ralf-load.avg_15_min', 'bono-net.in_errors_sec', 'homer-net.out_bytes_sec', 'ellis-io.write_req_sec', 'homer-mem.total_mb', 'homestead-load.avg_1_min', 'homer-load.avg_1_min', 'sprout-cpu.stolen_perc', 'ralf-cpu.idle_perc', 'sprout-io.read_req_sec', 'homestead-net.in_bytes_sec', 'homer-disk.space_used_perc', 'bono-net.out_packets_sec', 'homer-cpu.wait_perc', 'ellis-net.in_packets_sec', 'bono-mem.free_mb', 'ellis-io.read_req_sec', 'bono-mem.usable_mb', 'bono-net.in_packets_dropped_sec', 'homestead-mem.free_mb', 'homer-io.write_time_sec', 'sprout-io.write_time_sec', 'homestead-net.in_errors_sec', 'homestead-mem.usable_perc', 'homestead-net.in_packets_dropped_sec', 'homestead-io.write_req_sec', 'bono-net.in_bytes_sec', 'homestead-disk.space_used_perc', 'homer-net.out_packets_sec', 'bono-mem.usable_perc', 'ralf-net.out_errors_sec', 'homestead-load.avg_5_min', 'sprout-io.read_kbytes_sec', 'sprout-net.out_errors_sec', 'homestead-io.write_kbytes_sec', 'homestead-net.in_packets_sec', 'sprout-mem.usable_mb', 'homestead-cpu.idle_perc', 'ralf-io.write_time_sec', 'ralf-io.write_kbytes_sec', 'ralf-io.write_req_sec', 'ellis-net.out_bytes_sec', 'bono-io.read_kbytes_sec', 'bono-disk.space_used_perc', 'homer-net.in_packets_dropped_sec', 'ralf-mem.usable_mb', 'bono-load.avg_15_min', 'bono-io.read_time_sec', 'sprout-mem.usable_perc', 'bono-cpu.idle_perc', 'homer-mem.usable_perc', 'homestead-cpu.stolen_perc', 'ralf-io.read_req_sec', 'homer-cpu.idle_perc', 'homestead-mem.total_mb', 'ralf-load.avg_1_min', 'homer-io.read_kbytes_sec', 'homestead-io.read_req_sec', 'ellis-mem.free_mb', 'bono-io.write_time_sec', 'ellis-net.out_errors_sec', 'ellis-cpu.stolen_perc', 'ellis-mem.usable_perc', 'ralf-disk.inode_used_perc', 'sprout-load.avg_15_min', 'ellis-io.read_time_sec', 'ralf-net.out_packets_sec', 'sprout-io.write_req_sec', 'bono-cpu.stolen_perc', 'homestead-load.avg_15_min', 'bono-cpu.system_perc', 'homestead-net.out_packets_sec', 'ellis-io.write_kbytes_sec', 'sprout-cpu.idle_perc', 'ellis-mem.total_mb', 'homer-mem.usable_mb', 'bono-load.avg_5_min', 'ellis-load.avg_5_min', 'homer-cpu.stolen_perc', 'sprout-net.out_bytes_sec', 'homestead-mem.usable_mb', 'homestead-disk.inode_used_perc', 'ralf-net.in_packets_dropped_sec', 'sprout-io.write_kbytes_sec', 'ellis-load.avg_15_min', 'homer-load.avg_5_min', 'ralf-mem.usable_perc', 'bono-net.out_bytes_sec', 'ellis-cpu.system_perc', 'homer-io.read_time_sec', 'ellis-disk.inode_used_perc', 'homestead-io.read_time_sec', 'sprout-net.in_bytes_sec', 'bono-io.write_kbytes_sec', 'homestead-io.read_kbytes_sec', 'ellis-net.in_errors_sec', 'sprout-io.read_time_sec', 'homer-disk.inode_used_perc', 'ralf-cpu.wait_perc', 'homer-load.avg_15_min', 'sprout-load.avg_5_min', 'homer-io.read_req_sec', 'ralf-mem.total_mb', 'homer-mem.free_mb', 'homer-net.in_packets_sec', 'homestead-net.out_bytes_sec', 'sprout-disk.inode_used_perc', 'ellis-mem.usable_mb', 'homer-io.write_kbytes_sec', 'homer-net.out_errors_sec', 'homer-cpu.system_perc', 'ellis-io.read_kbytes_sec', 'sprout-load.avg_1_min', 'sprout-cpu.system_perc', 'ralf-cpu.stolen_perc', 'bono-mem.total_mb', 'bono-net.out_errors_sec', 'ellis-io.write_time_sec', 'ralf-io.read_time_sec', 'sprout-cpu.wait_perc', 'ellis-cpu.wait_perc', 'ralf-disk.space_used_perc', 'ralf-net.out_bytes_sec', 'ellis-net.in_packets_dropped_sec', 'homer-net.in_bytes_sec', 'ellis-net.in_bytes_sec', 'bono-cpu.wait_perc', 'ralf-net.in_packets_sec', 'sprout-mem.total_mb', 'ralf-net.in_bytes_sec', 'bono-load.avg_1_min', 'sprout-net.in_packets_sec', 'bono-io.write_req_sec', 'ralf-load.avg_5_min', 'ralf-net.in_errors_sec', 'bono-disk.inode_used_perc', 'homestead-io.write_time_sec', 'ellis-net.out_packets_sec', 'sprout-disk.space_used_perc', 'ralf-io.read_kbytes_sec', 'homestead-cpu.system_perc', 'sprout-mem.free_mb', 'homer-net.in_errors_sec', 'homestead-net.out_errors_sec', 'homer-io.write_req_sec', 'sprout-net.in_errors_sec', 'ellis-disk.space_used_perc', 'sprout-net.out_packets_sec', 'sprout-net.in_packets_dropped_sec', 'ralf-cpu.system_perc', 'ralf-mem.free_mb', 'bono-io.read_req_sec', 'bono-net.in_packets_sec', 'homestead-cpu.wait_perc', 'ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "nAia0RRkbcSV"
-      },
-      "source": [
-        "dframesorted = dframe.sort_index(axis=1, ascending=True, inplace=False, kind='quicksort')"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 270
-        },
-        "id": "76XHMM3cfWGW",
-        "outputId": "87965d6f-7c2a-4c39-ed9e-f372a0ade7ca"
-      },
-      "source": [
-        "dframesorted.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>bono-cpu.idle_perc</th>\n",
-              "      <th>bono-cpu.stolen_perc</th>\n",
-              "      <th>bono-cpu.system_perc</th>\n",
-              "      <th>bono-cpu.wait_perc</th>\n",
-              "      <th>bono-disk.inode_used_perc</th>\n",
-              "      <th>bono-disk.space_used_perc</th>\n",
-              "      <th>bono-io.read_kbytes_sec</th>\n",
-              "      <th>bono-io.read_req_sec</th>\n",
-              "      <th>bono-io.read_time_sec</th>\n",
-              "      <th>bono-io.write_kbytes_sec</th>\n",
-              "      <th>bono-io.write_req_sec</th>\n",
-              "      <th>bono-io.write_time_sec</th>\n",
-              "      <th>bono-load.avg_15_min</th>\n",
-              "      <th>bono-load.avg_1_min</th>\n",
-              "      <th>bono-load.avg_5_min</th>\n",
-              "      <th>bono-mem.free_mb</th>\n",
-              "      <th>bono-mem.total_mb</th>\n",
-              "      <th>bono-mem.usable_mb</th>\n",
-              "      <th>bono-mem.usable_perc</th>\n",
-              "      <th>bono-net.in_bytes_sec</th>\n",
-              "      <th>bono-net.in_errors_sec</th>\n",
-              "      <th>bono-net.in_packets_dropped_sec</th>\n",
-              "      <th>bono-net.in_packets_sec</th>\n",
-              "      <th>bono-net.out_bytes_sec</th>\n",
-              "      <th>bono-net.out_errors_sec</th>\n",
-              "      <th>bono-net.out_packets_sec</th>\n",
-              "      <th>ellis-cpu.idle_perc</th>\n",
-              "      <th>ellis-cpu.stolen_perc</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-disk.inode_used_perc</th>\n",
-              "      <th>ellis-disk.space_used_perc</th>\n",
-              "      <th>ellis-io.read_kbytes_sec</th>\n",
-              "      <th>ellis-io.read_req_sec</th>\n",
-              "      <th>ellis-io.read_time_sec</th>\n",
-              "      <th>ellis-io.write_kbytes_sec</th>\n",
-              "      <th>ellis-io.write_req_sec</th>\n",
-              "      <th>ellis-io.write_time_sec</th>\n",
-              "      <th>ellis-load.avg_15_min</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>...</th>\n",
-              "      <th>ralf-load.avg_15_min</th>\n",
-              "      <th>ralf-load.avg_1_min</th>\n",
-              "      <th>ralf-load.avg_5_min</th>\n",
-              "      <th>ralf-mem.free_mb</th>\n",
-              "      <th>ralf-mem.total_mb</th>\n",
-              "      <th>ralf-mem.usable_mb</th>\n",
-              "      <th>ralf-mem.usable_perc</th>\n",
-              "      <th>ralf-net.in_bytes_sec</th>\n",
-              "      <th>ralf-net.in_errors_sec</th>\n",
-              "      <th>ralf-net.in_packets_dropped_sec</th>\n",
-              "      <th>ralf-net.in_packets_sec</th>\n",
-              "      <th>ralf-net.out_bytes_sec</th>\n",
-              "      <th>ralf-net.out_errors_sec</th>\n",
-              "      <th>ralf-net.out_packets_sec</th>\n",
-              "      <th>sprout-cpu.idle_perc</th>\n",
-              "      <th>sprout-cpu.stolen_perc</th>\n",
-              "      <th>sprout-cpu.system_perc</th>\n",
-              "      <th>sprout-cpu.wait_perc</th>\n",
-              "      <th>sprout-disk.inode_used_perc</th>\n",
-              "      <th>sprout-disk.space_used_perc</th>\n",
-              "      <th>sprout-io.read_kbytes_sec</th>\n",
-              "      <th>sprout-io.read_req_sec</th>\n",
-              "      <th>sprout-io.read_time_sec</th>\n",
-              "      <th>sprout-io.write_kbytes_sec</th>\n",
-              "      <th>sprout-io.write_req_sec</th>\n",
-              "      <th>sprout-io.write_time_sec</th>\n",
-              "      <th>sprout-load.avg_15_min</th>\n",
-              "      <th>sprout-load.avg_1_min</th>\n",
-              "      <th>sprout-load.avg_5_min</th>\n",
-              "      <th>sprout-mem.free_mb</th>\n",
-              "      <th>sprout-mem.total_mb</th>\n",
-              "      <th>sprout-mem.usable_mb</th>\n",
-              "      <th>sprout-mem.usable_perc</th>\n",
-              "      <th>sprout-net.in_bytes_sec</th>\n",
-              "      <th>sprout-net.in_errors_sec</th>\n",
-              "      <th>sprout-net.in_packets_dropped_sec</th>\n",
-              "      <th>sprout-net.in_packets_sec</th>\n",
-              "      <th>sprout-net.out_bytes_sec</th>\n",
-              "      <th>sprout-net.out_errors_sec</th>\n",
-              "      <th>sprout-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>8.249</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>2.824</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.019</td>\n",
-              "      <td>1.727</td>\n",
-              "      <td>1.083</td>\n",
-              "      <td>6.593</td>\n",
-              "      <td>3.976</td>\n",
-              "      <td>5.287</td>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.529</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>7.156</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.026</td>\n",
-              "      <td>1.488</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>6.553</td>\n",
-              "      <td>7.035</td>\n",
-              "      <td>...</td>\n",
-              "      <td>6.025</td>\n",
-              "      <td>1.590</td>\n",
-              "      <td>4.116</td>\n",
-              "      <td>7.513</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.532</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.063</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.537</td>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.478</td>\n",
-              "      <td>4.784</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.982</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>6.638</td>\n",
-              "      <td>5.770</td>\n",
-              "      <td>6.718</td>\n",
-              "      <td>8.707</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.378</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.442</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>8.507</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>2.553</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.018</td>\n",
-              "      <td>1.716</td>\n",
-              "      <td>1.072</td>\n",
-              "      <td>6.366</td>\n",
-              "      <td>2.793</td>\n",
-              "      <td>4.878</td>\n",
-              "      <td>7.725</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.529</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>7.729</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>5.138</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.026</td>\n",
-              "      <td>1.501</td>\n",
-              "      <td>1.075</td>\n",
-              "      <td>6.659</td>\n",
-              "      <td>7.244</td>\n",
-              "      <td>...</td>\n",
-              "      <td>6.343</td>\n",
-              "      <td>4.910</td>\n",
-              "      <td>5.119</td>\n",
-              "      <td>7.509</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.528</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.049</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.525</td>\n",
-              "      <td>7.990</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>4.477</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.037</td>\n",
-              "      <td>1.990</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>6.638</td>\n",
-              "      <td>4.990</td>\n",
-              "      <td>6.579</td>\n",
-              "      <td>8.711</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.012</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.377</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.428</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>8.140</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>2.930</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.017</td>\n",
-              "      <td>1.666</td>\n",
-              "      <td>1.095</td>\n",
-              "      <td>6.196</td>\n",
-              "      <td>2.076</td>\n",
-              "      <td>4.519</td>\n",
-              "      <td>7.722</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.526</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.083</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>7.410</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>5.741</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.491</td>\n",
-              "      <td>1.081</td>\n",
-              "      <td>6.659</td>\n",
-              "      <td>6.302</td>\n",
-              "      <td>...</td>\n",
-              "      <td>6.502</td>\n",
-              "      <td>5.810</td>\n",
-              "      <td>5.575</td>\n",
-              "      <td>7.512</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.539</td>\n",
-              "      <td>7.866</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.398</td>\n",
-              "      <td>4.580</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.035</td>\n",
-              "      <td>1.984</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>6.537</td>\n",
-              "      <td>3.910</td>\n",
-              "      <td>6.210</td>\n",
-              "      <td>8.709</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.381</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.441</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>7.964</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.250</td>\n",
-              "      <td>3.171</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.017</td>\n",
-              "      <td>1.677</td>\n",
-              "      <td>1.095</td>\n",
-              "      <td>6.025</td>\n",
-              "      <td>1.645</td>\n",
-              "      <td>4.161</td>\n",
-              "      <td>7.722</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.526</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.081</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.170</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.135</td>\n",
-              "      <td>7.177</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.484</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>6.712</td>\n",
-              "      <td>5.988</td>\n",
-              "      <td>...</td>\n",
-              "      <td>6.449</td>\n",
-              "      <td>4.600</td>\n",
-              "      <td>5.438</td>\n",
-              "      <td>7.500</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.521</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.048</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.061</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.516</td>\n",
-              "      <td>7.955</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>4.545</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.976</td>\n",
-              "      <td>1.074</td>\n",
-              "      <td>6.384</td>\n",
-              "      <td>3.070</td>\n",
-              "      <td>5.840</td>\n",
-              "      <td>8.709</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.994</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.427</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>8.086</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>3.005</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.018</td>\n",
-              "      <td>1.705</td>\n",
-              "      <td>1.100</td>\n",
-              "      <td>6.139</td>\n",
-              "      <td>3.402</td>\n",
-              "      <td>4.519</td>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.528</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.183</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.142</td>\n",
-              "      <td>7.347</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>5.862</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.484</td>\n",
-              "      <td>1.087</td>\n",
-              "      <td>6.765</td>\n",
-              "      <td>6.023</td>\n",
-              "      <td>...</td>\n",
-              "      <td>6.502</td>\n",
-              "      <td>4.693</td>\n",
-              "      <td>5.575</td>\n",
-              "      <td>7.502</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.524</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.542</td>\n",
-              "      <td>7.848</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.518</td>\n",
-              "      <td>4.443</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.984</td>\n",
-              "      <td>1.074</td>\n",
-              "      <td>6.384</td>\n",
-              "      <td>3.370</td>\n",
-              "      <td>5.840</td>\n",
-              "      <td>8.707</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.380</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.441</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>5 rows × 156 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  bono-cpu.idle_perc  ... sprout-net.out_packets_sec\n",
-              "0              8.249  ...                      1.442\n",
-              "1              8.507  ...                      1.428\n",
-              "2              8.140  ...                      1.441\n",
-              "3              7.964  ...                      1.427\n",
-              "4              8.086  ...                      1.441\n",
-              "\n",
-              "[5 rows x 156 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 5
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "lKCAS0m7fe5F"
-      },
-      "source": [
-        "#dframesorted.describe()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "vnThYldxXdaw",
-        "outputId": "696f7fee-55eb-4d38-d471-17d1dd4e2e7e"
-      },
-      "source": [
-        "# here we print the name col to select later metrics per server. \n",
-        "print('Column names are: ',list(dframesorted.columns))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Column names are:  ['bono-cpu.idle_perc', 'bono-cpu.stolen_perc', 'bono-cpu.system_perc', 'bono-cpu.wait_perc', 'bono-disk.inode_used_perc', 'bono-disk.space_used_perc', 'bono-io.read_kbytes_sec', 'bono-io.read_req_sec', 'bono-io.read_time_sec', 'bono-io.write_kbytes_sec', 'bono-io.write_req_sec', 'bono-io.write_time_sec', 'bono-load.avg_15_min', 'bono-load.avg_1_min', 'bono-load.avg_5_min', 'bono-mem.free_mb', 'bono-mem.total_mb', 'bono-mem.usable_mb', 'bono-mem.usable_perc', 'bono-net.in_bytes_sec', 'bono-net.in_errors_sec', 'bono-net.in_packets_dropped_sec', 'bono-net.in_packets_sec', 'bono-net.out_bytes_sec', 'bono-net.out_errors_sec', 'bono-net.out_packets_sec', 'ellis-cpu.idle_perc', 'ellis-cpu.stolen_perc', 'ellis-cpu.system_perc', 'ellis-cpu.wait_perc', 'ellis-disk.inode_used_perc', 'ellis-disk.space_used_perc', 'ellis-io.read_kbytes_sec', 'ellis-io.read_req_sec', 'ellis-io.read_time_sec', 'ellis-io.write_kbytes_sec', 'ellis-io.write_req_sec', 'ellis-io.write_time_sec', 'ellis-load.avg_15_min', 'ellis-load.avg_1_min', 'ellis-load.avg_5_min', 'ellis-mem.free_mb', 'ellis-mem.total_mb', 'ellis-mem.usable_mb', 'ellis-mem.usable_perc', 'ellis-net.in_bytes_sec', 'ellis-net.in_errors_sec', 'ellis-net.in_packets_dropped_sec', 'ellis-net.in_packets_sec', 'ellis-net.out_bytes_sec', 'ellis-net.out_errors_sec', 'ellis-net.out_packets_sec', 'homer-cpu.idle_perc', 'homer-cpu.stolen_perc', 'homer-cpu.system_perc', 'homer-cpu.wait_perc', 'homer-disk.inode_used_perc', 'homer-disk.space_used_perc', 'homer-io.read_kbytes_sec', 'homer-io.read_req_sec', 'homer-io.read_time_sec', 'homer-io.write_kbytes_sec', 'homer-io.write_req_sec', 'homer-io.write_time_sec', 'homer-load.avg_15_min', 'homer-load.avg_1_min', 'homer-load.avg_5_min', 'homer-mem.free_mb', 'homer-mem.total_mb', 'homer-mem.usable_mb', 'homer-mem.usable_perc', 'homer-net.in_bytes_sec', 'homer-net.in_errors_sec', 'homer-net.in_packets_dropped_sec', 'homer-net.in_packets_sec', 'homer-net.out_bytes_sec', 'homer-net.out_errors_sec', 'homer-net.out_packets_sec', 'homestead-cpu.idle_perc', 'homestead-cpu.stolen_perc', 'homestead-cpu.system_perc', 'homestead-cpu.wait_perc', 'homestead-disk.inode_used_perc', 'homestead-disk.space_used_perc', 'homestead-io.read_kbytes_sec', 'homestead-io.read_req_sec', 'homestead-io.read_time_sec', 'homestead-io.write_kbytes_sec', 'homestead-io.write_req_sec', 'homestead-io.write_time_sec', 'homestead-load.avg_15_min', 'homestead-load.avg_1_min', 'homestead-load.avg_5_min', 'homestead-mem.free_mb', 'homestead-mem.total_mb', 'homestead-mem.usable_mb', 'homestead-mem.usable_perc', 'homestead-net.in_bytes_sec', 'homestead-net.in_errors_sec', 'homestead-net.in_packets_dropped_sec', 'homestead-net.in_packets_sec', 'homestead-net.out_bytes_sec', 'homestead-net.out_errors_sec', 'homestead-net.out_packets_sec', 'ralf-cpu.idle_perc', 'ralf-cpu.stolen_perc', 'ralf-cpu.system_perc', 'ralf-cpu.wait_perc', 'ralf-disk.inode_used_perc', 'ralf-disk.space_used_perc', 'ralf-io.read_kbytes_sec', 'ralf-io.read_req_sec', 'ralf-io.read_time_sec', 'ralf-io.write_kbytes_sec', 'ralf-io.write_req_sec', 'ralf-io.write_time_sec', 'ralf-load.avg_15_min', 'ralf-load.avg_1_min', 'ralf-load.avg_5_min', 'ralf-mem.free_mb', 'ralf-mem.total_mb', 'ralf-mem.usable_mb', 'ralf-mem.usable_perc', 'ralf-net.in_bytes_sec', 'ralf-net.in_errors_sec', 'ralf-net.in_packets_dropped_sec', 'ralf-net.in_packets_sec', 'ralf-net.out_bytes_sec', 'ralf-net.out_errors_sec', 'ralf-net.out_packets_sec', 'sprout-cpu.idle_perc', 'sprout-cpu.stolen_perc', 'sprout-cpu.system_perc', 'sprout-cpu.wait_perc', 'sprout-disk.inode_used_perc', 'sprout-disk.space_used_perc', 'sprout-io.read_kbytes_sec', 'sprout-io.read_req_sec', 'sprout-io.read_time_sec', 'sprout-io.write_kbytes_sec', 'sprout-io.write_req_sec', 'sprout-io.write_time_sec', 'sprout-load.avg_15_min', 'sprout-load.avg_1_min', 'sprout-load.avg_5_min', 'sprout-mem.free_mb', 'sprout-mem.total_mb', 'sprout-mem.usable_mb', 'sprout-mem.usable_perc', 'sprout-net.in_bytes_sec', 'sprout-net.in_errors_sec', 'sprout-net.in_packets_dropped_sec', 'sprout-net.in_packets_sec', 'sprout-net.out_bytes_sec', 'sprout-net.out_errors_sec', 'sprout-net.out_packets_sec']\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "8-pffUQBXojo"
-      },
-      "source": [
-        "# **X_126bis / all data with less 30 features and csv format**\n",
-        "cpu.stolen_perc\n",
-        "\n",
-        "mem.total_mb\n",
-        "\n",
-        "net.in_errors_sec\n",
-        "\n",
-        "net.in_packets_dropped_sec\n",
-        "\n",
-        "net.out_errors_sec"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "HE4xoUdNXgLi",
-        "outputId": "16443f8c-111b-4023-d192-345e02c5a49f"
-      },
-      "source": [
-        "X_126bis = dframesorted.drop(['sprout-cpu.stolen_perc', 'sprout-mem.total_mb', 'sprout-net.in_errors_sec', 'sprout-net.in_packets_dropped_sec', 'sprout-net.out_errors_sec','homer-cpu.stolen_perc', 'homer-mem.total_mb', 'homer-net.in_errors_sec', 'homer-net.in_packets_dropped_sec', 'homer-net.out_errors_sec','ellis-cpu.stolen_perc', 'ellis-mem.total_mb', 'ellis-net.in_errors_sec', 'ellis-net.in_packets_dropped_sec', 'ellis-net.out_errors_sec', 'bono-cpu.stolen_perc', 'bono-mem.total_mb', 'bono-net.in_errors_sec', 'bono-net.in_packets_dropped_sec', 'bono-net.out_errors_sec', 'ralf-cpu.stolen_perc', 'ralf-mem.total_mb', 'ralf-net.in_errors_sec', 'ralf-net.in_packets_dropped_sec', 'ralf-net.out_errors_sec', 'homestead-cpu.stolen_perc', 'homestead-mem.total_mb', 'homestead-net.in_errors_sec', 'homestead-net.in_packets_dropped_sec', 'homestead-net.out_errors_sec'], axis =1)\n",
-        "\n",
-        "dframesorted.shape, X_126bis.shape"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "((177000, 156), (177000, 126))"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 8
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "5_8LHtazXvwf"
-      },
-      "source": [
-        "X_126bis.to_csv('X_126bis.csv', sep=',')"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "sknAZgiPX6_2"
-      },
-      "source": [
-        "# **df_Ellis.csv / extract the ellis server metrics**\n",
-        "1) Ellis Server with 26 metrics\n",
-        "\n",
-        "2) subselection of the Ellis metrics"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "S6n-hPD3X43P"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['ellis-cpu.idle_perc', 'ellis-cpu.stolen_perc', 'ellis-cpu.system_perc', 'ellis-cpu.wait_perc', 'ellis-disk.inode_used_perc', 'ellis-disk.space_used_perc', 'ellis-io.read_kbytes_sec', 'ellis-io.read_req_sec', 'ellis-io.read_time_sec', 'ellis-io.write_kbytes_sec', 'ellis-io.write_req_sec', 'ellis-io.write_time_sec', 'ellis-load.avg_15_min', 'ellis-load.avg_1_min', 'ellis-load.avg_5_min', 'ellis-mem.free_mb', 'ellis-mem.total_mb', 'ellis-mem.usable_mb', 'ellis-mem.usable_perc', 'ellis-net.in_bytes_sec', 'ellis-net.in_errors_sec', 'ellis-net.in_packets_dropped_sec', 'ellis-net.in_packets_sec', 'ellis-net.out_bytes_sec', 'ellis-net.out_errors_sec', 'ellis-net.out_packets_sec']\n",
-        "df_Ellis = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "VU27zosAYA0b",
-        "outputId": "32ed0bbb-0386-40c8-ba57-0787d3afda76"
-      },
-      "source": [
-        "df_Ellis.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.idle_perc</th>\n",
-              "      <th>ellis-cpu.stolen_perc</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-disk.inode_used_perc</th>\n",
-              "      <th>ellis-disk.space_used_perc</th>\n",
-              "      <th>ellis-io.read_kbytes_sec</th>\n",
-              "      <th>ellis-io.read_req_sec</th>\n",
-              "      <th>ellis-io.read_time_sec</th>\n",
-              "      <th>ellis-io.write_kbytes_sec</th>\n",
-              "      <th>ellis-io.write_req_sec</th>\n",
-              "      <th>ellis-io.write_time_sec</th>\n",
-              "      <th>ellis-load.avg_15_min</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-load.avg_5_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-mem.total_mb</th>\n",
-              "      <th>ellis-mem.usable_mb</th>\n",
-              "      <th>ellis-mem.usable_perc</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.in_errors_sec</th>\n",
-              "      <th>ellis-net.in_packets_dropped_sec</th>\n",
-              "      <th>ellis-net.in_packets_sec</th>\n",
-              "      <th>ellis-net.out_bytes_sec</th>\n",
-              "      <th>ellis-net.out_errors_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>7.156</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.026</td>\n",
-              "      <td>1.488</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>6.553</td>\n",
-              "      <td>7.035</td>\n",
-              "      <td>7.161</td>\n",
-              "      <td>7.339</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>6.939</td>\n",
-              "      <td>6.838</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.033</td>\n",
-              "      <td>1.105</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.071</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>7.729</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>5.138</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.026</td>\n",
-              "      <td>1.501</td>\n",
-              "      <td>1.075</td>\n",
-              "      <td>6.659</td>\n",
-              "      <td>7.244</td>\n",
-              "      <td>7.410</td>\n",
-              "      <td>7.342</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>6.939</td>\n",
-              "      <td>6.838</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.031</td>\n",
-              "      <td>1.101</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.068</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>7.410</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>5.741</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.491</td>\n",
-              "      <td>1.081</td>\n",
-              "      <td>6.659</td>\n",
-              "      <td>6.302</td>\n",
-              "      <td>7.360</td>\n",
-              "      <td>7.342</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>6.969</td>\n",
-              "      <td>6.838</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.032</td>\n",
-              "      <td>1.103</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.070</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>7.177</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.484</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>6.712</td>\n",
-              "      <td>5.988</td>\n",
-              "      <td>7.360</td>\n",
-              "      <td>7.339</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>6.939</td>\n",
-              "      <td>6.838</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.032</td>\n",
-              "      <td>1.103</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.069</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>7.347</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>5.862</td>\n",
-              "      <td>5.950</td>\n",
-              "      <td>1.643</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.484</td>\n",
-              "      <td>1.087</td>\n",
-              "      <td>6.765</td>\n",
-              "      <td>6.023</td>\n",
-              "      <td>7.410</td>\n",
-              "      <td>7.342</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>6.939</td>\n",
-              "      <td>6.838</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.032</td>\n",
-              "      <td>1.104</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.070</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  ellis-cpu.idle_perc  ... ellis-net.out_packets_sec\n",
-              "0               7.156  ...                     1.071\n",
-              "1               7.729  ...                     1.068\n",
-              "2               7.410  ...                     1.070\n",
-              "3               7.177  ...                     1.069\n",
-              "4               7.347  ...                     1.070\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 11
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "0k96D8aDYFw-"
-      },
-      "source": [
-        "# **df_Ellis_7 / focus on the main 6 metrics**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "zVxKNXtfYCph"
-      },
-      "source": [
-        "selected_columns= ['ellis-load.avg_1_min', 'ellis-cpu.wait_perc', 'ellis-net.out_packets_sec', 'ellis-cpu.system_perc', 'ellis-net.in_bytes_sec', 'ellis-mem.free_mb']\n",
-        "df_Ellis_7 = select_columns(df_Ellis, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "7y_uHZ5TYJiD",
-        "outputId": "5aef0247-67d8-4d19-c337-54075e096e07"
-      },
-      "source": [
-        "df_Ellis_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/df_Ellis.csv')\n",
-        "df_Ellis_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>7.035</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.071</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>7.244</td>\n",
-              "      <td>5.138</td>\n",
-              "      <td>1.068</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>6.302</td>\n",
-              "      <td>5.741</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>5.988</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>6.023</td>\n",
-              "      <td>5.862</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  ellis-load.avg_1_min  ... ellis-mem.free_mb\n",
-              "0                7.035  ...             7.339\n",
-              "1                7.244  ...             7.342\n",
-              "2                6.302  ...             7.342\n",
-              "3                5.988  ...             7.339\n",
-              "4                6.023  ...             7.342\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "e9c4-7mZYLpq",
-        "outputId": "020a0e5f-a63a-4918-db1b-a9e1081ce38e"
-      },
-      "source": [
-        "df_Ellis_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                     Non-Null Count   Dtype \n",
-            "---  ------                     --------------   ----- \n",
-            " 0   ellis-load.avg_1_min       177000 non-null  object\n",
-            " 1   ellis-cpu.wait_perc        177000 non-null  object\n",
-            " 2   ellis-net.out_packets_sec  177000 non-null  object\n",
-            " 3   ellis-cpu.system_perc      177000 non-null  object\n",
-            " 4   ellis-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   ellis-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "iFy_Het0cqh7",
-        "outputId": "ad2ea7ad-1c70-4539-a558-bee07b0a8a19"
-      },
-      "source": [
-        "timestamp  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/timestamp.csv\")\n",
-        "timestamp.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Unnamed: 0</th>\n",
-              "      <th>Timestamp</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>0</td>\n",
-              "      <td>2016-09-14 00:00:02.897</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>1</td>\n",
-              "      <td>2016-09-14 00:00:32.886</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>2</td>\n",
-              "      <td>2016-09-14 00:01:02.887</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>3</td>\n",
-              "      <td>2016-09-14 00:01:32.908</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>4</td>\n",
-              "      <td>2016-09-14 00:02:02.910</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "   Unnamed: 0                Timestamp\n",
-              "0           0  2016-09-14 00:00:02.897\n",
-              "1           1  2016-09-14 00:00:32.886\n",
-              "2           2  2016-09-14 00:01:02.887\n",
-              "3           3  2016-09-14 00:01:32.908\n",
-              "4           4  2016-09-14 00:02:02.910"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 15
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q2-Wt45vdTzt"
-      },
-      "source": [
-        "df1 = timestamp[\"Timestamp\"]\n",
-        "df1\n",
-        "df1.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/TimestampNew.csv')"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "dcpx8F6ReZzb",
-        "outputId": "7009dff8-ee1a-43ee-b990-1bfba586cce9"
-      },
-      "source": [
-        "df1.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "0    2016-09-14 00:00:02.897\n",
-              "1    2016-09-14 00:00:32.886\n",
-              "2    2016-09-14 00:01:02.887\n",
-              "3    2016-09-14 00:01:32.908\n",
-              "4    2016-09-14 00:02:02.910\n",
-              "Name: Timestamp, dtype: object"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 17
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "mybijUDWfdcH"
-      },
-      "source": [
-        "#df_Ellis_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/df_EllisTime.csv') "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "2TddekZAfiad",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "outputId": "be25c51a-d1c0-4da8-9838-72fb59d85369"
-      },
-      "source": [
-        "df_Ellis_7"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>7.035</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.071</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>7.244</td>\n",
-              "      <td>5.138</td>\n",
-              "      <td>1.068</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>6.302</td>\n",
-              "      <td>5.741</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>5.988</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>6.023</td>\n",
-              "      <td>5.862</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>1.105</td>\n",
-              "      <td>1.121</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.529</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>1.063</td>\n",
-              "      <td>1.121</td>\n",
-              "      <td>1.001</td>\n",
-              "      <td>1.054</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.529</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>1.035</td>\n",
-              "      <td>1.121</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.271</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.525</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>1.024</td>\n",
-              "      <td>1.121</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.271</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.529</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>1.140</td>\n",
-              "      <td>1.040</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.529</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 6 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "       ellis-load.avg_1_min  ... ellis-mem.free_mb\n",
-              "0                     7.035  ...             7.339\n",
-              "1                     7.244  ...             7.342\n",
-              "2                     6.302  ...             7.342\n",
-              "3                     5.988  ...             7.339\n",
-              "4                     6.023  ...             7.342\n",
-              "...                     ...  ...               ...\n",
-              "176995                1.105  ...             5.529\n",
-              "176996                1.063  ...             5.529\n",
-              "176997                1.035  ...             5.525\n",
-              "176998                1.024  ...             5.529\n",
-              "176999                1.140  ...             5.529\n",
-              "\n",
-              "[177000 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 19
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "7gstjLldYT_r"
-      },
-      "source": [
-        "# df_Ellis_7.describe()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "bFMkMFqhs5pm"
-      },
-      "source": [
-        "# investigate why we need this float transformation. \n",
-        "df_Ellis_7 = df_Ellis_7.astype(np.float)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 882
-        },
-        "id": "mWxDJNMwtGYs",
-        "outputId": "73a4a63a-4bd6-4ef0-b140-4ef299152fa2"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis_7.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 6 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "dedoBLq_tIG_"
-      },
-      "source": [
-        "df_Ellis_7.to_csv('df_Ellis_7.csv', sep=';')"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "sObmuXeWtLL0",
-        "outputId": "e2bbea48-8fb3-4671-a4dc-5f9f2e464b59"
-      },
-      "source": [
-        "# we show here the boxplot\n",
-        "plt.figure(figsize=(20,20))\n",
-        "#df_Ellis_7.boxplot(figsize=(20,20))\n",
-        "ax = sns.boxplot(x=\"variable\", y=\"value\", data=pd.melt(df_Ellis_7))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1440x1440 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "wxNTLGMHtOF_"
-      },
-      "source": [
-        "# the gray related metrics will be dropped when using the df_Ellis\n",
-        "\n",
-        "#del df_Ellis['ellis-cpu.stolen_perc']\n",
-        "#del df_Ellis['ellis-mem.total_mb']\n",
-        "#del df_Ellis['ellis-net.in_errors_sec']\n",
-        "#del df_Ellis['ellis-net.in_packets_dropped_sec']\n",
-        "#del df_Ellis['ellis-net.out_errors_sec']"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "pcmqBw0gtUT5",
-        "outputId": "b0da529e-8895-483a-d7d1-e450fc6762e0"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "correaltionMatrice = df_Ellis_7.corr()\n",
-        "f, ax = plt.subplots(figsize=(30, 20))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": "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\n",
-            "text/plain": [
-              "<Figure size 2160x1440 with 2 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 411
-        },
-        "id": "7yZNvlQ2tWlu",
-        "outputId": "dc56cd65-e5e5-4179-aac9-6c6aac43c0eb"
-      },
-      "source": [
-        "mask = np.zeros_like(correaltionMatrice)\n",
-        "mask[np.triu_indices_from(mask)] = True\n",
-        "with sns.axes_style(\"white\"):\n",
-        "     ax = sns.heatmap(correaltionMatrice, mask=mask, vmin=0,vmax=1, square=True)\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "Whxt9FahtZ6i",
-        "outputId": "f6dd23c3-82b5-4dd1-9f18-6bd373ff9322"
-      },
-      "source": [
-        "df_Ellis_7.shape\n",
-        "df_Ellis_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>7.035</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.071</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>7.244</td>\n",
-              "      <td>5.138</td>\n",
-              "      <td>1.068</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>6.302</td>\n",
-              "      <td>5.741</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>5.988</td>\n",
-              "      <td>6.183</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>1.163</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.339</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>6.023</td>\n",
-              "      <td>5.862</td>\n",
-              "      <td>1.070</td>\n",
-              "      <td>1.217</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>7.342</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "   ellis-load.avg_1_min  ...  ellis-mem.free_mb\n",
-              "0                 7.035  ...              7.339\n",
-              "1                 7.244  ...              7.342\n",
-              "2                 6.302  ...              7.342\n",
-              "3                 5.988  ...              7.339\n",
-              "4                 6.023  ...              7.342\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 28
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "Tmzw5MYctb3h",
-        "outputId": "65c21482-29fa-42e3-eb8f-50414bb9c656"
-      },
-      "source": [
-        "# we show here the scatter_matrix\n",
-        "from pandas.plotting import scatter_matrix\n",
-        "scatter_matrix(df_Ellis_7, alpha=0.2, figsize=(30,30))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7efe4675bc50>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4678c910>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4673fe50>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe46702410>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe466b7990>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4666cf10>],\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f1d0650>],\n",
-              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7efe4efa33d0>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4efaea50>],\n",
-              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f585110>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f553790>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f6634d0>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f44a210>],\n",
-              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f1eb890>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f606190>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f0b0c50>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f331310>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f143990>]],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 29
-        },
-        {
-          "output_type": "display_data",
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\n",
-            "text/plain": [
-              "<Figure size 2160x2160 with 36 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "kcMuENePteVx",
-        "outputId": "7ed8fd61-a02c-4a01-f661-69938c0028ad"
-      },
-      "source": [
-        "# we show here the scatter_matrix (kde)\n",
-        "\n",
-        "scatter_matrix(df_Ellis_7, alpha=0.2, figsize=(30, 30), diagonal='kde')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7efe4f5b8a10>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe464dd9d0>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe464a9190>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe44753d50>],\n",
-              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7efe44713410>,\n",
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-              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7efe445f6690>,\n",
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-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe44522750>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe444d5cd0>,\n",
-              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7efe44499290>]],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 30
-        },
-        {
-          "output_type": "display_data",
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\n",
-            "text/plain": [
-              "<Figure size 2160x2160 with 36 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "thrxP0LQth88",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "d15b9169-79b7-47a0-e19f-b8477dd2b287"
-      },
-      "source": [
-        "#scatterplot the most obvious variable related to SalePrice\n",
-        "sns.pairplot(df_Ellis_7, size = 2.5)\n",
-        "plt.show();"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 1080x1080 with 42 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "HNMDfsExILYz"
-      },
-      "source": [
-        "# **Bono**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "mxaAX85otljN"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['bono-cpu.idle_perc', 'bono-cpu.stolen_perc', 'bono-cpu.system_perc', 'bono-cpu.wait_perc', 'bono-disk.inode_used_perc', 'bono-disk.space_used_perc', 'bono-io.read_kbytes_sec', 'bono-io.read_req_sec', 'bono-io.read_time_sec', 'bono-io.write_kbytes_sec', 'bono-io.write_req_sec', 'bono-io.write_time_sec', 'bono-load.avg_15_min', 'bono-load.avg_1_min', 'bono-load.avg_5_min', 'bono-mem.free_mb', 'bono-mem.total_mb', 'bono-mem.usable_mb', 'bono-mem.usable_perc', 'bono-net.in_bytes_sec', 'bono-net.in_errors_sec', 'bono-net.in_packets_dropped_sec', 'bono-net.in_packets_sec', 'bono-net.out_bytes_sec', 'bono-net.out_errors_sec', 'bono-net.out_packets_sec']\n",
-        "df_Bono = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "EKi0wnvUIlZb",
-        "outputId": "4e7d2685-b09c-43ae-9217-d7210a253950"
-      },
-      "source": [
-        "df_Bono.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>bono-cpu.idle_perc</th>\n",
-              "      <th>bono-cpu.stolen_perc</th>\n",
-              "      <th>bono-cpu.system_perc</th>\n",
-              "      <th>bono-cpu.wait_perc</th>\n",
-              "      <th>bono-disk.inode_used_perc</th>\n",
-              "      <th>bono-disk.space_used_perc</th>\n",
-              "      <th>bono-io.read_kbytes_sec</th>\n",
-              "      <th>bono-io.read_req_sec</th>\n",
-              "      <th>bono-io.read_time_sec</th>\n",
-              "      <th>bono-io.write_kbytes_sec</th>\n",
-              "      <th>bono-io.write_req_sec</th>\n",
-              "      <th>bono-io.write_time_sec</th>\n",
-              "      <th>bono-load.avg_15_min</th>\n",
-              "      <th>bono-load.avg_1_min</th>\n",
-              "      <th>bono-load.avg_5_min</th>\n",
-              "      <th>bono-mem.free_mb</th>\n",
-              "      <th>bono-mem.total_mb</th>\n",
-              "      <th>bono-mem.usable_mb</th>\n",
-              "      <th>bono-mem.usable_perc</th>\n",
-              "      <th>bono-net.in_bytes_sec</th>\n",
-              "      <th>bono-net.in_errors_sec</th>\n",
-              "      <th>bono-net.in_packets_dropped_sec</th>\n",
-              "      <th>bono-net.in_packets_sec</th>\n",
-              "      <th>bono-net.out_bytes_sec</th>\n",
-              "      <th>bono-net.out_errors_sec</th>\n",
-              "      <th>bono-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>8.249</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>2.824</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.019</td>\n",
-              "      <td>1.727</td>\n",
-              "      <td>1.083</td>\n",
-              "      <td>6.593</td>\n",
-              "      <td>3.976</td>\n",
-              "      <td>5.287</td>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.529</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>8.507</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>2.553</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.018</td>\n",
-              "      <td>1.716</td>\n",
-              "      <td>1.072</td>\n",
-              "      <td>6.366</td>\n",
-              "      <td>2.793</td>\n",
-              "      <td>4.878</td>\n",
-              "      <td>7.725</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.529</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>8.140</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>2.930</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.017</td>\n",
-              "      <td>1.666</td>\n",
-              "      <td>1.095</td>\n",
-              "      <td>6.196</td>\n",
-              "      <td>2.076</td>\n",
-              "      <td>4.519</td>\n",
-              "      <td>7.722</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.526</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.083</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.173</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>7.964</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.250</td>\n",
-              "      <td>3.171</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.017</td>\n",
-              "      <td>1.677</td>\n",
-              "      <td>1.095</td>\n",
-              "      <td>6.025</td>\n",
-              "      <td>1.645</td>\n",
-              "      <td>4.161</td>\n",
-              "      <td>7.722</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.526</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.081</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.170</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.135</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>8.086</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>3.005</td>\n",
-              "      <td>4.375</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.018</td>\n",
-              "      <td>1.705</td>\n",
-              "      <td>1.100</td>\n",
-              "      <td>6.139</td>\n",
-              "      <td>3.402</td>\n",
-              "      <td>4.519</td>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.528</td>\n",
-              "      <td>9.522</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.183</td>\n",
-              "      <td>1.003</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.142</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  bono-cpu.idle_perc  ... bono-net.out_packets_sec\n",
-              "0              8.249  ...                    1.136\n",
-              "1              8.507  ...                    1.136\n",
-              "2              8.140  ...                    1.136\n",
-              "3              7.964  ...                    1.135\n",
-              "4              8.086  ...                    1.142\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 33
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "gGCA3rWuJdQx"
-      },
-      "source": [
-        "selected_columns= ['bono-load.avg_1_min', 'bono-cpu.wait_perc', 'bono-net.out_packets_sec', 'bono-cpu.system_perc', 'bono-net.in_bytes_sec', 'bono-mem.free_mb']\n",
-        "df_Bono_7 = select_columns(df_Bono, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "9ZyhiI6AJo1Y",
-        "outputId": "9308469b-ba98-4152-dafa-308d3b6f7b04"
-      },
-      "source": [
-        "df_Bono_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/bono/df_Bono.csv')\n",
-        "df_Bono_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>bono-load.avg_1_min</th>\n",
-              "      <th>bono-cpu.wait_perc</th>\n",
-              "      <th>bono-net.out_packets_sec</th>\n",
-              "      <th>bono-cpu.system_perc</th>\n",
-              "      <th>bono-net.in_bytes_sec</th>\n",
-              "      <th>bono-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>3.976</td>\n",
-              "      <td>2.824</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>7.723</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>2.793</td>\n",
-              "      <td>2.553</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>7.725</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>2.076</td>\n",
-              "      <td>2.930</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>1.083</td>\n",
-              "      <td>7.722</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>1.645</td>\n",
-              "      <td>3.171</td>\n",
-              "      <td>1.135</td>\n",
-              "      <td>1.250</td>\n",
-              "      <td>1.081</td>\n",
-              "      <td>7.722</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>3.402</td>\n",
-              "      <td>3.005</td>\n",
-              "      <td>1.142</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>1.092</td>\n",
-              "      <td>7.723</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  bono-load.avg_1_min bono-cpu.wait_perc  ... bono-net.in_bytes_sec bono-mem.free_mb\n",
-              "0               3.976              2.824  ...                 1.084            7.723\n",
-              "1               2.793              2.553  ...                 1.084            7.725\n",
-              "2               2.076              2.930  ...                 1.083            7.722\n",
-              "3               1.645              3.171  ...                 1.081            7.722\n",
-              "4               3.402              3.005  ...                 1.092            7.723\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 35
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "4ZUXUW35J2fr",
-        "outputId": "fc474730-e953-4f09-8633-ece4e493d9de"
-      },
-      "source": [
-        "df_Bono_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                    Non-Null Count   Dtype \n",
-            "---  ------                    --------------   ----- \n",
-            " 0   bono-load.avg_1_min       177000 non-null  object\n",
-            " 1   bono-cpu.wait_perc        177000 non-null  object\n",
-            " 2   bono-net.out_packets_sec  177000 non-null  object\n",
-            " 3   bono-cpu.system_perc      177000 non-null  object\n",
-            " 4   bono-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   bono-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "QeQ3_oHsJ5BN"
-      },
-      "source": [
-        "# **Sprout**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "gAQmKdKfJ3st"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['sprout-cpu.idle_perc', 'sprout-cpu.stolen_perc', 'sprout-cpu.system_perc', 'sprout-cpu.wait_perc', 'sprout-disk.inode_used_perc', 'sprout-disk.space_used_perc', 'sprout-io.read_kbytes_sec', 'sprout-io.read_req_sec', 'sprout-io.read_time_sec', 'sprout-io.write_kbytes_sec', 'sprout-io.write_req_sec', 'sprout-io.write_time_sec', 'sprout-load.avg_15_min', 'sprout-load.avg_1_min', 'sprout-load.avg_5_min', 'sprout-mem.free_mb', 'sprout-mem.total_mb', 'sprout-mem.usable_mb', 'sprout-mem.usable_perc', 'sprout-net.in_bytes_sec', 'sprout-net.in_errors_sec', 'sprout-net.in_packets_dropped_sec', 'sprout-net.in_packets_sec', 'sprout-net.out_bytes_sec', 'sprout-net.out_errors_sec', 'sprout-net.out_packets_sec']\n",
-        "df_Sprout = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "wjdR0R7YMOyT",
-        "outputId": "4600cd66-0456-4da2-8723-17b5079f7f6b"
-      },
-      "source": [
-        "df_Sprout.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>sprout-cpu.idle_perc</th>\n",
-              "      <th>sprout-cpu.stolen_perc</th>\n",
-              "      <th>sprout-cpu.system_perc</th>\n",
-              "      <th>sprout-cpu.wait_perc</th>\n",
-              "      <th>sprout-disk.inode_used_perc</th>\n",
-              "      <th>sprout-disk.space_used_perc</th>\n",
-              "      <th>sprout-io.read_kbytes_sec</th>\n",
-              "      <th>sprout-io.read_req_sec</th>\n",
-              "      <th>sprout-io.read_time_sec</th>\n",
-              "      <th>sprout-io.write_kbytes_sec</th>\n",
-              "      <th>sprout-io.write_req_sec</th>\n",
-              "      <th>sprout-io.write_time_sec</th>\n",
-              "      <th>sprout-load.avg_15_min</th>\n",
-              "      <th>sprout-load.avg_1_min</th>\n",
-              "      <th>sprout-load.avg_5_min</th>\n",
-              "      <th>sprout-mem.free_mb</th>\n",
-              "      <th>sprout-mem.total_mb</th>\n",
-              "      <th>sprout-mem.usable_mb</th>\n",
-              "      <th>sprout-mem.usable_perc</th>\n",
-              "      <th>sprout-net.in_bytes_sec</th>\n",
-              "      <th>sprout-net.in_errors_sec</th>\n",
-              "      <th>sprout-net.in_packets_dropped_sec</th>\n",
-              "      <th>sprout-net.in_packets_sec</th>\n",
-              "      <th>sprout-net.out_bytes_sec</th>\n",
-              "      <th>sprout-net.out_errors_sec</th>\n",
-              "      <th>sprout-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>7.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.478</td>\n",
-              "      <td>4.784</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.982</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>6.638</td>\n",
-              "      <td>5.770</td>\n",
-              "      <td>6.718</td>\n",
-              "      <td>8.707</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.378</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.442</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>7.990</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>4.477</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.037</td>\n",
-              "      <td>1.990</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>6.638</td>\n",
-              "      <td>4.990</td>\n",
-              "      <td>6.579</td>\n",
-              "      <td>8.711</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.012</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.377</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.428</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>7.866</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.398</td>\n",
-              "      <td>4.580</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.035</td>\n",
-              "      <td>1.984</td>\n",
-              "      <td>1.069</td>\n",
-              "      <td>6.537</td>\n",
-              "      <td>3.910</td>\n",
-              "      <td>6.210</td>\n",
-              "      <td>8.709</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.381</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.441</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>7.955</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>4.545</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.976</td>\n",
-              "      <td>1.074</td>\n",
-              "      <td>6.384</td>\n",
-              "      <td>3.070</td>\n",
-              "      <td>5.840</td>\n",
-              "      <td>8.709</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.994</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.375</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.427</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>7.848</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.518</td>\n",
-              "      <td>4.443</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.034</td>\n",
-              "      <td>1.984</td>\n",
-              "      <td>1.074</td>\n",
-              "      <td>6.384</td>\n",
-              "      <td>3.370</td>\n",
-              "      <td>5.840</td>\n",
-              "      <td>8.707</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>8.975</td>\n",
-              "      <td>8.950</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.380</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.441</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  sprout-cpu.idle_perc  ... sprout-net.out_packets_sec\n",
-              "0                7.723  ...                      1.442\n",
-              "1                7.990  ...                      1.428\n",
-              "2                7.866  ...                      1.441\n",
-              "3                7.955  ...                      1.427\n",
-              "4                7.848  ...                      1.441\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 38
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6Tfi58LJMUNu"
-      },
-      "source": [
-        "selected_columns= ['sprout-load.avg_1_min', 'sprout-cpu.wait_perc', 'sprout-net.out_packets_sec', 'sprout-cpu.system_perc', 'sprout-net.in_bytes_sec', 'sprout-mem.free_mb']\n",
-        "df_Sprout_7 = select_columns(df_Sprout, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "fP5NM3VjM0Uw",
-        "outputId": "163390b3-9ce0-406a-d9c9-88687d696c66"
-      },
-      "source": [
-        "df_Sprout_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/sprout/df_Sprout.csv')\n",
-        "df_Sprout_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>sprout-load.avg_1_min</th>\n",
-              "      <th>sprout-cpu.wait_perc</th>\n",
-              "      <th>sprout-net.out_packets_sec</th>\n",
-              "      <th>sprout-cpu.system_perc</th>\n",
-              "      <th>sprout-net.in_bytes_sec</th>\n",
-              "      <th>sprout-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>5.770</td>\n",
-              "      <td>4.784</td>\n",
-              "      <td>1.442</td>\n",
-              "      <td>1.478</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>8.707</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>4.990</td>\n",
-              "      <td>4.477</td>\n",
-              "      <td>1.428</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>8.711</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>3.910</td>\n",
-              "      <td>4.580</td>\n",
-              "      <td>1.441</td>\n",
-              "      <td>1.398</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>8.709</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>3.070</td>\n",
-              "      <td>4.545</td>\n",
-              "      <td>1.427</td>\n",
-              "      <td>1.239</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>8.709</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>3.370</td>\n",
-              "      <td>4.443</td>\n",
-              "      <td>1.441</td>\n",
-              "      <td>1.518</td>\n",
-              "      <td>1.052</td>\n",
-              "      <td>8.707</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  sprout-load.avg_1_min  ... sprout-mem.free_mb\n",
-              "0                 5.770  ...              8.707\n",
-              "1                 4.990  ...              8.711\n",
-              "2                 3.910  ...              8.709\n",
-              "3                 3.070  ...              8.709\n",
-              "4                 3.370  ...              8.707\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 40
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Ybl5WrSYM9Q0",
-        "outputId": "50f23729-a029-440f-dc6f-828308bb342c"
-      },
-      "source": [
-        "df_Sprout_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                      Non-Null Count   Dtype \n",
-            "---  ------                      --------------   ----- \n",
-            " 0   sprout-load.avg_1_min       177000 non-null  object\n",
-            " 1   sprout-cpu.wait_perc        177000 non-null  object\n",
-            " 2   sprout-net.out_packets_sec  177000 non-null  object\n",
-            " 3   sprout-cpu.system_perc      177000 non-null  object\n",
-            " 4   sprout-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   sprout-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "AvKCUZL5NKKz"
-      },
-      "source": [
-        "# **Homestead**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "EaXOAy7BNF8s"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['homestead-cpu.idle_perc', 'homestead-cpu.stolen_perc', 'homestead-cpu.system_perc', 'homestead-cpu.wait_perc', 'homestead-disk.inode_used_perc', 'homestead-disk.space_used_perc', 'homestead-io.read_kbytes_sec', 'homestead-io.read_req_sec', 'homestead-io.read_time_sec', 'homestead-io.write_kbytes_sec', 'homestead-io.write_req_sec', 'homestead-io.write_time_sec', 'homestead-load.avg_15_min', 'homestead-load.avg_1_min', 'homestead-load.avg_5_min', 'homestead-mem.free_mb', 'homestead-mem.total_mb', 'homestead-mem.usable_mb', 'homestead-mem.usable_perc', 'homestead-net.in_bytes_sec', 'homestead-net.in_errors_sec', 'homestead-net.in_packets_dropped_sec', 'homestead-net.in_packets_sec', 'homestead-net.out_bytes_sec', 'homestead-net.out_errors_sec', 'homestead-net.out_packets_sec']\n",
-        "df_Homestead = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "Qc5vd1CVNas2",
-        "outputId": "8b6ab0c1-d15d-4545-e69b-dd39facc5915"
-      },
-      "source": [
-        "df_Homestead.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>homestead-cpu.idle_perc</th>\n",
-              "      <th>homestead-cpu.stolen_perc</th>\n",
-              "      <th>homestead-cpu.system_perc</th>\n",
-              "      <th>homestead-cpu.wait_perc</th>\n",
-              "      <th>homestead-disk.inode_used_perc</th>\n",
-              "      <th>homestead-disk.space_used_perc</th>\n",
-              "      <th>homestead-io.read_kbytes_sec</th>\n",
-              "      <th>homestead-io.read_req_sec</th>\n",
-              "      <th>homestead-io.read_time_sec</th>\n",
-              "      <th>homestead-io.write_kbytes_sec</th>\n",
-              "      <th>homestead-io.write_req_sec</th>\n",
-              "      <th>homestead-io.write_time_sec</th>\n",
-              "      <th>homestead-load.avg_15_min</th>\n",
-              "      <th>homestead-load.avg_1_min</th>\n",
-              "      <th>homestead-load.avg_5_min</th>\n",
-              "      <th>homestead-mem.free_mb</th>\n",
-              "      <th>homestead-mem.total_mb</th>\n",
-              "      <th>homestead-mem.usable_mb</th>\n",
-              "      <th>homestead-mem.usable_perc</th>\n",
-              "      <th>homestead-net.in_bytes_sec</th>\n",
-              "      <th>homestead-net.in_errors_sec</th>\n",
-              "      <th>homestead-net.in_packets_dropped_sec</th>\n",
-              "      <th>homestead-net.in_packets_sec</th>\n",
-              "      <th>homestead-net.out_bytes_sec</th>\n",
-              "      <th>homestead-net.out_errors_sec</th>\n",
-              "      <th>homestead-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>8.646</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>4.207</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.200</td>\n",
-              "      <td>6.195</td>\n",
-              "      <td>1.704</td>\n",
-              "      <td>4.106</td>\n",
-              "      <td>1.494</td>\n",
-              "      <td>2.245</td>\n",
-              "      <td>8.843</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.949</td>\n",
-              "      <td>4.938</td>\n",
-              "      <td>1.795</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.225</td>\n",
-              "      <td>1.765</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.056</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>9.038</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.326</td>\n",
-              "      <td>3.059</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.192</td>\n",
-              "      <td>5.915</td>\n",
-              "      <td>1.392</td>\n",
-              "      <td>4.041</td>\n",
-              "      <td>1.367</td>\n",
-              "      <td>2.200</td>\n",
-              "      <td>8.843</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.984</td>\n",
-              "      <td>4.938</td>\n",
-              "      <td>1.791</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.200</td>\n",
-              "      <td>1.760</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.020</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>9.180</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.326</td>\n",
-              "      <td>2.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.200</td>\n",
-              "      <td>6.101</td>\n",
-              "      <td>1.392</td>\n",
-              "      <td>4.106</td>\n",
-              "      <td>1.387</td>\n",
-              "      <td>2.222</td>\n",
-              "      <td>8.843</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.984</td>\n",
-              "      <td>4.938</td>\n",
-              "      <td>1.799</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.256</td>\n",
-              "      <td>1.770</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.101</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>9.216</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>2.723</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.203</td>\n",
-              "      <td>6.236</td>\n",
-              "      <td>1.312</td>\n",
-              "      <td>4.041</td>\n",
-              "      <td>1.274</td>\n",
-              "      <td>2.133</td>\n",
-              "      <td>8.843</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.984</td>\n",
-              "      <td>4.938</td>\n",
-              "      <td>1.799</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.247</td>\n",
-              "      <td>1.768</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.065</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>9.198</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>2.676</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.201</td>\n",
-              "      <td>6.195</td>\n",
-              "      <td>1.392</td>\n",
-              "      <td>4.041</td>\n",
-              "      <td>1.234</td>\n",
-              "      <td>2.111</td>\n",
-              "      <td>8.843</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.949</td>\n",
-              "      <td>4.938</td>\n",
-              "      <td>1.786</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.185</td>\n",
-              "      <td>1.759</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>5.016</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  homestead-cpu.idle_perc  ... homestead-net.out_packets_sec\n",
-              "0                   8.646  ...                         5.056\n",
-              "1                   9.038  ...                         5.020\n",
-              "2                   9.180  ...                         5.101\n",
-              "3                   9.216  ...                         5.065\n",
-              "4                   9.198  ...                         5.016\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 43
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "U5e-23VDNgjS"
-      },
-      "source": [
-        "selected_columns= ['homestead-load.avg_1_min', 'homestead-cpu.wait_perc', 'homestead-net.out_packets_sec', 'homestead-cpu.system_perc', 'homestead-net.in_bytes_sec', 'homestead-mem.free_mb']\n",
-        "df_Homestead_7 = select_columns(df_Homestead, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 221
-        },
-        "id": "03Y_KhJVNuOC",
-        "outputId": "ab3eef43-6a18-4c61-926a-43afac19d7a5"
-      },
-      "source": [
-        "df_Homestead_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/homestead/df_Homestead.csv')\n",
-        "df_Homestead_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>homestead-load.avg_1_min</th>\n",
-              "      <th>homestead-cpu.wait_perc</th>\n",
-              "      <th>homestead-net.out_packets_sec</th>\n",
-              "      <th>homestead-cpu.system_perc</th>\n",
-              "      <th>homestead-net.in_bytes_sec</th>\n",
-              "      <th>homestead-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>1.494</td>\n",
-              "      <td>4.207</td>\n",
-              "      <td>5.056</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>1.795</td>\n",
-              "      <td>8.843</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>1.367</td>\n",
-              "      <td>3.059</td>\n",
-              "      <td>5.020</td>\n",
-              "      <td>1.326</td>\n",
-              "      <td>1.791</td>\n",
-              "      <td>8.843</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>1.387</td>\n",
-              "      <td>2.723</td>\n",
-              "      <td>5.101</td>\n",
-              "      <td>1.326</td>\n",
-              "      <td>1.799</td>\n",
-              "      <td>8.843</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>1.274</td>\n",
-              "      <td>2.723</td>\n",
-              "      <td>5.065</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>1.799</td>\n",
-              "      <td>8.843</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>1.234</td>\n",
-              "      <td>2.676</td>\n",
-              "      <td>5.016</td>\n",
-              "      <td>1.280</td>\n",
-              "      <td>1.786</td>\n",
-              "      <td>8.843</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  homestead-load.avg_1_min  ... homestead-mem.free_mb\n",
-              "0                    1.494  ...                 8.843\n",
-              "1                    1.367  ...                 8.843\n",
-              "2                    1.387  ...                 8.843\n",
-              "3                    1.274  ...                 8.843\n",
-              "4                    1.234  ...                 8.843\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 45
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "CVdMWcneN7ix",
-        "outputId": "f3e00de9-f60d-44d0-ae5b-9c4eda033687"
-      },
-      "source": [
-        "df_Homestead_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                         Non-Null Count   Dtype \n",
-            "---  ------                         --------------   ----- \n",
-            " 0   homestead-load.avg_1_min       177000 non-null  object\n",
-            " 1   homestead-cpu.wait_perc        177000 non-null  object\n",
-            " 2   homestead-net.out_packets_sec  177000 non-null  object\n",
-            " 3   homestead-cpu.system_perc      177000 non-null  object\n",
-            " 4   homestead-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   homestead-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_kw5-s7hOFN3"
-      },
-      "source": [
-        "# **Ralf**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "v6xYItZWOANR"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['ralf-cpu.idle_perc', 'ralf-cpu.stolen_perc', 'ralf-cpu.system_perc', 'ralf-cpu.wait_perc', 'ralf-disk.inode_used_perc', 'ralf-disk.space_used_perc', 'ralf-io.read_kbytes_sec', 'ralf-io.read_req_sec', 'ralf-io.read_time_sec', 'ralf-io.write_kbytes_sec', 'ralf-io.write_req_sec', 'ralf-io.write_time_sec', 'ralf-load.avg_15_min', 'ralf-load.avg_1_min', 'ralf-load.avg_5_min', 'ralf-mem.free_mb', 'ralf-mem.total_mb', 'ralf-mem.usable_mb', 'ralf-mem.usable_perc', 'ralf-net.in_bytes_sec', 'ralf-net.in_errors_sec', 'ralf-net.in_packets_dropped_sec', 'ralf-net.in_packets_sec', 'ralf-net.out_bytes_sec', 'ralf-net.out_errors_sec', 'ralf-net.out_packets_sec']\n",
-        "df_Ralf = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "XlYi3QBlORiI",
-        "outputId": "6a4740f0-b2c8-4e48-9067-c17c7a267b0d"
-      },
-      "source": [
-        "df_Ralf.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ralf-cpu.idle_perc</th>\n",
-              "      <th>ralf-cpu.stolen_perc</th>\n",
-              "      <th>ralf-cpu.system_perc</th>\n",
-              "      <th>ralf-cpu.wait_perc</th>\n",
-              "      <th>ralf-disk.inode_used_perc</th>\n",
-              "      <th>ralf-disk.space_used_perc</th>\n",
-              "      <th>ralf-io.read_kbytes_sec</th>\n",
-              "      <th>ralf-io.read_req_sec</th>\n",
-              "      <th>ralf-io.read_time_sec</th>\n",
-              "      <th>ralf-io.write_kbytes_sec</th>\n",
-              "      <th>ralf-io.write_req_sec</th>\n",
-              "      <th>ralf-io.write_time_sec</th>\n",
-              "      <th>ralf-load.avg_15_min</th>\n",
-              "      <th>ralf-load.avg_1_min</th>\n",
-              "      <th>ralf-load.avg_5_min</th>\n",
-              "      <th>ralf-mem.free_mb</th>\n",
-              "      <th>ralf-mem.total_mb</th>\n",
-              "      <th>ralf-mem.usable_mb</th>\n",
-              "      <th>ralf-mem.usable_perc</th>\n",
-              "      <th>ralf-net.in_bytes_sec</th>\n",
-              "      <th>ralf-net.in_errors_sec</th>\n",
-              "      <th>ralf-net.in_packets_dropped_sec</th>\n",
-              "      <th>ralf-net.in_packets_sec</th>\n",
-              "      <th>ralf-net.out_bytes_sec</th>\n",
-              "      <th>ralf-net.out_errors_sec</th>\n",
-              "      <th>ralf-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>8.517</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.274</td>\n",
-              "      <td>3.108</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.775</td>\n",
-              "      <td>1.120</td>\n",
-              "      <td>6.025</td>\n",
-              "      <td>1.590</td>\n",
-              "      <td>4.116</td>\n",
-              "      <td>7.513</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.532</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.063</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.537</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>8.582</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.274</td>\n",
-              "      <td>2.991</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.025</td>\n",
-              "      <td>1.811</td>\n",
-              "      <td>1.078</td>\n",
-              "      <td>6.343</td>\n",
-              "      <td>4.910</td>\n",
-              "      <td>5.119</td>\n",
-              "      <td>7.509</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.528</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.049</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.062</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.525</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>8.517</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.320</td>\n",
-              "      <td>3.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.024</td>\n",
-              "      <td>1.774</td>\n",
-              "      <td>1.084</td>\n",
-              "      <td>6.502</td>\n",
-              "      <td>5.810</td>\n",
-              "      <td>5.575</td>\n",
-              "      <td>7.512</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>9.531</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.065</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.539</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>8.634</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.228</td>\n",
-              "      <td>2.894</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.024</td>\n",
-              "      <td>1.769</td>\n",
-              "      <td>1.072</td>\n",
-              "      <td>6.449</td>\n",
-              "      <td>4.600</td>\n",
-              "      <td>5.438</td>\n",
-              "      <td>7.500</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.521</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.048</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.061</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.516</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>8.322</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.365</td>\n",
-              "      <td>3.265</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.024</td>\n",
-              "      <td>1.771</td>\n",
-              "      <td>1.090</td>\n",
-              "      <td>6.502</td>\n",
-              "      <td>4.693</td>\n",
-              "      <td>5.575</td>\n",
-              "      <td>7.502</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>9.524</td>\n",
-              "      <td>9.519</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.064</td>\n",
-              "      <td>1.002</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.542</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  ralf-cpu.idle_perc  ... ralf-net.out_packets_sec\n",
-              "0              8.517  ...                    1.537\n",
-              "1              8.582  ...                    1.525\n",
-              "2              8.517  ...                    1.539\n",
-              "3              8.634  ...                    1.516\n",
-              "4              8.322  ...                    1.542\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 48
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "6l88CRqDOVs-"
-      },
-      "source": [
-        "selected_columns= ['ralf-load.avg_1_min', 'ralf-cpu.wait_perc', 'ralf-net.out_packets_sec', 'ralf-cpu.system_perc', 'ralf-net.in_bytes_sec', 'ralf-mem.free_mb']\n",
-        "df_Ralf_7 = select_columns(df_Ralf, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "u3v26LoiOi5L",
-        "outputId": "441d54ec-a644-446e-dc5b-e7ad5ec58456"
-      },
-      "source": [
-        "df_Ralf_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/ralf/df_Ralf.csv')\n",
-        "df_Ralf_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ralf-load.avg_1_min</th>\n",
-              "      <th>ralf-cpu.wait_perc</th>\n",
-              "      <th>ralf-net.out_packets_sec</th>\n",
-              "      <th>ralf-cpu.system_perc</th>\n",
-              "      <th>ralf-net.in_bytes_sec</th>\n",
-              "      <th>ralf-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>1.590</td>\n",
-              "      <td>3.108</td>\n",
-              "      <td>1.537</td>\n",
-              "      <td>1.274</td>\n",
-              "      <td>1.050</td>\n",
-              "      <td>7.513</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>4.910</td>\n",
-              "      <td>2.991</td>\n",
-              "      <td>1.525</td>\n",
-              "      <td>1.274</td>\n",
-              "      <td>1.049</td>\n",
-              "      <td>7.509</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>5.810</td>\n",
-              "      <td>3.050</td>\n",
-              "      <td>1.539</td>\n",
-              "      <td>1.320</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>7.512</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>4.600</td>\n",
-              "      <td>2.894</td>\n",
-              "      <td>1.516</td>\n",
-              "      <td>1.228</td>\n",
-              "      <td>1.048</td>\n",
-              "      <td>7.500</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>4.693</td>\n",
-              "      <td>3.265</td>\n",
-              "      <td>1.542</td>\n",
-              "      <td>1.365</td>\n",
-              "      <td>1.051</td>\n",
-              "      <td>7.502</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  ralf-load.avg_1_min ralf-cpu.wait_perc  ... ralf-net.in_bytes_sec ralf-mem.free_mb\n",
-              "0               1.590              3.108  ...                 1.050            7.513\n",
-              "1               4.910              2.991  ...                 1.049            7.509\n",
-              "2               5.810              3.050  ...                 1.051            7.512\n",
-              "3               4.600              2.894  ...                 1.048            7.500\n",
-              "4               4.693              3.265  ...                 1.051            7.502\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 50
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "mR7Fg1w8OtnU",
-        "outputId": "141c6b09-3c69-45cc-e723-728e1f0e8e68"
-      },
-      "source": [
-        "df_Ralf_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                    Non-Null Count   Dtype \n",
-            "---  ------                    --------------   ----- \n",
-            " 0   ralf-load.avg_1_min       177000 non-null  object\n",
-            " 1   ralf-cpu.wait_perc        177000 non-null  object\n",
-            " 2   ralf-net.out_packets_sec  177000 non-null  object\n",
-            " 3   ralf-cpu.system_perc      177000 non-null  object\n",
-            " 4   ralf-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   ralf-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "2-udEbTHO-HS"
-      },
-      "source": [
-        "# **Homer**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "vVpG5lJiOyYw"
-      },
-      "source": [
-        "# this function select column from the global df and create a new df with them\n",
-        "def select_columns(data_frame, column_names):\n",
-        "    new_frame = data_frame.loc[:, column_names]\n",
-        "    return new_frame\n",
-        "\n",
-        "selected_columns = ['homer-cpu.idle_perc', 'homer-cpu.stolen_perc', 'homer-cpu.system_perc', 'homer-cpu.wait_perc', 'homer-disk.inode_used_perc', 'homer-disk.space_used_perc', 'homer-io.read_kbytes_sec', 'homer-io.read_req_sec', 'homer-io.read_time_sec', 'homer-io.write_kbytes_sec', 'homer-io.write_req_sec', 'homer-io.write_time_sec', 'homer-load.avg_15_min', 'homer-load.avg_1_min', 'homer-load.avg_5_min', 'homer-mem.free_mb', 'homer-mem.total_mb', 'homer-mem.usable_mb', 'homer-mem.usable_perc', 'homer-net.in_bytes_sec', 'homer-net.in_errors_sec', 'homer-net.in_packets_dropped_sec', 'homer-net.in_packets_sec', 'homer-net.out_bytes_sec', 'homer-net.out_errors_sec', 'homer-net.out_packets_sec']\n",
-        "df_Homer = select_columns(dframesorted, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 241
-        },
-        "id": "cwMKYQWUPKpl",
-        "outputId": "ca108468-0c41-4f44-aef0-8c63239c9fd5"
-      },
-      "source": [
-        "df_Homer.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>homer-cpu.idle_perc</th>\n",
-              "      <th>homer-cpu.stolen_perc</th>\n",
-              "      <th>homer-cpu.system_perc</th>\n",
-              "      <th>homer-cpu.wait_perc</th>\n",
-              "      <th>homer-disk.inode_used_perc</th>\n",
-              "      <th>homer-disk.space_used_perc</th>\n",
-              "      <th>homer-io.read_kbytes_sec</th>\n",
-              "      <th>homer-io.read_req_sec</th>\n",
-              "      <th>homer-io.read_time_sec</th>\n",
-              "      <th>homer-io.write_kbytes_sec</th>\n",
-              "      <th>homer-io.write_req_sec</th>\n",
-              "      <th>homer-io.write_time_sec</th>\n",
-              "      <th>homer-load.avg_15_min</th>\n",
-              "      <th>homer-load.avg_1_min</th>\n",
-              "      <th>homer-load.avg_5_min</th>\n",
-              "      <th>homer-mem.free_mb</th>\n",
-              "      <th>homer-mem.total_mb</th>\n",
-              "      <th>homer-mem.usable_mb</th>\n",
-              "      <th>homer-mem.usable_perc</th>\n",
-              "      <th>homer-net.in_bytes_sec</th>\n",
-              "      <th>homer-net.in_errors_sec</th>\n",
-              "      <th>homer-net.in_packets_dropped_sec</th>\n",
-              "      <th>homer-net.in_packets_sec</th>\n",
-              "      <th>homer-net.out_bytes_sec</th>\n",
-              "      <th>homer-net.out_errors_sec</th>\n",
-              "      <th>homer-net.out_packets_sec</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>8.017</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.600</td>\n",
-              "      <td>4.808</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.142</td>\n",
-              "      <td>5.274</td>\n",
-              "      <td>1.362</td>\n",
-              "      <td>8.300</td>\n",
-              "      <td>5.052</td>\n",
-              "      <td>7.368</td>\n",
-              "      <td>2.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.141</td>\n",
-              "      <td>3.156</td>\n",
-              "      <td>1.310</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.473</td>\n",
-              "      <td>2.957</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.503</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>6.853</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.467</td>\n",
-              "      <td>7.438</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.136</td>\n",
-              "      <td>5.274</td>\n",
-              "      <td>1.621</td>\n",
-              "      <td>8.087</td>\n",
-              "      <td>3.450</td>\n",
-              "      <td>6.767</td>\n",
-              "      <td>2.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.141</td>\n",
-              "      <td>3.156</td>\n",
-              "      <td>1.307</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.448</td>\n",
-              "      <td>2.946</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.489</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>8.143</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.733</td>\n",
-              "      <td>4.392</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.135</td>\n",
-              "      <td>5.104</td>\n",
-              "      <td>1.362</td>\n",
-              "      <td>7.875</td>\n",
-              "      <td>2.791</td>\n",
-              "      <td>6.316</td>\n",
-              "      <td>2.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.141</td>\n",
-              "      <td>3.156</td>\n",
-              "      <td>1.317</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.566</td>\n",
-              "      <td>2.962</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.520</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>6.822</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.600</td>\n",
-              "      <td>7.369</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.138</td>\n",
-              "      <td>5.206</td>\n",
-              "      <td>1.569</td>\n",
-              "      <td>7.769</td>\n",
-              "      <td>2.649</td>\n",
-              "      <td>6.090</td>\n",
-              "      <td>2.050</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.141</td>\n",
-              "      <td>3.156</td>\n",
-              "      <td>1.309</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.473</td>\n",
-              "      <td>2.951</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.493</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>6.633</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.667</td>\n",
-              "      <td>7.715</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.140</td>\n",
-              "      <td>5.317</td>\n",
-              "      <td>1.621</td>\n",
-              "      <td>7.662</td>\n",
-              "      <td>2.696</td>\n",
-              "      <td>5.789</td>\n",
-              "      <td>2.041</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.129</td>\n",
-              "      <td>3.156</td>\n",
-              "      <td>1.306</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>3.441</td>\n",
-              "      <td>2.955</td>\n",
-              "      <td>1.000</td>\n",
-              "      <td>4.509</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  homer-cpu.idle_perc  ... homer-net.out_packets_sec\n",
-              "0               8.017  ...                     4.503\n",
-              "1               6.853  ...                     4.489\n",
-              "2               8.143  ...                     4.520\n",
-              "3               6.822  ...                     4.493\n",
-              "4               6.633  ...                     4.509\n",
-              "\n",
-              "[5 rows x 26 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 53
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "rsUb47imPOyE"
-      },
-      "source": [
-        "selected_columns= ['homer-load.avg_1_min', 'homer-cpu.wait_perc', 'homer-net.out_packets_sec', 'homer-cpu.system_perc', 'homer-net.in_bytes_sec', 'homer-mem.free_mb']\n",
-        "df_Homer_7 = select_columns(df_Homer, selected_columns)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 204
-        },
-        "id": "VZw7WV7tPd9i",
-        "outputId": "39dc88dd-eb89-45b0-a0d3-f261aab6bbd1"
-      },
-      "source": [
-        "df_Homer_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/homer/df_Homer.csv')\n",
-        "df_Homer_7.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>homer-load.avg_1_min</th>\n",
-              "      <th>homer-cpu.wait_perc</th>\n",
-              "      <th>homer-net.out_packets_sec</th>\n",
-              "      <th>homer-cpu.system_perc</th>\n",
-              "      <th>homer-net.in_bytes_sec</th>\n",
-              "      <th>homer-mem.free_mb</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>5.052</td>\n",
-              "      <td>4.808</td>\n",
-              "      <td>4.503</td>\n",
-              "      <td>1.600</td>\n",
-              "      <td>1.310</td>\n",
-              "      <td>2.050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>3.450</td>\n",
-              "      <td>7.438</td>\n",
-              "      <td>4.489</td>\n",
-              "      <td>1.467</td>\n",
-              "      <td>1.307</td>\n",
-              "      <td>2.050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>2.791</td>\n",
-              "      <td>4.392</td>\n",
-              "      <td>4.520</td>\n",
-              "      <td>1.733</td>\n",
-              "      <td>1.317</td>\n",
-              "      <td>2.050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>2.649</td>\n",
-              "      <td>7.369</td>\n",
-              "      <td>4.493</td>\n",
-              "      <td>1.600</td>\n",
-              "      <td>1.309</td>\n",
-              "      <td>2.050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>2.696</td>\n",
-              "      <td>7.715</td>\n",
-              "      <td>4.509</td>\n",
-              "      <td>1.667</td>\n",
-              "      <td>1.306</td>\n",
-              "      <td>2.041</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "  homer-load.avg_1_min  ... homer-mem.free_mb\n",
-              "0                5.052  ...             2.050\n",
-              "1                3.450  ...             2.050\n",
-              "2                2.791  ...             2.050\n",
-              "3                2.649  ...             2.050\n",
-              "4                2.696  ...             2.041\n",
-              "\n",
-              "[5 rows x 6 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 55
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "E1Cqq8V3PnEv",
-        "outputId": "9a80be17-5bb5-4f8d-a61c-d3206e730309"
-      },
-      "source": [
-        "df_Homer_7.info()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'pandas.core.frame.DataFrame'>\n",
-            "RangeIndex: 177000 entries, 0 to 176999\n",
-            "Data columns (total 6 columns):\n",
-            " #   Column                     Non-Null Count   Dtype \n",
-            "---  ------                     --------------   ----- \n",
-            " 0   homer-load.avg_1_min       177000 non-null  object\n",
-            " 1   homer-cpu.wait_perc        177000 non-null  object\n",
-            " 2   homer-net.out_packets_sec  177000 non-null  object\n",
-            " 3   homer-cpu.system_perc      177000 non-null  object\n",
-            " 4   homer-net.in_bytes_sec     177000 non-null  object\n",
-            " 5   homer-mem.free_mb          177000 non-null  object\n",
-            "dtypes: object(6)\n",
-            "memory usage: 8.1+ MB\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "8VFEalI0Prfe"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    }
-  ]
-}
-\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "PanwhFGBbDV7"
+   },
+   "outputs": [],
+   "source": [
+    "# we are here loading the all dataset and showing the all features and sort them per server\n",
+    "X = np.load('/gdrive/MyDrive/LFN Anuket/Analysis/data/X.npy', allow_pickle=True)\n",
+    "dframe = pd.DataFrame(data=X,columns=['ellis-cpu.idle_perc', 'ralf-load.avg_15_min', 'bono-net.in_errors_sec', 'homer-net.out_bytes_sec', 'ellis-io.write_req_sec', 'homer-mem.total_mb', 'homestead-load.avg_1_min', 'homer-load.avg_1_min', 'sprout-cpu.stolen_perc', 'ralf-cpu.idle_perc', 'sprout-io.read_req_sec', 'homestead-net.in_bytes_sec', 'homer-disk.space_used_perc', 'bono-net.out_packets_sec', 'homer-cpu.wait_perc', 'ellis-net.in_packets_sec', 'bono-mem.free_mb', 'ellis-io.read_req_sec', 'bono-mem.usable_mb', 'bono-net.in_packets_dropped_sec', 'homestead-mem.free_mb', 'homer-io.write_time_sec', 'sprout-io.write_time_sec', 'homestead-net.in_errors_sec', 'homestead-mem.usable_perc', 'homestead-net.in_packets_dropped_sec', 'homestead-io.write_req_sec', 'bono-net.in_bytes_sec', 'homestead-disk.space_used_perc', 'homer-net.out_packets_sec', 'bono-mem.usable_perc', 'ralf-net.out_errors_sec', 'homestead-load.avg_5_min', 'sprout-io.read_kbytes_sec', 'sprout-net.out_errors_sec', 'homestead-io.write_kbytes_sec', 'homestead-net.in_packets_sec', 'sprout-mem.usable_mb', 'homestead-cpu.idle_perc', 'ralf-io.write_time_sec', 'ralf-io.write_kbytes_sec', 'ralf-io.write_req_sec', 'ellis-net.out_bytes_sec', 'bono-io.read_kbytes_sec', 'bono-disk.space_used_perc', 'homer-net.in_packets_dropped_sec', 'ralf-mem.usable_mb', 'bono-load.avg_15_min', 'bono-io.read_time_sec', 'sprout-mem.usable_perc', 'bono-cpu.idle_perc', 'homer-mem.usable_perc', 'homestead-cpu.stolen_perc', 'ralf-io.read_req_sec', 'homer-cpu.idle_perc', 'homestead-mem.total_mb', 'ralf-load.avg_1_min', 'homer-io.read_kbytes_sec', 'homestead-io.read_req_sec', 'ellis-mem.free_mb', 'bono-io.write_time_sec', 'ellis-net.out_errors_sec', 'ellis-cpu.stolen_perc', 'ellis-mem.usable_perc', 'ralf-disk.inode_used_perc', 'sprout-load.avg_15_min', 'ellis-io.read_time_sec', 'ralf-net.out_packets_sec', 'sprout-io.write_req_sec', 'bono-cpu.stolen_perc', 'homestead-load.avg_15_min', 'bono-cpu.system_perc', 'homestead-net.out_packets_sec', 'ellis-io.write_kbytes_sec', 'sprout-cpu.idle_perc', 'ellis-mem.total_mb', 'homer-mem.usable_mb', 'bono-load.avg_5_min', 'ellis-load.avg_5_min', 'homer-cpu.stolen_perc', 'sprout-net.out_bytes_sec', 'homestead-mem.usable_mb', 'homestead-disk.inode_used_perc', 'ralf-net.in_packets_dropped_sec', 'sprout-io.write_kbytes_sec', 'ellis-load.avg_15_min', 'homer-load.avg_5_min', 'ralf-mem.usable_perc', 'bono-net.out_bytes_sec', 'ellis-cpu.system_perc', 'homer-io.read_time_sec', 'ellis-disk.inode_used_perc', 'homestead-io.read_time_sec', 'sprout-net.in_bytes_sec', 'bono-io.write_kbytes_sec', 'homestead-io.read_kbytes_sec', 'ellis-net.in_errors_sec', 'sprout-io.read_time_sec', 'homer-disk.inode_used_perc', 'ralf-cpu.wait_perc', 'homer-load.avg_15_min', 'sprout-load.avg_5_min', 'homer-io.read_req_sec', 'ralf-mem.total_mb', 'homer-mem.free_mb', 'homer-net.in_packets_sec', 'homestead-net.out_bytes_sec', 'sprout-disk.inode_used_perc', 'ellis-mem.usable_mb', 'homer-io.write_kbytes_sec', 'homer-net.out_errors_sec', 'homer-cpu.system_perc', 'ellis-io.read_kbytes_sec', 'sprout-load.avg_1_min', 'sprout-cpu.system_perc', 'ralf-cpu.stolen_perc', 'bono-mem.total_mb', 'bono-net.out_errors_sec', 'ellis-io.write_time_sec', 'ralf-io.read_time_sec', 'sprout-cpu.wait_perc', 'ellis-cpu.wait_perc', 'ralf-disk.space_used_perc', 'ralf-net.out_bytes_sec', 'ellis-net.in_packets_dropped_sec', 'homer-net.in_bytes_sec', 'ellis-net.in_bytes_sec', 'bono-cpu.wait_perc', 'ralf-net.in_packets_sec', 'sprout-mem.total_mb', 'ralf-net.in_bytes_sec', 'bono-load.avg_1_min', 'sprout-net.in_packets_sec', 'bono-io.write_req_sec', 'ralf-load.avg_5_min', 'ralf-net.in_errors_sec', 'bono-disk.inode_used_perc', 'homestead-io.write_time_sec', 'ellis-net.out_packets_sec', 'sprout-disk.space_used_perc', 'ralf-io.read_kbytes_sec', 'homestead-cpu.system_perc', 'sprout-mem.free_mb', 'homer-net.in_errors_sec', 'homestead-net.out_errors_sec', 'homer-io.write_req_sec', 'sprout-net.in_errors_sec', 'ellis-disk.space_used_perc', 'sprout-net.out_packets_sec', 'sprout-net.in_packets_dropped_sec', 'ralf-cpu.system_perc', 'ralf-mem.free_mb', 'bono-io.read_req_sec', 'bono-net.in_packets_sec', 'homestead-cpu.wait_perc', 'ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "nAia0RRkbcSV"
+   },
+   "outputs": [],
+   "source": [
+    "dframesorted = dframe.sort_index(axis=1, ascending=True, inplace=False, kind='quicksort')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 270
+    },
+    "id": "76XHMM3cfWGW",
+    "outputId": "87965d6f-7c2a-4c39-ed9e-f372a0ade7ca"
+   },
+   "outputs": [],
+   "source": [
+    "dframesorted.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "lKCAS0m7fe5F"
+   },
+   "outputs": [],
+   "source": [
+    "#dframesorted.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "vnThYldxXdaw",
+    "outputId": "696f7fee-55eb-4d38-d471-17d1dd4e2e7e"
+   },
+   "outputs": [],
+   "source": [
+    "# here we print the name col to select later metrics per server. \n",
+    "print('Column names are: ',list(dframesorted.columns))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8-pffUQBXojo"
+   },
+   "source": [
+    "# **X_126bis / all data with less 30 features and csv format**\n",
+    "cpu.stolen_perc\n",
+    "\n",
+    "mem.total_mb\n",
+    "\n",
+    "net.in_errors_sec\n",
+    "\n",
+    "net.in_packets_dropped_sec\n",
+    "\n",
+    "net.out_errors_sec"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "HE4xoUdNXgLi",
+    "outputId": "16443f8c-111b-4023-d192-345e02c5a49f"
+   },
+   "outputs": [],
+   "source": [
+    "X_126bis = dframesorted.drop(['sprout-cpu.stolen_perc', 'sprout-mem.total_mb', 'sprout-net.in_errors_sec', 'sprout-net.in_packets_dropped_sec', 'sprout-net.out_errors_sec','homer-cpu.stolen_perc', 'homer-mem.total_mb', 'homer-net.in_errors_sec', 'homer-net.in_packets_dropped_sec', 'homer-net.out_errors_sec','ellis-cpu.stolen_perc', 'ellis-mem.total_mb', 'ellis-net.in_errors_sec', 'ellis-net.in_packets_dropped_sec', 'ellis-net.out_errors_sec', 'bono-cpu.stolen_perc', 'bono-mem.total_mb', 'bono-net.in_errors_sec', 'bono-net.in_packets_dropped_sec', 'bono-net.out_errors_sec', 'ralf-cpu.stolen_perc', 'ralf-mem.total_mb', 'ralf-net.in_errors_sec', 'ralf-net.in_packets_dropped_sec', 'ralf-net.out_errors_sec', 'homestead-cpu.stolen_perc', 'homestead-mem.total_mb', 'homestead-net.in_errors_sec', 'homestead-net.in_packets_dropped_sec', 'homestead-net.out_errors_sec'], axis =1)\n",
+    "\n",
+    "dframesorted.shape, X_126bis.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "5_8LHtazXvwf"
+   },
+   "outputs": [],
+   "source": [
+    "X_126bis.to_csv('X_126bis.csv', sep=',')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sknAZgiPX6_2"
+   },
+   "source": [
+    "# **df_Ellis.csv / extract the ellis server metrics**\n",
+    "1) Ellis Server with 26 metrics\n",
+    "\n",
+    "2) subselection of the Ellis metrics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "S6n-hPD3X43P"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['ellis-cpu.idle_perc', 'ellis-cpu.stolen_perc', 'ellis-cpu.system_perc', 'ellis-cpu.wait_perc', 'ellis-disk.inode_used_perc', 'ellis-disk.space_used_perc', 'ellis-io.read_kbytes_sec', 'ellis-io.read_req_sec', 'ellis-io.read_time_sec', 'ellis-io.write_kbytes_sec', 'ellis-io.write_req_sec', 'ellis-io.write_time_sec', 'ellis-load.avg_15_min', 'ellis-load.avg_1_min', 'ellis-load.avg_5_min', 'ellis-mem.free_mb', 'ellis-mem.total_mb', 'ellis-mem.usable_mb', 'ellis-mem.usable_perc', 'ellis-net.in_bytes_sec', 'ellis-net.in_errors_sec', 'ellis-net.in_packets_dropped_sec', 'ellis-net.in_packets_sec', 'ellis-net.out_bytes_sec', 'ellis-net.out_errors_sec', 'ellis-net.out_packets_sec']\n",
+    "df_Ellis = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "VU27zosAYA0b",
+    "outputId": "32ed0bbb-0386-40c8-ba57-0787d3afda76"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0k96D8aDYFw-"
+   },
+   "source": [
+    "# **df_Ellis_7 / focus on the main 6 metrics**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "zVxKNXtfYCph"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['ellis-load.avg_1_min', 'ellis-cpu.wait_perc', 'ellis-net.out_packets_sec', 'ellis-cpu.system_perc', 'ellis-net.in_bytes_sec', 'ellis-mem.free_mb']\n",
+    "df_Ellis_7 = select_columns(df_Ellis, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "7y_uHZ5TYJiD",
+    "outputId": "5aef0247-67d8-4d19-c337-54075e096e07"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/df_Ellis.csv')\n",
+    "df_Ellis_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "e9c4-7mZYLpq",
+    "outputId": "020a0e5f-a63a-4918-db1b-a9e1081ce38e"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis_7.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "iFy_Het0cqh7",
+    "outputId": "ad2ea7ad-1c70-4539-a558-bee07b0a8a19"
+   },
+   "outputs": [],
+   "source": [
+    "timestamp  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/timestamp.csv\")\n",
+    "timestamp.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q2-Wt45vdTzt"
+   },
+   "outputs": [],
+   "source": [
+    "df1 = timestamp[\"Timestamp\"]\n",
+    "df1\n",
+    "df1.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/TimestampNew.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "dcpx8F6ReZzb",
+    "outputId": "7009dff8-ee1a-43ee-b990-1bfba586cce9"
+   },
+   "outputs": [],
+   "source": [
+    "df1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "mybijUDWfdcH"
+   },
+   "outputs": [],
+   "source": [
+    "#df_Ellis_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/New/df_EllisTime.csv') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2TddekZAfiad",
+    "outputId": "be25c51a-d1c0-4da8-9838-72fb59d85369"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis_7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "7gstjLldYT_r"
+   },
+   "outputs": [],
+   "source": [
+    "# df_Ellis_7.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "bFMkMFqhs5pm"
+   },
+   "outputs": [],
+   "source": [
+    "# investigate why we need this float transformation. \n",
+    "df_Ellis_7 = df_Ellis_7.astype(np.float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 882
+    },
+    "id": "mWxDJNMwtGYs",
+    "outputId": "73a4a63a-4bd6-4ef0-b140-4ef299152fa2"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis_7.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "dedoBLq_tIG_"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis_7.to_csv('df_Ellis_7.csv', sep=';')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "sObmuXeWtLL0",
+    "outputId": "e2bbea48-8fb3-4671-a4dc-5f9f2e464b59"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the boxplot\n",
+    "plt.figure(figsize=(20,20))\n",
+    "#df_Ellis_7.boxplot(figsize=(20,20))\n",
+    "ax = sns.boxplot(x=\"variable\", y=\"value\", data=pd.melt(df_Ellis_7))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "wxNTLGMHtOF_"
+   },
+   "outputs": [],
+   "source": [
+    "# the gray related metrics will be dropped when using the df_Ellis\n",
+    "\n",
+    "#del df_Ellis['ellis-cpu.stolen_perc']\n",
+    "#del df_Ellis['ellis-mem.total_mb']\n",
+    "#del df_Ellis['ellis-net.in_errors_sec']\n",
+    "#del df_Ellis['ellis-net.in_packets_dropped_sec']\n",
+    "#del df_Ellis['ellis-net.out_errors_sec']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "pcmqBw0gtUT5",
+    "outputId": "b0da529e-8895-483a-d7d1-e450fc6762e0"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "correaltionMatrice = df_Ellis_7.corr()\n",
+    "f, ax = plt.subplots(figsize=(30, 20))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 411
+    },
+    "id": "7yZNvlQ2tWlu",
+    "outputId": "dc56cd65-e5e5-4179-aac9-6c6aac43c0eb"
+   },
+   "outputs": [],
+   "source": [
+    "mask = np.zeros_like(correaltionMatrice)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "with sns.axes_style(\"white\"):\n",
+    "     ax = sns.heatmap(correaltionMatrice, mask=mask, vmin=0,vmax=1, square=True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "Whxt9FahtZ6i",
+    "outputId": "f6dd23c3-82b5-4dd1-9f18-6bd373ff9322"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis_7.shape\n",
+    "df_Ellis_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "Tmzw5MYctb3h",
+    "outputId": "65c21482-29fa-42e3-eb8f-50414bb9c656"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the scatter_matrix\n",
+    "from pandas.plotting import scatter_matrix\n",
+    "scatter_matrix(df_Ellis_7, alpha=0.2, figsize=(30,30))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "kcMuENePteVx",
+    "outputId": "7ed8fd61-a02c-4a01-f661-69938c0028ad"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the scatter_matrix (kde)\n",
+    "\n",
+    "scatter_matrix(df_Ellis_7, alpha=0.2, figsize=(30, 30), diagonal='kde')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "thrxP0LQth88",
+    "outputId": "d15b9169-79b7-47a0-e19f-b8477dd2b287"
+   },
+   "outputs": [],
+   "source": [
+    "#scatterplot the most obvious variable related to SalePrice\n",
+    "sns.pairplot(df_Ellis_7, size = 2.5)\n",
+    "plt.show();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "HNMDfsExILYz"
+   },
+   "source": [
+    "# **Bono**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "mxaAX85otljN"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['bono-cpu.idle_perc', 'bono-cpu.stolen_perc', 'bono-cpu.system_perc', 'bono-cpu.wait_perc', 'bono-disk.inode_used_perc', 'bono-disk.space_used_perc', 'bono-io.read_kbytes_sec', 'bono-io.read_req_sec', 'bono-io.read_time_sec', 'bono-io.write_kbytes_sec', 'bono-io.write_req_sec', 'bono-io.write_time_sec', 'bono-load.avg_15_min', 'bono-load.avg_1_min', 'bono-load.avg_5_min', 'bono-mem.free_mb', 'bono-mem.total_mb', 'bono-mem.usable_mb', 'bono-mem.usable_perc', 'bono-net.in_bytes_sec', 'bono-net.in_errors_sec', 'bono-net.in_packets_dropped_sec', 'bono-net.in_packets_sec', 'bono-net.out_bytes_sec', 'bono-net.out_errors_sec', 'bono-net.out_packets_sec']\n",
+    "df_Bono = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "EKi0wnvUIlZb",
+    "outputId": "4e7d2685-b09c-43ae-9217-d7210a253950"
+   },
+   "outputs": [],
+   "source": [
+    "df_Bono.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "gGCA3rWuJdQx"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['bono-load.avg_1_min', 'bono-cpu.wait_perc', 'bono-net.out_packets_sec', 'bono-cpu.system_perc', 'bono-net.in_bytes_sec', 'bono-mem.free_mb']\n",
+    "df_Bono_7 = select_columns(df_Bono, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "9ZyhiI6AJo1Y",
+    "outputId": "9308469b-ba98-4152-dafa-308d3b6f7b04"
+   },
+   "outputs": [],
+   "source": [
+    "df_Bono_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/bono/df_Bono.csv')\n",
+    "df_Bono_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "4ZUXUW35J2fr",
+    "outputId": "fc474730-e953-4f09-8633-ece4e493d9de"
+   },
+   "outputs": [],
+   "source": [
+    "df_Bono_7.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "QeQ3_oHsJ5BN"
+   },
+   "source": [
+    "# **Sprout**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "gAQmKdKfJ3st"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['sprout-cpu.idle_perc', 'sprout-cpu.stolen_perc', 'sprout-cpu.system_perc', 'sprout-cpu.wait_perc', 'sprout-disk.inode_used_perc', 'sprout-disk.space_used_perc', 'sprout-io.read_kbytes_sec', 'sprout-io.read_req_sec', 'sprout-io.read_time_sec', 'sprout-io.write_kbytes_sec', 'sprout-io.write_req_sec', 'sprout-io.write_time_sec', 'sprout-load.avg_15_min', 'sprout-load.avg_1_min', 'sprout-load.avg_5_min', 'sprout-mem.free_mb', 'sprout-mem.total_mb', 'sprout-mem.usable_mb', 'sprout-mem.usable_perc', 'sprout-net.in_bytes_sec', 'sprout-net.in_errors_sec', 'sprout-net.in_packets_dropped_sec', 'sprout-net.in_packets_sec', 'sprout-net.out_bytes_sec', 'sprout-net.out_errors_sec', 'sprout-net.out_packets_sec']\n",
+    "df_Sprout = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "wjdR0R7YMOyT",
+    "outputId": "4600cd66-0456-4da2-8723-17b5079f7f6b"
+   },
+   "outputs": [],
+   "source": [
+    "df_Sprout.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "6Tfi58LJMUNu"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['sprout-load.avg_1_min', 'sprout-cpu.wait_perc', 'sprout-net.out_packets_sec', 'sprout-cpu.system_perc', 'sprout-net.in_bytes_sec', 'sprout-mem.free_mb']\n",
+    "df_Sprout_7 = select_columns(df_Sprout, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "fP5NM3VjM0Uw",
+    "outputId": "163390b3-9ce0-406a-d9c9-88687d696c66"
+   },
+   "outputs": [],
+   "source": [
+    "df_Sprout_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/sprout/df_Sprout.csv')\n",
+    "df_Sprout_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Ybl5WrSYM9Q0",
+    "outputId": "50f23729-a029-440f-dc6f-828308bb342c"
+   },
+   "outputs": [],
+   "source": [
+    "df_Sprout_7.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "AvKCUZL5NKKz"
+   },
+   "source": [
+    "# **Homestead**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "EaXOAy7BNF8s"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['homestead-cpu.idle_perc', 'homestead-cpu.stolen_perc', 'homestead-cpu.system_perc', 'homestead-cpu.wait_perc', 'homestead-disk.inode_used_perc', 'homestead-disk.space_used_perc', 'homestead-io.read_kbytes_sec', 'homestead-io.read_req_sec', 'homestead-io.read_time_sec', 'homestead-io.write_kbytes_sec', 'homestead-io.write_req_sec', 'homestead-io.write_time_sec', 'homestead-load.avg_15_min', 'homestead-load.avg_1_min', 'homestead-load.avg_5_min', 'homestead-mem.free_mb', 'homestead-mem.total_mb', 'homestead-mem.usable_mb', 'homestead-mem.usable_perc', 'homestead-net.in_bytes_sec', 'homestead-net.in_errors_sec', 'homestead-net.in_packets_dropped_sec', 'homestead-net.in_packets_sec', 'homestead-net.out_bytes_sec', 'homestead-net.out_errors_sec', 'homestead-net.out_packets_sec']\n",
+    "df_Homestead = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "Qc5vd1CVNas2",
+    "outputId": "8b6ab0c1-d15d-4545-e69b-dd39facc5915"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homestead.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "U5e-23VDNgjS"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['homestead-load.avg_1_min', 'homestead-cpu.wait_perc', 'homestead-net.out_packets_sec', 'homestead-cpu.system_perc', 'homestead-net.in_bytes_sec', 'homestead-mem.free_mb']\n",
+    "df_Homestead_7 = select_columns(df_Homestead, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 221
+    },
+    "id": "03Y_KhJVNuOC",
+    "outputId": "ab3eef43-6a18-4c61-926a-43afac19d7a5"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homestead_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/homestead/df_Homestead.csv')\n",
+    "df_Homestead_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "CVdMWcneN7ix",
+    "outputId": "f3e00de9-f60d-44d0-ae5b-9c4eda033687"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homestead_7.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_kw5-s7hOFN3"
+   },
+   "source": [
+    "# **Ralf**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "v6xYItZWOANR"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['ralf-cpu.idle_perc', 'ralf-cpu.stolen_perc', 'ralf-cpu.system_perc', 'ralf-cpu.wait_perc', 'ralf-disk.inode_used_perc', 'ralf-disk.space_used_perc', 'ralf-io.read_kbytes_sec', 'ralf-io.read_req_sec', 'ralf-io.read_time_sec', 'ralf-io.write_kbytes_sec', 'ralf-io.write_req_sec', 'ralf-io.write_time_sec', 'ralf-load.avg_15_min', 'ralf-load.avg_1_min', 'ralf-load.avg_5_min', 'ralf-mem.free_mb', 'ralf-mem.total_mb', 'ralf-mem.usable_mb', 'ralf-mem.usable_perc', 'ralf-net.in_bytes_sec', 'ralf-net.in_errors_sec', 'ralf-net.in_packets_dropped_sec', 'ralf-net.in_packets_sec', 'ralf-net.out_bytes_sec', 'ralf-net.out_errors_sec', 'ralf-net.out_packets_sec']\n",
+    "df_Ralf = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "XlYi3QBlORiI",
+    "outputId": "6a4740f0-b2c8-4e48-9067-c17c7a267b0d"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ralf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "6l88CRqDOVs-"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['ralf-load.avg_1_min', 'ralf-cpu.wait_perc', 'ralf-net.out_packets_sec', 'ralf-cpu.system_perc', 'ralf-net.in_bytes_sec', 'ralf-mem.free_mb']\n",
+    "df_Ralf_7 = select_columns(df_Ralf, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "u3v26LoiOi5L",
+    "outputId": "441d54ec-a644-446e-dc5b-e7ad5ec58456"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ralf_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/ralf/df_Ralf.csv')\n",
+    "df_Ralf_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "mR7Fg1w8OtnU",
+    "outputId": "141c6b09-3c69-45cc-e723-728e1f0e8e68"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ralf_7.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2-udEbTHO-HS"
+   },
+   "source": [
+    "# **Homer**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "vVpG5lJiOyYw"
+   },
+   "outputs": [],
+   "source": [
+    "# this function select column from the global df and create a new df with them\n",
+    "def select_columns(data_frame, column_names):\n",
+    "    new_frame = data_frame.loc[:, column_names]\n",
+    "    return new_frame\n",
+    "\n",
+    "selected_columns = ['homer-cpu.idle_perc', 'homer-cpu.stolen_perc', 'homer-cpu.system_perc', 'homer-cpu.wait_perc', 'homer-disk.inode_used_perc', 'homer-disk.space_used_perc', 'homer-io.read_kbytes_sec', 'homer-io.read_req_sec', 'homer-io.read_time_sec', 'homer-io.write_kbytes_sec', 'homer-io.write_req_sec', 'homer-io.write_time_sec', 'homer-load.avg_15_min', 'homer-load.avg_1_min', 'homer-load.avg_5_min', 'homer-mem.free_mb', 'homer-mem.total_mb', 'homer-mem.usable_mb', 'homer-mem.usable_perc', 'homer-net.in_bytes_sec', 'homer-net.in_errors_sec', 'homer-net.in_packets_dropped_sec', 'homer-net.in_packets_sec', 'homer-net.out_bytes_sec', 'homer-net.out_errors_sec', 'homer-net.out_packets_sec']\n",
+    "df_Homer = select_columns(dframesorted, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 241
+    },
+    "id": "cwMKYQWUPKpl",
+    "outputId": "ca108468-0c41-4f44-aef0-8c63239c9fd5"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homer.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "rsUb47imPOyE"
+   },
+   "outputs": [],
+   "source": [
+    "selected_columns= ['homer-load.avg_1_min', 'homer-cpu.wait_perc', 'homer-net.out_packets_sec', 'homer-cpu.system_perc', 'homer-net.in_bytes_sec', 'homer-mem.free_mb']\n",
+    "df_Homer_7 = select_columns(df_Homer, selected_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "id": "VZw7WV7tPd9i",
+    "outputId": "39dc88dd-eb89-45b0-a0d3-f261aab6bbd1"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homer_7.to_csv('/gdrive/MyDrive/LFN Anuket/Analysis/data/homer/df_Homer.csv')\n",
+    "df_Homer_7.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "E1Cqq8V3PnEv",
+    "outputId": "9a80be17-5bb5-4f8d-a61c-d3206e730309"
+   },
+   "outputs": [],
+   "source": [
+    "df_Homer_7.info()"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "vIMS_Visualization.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
author	Sridhar K. N. Rao <srao@linuxfoundation.org>
	Tue, 3 May 2022 21:12:21 +0000 (02:42 +0530)
committer	Sridhar K. N. Rao <srao@linuxfoundation.org>
	Tue, 3 May 2022 21:13:10 +0000 (02:43 +0530)
models/failure_prediction/jnotebooks/Attention_LSTM.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/CNN.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/Decision_Tree.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/FeatureCreation.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/LSTM.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/LSTM_Attention.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/LSTM_correlation.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb		patch \| blob \| history
models/failure_prediction/jnotebooks/vIMS_Visualization.ipynb		patch \| blob \| history