Stock_Market_Prediction.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Stock Market Prediction.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "1ukdImbOBtJGEsDd9rXSb-EnKcftKxmCJ",
      "authorship_tag": "ABX9TyMHJdNotspmZdf+835yllyM",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/SparshRastogi/Covid-19-Risk-Calculator/blob/main/Stock_Market_Prediction.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "67i7E8QA2aIi"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import sklearn \n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.metrics import mean_squared_error"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow\n",
        "import keras\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense,LSTM"
      ],
      "metadata": {
        "id": "Nr8iYHmH2rPX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install pandas-datareader"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tYRsoPbf3E_l",
        "outputId": "677779ed-e157-49a8-8376-5fb4fab870ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pandas-datareader in /usr/local/lib/python3.7/dist-packages (0.9.0)\n",
            "Requirement already satisfied: lxml in /usr/local/lib/python3.7/dist-packages (from pandas-datareader) (4.2.6)\n",
            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from pandas-datareader) (2.23.0)\n",
            "Requirement already satisfied: pandas>=0.23 in /usr/local/lib/python3.7/dist-packages (from pandas-datareader) (1.3.5)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.23->pandas-datareader) (1.21.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.23->pandas-datareader) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.23->pandas-datareader) (2018.9)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.23->pandas-datareader) (1.15.0)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pandas-datareader) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pandas-datareader) (2021.10.8)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pandas-datareader) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pandas-datareader) (3.0.4)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas_datareader as pdr"
      ],
      "metadata": {
        "id": "MpbRKYvl3In3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "company = input('Enter company name: ')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t9c0hfI34rv0",
        "outputId": "2ac071ef-2338-454c-a7e7-5af75404a185"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Enter company name: Aapl\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pdr.get_data_tiingo(company, api_key ='074deba77b28710c27bc34818a008f0c1945f238')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YgdIklrX3Utx",
        "outputId": "8b12e01f-d4b5-42d4-a7a6-30239c95123d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas_datareader/tiingo.py:234: FutureWarning: In a future version of pandas all arguments of concat except for the argument 'objs' will be keyword-only\n",
            "  return pd.concat(dfs, self._concat_axis)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 692
        },
        "id": "LArWaSHa486W",
        "outputId": "c623d7de-82d0-4977-db61-3286f15ac093"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-8b029f66-04dc-4585-8899-94a43ae0cef8\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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></th>\n",
              "      <th>close</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>open</th>\n",
              "      <th>volume</th>\n",
              "      <th>adjClose</th>\n",
              "      <th>adjHigh</th>\n",
              "      <th>adjLow</th>\n",
              "      <th>adjOpen</th>\n",
              "      <th>adjVolume</th>\n",
              "      <th>divCash</th>\n",
              "      <th>splitFactor</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>symbol</th>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></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 rowspan=\"11\" valign=\"top\">Aapl</th>\n",
              "      <th>2017-02-27 00:00:00+00:00</th>\n",
              "      <td>136.93</td>\n",
              "      <td>137.4350</td>\n",
              "      <td>136.280</td>\n",
              "      <td>137.14</td>\n",
              "      <td>20257426</td>\n",
              "      <td>32.316004</td>\n",
              "      <td>32.435186</td>\n",
              "      <td>32.162601</td>\n",
              "      <td>32.365565</td>\n",
              "      <td>81029704</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-28 00:00:00+00:00</th>\n",
              "      <td>136.99</td>\n",
              "      <td>137.4350</td>\n",
              "      <td>136.700</td>\n",
              "      <td>137.08</td>\n",
              "      <td>23482860</td>\n",
              "      <td>32.330164</td>\n",
              "      <td>32.435186</td>\n",
              "      <td>32.261723</td>\n",
              "      <td>32.351404</td>\n",
              "      <td>93931440</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-01 00:00:00+00:00</th>\n",
              "      <td>139.79</td>\n",
              "      <td>140.1500</td>\n",
              "      <td>137.595</td>\n",
              "      <td>137.89</td>\n",
              "      <td>36414585</td>\n",
              "      <td>32.990975</td>\n",
              "      <td>33.075936</td>\n",
              "      <td>32.472946</td>\n",
              "      <td>32.542568</td>\n",
              "      <td>145658340</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-02 00:00:00+00:00</th>\n",
              "      <td>138.96</td>\n",
              "      <td>140.2786</td>\n",
              "      <td>138.760</td>\n",
              "      <td>140.00</td>\n",
              "      <td>26210984</td>\n",
              "      <td>32.795092</td>\n",
              "      <td>33.106286</td>\n",
              "      <td>32.747891</td>\n",
              "      <td>33.040536</td>\n",
              "      <td>104843936</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-03-03 00:00:00+00:00</th>\n",
              "      <td>139.78</td>\n",
              "      <td>139.8300</td>\n",
              "      <td>138.590</td>\n",
              "      <td>138.78</td>\n",
              "      <td>21571121</td>\n",
              "      <td>32.988615</td>\n",
              "      <td>33.000415</td>\n",
              "      <td>32.707770</td>\n",
              "      <td>32.752611</td>\n",
              "      <td>86284484</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-16 00:00:00+00:00</th>\n",
              "      <td>172.55</td>\n",
              "      <td>173.3400</td>\n",
              "      <td>170.050</td>\n",
              "      <td>171.85</td>\n",
              "      <td>61177398</td>\n",
              "      <td>172.550000</td>\n",
              "      <td>173.340000</td>\n",
              "      <td>170.050000</td>\n",
              "      <td>171.850000</td>\n",
              "      <td>61177398</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-17 00:00:00+00:00</th>\n",
              "      <td>168.88</td>\n",
              "      <td>171.9100</td>\n",
              "      <td>168.470</td>\n",
              "      <td>171.03</td>\n",
              "      <td>69589344</td>\n",
              "      <td>168.880000</td>\n",
              "      <td>171.910000</td>\n",
              "      <td>168.470000</td>\n",
              "      <td>171.030000</td>\n",
              "      <td>69589344</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-18 00:00:00+00:00</th>\n",
              "      <td>167.30</td>\n",
              "      <td>170.5413</td>\n",
              "      <td>166.190</td>\n",
              "      <td>169.82</td>\n",
              "      <td>82772674</td>\n",
              "      <td>167.300000</td>\n",
              "      <td>170.541300</td>\n",
              "      <td>166.190000</td>\n",
              "      <td>169.820000</td>\n",
              "      <td>82772674</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-22 00:00:00+00:00</th>\n",
              "      <td>164.32</td>\n",
              "      <td>166.6900</td>\n",
              "      <td>162.150</td>\n",
              "      <td>164.98</td>\n",
              "      <td>90457637</td>\n",
              "      <td>164.320000</td>\n",
              "      <td>166.690000</td>\n",
              "      <td>162.150000</td>\n",
              "      <td>164.980000</td>\n",
              "      <td>90457637</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 00:00:00+00:00</th>\n",
              "      <td>160.07</td>\n",
              "      <td>166.1500</td>\n",
              "      <td>159.750</td>\n",
              "      <td>165.54</td>\n",
              "      <td>90009247</td>\n",
              "      <td>160.070000</td>\n",
              "      <td>166.150000</td>\n",
              "      <td>159.750000</td>\n",
              "      <td>165.540000</td>\n",
              "      <td>90009247</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1258 rows × 12 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b029f66-04dc-4585-8899-94a43ae0cef8')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8b029f66-04dc-4585-8899-94a43ae0cef8 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8b029f66-04dc-4585-8899-94a43ae0cef8');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                                   close      high  ...  divCash  splitFactor\n",
              "symbol date                                         ...                      \n",
              "Aapl   2017-02-27 00:00:00+00:00  136.93  137.4350  ...      0.0          1.0\n",
              "       2017-02-28 00:00:00+00:00  136.99  137.4350  ...      0.0          1.0\n",
              "       2017-03-01 00:00:00+00:00  139.79  140.1500  ...      0.0          1.0\n",
              "       2017-03-02 00:00:00+00:00  138.96  140.2786  ...      0.0          1.0\n",
              "       2017-03-03 00:00:00+00:00  139.78  139.8300  ...      0.0          1.0\n",
              "...                                  ...       ...  ...      ...          ...\n",
              "       2022-02-16 00:00:00+00:00  172.55  173.3400  ...      0.0          1.0\n",
              "       2022-02-17 00:00:00+00:00  168.88  171.9100  ...      0.0          1.0\n",
              "       2022-02-18 00:00:00+00:00  167.30  170.5413  ...      0.0          1.0\n",
              "       2022-02-22 00:00:00+00:00  164.32  166.6900  ...      0.0          1.0\n",
              "       2022-02-23 00:00:00+00:00  160.07  166.1500  ...      0.0          1.0\n",
              "\n",
              "[1258 rows x 12 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 164
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "PCl7KJ7z6W4F",
        "outputId": "a679844c-7a34-421a-bb98-b4b7629c1f83"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "MessageError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mMessageError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-7-d5df0069828e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgoogle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolab\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdrive\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdrive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/content/drive'\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/usr/local/lib/python3.7/dist-packages/google/colab/drive.py\u001b[0m in \u001b[0;36mmount\u001b[0;34m(mountpoint, force_remount, timeout_ms, use_metadata_server)\u001b[0m\n\u001b[1;32m    113\u001b[0m       \u001b[0mforce_remount\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mforce_remount\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m       \u001b[0mtimeout_ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout_ms\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 115\u001b[0;31m       ephemeral=True)\n\u001b[0m\u001b[1;32m    116\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/drive.py\u001b[0m in \u001b[0;36m_mount\u001b[0;34m(mountpoint, force_remount, timeout_ms, use_metadata_server, ephemeral)\u001b[0m\n\u001b[1;32m    133\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mephemeral\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    134\u001b[0m     _message.blocking_request(\n\u001b[0;32m--> 135\u001b[0;31m         'request_auth', request={'authType': 'dfs_ephemeral'}, timeout_sec=None)\n\u001b[0m\u001b[1;32m    136\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    137\u001b[0m   \u001b[0mmountpoint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_os\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpanduser\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmountpoint\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/google/colab/_message.py\u001b[0m in \u001b[0;36mblocking_request\u001b[0;34m(request_type, request, timeout_sec, parent)\u001b[0m\n\u001b[1;32m    173\u001b[0m   request_id = send_request(\n\u001b[1;32m    174\u001b[0m       request_type, request, parent=parent, expect_reply=True)\n\u001b[0;32m--> 175\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0mread_reply_from_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_sec\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/usr/local/lib/python3.7/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mread_reply_from_input\u001b[0;34m(message_id, timeout_sec)\u001b[0m\n\u001b[1;32m    104\u001b[0m         reply.get('colab_msg_id') == message_id):\n\u001b[1;32m    105\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mMessageError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreply\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\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    107\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mMessageError\u001b[0m: Error: credential propagation was unsuccessful"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv(f'/content/drive/MyDrive/{company}.csv')"
      ],
      "metadata": {
        "id": "UppIuj0M5-Gq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1 = df.reset_index()['close']"
      ],
      "metadata": {
        "id": "OBVK3baz7SZF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HssTQ7WK7l0S",
        "outputId": "57793547-9f03-44b8-c839-edb9ba88ca82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       136.93\n",
              "1       136.99\n",
              "2       139.79\n",
              "3       138.96\n",
              "4       139.78\n",
              "         ...  \n",
              "1253    172.55\n",
              "1254    168.88\n",
              "1255    167.30\n",
              "1256    164.32\n",
              "1257    160.07\n",
              "Name: close, Length: 1258, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 187
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "5Cjac6DY7Yn1",
        "outputId": "381306a1-6697-4b21-c28a-eee396ade4c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f3e05423090>]"
            ]
          },
          "metadata": {},
          "execution_count": 188
        },
        {
          "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",
      "source": [
        "scaler = MinMaxScaler()\n",
        "df1 = scaler.fit_transform(np.array(df1).reshape(-1,1))"
      ],
      "metadata": {
        "id": "97y-V1YN8Yx6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DwAb4jJ480_y",
        "outputId": "a7757229-8168-43c8-a2a5-af897b678a8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.07536631],\n",
              "       [0.07551659],\n",
              "       [0.08252974],\n",
              "       ...,\n",
              "       [0.15143394],\n",
              "       [0.14396994],\n",
              "       [0.13332498]])"
            ]
          },
          "metadata": {},
          "execution_count": 190
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_size=int(len(df1)*0.70)\n",
        "test_size=len(df1)-training_size\n",
        "train_data,test_data=df1[0:training_size,:],df1[training_size:len(df1),:1]"
      ],
      "metadata": {
        "id": "HYgUXl049l3r"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_data"
      ],
      "metadata": {
        "id": "wE6WSpX4-VTL",
        "outputId": "99df3398-d90a-483c-8fbf-f20e067eefb2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.07536631],\n",
              "       [0.07551659],\n",
              "       [0.08252974],\n",
              "       [0.08045085],\n",
              "       [0.0825047 ],\n",
              "       [0.08140263],\n",
              "       [0.08185348],\n",
              "       [0.08055103],\n",
              "       [0.07974953],\n",
              "       [0.08090169],\n",
              "       [0.08105197],\n",
              "       [0.08052599],\n",
              "       [0.08420789],\n",
              "       [0.08478397],\n",
              "       [0.08303068],\n",
              "       [0.08671259],\n",
              "       [0.08265498],\n",
              "       [0.0866124 ],\n",
              "       [0.08536005],\n",
              "       [0.08465874],\n",
              "       [0.08525986],\n",
              "       [0.09257358],\n",
              "       [0.09337508],\n",
              "       [0.09289919],\n",
              "       [0.09222292],\n",
              "       [0.09232311],\n",
              "       [0.09500313],\n",
              "       [0.09312461],\n",
              "       [0.09222292],\n",
              "       [0.09142142],\n",
              "       [0.09099562],\n",
              "       [0.08713838],\n",
              "       [0.08756418],\n",
              "       [0.08568566],\n",
              "       [0.08763932],\n",
              "       [0.08606137],\n",
              "       [0.08475892],\n",
              "       [0.08916719],\n",
              "       [0.08874139],\n",
              "       [0.09217282],\n",
              "       [0.094402  ],\n",
              "       [0.09227301],\n",
              "       [0.09254853],\n",
              "       [0.09219787],\n",
              "       [0.09953663],\n",
              "       [0.101866  ],\n",
              "       [0.10073889],\n",
              "       [0.0994114 ],\n",
              "       [0.10549781],\n",
              "       [0.11564183],\n",
              "       [0.11809643],\n",
              "       [0.116268  ],\n",
              "       [0.11799624],\n",
              "       [0.12338134],\n",
              "       [0.12237946],\n",
              "       [0.12180338],\n",
              "       [0.10872887],\n",
              "       [0.11446462],\n",
              "       [0.11576706],\n",
              "       [0.11809643],\n",
              "       [0.11762054],\n",
              "       [0.11646838],\n",
              "       [0.11779587],\n",
              "       [0.11714465],\n",
              "       [0.11729493],\n",
              "       [0.11501565],\n",
              "       [0.11606763],\n",
              "       [0.12175329],\n",
              "       [0.11794615],\n",
              "       [0.11924859],\n",
              "       [0.12155291],\n",
              "       [0.12060113],\n",
              "       [0.1055479 ],\n",
              "       [0.09663118],\n",
              "       [0.09956168],\n",
              "       [0.09597996],\n",
              "       [0.09380088],\n",
              "       [0.08874139],\n",
              "       [0.0989355 ],\n",
              "       [0.09560426],\n",
              "       [0.0977583 ],\n",
              "       [0.09715717],\n",
              "       [0.09878522],\n",
              "       [0.09763306],\n",
              "       [0.09239825],\n",
              "       [0.09765811],\n",
              "       [0.09227301],\n",
              "       [0.09312461],\n",
              "       [0.09182217],\n",
              "       [0.09329994],\n",
              "       [0.08989355],\n",
              "       [0.09352536],\n",
              "       [0.09572949],\n",
              "       [0.0969067 ],\n",
              "       [0.09743269],\n",
              "       [0.10251722],\n",
              "       [0.10569818],\n",
              "       [0.10700063],\n",
              "       [0.10830307],\n",
              "       [0.11065748],\n",
              "       [0.10895429],\n",
              "       [0.10877896],\n",
              "       [0.11333751],\n",
              "       [0.11496556],\n",
              "       [0.11676894],\n",
              "       [0.10950532],\n",
              "       [0.10685034],\n",
              "       [0.10492173],\n",
              "       [0.10822793],\n",
              "       [0.12598622],\n",
              "       [0.12205385],\n",
              "       [0.1241077 ],\n",
              "       [0.13016907],\n",
              "       [0.13335003],\n",
              "       [0.13580463],\n",
              "       [0.12142768],\n",
              "       [0.12683782],\n",
              "       [0.13277395],\n",
              "       [0.13715717],\n",
              "       [0.13552912],\n",
              "       [0.12778961],\n",
              "       [0.12688791],\n",
              "       [0.12616155],\n",
              "       [0.13259862],\n",
              "       [0.13309956],\n",
              "       [0.13132123],\n",
              "       [0.132799  ],\n",
              "       [0.13683156],\n",
              "       [0.14043832],\n",
              "       [0.14154039],\n",
              "       [0.14316844],\n",
              "       [0.14329368],\n",
              "       [0.13835942],\n",
              "       [0.13793363],\n",
              "       [0.13630557],\n",
              "       [0.12971822],\n",
              "       [0.1369067 ],\n",
              "       [0.13530369],\n",
              "       [0.13227301],\n",
              "       [0.12884158],\n",
              "       [0.13284909],\n",
              "       [0.12981841],\n",
              "       [0.12996869],\n",
              "       [0.1233062 ],\n",
              "       [0.11659361],\n",
              "       [0.11283657],\n",
              "       [0.10948028],\n",
              "       [0.11596744],\n",
              "       [0.11869756],\n",
              "       [0.1163181 ],\n",
              "       [0.11842204],\n",
              "       [0.11764559],\n",
              "       [0.11932373],\n",
              "       [0.11681904],\n",
              "       [0.12160301],\n",
              "       [0.12137758],\n",
              "       [0.12273012],\n",
              "       [0.1228804 ],\n",
              "       [0.12450845],\n",
              "       [0.12313087],\n",
              "       [0.12561052],\n",
              "       [0.13284909],\n",
              "       [0.13432686],\n",
              "       [0.13254853],\n",
              "       [0.12308078],\n",
              "       [0.12375704],\n",
              "       [0.12355667],\n",
              "       [0.12588604],\n",
              "       [0.1241578 ],\n",
              "       [0.12666249],\n",
              "       [0.14078898],\n",
              "       [0.14998121],\n",
              "       [0.15579211],\n",
              "       [0.15040701],\n",
              "       [0.15346274],\n",
              "       [0.16445836],\n",
              "       [0.16884158],\n",
              "       [0.17024421],\n",
              "       [0.17382592],\n",
              "       [0.17292423],\n",
              "       [0.16989355],\n",
              "       [0.16814026],\n",
              "       [0.16155291],\n",
              "       [0.1558923 ],\n",
              "       [0.16095178],\n",
              "       [0.15857232],\n",
              "       [0.15814652],\n",
              "       [0.16606137],\n",
              "       [0.17061991],\n",
              "       [0.17064496],\n",
              "       [0.16844083],\n",
              "       [0.16588604],\n",
              "       [0.15689418],\n",
              "       [0.16283031],\n",
              "       [0.16082655],\n",
              "       [0.15769568],\n",
              "       [0.15729493],\n",
              "       [0.15571697],\n",
              "       [0.15649343],\n",
              "       [0.15661866],\n",
              "       [0.16488416],\n",
              "       [0.1624546 ],\n",
              "       [0.16388228],\n",
              "       [0.16375704],\n",
              "       [0.16814026],\n",
              "       [0.17427677],\n",
              "       [0.16956794],\n",
              "       [0.16909205],\n",
              "       [0.17074515],\n",
              "       [0.17074515],\n",
              "       [0.1596243 ],\n",
              "       [0.15969944],\n",
              "       [0.16090169],\n",
              "       [0.156268  ],\n",
              "       [0.16385723],\n",
              "       [0.16378209],\n",
              "       [0.16578585],\n",
              "       [0.1707201 ],\n",
              "       [0.16909205],\n",
              "       [0.16904195],\n",
              "       [0.16894177],\n",
              "       [0.17142142],\n",
              "       [0.17595492],\n",
              "       [0.17370069],\n",
              "       [0.18098936],\n",
              "       [0.18139011],\n",
              "       [0.17938635],\n",
              "       [0.17572949],\n",
              "       [0.17582968],\n",
              "       [0.16876644],\n",
              "       [0.16097683],\n",
              "       [0.16197871],\n",
              "       [0.15308704],\n",
              "       [0.15060739],\n",
              "       [0.15175955],\n",
              "       [0.15263619],\n",
              "       [0.134402  ],\n",
              "       [0.12435817],\n",
              "       [0.14073889],\n",
              "       [0.1319975 ],\n",
              "       [0.12100188],\n",
              "       [0.1241578 ],\n",
              "       [0.13993738],\n",
              "       [0.14402004],\n",
              "       [0.15160927],\n",
              "       [0.16568566],\n",
              "       [0.16428303],\n",
              "       [0.16283031],\n",
              "       [0.16087664],\n",
              "       [0.16445836],\n",
              "       [0.17197245],\n",
              "       [0.18066374],\n",
              "       [0.17921102],\n",
              "       [0.17853475],\n",
              "       [0.1707201 ],\n",
              "       [0.17375078],\n",
              "       [0.17527865],\n",
              "       [0.17490294],\n",
              "       [0.17079524],\n",
              "       [0.17557921],\n",
              "       [0.18319349],\n",
              "       [0.18755166],\n",
              "       [0.18316844],\n",
              "       [0.17933626],\n",
              "       [0.17986224],\n",
              "       [0.17828428],\n",
              "       [0.17147151],\n",
              "       [0.17132123],\n",
              "       [0.16137758],\n",
              "       [0.15531622],\n",
              "       [0.14552286],\n",
              "       [0.16513463],\n",
              "       [0.15403882],\n",
              "       [0.14938009],\n",
              "       [0.15263619],\n",
              "       [0.14988103],\n",
              "       [0.15416406],\n",
              "       [0.16222918],\n",
              "       [0.16520977],\n",
              "       [0.15413901],\n",
              "       [0.15832185],\n",
              "       [0.16633688],\n",
              "       [0.16430808],\n",
              "       [0.16856606],\n",
              "       [0.17004383],\n",
              "       [0.17277395],\n",
              "       [0.17883532],\n",
              "       [0.17783344],\n",
              "       [0.16520977],\n",
              "       [0.14747652],\n",
              "       [0.14627426],\n",
              "       [0.14051346],\n",
              "       [0.1422918 ],\n",
              "       [0.14371947],\n",
              "       [0.13896055],\n",
              "       [0.14632436],\n",
              "       [0.15594239],\n",
              "       [0.17465247],\n",
              "       [0.17545398],\n",
              "       [0.19283657],\n",
              "       [0.19616781],\n",
              "       [0.19839699],\n",
              "       [0.20167815],\n",
              "       [0.20839073],\n",
              "       [0.20475892],\n",
              "       [0.20365686],\n",
              "       [0.19937383],\n",
              "       [0.203732  ],\n",
              "       [0.20075141],\n",
              "       [0.19904822],\n",
              "       [0.20235441],\n",
              "       [0.20117721],\n",
              "       [0.20418284],\n",
              "       [0.20365686],\n",
              "       [0.20473388],\n",
              "       [0.20303068],\n",
              "       [0.2020288 ],\n",
              "       [0.20045085],\n",
              "       [0.20889167],\n",
              "       [0.21287414],\n",
              "       [0.21658109],\n",
              "       [0.21825924],\n",
              "       [0.21695679],\n",
              "       [0.21254853],\n",
              "       [0.21137132],\n",
              "       [0.21400125],\n",
              "       [0.21004383],\n",
              "       [0.2102943 ],\n",
              "       [0.2053851 ],\n",
              "       [0.20513463],\n",
              "       [0.1974953 ],\n",
              "       [0.19952411],\n",
              "       [0.19691922],\n",
              "       [0.19556669],\n",
              "       [0.18867877],\n",
              "       [0.19433939],\n",
              "       [0.19366312],\n",
              "       [0.19701941],\n",
              "       [0.19604258],\n",
              "       [0.2012273 ],\n",
              "       [0.19306199],\n",
              "       [0.19676894],\n",
              "       [0.20320601],\n",
              "       [0.20974327],\n",
              "       [0.20916719],\n",
              "       [0.20298059],\n",
              "       [0.21087038],\n",
              "       [0.21162179],\n",
              "       [0.21056982],\n",
              "       [0.21192235],\n",
              "       [0.20929242],\n",
              "       [0.21299937],\n",
              "       [0.21189731],\n",
              "       [0.21232311],\n",
              "       [0.21580463],\n",
              "       [0.22036318],\n",
              "       [0.21883532],\n",
              "       [0.21074515],\n",
              "       [0.20806512],\n",
              "       [0.20901691],\n",
              "       [0.23709455],\n",
              "       [0.25184721],\n",
              "       [0.25335003],\n",
              "       [0.2560551 ],\n",
              "       [0.2511459 ],\n",
              "       [0.25149656],\n",
              "       [0.25557921],\n",
              "       [0.25219787],\n",
              "       [0.25555416],\n",
              "       [0.2577583 ],\n",
              "       [0.2589856 ],\n",
              "       [0.26670006],\n",
              "       [0.27737007],\n",
              "       [0.27206011],\n",
              "       [0.27100814],\n",
              "       [0.27103319],\n",
              "       [0.27213525],\n",
              "       [0.2738134 ],\n",
              "       [0.27827176],\n",
              "       [0.28268003],\n",
              "       [0.29089543],\n",
              "       [0.29603006],\n",
              "       [0.30254227],\n",
              "       [0.3043707 ],\n",
              "       [0.3006387 ],\n",
              "       [0.29119599],\n",
              "       [0.28668754],\n",
              "       [0.27924859],\n",
              "       [0.29307451],\n",
              "       [0.28611146],\n",
              "       [0.29948654],\n",
              "       [0.29304947],\n",
              "       [0.27812148],\n",
              "       [0.27902317],\n",
              "       [0.27934878],\n",
              "       [0.28350657],\n",
              "       [0.27757044],\n",
              "       [0.28541014],\n",
              "       [0.28891672],\n",
              "       [0.28448341],\n",
              "       [0.29582968],\n",
              "       [0.29780839],\n",
              "       [0.30161553],\n",
              "       [0.30667502],\n",
              "       [0.31366312],\n",
              "       [0.30344396],\n",
              "       [0.29417658],\n",
              "       [0.29287414],\n",
              "       [0.3006387 ],\n",
              "       [0.27431434],\n",
              "       [0.26953037],\n",
              "       [0.28871634],\n",
              "       [0.27681904],\n",
              "       [0.28881653],\n",
              "       [0.28641202],\n",
              "       [0.27346274],\n",
              "       [0.28170319],\n",
              "       [0.28505949],\n",
              "       [0.29026925],\n",
              "       [0.27113338],\n",
              "       [0.28293049],\n",
              "       [0.27416406],\n",
              "       [0.26399499],\n",
              "       [0.26664997],\n",
              "       [0.28057608],\n",
              "       [0.28899186],\n",
              "       [0.25207264],\n",
              "       [0.23731997],\n",
              "       [0.24278021],\n",
              "       [0.25825924],\n",
              "       [0.25460238],\n",
              "       [0.2445335 ],\n",
              "       [0.21873513],\n",
              "       [0.21387602],\n",
              "       [0.20027552],\n",
              "       [0.21182217],\n",
              "       [0.21713212],\n",
              "       [0.1979211 ],\n",
              "       [0.1756794 ],\n",
              "       [0.17517846],\n",
              "       [0.16393237],\n",
              "       [0.16976832],\n",
              "       [0.16881653],\n",
              "       [0.185598  ],\n",
              "       [0.18211647],\n",
              "       [0.17968691],\n",
              "       [0.19531622],\n",
              "       [0.17495304],\n",
              "       [0.17001879],\n",
              "       [0.15441453],\n",
              "       [0.15719474],\n",
              "       [0.15476518],\n",
              "       [0.15594239],\n",
              "       [0.16057608],\n",
              "       [0.14687539],\n",
              "       [0.14301816],\n",
              "       [0.14835316],\n",
              "       [0.13537884],\n",
              "       [0.12520977],\n",
              "       [0.10993112],\n",
              "       [0.10016281],\n",
              "       [0.12606137],\n",
              "       [0.12350657],\n",
              "       [0.12370695],\n",
              "       [0.12748904],\n",
              "       [0.12793989],\n",
              "       [0.08854101],\n",
              "       [0.10374452],\n",
              "       [0.10291797],\n",
              "       [0.10998121],\n",
              "       [0.11639324],\n",
              "       [0.11762054],\n",
              "       [0.11383845],\n",
              "       [0.10810269],\n",
              "       [0.11579211],\n",
              "       [0.12047589],\n",
              "       [0.12278021],\n",
              "       [0.12518472],\n",
              "       [0.11636819],\n",
              "       [0.1179211 ],\n",
              "       [0.11486537],\n",
              "       [0.12753914],\n",
              "       [0.12388228],\n",
              "       [0.11982467],\n",
              "       [0.14629931],\n",
              "       [0.1492799 ],\n",
              "       [0.14948028],\n",
              "       [0.16132749],\n",
              "       [0.16866625],\n",
              "       [0.16881653],\n",
              "       [0.16055103],\n",
              "       [0.15922354],\n",
              "       [0.15676894],\n",
              "       [0.1604258 ],\n",
              "       [0.15864746],\n",
              "       [0.16020038],\n",
              "       [0.15924859],\n",
              "       [0.16052599],\n",
              "       [0.16328115],\n",
              "       [0.1608516 ],\n",
              "       [0.16563557],\n",
              "       [0.16879148],\n",
              "       [0.16904195],\n",
              "       [0.17039449],\n",
              "       [0.16608641],\n",
              "       [0.17064496],\n",
              "       [0.17284909],\n",
              "       [0.17204759],\n",
              "       [0.16951785],\n",
              "       [0.16445836],\n",
              "       [0.16548528],\n",
              "       [0.18048842],\n",
              "       [0.18552286],\n",
              "       [0.18752661],\n",
              "       [0.1925861 ],\n",
              "       [0.19857232],\n",
              "       [0.20333125],\n",
              "       [0.19959925],\n",
              "       [0.2036819 ],\n",
              "       [0.22103945],\n",
              "       [0.21092048],\n",
              "       [0.20513463],\n",
              "       [0.20025047],\n",
              "       [0.20445836],\n",
              "       [0.20508453],\n",
              "       [0.20816531],\n",
              "       [0.21139637],\n",
              "       [0.21835942],\n",
              "       [0.22169067],\n",
              "       [0.22254227],\n",
              "       [0.22582342],\n",
              "       [0.23358798],\n",
              "       [0.23208516],\n",
              "       [0.23489042],\n",
              "       [0.23070758],\n",
              "       [0.2305072 ],\n",
              "       [0.23140889],\n",
              "       [0.23145899],\n",
              "       [0.24117721],\n",
              "       [0.24300564],\n",
              "       [0.24468378],\n",
              "       [0.25207264],\n",
              "       [0.25127113],\n",
              "       [0.2465623 ],\n",
              "       [0.2441077 ],\n",
              "       [0.24488416],\n",
              "       [0.23501565],\n",
              "       [0.25968691],\n",
              "       [0.25625548],\n",
              "       [0.26276769],\n",
              "       [0.25457733],\n",
              "       [0.24050094],\n",
              "       [0.24060113],\n",
              "       [0.23514089],\n",
              "       [0.22627426],\n",
              "       [0.19757044],\n",
              "       [0.20493425],\n",
              "       [0.21059487],\n",
              "       [0.20849092],\n",
              "       [0.20578585],\n",
              "       [0.19098309],\n",
              "       [0.19977458],\n",
              "       [0.19020664],\n",
              "       [0.18239198],\n",
              "       [0.18066374],\n",
              "       [0.17881027],\n",
              "       [0.17668128],\n",
              "       [0.1789856 ],\n",
              "       [0.17089543],\n",
              "       [0.16646212],\n",
              "       [0.18234189],\n",
              "       [0.18960551],\n",
              "       [0.1963181 ],\n",
              "       [0.20866625],\n",
              "       [0.21475266],\n",
              "       [0.22033813],\n",
              "       [0.21878522],\n",
              "       [0.21868503],\n",
              "       [0.21515341],\n",
              "       [0.21803381],\n",
              "       [0.22945523],\n",
              "       [0.2280025 ],\n",
              "       [0.23198497],\n",
              "       [0.23028178],\n",
              "       [0.22978084],\n",
              "       [0.2222417 ],\n",
              "       [0.23283657],\n",
              "       [0.23268629],\n",
              "       [0.22812774],\n",
              "       [0.23721979],\n",
              "       [0.24017533],\n",
              "       [0.24438322],\n",
              "       [0.24393237],\n",
              "       [0.2333876 ],\n",
              "       [0.23644333],\n",
              "       [0.24142768],\n",
              "       [0.23772073],\n",
              "       [0.24160301],\n",
              "       [0.24638698],\n",
              "       [0.24460864],\n",
              "       [0.24172824],\n",
              "       [0.24751409],\n",
              "       [0.23982467],\n",
              "       [0.25142142],\n",
              "       [0.25547902],\n",
              "       [0.25505322],\n",
              "       [0.25092048],\n",
              "       [0.25272386],\n",
              "       [0.25758297],\n",
              "       [0.25532874],\n",
              "       [0.26599875],\n",
              "       [0.2544521 ],\n",
              "       [0.24340639],\n",
              "       [0.21665623],\n",
              "       [0.22582342],\n",
              "       [0.230933  ],\n",
              "       [0.24192862],\n",
              "       [0.23581716],\n",
              "       [0.23453976],\n",
              "       [0.25580463],\n",
              "       [0.24022542],\n",
              "       [0.23769568],\n",
              "       [0.24961803],\n",
              "       [0.25926111],\n",
              "       [0.25928616],\n",
              "       [0.26499687],\n",
              "       [0.26454602],\n",
              "       [0.23994991],\n",
              "       [0.24959299],\n",
              "       [0.24375704],\n",
              "       [0.24718848],\n",
              "       [0.25590482],\n",
              "       [0.25522855],\n",
              "       [0.24761428],\n",
              "       [0.25635567],\n",
              "       [0.26659987],\n",
              "       [0.26654978],\n",
              "       [0.26882905],\n",
              "       [0.27516594],\n",
              "       [0.29242329],\n",
              "       [0.29117095],\n",
              "       [0.28030056],\n",
              "       [0.28318096],\n",
              "       [0.28518472],\n",
              "       [0.29036944],\n",
              "       [0.28583594],\n",
              "       [0.27774577],\n",
              "       [0.28022542],\n",
              "       [0.27762054],\n",
              "       [0.28601127],\n",
              "       [0.28315592],\n",
              "       [0.28047589],\n",
              "       [0.29337508],\n",
              "       [0.29492799],\n",
              "       [0.28082655],\n",
              "       [0.28548528],\n",
              "       [0.30098936],\n",
              "       [0.30111459],\n",
              "       [0.2944521 ],\n",
              "       [0.30103945],\n",
              "       [0.30870382],\n",
              "       [0.32403256],\n",
              "       [0.32318096],\n",
              "       [0.32180338],\n",
              "       [0.31942392],\n",
              "       [0.32170319],\n",
              "       [0.3245335 ],\n",
              "       [0.33480276],\n",
              "       [0.33342517],\n",
              "       [0.34149029],\n",
              "       [0.34249217],\n",
              "       [0.35000626],\n",
              "       [0.35619286],\n",
              "       [0.34176581],\n",
              "       [0.34169067],\n",
              "       [0.3554665 ],\n",
              "       [0.37314966],\n",
              "       [0.37735755],\n",
              "       [0.37643081],\n",
              "       [0.37670632],\n",
              "       [0.38219161],\n",
              "       [0.38396994],\n",
              "       [0.38912962],\n",
              "       [0.38852849],\n",
              "       [0.39481528],\n",
              "       [0.39023168],\n",
              "       [0.39804634],\n",
              "       [0.40140263],\n",
              "       [0.39937383],\n",
              "       [0.39160927],\n",
              "       [0.38865373],\n",
              "       [0.38807765],\n",
              "       [0.3995742 ],\n",
              "       [0.39436443],\n",
              "       [0.40325611],\n",
              "       [0.40177833],\n",
              "       [0.39403882],\n",
              "       [0.3822417 ],\n",
              "       [0.38797746],\n",
              "       [0.39759549],\n",
              "       [0.41044458],\n",
              "       [0.40095178],\n",
              "       [0.40485911],\n",
              "       [0.41059487],\n",
              "       [0.41232311],\n",
              "       [0.42156544],\n",
              "       [0.43336255],\n",
              "       [0.43474014],\n",
              "       [0.43306199],\n",
              "       [0.43376331],\n",
              "       [0.43231058],\n",
              "       [0.443732  ],\n",
              "       [0.44440827],\n",
              "       [0.45853475],\n",
              "       [0.45825924],\n",
              "       [0.46256731],\n",
              "       [0.46790232],\n",
              "       [0.48468378],\n",
              "       [0.47737007],\n",
              "       [0.4833062 ],\n",
              "       [0.47977458],\n",
              "       [0.49179712],\n",
              "       [0.50792736],\n",
              "       [0.50968065],\n",
              "       [0.52628679],\n",
              "       [0.51556669],\n",
              "       [0.51221039],\n",
              "       [0.52197871],\n",
              "       [0.5307201 ],\n",
              "       [0.52530996],\n",
              "       [0.52814026],\n",
              "       [0.53197245],\n",
              "       [0.52966813],\n",
              "       [0.50622417],\n",
              "       [0.52811522],\n",
              "       [0.54477145],\n",
              "       [0.54359424],\n",
              "       [0.5076268 ],\n",
              "       [0.50549781],\n",
              "       [0.53102066],\n",
              "       [0.53753287],\n",
              "       [0.54695053],\n",
              "       [0.53397621],\n",
              "       [0.53778334],\n",
              "       [0.53292423],\n",
              "       [0.55193488],\n",
              "       [0.54609894],\n",
              "       [0.54629931],\n",
              "       [0.53139637],\n",
              "       [0.54296807],\n",
              "       [0.53465247],\n",
              "       [0.51649343],\n",
              "       [0.47924859],\n",
              "       [0.45395116],\n",
              "       [0.46539762],\n",
              "       [0.41748278],\n",
              "       [0.41708203],\n",
              "       [0.48082655],\n",
              "       [0.45705698],\n",
              "       [0.49067001],\n",
              "       [0.46607389],\n",
              "       [0.45633062],\n",
              "       [0.39907326],\n",
              "       [0.44708829],\n",
              "       [0.42226675],\n",
              "       [0.35413901],\n",
              "       [0.42862868],\n",
              "       [0.33906074],\n",
              "       [0.36573575],\n",
              "       [0.35023168],\n",
              "       [0.34549781],\n",
              "       [0.30657483],\n",
              "       [0.29437696],\n",
              "       [0.35075767],\n",
              "       [0.34735128],\n",
              "       [0.37971196],\n",
              "       [0.35291171],\n",
              "       [0.37061991],\n",
              "       [0.36931747],\n",
              "       [0.33580463],\n",
              "       [0.34587351],\n",
              "       [0.33705698],\n",
              "       [0.38980589],\n",
              "       [0.38219161],\n",
              "       [0.39882279],\n",
              "       [0.40363181],\n",
              "       [0.41680651],\n",
              "       [0.45137132],\n",
              "       [0.44480902],\n",
              "       [0.45046963],\n",
              "       [0.44072636],\n",
              "       [0.42602379],\n",
              "       [0.40458359],\n",
              "       [0.4239449 ],\n",
              "       [0.42126487],\n",
              "       [0.44115216],\n",
              "       [0.4416531 ],\n",
              "       [0.43015654],\n",
              "       [0.45307451],\n",
              "       [0.46827802],\n",
              "       [0.45643081],\n",
              "       [0.46667502],\n",
              "       [0.47769568],\n",
              "       [0.4853851 ],\n",
              "       [0.4931747 ],\n",
              "       [0.50917971],\n",
              "       [0.52140263],\n",
              "       [0.51238572],\n",
              "       [0.50296807],\n",
              "       [0.50770194],\n",
              "       [0.50311835],\n",
              "       [0.5212774 ],\n",
              "       [0.51671885],\n",
              "       [0.53197245],\n",
              "       [0.52601127],\n",
              "       [0.53112085],\n",
              "       [0.52571071],\n",
              "       [0.52916719],\n",
              "       [0.52951785],\n",
              "       [0.52874139],\n",
              "       [0.53853475],\n",
              "       [0.54226675],\n",
              "       [0.54672511],\n",
              "       [0.53971196],\n",
              "       [0.56270507],\n",
              "       [0.56761428],\n",
              "       [0.59398873],\n",
              "       [0.61615529],\n",
              "       [0.57372574],\n",
              "       [0.58098936],\n",
              "       [0.59148403],\n",
              "       [0.61425172],\n",
              "       [0.61302442],\n",
              "       [0.61337508],\n",
              "       [0.60834064],\n",
              "       [0.63125861],\n",
              "       [0.65044458],\n",
              "       [0.6342392 ],\n",
              "       [0.64621165],\n",
              "       [0.618134  ],\n",
              "       [0.63854728],\n",
              "       [0.64611146],\n",
              "       [0.64438322],\n",
              "       [0.64438322],\n",
              "       [0.66877896],\n",
              "       [0.66587351],\n",
              "       [0.68761428],\n",
              "       [0.69172198],\n",
              "       [0.69340013],\n",
              "       [0.68896681],\n",
              "       [0.70479649],\n",
              "       [0.71148403],\n",
              "       [0.69943644],\n",
              "       [0.69748278],\n",
              "       [0.71782091],\n",
              "       [0.70422041],\n",
              "       [0.70695053],\n",
              "       [0.66259236],\n",
              "       [0.66028804],\n",
              "       [0.68227927],\n",
              "       [0.66667502],\n",
              "       [0.68458359],\n",
              "       [0.6961052 ],\n",
              "       [0.79699436],\n",
              "       [0.82381966],\n",
              "       [0.83110833],\n",
              "       [0.8350908 ],\n",
              "       [0.87356293],\n",
              "       [0.84561052],\n",
              "       [0.86179086],\n",
              "       [0.82820288],\n",
              "       [0.86462116],\n",
              "       [0.88465874],\n",
              "       [0.88363181],\n",
              "       [0.88062617],\n",
              "       [0.89019411],\n",
              "       [0.89164684],\n",
              "       [0.91737007],\n",
              "       [0.97843456],\n",
              "       [0.99333751]])"
            ]
          },
          "metadata": {},
          "execution_count": 192
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_data"
      ],
      "metadata": {
        "id": "vD6SdiCwCPKQ",
        "outputId": "11f55f90-d5b0-4b1f-b7d7-9f3461ef541c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[9.82993112e-01],\n",
              "       [1.00000000e+00],\n",
              "       [9.84846587e-01],\n",
              "       [9.82817783e-01],\n",
              "       [5.56042580e-02],\n",
              "       [6.84783970e-02],\n",
              "       [6.15153413e-02],\n",
              "       [3.51659361e-02],\n",
              "       [3.53663118e-02],\n",
              "       [1.49780839e-02],\n",
              "       [2.62492173e-02],\n",
              "       [1.66562304e-02],\n",
              "       [1.29242329e-02],\n",
              "       [2.13274890e-02],\n",
              "       [2.17908579e-02],\n",
              "       [1.32498435e-02],\n",
              "       [8.76643707e-03],\n",
              "       [0.00000000e+00],\n",
              "       [8.11521603e-03],\n",
              "       [1.24483406e-02],\n",
              "       [7.01314966e-04],\n",
              "       [3.45648090e-03],\n",
              "       [1.36255479e-02],\n",
              "       [2.03381340e-02],\n",
              "       [1.81590482e-02],\n",
              "       [2.24671259e-02],\n",
              "       [2.49217282e-02],\n",
              "       [1.54790232e-02],\n",
              "       [2.41953663e-02],\n",
              "       [1.58296807e-02],\n",
              "       [2.06386976e-02],\n",
              "       [2.03631810e-02],\n",
              "       [2.53725736e-02],\n",
              "       [4.39824671e-02],\n",
              "       [3.57169693e-02],\n",
              "       [3.59423920e-02],\n",
              "       [3.47401378e-02],\n",
              "       [3.05072010e-02],\n",
              "       [2.28929242e-02],\n",
              "       [2.67251096e-02],\n",
              "       [2.51221039e-02],\n",
              "       [2.23168441e-02],\n",
              "       [2.05385097e-02],\n",
              "       [2.05635567e-02],\n",
              "       [2.44458359e-02],\n",
              "       [1.09204759e-02],\n",
              "       [2.12398247e-02],\n",
              "       [5.05948654e-03],\n",
              "       [4.83406387e-03],\n",
              "       [9.01690670e-03],\n",
              "       [2.03130870e-02],\n",
              "       [3.05322480e-02],\n",
              "       [2.96806512e-02],\n",
              "       [2.37445210e-02],\n",
              "       [2.28678773e-02],\n",
              "       [3.16844083e-02],\n",
              "       [3.09830933e-02],\n",
              "       [3.11083281e-02],\n",
              "       [3.37132123e-02],\n",
              "       [3.14339386e-02],\n",
              "       [2.80275517e-02],\n",
              "       [2.95554164e-02],\n",
              "       [2.62993112e-02],\n",
              "       [1.75579211e-02],\n",
              "       [2.08641202e-02],\n",
              "       [2.30181590e-02],\n",
              "       [2.44207890e-02],\n",
              "       [3.05823419e-02],\n",
              "       [3.97745773e-02],\n",
              "       [4.06762680e-02],\n",
              "       [4.03256105e-02],\n",
              "       [3.85973701e-02],\n",
              "       [4.23544145e-02],\n",
              "       [4.39323732e-02],\n",
              "       [3.74201628e-02],\n",
              "       [4.10770194e-02],\n",
              "       [3.89981215e-02],\n",
              "       [3.74201628e-02],\n",
              "       [5.26988103e-02],\n",
              "       [5.25234815e-02],\n",
              "       [5.47526612e-02],\n",
              "       [4.96305573e-02],\n",
              "       [5.35754540e-02],\n",
              "       [6.27175955e-02],\n",
              "       [6.04132749e-02],\n",
              "       [6.29430182e-02],\n",
              "       [7.47651847e-02],\n",
              "       [7.02066374e-02],\n",
              "       [6.73262367e-02],\n",
              "       [6.47463995e-02],\n",
              "       [5.65309956e-02],\n",
              "       [6.05385097e-02],\n",
              "       [4.94927990e-02],\n",
              "       [6.03130870e-02],\n",
              "       [6.31433939e-02],\n",
              "       [5.54539762e-02],\n",
              "       [5.50031309e-02],\n",
              "       [6.02379461e-02],\n",
              "       [5.52786475e-02],\n",
              "       [5.08453350e-02],\n",
              "       [5.25735755e-02],\n",
              "       [6.30932999e-02],\n",
              "       [7.52160301e-02],\n",
              "       [8.07263619e-02],\n",
              "       [9.03694427e-02],\n",
              "       [9.09705698e-02],\n",
              "       [8.82154039e-02],\n",
              "       [7.57670632e-02],\n",
              "       [6.29179712e-02],\n",
              "       [6.83782091e-02],\n",
              "       [7.05072010e-02],\n",
              "       [6.78772699e-02],\n",
              "       [7.65184721e-02],\n",
              "       [7.49405135e-02],\n",
              "       [7.53162179e-02],\n",
              "       [7.30619912e-02],\n",
              "       [7.15090795e-02],\n",
              "       [7.08578585e-02],\n",
              "       [7.14589856e-02],\n",
              "       [6.59987477e-02],\n",
              "       [6.01127113e-02],\n",
              "       [5.72824045e-02],\n",
              "       [5.76831559e-02],\n",
              "       [4.79899812e-02],\n",
              "       [4.76393237e-02],\n",
              "       [4.63619286e-02],\n",
              "       [3.54414527e-02],\n",
              "       [3.61177207e-02],\n",
              "       [5.24733876e-02],\n",
              "       [4.57858485e-02],\n",
              "       [3.81214778e-02],\n",
              "       [3.32874139e-02],\n",
              "       [3.65184721e-02],\n",
              "       [2.38447088e-02],\n",
              "       [3.56793989e-02],\n",
              "       [3.29117095e-02],\n",
              "       [3.78710081e-02],\n",
              "       [3.55416406e-02],\n",
              "       [4.29555416e-02],\n",
              "       [4.69129618e-02],\n",
              "       [4.48841578e-02],\n",
              "       [3.42892924e-02],\n",
              "       [3.29367564e-02],\n",
              "       [4.14527239e-02],\n",
              "       [3.93237320e-02],\n",
              "       [3.31872260e-02],\n",
              "       [3.44395742e-02],\n",
              "       [3.59924859e-02],\n",
              "       [3.64433312e-02],\n",
              "       [3.27113338e-02],\n",
              "       [3.83469004e-02],\n",
              "       [4.04758923e-02],\n",
              "       [4.77395116e-02],\n",
              "       [4.85159674e-02],\n",
              "       [5.27489042e-02],\n",
              "       [5.89104571e-02],\n",
              "       [6.55103319e-02],\n",
              "       [6.11145899e-02],\n",
              "       [6.91045711e-02],\n",
              "       [6.30932999e-02],\n",
              "       [6.92798998e-02],\n",
              "       [6.84283031e-02],\n",
              "       [7.01314966e-02],\n",
              "       [6.57983719e-02],\n",
              "       [6.67752035e-02],\n",
              "       [6.28678773e-02],\n",
              "       [6.88290545e-02],\n",
              "       [6.98309330e-02],\n",
              "       [6.90043832e-02],\n",
              "       [6.69755792e-02],\n",
              "       [6.67251096e-02],\n",
              "       [6.16656230e-02],\n",
              "       [6.43706951e-02],\n",
              "       [5.26236694e-02],\n",
              "       [5.32498435e-02],\n",
              "       [5.73575454e-02],\n",
              "       [5.85347527e-02],\n",
              "       [5.01189731e-02],\n",
              "       [4.77645585e-02],\n",
              "       [3.98998121e-02],\n",
              "       [4.54101440e-02],\n",
              "       [5.16217909e-02],\n",
              "       [4.86662492e-02],\n",
              "       [4.51095805e-02],\n",
              "       [4.47088291e-02],\n",
              "       [5.12711334e-02],\n",
              "       [4.65623043e-02],\n",
              "       [5.07451472e-02],\n",
              "       [5.02442079e-02],\n",
              "       [5.01189731e-02],\n",
              "       [4.61865999e-02],\n",
              "       [4.45084534e-02],\n",
              "       [4.36819036e-02],\n",
              "       [4.56355667e-02],\n",
              "       [4.18284283e-02],\n",
              "       [4.77144646e-02],\n",
              "       [4.77395116e-02],\n",
              "       [4.98434565e-02],\n",
              "       [5.08202880e-02],\n",
              "       [4.82654978e-02],\n",
              "       [5.13713212e-02],\n",
              "       [5.92110207e-02],\n",
              "       [5.71070758e-02],\n",
              "       [5.83844709e-02],\n",
              "       [6.24921728e-02],\n",
              "       [5.91609267e-02],\n",
              "       [6.37695679e-02],\n",
              "       [6.79774577e-02],\n",
              "       [6.72761428e-02],\n",
              "       [6.65497808e-02],\n",
              "       [6.57983719e-02],\n",
              "       [6.99812148e-02],\n",
              "       [7.38634941e-02],\n",
              "       [7.54414527e-02],\n",
              "       [7.62179086e-02],\n",
              "       [8.29555416e-02],\n",
              "       [8.81152160e-02],\n",
              "       [9.45021916e-02],\n",
              "       [9.11709455e-02],\n",
              "       [9.58547276e-02],\n",
              "       [9.43268629e-02],\n",
              "       [9.71822167e-02],\n",
              "       [1.05973701e-01],\n",
              "       [1.04295554e-01],\n",
              "       [9.90607389e-02],\n",
              "       [8.91922354e-02],\n",
              "       [9.84596118e-02],\n",
              "       [9.65810895e-02],\n",
              "       [1.00087664e-01],\n",
              "       [1.04495930e-01],\n",
              "       [1.05572949e-01],\n",
              "       [1.00012523e-01],\n",
              "       [9.55291171e-02],\n",
              "       [9.71822167e-02],\n",
              "       [9.77332498e-02],\n",
              "       [9.68816531e-02],\n",
              "       [1.01490294e-01],\n",
              "       [1.00463369e-01],\n",
              "       [1.00738885e-01],\n",
              "       [9.84345648e-02],\n",
              "       [9.83093300e-02],\n",
              "       [9.70820288e-02],\n",
              "       [9.77332498e-02],\n",
              "       [1.05322480e-01],\n",
              "       [1.05848466e-01],\n",
              "       [1.10907952e-01],\n",
              "       [1.08578585e-01],\n",
              "       [9.89855980e-02],\n",
              "       [9.98371947e-02],\n",
              "       [1.03569192e-01],\n",
              "       [1.07376331e-01],\n",
              "       [1.07150908e-01],\n",
              "       [1.03994991e-01],\n",
              "       [1.01941140e-01],\n",
              "       [1.04596118e-01],\n",
              "       [1.15917345e-01],\n",
              "       [1.12686287e-01],\n",
              "       [1.14389480e-01],\n",
              "       [1.17244834e-01],\n",
              "       [1.18872887e-01],\n",
              "       [1.24859111e-01],\n",
              "       [1.20901691e-01],\n",
              "       [1.18296807e-01],\n",
              "       [1.05522855e-01],\n",
              "       [1.06975579e-01],\n",
              "       [1.03393863e-01],\n",
              "       [1.05673137e-01],\n",
              "       [1.05072010e-01],\n",
              "       [9.82341891e-02],\n",
              "       [9.04195366e-02],\n",
              "       [9.16468378e-02],\n",
              "       [9.77082029e-02],\n",
              "       [1.00162805e-01],\n",
              "       [1.00388228e-01],\n",
              "       [9.65059487e-02],\n",
              "       [8.78396994e-02],\n",
              "       [9.01440200e-02],\n",
              "       [8.68127740e-02],\n",
              "       [8.96931747e-02],\n",
              "       [8.09016907e-02],\n",
              "       [8.58359424e-02],\n",
              "       [8.80651221e-02],\n",
              "       [9.12961803e-02],\n",
              "       [9.03193488e-02],\n",
              "       [9.00939261e-02],\n",
              "       [8.68378209e-02],\n",
              "       [8.53350031e-02],\n",
              "       [9.24733876e-02],\n",
              "       [9.51784596e-02],\n",
              "       [9.94614903e-02],\n",
              "       [1.04996869e-01],\n",
              "       [1.06249217e-01],\n",
              "       [1.06800250e-01],\n",
              "       [1.04821540e-01],\n",
              "       [1.04696306e-01],\n",
              "       [1.06399499e-01],\n",
              "       [1.05222292e-01],\n",
              "       [1.14539762e-01],\n",
              "       [1.07601753e-01],\n",
              "       [1.05497808e-01],\n",
              "       [1.08152786e-01],\n",
              "       [1.11834690e-01],\n",
              "       [1.10507201e-01],\n",
              "       [1.11308704e-01],\n",
              "       [1.09204759e-01],\n",
              "       [1.10131497e-01],\n",
              "       [1.02892924e-01],\n",
              "       [1.02767689e-01],\n",
              "       [1.08077646e-01],\n",
              "       [1.08102693e-01],\n",
              "       [1.10607389e-01],\n",
              "       [1.16844083e-01],\n",
              "       [1.27814652e-01],\n",
              "       [1.34527239e-01],\n",
              "       [1.35704446e-01],\n",
              "       [1.36681277e-01],\n",
              "       [1.38008766e-01],\n",
              "       [1.25159674e-01],\n",
              "       [1.33750783e-01],\n",
              "       [1.46424546e-01],\n",
              "       [1.45097057e-01],\n",
              "       [1.42567314e-01],\n",
              "       [1.37758297e-01],\n",
              "       [1.46474640e-01],\n",
              "       [1.61152160e-01],\n",
              "       [1.70920476e-01],\n",
              "       [1.69618034e-01],\n",
              "       [1.81865999e-01],\n",
              "       [1.72573575e-01],\n",
              "       [1.69041954e-01],\n",
              "       [1.81490294e-01],\n",
              "       [1.63857232e-01],\n",
              "       [1.61051972e-01],\n",
              "       [1.57570445e-01],\n",
              "       [1.65685661e-01],\n",
              "       [1.72323106e-01],\n",
              "       [1.73926111e-01],\n",
              "       [1.84070131e-01],\n",
              "       [1.81465247e-01],\n",
              "       [1.81690670e-01],\n",
              "       [1.78735128e-01],\n",
              "       [1.77157170e-01],\n",
              "       [1.88278021e-01],\n",
              "       [1.82492173e-01],\n",
              "       [1.70519724e-01],\n",
              "       [1.63206011e-01],\n",
              "       [1.63631810e-01],\n",
              "       [1.63681904e-01],\n",
              "       [1.70920476e-01],\n",
              "       [1.72047589e-01],\n",
              "       [1.63681904e-01],\n",
              "       [1.65886036e-01],\n",
              "       [1.57695679e-01],\n",
              "       [1.48753914e-01],\n",
              "       [1.44445836e-01],\n",
              "       [1.39185974e-01],\n",
              "       [1.37207264e-01],\n",
              "       [1.32598622e-01],\n",
              "       [1.32373200e-01],\n",
              "       [1.31195992e-01],\n",
              "       [1.59023168e-01],\n",
              "       [1.70169067e-01],\n",
              "       [1.69743269e-01],\n",
              "       [1.72824045e-01],\n",
              "       [1.65460238e-01],\n",
              "       [1.64182843e-01],\n",
              "       [1.62354415e-01],\n",
              "       [1.70294302e-01],\n",
              "       [1.73926111e-01],\n",
              "       [1.63506575e-01],\n",
              "       [1.54790232e-01],\n",
              "       [1.55391359e-01],\n",
              "       [1.65184721e-01],\n",
              "       [1.64583594e-01],\n",
              "       [1.55391359e-01],\n",
              "       [1.51433939e-01],\n",
              "       [1.43969944e-01],\n",
              "       [1.33324984e-01]])"
            ]
          },
          "metadata": {},
          "execution_count": 193
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "timespan = 5\n",
        "timespan = int(input('Enter time span in days: '))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ifCNFkfXObBr",
        "outputId": "8e8fea72-f177-4fd4-be15-e06c3d1608d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Enter time span in days: 100\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def create_dataset (dataset, span=timespan):\n",
        "    x,y= [], []\n",
        "    for i in range (len (dataset)-span-1):\n",
        "        a = dataset[i: (i+span), 0] ###=0, 0,1,2,3---1-99 |\n",
        "        x.append(a)\n",
        "        y.append(dataset[i+ span, 0])\n",
        "    return np.array(x), np.array(y)"
      ],
      "metadata": {
        "id": "8neQmISfOEoC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, y_train = create_dataset (train_data, timespan)\n",
        "x_test, y_test= create_dataset (test_data, timespan)"
      ],
      "metadata": {
        "id": "gGqCdqP7PVq9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train = x_train.reshape(x_train.shape[0],x_train.shape[1], 1) \n",
        "x_test = x_test.reshape(x_test.shape[0],x_test.shape[1], 1)"
      ],
      "metadata": {
        "id": "9FWNfl7gN11e"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model=Sequential()\n",
        "model.add(LSTM(50, return_sequences=True, input_shape=(timespan,1)))\n",
        "model.add (LSTM(50, return_sequences=True))\n",
        "model.add(LSTM(50))\n",
        "model.add (Dense(1))\n",
        "model.compile(loss='mean_squared_error', optimizer='adam')"
      ],
      "metadata": {
        "id": "Ph6__tMPP-S4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(x_train,y_train,validation_data=(x_test,y_test), epochs=100, batch_size=64, verbose=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TaqynJTzR6EN",
        "outputId": "af6a9b82-d08a-4fc0-dbdf-fb0e08218ea9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "13/13 [==============================] - 9s 288ms/step - loss: 0.0263 - val_loss: 0.0017\n",
            "Epoch 2/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 0.0056 - val_loss: 0.0015\n",
            "Epoch 3/100\n",
            "13/13 [==============================] - 2s 176ms/step - loss: 0.0017 - val_loss: 3.0024e-04\n",
            "Epoch 4/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 0.0015 - val_loss: 3.4431e-04\n",
            "Epoch 5/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 0.0015 - val_loss: 3.4595e-04\n",
            "Epoch 6/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 0.0014 - val_loss: 2.6911e-04\n",
            "Epoch 7/100\n",
            "13/13 [==============================] - 2s 177ms/step - loss: 0.0011 - val_loss: 2.6297e-04\n",
            "Epoch 8/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 0.0010 - val_loss: 3.0069e-04\n",
            "Epoch 9/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 0.0012 - val_loss: 3.6005e-04\n",
            "Epoch 10/100\n",
            "13/13 [==============================] - 2s 187ms/step - loss: 0.0010 - val_loss: 4.5093e-04\n",
            "Epoch 11/100\n",
            "13/13 [==============================] - 2s 177ms/step - loss: 9.2792e-04 - val_loss: 3.1615e-04\n",
            "Epoch 12/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 9.7839e-04 - val_loss: 3.0734e-04\n",
            "Epoch 13/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 8.6432e-04 - val_loss: 3.2337e-04\n",
            "Epoch 14/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 8.0043e-04 - val_loss: 4.7747e-04\n",
            "Epoch 15/100\n",
            "13/13 [==============================] - 2s 177ms/step - loss: 9.0775e-04 - val_loss: 2.5688e-04\n",
            "Epoch 16/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 8.0268e-04 - val_loss: 3.2163e-04\n",
            "Epoch 17/100\n",
            "13/13 [==============================] - 2s 177ms/step - loss: 7.8015e-04 - val_loss: 2.4937e-04\n",
            "Epoch 18/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 7.5663e-04 - val_loss: 4.1204e-04\n",
            "Epoch 19/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 7.5948e-04 - val_loss: 2.2062e-04\n",
            "Epoch 20/100\n",
            "13/13 [==============================] - 2s 186ms/step - loss: 8.3271e-04 - val_loss: 4.2157e-04\n",
            "Epoch 21/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 7.4498e-04 - val_loss: 2.0098e-04\n",
            "Epoch 22/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 8.5661e-04 - val_loss: 6.6148e-04\n",
            "Epoch 23/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 8.3190e-04 - val_loss: 1.9716e-04\n",
            "Epoch 24/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 7.0397e-04 - val_loss: 2.8503e-04\n",
            "Epoch 25/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 6.3097e-04 - val_loss: 2.2275e-04\n",
            "Epoch 26/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 6.5311e-04 - val_loss: 2.0342e-04\n",
            "Epoch 27/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 6.2755e-04 - val_loss: 2.1287e-04\n",
            "Epoch 28/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 6.7782e-04 - val_loss: 2.4950e-04\n",
            "Epoch 29/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 6.1650e-04 - val_loss: 2.7772e-04\n",
            "Epoch 30/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 6.8972e-04 - val_loss: 1.9002e-04\n",
            "Epoch 31/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 6.8657e-04 - val_loss: 3.2399e-04\n",
            "Epoch 32/100\n",
            "13/13 [==============================] - 2s 177ms/step - loss: 7.0691e-04 - val_loss: 2.8428e-04\n",
            "Epoch 33/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 6.7760e-04 - val_loss: 1.6908e-04\n",
            "Epoch 34/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 6.2930e-04 - val_loss: 1.9753e-04\n",
            "Epoch 35/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 6.2212e-04 - val_loss: 2.0244e-04\n",
            "Epoch 36/100\n",
            "13/13 [==============================] - 3s 220ms/step - loss: 5.6319e-04 - val_loss: 2.3017e-04\n",
            "Epoch 37/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 6.1339e-04 - val_loss: 2.1318e-04\n",
            "Epoch 38/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 5.5967e-04 - val_loss: 2.0358e-04\n",
            "Epoch 39/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 5.5522e-04 - val_loss: 1.8516e-04\n",
            "Epoch 40/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 5.4784e-04 - val_loss: 2.1315e-04\n",
            "Epoch 41/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 6.2438e-04 - val_loss: 1.7356e-04\n",
            "Epoch 42/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 5.9827e-04 - val_loss: 1.7700e-04\n",
            "Epoch 43/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 5.6442e-04 - val_loss: 2.1838e-04\n",
            "Epoch 44/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.7419e-04 - val_loss: 1.5636e-04\n",
            "Epoch 45/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 5.7325e-04 - val_loss: 2.7766e-04\n",
            "Epoch 46/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.7304e-04 - val_loss: 2.7476e-04\n",
            "Epoch 47/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 9.3454e-04 - val_loss: 1.7226e-04\n",
            "Epoch 48/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 6.5942e-04 - val_loss: 1.5375e-04\n",
            "Epoch 49/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.7746e-04 - val_loss: 1.9510e-04\n",
            "Epoch 50/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 5.2883e-04 - val_loss: 1.5461e-04\n",
            "Epoch 51/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.1959e-04 - val_loss: 2.2009e-04\n",
            "Epoch 52/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 5.1999e-04 - val_loss: 1.5873e-04\n",
            "Epoch 53/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 5.6453e-04 - val_loss: 1.7349e-04\n",
            "Epoch 54/100\n",
            "13/13 [==============================] - 2s 186ms/step - loss: 5.1500e-04 - val_loss: 1.7229e-04\n",
            "Epoch 55/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.1958e-04 - val_loss: 1.5625e-04\n",
            "Epoch 56/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.9598e-04 - val_loss: 1.7850e-04\n",
            "Epoch 57/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 5.0477e-04 - val_loss: 1.6631e-04\n",
            "Epoch 58/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 5.2231e-04 - val_loss: 2.1383e-04\n",
            "Epoch 59/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.9710e-04 - val_loss: 1.4123e-04\n",
            "Epoch 60/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 5.1642e-04 - val_loss: 2.5038e-04\n",
            "Epoch 61/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 4.9651e-04 - val_loss: 1.5619e-04\n",
            "Epoch 62/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 4.7956e-04 - val_loss: 1.9953e-04\n",
            "Epoch 63/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.9157e-04 - val_loss: 1.3961e-04\n",
            "Epoch 64/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 5.3077e-04 - val_loss: 1.8633e-04\n",
            "Epoch 65/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 5.0478e-04 - val_loss: 1.3437e-04\n",
            "Epoch 66/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 4.5428e-04 - val_loss: 1.8136e-04\n",
            "Epoch 67/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 4.5587e-04 - val_loss: 1.3687e-04\n",
            "Epoch 68/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.0593e-04 - val_loss: 1.5648e-04\n",
            "Epoch 69/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.6619e-04 - val_loss: 1.4763e-04\n",
            "Epoch 70/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 4.4457e-04 - val_loss: 1.6059e-04\n",
            "Epoch 71/100\n",
            "13/13 [==============================] - 2s 186ms/step - loss: 4.3343e-04 - val_loss: 1.3116e-04\n",
            "Epoch 72/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 4.7365e-04 - val_loss: 2.5975e-04\n",
            "Epoch 73/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 4.6531e-04 - val_loss: 1.3264e-04\n",
            "Epoch 74/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.7921e-04 - val_loss: 1.5439e-04\n",
            "Epoch 75/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 5.0688e-04 - val_loss: 1.2925e-04\n",
            "Epoch 76/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 4.4559e-04 - val_loss: 1.3566e-04\n",
            "Epoch 77/100\n",
            "13/13 [==============================] - 2s 184ms/step - loss: 4.4701e-04 - val_loss: 1.2970e-04\n",
            "Epoch 78/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 4.1580e-04 - val_loss: 1.4230e-04\n",
            "Epoch 79/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 3.8687e-04 - val_loss: 1.5106e-04\n",
            "Epoch 80/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 3.8297e-04 - val_loss: 1.8356e-04\n",
            "Epoch 81/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 3.9915e-04 - val_loss: 1.4061e-04\n",
            "Epoch 82/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 3.7189e-04 - val_loss: 1.2035e-04\n",
            "Epoch 83/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 4.4113e-04 - val_loss: 2.5561e-04\n",
            "Epoch 84/100\n",
            "13/13 [==============================] - 2s 183ms/step - loss: 4.3004e-04 - val_loss: 1.2908e-04\n",
            "Epoch 85/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 3.8196e-04 - val_loss: 1.1841e-04\n",
            "Epoch 86/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 4.4776e-04 - val_loss: 1.2407e-04\n",
            "Epoch 87/100\n",
            "13/13 [==============================] - 2s 178ms/step - loss: 4.3140e-04 - val_loss: 2.2213e-04\n",
            "Epoch 88/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 4.1276e-04 - val_loss: 1.1715e-04\n",
            "Epoch 89/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 4.2639e-04 - val_loss: 1.2201e-04\n",
            "Epoch 90/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 3.3620e-04 - val_loss: 1.2478e-04\n",
            "Epoch 91/100\n",
            "13/13 [==============================] - 2s 182ms/step - loss: 3.3027e-04 - val_loss: 1.3949e-04\n",
            "Epoch 92/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 3.3535e-04 - val_loss: 2.2500e-04\n",
            "Epoch 93/100\n",
            "13/13 [==============================] - 2s 179ms/step - loss: 4.2851e-04 - val_loss: 1.1159e-04\n",
            "Epoch 94/100\n",
            "13/13 [==============================] - 2s 188ms/step - loss: 3.2078e-04 - val_loss: 1.0704e-04\n",
            "Epoch 95/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 3.4217e-04 - val_loss: 1.9062e-04\n",
            "Epoch 96/100\n",
            "13/13 [==============================] - 2s 185ms/step - loss: 5.3413e-04 - val_loss: 1.0844e-04\n",
            "Epoch 97/100\n",
            "13/13 [==============================] - 2s 187ms/step - loss: 4.1706e-04 - val_loss: 1.3046e-04\n",
            "Epoch 98/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 3.2518e-04 - val_loss: 1.0554e-04\n",
            "Epoch 99/100\n",
            "13/13 [==============================] - 2s 181ms/step - loss: 3.0113e-04 - val_loss: 1.5734e-04\n",
            "Epoch 100/100\n",
            "13/13 [==============================] - 2s 180ms/step - loss: 2.9432e-04 - val_loss: 1.0401e-04\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f3e051db810>"
            ]
          },
          "metadata": {},
          "execution_count": 200
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_predict=model.predict(x_train) \n",
        "test_predict=model.predict(x_test)"
      ],
      "metadata": {
        "id": "GG4FGXaiSq2c"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_predict=scaler.inverse_transform(train_predict) \n",
        "test_predict=scaler.inverse_transform(test_predict)"
      ],
      "metadata": {
        "id": "jSvXi6KySwmH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_squared_error(y_train, train_predict,squared= False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gsOCVNEeS3Vt",
        "outputId": "e3ba0ef8-7720-467d-9701-2876b667b82c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "229.12005367598866"
            ]
          },
          "metadata": {},
          "execution_count": 203
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_squared_error(y_test, test_predict,squared  = False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K9mrNiMZTJXm",
        "outputId": "8ebd8673-49c9-4985-e236-ce3754b7a367"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "146.54060077964144"
            ]
          },
          "metadata": {},
          "execution_count": 204
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "l = len(test_data)"
      ],
      "metadata": {
        "id": "m4YLTDGsYAzM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_input=test_data[l - timespan:].reshape (1,-1)\n",
        "x_input.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "76jQ_IcPX5jD",
        "outputId": "2496747b-a71c-431e-e303-1189b054f761"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 100)"
            ]
          },
          "metadata": {},
          "execution_count": 206
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_input"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WCgmvE2WcnA4",
        "outputId": "4ea865c7-a51d-4117-eb6b-80efc78584f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.08969317, 0.08090169, 0.08583594, 0.08806512, 0.09129618,\n",
              "        0.09031935, 0.09009393, 0.08683782, 0.085335  , 0.09247339,\n",
              "        0.09517846, 0.09946149, 0.10499687, 0.10624922, 0.10680025,\n",
              "        0.10482154, 0.10469631, 0.1063995 , 0.10522229, 0.11453976,\n",
              "        0.10760175, 0.10549781, 0.10815279, 0.11183469, 0.1105072 ,\n",
              "        0.1113087 , 0.10920476, 0.1101315 , 0.10289292, 0.10276769,\n",
              "        0.10807765, 0.10810269, 0.11060739, 0.11684408, 0.12781465,\n",
              "        0.13452724, 0.13570445, 0.13668128, 0.13800877, 0.12515967,\n",
              "        0.13375078, 0.14642455, 0.14509706, 0.14256731, 0.1377583 ,\n",
              "        0.14647464, 0.16115216, 0.17092048, 0.16961803, 0.181866  ,\n",
              "        0.17257358, 0.16904195, 0.18149029, 0.16385723, 0.16105197,\n",
              "        0.15757044, 0.16568566, 0.17232311, 0.17392611, 0.18407013,\n",
              "        0.18146525, 0.18169067, 0.17873513, 0.17715717, 0.18827802,\n",
              "        0.18249217, 0.17051972, 0.16320601, 0.16363181, 0.1636819 ,\n",
              "        0.17092048, 0.17204759, 0.1636819 , 0.16588604, 0.15769568,\n",
              "        0.14875391, 0.14444584, 0.13918597, 0.13720726, 0.13259862,\n",
              "        0.1323732 , 0.13119599, 0.15902317, 0.17016907, 0.16974327,\n",
              "        0.17282405, 0.16546024, 0.16418284, 0.16235441, 0.1702943 ,\n",
              "        0.17392611, 0.16350657, 0.15479023, 0.15539136, 0.16518472,\n",
              "        0.16458359, 0.15539136, 0.15143394, 0.14396994, 0.13332498]])"
            ]
          },
          "metadata": {},
          "execution_count": 207
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "temp_input=list(x_input)\n",
        "temp_input=temp_input[0].tolist()"
      ],
      "metadata": {
        "id": "meHfHThMYW3b"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "temp_input"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SSA-F-w8byPF",
        "outputId": "e06cdf70-69f5-4fd2-f2d7-5c5a3d7343d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.08969317470256727,\n",
              " 0.08090169067000619,\n",
              " 0.08583594239198494,\n",
              " 0.08806512210394485,\n",
              " 0.09129618033813391,\n",
              " 0.09031934877896053,\n",
              " 0.09009392611145894,\n",
              " 0.0868378209142141,\n",
              " 0.08533500313087033,\n",
              " 0.09247338760175322,\n",
              " 0.09517845961177201,\n",
              " 0.09946149029430179,\n",
              " 0.10499686912961798,\n",
              " 0.10624921728240444,\n",
              " 0.10680025046963049,\n",
              " 0.10482154038822789,\n",
              " 0.10469630557294918,\n",
              " 0.10639949906073881,\n",
              " 0.10522229179711956,\n",
              " 0.11453976205385091,\n",
              " 0.10760175328741389,\n",
              " 0.10549780839073258,\n",
              " 0.10815278647463994,\n",
              " 0.11183469004383217,\n",
              " 0.1105072010018785,\n",
              " 0.11130870381966185,\n",
              " 0.10920475892298054,\n",
              " 0.11013149655604254,\n",
              " 0.10289292423293667,\n",
              " 0.10276768941765807,\n",
              " 0.10807764558547273,\n",
              " 0.10810269254852845,\n",
              " 0.11060738885410137,\n",
              " 0.11684408265497809,\n",
              " 0.12781465247338758,\n",
              " 0.13452723857232307,\n",
              " 0.13570444583594238,\n",
              " 0.13668127739511576,\n",
              " 0.13800876643706944,\n",
              " 0.12515967438948022,\n",
              " 0.1337507827175955,\n",
              " 0.14642454602379462,\n",
              " 0.14509705698184094,\n",
              " 0.14256731371321218,\n",
              " 0.1377582968065122,\n",
              " 0.146474639949906,\n",
              " 0.1611521603005635,\n",
              " 0.17092047589229803,\n",
              " 0.16961803381340007,\n",
              " 0.18186599874765175,\n",
              " 0.17257357545397617,\n",
              " 0.16904195366311836,\n",
              " 0.1814902943018159,\n",
              " 0.1638572323105823,\n",
              " 0.16105197244834057,\n",
              " 0.1575704445835942,\n",
              " 0.1656856606136506,\n",
              " 0.1723231058234188,\n",
              " 0.17392611145898557,\n",
              " 0.18407013149655604,\n",
              " 0.18146524733876013,\n",
              " 0.1816906700062617,\n",
              " 0.1787351283656856,\n",
              " 0.17715716969317463,\n",
              " 0.18827802128991855,\n",
              " 0.182492172824045,\n",
              " 0.1705197244834063,\n",
              " 0.16320601127113332,\n",
              " 0.16363180964308072,\n",
              " 0.1636819035691922,\n",
              " 0.17092047589229803,\n",
              " 0.17204758922980584,\n",
              " 0.1636819035691922,\n",
              " 0.1658860363180964,\n",
              " 0.15769567939887286,\n",
              " 0.1487539135879774,\n",
              " 0.1444458359423919,\n",
              " 0.13918597370068875,\n",
              " 0.13720726361928615,\n",
              " 0.1325986224170319,\n",
              " 0.13237319974953032,\n",
              " 0.13119599248591102,\n",
              " 0.15902316844082653,\n",
              " 0.17016906700062612,\n",
              " 0.16974326862867878,\n",
              " 0.17282404508453347,\n",
              " 0.165460237946149,\n",
              " 0.16418284283030676,\n",
              " 0.16235441452723853,\n",
              " 0.17029430181590482,\n",
              " 0.17392611145898557,\n",
              " 0.16350657482780212,\n",
              " 0.1547902316844082,\n",
              " 0.15539135879774574,\n",
              " 0.16518472135253592,\n",
              " 0.1645835942391985,\n",
              " 0.15539135879774574,\n",
              " 0.15143393863494048,\n",
              " 0.14396994364433308,\n",
              " 0.13332498434564805]"
            ]
          },
          "metadata": {},
          "execution_count": 209
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "output = []"
      ],
      "metadata": {
        "id": "W0aO-tdtQgDG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lst_output= []\n",
        "n_steps = timespan \n",
        "i=1\n",
        "while(i<=30):\n",
        "   if(len (temp_input) > timespan):\n",
        "       x_input=np.array(temp_input[1:])\n",
        "       print(\"{} day input {}\".format(i,x_input))\n",
        "       x_input=x_input.reshape(1,-1)\n",
        "       x_input = x_input.reshape((1, n_steps,1))\n",
        "       yhat = model.predict(x_input, verbose=0)\n",
        "       print(\"{} day output {}\".format(i,yhat))\n",
        "       temp_input.extend (yhat[0].tolist()) \n",
        "       temp_input=temp_input[1:] \n",
        "      # j = scaler.inverse_transform(yhat)\n",
        "      # print('Value',j)\n",
        "      # output.append(j)\n",
        " #print(temp_input)\n",
        "       lst_output.extend(yhat.tolist())\n",
        "       i+=1\n",
        "   else:\n",
        "       x_input = x_input.reshape((1, n_steps,1)) \n",
        "       yhat = model.predict(x_input, verbose=0) \n",
        "       print (yhat[0]) \n",
        "       temp_input.extend(yhat[0].tolist()) \n",
        "       print(len(temp_input)) \n",
        "       lst_output.extend(yhat.tolist())\n",
        "       i=i+1\n",
        "   #output.append(scaler.inverse_transform(yhat))\n",
        "\n",
        "print(lst_output)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "anMLxXZUZUZi",
        "outputId": "1536bfb4-c546-454e-962d-942afaee669e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.15337375]\n",
            "101\n",
            "2 day input [0.08090169 0.08583594 0.08806512 0.09129618 0.09031935 0.09009393\n",
            " 0.08683782 0.085335   0.09247339 0.09517846 0.09946149 0.10499687\n",
            " 0.10624922 0.10680025 0.10482154 0.10469631 0.1063995  0.10522229\n",
            " 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072\n",
            " 0.1113087  0.10920476 0.1101315  0.10289292 0.10276769 0.10807765\n",
            " 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445\n",
            " 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706\n",
            " 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803\n",
            " 0.181866   0.17257358 0.16904195 0.18149029 0.16385723 0.16105197\n",
            " 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525\n",
            " 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972\n",
            " 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819\n",
            " 0.16588604 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726\n",
            " 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327\n",
            " 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611\n",
            " 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136\n",
            " 0.15143394 0.14396994 0.13332498 0.15337375]\n",
            "2 day output [[0.150211]]\n",
            "3 day input [0.08583594 0.08806512 0.09129618 0.09031935 0.09009393 0.08683782\n",
            " 0.085335   0.09247339 0.09517846 0.09946149 0.10499687 0.10624922\n",
            " 0.10680025 0.10482154 0.10469631 0.1063995  0.10522229 0.11453976\n",
            " 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087\n",
            " 0.10920476 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269\n",
            " 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128\n",
            " 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731\n",
            " 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803 0.181866\n",
            " 0.17257358 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044\n",
            " 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067\n",
            " 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601\n",
            " 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604\n",
            " 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862\n",
            " 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327 0.17282405\n",
            " 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657\n",
            " 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394\n",
            " 0.14396994 0.13332498 0.15337375 0.15021101]\n",
            "3 day output [[0.1482955]]\n",
            "4 day input [0.08806512 0.09129618 0.09031935 0.09009393 0.08683782 0.085335\n",
            " 0.09247339 0.09517846 0.09946149 0.10499687 0.10624922 0.10680025\n",
            " 0.10482154 0.10469631 0.1063995  0.10522229 0.11453976 0.10760175\n",
            " 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476\n",
            " 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269 0.11060739\n",
            " 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877\n",
            " 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583\n",
            " 0.14647464 0.16115216 0.17092048 0.16961803 0.181866   0.17257358\n",
            " 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566\n",
            " 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513\n",
            " 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181\n",
            " 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604 0.15769568\n",
            " 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732\n",
            " 0.13119599 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024\n",
            " 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023\n",
            " 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994\n",
            " 0.13332498 0.15337375 0.15021101 0.14829551]\n",
            "4 day output [[0.14735933]]\n",
            "5 day input [0.09129618 0.09031935 0.09009393 0.08683782 0.085335   0.09247339\n",
            " 0.09517846 0.09946149 0.10499687 0.10624922 0.10680025 0.10482154\n",
            " 0.10469631 0.1063995  0.10522229 0.11453976 0.10760175 0.10549781\n",
            " 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315\n",
            " 0.10289292 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408\n",
            " 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967\n",
            " 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464\n",
            " 0.16115216 0.17092048 0.16961803 0.181866   0.17257358 0.16904195\n",
            " 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311\n",
            " 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717\n",
            " 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819\n",
            " 0.17092048 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391\n",
            " 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599\n",
            " 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284\n",
            " 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136\n",
            " 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498\n",
            " 0.15337375 0.15021101 0.14829551 0.14735933]\n",
            "5 day output [[0.14703415]]\n",
            "6 day input [0.09031935 0.09009393 0.08683782 0.085335   0.09247339 0.09517846\n",
            " 0.09946149 0.10499687 0.10624922 0.10680025 0.10482154 0.10469631\n",
            " 0.1063995  0.10522229 0.11453976 0.10760175 0.10549781 0.10815279\n",
            " 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292\n",
            " 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465\n",
            " 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078\n",
            " 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216\n",
            " 0.17092048 0.16961803 0.181866   0.17257358 0.16904195 0.18149029\n",
            " 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611\n",
            " 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802\n",
            " 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048\n",
            " 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584\n",
            " 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317\n",
            " 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441\n",
            " 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136 0.16518472\n",
            " 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375\n",
            " 0.15021101 0.14829551 0.14735933 0.14703415]\n",
            "6 day output [[0.14703013]]\n",
            "7 day input [0.09009393 0.08683782 0.085335   0.09247339 0.09517846 0.09946149\n",
            " 0.10499687 0.10624922 0.10680025 0.10482154 0.10469631 0.1063995\n",
            " 0.10522229 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469\n",
            " 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292 0.10276769\n",
            " 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724\n",
            " 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455\n",
            " 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048\n",
            " 0.16961803 0.181866   0.17257358 0.16904195 0.18149029 0.16385723\n",
            " 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013\n",
            " 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217\n",
            " 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759\n",
            " 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584 0.13918597\n",
            " 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907\n",
            " 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943\n",
            " 0.17392611 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359\n",
            " 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101\n",
            " 0.14829551 0.14735933 0.14703415 0.14703013]\n",
            "7 day output [[0.14716662]]\n",
            "8 day input [0.08683782 0.085335   0.09247339 0.09517846 0.09946149 0.10499687\n",
            " 0.10624922 0.10680025 0.10482154 0.10469631 0.1063995  0.10522229\n",
            " 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072\n",
            " 0.1113087  0.10920476 0.1101315  0.10289292 0.10276769 0.10807765\n",
            " 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445\n",
            " 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706\n",
            " 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803\n",
            " 0.181866   0.17257358 0.16904195 0.18149029 0.16385723 0.16105197\n",
            " 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525\n",
            " 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972\n",
            " 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819\n",
            " 0.16588604 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726\n",
            " 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327\n",
            " 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611\n",
            " 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136\n",
            " 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551\n",
            " 0.14735933 0.14703415 0.14703013 0.14716662]\n",
            "8 day output [[0.1473488]]\n",
            "9 day input [0.085335   0.09247339 0.09517846 0.09946149 0.10499687 0.10624922\n",
            " 0.10680025 0.10482154 0.10469631 0.1063995  0.10522229 0.11453976\n",
            " 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087\n",
            " 0.10920476 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269\n",
            " 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128\n",
            " 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731\n",
            " 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803 0.181866\n",
            " 0.17257358 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044\n",
            " 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067\n",
            " 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601\n",
            " 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604\n",
            " 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862\n",
            " 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327 0.17282405\n",
            " 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657\n",
            " 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394\n",
            " 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933\n",
            " 0.14703415 0.14703013 0.14716662 0.14734881]\n",
            "9 day output [[0.14753501]]\n",
            "10 day input [0.09247339 0.09517846 0.09946149 0.10499687 0.10624922 0.10680025\n",
            " 0.10482154 0.10469631 0.1063995  0.10522229 0.11453976 0.10760175\n",
            " 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476\n",
            " 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269 0.11060739\n",
            " 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877\n",
            " 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583\n",
            " 0.14647464 0.16115216 0.17092048 0.16961803 0.181866   0.17257358\n",
            " 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566\n",
            " 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513\n",
            " 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181\n",
            " 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604 0.15769568\n",
            " 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732\n",
            " 0.13119599 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024\n",
            " 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023\n",
            " 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994\n",
            " 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415\n",
            " 0.14703013 0.14716662 0.14734881 0.14753501]\n",
            "10 day output [[0.14771146]]\n",
            "11 day input [0.09517846 0.09946149 0.10499687 0.10624922 0.10680025 0.10482154\n",
            " 0.10469631 0.1063995  0.10522229 0.11453976 0.10760175 0.10549781\n",
            " 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315\n",
            " 0.10289292 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408\n",
            " 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967\n",
            " 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464\n",
            " 0.16115216 0.17092048 0.16961803 0.181866   0.17257358 0.16904195\n",
            " 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311\n",
            " 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717\n",
            " 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819\n",
            " 0.17092048 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391\n",
            " 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599\n",
            " 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284\n",
            " 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136\n",
            " 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498\n",
            " 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013\n",
            " 0.14716662 0.14734881 0.14753501 0.14771146]\n",
            "11 day output [[0.14787674]]\n",
            "12 day input [0.09946149 0.10499687 0.10624922 0.10680025 0.10482154 0.10469631\n",
            " 0.1063995  0.10522229 0.11453976 0.10760175 0.10549781 0.10815279\n",
            " 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292\n",
            " 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465\n",
            " 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078\n",
            " 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216\n",
            " 0.17092048 0.16961803 0.181866   0.17257358 0.16904195 0.18149029\n",
            " 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611\n",
            " 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802\n",
            " 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048\n",
            " 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584\n",
            " 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317\n",
            " 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441\n",
            " 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136 0.16518472\n",
            " 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375\n",
            " 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662\n",
            " 0.14734881 0.14753501 0.14771146 0.14787674]\n",
            "12 day output [[0.14803354]]\n",
            "13 day input [0.10499687 0.10624922 0.10680025 0.10482154 0.10469631 0.1063995\n",
            " 0.10522229 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469\n",
            " 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292 0.10276769\n",
            " 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724\n",
            " 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455\n",
            " 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048\n",
            " 0.16961803 0.181866   0.17257358 0.16904195 0.18149029 0.16385723\n",
            " 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013\n",
            " 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217\n",
            " 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759\n",
            " 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584 0.13918597\n",
            " 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907\n",
            " 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943\n",
            " 0.17392611 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359\n",
            " 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101\n",
            " 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881\n",
            " 0.14753501 0.14771146 0.14787674 0.14803354]\n",
            "13 day output [[0.14818566]]\n",
            "14 day input [0.10624922 0.10680025 0.10482154 0.10469631 0.1063995  0.10522229\n",
            " 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072\n",
            " 0.1113087  0.10920476 0.1101315  0.10289292 0.10276769 0.10807765\n",
            " 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445\n",
            " 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706\n",
            " 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803\n",
            " 0.181866   0.17257358 0.16904195 0.18149029 0.16385723 0.16105197\n",
            " 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525\n",
            " 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972\n",
            " 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819\n",
            " 0.16588604 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726\n",
            " 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327\n",
            " 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611\n",
            " 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136\n",
            " 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551\n",
            " 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501\n",
            " 0.14771146 0.14787674 0.14803354 0.14818566]\n",
            "14 day output [[0.14833643]]\n",
            "15 day input [0.10680025 0.10482154 0.10469631 0.1063995  0.10522229 0.11453976\n",
            " 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087\n",
            " 0.10920476 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269\n",
            " 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128\n",
            " 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731\n",
            " 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803 0.181866\n",
            " 0.17257358 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044\n",
            " 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067\n",
            " 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601\n",
            " 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604\n",
            " 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862\n",
            " 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327 0.17282405\n",
            " 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657\n",
            " 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394\n",
            " 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933\n",
            " 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146\n",
            " 0.14787674 0.14803354 0.14818566 0.14833643]\n",
            "15 day output [[0.14848875]]\n",
            "16 day input [0.10482154 0.10469631 0.1063995  0.10522229 0.11453976 0.10760175\n",
            " 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476\n",
            " 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269 0.11060739\n",
            " 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877\n",
            " 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583\n",
            " 0.14647464 0.16115216 0.17092048 0.16961803 0.181866   0.17257358\n",
            " 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566\n",
            " 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513\n",
            " 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181\n",
            " 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604 0.15769568\n",
            " 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732\n",
            " 0.13119599 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024\n",
            " 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023\n",
            " 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994\n",
            " 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415\n",
            " 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674\n",
            " 0.14803354 0.14818566 0.14833643 0.14848875]\n",
            "16 day output [[0.14864504]]\n",
            "17 day input [0.10469631 0.1063995  0.10522229 0.11453976 0.10760175 0.10549781\n",
            " 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315\n",
            " 0.10289292 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408\n",
            " 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967\n",
            " 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464\n",
            " 0.16115216 0.17092048 0.16961803 0.181866   0.17257358 0.16904195\n",
            " 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311\n",
            " 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717\n",
            " 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819\n",
            " 0.17092048 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391\n",
            " 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599\n",
            " 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284\n",
            " 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136\n",
            " 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498\n",
            " 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013\n",
            " 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354\n",
            " 0.14818566 0.14833643 0.14848875 0.14864504]\n",
            "17 day output [[0.14880735]]\n",
            "18 day input [0.1063995  0.10522229 0.11453976 0.10760175 0.10549781 0.10815279\n",
            " 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292\n",
            " 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465\n",
            " 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078\n",
            " 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216\n",
            " 0.17092048 0.16961803 0.181866   0.17257358 0.16904195 0.18149029\n",
            " 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611\n",
            " 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802\n",
            " 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048\n",
            " 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584\n",
            " 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317\n",
            " 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441\n",
            " 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136 0.16518472\n",
            " 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375\n",
            " 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662\n",
            " 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354 0.14818566\n",
            " 0.14833643 0.14848875 0.14864504 0.14880735]\n",
            "18 day output [[0.14897718]]\n",
            "19 day input [0.10522229 0.11453976 0.10760175 0.10549781 0.10815279 0.11183469\n",
            " 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292 0.10276769\n",
            " 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724\n",
            " 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455\n",
            " 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048\n",
            " 0.16961803 0.181866   0.17257358 0.16904195 0.18149029 0.16385723\n",
            " 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013\n",
            " 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217\n",
            " 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759\n",
            " 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584 0.13918597\n",
            " 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907\n",
            " 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943\n",
            " 0.17392611 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359\n",
            " 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101\n",
            " 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881\n",
            " 0.14753501 0.14771146 0.14787674 0.14803354 0.14818566 0.14833643\n",
            " 0.14848875 0.14864504 0.14880735 0.14897718]\n",
            "19 day output [[0.14915559]]\n",
            "20 day input [0.11453976 0.10760175 0.10549781 0.10815279 0.11183469 0.1105072\n",
            " 0.1113087  0.10920476 0.1101315  0.10289292 0.10276769 0.10807765\n",
            " 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445\n",
            " 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706\n",
            " 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803\n",
            " 0.181866   0.17257358 0.16904195 0.18149029 0.16385723 0.16105197\n",
            " 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525\n",
            " 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972\n",
            " 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819\n",
            " 0.16588604 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726\n",
            " 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327\n",
            " 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611\n",
            " 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136\n",
            " 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551\n",
            " 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501\n",
            " 0.14771146 0.14787674 0.14803354 0.14818566 0.14833643 0.14848875\n",
            " 0.14864504 0.14880735 0.14897718 0.14915559]\n",
            "20 day output [[0.14934331]]\n",
            "21 day input [0.10760175 0.10549781 0.10815279 0.11183469 0.1105072  0.1113087\n",
            " 0.10920476 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269\n",
            " 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128\n",
            " 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731\n",
            " 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803 0.181866\n",
            " 0.17257358 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044\n",
            " 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067\n",
            " 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601\n",
            " 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604\n",
            " 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862\n",
            " 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327 0.17282405\n",
            " 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657\n",
            " 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394\n",
            " 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933\n",
            " 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146\n",
            " 0.14787674 0.14803354 0.14818566 0.14833643 0.14848875 0.14864504\n",
            " 0.14880735 0.14897718 0.14915559 0.14934331]\n",
            "21 day output [[0.14954047]]\n",
            "22 day input [0.10549781 0.10815279 0.11183469 0.1105072  0.1113087  0.10920476\n",
            " 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269 0.11060739\n",
            " 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877\n",
            " 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583\n",
            " 0.14647464 0.16115216 0.17092048 0.16961803 0.181866   0.17257358\n",
            " 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566\n",
            " 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513\n",
            " 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181\n",
            " 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604 0.15769568\n",
            " 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732\n",
            " 0.13119599 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024\n",
            " 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023\n",
            " 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994\n",
            " 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415\n",
            " 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674\n",
            " 0.14803354 0.14818566 0.14833643 0.14848875 0.14864504 0.14880735\n",
            " 0.14897718 0.14915559 0.14934331 0.14954047]\n",
            "22 day output [[0.14974691]]\n",
            "23 day input [0.10815279 0.11183469 0.1105072  0.1113087  0.10920476 0.1101315\n",
            " 0.10289292 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408\n",
            " 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967\n",
            " 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464\n",
            " 0.16115216 0.17092048 0.16961803 0.181866   0.17257358 0.16904195\n",
            " 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311\n",
            " 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717\n",
            " 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819\n",
            " 0.17092048 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391\n",
            " 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599\n",
            " 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284\n",
            " 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136\n",
            " 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498\n",
            " 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013\n",
            " 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354\n",
            " 0.14818566 0.14833643 0.14848875 0.14864504 0.14880735 0.14897718\n",
            " 0.14915559 0.14934331 0.14954047 0.14974691]\n",
            "23 day output [[0.14996202]]\n",
            "24 day input [0.11183469 0.1105072  0.1113087  0.10920476 0.1101315  0.10289292\n",
            " 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465\n",
            " 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078\n",
            " 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216\n",
            " 0.17092048 0.16961803 0.181866   0.17257358 0.16904195 0.18149029\n",
            " 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611\n",
            " 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802\n",
            " 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048\n",
            " 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584\n",
            " 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317\n",
            " 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441\n",
            " 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136 0.16518472\n",
            " 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375\n",
            " 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662\n",
            " 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354 0.14818566\n",
            " 0.14833643 0.14848875 0.14864504 0.14880735 0.14897718 0.14915559\n",
            " 0.14934331 0.14954047 0.14974691 0.14996202]\n",
            "24 day output [[0.15018499]]\n",
            "25 day input [0.1105072  0.1113087  0.10920476 0.1101315  0.10289292 0.10276769\n",
            " 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724\n",
            " 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455\n",
            " 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048\n",
            " 0.16961803 0.181866   0.17257358 0.16904195 0.18149029 0.16385723\n",
            " 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013\n",
            " 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217\n",
            " 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759\n",
            " 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584 0.13918597\n",
            " 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907\n",
            " 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943\n",
            " 0.17392611 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359\n",
            " 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101\n",
            " 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881\n",
            " 0.14753501 0.14771146 0.14787674 0.14803354 0.14818566 0.14833643\n",
            " 0.14848875 0.14864504 0.14880735 0.14897718 0.14915559 0.14934331\n",
            " 0.14954047 0.14974691 0.14996202 0.15018499]\n",
            "25 day output [[0.15041474]]\n",
            "26 day input [0.1113087  0.10920476 0.1101315  0.10289292 0.10276769 0.10807765\n",
            " 0.10810269 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445\n",
            " 0.13668128 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706\n",
            " 0.14256731 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803\n",
            " 0.181866   0.17257358 0.16904195 0.18149029 0.16385723 0.16105197\n",
            " 0.15757044 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525\n",
            " 0.18169067 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972\n",
            " 0.16320601 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819\n",
            " 0.16588604 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726\n",
            " 0.13259862 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327\n",
            " 0.17282405 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611\n",
            " 0.16350657 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136\n",
            " 0.15143394 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551\n",
            " 0.14735933 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501\n",
            " 0.14771146 0.14787674 0.14803354 0.14818566 0.14833643 0.14848875\n",
            " 0.14864504 0.14880735 0.14897718 0.14915559 0.14934331 0.14954047\n",
            " 0.14974691 0.14996202 0.15018499 0.15041474]\n",
            "26 day output [[0.15065019]]\n",
            "27 day input [0.10920476 0.1101315  0.10289292 0.10276769 0.10807765 0.10810269\n",
            " 0.11060739 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128\n",
            " 0.13800877 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731\n",
            " 0.1377583  0.14647464 0.16115216 0.17092048 0.16961803 0.181866\n",
            " 0.17257358 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044\n",
            " 0.16568566 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067\n",
            " 0.17873513 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601\n",
            " 0.16363181 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604\n",
            " 0.15769568 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862\n",
            " 0.1323732  0.13119599 0.15902317 0.17016907 0.16974327 0.17282405\n",
            " 0.16546024 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657\n",
            " 0.15479023 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394\n",
            " 0.14396994 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933\n",
            " 0.14703415 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146\n",
            " 0.14787674 0.14803354 0.14818566 0.14833643 0.14848875 0.14864504\n",
            " 0.14880735 0.14897718 0.14915559 0.14934331 0.14954047 0.14974691\n",
            " 0.14996202 0.15018499 0.15041474 0.15065019]\n",
            "27 day output [[0.15089014]]\n",
            "28 day input [0.1101315  0.10289292 0.10276769 0.10807765 0.10810269 0.11060739\n",
            " 0.11684408 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877\n",
            " 0.12515967 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583\n",
            " 0.14647464 0.16115216 0.17092048 0.16961803 0.181866   0.17257358\n",
            " 0.16904195 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566\n",
            " 0.17232311 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513\n",
            " 0.17715717 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181\n",
            " 0.1636819  0.17092048 0.17204759 0.1636819  0.16588604 0.15769568\n",
            " 0.14875391 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732\n",
            " 0.13119599 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024\n",
            " 0.16418284 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023\n",
            " 0.15539136 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994\n",
            " 0.13332498 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415\n",
            " 0.14703013 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674\n",
            " 0.14803354 0.14818566 0.14833643 0.14848875 0.14864504 0.14880735\n",
            " 0.14897718 0.14915559 0.14934331 0.14954047 0.14974691 0.14996202\n",
            " 0.15018499 0.15041474 0.15065019 0.15089014]\n",
            "28 day output [[0.15113334]]\n",
            "29 day input [0.10289292 0.10276769 0.10807765 0.10810269 0.11060739 0.11684408\n",
            " 0.12781465 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967\n",
            " 0.13375078 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464\n",
            " 0.16115216 0.17092048 0.16961803 0.181866   0.17257358 0.16904195\n",
            " 0.18149029 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311\n",
            " 0.17392611 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717\n",
            " 0.18827802 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819\n",
            " 0.17092048 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391\n",
            " 0.14444584 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599\n",
            " 0.15902317 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284\n",
            " 0.16235441 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136\n",
            " 0.16518472 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498\n",
            " 0.15337375 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013\n",
            " 0.14716662 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354\n",
            " 0.14818566 0.14833643 0.14848875 0.14864504 0.14880735 0.14897718\n",
            " 0.14915559 0.14934331 0.14954047 0.14974691 0.14996202 0.15018499\n",
            " 0.15041474 0.15065019 0.15089014 0.15113334]\n",
            "29 day output [[0.1513788]]\n",
            "30 day input [0.10276769 0.10807765 0.10810269 0.11060739 0.11684408 0.12781465\n",
            " 0.13452724 0.13570445 0.13668128 0.13800877 0.12515967 0.13375078\n",
            " 0.14642455 0.14509706 0.14256731 0.1377583  0.14647464 0.16115216\n",
            " 0.17092048 0.16961803 0.181866   0.17257358 0.16904195 0.18149029\n",
            " 0.16385723 0.16105197 0.15757044 0.16568566 0.17232311 0.17392611\n",
            " 0.18407013 0.18146525 0.18169067 0.17873513 0.17715717 0.18827802\n",
            " 0.18249217 0.17051972 0.16320601 0.16363181 0.1636819  0.17092048\n",
            " 0.17204759 0.1636819  0.16588604 0.15769568 0.14875391 0.14444584\n",
            " 0.13918597 0.13720726 0.13259862 0.1323732  0.13119599 0.15902317\n",
            " 0.17016907 0.16974327 0.17282405 0.16546024 0.16418284 0.16235441\n",
            " 0.1702943  0.17392611 0.16350657 0.15479023 0.15539136 0.16518472\n",
            " 0.16458359 0.15539136 0.15143394 0.14396994 0.13332498 0.15337375\n",
            " 0.15021101 0.14829551 0.14735933 0.14703415 0.14703013 0.14716662\n",
            " 0.14734881 0.14753501 0.14771146 0.14787674 0.14803354 0.14818566\n",
            " 0.14833643 0.14848875 0.14864504 0.14880735 0.14897718 0.14915559\n",
            " 0.14934331 0.14954047 0.14974691 0.14996202 0.15018499 0.15041474\n",
            " 0.15065019 0.15089014 0.15113334 0.1513788 ]\n",
            "30 day output [[0.15162538]]\n",
            "[[0.15337374806404114], [0.15021100640296936], [0.14829550683498383], [0.14735932648181915], [0.147034153342247], [0.14703013002872467], [0.14716662466526031], [0.1473488062620163], [0.14753501117229462], [0.14771145582199097], [0.14787673950195312], [0.14803354442119598], [0.14818565547466278], [0.14833642542362213], [0.14848874509334564], [0.1486450433731079], [0.1488073468208313], [0.14897717535495758], [0.14915558695793152], [0.1493433117866516], [0.1495404690504074], [0.14974690973758698], [0.14996202290058136], [0.1501849889755249], [0.15041473507881165], [0.15065018832683563], [0.15089014172554016], [0.15113334357738495], [0.15137879550457], [0.1516253799200058]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "output = scaler.inverse_transform(lst_output[1:])"
      ],
      "metadata": {
        "id": "OVt6HH-kRYx2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "output"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3NzIp6OBWhyS",
        "outputId": "8492862d-285f-4af8-b16b-1ba64dab609c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.9698875 ],\n",
              "       [1.05961323],\n",
              "       [1.15387118],\n",
              "       [1.24455428],\n",
              "       [1.32727408],\n",
              "       [1.40117002],\n",
              "       [1.46832013],\n",
              "       [1.53230715],\n",
              "       [1.59657431],\n",
              "       [1.66317499],\n",
              "       [1.73229551],\n",
              "       [1.80255544],\n",
              "       [1.8717984 ],\n",
              "       [1.93795538],\n",
              "       [1.99962711],\n",
              "       [2.05626464],\n",
              "       [2.10802984],\n",
              "       [2.15550852],\n",
              "       [2.19942474],\n",
              "       [2.24044347],\n",
              "       [2.27907896],\n",
              "       [2.31568074],\n",
              "       [2.35046005],\n",
              "       [2.38353634],\n",
              "       [2.41497254],\n",
              "       [2.44480991],\n",
              "       [2.47307611],\n",
              "       [2.49980307],\n",
              "       [2.52502203]])"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "output"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VtF9DlqrSm89",
        "outputId": "cbb03a6a-968d-492c-ecb6-55cd6f11ac66"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[2.5487685]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "lst_output = lst_output.reshape(-1,1)\n",
        "output = scaler.inverse_transform(lst_output)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 305
        },
        "id": "RXxtyeAWP21_",
        "outputId": "9bcd8f18-d5e9-4889-a921-079d97b4e1b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-212-98899722bef0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mlst_output\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlst_output\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\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[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscaler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minverse_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlst_output\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'list' object has no attribute 'reshape'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "day_new=np.arange(1,timespan + 1) \n",
        "day_pred=np.arange (timespan + 1,timespan + 31)"
      ],
      "metadata": {
        "id": "AymUMi-OP87l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3=df1.tolist() \n",
        "df3.extend(lst_output)"
      ],
      "metadata": {
        "id": "8KRI1PaTZFXh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(df1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kEcjGGHcZgDg",
        "outputId": "3a20a637-73e8-4219-9ae6-e996bf5c17d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1258"
            ]
          },
          "metadata": {},
          "execution_count": 215
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6RU6hYr9ZPmK",
        "outputId": "53b047f2-24c7-4197-8ae2-1d0dbba7bf0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[[0.07536631183469],\n",
              " [0.07551659361302443],\n",
              " [0.08252974326862861],\n",
              " [0.08045084533500313],\n",
              " [0.08250469630557289],\n",
              " [0.0814026299311208],\n",
              " [0.08185347526612397],\n",
              " [0.080551033187226],\n",
              " [0.07974953036944266],\n",
              " [0.08090169067000619],\n",
              " [0.08105197244834056],\n",
              " [0.08052598622417029],\n",
              " [0.08420788979336252],\n",
              " [0.08478396994364429],\n",
              " [0.08303068252974327],\n",
              " [0.0867125860989355],\n",
              " [0.08265497808390732],\n",
              " [0.08661239824671252],\n",
              " [0.08536005009392605],\n",
              " [0.08465873512836564],\n",
              " [0.08525986224170312],\n",
              " [0.09257357545397621],\n",
              " [0.0933750782717595],\n",
              " [0.09289918597370067],\n",
              " [0.09222291797119592],\n",
              " [0.09232310582341885],\n",
              " [0.09500313087038192],\n",
              " [0.09312460864120226],\n",
              " [0.09222291797119592],\n",
              " [0.09142141515341262],\n",
              " [0.09099561678146517],\n",
              " [0.08713838447088285],\n",
              " [0.0875641828428303],\n",
              " [0.08568566061365057],\n",
              " [0.08763932373199751],\n",
              " [0.08606136505948647],\n",
              " [0.08475892298058857],\n",
              " [0.08916718847839694],\n",
              " [0.0887413901064496],\n",
              " [0.09217282404508448],\n",
              " [0.09440200375704444],\n",
              " [0.09227301189730741],\n",
              " [0.09254852849092043],\n",
              " [0.09219787100814025],\n",
              " [0.099536631183469],\n",
              " [0.10186599874765179],\n",
              " [0.10073888541014397],\n",
              " [0.0994113963681903],\n",
              " [0.10549780839073258],\n",
              " [0.115641828428303],\n",
              " [0.11809643080776455],\n",
              " [0.11626800250469627],\n",
              " [0.11799624295554156],\n",
              " [0.12338134001252343],\n",
              " [0.12237946149029422],\n",
              " [0.12180338134001245],\n",
              " [0.1087288666249217],\n",
              " [0.1144646211646837],\n",
              " [0.11576706324358166],\n",
              " [0.11809643080776455],\n",
              " [0.11762053850970566],\n",
              " [0.11646837820914213],\n",
              " [0.11779586725109575],\n",
              " [0.11714464621164683],\n",
              " [0.11729492798998115],\n",
              " [0.11501565435190975],\n",
              " [0.11606762680025046],\n",
              " [0.12175328741390101],\n",
              " [0.11794614902943018],\n",
              " [0.11924859110832803],\n",
              " [0.1215529117094552],\n",
              " [0.12060112711333748],\n",
              " [0.10554790231684402],\n",
              " [0.09663118346900429],\n",
              " [0.09956167814652472],\n",
              " [0.09597996242955537],\n",
              " [0.0938008766437069],\n",
              " [0.0887413901064496],\n",
              " [0.09893550407013146],\n",
              " [0.09560425798371941],\n",
              " [0.09775829680651216],\n",
              " [0.09715716969317467],\n",
              " [0.09878522229179709],\n",
              " [0.0976330619912335],\n",
              " [0.09239824671258601],\n",
              " [0.09765810895428928],\n",
              " [0.09227301189730741],\n",
              " [0.09312460864120226],\n",
              " [0.0918221665623043],\n",
              " [0.09329993738259235],\n",
              " [0.08989355040701308],\n",
              " [0.09352536005009388],\n",
              " [0.09572949279899806],\n",
              " [0.09690670006261737],\n",
              " [0.0974326862867877],\n",
              " [0.10251721978710082],\n",
              " [0.1056981840951784],\n",
              " [0.10700062617407635],\n",
              " [0.10830306825297431],\n",
              " [0.11065748278021287],\n",
              " [0.10895428929242323],\n",
              " [0.10877896055103314],\n",
              " [0.11333750782717594],\n",
              " [0.11496556042579836],\n",
              " [0.11676894176581087],\n",
              " [0.10950532247964928],\n",
              " [0.10685034439574198],\n",
              " [0.10492172824045076],\n",
              " [0.10822792736380715],\n",
              " [0.1259862241703193],\n",
              " [0.12205385097056975],\n",
              " [0.12410770194113957],\n",
              " [0.13016906700062614],\n",
              " [0.13335003130870382],\n",
              " [0.1358046286787727],\n",
              " [0.1214276768941765],\n",
              " [0.12683782091421408],\n",
              " [0.132773951158422],\n",
              " [0.13715716969317465],\n",
              " [0.13552911709455223],\n",
              " [0.12778960551033186],\n",
              " [0.12688791484032558],\n",
              " [0.12616155291170944],\n",
              " [0.1325986224170319],\n",
              " [0.13309956167814646],\n",
              " [0.13132122730118972],\n",
              " [0.13279899812147777],\n",
              " [0.1368315591734502],\n",
              " [0.1404383218534752],\n",
              " [0.1415403882279273],\n",
              " [0.14316844082654973],\n",
              " [0.14329367564182843],\n",
              " [0.13835942391984973],\n",
              " [0.13793362554790228],\n",
              " [0.1363055729492798],\n",
              " [0.12971822166562297],\n",
              " [0.13690670006261735],\n",
              " [0.1353036944270507],\n",
              " [0.13227301189730745],\n",
              " [0.12884157795867246],\n",
              " [0.13284909204758916],\n",
              " [0.1298184095178459],\n",
              " [0.12996869129618027],\n",
              " [0.12330619912335622],\n",
              " [0.11659361302442073],\n",
              " [0.11283656856606128],\n",
              " [0.10948027551659362],\n",
              " [0.11596743894802747],\n",
              " [0.11869755792110198],\n",
              " [0.1163180964308077],\n",
              " [0.11842204132748901],\n",
              " [0.11764558547276138],\n",
              " [0.11932373199749524],\n",
              " [0.11681903569192231],\n",
              " [0.12160300563556659],\n",
              " [0.12137758296806511],\n",
              " [0.12273011897307445],\n",
              " [0.12288040075140888],\n",
              " [0.1245084533500313],\n",
              " [0.12313087038196613],\n",
              " [0.1256105197244834],\n",
              " [0.13284909204758916],\n",
              " [0.1343268628678772],\n",
              " [0.13254852849092041],\n",
              " [0.12308077645585463],\n",
              " [0.12375704445835939],\n",
              " [0.12355666875391352],\n",
              " [0.12588603631809636],\n",
              " [0.12415779586725106],\n",
              " [0.126662492172824],\n",
              " [0.14078897933625545],\n",
              " [0.14998121477770815],\n",
              " [0.15579211020663736],\n",
              " [0.15040701314965554],\n",
              " [0.15346274264245457],\n",
              " [0.1644583594239198],\n",
              " [0.16884157795867244],\n",
              " [0.17024420788979333],\n",
              " [0.17382592360676263],\n",
              " [0.17292423293675635],\n",
              " [0.1698935504070131],\n",
              " [0.16814026299311202],\n",
              " [0.16155291170945518],\n",
              " [0.15589229805886035],\n",
              " [0.16095178459611764],\n",
              " [0.15857232310582337],\n",
              " [0.15814652473387597],\n",
              " [0.16606136505948643],\n",
              " [0.1706199123356293],\n",
              " [0.170644959298685],\n",
              " [0.16844082654978082],\n",
              " [0.1658860363180964],\n",
              " [0.15689417658108945],\n",
              " [0.16283030682529737],\n",
              " [0.16082654978083905],\n",
              " [0.15769567939887286],\n",
              " [0.15729492798998113],\n",
              " [0.1557169693174702],\n",
              " [0.15649342517219783],\n",
              " [0.15661865998747648],\n",
              " [0.16488415779586718],\n",
              " [0.1624546023794614],\n",
              " [0.16388227927363808],\n",
              " [0.16375704445835937],\n",
              " [0.16814026299311202],\n",
              " [0.17427676894176575],\n",
              " [0.16956793988728858],\n",
              " [0.16909204758922974],\n",
              " [0.17074514715090788],\n",
              " [0.17074514715090788],\n",
              " [0.15962429555416402],\n",
              " [0.15969943644333118],\n",
              " [0.16090169067000626],\n",
              " [0.15626800250469625],\n",
              " [0.1638572323105823],\n",
              " [0.1637820914214151],\n",
              " [0.16578584846587346],\n",
              " [0.17072010018785216],\n",
              " [0.16909204758922974],\n",
              " [0.16904195366311836],\n",
              " [0.16894176581089537],\n",
              " [0.17142141515341258],\n",
              " [0.17595491546649966],\n",
              " [0.17370068879148398],\n",
              " [0.18098935504070124],\n",
              " [0.1813901064495929],\n",
              " [0.1793863494051346],\n",
              " [0.17572949279899808],\n",
              " [0.17582968065122095],\n",
              " [0.16876643706950528],\n",
              " [0.16097683155917342],\n",
              " [0.16197871008140258],\n",
              " [0.15308703819661862],\n",
              " [0.1506073888541014],\n",
              " [0.151759549154665],\n",
              " [0.1526361928616155],\n",
              " [0.13440200375704442],\n",
              " [0.12435817157169693],\n",
              " [0.14073888541014395],\n",
              " [0.13199749530369437],\n",
              " [0.12100187852222916],\n",
              " [0.12415779586725106],\n",
              " [0.13993738259236066],\n",
              " [0.14402003757044457],\n",
              " [0.15160926737633057],\n",
              " [0.1656856606136506],\n",
              " [0.1642830306825297],\n",
              " [0.16283030682529737],\n",
              " [0.16087664370695048],\n",
              " [0.1644583594239198],\n",
              " [0.17197244834063863],\n",
              " [0.18066374452097678],\n",
              " [0.17921102066374445],\n",
              " [0.1785347526612398],\n",
              " [0.17072010018785216],\n",
              " [0.17375078271759548],\n",
              " [0.1752786474639949],\n",
              " [0.17490294301815895],\n",
              " [0.17079524107701938],\n",
              " [0.1755792110206637],\n",
              " [0.18319348778960542],\n",
              " [0.18755165936130241],\n",
              " [0.1831684408265497],\n",
              " [0.1793362554790231],\n",
              " [0.17986224170319348],\n",
              " [0.1782842830306825],\n",
              " [0.17147150907952408],\n",
              " [0.1713212273011897],\n",
              " [0.1613775829680651],\n",
              " [0.15531621790857852],\n",
              " [0.14552285535378828],\n",
              " [0.16513462742642454],\n",
              " [0.15403882279273634],\n",
              " [0.1493800876643706],\n",
              " [0.1526361928616155],\n",
              " [0.14988102692548527],\n",
              " [0.15416405760801494],\n",
              " [0.16222917971195994],\n",
              " [0.1652097683155917],\n",
              " [0.15413901064495922],\n",
              " [0.15832185347526612],\n",
              " [0.1663368816530995],\n",
              " [0.16430807764558542],\n",
              " [0.16856606136505942],\n",
              " [0.17004383218534747],\n",
              " [0.17277395115842198],\n",
              " [0.17883531621790855],\n",
              " [0.17783343769567939],\n",
              " [0.1652097683155917],\n",
              " [0.14747651847213522],\n",
              " [0.1462742642454602],\n",
              " [0.14051346274264243],\n",
              " [0.14229179711959922],\n",
              " [0.14371947401377577],\n",
              " [0.13896055103318716],\n",
              " [0.14632435817157163],\n",
              " [0.15594239198497178],\n",
              " [0.1746524733876017],\n",
              " [0.175453976205385],\n",
              " [0.19283656856606135],\n",
              " [0.19616781465247335],\n",
              " [0.1983969943644333],\n",
              " [0.20167814652473387],\n",
              " [0.2083907326236693],\n",
              " [0.20475892298058856],\n",
              " [0.20365685660613647],\n",
              " [0.1993738259236067],\n",
              " [0.20373199749530368],\n",
              " [0.20075140889167187],\n",
              " [0.19904821540388223],\n",
              " [0.2023544145272385],\n",
              " [0.2011772072636192],\n",
              " [0.2041828428303068],\n",
              " [0.20365685660613647],\n",
              " [0.20473387601753285],\n",
              " [0.2030306825297432],\n",
              " [0.20202880400751405],\n",
              " [0.20045084533500307],\n",
              " [0.20889167188478397],\n",
              " [0.21287413901064495],\n",
              " [0.2165810895428929],\n",
              " [0.2182592360676267],\n",
              " [0.21695679398872886],\n",
              " [0.21254852849092037],\n",
              " [0.21137132122730112],\n",
              " [0.21400125234815276],\n",
              " [0.21004383218534745],\n",
              " [0.2102943018159048],\n",
              " [0.20538509705698182],\n",
              " [0.20513462742642452],\n",
              " [0.19749530369442703],\n",
              " [0.19952410770194107],\n",
              " [0.19691922354414526],\n",
              " [0.1955666875391358],\n",
              " [0.18867877269881017],\n",
              " [0.19433938634940512],\n",
              " [0.19366311834690036],\n",
              " [0.19701941139636814],\n",
              " [0.19604257983719475],\n",
              " [0.2012273011897307],\n",
              " [0.19306199123356288],\n",
              " [0.1967689417658109],\n",
              " [0.2032060112711333],\n",
              " [0.20974326862867876],\n",
              " [0.20916718847839694],\n",
              " [0.20298058860363177],\n",
              " [0.21087038196618657],\n",
              " [0.21162179085785848],\n",
              " [0.21056981840951777],\n",
              " [0.21192235441452717],\n",
              " [0.2092924232936756],\n",
              " [0.21299937382592354],\n",
              " [0.21189730745147145],\n",
              " [0.2123231058234189],\n",
              " [0.21580463368816527],\n",
              " [0.22036318096430801],\n",
              " [0.21883531621790853],\n",
              " [0.21074514715090786],\n",
              " [0.20806512210394484],\n",
              " [0.20901690670006257],\n",
              " [0.23709455228553528],\n",
              " [0.25184721352535994],\n",
              " [0.25335003130870376],\n",
              " [0.25605510331872255],\n",
              " [0.2511458985597996],\n",
              " [0.25149655604257976],\n",
              " [0.25557921102066367],\n",
              " [0.25219787100814023],\n",
              " [0.25555416405760795],\n",
              " [0.25775829680651213],\n",
              " [0.25898559799624293],\n",
              " [0.2667000626174076],\n",
              " [0.27737006887914833],\n",
              " [0.27206011271133373],\n",
              " [0.2710081402629931],\n",
              " [0.2710331872260488],\n",
              " [0.2721352536005009],\n",
              " [0.27381340012523475],\n",
              " [0.27827175954915456],\n",
              " [0.28268002504696293],\n",
              " [0.2908954289292423],\n",
              " [0.29603005635566687],\n",
              " [0.30254226675015644],\n",
              " [0.3043706950532247],\n",
              " [0.3006386975579211],\n",
              " [0.29119599248591105],\n",
              " [0.2866875391358798],\n",
              " [0.27924859110832806],\n",
              " [0.2930745147150908],\n",
              " [0.2861114589855979],\n",
              " [0.29948653725735747],\n",
              " [0.29304946775203505],\n",
              " [0.27812147777082025],\n",
              " [0.2790231684408265],\n",
              " [0.27934877896055105],\n",
              " [0.2835065748278021],\n",
              " [0.2775704445835942],\n",
              " [0.28541014402003745],\n",
              " [0.2889167188478396],\n",
              " [0.2844834063869755],\n",
              " [0.295829680651221],\n",
              " [0.2978083907326236],\n",
              " [0.3016155291170945],\n",
              " [0.3066750156543519],\n",
              " [0.31366311834690036],\n",
              " [0.3034439574201628],\n",
              " [0.29417658108954287],\n",
              " [0.2928741390106449],\n",
              " [0.3006386975579211],\n",
              " [0.27431433938634936],\n",
              " [0.269530369442705],\n",
              " [0.28871634314339384],\n",
              " [0.2768190356919223],\n",
              " [0.2888165309956167],\n",
              " [0.28641202254226666],\n",
              " [0.27346274264245457],\n",
              " [0.28170319348778955],\n",
              " [0.28505948653725727],\n",
              " [0.290269254852849],\n",
              " [0.2711333750782717],\n",
              " [0.28293049467752035],\n",
              " [0.27416405760801504],\n",
              " [0.2639949906073888],\n",
              " [0.26664996869129615],\n",
              " [0.28057608015028174],\n",
              " [0.28899185973700686],\n",
              " [0.2520726361928615],\n",
              " [0.23731997495303686],\n",
              " [0.242780212899186],\n",
              " [0.25825923606762674],\n",
              " [0.2546023794614903],\n",
              " [0.24453350031308702],\n",
              " [0.2187351283656856],\n",
              " [0.21387601753287405],\n",
              " [0.20027551659361303],\n",
              " [0.2118221665623043],\n",
              " [0.21713212273011895],\n",
              " [0.19792110206637442],\n",
              " [0.17567939887288658],\n",
              " [0.17517845961177203],\n",
              " [0.16393237319974946],\n",
              " [0.16976831559173444],\n",
              " [0.16881653099561678],\n",
              " [0.18559799624295548],\n",
              " [0.1821164683782091],\n",
              " [0.1796869129618034],\n",
              " [0.1953162179085785],\n",
              " [0.17495303694427045],\n",
              " [0.17001878522229175],\n",
              " [0.1544145272385723],\n",
              " [0.15719474013775825],\n",
              " [0.15476518472135248],\n",
              " [0.15594239198497178],\n",
              " [0.16057608015028169],\n",
              " [0.14687539135879768],\n",
              " [0.14301815904821535],\n",
              " [0.14835316217908573],\n",
              " [0.1353788353162178],\n",
              " [0.12520976831559172],\n",
              " [0.10993112085159668],\n",
              " [0.10016280525986221],\n",
              " [0.12606136505948645],\n",
              " [0.12350657482780208],\n",
              " [0.1237069505322479],\n",
              " [0.12748904195366312],\n",
              " [0.12793988728866618],\n",
              " [0.08854101440200374],\n",
              " [0.10374452097683151],\n",
              " [0.10291797119599244],\n",
              " [0.10998121477770817],\n",
              " [0.11639323731997492],\n",
              " [0.11762053850970566],\n",
              " [0.1138384470882905],\n",
              " [0.10810269254852845],\n",
              " [0.11579211020663738],\n",
              " [0.12047589229805883],\n",
              " [0.12278021289918595],\n",
              " [0.12518472135253594],\n",
              " [0.1163681903569192],\n",
              " [0.1179211020663744],\n",
              " [0.11486537257357538],\n",
              " [0.1275391358797745],\n",
              " [0.12388227927363804],\n",
              " [0.11982467125860985],\n",
              " [0.14629931120851591],\n",
              " [0.14927989981214773],\n",
              " [0.1494802755165936],\n",
              " [0.1613274890419536],\n",
              " [0.1686662492172824],\n",
              " [0.16881653099561678],\n",
              " [0.16055103318722602],\n",
              " [0.15922354414527234],\n",
              " [0.15676894176581085],\n",
              " [0.16042579837194731],\n",
              " [0.15864746399499058],\n",
              " [0.16020037570444584],\n",
              " [0.15924859110832806],\n",
              " [0.1605259862241703],\n",
              " [0.16328115216030054],\n",
              " [0.16085159674389476],\n",
              " [0.1656355666875391],\n",
              " [0.168791484032561],\n",
              " [0.16904195366311836],\n",
              " [0.1703944896681277],\n",
              " [0.16608641202254226],\n",
              " [0.170644959298685],\n",
              " [0.1728490920475892],\n",
              " [0.17204758922980584],\n",
              " [0.1695178459611772],\n",
              " [0.1644583594239198],\n",
              " [0.16548528490920472],\n",
              " [0.1804884157795867],\n",
              " [0.18552285535378832],\n",
              " [0.1875266123982467],\n",
              " [0.192586098935504],\n",
              " [0.1985723231058234],\n",
              " [0.203331246086412],\n",
              " [0.19959924859110828],\n",
              " [0.2036819035691922],\n",
              " [0.2210394489668127],\n",
              " [0.21092047589229806],\n",
              " [0.20513462742642452],\n",
              " [0.2002504696305572],\n",
              " [0.20445835942391982],\n",
              " [0.20508453350031303],\n",
              " [0.20816530995616772],\n",
              " [0.2113963681903569],\n",
              " [0.2183594239198497],\n",
              " [0.2216906700062617],\n",
              " [0.22254226675015648],\n",
              " [0.22582341891045704],\n",
              " [0.23358797745773324],\n",
              " [0.23208515967438942],\n",
              " [0.2348904195366312],\n",
              " [0.2307075767063243],\n",
              " [0.2305072010018785],\n",
              " [0.23140889167188472],\n",
              " [0.23145898559799621],\n",
              " [0.2411772072636192],\n",
              " [0.24300563556668747],\n",
              " [0.24468378209142133],\n",
              " [0.2520726361928615],\n",
              " [0.25127113337507817],\n",
              " [0.24656230432060106],\n",
              " [0.24410770194113957],\n",
              " [0.2448841577958672],\n",
              " [0.2350156543519098],\n",
              " [0.2596869129618034],\n",
              " [0.2562554790231684],\n",
              " [0.2627676894176581],\n",
              " [0.25457733249843445],\n",
              " [0.24050093926111454],\n",
              " [0.24060112711333742],\n",
              " [0.2351408891671884],\n",
              " [0.2262742642454602],\n",
              " [0.19757044458359418],\n",
              " [0.20493425172197866],\n",
              " [0.2105948653725735],\n",
              " [0.2084909204758923],\n",
              " [0.20578584846587344],\n",
              " [0.19098309329993735],\n",
              " [0.19977457733249837],\n",
              " [0.19020663744520971],\n",
              " [0.18239198497182213],\n",
              " [0.18066374452097678],\n",
              " [0.17881026925485277],\n",
              " [0.1766812773951158],\n",
              " [0.17898559799624292],\n",
              " [0.17089542892924225],\n",
              " [0.16646211646837822],\n",
              " [0.18234189104571064],\n",
              " [0.18960551033187217],\n",
              " [0.19631809643080772],\n",
              " [0.20866624921728238],\n",
              " [0.21475266123982467],\n",
              " [0.2203381340012523],\n",
              " [0.2187852222917971],\n",
              " [0.21868503443957416],\n",
              " [0.21515341264871635],\n",
              " [0.21803381340012518],\n",
              " [0.22945522855353778],\n",
              " [0.22800250469630556],\n",
              " [0.23198497182216654],\n",
              " [0.2302817783343769],\n",
              " [0.22978083907326236],\n",
              " [0.22224170319348774],\n",
              " [0.23283656856606133],\n",
              " [0.23268628678772701],\n",
              " [0.22812773951158416],\n",
              " [0.23721978710081398],\n",
              " [0.24017532874139008],\n",
              " [0.2443832185347526],\n",
              " [0.24393237319974942],\n",
              " [0.23338760175328738],\n",
              " [0.23644333124608635],\n",
              " [0.2414276768941765],\n",
              " [0.2377207263619286],\n",
              " [0.24160300563556664],\n",
              " [0.24638697557921102],\n",
              " [0.24460864120225417],\n",
              " [0.24172824045084523],\n",
              " [0.24751408891671883],\n",
              " [0.2398246712586099],\n",
              " [0.2514214151534126],\n",
              " [0.2554790231684408],\n",
              " [0.25505322479649334],\n",
              " [0.250920475892298],\n",
              " [0.25272385723231056],\n",
              " [0.2575829680651221],\n",
              " [0.25532874139010636],\n",
              " [0.2659987476518471],\n",
              " [0.25445209768315585],\n",
              " [0.2434063869755792],\n",
              " [0.21665623043206006],\n",
              " [0.22582341891045704],\n",
              " [0.23093299937382583],\n",
              " [0.2419286161552911],\n",
              " [0.23581715716969315],\n",
              " [0.2345397620538509],\n",
              " [0.25580463368816525],\n",
              " [0.24022542266750152],\n",
              " [0.23769567939887287],\n",
              " [0.24961803381340003],\n",
              " [0.25926111458985596],\n",
              " [0.2592861615529117],\n",
              " [0.2649968691296179],\n",
              " [0.26454602379461484],\n",
              " [0.2399499060738885],\n",
              " [0.24959298685034442],\n",
              " [0.24375704445835938],\n",
              " [0.24718847839699437],\n",
              " [0.2559048215403881],\n",
              " [0.2552285535378835],\n",
              " [0.2476142767689417],\n",
              " [0.2563556668753913],\n",
              " [0.2665998747651847],\n",
              " [0.26654978083907316],\n",
              " [0.2688290544771446],\n",
              " [0.27516593613024415],\n",
              " [0.29242329367564174],\n",
              " [0.29117094552285533],\n",
              " [0.2803005635566687],\n",
              " [0.28318096430807765],\n",
              " [0.285184721352536],\n",
              " [0.290369442705072],\n",
              " [0.2858359423919849],\n",
              " [0.27774577332498424],\n",
              " [0.28022542266750156],\n",
              " [0.27762053850970564],\n",
              " [0.28601127113337504],\n",
              " [0.2831559173450218],\n",
              " [0.28047589229805875],\n",
              " [0.2933750782717595],\n",
              " [0.2949279899812148],\n",
              " [0.28082654978083904],\n",
              " [0.2854852849092047],\n",
              " [0.3009893550407013],\n",
              " [0.3011145898559799],\n",
              " [0.2944520976831559],\n",
              " [0.30103944896681273],\n",
              " [0.30870381966186594],\n",
              " [0.32403256105197237],\n",
              " [0.3231809643080776],\n",
              " [0.32180338134001246],\n",
              " [0.31942391984971813],\n",
              " [0.3217031934877896],\n",
              " [0.324533500313087],\n",
              " [0.3348027551659361],\n",
              " [0.333425172197871],\n",
              " [0.3414902943018158],\n",
              " [0.34249217282404504],\n",
              " [0.35000626174076394],\n",
              " [0.35619286161552904],\n",
              " [0.34176581089542885],\n",
              " [0.3416906700062617],\n",
              " [0.35546649968691285],\n",
              " [0.3731496556042579],\n",
              " [0.3773575453976205],\n",
              " [0.37643080776455845],\n",
              " [0.3767063243581716],\n",
              " [0.38219160926737633],\n",
              " [0.38396994364433307],\n",
              " [0.38912961803381335],\n",
              " [0.38852849092047576],\n",
              " [0.39481527864746396],\n",
              " [0.39023168440826544],\n",
              " [0.398046336881653],\n",
              " [0.4014026299311208],\n",
              " [0.39937382592360676],\n",
              " [0.39160926737633056],\n",
              " [0.38865372573575446],\n",
              " [0.3880776455854726],\n",
              " [0.3995742016280525],\n",
              " [0.3943644333124609],\n",
              " [0.4032561051972447],\n",
              " [0.4017783343769567],\n",
              " [0.39403882279273644],\n",
              " [0.38224170319348766],\n",
              " [0.3879774577332498],\n",
              " [0.3975954915466499],\n",
              " [0.41044458359423913],\n",
              " [0.40095178459611774],\n",
              " [0.4048591108328115],\n",
              " [0.41059486537257345],\n",
              " [0.41232310582341886],\n",
              " [0.42156543519098294],\n",
              " [0.4333625547902316],\n",
              " [0.43474013775829684],\n",
              " [0.43306199123356287],\n",
              " [0.43376330619912323],\n",
              " [0.43231058234189096],\n",
              " [0.4437319974953036],\n",
              " [0.44440826549780826],\n",
              " [0.45853475266123983],\n",
              " [0.4582592360676268],\n",
              " [0.4625673137132122],\n",
              " [0.4679023168440825],\n",
              " [0.48468378209142143],\n",
              " [0.4773700688791484],\n",
              " [0.4833061991233562],\n",
              " [0.47977457733249834],\n",
              " [0.4917971195992485],\n",
              " [0.5079273638071382],\n",
              " [0.5096806512210394],\n",
              " [0.5262867877269879],\n",
              " [0.5155666875391358],\n",
              " [0.5122103944896681],\n",
              " [0.5219787100814026],\n",
              " [0.5307201001878521],\n",
              " [0.5253099561678145],\n",
              " [0.528140262993112],\n",
              " [0.5319724483406387],\n",
              " [0.5296681277395114],\n",
              " [0.5062241703193486],\n",
              " [0.5281152160300562],\n",
              " [0.5447714464621163],\n",
              " [0.5435942391984971],\n",
              " [0.5076268002504696],\n",
              " [0.5054978083907327],\n",
              " [0.531020663744521],\n",
              " [0.5375328741390106],\n",
              " [0.5469505322479649],\n",
              " [0.5339762053850969],\n",
              " [0.5377833437695678],\n",
              " [0.5329242329367563],\n",
              " [0.5519348778960551],\n",
              " [0.5460989355040702],\n",
              " [0.5462993112085159],\n",
              " [0.5313963681903568],\n",
              " [0.5429680651221038],\n",
              " [0.5346524733876017],\n",
              " [0.5164934251721978],\n",
              " [0.4792485911083281],\n",
              " [0.4539511584220412],\n",
              " [0.4653976205385096],\n",
              " [0.41748278021289903],\n",
              " [0.4170820288040075],\n",
              " [0.480826549780839],\n",
              " [0.4570569818409517],\n",
              " [0.4906700062617407],\n",
              " [0.46607388854101434],\n",
              " [0.45633061991233553],\n",
              " [0.399073262366938],\n",
              " [0.44708829054477134],\n",
              " [0.4222667501565435],\n",
              " [0.3541390106449592],\n",
              " [0.4286286787726988],\n",
              " [0.33906073888541016],\n",
              " [0.365735754539762],\n",
              " [0.3502316844082654],\n",
              " [0.3454978083907326],\n",
              " [0.3065748278021289],\n",
              " [0.29437695679398873],\n",
              " [0.35075767063243574],\n",
              " [0.3473512836568566],\n",
              " [0.379711959924859],\n",
              " [0.3529117094552285],\n",
              " [0.37061991233562924],\n",
              " [0.3693174702567313],\n",
              " [0.3358046336881652],\n",
              " [0.3458735128365685],\n",
              " [0.33705698184095173],\n",
              " [0.3898058860363181],\n",
              " [0.38219160926737633],\n",
              " [0.3988227927363806],\n",
              " [0.4036318096430807],\n",
              " [0.4168065122103944],\n",
              " [0.4513713212273011],\n",
              " [0.4448090169067],\n",
              " [0.4504696305572949],\n",
              " [0.4407263619286161],\n",
              " [0.42602379461490286],\n",
              " [0.4045835942391985],\n",
              " [0.4239448966812774],\n",
              " [0.4212648716343142],\n",
              " [0.44115216030056353],\n",
              " [0.44165309956167814],\n",
              " [0.4301565435190982],\n",
              " [0.4530745147150908],\n",
              " [0.4682780212899185],\n",
              " [0.4564308077645585],\n",
              " [0.46667501565435193],\n",
              " [0.47769567939887286],\n",
              " [0.4853850970569818],\n",
              " [0.4931747025673137],\n",
              " [0.5091797119599248],\n",
              " [0.5214026299311207],\n",
              " [0.5123857232310582],\n",
              " [0.5029680651221038],\n",
              " [0.5077019411396368],\n",
              " [0.5031183469004381],\n",
              " [0.521277395115842],\n",
              " [0.5167188478396993],\n",
              " [0.5319724483406387],\n",
              " [0.5260112711333751],\n",
              " [0.5311208515967438],\n",
              " [0.5257107075767062],\n",
              " [0.529167188478397],\n",
              " [0.5295178459611771],\n",
              " [0.5287413901064495],\n",
              " [0.5385347526612398],\n",
              " [0.5422667501565435],\n",
              " [0.5467251095804633],\n",
              " [0.539711959924859],\n",
              " [0.5627050720100186],\n",
              " [0.5676142767689416],\n",
              " [0.5939887288666248],\n",
              " [0.6161552911709454],\n",
              " [0.5737257357545396],\n",
              " [0.5809893550407013],\n",
              " [0.591484032561052],\n",
              " [0.61425172197871],\n",
              " [0.6130244207889792],\n",
              " [0.6133750782717595],\n",
              " [0.6083406386975578],\n",
              " [0.6312586098935504],\n",
              " [0.650444583594239],\n",
              " [0.6342391984971822],\n",
              " [0.6462116468378207],\n",
              " [0.618134001252348],\n",
              " [0.6385472761427675],\n",
              " [0.6461114589855979],\n",
              " [0.6443832185347527],\n",
              " [0.6443832185347527],\n",
              " [0.6687789605510333],\n",
              " [0.6658735128365685],\n",
              " [0.6876142767689417],\n",
              " [0.6917219787100812],\n",
              " [0.6934001252348152],\n",
              " [0.6889668127739512],\n",
              " [0.7047964934251723],\n",
              " [0.7114840325610519],\n",
              " [0.6994364433312459],\n",
              " [0.6974827802128991],\n",
              " [0.7178209142141514],\n",
              " [0.7042204132748904],\n",
              " [0.7069505322479648],\n",
              " [0.662592360676268],\n",
              " [0.6602880400751407],\n",
              " [0.6822792736380714],\n",
              " [0.6666750156543517],\n",
              " [0.6845835942391985],\n",
              " [0.696105197244834],\n",
              " [0.7969943644333124],\n",
              " [0.8238196618659985],\n",
              " [0.8311083281152161],\n",
              " [0.8350907952410769],\n",
              " [0.8735629304946775],\n",
              " [0.8456105197244832],\n",
              " [0.8617908578584845],\n",
              " [0.8282028804007513],\n",
              " [0.864621164683782],\n",
              " [0.8846587351283657],\n",
              " [0.8836318096430806],\n",
              " [0.8806261740763932],\n",
              " [0.8901941139636818],\n",
              " [0.8916468378209141],\n",
              " [0.9173700688791484],\n",
              " [0.9784345648090169],\n",
              " [0.9933375078271758],\n",
              " [0.9829931120851596],\n",
              " [0.9999999999999998],\n",
              " [0.9848465873512835],\n",
              " [0.9828177833437695],\n",
              " [0.05560425798371943],\n",
              " [0.06847839699436442],\n",
              " [0.061515341264871626],\n",
              " [0.03516593613024416],\n",
              " [0.03536631183468997],\n",
              " [0.01497808390732619],\n",
              " [0.02624921728240448],\n",
              " [0.01665623043206005],\n",
              " [0.012924232936756375],\n",
              " [0.02132748904195364],\n",
              " [0.021790857858484614],\n",
              " [0.013249843456480837],\n",
              " [0.008766437069505306],\n",
              " [0.0],\n",
              " [0.008115216030056327],\n",
              " [0.012448340638697541],\n",
              " [0.0007013149655604178],\n",
              " [0.0034564809016906506],\n",
              " [0.013625547902316792],\n",
              " [0.020338134001252284],\n",
              " [0.018159048215403872],\n",
              " [0.022467125860989312],\n",
              " [0.024921728240450802],\n",
              " [0.015479023168440798],\n",
              " [0.024195366311834665],\n",
              " [0.01582968065122098],\n",
              " [0.020638697557921082],\n",
              " [0.02036318096430806],\n",
              " [0.025372573575453916],\n",
              " [0.04398246712586096],\n",
              " [0.035716969317470204],\n",
              " [0.03594239198497179],\n",
              " [0.03474013775829676],\n",
              " [0.03050720100187848],\n",
              " [0.022892924232936707],\n",
              " [0.02672510958046337],\n",
              " [0.025122103944896668],\n",
              " [0.02231684408265494],\n",
              " [0.02053850970569815],\n",
              " [0.02056355666875387],\n",
              " [0.024445835942391914],\n",
              " [0.010920475892298054],\n",
              " [0.021239824671258567],\n",
              " [0.005059486537257296],\n",
              " [0.004834063869755767],\n",
              " [0.009016906700062555],\n",
              " [0.020313087038196564],\n",
              " [0.0305322479649342],\n",
              " [0.02968065122103941],\n",
              " [0.023744520976831496],\n",
              " [0.022867877269880987],\n",
              " [0.03168440826549773],\n",
              " [0.030983093299937314],\n",
              " [0.031108328115216022],\n",
              " [0.03371321227301183],\n",
              " [0.031433938634940484],\n",
              " [0.02802755165936127],\n",
              " [0.02955541640576076],\n",
              " [0.02629931120851592],\n",
              " [0.01755792110206633],\n",
              " [0.02086412022542261],\n",
              " [0.02301815904821536],\n",
              " [0.02442078897933625],\n",
              " [0.03058234189104564],\n",
              " [0.039774577332498395],\n",
              " [0.04067626800250468],\n",
              " [0.04032561051972444],\n",
              " [0.03859737006887909],\n",
              " [0.04235441452723854],\n",
              " [0.043932373199749464],\n",
              " [0.03742016280525984],\n",
              " [0.0410770194113963],\n",
              " [0.038998121477770764],\n",
              " [0.03742016280525984],\n",
              " [0.052698810269254825],\n",
              " [0.052523481527864735],\n",
              " [0.054752661239824585],\n",
              " [0.049630557294927935],\n",
              " [0.053575453976205334],\n",
              " [0.0627175954915466],\n",
              " [0.06041327489041953],\n",
              " [0.06294301815904818],\n",
              " [0.07476518472135252],\n",
              " [0.07020663744520972],\n",
              " [0.06732623669380083],\n",
              " [0.06474639949906069],\n",
              " [0.05653099561678143],\n",
              " [0.06053850970569813],\n",
              " [0.04949279899812142],\n",
              " [0.060313087038196544],\n",
              " [0.06314339386349405],\n",
              " [0.05545397620538506],\n",
              " [0.055003130870381944],\n",
              " [0.06023794614902933],\n",
              " [0.05527864746399497],\n",
              " [0.05084533500313082],\n",
              " [0.052573575453976173],\n",
              " [0.06309329993738255],\n",
              " [0.07521603005635563],\n",
              " [0.0807263619286161],\n",
              " [0.09036944270507191],\n",
              " [0.09097056981840945],\n",
              " [0.08821540388227922],\n",
              " [0.07576706324358168],\n",
              " [0.06291797119599246],\n",
              " [0.06837820914214143],\n",
              " [0.07050720100187852],\n",
              " [0.06787726988102688],\n",
              " [0.07651847213525353],\n",
              " [0.07494051346274255],\n",
              " [0.07531621790857851],\n",
              " [0.07306199123356288],\n",
              " [0.07150907952410762],\n",
              " [0.0708578584846587],\n",
              " [0.07145898559799624],\n",
              " [0.06599874765184716],\n",
              " ...]"
            ]
          },
          "metadata": {},
          "execution_count": 216
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(day_new, scaler.inverse_transform(df1[1158:])) \n",
        "plt.plot(day_pred, scaler.inverse_transform(lst_output))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "x-2GOdcjZtZF",
        "outputId": "41a5c859-9537-4986-80d1-ea264e8ebf59"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f3e0205c790>]"
            ]
          },
          "metadata": {},
          "execution_count": 218
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}