Task 1 Stock Market Prediction and Forcasting using LSTM.ipynb

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      "name": "Task 1: Stock_Market_Prediction_and_Forecasting_using_LSTM.ipynb",
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      "source": [
        "<h1>Task 1 : Stock Market Prediction And Forecasting using LSTM</h1>\n",
        "\n",
        "<p>Krithika Naidu | Data Science<p>\n",
        "# LGMVIP"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JYzLc-oSobyX"
      },
      "source": [
        "Stock Market Prediction and Forecasting using LSTM"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v2zb91Y1IQmk"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import math\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.metrics import mean_squared_error\n",
        "import tensorflow as tf\n",
        "from tensorflow.python.keras.models import Sequential\n",
        "from tensorflow.python.keras.layers import Dense\n",
        "from tensorflow.python.keras.layers import LSTM"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nEDEYM5qIdcg"
      },
      "source": [
        "import csv"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uYs_tkUyIpWR",
        "outputId": "0caa0795-327d-44b4-fb3d-18b2ece7e9b2"
      },
      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/mwitiderrick/stockprice/master/NSE-TATAGLOBAL.csv')\n",
        "print(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "            Date    Open    High  ...   Close  Total Trade Quantity  Turnover (Lacs)\n",
            "0     2018-09-28  234.05  235.95  ...  233.75               3069914          7162.35\n",
            "1     2018-09-27  234.55  236.80  ...  233.25               5082859         11859.95\n",
            "2     2018-09-26  240.00  240.00  ...  234.25               2240909          5248.60\n",
            "3     2018-09-25  233.30  236.75  ...  236.10               2349368          5503.90\n",
            "4     2018-09-24  233.55  239.20  ...  233.30               3423509          7999.55\n",
            "...          ...     ...     ...  ...     ...                   ...              ...\n",
            "2030  2010-07-27  117.60  119.50  ...  118.65                586100           694.98\n",
            "2031  2010-07-26  120.10  121.00  ...  117.60                658440           780.01\n",
            "2032  2010-07-23  121.80  121.95  ...  120.65                281312           340.31\n",
            "2033  2010-07-22  120.30  122.00  ...  120.90                293312           355.17\n",
            "2034  2010-07-21  122.10  123.00  ...  121.55                658666           803.56\n",
            "\n",
            "[2035 rows x 8 columns]\n"
          ]
        }
      ]
    },
    {
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        "outputId": "ae7e1520-558b-4818-a900-6e9ba71c0392"
      },
      "source": [
        "df = df.dropna()\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Last</th>\n",
              "      <th>Close</th>\n",
              "      <th>Total Trade Quantity</th>\n",
              "      <th>Turnover (Lacs)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2018-09-28</td>\n",
              "      <td>234.05</td>\n",
              "      <td>235.95</td>\n",
              "      <td>230.20</td>\n",
              "      <td>233.50</td>\n",
              "      <td>233.75</td>\n",
              "      <td>3069914</td>\n",
              "      <td>7162.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2018-09-27</td>\n",
              "      <td>234.55</td>\n",
              "      <td>236.80</td>\n",
              "      <td>231.10</td>\n",
              "      <td>233.80</td>\n",
              "      <td>233.25</td>\n",
              "      <td>5082859</td>\n",
              "      <td>11859.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2018-09-26</td>\n",
              "      <td>240.00</td>\n",
              "      <td>240.00</td>\n",
              "      <td>232.50</td>\n",
              "      <td>235.00</td>\n",
              "      <td>234.25</td>\n",
              "      <td>2240909</td>\n",
              "      <td>5248.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2018-09-25</td>\n",
              "      <td>233.30</td>\n",
              "      <td>236.75</td>\n",
              "      <td>232.00</td>\n",
              "      <td>236.25</td>\n",
              "      <td>236.10</td>\n",
              "      <td>2349368</td>\n",
              "      <td>5503.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2018-09-24</td>\n",
              "      <td>233.55</td>\n",
              "      <td>239.20</td>\n",
              "      <td>230.75</td>\n",
              "      <td>234.00</td>\n",
              "      <td>233.30</td>\n",
              "      <td>3423509</td>\n",
              "      <td>7999.55</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            "text/plain": [
              "         Date    Open    High  ...   Close  Total Trade Quantity  Turnover (Lacs)\n",
              "0  2018-09-28  234.05  235.95  ...  233.75               3069914          7162.35\n",
              "1  2018-09-27  234.55  236.80  ...  233.25               5082859         11859.95\n",
              "2  2018-09-26  240.00  240.00  ...  234.25               2240909          5248.60\n",
              "3  2018-09-25  233.30  236.75  ...  236.10               2349368          5503.90\n",
              "4  2018-09-24  233.55  239.20  ...  233.30               3423509          7999.55\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
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        "id": "WjkbhQ8GKHqk",
        "outputId": "335762bb-8a88-4468-c1a0-a99e71bb12cf"
      },
      "source": [
        "df.tail()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Last</th>\n",
              "      <th>Close</th>\n",
              "      <th>Total Trade Quantity</th>\n",
              "      <th>Turnover (Lacs)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2030</th>\n",
              "      <td>2010-07-27</td>\n",
              "      <td>117.6</td>\n",
              "      <td>119.50</td>\n",
              "      <td>112.00</td>\n",
              "      <td>118.80</td>\n",
              "      <td>118.65</td>\n",
              "      <td>586100</td>\n",
              "      <td>694.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2031</th>\n",
              "      <td>2010-07-26</td>\n",
              "      <td>120.1</td>\n",
              "      <td>121.00</td>\n",
              "      <td>117.10</td>\n",
              "      <td>117.10</td>\n",
              "      <td>117.60</td>\n",
              "      <td>658440</td>\n",
              "      <td>780.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2032</th>\n",
              "      <td>2010-07-23</td>\n",
              "      <td>121.8</td>\n",
              "      <td>121.95</td>\n",
              "      <td>120.25</td>\n",
              "      <td>120.35</td>\n",
              "      <td>120.65</td>\n",
              "      <td>281312</td>\n",
              "      <td>340.31</td>\n",
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              "    <tr>\n",
              "      <th>2033</th>\n",
              "      <td>2010-07-22</td>\n",
              "      <td>120.3</td>\n",
              "      <td>122.00</td>\n",
              "      <td>120.25</td>\n",
              "      <td>120.75</td>\n",
              "      <td>120.90</td>\n",
              "      <td>293312</td>\n",
              "      <td>355.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2034</th>\n",
              "      <td>2010-07-21</td>\n",
              "      <td>122.1</td>\n",
              "      <td>123.00</td>\n",
              "      <td>121.05</td>\n",
              "      <td>121.10</td>\n",
              "      <td>121.55</td>\n",
              "      <td>658666</td>\n",
              "      <td>803.56</td>\n",
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              "            Date   Open    High  ...   Close  Total Trade Quantity  Turnover (Lacs)\n",
              "2030  2010-07-27  117.6  119.50  ...  118.65                586100           694.98\n",
              "2031  2010-07-26  120.1  121.00  ...  117.60                658440           780.01\n",
              "2032  2010-07-23  121.8  121.95  ...  120.65                281312           340.31\n",
              "2033  2010-07-22  120.3  122.00  ...  120.90                293312           355.17\n",
              "2034  2010-07-21  122.1  123.00  ...  121.55                658666           803.56\n",
              "\n",
              "[5 rows x 8 columns]"
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          "execution_count": 9
        }
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        "id": "oPuIPfq4KT-j",
        "outputId": "c40a30ca-e17b-46e9-f783-b31ae99ec3c9"
      },
      "source": [
        "print(df.index)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
            "            ...\n",
            "            2025, 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034],\n",
            "           dtype='int64', length=2035)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JwXrMx5VKlYt",
        "outputId": "29d7df4e-4d1d-49ee-81e2-b777d77f0065"
      },
      "source": [
        "print(df.shape)\n",
        "print(df.size)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(2035, 8)\n",
            "16280\n"
          ]
        }
      ]
    },
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        "outputId": "9f6b4a4c-dcc4-4cda-e850-724e3af65f74"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Date', 'Open', 'High', 'Low', 'Last', 'Close', 'Total Trade Quantity',\n",
              "       'Turnover (Lacs)'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "qRLBnVjcLFXF",
        "outputId": "1ca9feeb-b518-4ddb-bf1c-8622e6dc6212"
      },
      "source": [
        "df.info"
      ],
      "execution_count": null,
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.info of             Date    Open    High  ...   Close  Total Trade Quantity  Turnover (Lacs)\n",
              "0     2018-09-28  234.05  235.95  ...  233.75               3069914          7162.35\n",
              "1     2018-09-27  234.55  236.80  ...  233.25               5082859         11859.95\n",
              "2     2018-09-26  240.00  240.00  ...  234.25               2240909          5248.60\n",
              "3     2018-09-25  233.30  236.75  ...  236.10               2349368          5503.90\n",
              "4     2018-09-24  233.55  239.20  ...  233.30               3423509          7999.55\n",
              "...          ...     ...     ...  ...     ...                   ...              ...\n",
              "2030  2010-07-27  117.60  119.50  ...  118.65                586100           694.98\n",
              "2031  2010-07-26  120.10  121.00  ...  117.60                658440           780.01\n",
              "2032  2010-07-23  121.80  121.95  ...  120.65                281312           340.31\n",
              "2033  2010-07-22  120.30  122.00  ...  120.90                293312           355.17\n",
              "2034  2010-07-21  122.10  123.00  ...  121.55                658666           803.56\n",
              "\n",
              "[2035 rows x 8 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
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        },
        "id": "IbBFH8WeLJy3",
        "outputId": "c4bdd6fb-2c33-4bd4-ce02-5c8d8c1cc140"
      },
      "source": [
        "df_close = df['Close']\n",
        "df_close.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2035,)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        },
        "id": "KrbWoPVGLSf9",
        "outputId": "320fa098-138a-4197-a388-42fbc4f911f1"
      },
      "source": [
        "df_close"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       233.75\n",
              "1       233.25\n",
              "2       234.25\n",
              "3       236.10\n",
              "4       233.30\n",
              "         ...  \n",
              "2030    118.65\n",
              "2031    117.60\n",
              "2032    120.65\n",
              "2033    120.90\n",
              "2034    121.55\n",
              "Name: Close, Length: 2035, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        },
        "id": "Jwr43dtKLiSS",
        "outputId": "4bb476ba-ec00-444b-8058-0274e4785a34"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date                    0\n",
              "Open                    0\n",
              "High                    0\n",
              "Low                     0\n",
              "Last                    0\n",
              "Close                   0\n",
              "Total Trade Quantity    0\n",
              "Turnover (Lacs)         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
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          "height": 283
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        "id": "O6baf-VLLn0Z",
        "outputId": "037644a5-67cb-429b-8ff8-d6b82ec6136d"
      },
      "source": [
        "plt.plot(df_close)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f3624f59e50>]"
            ]
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          "metadata": {},
          "execution_count": 17
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        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BUWF0U5hcSXL",
        "outputId": "1be36c55-f479-4274-f3cf-81d2edb97e75"
      },
      "source": [
        "scaler = MinMaxScaler(feature_range = (0,1))\n",
        "df_close = scaler.fit_transform(np.array(df_close).reshape(-1,1))\n",
        "\n",
        "#Split the data into train and test split\n",
        "training_size = int(len(df_close) * 0.75)\n",
        "test_size = len(df_close) - training_size\n",
        "train_data, test_data = df_close[0:training_size,:], df_close[training_size:len(df_close),:1]\n",
        "\n",
        "def create_dataset(dataset, time_step = 1):\n",
        "    dataX, dataY = [], []\n",
        "    for i in range(len(dataset) - time_step - 1):\n",
        "        a = dataset[i:(i+time_step), 0]\n",
        "        dataX.append(a)\n",
        "        dataY.append(dataset[i+time_step, 0])\n",
        "    return np.array(dataX), np.array(dataY)\n",
        "\n",
        "time_step = 100\n",
        "x_train, y_train = create_dataset(train_data, time_step)\n",
        "x_test, y_test = create_dataset(test_data, time_step)\n",
        "\n",
        "#Reshape the input to be [samples, time steps, features] which is the requirement of LSTM\n",
        "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)\n",
        "\n",
        "#Create the LSTM Model\n",
        "model = Sequential()\n",
        "model.add(LSTM(50, return_sequences = True, input_shape = (100,1)))\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')\n",
        "\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "lstm (LSTM)                  (None, 100, 50)           10400     \n",
            "_________________________________________________________________\n",
            "lstm_1 (LSTM)                (None, 100, 50)           20200     \n",
            "_________________________________________________________________\n",
            "lstm_2 (LSTM)                (None, 50)                20200     \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 51        \n",
            "=================================================================\n",
            "Total params: 50,851\n",
            "Trainable params: 50,851\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3eEWzfvrL1G8",
        "outputId": "d85109de-4837-4bea-ccd9-2b05377db126"
      },
      "source": [
        "model.fit(x_train, y_train, validation_data = (x_test, y_test), epochs = 100, batch_size = 64, verbose = 1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "23/23 [==============================] - 17s 418ms/step - loss: 0.0249 - val_loss: 0.0081\n",
            "Epoch 2/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 0.0026 - val_loss: 9.8671e-04\n",
            "Epoch 3/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 0.0015 - val_loss: 0.0015\n",
            "Epoch 4/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 0.0014 - val_loss: 0.0014\n",
            "Epoch 5/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 0.0013 - val_loss: 0.0014\n",
            "Epoch 6/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 0.0012 - val_loss: 0.0015\n",
            "Epoch 7/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 0.0012 - val_loss: 9.8541e-04\n",
            "Epoch 8/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 0.0011 - val_loss: 0.0011\n",
            "Epoch 9/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 0.0010 - val_loss: 0.0011\n",
            "Epoch 10/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 9.6401e-04 - val_loss: 8.8431e-04\n",
            "Epoch 11/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 9.7051e-04 - val_loss: 0.0011\n",
            "Epoch 12/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 8.7970e-04 - val_loss: 6.1860e-04\n",
            "Epoch 13/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 9.8308e-04 - val_loss: 8.1365e-04\n",
            "Epoch 14/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 8.6582e-04 - val_loss: 8.8168e-04\n",
            "Epoch 15/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 8.5631e-04 - val_loss: 7.6471e-04\n",
            "Epoch 16/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 8.9753e-04 - val_loss: 6.6216e-04\n",
            "Epoch 17/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 7.7335e-04 - val_loss: 9.0191e-04\n",
            "Epoch 18/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 7.2652e-04 - val_loss: 7.4329e-04\n",
            "Epoch 19/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 6.9403e-04 - val_loss: 6.4350e-04\n",
            "Epoch 20/100\n",
            "23/23 [==============================] - 9s 378ms/step - loss: 7.3059e-04 - val_loss: 9.6161e-04\n",
            "Epoch 21/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 6.7667e-04 - val_loss: 7.1891e-04\n",
            "Epoch 22/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 6.5377e-04 - val_loss: 8.5077e-04\n",
            "Epoch 23/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 7.8365e-04 - val_loss: 7.5281e-04\n",
            "Epoch 24/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 6.1356e-04 - val_loss: 9.6311e-04\n",
            "Epoch 25/100\n",
            "23/23 [==============================] - 9s 378ms/step - loss: 6.4958e-04 - val_loss: 6.4432e-04\n",
            "Epoch 26/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 5.7689e-04 - val_loss: 7.4456e-04\n",
            "Epoch 27/100\n",
            "23/23 [==============================] - 9s 383ms/step - loss: 5.8305e-04 - val_loss: 6.7024e-04\n",
            "Epoch 28/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 5.4969e-04 - val_loss: 6.7455e-04\n",
            "Epoch 29/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 5.4862e-04 - val_loss: 7.9753e-04\n",
            "Epoch 30/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 6.2925e-04 - val_loss: 5.5629e-04\n",
            "Epoch 31/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 5.1656e-04 - val_loss: 5.5051e-04\n",
            "Epoch 32/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 5.1907e-04 - val_loss: 4.3899e-04\n",
            "Epoch 33/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 5.8575e-04 - val_loss: 5.6290e-04\n",
            "Epoch 34/100\n",
            "23/23 [==============================] - 9s 378ms/step - loss: 5.3591e-04 - val_loss: 5.7914e-04\n",
            "Epoch 35/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 4.5247e-04 - val_loss: 6.8668e-04\n",
            "Epoch 36/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 4.5825e-04 - val_loss: 5.0297e-04\n",
            "Epoch 37/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 4.6399e-04 - val_loss: 5.1945e-04\n",
            "Epoch 38/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 4.8067e-04 - val_loss: 4.4733e-04\n",
            "Epoch 39/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 5.1492e-04 - val_loss: 3.9811e-04\n",
            "Epoch 40/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 4.6302e-04 - val_loss: 4.3585e-04\n",
            "Epoch 41/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 4.1999e-04 - val_loss: 4.1365e-04\n",
            "Epoch 42/100\n",
            "23/23 [==============================] - 9s 378ms/step - loss: 3.5916e-04 - val_loss: 3.8075e-04\n",
            "Epoch 43/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 3.5385e-04 - val_loss: 4.0037e-04\n",
            "Epoch 44/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 3.7313e-04 - val_loss: 3.6552e-04\n",
            "Epoch 45/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 3.3579e-04 - val_loss: 4.2078e-04\n",
            "Epoch 46/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 3.2994e-04 - val_loss: 3.1114e-04\n",
            "Epoch 47/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 3.1732e-04 - val_loss: 3.7872e-04\n",
            "Epoch 48/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 2.9960e-04 - val_loss: 2.9371e-04\n",
            "Epoch 49/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 3.1122e-04 - val_loss: 2.7675e-04\n",
            "Epoch 50/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 2.7060e-04 - val_loss: 3.9066e-04\n",
            "Epoch 51/100\n",
            "23/23 [==============================] - 9s 384ms/step - loss: 2.8411e-04 - val_loss: 2.6706e-04\n",
            "Epoch 52/100\n",
            "23/23 [==============================] - 9s 384ms/step - loss: 2.6010e-04 - val_loss: 3.8261e-04\n",
            "Epoch 53/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 2.6627e-04 - val_loss: 2.9451e-04\n",
            "Epoch 54/100\n",
            "23/23 [==============================] - 9s 384ms/step - loss: 2.5155e-04 - val_loss: 4.4691e-04\n",
            "Epoch 55/100\n",
            "23/23 [==============================] - 9s 384ms/step - loss: 2.5282e-04 - val_loss: 3.1516e-04\n",
            "Epoch 56/100\n",
            "23/23 [==============================] - 9s 385ms/step - loss: 2.4007e-04 - val_loss: 2.2432e-04\n",
            "Epoch 57/100\n",
            "23/23 [==============================] - 9s 384ms/step - loss: 2.6797e-04 - val_loss: 2.8473e-04\n",
            "Epoch 58/100\n",
            "23/23 [==============================] - 9s 383ms/step - loss: 2.5941e-04 - val_loss: 2.3289e-04\n",
            "Epoch 59/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 2.4837e-04 - val_loss: 2.1711e-04\n",
            "Epoch 60/100\n",
            "23/23 [==============================] - 9s 374ms/step - loss: 2.6877e-04 - val_loss: 2.2034e-04\n",
            "Epoch 61/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.6918e-04 - val_loss: 1.8926e-04\n",
            "Epoch 62/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.1961e-04 - val_loss: 2.3782e-04\n",
            "Epoch 63/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.3575e-04 - val_loss: 2.7463e-04\n",
            "Epoch 64/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.1753e-04 - val_loss: 2.8913e-04\n",
            "Epoch 65/100\n",
            "23/23 [==============================] - 9s 374ms/step - loss: 2.0688e-04 - val_loss: 1.6956e-04\n",
            "Epoch 66/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.4070e-04 - val_loss: 2.3238e-04\n",
            "Epoch 67/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.4163e-04 - val_loss: 2.0028e-04\n",
            "Epoch 68/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.0851e-04 - val_loss: 1.6630e-04\n",
            "Epoch 69/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.4349e-04 - val_loss: 2.0330e-04\n",
            "Epoch 70/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.0315e-04 - val_loss: 2.7242e-04\n",
            "Epoch 71/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.1025e-04 - val_loss: 1.8529e-04\n",
            "Epoch 72/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.0338e-04 - val_loss: 1.6478e-04\n",
            "Epoch 73/100\n",
            "23/23 [==============================] - 9s 378ms/step - loss: 2.2876e-04 - val_loss: 2.0034e-04\n",
            "Epoch 74/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.2546e-04 - val_loss: 1.5065e-04\n",
            "Epoch 75/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.0909e-04 - val_loss: 1.6549e-04\n",
            "Epoch 76/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.2737e-04 - val_loss: 2.6997e-04\n",
            "Epoch 77/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.1660e-04 - val_loss: 1.5981e-04\n",
            "Epoch 78/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.6134e-04 - val_loss: 2.4495e-04\n",
            "Epoch 79/100\n",
            "23/23 [==============================] - 9s 376ms/step - loss: 2.3936e-04 - val_loss: 2.7288e-04\n",
            "Epoch 80/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.1790e-04 - val_loss: 1.6138e-04\n",
            "Epoch 81/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 1.9218e-04 - val_loss: 2.0210e-04\n",
            "Epoch 82/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.4097e-04 - val_loss: 1.5394e-04\n",
            "Epoch 83/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.5684e-04 - val_loss: 2.7519e-04\n",
            "Epoch 84/100\n",
            "23/23 [==============================] - 9s 375ms/step - loss: 2.2278e-04 - val_loss: 1.6234e-04\n",
            "Epoch 85/100\n",
            "23/23 [==============================] - 9s 374ms/step - loss: 1.9976e-04 - val_loss: 1.4901e-04\n",
            "Epoch 86/100\n",
            "23/23 [==============================] - 9s 380ms/step - loss: 1.9826e-04 - val_loss: 1.5528e-04\n",
            "Epoch 87/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 2.0887e-04 - val_loss: 1.4228e-04\n",
            "Epoch 88/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.0480e-04 - val_loss: 1.3987e-04\n",
            "Epoch 89/100\n",
            "23/23 [==============================] - 9s 383ms/step - loss: 1.9776e-04 - val_loss: 1.6367e-04\n",
            "Epoch 90/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 1.8491e-04 - val_loss: 1.3565e-04\n",
            "Epoch 91/100\n",
            "23/23 [==============================] - 9s 377ms/step - loss: 2.6681e-04 - val_loss: 1.8756e-04\n",
            "Epoch 92/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 2.0148e-04 - val_loss: 1.4791e-04\n",
            "Epoch 93/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 1.9912e-04 - val_loss: 1.8466e-04\n",
            "Epoch 94/100\n",
            "23/23 [==============================] - 9s 383ms/step - loss: 2.1835e-04 - val_loss: 1.5894e-04\n",
            "Epoch 95/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 2.2060e-04 - val_loss: 2.5957e-04\n",
            "Epoch 96/100\n",
            "23/23 [==============================] - 9s 382ms/step - loss: 2.1597e-04 - val_loss: 1.7496e-04\n",
            "Epoch 97/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 1.9883e-04 - val_loss: 1.7381e-04\n",
            "Epoch 98/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 2.1580e-04 - val_loss: 2.2536e-04\n",
            "Epoch 99/100\n",
            "23/23 [==============================] - 9s 379ms/step - loss: 2.5770e-04 - val_loss: 1.5569e-04\n",
            "Epoch 100/100\n",
            "23/23 [==============================] - 9s 381ms/step - loss: 3.1526e-04 - val_loss: 1.6039e-04\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7f361f768dd0>"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JL7cLTCxMU-A",
        "outputId": "c1c1df43-a711-4ac2-fde3-34d53b11e23f"
      },
      "source": [
        "#Lets predict and check performance metrics\n",
        "train_predict = model.predict(x_train)\n",
        "test_predict = model.predict(x_test)\n",
        "\n",
        "#Transform back to original form\n",
        "train_predict = scaler.inverse_transform(train_predict)\n",
        "test_predict = scaler.inverse_transform(test_predict)\n",
        "\n",
        "#Calculate RMSE performance metrics\n",
        "math.sqrt(mean_squared_error(y_train, train_predict))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "163.78480694316863"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-7T3aLcnS_1-",
        "outputId": "c9ff98df-092a-46ae-f139-bd45d586599a"
      },
      "source": [
        "#Test Data RMSE\n",
        "math.sqrt(mean_squared_error(y_test, test_predict))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "105.5807597941825"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "flUXFlxmaEkl",
        "outputId": "73f9f1be-db8b-4f40-e1f3-8275a84b784f"
      },
      "source": [
        "#Plotting\n",
        "\n",
        "#Shift train prediction for plotting\n",
        "look_back = 100\n",
        "trainPredictPlot = np.empty_like(df_close)\n",
        "trainPredictPlot[:,:] = np.nan\n",
        "trainPredictPlot[look_back:len(train_predict) + look_back, :] = train_predict\n",
        "\n",
        "#Shift test prediction for plotting\n",
        "testPredictPlot = np.empty_like(df_close)\n",
        "testPredictPlot[:,:] = np.nan\n",
        "testPredictPlot[len(train_predict) + (look_back * 2)+1:len(df_close) - 1, :] = test_predict\n",
        "\n",
        "#Plot baseline and predictions\n",
        "plt.plot(scaler.inverse_transform(df_close))\n",
        "plt.plot(trainPredictPlot)\n",
        "plt.plot(testPredictPlot)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oFS2lRl3aFsQ",
        "outputId": "b9a23742-a890-4641-b26f-1a485ce83dfb"
      },
      "source": [
        "len(test_data), x_test.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(509, (408, 100, 1))"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y5SNDLiYaJ2p",
        "outputId": "77a14a89-e9a4-42bf-ece5-c21690394b0e"
      },
      "source": [
        "x_input = test_data[207:].reshape(1,-1)\n",
        "x_input.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 302)"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e5fH5GAjaL1m",
        "outputId": "87ec6df1-5b5c-4449-f5e5-53c241117d8b"
      },
      "source": [
        "temp_input = list(x_input)\n",
        "temp_input = temp_input[0].tolist()\n",
        "\n",
        "lst_output=[]\n",
        "n_steps=300\n",
        "nextNumberOfDays = 30\n",
        "i=0\n",
        "\n",
        "while(i<nextNumberOfDays):\n",
        "    \n",
        "    if(len(temp_input)>300):\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",
        "        lst_output.extend(yhat.tolist())\n",
        "        i=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",
        "    \n",
        "\n",
        "print(lst_output)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 day input [0.02246732 0.03125    0.02348856 0.0249183  0.02144608 0.04840686\n",
            " 0.04575163 0.03962418 0.03921569 0.04758987 0.04513889 0.04166667\n",
            " 0.04125817 0.05044935 0.05555556 0.05494281 0.05412582 0.0435049\n",
            " 0.04799837 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092\n",
            " 0.04554739 0.03941993 0.02716503 0.03125    0.05882353 0.07148693\n",
            " 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817\n",
            " 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837\n",
            " 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549  0.08169935\n",
            " 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261\n",
            " 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824\n",
            " 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219\n",
            " 0.03941993 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948\n",
            " 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569\n",
            " 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804\n",
            " 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203\n",
            " 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641\n",
            " 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085\n",
            " 0.0692402  0.0755719  0.07781863 0.08088235 0.08843954 0.09395425\n",
            " 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261\n",
            " 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366\n",
            " 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876\n",
            " 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993\n",
            " 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908\n",
            " 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294\n",
            " 0.04105392 0.03390523 0.03125    0.02634804 0.05861928 0.06311275\n",
            " 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752 0.0557598\n",
            " 0.0439134  0.02920752 0.02818627 0.04718137 0.06045752 0.05861928\n",
            " 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817\n",
            " 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222\n",
            " 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974\n",
            " 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686\n",
            " 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222\n",
            " 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667\n",
            " 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889\n",
            " 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647\n",
            " 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399\n",
            " 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673\n",
            " 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458\n",
            " 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444\n",
            " 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268\n",
            " 0.21568627 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817\n",
            " 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013\n",
            " 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458\n",
            " 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072\n",
            " 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288\n",
            " 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634\n",
            " 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451\n",
            " 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673\n",
            " 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908\n",
            " 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967]\n",
            "WARNING:tensorflow:Model was constructed with shape (None, 100, 1) for input KerasTensor(type_spec=TensorSpec(shape=(None, 100, 1), dtype=tf.float32, name='lstm_input'), name='lstm_input', description=\"created by layer 'lstm_input'\"), but it was called on an input with incompatible shape (None, 300, 1).\n",
            "0 day output [[0.16633245]]\n",
            "1 day input [0.03125    0.02348856 0.0249183  0.02144608 0.04840686 0.04575163\n",
            " 0.03962418 0.03921569 0.04758987 0.04513889 0.04166667 0.04125817\n",
            " 0.05044935 0.05555556 0.05494281 0.05412582 0.0435049  0.04799837\n",
            " 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739\n",
            " 0.03941993 0.02716503 0.03125    0.05882353 0.07148693 0.08721405\n",
            " 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327\n",
            " 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451\n",
            " 0.09803922 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654\n",
            " 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183\n",
            " 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745\n",
            " 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993\n",
            " 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948 0.07230392\n",
            " 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582\n",
            " 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804 0.02410131\n",
            " 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922\n",
            " 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444\n",
            " 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402\n",
            " 0.0755719  0.07781863 0.08088235 0.08843954 0.09395425 0.09599673\n",
            " 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477\n",
            " 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745\n",
            " 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118\n",
            " 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471\n",
            " 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275\n",
            " 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294 0.04105392\n",
            " 0.03390523 0.03125    0.02634804 0.05861928 0.06311275 0.0620915\n",
            " 0.05535131 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134\n",
            " 0.02920752 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301\n",
            " 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542\n",
            " 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497\n",
            " 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386\n",
            " 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464\n",
            " 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418\n",
            " 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621\n",
            " 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667\n",
            " 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405\n",
            " 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993\n",
            " 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556\n",
            " 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307\n",
            " 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163\n",
            " 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627\n",
            " 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275\n",
            " 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386\n",
            " 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314\n",
            " 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399\n",
            " 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046\n",
            " 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758\n",
            " 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092\n",
            " 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242\n",
            " 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928\n",
            " 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245]\n",
            "1 day output [[0.16762973]]\n",
            "2 day input [0.02348856 0.0249183  0.02144608 0.04840686 0.04575163 0.03962418\n",
            " 0.03921569 0.04758987 0.04513889 0.04166667 0.04125817 0.05044935\n",
            " 0.05555556 0.05494281 0.05412582 0.0435049  0.04799837 0.05147059\n",
            " 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993\n",
            " 0.02716503 0.03125    0.05882353 0.07148693 0.08721405 0.08986928\n",
            " 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863\n",
            " 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922\n",
            " 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627\n",
            " 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863\n",
            " 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549\n",
            " 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993 0.0379902\n",
            " 0.04656863 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288\n",
            " 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366\n",
            " 0.05167484 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601\n",
            " 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575\n",
            " 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235\n",
            " 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719\n",
            " 0.07781863 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131\n",
            " 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902\n",
            " 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582\n",
            " 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144\n",
            " 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471 0.06678922\n",
            " 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085\n",
            " 0.05167484 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523\n",
            " 0.03125    0.02634804 0.05861928 0.06311275 0.0620915  0.05535131\n",
            " 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752\n",
            " 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346\n",
            " 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967\n",
            " 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248\n",
            " 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327\n",
            " 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732\n",
            " 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111\n",
            " 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902\n",
            " 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438\n",
            " 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405 0.14644608\n",
            " 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157\n",
            " 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379\n",
            " 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843\n",
            " 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242\n",
            " 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261\n",
            " 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307\n",
            " 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131\n",
            " 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065\n",
            " 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222\n",
            " 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405\n",
            " 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758 0.12479575\n",
            " 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497\n",
            " 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059\n",
            " 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327\n",
            " 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973]\n",
            "2 day output [[0.16847919]]\n",
            "3 day input [0.0249183  0.02144608 0.04840686 0.04575163 0.03962418 0.03921569\n",
            " 0.04758987 0.04513889 0.04166667 0.04125817 0.05044935 0.05555556\n",
            " 0.05494281 0.05412582 0.0435049  0.04799837 0.05147059 0.05065359\n",
            " 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503\n",
            " 0.03125    0.05882353 0.07148693 0.08721405 0.08986928 0.10498366\n",
            " 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948\n",
            " 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922 0.09987745\n",
            " 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085\n",
            " 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346\n",
            " 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281\n",
            " 0.04799837 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863\n",
            " 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013\n",
            " 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484\n",
            " 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784\n",
            " 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275\n",
            " 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235 0.07700163\n",
            " 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719  0.07781863\n",
            " 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778\n",
            " 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105\n",
            " 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386\n",
            " 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549\n",
            " 0.06821895 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216\n",
            " 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484\n",
            " 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523 0.03125\n",
            " 0.02634804 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882\n",
            " 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627\n",
            " 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418\n",
            " 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967 0.10089869\n",
            " 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477\n",
            " 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373\n",
            " 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732 0.11683007\n",
            " 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137\n",
            " 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575\n",
            " 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719\n",
            " 0.13071895 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007\n",
            " 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007\n",
            " 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333\n",
            " 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399\n",
            " 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641\n",
            " 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876\n",
            " 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536\n",
            " 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961\n",
            " 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412\n",
            " 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562\n",
            " 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268\n",
            " 0.15196078 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745\n",
            " 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967\n",
            " 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353\n",
            " 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405\n",
            " 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973 0.16847919]\n",
            "3 day output [[0.16922805]]\n",
            "4 day input [0.02144608 0.04840686 0.04575163 0.03962418 0.03921569 0.04758987\n",
            " 0.04513889 0.04166667 0.04125817 0.05044935 0.05555556 0.05494281\n",
            " 0.05412582 0.0435049  0.04799837 0.05147059 0.05065359 0.03431373\n",
            " 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503 0.03125\n",
            " 0.05882353 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229\n",
            " 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134\n",
            " 0.10457516 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654\n",
            " 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085 0.08823529\n",
            " 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052\n",
            " 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837\n",
            " 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784\n",
            " 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601\n",
            " 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882\n",
            " 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784 0.02961601\n",
            " 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085\n",
            " 0.06658497 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232\n",
            " 0.06781046 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235\n",
            " 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157\n",
            " 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373\n",
            " 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745\n",
            " 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895\n",
            " 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216 0.07169118\n",
            " 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275\n",
            " 0.04003268 0.03860294 0.04105392 0.03390523 0.03125    0.02634804\n",
            " 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706\n",
            " 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137\n",
            " 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719\n",
            " 0.07700163 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092\n",
            " 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725\n",
            " 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317\n",
            " 0.12479575 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706\n",
            " 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588\n",
            " 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039\n",
            " 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895\n",
            " 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948\n",
            " 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621\n",
            " 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458\n",
            " 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248\n",
            " 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366\n",
            " 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876 0.21098856\n",
            " 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497\n",
            " 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595\n",
            " 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935\n",
            " 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065\n",
            " 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268  0.15196078\n",
            " 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059\n",
            " 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967 0.12806373\n",
            " 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856\n",
            " 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732\n",
            " 0.16319444 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805]\n",
            "4 day output [[0.16995464]]\n",
            "5 day input [0.04840686 0.04575163 0.03962418 0.03921569 0.04758987 0.04513889\n",
            " 0.04166667 0.04125817 0.05044935 0.05555556 0.05494281 0.05412582\n",
            " 0.0435049  0.04799837 0.05147059 0.05065359 0.03431373 0.04575163\n",
            " 0.04187092 0.04554739 0.03941993 0.02716503 0.03125    0.05882353\n",
            " 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392\n",
            " 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516\n",
            " 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549\n",
            " 0.08169935 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882\n",
            " 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353\n",
            " 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314\n",
            " 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784 0.07209967\n",
            " 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399\n",
            " 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049\n",
            " 0.02634804 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163\n",
            " 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497\n",
            " 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046\n",
            " 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235 0.08843954\n",
            " 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183\n",
            " 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484\n",
            " 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797\n",
            " 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402\n",
            " 0.07066993 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706\n",
            " 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268\n",
            " 0.03860294 0.04105392 0.03390523 0.03125    0.02634804 0.05861928\n",
            " 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752\n",
            " 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137 0.06045752\n",
            " 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163\n",
            " 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922\n",
            " 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007\n",
            " 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575\n",
            " 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072\n",
            " 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614\n",
            " 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438\n",
            " 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895\n",
            " 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647\n",
            " 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908\n",
            " 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556\n",
            " 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595\n",
            " 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549\n",
            " 0.2128268  0.21568627 0.20445261 0.21772876 0.21098856 0.21425654\n",
            " 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542\n",
            " 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039\n",
            " 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353\n",
            " 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219\n",
            " 0.17177288 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307\n",
            " 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768\n",
            " 0.12377451 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046\n",
            " 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235\n",
            " 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444\n",
            " 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464]\n",
            "5 day output [[0.1706922]]\n",
            "6 day input [0.04575163 0.03962418 0.03921569 0.04758987 0.04513889 0.04166667\n",
            " 0.04125817 0.05044935 0.05555556 0.05494281 0.05412582 0.0435049\n",
            " 0.04799837 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092\n",
            " 0.04554739 0.03941993 0.02716503 0.03125    0.05882353 0.07148693\n",
            " 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817\n",
            " 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837\n",
            " 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549  0.08169935\n",
            " 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261\n",
            " 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824\n",
            " 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219\n",
            " 0.03941993 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948\n",
            " 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569\n",
            " 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804\n",
            " 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203\n",
            " 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641\n",
            " 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085\n",
            " 0.0692402  0.0755719  0.07781863 0.08088235 0.08843954 0.09395425\n",
            " 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261\n",
            " 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366\n",
            " 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876\n",
            " 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993\n",
            " 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908\n",
            " 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294\n",
            " 0.04105392 0.03390523 0.03125    0.02634804 0.05861928 0.06311275\n",
            " 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752 0.0557598\n",
            " 0.0439134  0.02920752 0.02818627 0.04718137 0.06045752 0.05861928\n",
            " 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817\n",
            " 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222\n",
            " 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974\n",
            " 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686\n",
            " 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222\n",
            " 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667\n",
            " 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889\n",
            " 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647\n",
            " 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399\n",
            " 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673\n",
            " 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458\n",
            " 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444\n",
            " 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268\n",
            " 0.21568627 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817\n",
            " 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013\n",
            " 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458\n",
            " 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072\n",
            " 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288\n",
            " 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634\n",
            " 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451\n",
            " 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673\n",
            " 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908\n",
            " 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967\n",
            " 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221]\n",
            "6 day output [[0.1714562]]\n",
            "7 day input [0.03962418 0.03921569 0.04758987 0.04513889 0.04166667 0.04125817\n",
            " 0.05044935 0.05555556 0.05494281 0.05412582 0.0435049  0.04799837\n",
            " 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739\n",
            " 0.03941993 0.02716503 0.03125    0.05882353 0.07148693 0.08721405\n",
            " 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327\n",
            " 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451\n",
            " 0.09803922 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654\n",
            " 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183\n",
            " 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745\n",
            " 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993\n",
            " 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948 0.07230392\n",
            " 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582\n",
            " 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804 0.02410131\n",
            " 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922\n",
            " 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444\n",
            " 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402\n",
            " 0.0755719  0.07781863 0.08088235 0.08843954 0.09395425 0.09599673\n",
            " 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477\n",
            " 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745\n",
            " 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118\n",
            " 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471\n",
            " 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275\n",
            " 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294 0.04105392\n",
            " 0.03390523 0.03125    0.02634804 0.05861928 0.06311275 0.0620915\n",
            " 0.05535131 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134\n",
            " 0.02920752 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301\n",
            " 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542\n",
            " 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497\n",
            " 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386\n",
            " 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464\n",
            " 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418\n",
            " 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621\n",
            " 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667\n",
            " 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405\n",
            " 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993\n",
            " 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556\n",
            " 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307\n",
            " 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163\n",
            " 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627\n",
            " 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275\n",
            " 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386\n",
            " 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314\n",
            " 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399\n",
            " 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046\n",
            " 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758\n",
            " 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092\n",
            " 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242\n",
            " 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928\n",
            " 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245\n",
            " 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562 ]\n",
            "7 day output [[0.1722502]]\n",
            "8 day input [0.03921569 0.04758987 0.04513889 0.04166667 0.04125817 0.05044935\n",
            " 0.05555556 0.05494281 0.05412582 0.0435049  0.04799837 0.05147059\n",
            " 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993\n",
            " 0.02716503 0.03125    0.05882353 0.07148693 0.08721405 0.08986928\n",
            " 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863\n",
            " 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922\n",
            " 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627\n",
            " 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863\n",
            " 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549\n",
            " 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993 0.0379902\n",
            " 0.04656863 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288\n",
            " 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366\n",
            " 0.05167484 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601\n",
            " 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575\n",
            " 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235\n",
            " 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719\n",
            " 0.07781863 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131\n",
            " 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902\n",
            " 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582\n",
            " 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144\n",
            " 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471 0.06678922\n",
            " 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085\n",
            " 0.05167484 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523\n",
            " 0.03125    0.02634804 0.05861928 0.06311275 0.0620915  0.05535131\n",
            " 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752\n",
            " 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346\n",
            " 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967\n",
            " 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248\n",
            " 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327\n",
            " 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732\n",
            " 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111\n",
            " 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902\n",
            " 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438\n",
            " 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405 0.14644608\n",
            " 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157\n",
            " 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379\n",
            " 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843\n",
            " 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242\n",
            " 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261\n",
            " 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307\n",
            " 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131\n",
            " 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065\n",
            " 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222\n",
            " 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405\n",
            " 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758 0.12479575\n",
            " 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497\n",
            " 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059\n",
            " 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327\n",
            " 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973\n",
            " 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502 ]\n",
            "8 day output [[0.17307197]]\n",
            "9 day input [0.04758987 0.04513889 0.04166667 0.04125817 0.05044935 0.05555556\n",
            " 0.05494281 0.05412582 0.0435049  0.04799837 0.05147059 0.05065359\n",
            " 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503\n",
            " 0.03125    0.05882353 0.07148693 0.08721405 0.08986928 0.10498366\n",
            " 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948\n",
            " 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922 0.09987745\n",
            " 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085\n",
            " 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346\n",
            " 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281\n",
            " 0.04799837 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863\n",
            " 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013\n",
            " 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484\n",
            " 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784\n",
            " 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275\n",
            " 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235 0.07700163\n",
            " 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719  0.07781863\n",
            " 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778\n",
            " 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105\n",
            " 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386\n",
            " 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549\n",
            " 0.06821895 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216\n",
            " 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484\n",
            " 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523 0.03125\n",
            " 0.02634804 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882\n",
            " 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627\n",
            " 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418\n",
            " 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967 0.10089869\n",
            " 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477\n",
            " 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373\n",
            " 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732 0.11683007\n",
            " 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137\n",
            " 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575\n",
            " 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719\n",
            " 0.13071895 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007\n",
            " 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007\n",
            " 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333\n",
            " 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399\n",
            " 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641\n",
            " 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876\n",
            " 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536\n",
            " 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961\n",
            " 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412\n",
            " 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562\n",
            " 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268\n",
            " 0.15196078 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745\n",
            " 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967\n",
            " 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353\n",
            " 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405\n",
            " 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973 0.16847919\n",
            " 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197]\n",
            "9 day output [[0.17391658]]\n",
            "10 day input [0.04513889 0.04166667 0.04125817 0.05044935 0.05555556 0.05494281\n",
            " 0.05412582 0.0435049  0.04799837 0.05147059 0.05065359 0.03431373\n",
            " 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503 0.03125\n",
            " 0.05882353 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229\n",
            " 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134\n",
            " 0.10457516 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654\n",
            " 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085 0.08823529\n",
            " 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052\n",
            " 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837\n",
            " 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784\n",
            " 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601\n",
            " 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882\n",
            " 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784 0.02961601\n",
            " 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085\n",
            " 0.06658497 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232\n",
            " 0.06781046 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235\n",
            " 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157\n",
            " 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373\n",
            " 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745\n",
            " 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895\n",
            " 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216 0.07169118\n",
            " 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275\n",
            " 0.04003268 0.03860294 0.04105392 0.03390523 0.03125    0.02634804\n",
            " 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706\n",
            " 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137\n",
            " 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719\n",
            " 0.07700163 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092\n",
            " 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725\n",
            " 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317\n",
            " 0.12479575 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706\n",
            " 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588\n",
            " 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039\n",
            " 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895\n",
            " 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948\n",
            " 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621\n",
            " 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458\n",
            " 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248\n",
            " 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366\n",
            " 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876 0.21098856\n",
            " 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497\n",
            " 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595\n",
            " 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935\n",
            " 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065\n",
            " 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268  0.15196078\n",
            " 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059\n",
            " 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967 0.12806373\n",
            " 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856\n",
            " 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732\n",
            " 0.16319444 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805\n",
            " 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658]\n",
            "10 day output [[0.17477898]]\n",
            "11 day input [0.04166667 0.04125817 0.05044935 0.05555556 0.05494281 0.05412582\n",
            " 0.0435049  0.04799837 0.05147059 0.05065359 0.03431373 0.04575163\n",
            " 0.04187092 0.04554739 0.03941993 0.02716503 0.03125    0.05882353\n",
            " 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392\n",
            " 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516\n",
            " 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549\n",
            " 0.08169935 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882\n",
            " 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353\n",
            " 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314\n",
            " 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784 0.07209967\n",
            " 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399\n",
            " 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049\n",
            " 0.02634804 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163\n",
            " 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497\n",
            " 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046\n",
            " 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235 0.08843954\n",
            " 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183\n",
            " 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484\n",
            " 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797\n",
            " 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402\n",
            " 0.07066993 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706\n",
            " 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268\n",
            " 0.03860294 0.04105392 0.03390523 0.03125    0.02634804 0.05861928\n",
            " 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752\n",
            " 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137 0.06045752\n",
            " 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163\n",
            " 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922\n",
            " 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007\n",
            " 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575\n",
            " 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072\n",
            " 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614\n",
            " 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438\n",
            " 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895\n",
            " 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647\n",
            " 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908\n",
            " 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556\n",
            " 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595\n",
            " 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549\n",
            " 0.2128268  0.21568627 0.20445261 0.21772876 0.21098856 0.21425654\n",
            " 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542\n",
            " 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039\n",
            " 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353\n",
            " 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219\n",
            " 0.17177288 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307\n",
            " 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768\n",
            " 0.12377451 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046\n",
            " 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235\n",
            " 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444\n",
            " 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464\n",
            " 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898]\n",
            "11 day output [[0.17565471]]\n",
            "12 day input [0.04125817 0.05044935 0.05555556 0.05494281 0.05412582 0.0435049\n",
            " 0.04799837 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092\n",
            " 0.04554739 0.03941993 0.02716503 0.03125    0.05882353 0.07148693\n",
            " 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817\n",
            " 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837\n",
            " 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549  0.08169935\n",
            " 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261\n",
            " 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824\n",
            " 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219\n",
            " 0.03941993 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948\n",
            " 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569\n",
            " 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804\n",
            " 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203\n",
            " 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641\n",
            " 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085\n",
            " 0.0692402  0.0755719  0.07781863 0.08088235 0.08843954 0.09395425\n",
            " 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261\n",
            " 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366\n",
            " 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876\n",
            " 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993\n",
            " 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908\n",
            " 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294\n",
            " 0.04105392 0.03390523 0.03125    0.02634804 0.05861928 0.06311275\n",
            " 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752 0.0557598\n",
            " 0.0439134  0.02920752 0.02818627 0.04718137 0.06045752 0.05861928\n",
            " 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817\n",
            " 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222\n",
            " 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974\n",
            " 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686\n",
            " 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222\n",
            " 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667\n",
            " 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889\n",
            " 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647\n",
            " 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399\n",
            " 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673\n",
            " 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458\n",
            " 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444\n",
            " 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268\n",
            " 0.21568627 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817\n",
            " 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013\n",
            " 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458\n",
            " 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072\n",
            " 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288\n",
            " 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634\n",
            " 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451\n",
            " 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673\n",
            " 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908\n",
            " 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967\n",
            " 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221\n",
            " 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898 0.17565471]\n",
            "12 day output [[0.17653994]]\n",
            "13 day input [0.05044935 0.05555556 0.05494281 0.05412582 0.0435049  0.04799837\n",
            " 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739\n",
            " 0.03941993 0.02716503 0.03125    0.05882353 0.07148693 0.08721405\n",
            " 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327\n",
            " 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451\n",
            " 0.09803922 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654\n",
            " 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183\n",
            " 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745\n",
            " 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993\n",
            " 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948 0.07230392\n",
            " 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582\n",
            " 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804 0.02410131\n",
            " 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922\n",
            " 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444\n",
            " 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402\n",
            " 0.0755719  0.07781863 0.08088235 0.08843954 0.09395425 0.09599673\n",
            " 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477\n",
            " 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745\n",
            " 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118\n",
            " 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471\n",
            " 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275\n",
            " 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294 0.04105392\n",
            " 0.03390523 0.03125    0.02634804 0.05861928 0.06311275 0.0620915\n",
            " 0.05535131 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134\n",
            " 0.02920752 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301\n",
            " 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542\n",
            " 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497\n",
            " 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386\n",
            " 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464\n",
            " 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418\n",
            " 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621\n",
            " 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667\n",
            " 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405\n",
            " 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993\n",
            " 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556\n",
            " 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307\n",
            " 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163\n",
            " 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627\n",
            " 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275\n",
            " 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386\n",
            " 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314\n",
            " 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399\n",
            " 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046\n",
            " 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758\n",
            " 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092\n",
            " 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242\n",
            " 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928\n",
            " 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245\n",
            " 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562\n",
            " 0.1722502  0.17307197 0.17391658 0.17477898 0.17565471 0.17653994]\n",
            "13 day output [[0.17743164]]\n",
            "14 day input [0.05555556 0.05494281 0.05412582 0.0435049  0.04799837 0.05147059\n",
            " 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993\n",
            " 0.02716503 0.03125    0.05882353 0.07148693 0.08721405 0.08986928\n",
            " 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863\n",
            " 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922\n",
            " 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627\n",
            " 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863\n",
            " 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549\n",
            " 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993 0.0379902\n",
            " 0.04656863 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288\n",
            " 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366\n",
            " 0.05167484 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601\n",
            " 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575\n",
            " 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235\n",
            " 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719\n",
            " 0.07781863 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131\n",
            " 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902\n",
            " 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582\n",
            " 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144\n",
            " 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471 0.06678922\n",
            " 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085\n",
            " 0.05167484 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523\n",
            " 0.03125    0.02634804 0.05861928 0.06311275 0.0620915  0.05535131\n",
            " 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752\n",
            " 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346\n",
            " 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967\n",
            " 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248\n",
            " 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327\n",
            " 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732\n",
            " 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111\n",
            " 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902\n",
            " 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438\n",
            " 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405 0.14644608\n",
            " 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157\n",
            " 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379\n",
            " 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843\n",
            " 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242\n",
            " 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261\n",
            " 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307\n",
            " 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131\n",
            " 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065\n",
            " 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222\n",
            " 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405\n",
            " 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758 0.12479575\n",
            " 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497\n",
            " 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059\n",
            " 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327\n",
            " 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973\n",
            " 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502\n",
            " 0.17307197 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164]\n",
            "14 day output [[0.17832704]]\n",
            "15 day input [0.05494281 0.05412582 0.0435049  0.04799837 0.05147059 0.05065359\n",
            " 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503\n",
            " 0.03125    0.05882353 0.07148693 0.08721405 0.08986928 0.10498366\n",
            " 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948\n",
            " 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922 0.09987745\n",
            " 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085\n",
            " 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346\n",
            " 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281\n",
            " 0.04799837 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863\n",
            " 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013\n",
            " 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484\n",
            " 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784\n",
            " 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275\n",
            " 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235 0.07700163\n",
            " 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719  0.07781863\n",
            " 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778\n",
            " 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105\n",
            " 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386\n",
            " 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549\n",
            " 0.06821895 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216\n",
            " 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484\n",
            " 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523 0.03125\n",
            " 0.02634804 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882\n",
            " 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627\n",
            " 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418\n",
            " 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967 0.10089869\n",
            " 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477\n",
            " 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373\n",
            " 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732 0.11683007\n",
            " 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137\n",
            " 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575\n",
            " 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719\n",
            " 0.13071895 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007\n",
            " 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007\n",
            " 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333\n",
            " 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399\n",
            " 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641\n",
            " 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876\n",
            " 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536\n",
            " 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961\n",
            " 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412\n",
            " 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562\n",
            " 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268\n",
            " 0.15196078 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745\n",
            " 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967\n",
            " 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353\n",
            " 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405\n",
            " 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973 0.16847919\n",
            " 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197\n",
            " 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704]\n",
            "15 day output [[0.17922379]]\n",
            "16 day input [0.05412582 0.0435049  0.04799837 0.05147059 0.05065359 0.03431373\n",
            " 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503 0.03125\n",
            " 0.05882353 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229\n",
            " 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134\n",
            " 0.10457516 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654\n",
            " 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085 0.08823529\n",
            " 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052\n",
            " 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837\n",
            " 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784\n",
            " 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601\n",
            " 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882\n",
            " 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784 0.02961601\n",
            " 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085\n",
            " 0.06658497 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232\n",
            " 0.06781046 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235\n",
            " 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157\n",
            " 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373\n",
            " 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745\n",
            " 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895\n",
            " 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216 0.07169118\n",
            " 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275\n",
            " 0.04003268 0.03860294 0.04105392 0.03390523 0.03125    0.02634804\n",
            " 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706\n",
            " 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137\n",
            " 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719\n",
            " 0.07700163 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092\n",
            " 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725\n",
            " 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317\n",
            " 0.12479575 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706\n",
            " 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588\n",
            " 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039\n",
            " 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895\n",
            " 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948\n",
            " 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621\n",
            " 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458\n",
            " 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248\n",
            " 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366\n",
            " 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876 0.21098856\n",
            " 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497\n",
            " 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595\n",
            " 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935\n",
            " 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065\n",
            " 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268  0.15196078\n",
            " 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059\n",
            " 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967 0.12806373\n",
            " 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856\n",
            " 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732\n",
            " 0.16319444 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805\n",
            " 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658\n",
            " 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379]\n",
            "16 day output [[0.18011948]]\n",
            "17 day input [0.0435049  0.04799837 0.05147059 0.05065359 0.03431373 0.04575163\n",
            " 0.04187092 0.04554739 0.03941993 0.02716503 0.03125    0.05882353\n",
            " 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392\n",
            " 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516\n",
            " 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549\n",
            " 0.08169935 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882\n",
            " 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353\n",
            " 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314\n",
            " 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784 0.07209967\n",
            " 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399\n",
            " 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049\n",
            " 0.02634804 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163\n",
            " 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497\n",
            " 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046\n",
            " 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235 0.08843954\n",
            " 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183\n",
            " 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484\n",
            " 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797\n",
            " 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402\n",
            " 0.07066993 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706\n",
            " 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268\n",
            " 0.03860294 0.04105392 0.03390523 0.03125    0.02634804 0.05861928\n",
            " 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752\n",
            " 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137 0.06045752\n",
            " 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163\n",
            " 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922\n",
            " 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007\n",
            " 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575\n",
            " 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072\n",
            " 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614\n",
            " 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438\n",
            " 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895\n",
            " 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647\n",
            " 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908\n",
            " 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556\n",
            " 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595\n",
            " 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549\n",
            " 0.2128268  0.21568627 0.20445261 0.21772876 0.21098856 0.21425654\n",
            " 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542\n",
            " 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039\n",
            " 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353\n",
            " 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219\n",
            " 0.17177288 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307\n",
            " 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768\n",
            " 0.12377451 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046\n",
            " 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235\n",
            " 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444\n",
            " 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464\n",
            " 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898\n",
            " 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379 0.18011948]\n",
            "17 day output [[0.18101205]]\n",
            "18 day input [0.04799837 0.05147059 0.05065359 0.03431373 0.04575163 0.04187092\n",
            " 0.04554739 0.03941993 0.02716503 0.03125    0.05882353 0.07148693\n",
            " 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817\n",
            " 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837\n",
            " 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549  0.08169935\n",
            " 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261\n",
            " 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824\n",
            " 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219\n",
            " 0.03941993 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948\n",
            " 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569\n",
            " 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804\n",
            " 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203\n",
            " 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641\n",
            " 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085\n",
            " 0.0692402  0.0755719  0.07781863 0.08088235 0.08843954 0.09395425\n",
            " 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261\n",
            " 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366\n",
            " 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876\n",
            " 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993\n",
            " 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908\n",
            " 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294\n",
            " 0.04105392 0.03390523 0.03125    0.02634804 0.05861928 0.06311275\n",
            " 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752 0.0557598\n",
            " 0.0439134  0.02920752 0.02818627 0.04718137 0.06045752 0.05861928\n",
            " 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817\n",
            " 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222\n",
            " 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974\n",
            " 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686\n",
            " 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222\n",
            " 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667\n",
            " 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889\n",
            " 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647\n",
            " 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399\n",
            " 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673\n",
            " 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458\n",
            " 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444\n",
            " 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268\n",
            " 0.21568627 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817\n",
            " 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013\n",
            " 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458\n",
            " 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072\n",
            " 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288\n",
            " 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634\n",
            " 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451\n",
            " 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673\n",
            " 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908\n",
            " 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967\n",
            " 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221\n",
            " 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898 0.17565471\n",
            " 0.17653994 0.17743164 0.17832704 0.17922379 0.18011948 0.18101205]\n",
            "18 day output [[0.18189938]]\n",
            "19 day input [0.05147059 0.05065359 0.03431373 0.04575163 0.04187092 0.04554739\n",
            " 0.03941993 0.02716503 0.03125    0.05882353 0.07148693 0.08721405\n",
            " 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327\n",
            " 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451\n",
            " 0.09803922 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654\n",
            " 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183\n",
            " 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745\n",
            " 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993\n",
            " 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948 0.07230392\n",
            " 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582\n",
            " 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804 0.02410131\n",
            " 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922\n",
            " 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444\n",
            " 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402\n",
            " 0.0755719  0.07781863 0.08088235 0.08843954 0.09395425 0.09599673\n",
            " 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477\n",
            " 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745\n",
            " 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118\n",
            " 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471\n",
            " 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275\n",
            " 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294 0.04105392\n",
            " 0.03390523 0.03125    0.02634804 0.05861928 0.06311275 0.0620915\n",
            " 0.05535131 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134\n",
            " 0.02920752 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301\n",
            " 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542\n",
            " 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497\n",
            " 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386\n",
            " 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464\n",
            " 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418\n",
            " 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621\n",
            " 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667\n",
            " 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405\n",
            " 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993\n",
            " 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556\n",
            " 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307\n",
            " 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163\n",
            " 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627\n",
            " 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275\n",
            " 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386\n",
            " 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314\n",
            " 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399\n",
            " 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046\n",
            " 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758\n",
            " 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092\n",
            " 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242\n",
            " 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928\n",
            " 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245\n",
            " 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562\n",
            " 0.1722502  0.17307197 0.17391658 0.17477898 0.17565471 0.17653994\n",
            " 0.17743164 0.17832704 0.17922379 0.18011948 0.18101205 0.18189938]\n",
            "19 day output [[0.18277971]]\n",
            "20 day input [0.05065359 0.03431373 0.04575163 0.04187092 0.04554739 0.03941993\n",
            " 0.02716503 0.03125    0.05882353 0.07148693 0.08721405 0.08986928\n",
            " 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863\n",
            " 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922\n",
            " 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627\n",
            " 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863\n",
            " 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549\n",
            " 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993 0.0379902\n",
            " 0.04656863 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288\n",
            " 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366\n",
            " 0.05167484 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601\n",
            " 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575\n",
            " 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235\n",
            " 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719\n",
            " 0.07781863 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131\n",
            " 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902\n",
            " 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582\n",
            " 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144\n",
            " 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471 0.06678922\n",
            " 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085\n",
            " 0.05167484 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523\n",
            " 0.03125    0.02634804 0.05861928 0.06311275 0.0620915  0.05535131\n",
            " 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752\n",
            " 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346\n",
            " 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967\n",
            " 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248\n",
            " 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327\n",
            " 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732\n",
            " 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111\n",
            " 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902\n",
            " 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438\n",
            " 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405 0.14644608\n",
            " 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157\n",
            " 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379\n",
            " 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843\n",
            " 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242\n",
            " 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261\n",
            " 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307\n",
            " 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131\n",
            " 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065\n",
            " 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222\n",
            " 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405\n",
            " 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758 0.12479575\n",
            " 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497\n",
            " 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059\n",
            " 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327\n",
            " 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973\n",
            " 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502\n",
            " 0.17307197 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164\n",
            " 0.17832704 0.17922379 0.18011948 0.18101205 0.18189938 0.18277971]\n",
            "20 day output [[0.18365148]]\n",
            "21 day input [0.03431373 0.04575163 0.04187092 0.04554739 0.03941993 0.02716503\n",
            " 0.03125    0.05882353 0.07148693 0.08721405 0.08986928 0.10498366\n",
            " 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948\n",
            " 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922 0.09987745\n",
            " 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085\n",
            " 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346\n",
            " 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281\n",
            " 0.04799837 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863\n",
            " 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013\n",
            " 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484\n",
            " 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784\n",
            " 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275\n",
            " 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235 0.07700163\n",
            " 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719  0.07781863\n",
            " 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778\n",
            " 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105\n",
            " 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386\n",
            " 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549\n",
            " 0.06821895 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216\n",
            " 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484\n",
            " 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523 0.03125\n",
            " 0.02634804 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882\n",
            " 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627\n",
            " 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418\n",
            " 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967 0.10089869\n",
            " 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477\n",
            " 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373\n",
            " 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732 0.11683007\n",
            " 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137\n",
            " 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575\n",
            " 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719\n",
            " 0.13071895 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007\n",
            " 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007\n",
            " 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333\n",
            " 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399\n",
            " 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641\n",
            " 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876\n",
            " 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536\n",
            " 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961\n",
            " 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412\n",
            " 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562\n",
            " 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268\n",
            " 0.15196078 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745\n",
            " 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967\n",
            " 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353\n",
            " 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405\n",
            " 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973 0.16847919\n",
            " 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197\n",
            " 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704\n",
            " 0.17922379 0.18011948 0.18101205 0.18189938 0.18277971 0.18365148]\n",
            "21 day output [[0.18451339]]\n",
            "22 day input [0.04575163 0.04187092 0.04554739 0.03941993 0.02716503 0.03125\n",
            " 0.05882353 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229\n",
            " 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134\n",
            " 0.10457516 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654\n",
            " 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085 0.08823529\n",
            " 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052\n",
            " 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837\n",
            " 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784\n",
            " 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601\n",
            " 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882\n",
            " 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784 0.02961601\n",
            " 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085\n",
            " 0.06658497 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232\n",
            " 0.06781046 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235\n",
            " 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157\n",
            " 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373\n",
            " 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745\n",
            " 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895\n",
            " 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216 0.07169118\n",
            " 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275\n",
            " 0.04003268 0.03860294 0.04105392 0.03390523 0.03125    0.02634804\n",
            " 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706\n",
            " 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137\n",
            " 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719\n",
            " 0.07700163 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092\n",
            " 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725\n",
            " 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317\n",
            " 0.12479575 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706\n",
            " 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588\n",
            " 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039\n",
            " 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895\n",
            " 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948\n",
            " 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621\n",
            " 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458\n",
            " 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248\n",
            " 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366\n",
            " 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876 0.21098856\n",
            " 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497\n",
            " 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595\n",
            " 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935\n",
            " 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065\n",
            " 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268  0.15196078\n",
            " 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059\n",
            " 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967 0.12806373\n",
            " 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856\n",
            " 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732\n",
            " 0.16319444 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805\n",
            " 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658\n",
            " 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379\n",
            " 0.18011948 0.18101205 0.18189938 0.18277971 0.18365148 0.18451339]\n",
            "22 day output [[0.18536456]]\n",
            "23 day input [0.04187092 0.04554739 0.03941993 0.02716503 0.03125    0.05882353\n",
            " 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392\n",
            " 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516\n",
            " 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549\n",
            " 0.08169935 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882\n",
            " 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353\n",
            " 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314\n",
            " 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784 0.07209967\n",
            " 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399\n",
            " 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049\n",
            " 0.02634804 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163\n",
            " 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497\n",
            " 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046\n",
            " 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235 0.08843954\n",
            " 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183\n",
            " 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484\n",
            " 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797\n",
            " 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402\n",
            " 0.07066993 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706\n",
            " 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268\n",
            " 0.03860294 0.04105392 0.03390523 0.03125    0.02634804 0.05861928\n",
            " 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752\n",
            " 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137 0.06045752\n",
            " 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163\n",
            " 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922\n",
            " 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007\n",
            " 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575\n",
            " 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072\n",
            " 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614\n",
            " 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438\n",
            " 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895\n",
            " 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647\n",
            " 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908\n",
            " 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556\n",
            " 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595\n",
            " 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549\n",
            " 0.2128268  0.21568627 0.20445261 0.21772876 0.21098856 0.21425654\n",
            " 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542\n",
            " 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039\n",
            " 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353\n",
            " 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219\n",
            " 0.17177288 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307\n",
            " 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768\n",
            " 0.12377451 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046\n",
            " 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235\n",
            " 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444\n",
            " 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464\n",
            " 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898\n",
            " 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379 0.18011948\n",
            " 0.18101205 0.18189938 0.18277971 0.18365148 0.18451339 0.18536456]\n",
            "23 day output [[0.18620431]]\n",
            "24 day input [0.04554739 0.03941993 0.02716503 0.03125    0.05882353 0.07148693\n",
            " 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817\n",
            " 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837\n",
            " 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549  0.08169935\n",
            " 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261\n",
            " 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824\n",
            " 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219\n",
            " 0.03941993 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948\n",
            " 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569\n",
            " 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804\n",
            " 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203\n",
            " 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641\n",
            " 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085\n",
            " 0.0692402  0.0755719  0.07781863 0.08088235 0.08843954 0.09395425\n",
            " 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261\n",
            " 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366\n",
            " 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876\n",
            " 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993\n",
            " 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908\n",
            " 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294\n",
            " 0.04105392 0.03390523 0.03125    0.02634804 0.05861928 0.06311275\n",
            " 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752 0.0557598\n",
            " 0.0439134  0.02920752 0.02818627 0.04718137 0.06045752 0.05861928\n",
            " 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817\n",
            " 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222\n",
            " 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974\n",
            " 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686\n",
            " 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222\n",
            " 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667\n",
            " 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889\n",
            " 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647\n",
            " 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399\n",
            " 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673\n",
            " 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458\n",
            " 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444\n",
            " 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268\n",
            " 0.21568627 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817\n",
            " 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013\n",
            " 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458\n",
            " 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072\n",
            " 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288\n",
            " 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634\n",
            " 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451\n",
            " 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673\n",
            " 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908\n",
            " 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967\n",
            " 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221\n",
            " 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898 0.17565471\n",
            " 0.17653994 0.17743164 0.17832704 0.17922379 0.18011948 0.18101205\n",
            " 0.18189938 0.18277971 0.18365148 0.18451339 0.18536456 0.18620431]\n",
            "24 day output [[0.18703231]]\n",
            "25 day input [0.03941993 0.02716503 0.03125    0.05882353 0.07148693 0.08721405\n",
            " 0.08986928 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327\n",
            " 0.10906863 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451\n",
            " 0.09803922 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654\n",
            " 0.09068627 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183\n",
            " 0.07781863 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745\n",
            " 0.06372549 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993\n",
            " 0.0379902  0.04656863 0.05085784 0.07209967 0.06535948 0.07230392\n",
            " 0.07802288 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582\n",
            " 0.0498366  0.05167484 0.05330882 0.0435049  0.02634804 0.02410131\n",
            " 0.02961601 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922\n",
            " 0.06229575 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444\n",
            " 0.08088235 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402\n",
            " 0.0755719  0.07781863 0.08088235 0.08843954 0.09395425 0.09599673\n",
            " 0.08660131 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477\n",
            " 0.09129902 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745\n",
            " 0.08537582 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118\n",
            " 0.07026144 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471\n",
            " 0.06678922 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275\n",
            " 0.0629085  0.05167484 0.03186275 0.04003268 0.03860294 0.04105392\n",
            " 0.03390523 0.03125    0.02634804 0.05861928 0.06311275 0.0620915\n",
            " 0.05535131 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134\n",
            " 0.02920752 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301\n",
            " 0.06699346 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542\n",
            " 0.10334967 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497\n",
            " 0.09579248 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386\n",
            " 0.12275327 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464\n",
            " 0.11621732 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418\n",
            " 0.14236111 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621\n",
            " 0.12254902 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667\n",
            " 0.14011438 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405\n",
            " 0.14644608 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993\n",
            " 0.17892157 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556\n",
            " 0.18239379 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307\n",
            " 0.19607843 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163\n",
            " 0.19771242 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627\n",
            " 0.20445261 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275\n",
            " 0.17851307 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386\n",
            " 0.18035131 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314\n",
            " 0.16830065 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399\n",
            " 0.19097222 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046\n",
            " 0.14971405 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758\n",
            " 0.12479575 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092\n",
            " 0.12908497 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242\n",
            " 0.14522059 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928\n",
            " 0.15400327 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245\n",
            " 0.16762973 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562\n",
            " 0.1722502  0.17307197 0.17391658 0.17477898 0.17565471 0.17653994\n",
            " 0.17743164 0.17832704 0.17922379 0.18011948 0.18101205 0.18189938\n",
            " 0.18277971 0.18365148 0.18451339 0.18536456 0.18620431 0.18703231]\n",
            "25 day output [[0.18784834]]\n",
            "26 day input [0.02716503 0.03125    0.05882353 0.07148693 0.08721405 0.08986928\n",
            " 0.10498366 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863\n",
            " 0.09660948 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922\n",
            " 0.09987745 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627\n",
            " 0.08129085 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863\n",
            " 0.09824346 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549\n",
            " 0.0494281  0.04799837 0.04534314 0.0443219  0.03941993 0.0379902\n",
            " 0.04656863 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288\n",
            " 0.07741013 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366\n",
            " 0.05167484 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601\n",
            " 0.01960784 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575\n",
            " 0.06311275 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235\n",
            " 0.07700163 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719\n",
            " 0.07781863 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131\n",
            " 0.09027778 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902\n",
            " 0.08803105 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582\n",
            " 0.08047386 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144\n",
            " 0.0747549  0.06821895 0.0692402  0.07066993 0.06801471 0.06678922\n",
            " 0.07414216 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085\n",
            " 0.05167484 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523\n",
            " 0.03125    0.02634804 0.05861928 0.06311275 0.0620915  0.05535131\n",
            " 0.08455882 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752\n",
            " 0.02818627 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346\n",
            " 0.07087418 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967\n",
            " 0.10089869 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248\n",
            " 0.09109477 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327\n",
            " 0.12806373 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732\n",
            " 0.11683007 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111\n",
            " 0.14093137 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902\n",
            " 0.12479575 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438\n",
            " 0.1380719  0.13071895 0.13071895 0.12867647 0.11846405 0.14644608\n",
            " 0.14808007 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157\n",
            " 0.17933007 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379\n",
            " 0.17708333 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843\n",
            " 0.18913399 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242\n",
            " 0.19934641 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261\n",
            " 0.21772876 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307\n",
            " 0.17381536 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131\n",
            " 0.17401961 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065\n",
            " 0.17279412 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222\n",
            " 0.17238562 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405\n",
            " 0.1503268  0.15196078 0.14726307 0.14501634 0.14603758 0.12479575\n",
            " 0.13112745 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497\n",
            " 0.13459967 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059\n",
            " 0.15257353 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327\n",
            " 0.14971405 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973\n",
            " 0.16847919 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502\n",
            " 0.17307197 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164\n",
            " 0.17832704 0.17922379 0.18011948 0.18101205 0.18189938 0.18277971\n",
            " 0.18365148 0.18451339 0.18536456 0.18620431 0.18703231 0.18784834]\n",
            "26 day output [[0.18865255]]\n",
            "27 day input [0.03125    0.05882353 0.07148693 0.08721405 0.08986928 0.10498366\n",
            " 0.08905229 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948\n",
            " 0.1064134  0.10457516 0.11049837 0.1127451  0.09803922 0.09987745\n",
            " 0.08925654 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085\n",
            " 0.08823529 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346\n",
            " 0.09089052 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281\n",
            " 0.04799837 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863\n",
            " 0.05085784 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013\n",
            " 0.06086601 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484\n",
            " 0.05330882 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784\n",
            " 0.02961601 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275\n",
            " 0.0629085  0.06658497 0.07434641 0.06944444 0.08088235 0.07700163\n",
            " 0.0684232  0.06781046 0.0629085  0.0692402  0.0755719  0.07781863\n",
            " 0.08088235 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778\n",
            " 0.08517157 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105\n",
            " 0.09681373 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386\n",
            " 0.06862745 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549\n",
            " 0.06821895 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216\n",
            " 0.07169118 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484\n",
            " 0.03186275 0.04003268 0.03860294 0.04105392 0.03390523 0.03125\n",
            " 0.02634804 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882\n",
            " 0.05514706 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627\n",
            " 0.04718137 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418\n",
            " 0.0755719  0.07700163 0.10375817 0.10314542 0.10334967 0.10089869\n",
            " 0.10437092 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477\n",
            " 0.09313725 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373\n",
            " 0.1313317  0.12479575 0.11090686 0.10743464 0.11621732 0.11683007\n",
            " 0.11764706 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137\n",
            " 0.13970588 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575\n",
            " 0.13848039 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719\n",
            " 0.13071895 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007\n",
            " 0.15910948 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007\n",
            " 0.19260621 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333\n",
            " 0.17810458 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399\n",
            " 0.18954248 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641\n",
            " 0.19873366 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876\n",
            " 0.21098856 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536\n",
            " 0.16033497 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961\n",
            " 0.16278595 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412\n",
            " 0.17544935 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562\n",
            " 0.16830065 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268\n",
            " 0.15196078 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745\n",
            " 0.11397059 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967\n",
            " 0.12806373 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353\n",
            " 0.14848856 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405\n",
            " 0.1621732  0.16319444 0.16584967 0.16633245 0.16762973 0.16847919\n",
            " 0.16922805 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197\n",
            " 0.17391658 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704\n",
            " 0.17922379 0.18011948 0.18101205 0.18189938 0.18277971 0.18365148\n",
            " 0.18451339 0.18536456 0.18620431 0.18703231 0.18784834 0.18865255]\n",
            "27 day output [[0.18944514]]\n",
            "28 day input [0.05882353 0.07148693 0.08721405 0.08986928 0.10498366 0.08905229\n",
            " 0.10355392 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134\n",
            " 0.10457516 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654\n",
            " 0.0747549  0.08169935 0.08925654 0.09068627 0.08129085 0.08823529\n",
            " 0.08455882 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052\n",
            " 0.09007353 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837\n",
            " 0.04534314 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784\n",
            " 0.07209967 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601\n",
            " 0.06413399 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882\n",
            " 0.0435049  0.02634804 0.02410131 0.02961601 0.01960784 0.02961601\n",
            " 0.04575163 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085\n",
            " 0.06658497 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232\n",
            " 0.06781046 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235\n",
            " 0.08843954 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157\n",
            " 0.08374183 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373\n",
            " 0.11417484 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745\n",
            " 0.06576797 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895\n",
            " 0.0692402  0.07066993 0.06801471 0.06678922 0.07414216 0.07169118\n",
            " 0.08639706 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275\n",
            " 0.04003268 0.03860294 0.04105392 0.03390523 0.03125    0.02634804\n",
            " 0.05861928 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706\n",
            " 0.06045752 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137\n",
            " 0.06045752 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719\n",
            " 0.07700163 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092\n",
            " 0.09803922 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725\n",
            " 0.08558007 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317\n",
            " 0.12479575 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706\n",
            " 0.12888072 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588\n",
            " 0.13827614 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039\n",
            " 0.14011438 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895\n",
            " 0.13071895 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948\n",
            " 0.15992647 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621\n",
            " 0.20812908 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458\n",
            " 0.18055556 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248\n",
            " 0.19403595 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366\n",
            " 0.1997549  0.2128268  0.21568627 0.20445261 0.21772876 0.21098856\n",
            " 0.21425654 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497\n",
            " 0.16564542 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595\n",
            " 0.16973039 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935\n",
            " 0.18382353 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065\n",
            " 0.1693219  0.17177288 0.16156046 0.14971405 0.1503268  0.15196078\n",
            " 0.14726307 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059\n",
            " 0.1190768  0.12377451 0.13562092 0.12908497 0.13459967 0.12806373\n",
            " 0.13031046 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856\n",
            " 0.14338235 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732\n",
            " 0.16319444 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805\n",
            " 0.16995464 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658\n",
            " 0.17477898 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379\n",
            " 0.18011948 0.18101205 0.18189938 0.18277971 0.18365148 0.18451339\n",
            " 0.18536456 0.18620431 0.18703231 0.18784834 0.18865255 0.18944514]\n",
            "28 day output [[0.19022633]]\n",
            "29 day input [0.07148693 0.08721405 0.08986928 0.10498366 0.08905229 0.10355392\n",
            " 0.10375817 0.12275327 0.10906863 0.09660948 0.1064134  0.10457516\n",
            " 0.11049837 0.1127451  0.09803922 0.09987745 0.08925654 0.0747549\n",
            " 0.08169935 0.08925654 0.09068627 0.08129085 0.08823529 0.08455882\n",
            " 0.07945261 0.08374183 0.07781863 0.09824346 0.09089052 0.09007353\n",
            " 0.09558824 0.06862745 0.06372549 0.0494281  0.04799837 0.04534314\n",
            " 0.0443219  0.03941993 0.0379902  0.04656863 0.05085784 0.07209967\n",
            " 0.06535948 0.07230392 0.07802288 0.07741013 0.06086601 0.06413399\n",
            " 0.07046569 0.05412582 0.0498366  0.05167484 0.05330882 0.0435049\n",
            " 0.02634804 0.02410131 0.02961601 0.01960784 0.02961601 0.04575163\n",
            " 0.05923203 0.06678922 0.06229575 0.06311275 0.0629085  0.06658497\n",
            " 0.07434641 0.06944444 0.08088235 0.07700163 0.0684232  0.06781046\n",
            " 0.0629085  0.0692402  0.0755719  0.07781863 0.08088235 0.08843954\n",
            " 0.09395425 0.09599673 0.08660131 0.09027778 0.08517157 0.08374183\n",
            " 0.07945261 0.09109477 0.09129902 0.08803105 0.09681373 0.11417484\n",
            " 0.10498366 0.09987745 0.08537582 0.08047386 0.06862745 0.06576797\n",
            " 0.06147876 0.07169118 0.07026144 0.0747549  0.06821895 0.0692402\n",
            " 0.07066993 0.06801471 0.06678922 0.07414216 0.07169118 0.08639706\n",
            " 0.08312908 0.06311275 0.0629085  0.05167484 0.03186275 0.04003268\n",
            " 0.03860294 0.04105392 0.03390523 0.03125    0.02634804 0.05861928\n",
            " 0.06311275 0.0620915  0.05535131 0.08455882 0.05514706 0.06045752\n",
            " 0.0557598  0.0439134  0.02920752 0.02818627 0.04718137 0.06045752\n",
            " 0.05861928 0.06168301 0.06699346 0.07087418 0.0755719  0.07700163\n",
            " 0.10375817 0.10314542 0.10334967 0.10089869 0.10437092 0.09803922\n",
            " 0.09722222 0.09783497 0.09579248 0.09109477 0.09313725 0.08558007\n",
            " 0.09517974 0.11172386 0.12275327 0.12806373 0.1313317  0.12479575\n",
            " 0.11090686 0.10743464 0.11621732 0.11683007 0.11764706 0.12888072\n",
            " 0.12847222 0.13337418 0.14236111 0.14093137 0.13970588 0.13827614\n",
            " 0.13541667 0.13010621 0.12254902 0.12479575 0.13848039 0.14011438\n",
            " 0.13888889 0.13541667 0.14011438 0.1380719  0.13071895 0.13071895\n",
            " 0.12867647 0.11846405 0.14644608 0.14808007 0.15910948 0.15992647\n",
            " 0.15788399 0.16441993 0.17892157 0.17933007 0.19260621 0.20812908\n",
            " 0.18974673 0.18055556 0.18239379 0.17708333 0.17810458 0.18055556\n",
            " 0.17810458 0.17851307 0.19607843 0.18913399 0.18954248 0.19403595\n",
            " 0.19444444 0.20200163 0.19771242 0.19934641 0.19873366 0.1997549\n",
            " 0.2128268  0.21568627 0.20445261 0.21772876 0.21098856 0.21425654\n",
            " 0.19750817 0.18811275 0.17851307 0.17381536 0.16033497 0.16564542\n",
            " 0.17116013 0.17422386 0.18035131 0.17401961 0.16278595 0.16973039\n",
            " 0.17810458 0.17034314 0.16830065 0.17279412 0.17544935 0.18382353\n",
            " 0.19138072 0.18913399 0.19097222 0.17238562 0.16830065 0.1693219\n",
            " 0.17177288 0.16156046 0.14971405 0.1503268  0.15196078 0.14726307\n",
            " 0.14501634 0.14603758 0.12479575 0.13112745 0.11397059 0.1190768\n",
            " 0.12377451 0.13562092 0.12908497 0.13459967 0.12806373 0.13031046\n",
            " 0.12724673 0.13521242 0.14522059 0.15257353 0.14848856 0.14338235\n",
            " 0.14562908 0.15236928 0.15400327 0.14971405 0.1621732  0.16319444\n",
            " 0.16584967 0.16633245 0.16762973 0.16847919 0.16922805 0.16995464\n",
            " 0.17069221 0.1714562  0.1722502  0.17307197 0.17391658 0.17477898\n",
            " 0.17565471 0.17653994 0.17743164 0.17832704 0.17922379 0.18011948\n",
            " 0.18101205 0.18189938 0.18277971 0.18365148 0.18451339 0.18536456\n",
            " 0.18620431 0.18703231 0.18784834 0.18865255 0.18944514 0.19022633]\n",
            "29 day output [[0.19099657]]\n",
            "[[0.1663324534893036], [0.16762973368167877], [0.16847918927669525], [0.16922804713249207], [0.16995464265346527], [0.17069220542907715], [0.1714562028646469], [0.1722501963376999], [0.1730719655752182], [0.17391657829284668], [0.1747789829969406], [0.17565470933914185], [0.17653994262218475], [0.1774316430091858], [0.1783270388841629], [0.17922379076480865], [0.18011948466300964], [0.18101204931735992], [0.18189938366413116], [0.1827797144651413], [0.18365147709846497], [0.1845133900642395], [0.18536455929279327], [0.18620431423187256], [0.1870323121547699], [0.18784834444522858], [0.18865254521369934], [0.1894451379776001], [0.19022633135318756], [0.19099657237529755]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z3VYdJSYaOvX",
        "outputId": "1d451c0a-c7d1-4850-9583-13fa0dd9a42b"
      },
      "source": [
        "day_new = np.arange(1,101)\n",
        "day_pred = np.arange(101,131)\n",
        "\n",
        "df3 = df_close.tolist()\n",
        "df3.extend(lst_output)\n",
        "\n",
        "len(df_close)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2035"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 287
        },
        "id": "0amGAC_Satd4",
        "outputId": "08bd5dc1-472a-4894-8c59-88e31d3ce4af"
      },
      "source": [
        "# plt.plot(day_new, scaler.inverse_transform(df_close()))\n",
        "plt.plot(day_pred, scaler.inverse_transform(lst_output))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f361f292750>]"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dWKCRMpPawa_"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}