notebook/lstm_autoencoder_feature_extraction.ipynb

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    "colab": {
      "name": "lstm_autoencoder_feature_extraction.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bbgSPkLs2O5R"
      },
      "source": [
        "https://machinelearningmastery.com/lstm-autoencoders/\n",
        "\n",
        "https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/\n",
        "\n",
        "https://towardsdatascience.com/lstm-autoencoder-for-extreme-rare-event-classification-in-keras-ce209a224cfb\n",
        "\n",
        "https://towardsdatascience.com/step-by-step-understanding-lstm-autoencoder-layers-ffab055b6352"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A47cl9CReAWh"
      },
      "source": [
        "1. MinMax scalar\n",
        "2. Different loss functions\n",
        "3. How to take output of encoder part"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LAyyJc797b46"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "import tensorflow as tf"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n2VQum6kIKHf",
        "outputId": "7ec354a8-f363-439d-8131-d726b768f4a8"
      },
      "source": [
        "!pip install -U keras-tuner\n",
        "import kerastuner as kt"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting keras-tuner\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/20/ec/1ef246787174b1e2bb591c95f29d3c1310070cad877824f907faba3dade9/keras-tuner-1.0.2.tar.gz (62kB)\n",
            "\r\u001b[K     |█████▏                          | 10kB 25.8MB/s eta 0:00:01\r\u001b[K     |██████████▍                     | 20kB 32.9MB/s eta 0:00:01\r\u001b[K     |███████████████▋                | 30kB 24.0MB/s eta 0:00:01\r\u001b[K     |████████████████████▉           | 40kB 27.9MB/s eta 0:00:01\r\u001b[K     |██████████████████████████      | 51kB 28.6MB/s eta 0:00:01\r\u001b[K     |███████████████████████████████▎| 61kB 31.0MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 71kB 10.7MB/s \n",
            "\u001b[?25hRequirement already satisfied, skipping upgrade: packaging in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (20.8)\n",
            "Requirement already satisfied, skipping upgrade: future in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (0.16.0)\n",
            "Requirement already satisfied, skipping upgrade: numpy in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (1.19.5)\n",
            "Requirement already satisfied, skipping upgrade: tabulate in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (0.8.7)\n",
            "Collecting terminaltables\n",
            "  Downloading https://files.pythonhosted.org/packages/9b/c4/4a21174f32f8a7e1104798c445dacdc1d4df86f2f26722767034e4de4bff/terminaltables-3.1.0.tar.gz\n",
            "Collecting colorama\n",
            "  Downloading https://files.pythonhosted.org/packages/44/98/5b86278fbbf250d239ae0ecb724f8572af1c91f4a11edf4d36a206189440/colorama-0.4.4-py2.py3-none-any.whl\n",
            "Requirement already satisfied, skipping upgrade: tqdm in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (4.41.1)\n",
            "Requirement already satisfied, skipping upgrade: requests in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (2.23.0)\n",
            "Requirement already satisfied, skipping upgrade: scipy in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (1.4.1)\n",
            "Requirement already satisfied, skipping upgrade: scikit-learn in /usr/local/lib/python3.6/dist-packages (from keras-tuner) (0.22.2.post1)\n",
            "Requirement already satisfied, skipping upgrade: pyparsing>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from packaging->keras-tuner) (2.4.7)\n",
            "Requirement already satisfied, skipping upgrade: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->keras-tuner) (1.24.3)\n",
            "Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->keras-tuner) (2.10)\n",
            "Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->keras-tuner) (3.0.4)\n",
            "Requirement already satisfied, skipping upgrade: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->keras-tuner) (2020.12.5)\n",
            "Requirement already satisfied, skipping upgrade: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->keras-tuner) (1.0.0)\n",
            "Building wheels for collected packages: keras-tuner, terminaltables\n",
            "  Building wheel for keras-tuner (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for keras-tuner: filename=keras_tuner-1.0.2-cp36-none-any.whl size=78939 sha256=7ed8543cefb46119309e0e98db54a4cbb9429b5de88306b885ec5543dd43c565\n",
            "  Stored in directory: /root/.cache/pip/wheels/bb/a1/8a/7c3de0efb3707a1701b36ebbfdbc4e67aedf6d4943a1f463d6\n",
            "  Building wheel for terminaltables (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for terminaltables: filename=terminaltables-3.1.0-cp36-none-any.whl size=15358 sha256=0c94db765e917442d4c615fcdb1e6c9f3b91b1e741e96b934de1b72dca0e6186\n",
            "  Stored in directory: /root/.cache/pip/wheels/30/6b/50/6c75775b681fb36cdfac7f19799888ef9d8813aff9e379663e\n",
            "Successfully built keras-tuner terminaltables\n",
            "Installing collected packages: terminaltables, colorama, keras-tuner\n",
            "Successfully installed colorama-0.4.4 keras-tuner-1.0.2 terminaltables-3.1.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
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      "metadata": {
        "id": "Fu86dSgQGMHX"
      },
      "source": [
        "plt.rcParams[\"figure.figsize\"] = [16,9]"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TJntx7w6CLVE"
      },
      "source": [
        "# _initializing constant variables\n",
        "#input_file_path = os.getcwd() + f'/../data/output_csv/processed_data.csv'\n",
        "input_file_path = f'/content/drive/MyDrive/Colab Notebooks/processed_data.csv'\n",
        "col_names = ['timestamp (s)','subject_id', 'activityID', 'X1', 'Y1', 'Z1', 'X2', 'Y2', 'Z2']\n",
        "main_df = pd.read_csv(input_file_path,names=col_names)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "JI6YoohiC4ak",
        "outputId": "ed42a32d-ac35-480e-e178-42a0a3b9f6b1"
      },
      "source": [
        "main_df"
      ],
      "execution_count": 7,
      "outputs": [
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              "           activityID\n",
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      "cell_type": "code",
      "metadata": {
        "id": "8_W_yQ4t2N1r"
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      "source": [
        "main_df = main_df.loc[main_df['subject_id'] != 103]"
      ],
      "execution_count": 9,
      "outputs": []
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        "main_df.sort_values(by=['activityID'], inplace=True)\n",
        "main_df[['timestamp (s)', 'activityID']].groupby(['activityID']).agg(['count'])"
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      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
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            "  \"\"\"Entry point for launching an IPython kernel.\n"
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              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>activityID</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>170454</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>156264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>169253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>203884</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>164530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>186114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>154959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>210496</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           timestamp (s)\n",
              "                   count\n",
              "activityID              \n",
              "1                 170454\n",
              "2                 156264\n",
              "3                 169253\n",
              "4                 203884\n",
              "6                 164530\n",
              "7                 186114\n",
              "16                154959\n",
              "17                210496"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8kuYMnzu8DTa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bbaae26b-5102-4df2-f10c-4ca024ec0a4d"
      },
      "source": [
        "drop_cols = ['timestamp (s)', 'subject_id']\n",
        "main_df.drop(columns=drop_cols, axis=1, inplace=True)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py:4174: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  errors=errors,\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "Fz-JBXBYAoo2",
        "outputId": "985fbbf5-e736-4ab6-f46f-b23100a37111"
      },
      "source": [
        "main_df"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>activityID</th>\n",
              "      <th>X1</th>\n",
              "      <th>Y1</th>\n",
              "      <th>Z1</th>\n",
              "      <th>X2</th>\n",
              "      <th>Y2</th>\n",
              "      <th>Z2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2.21530</td>\n",
              "      <td>8.279150</td>\n",
              "      <td>5.58753</td>\n",
              "      <td>-0.004750</td>\n",
              "      <td>0.037579</td>\n",
              "      <td>-0.011145</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>551485</th>\n",
              "      <td>1</td>\n",
              "      <td>4.83383</td>\n",
              "      <td>0.394111</td>\n",
              "      <td>8.65537</td>\n",
              "      <td>-0.014979</td>\n",
              "      <td>-0.013408</td>\n",
              "      <td>-0.003733</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>551486</th>\n",
              "      <td>1</td>\n",
              "      <td>4.90084</td>\n",
              "      <td>0.504997</td>\n",
              "      <td>8.38659</td>\n",
              "      <td>-0.016116</td>\n",
              "      <td>-0.037889</td>\n",
              "      <td>-0.011223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>551487</th>\n",
              "      <td>1</td>\n",
              "      <td>5.01421</td>\n",
              "      <td>0.693482</td>\n",
              "      <td>8.34916</td>\n",
              "      <td>-0.027256</td>\n",
              "      <td>0.010782</td>\n",
              "      <td>-0.028180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>551488</th>\n",
              "      <td>1</td>\n",
              "      <td>4.90352</td>\n",
              "      <td>0.505668</td>\n",
              "      <td>8.46360</td>\n",
              "      <td>-0.028567</td>\n",
              "      <td>-0.001170</td>\n",
              "      <td>-0.036104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>835265</th>\n",
              "      <td>17</td>\n",
              "      <td>-4.65970</td>\n",
              "      <td>7.386130</td>\n",
              "      <td>5.75697</td>\n",
              "      <td>2.426860</td>\n",
              "      <td>-0.878047</td>\n",
              "      <td>-0.376608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>835266</th>\n",
              "      <td>17</td>\n",
              "      <td>-4.31906</td>\n",
              "      <td>7.459380</td>\n",
              "      <td>5.76183</td>\n",
              "      <td>2.523730</td>\n",
              "      <td>-0.979366</td>\n",
              "      <td>-0.292547</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>835267</th>\n",
              "      <td>17</td>\n",
              "      <td>-4.44687</td>\n",
              "      <td>7.683860</td>\n",
              "      <td>5.29731</td>\n",
              "      <td>2.610760</td>\n",
              "      <td>-0.987398</td>\n",
              "      <td>-0.275793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>835255</th>\n",
              "      <td>17</td>\n",
              "      <td>-3.81678</td>\n",
              "      <td>5.034520</td>\n",
              "      <td>6.58577</td>\n",
              "      <td>1.011110</td>\n",
              "      <td>-0.474947</td>\n",
              "      <td>-0.529987</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1425369</th>\n",
              "      <td>17</td>\n",
              "      <td>-4.33087</td>\n",
              "      <td>-3.526560</td>\n",
              "      <td>7.68459</td>\n",
              "      <td>0.278158</td>\n",
              "      <td>0.013944</td>\n",
              "      <td>-0.527955</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1415954 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         activityID       X1        Y1       Z1        X2        Y2        Z2\n",
              "0                 1  2.21530  8.279150  5.58753 -0.004750  0.037579 -0.011145\n",
              "551485            1  4.83383  0.394111  8.65537 -0.014979 -0.013408 -0.003733\n",
              "551486            1  4.90084  0.504997  8.38659 -0.016116 -0.037889 -0.011223\n",
              "551487            1  5.01421  0.693482  8.34916 -0.027256  0.010782 -0.028180\n",
              "551488            1  4.90352  0.505668  8.46360 -0.028567 -0.001170 -0.036104\n",
              "...             ...      ...       ...      ...       ...       ...       ...\n",
              "835265           17 -4.65970  7.386130  5.75697  2.426860 -0.878047 -0.376608\n",
              "835266           17 -4.31906  7.459380  5.76183  2.523730 -0.979366 -0.292547\n",
              "835267           17 -4.44687  7.683860  5.29731  2.610760 -0.987398 -0.275793\n",
              "835255           17 -3.81678  5.034520  6.58577  1.011110 -0.474947 -0.529987\n",
              "1425369          17 -4.33087 -3.526560  7.68459  0.278158  0.013944 -0.527955\n",
              "\n",
              "[1415954 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zCVO1Uhs59iB"
      },
      "source": [
        "activities = set(list(main_df.activityID.unique()))\n",
        "final_sensor_data = pd.DataFrame(columns=main_df.columns)\n",
        "timesteps = 50\n",
        "features = 6\n",
        "\n",
        "for activity in activities:\n",
        "    activity_df = main_df.loc[main_df['activityID'] == activity]\n",
        "\n",
        "    extra_rows = len(activity_df.index)%timesteps\n",
        "    timestep_rows = (len(activity_df.index) - extra_rows)\n",
        "\n",
        "    if extra_rows > 0:\n",
        "      activity_df = activity_df.iloc[:timestep_rows]\n",
        "\n",
        "    final_sensor_data = pd.concat([final_sensor_data, activity_df])"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MF7f2SdcBF4a",
        "outputId": "bee777ff-8d41-479a-c630-dd84a88871fe"
      },
      "source": [
        "activity_data = final_sensor_data.iloc[:, 0].values\n",
        "sensor_data = final_sensor_data.iloc[:, 1:].values.astype('float32')\n",
        "print(sensor_data.shape)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1415800, 6)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "LsUtLqRcEx7i",
        "outputId": "963d8901-a3ee-4de3-9fa4-06529e5bdf02"
      },
      "source": [
        "plt.figure()\n",
        "for col in range(features):\n",
        "\tplt.subplot(features, 1, col+1)\n",
        "\tplt.plot(sensor_data[:, col])\n",
        "\tplt.title(col_names[col+3], y=0.5, loc='right')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x648 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "uhLsk53eG13z",
        "outputId": "731b9bcf-47d9-4926-819b-4928fd992ea8"
      },
      "source": [
        "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
        "\n",
        "for idx in range(features):\n",
        "    sensor_data[:, idx] = MinMaxScaler().fit_transform(sensor_data[:, idx].reshape(-1, 1)).reshape(1,-1)\n",
        "\n",
        "plt.figure()\n",
        "for col in range(features):\n",
        "\tplt.subplot(features, 1, col+1)\n",
        "\tplt.plot(sensor_data[:, col])\n",
        "\tplt.title(col_names[col+3], y=0.5, loc='right')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x648 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dIgcdeLFGKIY",
        "outputId": "8be2ece5-16b2-4051-8347-2d0f8309f996"
      },
      "source": [
        "sensor_data.shape"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1415800, 6)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bwDpHKJyC4nB",
        "outputId": "fda806fa-73bd-4532-fc7a-d1eebdec614d"
      },
      "source": [
        "activity_data.shape"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1415800,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e_A_6ilDYmGR",
        "outputId": "1f4c44c5-2725-4995-94d5-24fc0bb82ef7"
      },
      "source": [
        "# _input data format - [samples, timesteps, features]\n",
        "sensor_data = sensor_data.reshape(-1, timesteps, features)\n",
        "sensor_data.shape"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 50, 6)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3KB5AbUYDC_M",
        "outputId": "00186938-6a9c-49b6-adfa-489aba357bc4"
      },
      "source": [
        "# _input data format - [samples, timesteps, features]\n",
        "activity_data = activity_data.reshape(-1, timesteps)\n",
        "activity_data.shape"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 50)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OJVd1SgfKSr3"
      },
      "source": [
        "def build_model(hp):\n",
        "\n",
        "    lstm_layer_1_output_params = hp.Int(\n",
        "        'output_1', min_value=60, max_value=100, step=5)\n",
        "    lstm_layer_2_output_params = hp.Int(\n",
        "        'output_2', min_value=30, max_value=60, step=5)\n",
        "    \n",
        "    lstm_layer_1_dropoutrate_params = hp.Float(\n",
        "        'dropoutrate_1', min_value=0.2, max_value=0.5, step=0.1)\n",
        "    lstm_layer_2_dropoutrate_params = hp.Float(\n",
        "        'dropoutrate_2', min_value=0.2, max_value=0.5, step=0.1)\n",
        "\n",
        "    activation_fn_params = hp.Choice(\n",
        "        'act_fn', values=['relu', 'tanh'])\n",
        "\n",
        "    learning_rate_params = hp.Choice(\n",
        "        'learning_rate', values=[1e-2, 1e-3])\n",
        "\n",
        "    model = tf.keras.models.Sequential([\n",
        "        tf.keras.layers.LSTM(lstm_layer_1_output_params, activation=activation_fn_params, input_shape=(timesteps, features), return_sequences=True),\n",
        "        tf.keras.layers.LSTM(lstm_layer_2_output_params, activation=activation_fn_params, return_sequences=False),\n",
        "        tf.keras.layers.Dropout(rate=lstm_layer_1_dropoutrate_params),\n",
        "\n",
        "        tf.keras.layers.RepeatVector(timesteps),\n",
        "\n",
        "        tf.keras.layers.LSTM(lstm_layer_2_output_params, activation=activation_fn_params, return_sequences=True),\n",
        "        tf.keras.layers.LSTM(lstm_layer_1_output_params, activation=activation_fn_params, return_sequences=True),\n",
        "        tf.keras.layers.Dropout(rate=lstm_layer_2_dropoutrate_params),\n",
        "\n",
        "        tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(features))    \n",
        "    ])\n",
        "    model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=learning_rate_params),loss='mae')\n",
        "\n",
        "    return model"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h8XRnw_4Ke5p",
        "outputId": "d1ba0dcb-aa30-46a8-daae-acdd5ee5bcfc"
      },
      "source": [
        "tuner_bo = kt.tuners.BayesianOptimization(\n",
        "                build_model,objective=kt.Objective('val_loss', direction=\"min\"), max_trials =30, executions_per_trial=2\n",
        ")\n",
        "\n",
        "tuner_bo.search(sensor_data, sensor_data, epochs=5, batch_size=64 ,validation_split=0.3)\n",
        "best_model = tuner_bo.get_best_models(num_models=1)[0]\n",
        "print(best_model.summary())\n",
        "\n",
        "best_hp = tuner_bo.get_best_hyperparameters()[0]\n",
        "print(best_hp.values)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Trial 30 Complete [00h 01m 01s]\n",
            "val_loss: 0.025184335187077522\n",
            "\n",
            "Best val_loss So Far: 0.023602266795933247\n",
            "Total elapsed time: 04h 22m 26s\n",
            "INFO:tensorflow:Oracle triggered exit\n",
            "WARNING:tensorflow:Layer lstm will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
            "WARNING:tensorflow:Layer lstm_1 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
            "WARNING:tensorflow:Layer lstm_2 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
            "WARNING:tensorflow:Layer lstm_3 will not use cuDNN kernel since it doesn't meet the cuDNN kernel criteria. It will use generic GPU kernel as fallback when running on GPU\n",
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "lstm (LSTM)                  (None, 50, 95)            38760     \n",
            "_________________________________________________________________\n",
            "lstm_1 (LSTM)                (None, 60)                37440     \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 60)                0         \n",
            "_________________________________________________________________\n",
            "repeat_vector (RepeatVector) (None, 50, 60)            0         \n",
            "_________________________________________________________________\n",
            "lstm_2 (LSTM)                (None, 50, 60)            29040     \n",
            "_________________________________________________________________\n",
            "lstm_3 (LSTM)                (None, 50, 95)            59280     \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 50, 95)            0         \n",
            "_________________________________________________________________\n",
            "time_distributed (TimeDistri (None, 50, 6)             576       \n",
            "=================================================================\n",
            "Total params: 165,096\n",
            "Trainable params: 165,096\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "{'output_1': 95, 'output_2': 60, 'dropoutrate_1': 0.2, 'dropoutrate_2': 0.5000000000000001, 'act_fn': 'relu', 'learning_rate': 0.001}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZtL7qoLmbZQA",
        "outputId": "fca254b6-ad66-4d01-9e0d-850b3f6a3437"
      },
      "source": [
        "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
        "    min_delta=0.001, \n",
        "    patience=5, \n",
        "    restore_best_weights=True,\n",
        ")\n",
        "\n",
        "history = best_model.fit(sensor_data, sensor_data, epochs=50, validation_split=0.4, callbacks=[early_stopping], batch_size=32)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "531/531 [==============================] - 184s 340ms/step - loss: 0.0156 - val_loss: 0.0253\n",
            "Epoch 2/50\n",
            "531/531 [==============================] - 177s 333ms/step - loss: 0.0154 - val_loss: 0.0250\n",
            "Epoch 3/50\n",
            "531/531 [==============================] - 175s 329ms/step - loss: 0.0151 - val_loss: 0.0250\n",
            "Epoch 4/50\n",
            "531/531 [==============================] - 179s 338ms/step - loss: 0.0151 - val_loss: 0.0245\n",
            "Epoch 5/50\n",
            "531/531 [==============================] - 182s 343ms/step - loss: 0.0149 - val_loss: 0.0245\n",
            "Epoch 6/50\n",
            "531/531 [==============================] - 173s 327ms/step - loss: 0.0144 - val_loss: 0.0242\n",
            "Epoch 7/50\n",
            "531/531 [==============================] - 176s 332ms/step - loss: 0.0142 - val_loss: 0.0232\n",
            "Epoch 8/50\n",
            "531/531 [==============================] - 179s 337ms/step - loss: 0.0139 - val_loss: 0.0225\n",
            "Epoch 9/50\n",
            "531/531 [==============================] - 174s 328ms/step - loss: 0.0137 - val_loss: 0.0222\n",
            "Epoch 10/50\n",
            "531/531 [==============================] - 174s 328ms/step - loss: 0.0133 - val_loss: 0.0219\n",
            "Epoch 11/50\n",
            "531/531 [==============================] - 175s 330ms/step - loss: 0.0132 - val_loss: 0.0217\n",
            "Epoch 12/50\n",
            "531/531 [==============================] - 173s 326ms/step - loss: 0.0130 - val_loss: 0.0219\n",
            "Epoch 13/50\n",
            "531/531 [==============================] - 171s 323ms/step - loss: 0.0129 - val_loss: 0.0210\n",
            "Epoch 14/50\n",
            "531/531 [==============================] - 175s 330ms/step - loss: 0.0127 - val_loss: 0.0208\n",
            "Epoch 15/50\n",
            "531/531 [==============================] - 169s 318ms/step - loss: 0.0125 - val_loss: 0.0202\n",
            "Epoch 16/50\n",
            "531/531 [==============================] - 170s 320ms/step - loss: 0.0123 - val_loss: 0.0206\n",
            "Epoch 17/50\n",
            "531/531 [==============================] - 173s 326ms/step - loss: 0.0125 - val_loss: 0.0201\n",
            "Epoch 18/50\n",
            "531/531 [==============================] - 169s 319ms/step - loss: 0.0124 - val_loss: 0.0202\n",
            "Epoch 19/50\n",
            "531/531 [==============================] - 172s 324ms/step - loss: 0.0122 - val_loss: 0.0196\n",
            "Epoch 20/50\n",
            "531/531 [==============================] - 163s 307ms/step - loss: 0.0121 - val_loss: 0.0207\n",
            "Epoch 21/50\n",
            "531/531 [==============================] - 165s 310ms/step - loss: 0.0121 - val_loss: 0.0193\n",
            "Epoch 22/50\n",
            "531/531 [==============================] - 170s 321ms/step - loss: 0.0120 - val_loss: 0.0199\n",
            "Epoch 23/50\n",
            "531/531 [==============================] - 173s 326ms/step - loss: 0.0120 - val_loss: 0.0198\n",
            "Epoch 24/50\n",
            "531/531 [==============================] - 176s 331ms/step - loss: 0.0121 - val_loss: 0.0194\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "anH4s0ljYk7X"
      },
      "source": [
        "# lstm_ae_model = tf.keras.models.Sequential([\n",
        "#     tf.keras.layers.LSTM(50, activation='relu', input_shape=(timesteps, features), return_sequences=True),\n",
        "#     tf.keras.layers.LSTM(25, activation='relu', return_sequences=False),\n",
        "#     tf.keras.layers.Dropout(rate=0.2),\n",
        "\n",
        "#     tf.keras.layers.RepeatVector(timesteps),\n",
        "\n",
        "#     tf.keras.layers.LSTM(25, activation='relu', return_sequences=True),\n",
        "#     tf.keras.layers.LSTM(50, activation='relu', return_sequences=True),\n",
        "#     tf.keras.layers.Dropout(rate=0.2),\n",
        "\n",
        "#     tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(features))    \n",
        "# ])\n",
        "# lstm_ae_model.compile(optimizer='adam', loss='mae')\n",
        "# lstm_ae_model.summary()"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3UFj8qZXgqQl"
      },
      "source": [
        "# early_stopping = tf.keras.callbacks.EarlyStopping(\n",
        "#     min_delta=0.001, \n",
        "#     patience=5, \n",
        "#     restore_best_weights=True,\n",
        "# )\n",
        "\n",
        "# history = lstm_ae_model.fit(sensor_data, sensor_data, epochs=50, validation_split=0.4, callbacks=[early_stopping], batch_size=32)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "vDLTiAVZb8-1",
        "outputId": "9c30f34f-fbcd-4b0d-ccd5-596257c46232"
      },
      "source": [
        "plt.plot(history.history['loss'])\n",
        "plt.show()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1152x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MB0XDfXM3tOP",
        "outputId": "33e96314-d110-4b60-df3d-b1041b553681"
      },
      "source": [
        "get_3rd_layer_output = tf.keras.backend.function([best_model.layers[0].input],\n",
        "                                  [best_model.layers[2].output])\n",
        "encoder_output = get_3rd_layer_output(sensor_data)\n",
        "sensor_features = np.asarray(encoder_output).astype('float32')\n",
        "sensor_features = sensor_features.reshape(sensor_features.shape[1], sensor_features.shape[2])\n",
        "sensor_features.shape"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 60)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IjzlaHLKh1bu",
        "outputId": "edd22223-bb92-4e5d-e748-ea6464264b02"
      },
      "source": [
        "activity_data.shape"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 50)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ygZwbcSRiN7V",
        "outputId": "743b4978-2ea9-4436-de07-99a8d9a0d91c"
      },
      "source": [
        "activity_data = activity_data[:, 0]\n",
        "activity_data = activity_data.reshape(-1, 1).astype('int32')\n",
        "activity_data.shape"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mrjWIm_4iv2k",
        "outputId": "178f14d3-da8c-49b9-ea69-44895aee8355"
      },
      "source": [
        "final_data = np.append(activity_data, sensor_features, axis=1)\n",
        "final_data.shape"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28316, 61)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3GEWu29zgo-o"
      },
      "source": [
        "np.savetxt(\"sensor_features_lstm_tuned.csv\", final_data, delimiter=\",\")"
      ],
      "execution_count": 32,
      "outputs": []
    }
  ]
}