notebooks/03_Baseline_model.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/YaninaK/predictive-maintenance/blob/main/notebooks/03_Baseline_model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Модель раннего обнаружения неисправностей промышленного оборудования\n",
        "## Базовая модель\n",
        "\n",
        "#### [Чтение и предварительная очистка данных](https://colab.research.google.com/drive/1UHlDhDV11MuN3C4U-KqpJP736KmudnyA?usp=sharing)\n",
        "\n",
        "#### [Исследователский анализ данных](https://colab.research.google.com/drive/1E0JIOFlRn83lFcZxb2tp2mXKXB5N19t4?usp=sharing)"
      ],
      "metadata": {
        "id": "Vvzf-626kqJ3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "ОПИСАНИЕ ЗАДАЧИ\n",
        "\n",
        "Разработать модель, определяющую возможность возникновения нештатной работы оборудования на временном горизонте не менее 3 часов до аварийного простоя."
      ],
      "metadata": {
        "id": "JZTIpSf6kxod"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "[РЕСУРСЫ](https://drive.google.com/file/d/1jrbfHULbZuCnwJQwNllQUFlCGpR_lHDc/view?usp=sharing)\n",
        "\n",
        "Наборы обезличенных данных из внутренних систем ПАО «Северсталь», содержащие:\n",
        "* Перечень нештатных событий, приведших к остановке линии;\n",
        "* Перечень нештатных событий, повлекших деградацию функций агрегатов;\n",
        "* Перечень сигналов с датчиков, контроллеров."
      ],
      "metadata": {
        "id": "raHYZ7h-kySA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qpJLE0aak1xe",
        "outputId": "0d4687c2-f323-45f6-d81e-ab57a075ce62"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/YaninaK/predictive-maintenance.git -q\n",
        "!pip install -r predictive-maintenance/requirements_Colab.txt -q"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YB_hsyHilo00",
        "outputId": "125913fa-2114-4b82-d931-c9ca159f9279"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m310.8/310.8 MB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.3/75.3 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.8/79.8 kB\u001b[0m \u001b[31m10.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Building wheel for pyspark (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
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    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/predictive-maintenance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RWeYNyTdlwqS",
        "outputId": "ebef8034-6252-48f5-f211-95d80bd41eb6"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/predictive-maintenance\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import sys\n",
        "import os\n",
        "\n",
        "sys.path.append(os.getcwd())\n",
        "sys.path.append(os.path.join(os.getcwd(), \"src\", \"predictive_maintenance\"))"
      ],
      "metadata": {
        "id": "VD48OdEZlx8A"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import joblib\n",
        "import tensorflow as tf\n",
        "\n",
        "import bambi as bmb\n",
        "import arviz as az\n",
        "\n",
        "from data.utilities import load_X,  load_y, get_y_summary\n",
        "from features.etalon_periods import (\n",
        "    select_etalon_periods, get_pca_components, generate_etalon_dataset,\n",
        ")\n",
        "from models.stoppages import get_M1_dataset\n",
        "from data.anomalies import get_M3_dataset, generate_targets\n",
        "from data.train_test_datasets import (\n",
        "    combine_test_intervals, generate_test_dataset\n",
        ")\n",
        "from models.model_LSTM import get_model_LSTM\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "XKrLmWNX6DPU"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "metadata": {
        "id": "e4vpidOIl55b"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "az.style.use(\"arviz-darkgrid\")\n",
        "SEED = 25"
      ],
      "metadata": {
        "id": "tPQJDLY7GdR8"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PATH = '/content/drive/MyDrive/ML_projects/02_Predictive_maintenance/'\n",
        "FOLDER = \"data/02_intermediate/\""
      ],
      "metadata": {
        "id": "HwuGKLR3GgRY"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1. Загрузка данных"
      ],
      "metadata": {
        "id": "PWdg8aSymKG9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "messages = (\n",
        "    pd.read_parquet(PATH + FOLDER + \"messages_unified.parquet\")\n",
        "    .sort_values(by='ДАТА_НАЧАЛА_НЕИСПРАВНОСТИ')\n",
        "    .reset_index(drop=True)\n",
        ")\n",
        "print(f'messages.shape = {messages.shape}\\n')\n",
        "messages.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 184
        },
        "id": "qh2QkEb5mJSy",
        "outputId": "f8aca8cb-b80c-43a1-f04f-a30a17afce8c"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "messages.shape = (981, 11)\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
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              "               МАШИНА         ИМЯ_МАШИНЫ               ТЕХ_МЕСТО  \\\n",
              "0         AA2/006-006  ЭКСГАУСТЕР А/М №9     AA2/006-006-002-008   \n",
              "1  CH-AGP-AG2/011-005  ЭКСГАУСТЕР А/М №9  CH-AGP-AG2/011-005-002   \n",
              "\n",
              "                    НАЗВАНИЕ_ТЕХ_МЕСТА ВИД_СООБЩЕНИЯ              ОПИСАНИЕ  \\\n",
              "0     ЗАПОРНАЯ АРМАТУРА ЭКСГАУСТЕРА №9            M3  неисправен двигатель   \n",
              "1  МАСЛОСТАНЦИЯ ЖИДКОЙ СМАЗКИ ЭКСГ. №9            M3  неисправен двигатель   \n",
              "\n",
              "  ДАТА_НАЧАЛА_НЕИСПРАВНОСТИ ДАТА_УСТРАНЕНИЯ_НЕИСПРАВНОСТИ ТЕКСТ_ГРУППЫ_КОДОВ  \\\n",
              "0       2019-01-21 00:00:00                    2019-02-25               None   \n",
              "1       2019-01-21 12:26:08                    2019-02-25               None   \n",
              "\n",
              "  equipment                        unified_name  \n",
              "0         9     ЗАПОРНАЯ АРМАТУРА ЭКСГАУСТЕРА №  \n",
              "1         9  МАСЛОСТАНЦИЯ ЖИДКОЙ СМАЗКИ ЭКСГ_ №  "
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              "      <th>МАШИНА</th>\n",
              "      <th>ИМЯ_МАШИНЫ</th>\n",
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              "      <th>0</th>\n",
              "      <td>AA2/006-006</td>\n",
              "      <td>ЭКСГАУСТЕР А/М №9</td>\n",
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              "      <td>2019-01-21 12:26:08</td>\n",
              "      <td>2019-02-25</td>\n",
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              "      <td>9</td>\n",
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              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
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              "\n",
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              "    40% {\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
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              "        document.querySelector('#df-3c1be95c-dc0e-429c-bc42-101659f3f416 button');\n",
              "      quickchartButtonEl.style.display =\n",
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              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2. Модель LSTM"
      ],
      "metadata": {
        "id": "rEaGE6T0i72-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "INPUT_SEQUENCE_LENGTH = 23"
      ],
      "metadata": {
        "id": "PU4YsAbw_HB4"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2.1. Генерация эталонного датасета."
      ],
      "metadata": {
        "id": "k8Y2cmcim8IY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "etalon_periods = select_etalon_periods(messages, path=PATH)\n",
        "etalon_periods.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "uX8LKiCYkhrQ",
        "outputId": "310f7ca9-5eea-4b91-a134-b87e9ce7f303"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                        col_0     col_1     col_2     col_3     col_4  \\\n",
              "dt                                                                      \n",
              "2019-01-16 13:00:00  1.563937  0.737879  0.645386  1.629186  3.351842   \n",
              "2019-01-16 14:00:00  1.557182  0.743087  0.638876  1.568169  2.738252   \n",
              "\n",
              "                        col_5       col_6      col_7     col_8      col_9  \\\n",
              "dt                                                                          \n",
              "2019-01-16 13:00:00  0.744417  119.448131  40.319054  33.33406  41.457225   \n",
              "2019-01-16 14:00:00  0.730758  119.764306  40.165818  33.05043  41.361075   \n",
              "\n",
              "                        col_10     col_11     col_12      col_13      col_14  \\\n",
              "dt                                                                             \n",
              "2019-01-16 13:00:00  39.738215  39.953993  44.636200  360.921722  360.921722   \n",
              "2019-01-16 14:00:00  39.622131  39.864005  44.536324  357.194764  357.194764   \n",
              "\n",
              "                         col_15  equipment  \n",
              "dt                                          \n",
              "2019-01-16 13:00:00  243.680833          4  \n",
              "2019-01-16 14:00:00  244.688722          4  "
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th>2019-01-16 13:00:00</th>\n",
              "      <td>1.563937</td>\n",
              "      <td>0.737879</td>\n",
              "      <td>0.645386</td>\n",
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              "      <td>4</td>\n",
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              "    <tr>\n",
              "      <th>2019-01-16 14:00:00</th>\n",
              "      <td>1.557182</td>\n",
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              "      <td>2.738252</td>\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-37b76960-4710-413e-9d95-ab996f71cae5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
              "  <script>\n",
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              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
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              "    }\n",
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              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4bf8b5b4-cc05-4ae9-a6eb-3f15925861d4 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "etalon_features, scaler_lstm, pca = get_pca_components(etalon_periods)\n",
        "etalon_features.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "7ihYsIKgY54N",
        "outputId": "8e9e1b3b-8bef-4fe2-8c60-73efd5034d58"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     factor_0  factor_1  factor_2  Hotelling's T-squared  \\\n",
              "dt                                                                         \n",
              "2019-01-16 13:00:00 -0.988189  0.345751 -2.726740               3.577083   \n",
              "2019-01-16 14:00:00 -0.861942  0.575467 -2.257506               2.532197   \n",
              "\n",
              "                     Q residuals  equipment  \n",
              "dt                                           \n",
              "2019-01-16 13:00:00    16.641088          4  \n",
              "2019-01-16 14:00:00    10.083960          4  "
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              "      <th></th>\n",
              "      <th>factor_0</th>\n",
              "      <th>factor_1</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-01-16 13:00:00</th>\n",
              "      <td>-0.988189</td>\n",
              "      <td>0.345751</td>\n",
              "      <td>-2.726740</td>\n",
              "      <td>3.577083</td>\n",
              "      <td>16.641088</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-16 14:00:00</th>\n",
              "      <td>-0.861942</td>\n",
              "      <td>0.575467</td>\n",
              "      <td>-2.257506</td>\n",
              "      <td>2.532197</td>\n",
              "      <td>10.083960</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-16ccc559-1acb-4a60-beb1-65997fe742d4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-16ccc559-1acb-4a60-beb1-65997fe742d4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-16ccc559-1acb-4a60-beb1-65997fe742d4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-12476e99-f897-4d17-b180-79250b39248e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-12476e99-f897-4d17-b180-79250b39248e')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-12476e99-f897-4d17-b180-79250b39248e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "etalon_dataset = generate_etalon_dataset(etalon_features)\n",
        "etalon_dataset.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uj_uHPDrV5s7",
        "outputId": "d179e5ff-69dc-40df-8e7e-7a48be5f29f7"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(7062, 50, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ind = np.arange(etalon_dataset.shape[0])\n",
        "np.random.shuffle(ind)\n",
        "etalon_dataset = etalon_dataset[ind, :, :]"
      ],
      "metadata": {
        "id": "SobDzrJybUj_"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2.2. Обучение модели LSTM"
      ],
      "metadata": {
        "id": "sJcbjDqPgSTp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "t = INPUT_SEQUENCE_LENGTH\n",
        "model_path = \"models/LSTM_model.h5\"\n",
        "history_path = \"models/model_LSTM_training_history.joblib\""
      ],
      "metadata": {
        "id": "8s8Zj5URuQ-w"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "regenerate = False\n",
        "if regenerate:\n",
        "  lstm_model = get_model_LSTM()\n",
        "  n_epochs = 60\n",
        "  batch_size = 64\n",
        "  m = 1024\n",
        "  reduce_lr = tf.keras.callbacks.LearningRateScheduler(\n",
        "      lambda epoch: 3e-2 * 0.95 ** epoch\n",
        "  )\n",
        "  history = lstm_model.fit(\n",
        "      etalon_dataset[:-m, :t, :], etalon_dataset[:-m, t:, :],\n",
        "      epochs=n_epochs,\n",
        "      validation_data=(etalon_dataset[-m:, :t, :], etalon_dataset[-m:, t:, :]),\n",
        "      batch_size=batch_size,\n",
        "      verbose=1,\n",
        "      callbacks=[reduce_lr],\n",
        "      shuffle=True,\n",
        "      workers=-1,\n",
        "      use_multiprocessing=True\n",
        "  )\n",
        "  lstm_model.save(PATH + model_path)\n",
        "  history = history.history\n",
        "  joblib.dump(history, PATH + history_path)\n",
        "\n",
        "else:\n",
        "  lstm_model = tf.keras.models.load_model(PATH + model_path)\n",
        "  history = joblib.load(PATH + history_path)"
      ],
      "metadata": {
        "id": "z_SJ_BbBU9VX"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(lstm_model.summary())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qb5UszO1AsmE",
        "outputId": "7e09607a-37d8-4281-d904-e2d187b485cf"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"lstm_model\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                Output Shape                 Param #   Connected to                  \n",
            "==================================================================================================\n",
            " encoder_inputs (InputLayer  [(None, 23, 5)]              0         []                            \n",
            " )                                                                                                \n",
            "                                                                                                  \n",
            " encoder_output1 (LSTM)      [(None, 23, 150),            93600     ['encoder_inputs[0][0]']      \n",
            "                              (None, 150),                                                        \n",
            "                              (None, 150)]                                                        \n",
            "                                                                                                  \n",
            " encoder_output2 (LSTM)      [(None, 150),                180600    ['encoder_output1[0][0]']     \n",
            "                              (None, 150),                                                        \n",
            "                              (None, 150)]                                                        \n",
            "                                                                                                  \n",
            " decoder_inputs (RepeatVect  (None, 27, 150)              0         ['encoder_output2[0][0]']     \n",
            " or)                                                                                              \n",
            "                                                                                                  \n",
            " decoder_l1 (LSTM)           (None, 27, 150)              180600    ['decoder_inputs[0][0]',      \n",
            "                                                                     'encoder_output1[0][1]',     \n",
            "                                                                     'encoder_output1[0][2]']     \n",
            "                                                                                                  \n",
            " decoder_l2 (LSTM)           (None, 27, 150)              180600    ['decoder_l1[0][0]',          \n",
            "                                                                     'encoder_output2[0][1]',     \n",
            "                                                                     'encoder_output2[0][2]']     \n",
            "                                                                                                  \n",
            " decoder_outputs (TimeDistr  (None, 27, 5)                755       ['decoder_l2[0][0]']          \n",
            " ibuted)                                                                                          \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 636155 (2.43 MB)\n",
            "Trainable params: 636155 (2.43 MB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "__________________________________________________________________________________________________\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6, 4))\n",
        "plt.plot(history['loss'])\n",
        "plt.plot(history['val_loss'])\n",
        "plt.title(\"LSTM model Loss\")\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend(['Train', 'Valid'])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "rr5YoDuE7x3M",
        "outputId": "cb3482fd-7096-4a4a-8f10-fbb75e3a62ee"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3. Байесовская модель"
      ],
      "metadata": {
        "id": "xjDX76986QYf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3.1. Подготовка эталонных данных для байесовской модели"
      ],
      "metadata": {
        "id": "oS0kSueSezwN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pred_etalon = lstm_model.predict(etalon_dataset[:, :t, :])\n",
        "pred_etalon.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "69fEVW9nX3FR",
        "outputId": "9171af3c-5183-41c9-d29d-3de0f8180e4c"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "221/221 [==============================] - 6s 5ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(7062, 27, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "T2_Q_from_LSTM_etalon = pred_etalon[:, :, -2:].reshape(-1, 2)\n",
        "T2_Q_from_LSTM_etalon = pd.DataFrame(T2_Q_from_LSTM_etalon, columns=['T2', 'Q'])\n",
        "T2_Q_from_LSTM_etalon['good'] = 1\n",
        "\n",
        "T2_Q_from_LSTM_etalon.tail(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "Ezbm_NhrZOqO",
        "outputId": "763ac5a7-54f9-4dca-81f7-f42b8f837dcf"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              T2         Q  good\n",
              "190672  1.717851  4.149052     1\n",
              "190673  1.717983  4.149205     1"
            ],
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6562b0a8-72bf-483e-b6d6-71c25f180437')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6562b0a8-72bf-483e-b6d6-71c25f180437 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3.2. Обучение модели на эталонных данных"
      ],
      "metadata": {
        "id": "9Zcyg2-1fHpk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bayesian_model_path = \"models/Bayesian_model_v3.h5netcdf\""
      ],
      "metadata": {
        "id": "1bw_GkzBUx00"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "regenerate = False\n",
        "if regenerate:\n",
        "  bmb_model = bmb.Model(\n",
        "    \"good ~ T2 + Q\", data=T2_Q_from_LSTM_etalon, family=\"bernoulli\"\n",
        "  )\n",
        "  model_fitted = bmb_model.fit(\n",
        "      draws=2000,\n",
        "      target_accept=0.85,\n",
        "      random_seed=SEED,\n",
        "      idata_kwargs={\"log_likelihood\": True},\n",
        "  )\n",
        "  model_fitted.to_netcdf(PATH + bayesian_model_path)\n",
        "else:\n",
        "  model_fitted = az.InferenceData.from_netcdf(PATH + bayesian_model_path)\n",
        "\n",
        "az.plot_trace(model_fitted, compact=False);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 628
        },
        "id": "WrzPbmT20Uas",
        "outputId": "02623530-99d6-4a64-b5d5-5dd19ae24ddf"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 6 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(columns=['Intercept', 'T2','Q'])\n",
        "for i in range(2):\n",
        "  intercept = model_fitted.posterior['Intercept'].to_numpy()[i]\n",
        "  T2 = model_fitted.posterior['T2'].to_numpy()[i]\n",
        "  Q = model_fitted.posterior['Q'].to_numpy()[i]\n",
        "\n",
        "  df_ = pd.DataFrame(zip(intercept, T2, Q), columns=['Intercept', 'T2','Q'])\n",
        "  df = pd.concat([df, df_], axis=0)\n",
        "\n",
        "df.describe().T"
      ],
      "metadata": {
        "id": "QlMaB9Mm3LAf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "1e226b8c-44b7-4d46-9aba-b63db44165be"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            count       mean       std       min        25%        50%  \\\n",
              "Intercept  4000.0  11.734078  1.797396  6.392747  10.524026  11.603146   \n",
              "T2         4000.0   0.481127  0.546622 -0.473097   0.047160   0.372549   \n",
              "Q          4000.0   0.164576  0.191092 -0.198077   0.014871   0.132381   \n",
              "\n",
              "                 75%        max  \n",
              "Intercept  12.858251  19.892180  \n",
              "T2          0.818187   3.330774  \n",
              "Q           0.277425   1.036800  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Intercept</th>\n",
              "      <td>4000.0</td>\n",
              "      <td>11.734078</td>\n",
              "      <td>1.797396</td>\n",
              "      <td>6.392747</td>\n",
              "      <td>10.524026</td>\n",
              "      <td>11.603146</td>\n",
              "      <td>12.858251</td>\n",
              "      <td>19.892180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>T2</th>\n",
              "      <td>4000.0</td>\n",
              "      <td>0.481127</td>\n",
              "      <td>0.546622</td>\n",
              "      <td>-0.473097</td>\n",
              "      <td>0.047160</td>\n",
              "      <td>0.372549</td>\n",
              "      <td>0.818187</td>\n",
              "      <td>3.330774</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Q</th>\n",
              "      <td>4000.0</td>\n",
              "      <td>0.164576</td>\n",
              "      <td>0.191092</td>\n",
              "      <td>-0.198077</td>\n",
              "      <td>0.014871</td>\n",
              "      <td>0.132381</td>\n",
              "      <td>0.277425</td>\n",
              "      <td>1.036800</td>\n",
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              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f1940e16-f8c8-4441-88ab-2894bb3fd6ff button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f1940e16-f8c8-4441-88ab-2894bb3fd6ff');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-29514df0-87bb-4287-90f1-7bc0d07c0128\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-29514df0-87bb-4287-90f1-7bc0d07c0128')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-29514df0-87bb-4287-90f1-7bc0d07c0128 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3.3. Предсказание остановок."
      ],
      "metadata": {
        "id": "GEvRMF7Sdiax"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### LSTM input"
      ],
      "metadata": {
        "id": "6IQubpFsnAXZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "INPUT_SEQUENCE_LENGTH"
      ],
      "metadata": {
        "id": "JfuKamRmm0PV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2bc47410-4fb8-4f23-cee1-ea77303de27a"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "M1_dataset, M1_labels = get_M1_dataset(\n",
        "    scaler_lstm,\n",
        "    pca,\n",
        "    messages,\n",
        "    path=PATH\n",
        ")\n",
        "M1_dataset.shape, len(M1_labels)"
      ],
      "metadata": {
        "id": "13-v-Q3hbFxw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "348cd640-d7d3-4eca-e72f-05be9cf4023f"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((61, 23, 5), 61)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### LSTM output"
      ],
      "metadata": {
        "id": "Y79htNiLnK_h"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pred_stoppages = lstm_model.predict(M1_dataset)\n",
        "pred_stoppages.shape"
      ],
      "metadata": {
        "id": "RENxOUcUXu4U",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d20623d6-1a0d-4d63-f1ab-bb1f1fabcf17"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2/2 [==============================] - 0s 8ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(61, 27, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "T2_Q_from_stoppages = pred_stoppages[:, :, -2:].reshape(-1, 2)\n",
        "T2_Q_from_stoppages = pd.DataFrame(T2_Q_from_stoppages, columns=['T2', 'Q'])\n",
        "\n",
        "T2_Q_from_stoppages.tail(2)"
      ],
      "metadata": {
        "id": "vx6-Yr_2bF1H",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "c71293d6-a372-4413-8aa3-f63aae549012"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            T2          Q\n",
              "1645  4.727775  69.477028\n",
              "1646  4.737813  69.449219"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b2e20e61-2d9b-4405-b2ae-833ae716b0cf\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>T2</th>\n",
              "      <th>Q</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1645</th>\n",
              "      <td>4.727775</td>\n",
              "      <td>69.477028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1646</th>\n",
              "      <td>4.737813</td>\n",
              "      <td>69.449219</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b2e20e61-2d9b-4405-b2ae-833ae716b0cf')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b2e20e61-2d9b-4405-b2ae-833ae716b0cf button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b2e20e61-2d9b-4405-b2ae-833ae716b0cf');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7b52d24b-b277-4bac-800f-ec5ddac42926\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7b52d24b-b277-4bac-800f-ec5ddac42926')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7b52d24b-b277-4bac-800f-ec5ddac42926 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Инференс байесовской модели горизонт - 27 часов."
      ],
      "metadata": {
        "id": "bC57lIbZGiQf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bmb_model = bmb.Model(\n",
        "    \"good ~ T2 + Q\", data=T2_Q_from_LSTM_etalon, family=\"bernoulli\"\n",
        ")\n",
        "bmb_model.predict(model_fitted, data=T2_Q_from_stoppages)"
      ],
      "metadata": {
        "id": "BxKJcRmotHrB"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "good_posterior = az.extract(model_fitted)['good_mean']\n",
        "y_pred = good_posterior.to_numpy().mean(axis=1)\n",
        "y_pred.shape"
      ],
      "metadata": {
        "id": "umpo5dEctHwX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8393df98-62d5-44c4-9b58-8299df195864"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1647,)"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y = y_pred.reshape(-1, 27)\n",
        "\n",
        "i = -1\n",
        "plt.figure(figsize=(6, 3))\n",
        "plt.plot(y[i, :]);"
      ],
      "metadata": {
        "id": "nYtvLp-ptjn7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        },
        "outputId": "569c3678-ab16-4f8b-e1f9-a1ba61f365e0"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Если убрать 3 первые и 3 последние точки, то график приобретает ожидаемую форму:"
      ],
      "metadata": {
        "id": "1nAPgxuBt8-X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "i = -1\n",
        "plt.figure(figsize=(6, 3))\n",
        "plt.plot(y[i, 3:-3]);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        },
        "id": "483wDHkut9fQ",
        "outputId": "34b4ad61-6e5d-4928-9330-af230761b64b"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "В таком случае, о неплановой остановке, которая произойдет через 27 часов, мы можем предупредить за сутки. И это происходит во всех 61 случаях:"
      ],
      "metadata": {
        "id": "CykpBRg4uGbH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "y_tranc = y[:, 3:-3].flatten()\n",
        "\n",
        "plt.figure(figsize=(15, 3))\n",
        "plt.plot(y_tranc);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        },
        "id": "6UxIFZVbuHLz",
        "outputId": "6f3f0605-0ca2-4239-dc41-ae1e537cfbbf"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}