notebooks/version_06_2/6_hybrid_modelling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using FEDOT for hybrid modeling with custom model tuning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### FEDOT version = 0.6.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "!pip install fedot==0.6.2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Original repository on GitHub](https://github.com/nccr-itmo/FEDOT)\n",
    "\n",
    "This tutorial was prepared by [Natural Systems Simulation Team](https://github.com/ITMO-NSS-team)\n",
    "\n",
    "--- \n",
    "\n",
    "If you want to learn some basic things about FEDOT and time series forecasting, you can use [this notebook](3_intro_ts_forecasting.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Additional imports \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from hyperopt import hp\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "# Imports for creating plots\n",
    "import matplotlib.pyplot as plt\n",
    "from pylab import rcParams\n",
    "rcParams['figure.figsize'] = 18, 7\n",
    "\n",
    "# Pipeline and nodes\n",
    "from fedot.core.pipelines.node import PrimaryNode, SecondaryNode\n",
    "from fedot.core.pipelines.pipeline import Pipeline\n",
    "\n",
    "# Data\n",
    "from fedot.core.repository.dataset_types import DataTypesEnum\n",
    "from fedot.core.data.data import InputData\n",
    "from fedot.core.data.data_split import train_test_data_setup\n",
    "\n",
    "# Tasks\n",
    "from fedot.core.repository.tasks import TaskTypesEnum, Task, TsForecastingParams\n",
    "\n",
    "#Tuning\n",
    "from fedot.core.pipelines.tuning.search_space import SearchSpace\n",
    "from fedot.core.pipelines.tuning.unified import PipelineTuner\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import logging\n",
    "logging.raiseExceptions = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Read the file\n",
    "df = pd.read_csv('../data/metocean.csv')\n",
    "\n",
    "plt.plot(np.arange(len(df['value'])), df['value'])\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "# Specify forecast length\n",
    "len_forecast = 50\n",
    "\n",
    "# Got univariate time series as numpy array\n",
    "time_series = np.array(df['value'])\n",
    "\n",
    "# Wrapp data into InputData\n",
    "task = Task(TaskTypesEnum.ts_forecasting, TsForecastingParams(forecast_length=len_forecast))\n",
    "\n",
    "# Split data into train and test\n",
    "train_input, predict_input = train_test_data_setup(InputData(idx=range(len(time_series)),\n",
    "                                                                 features=time_series,\n",
    "                                                                 target=time_series,\n",
    "                                                                 task=Task(TaskTypesEnum.ts_forecasting,\n",
    "                                                                           TsForecastingParams(forecast_length=len_forecast)),\n",
    "                                                                 data_type=DataTypesEnum.ts))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have a time series of sea level. Based on this time series we will conduct the case of forecasting with custom model implantation in the pipeline."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom model specification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some custom models have necessary step of fitting, but some of them such as domain specific models doesn't need fitting at all. For using with FEDOT custom model should be wrapped into function that provides fit (if it is necessary) and predict steps. Fit step returns model object, predict step returns predicted values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's prepare a function for imitation custom model without fitting\n",
    "def domain_model_imitation_predict(fitted_model: any, idx: np.array, predict_data: np.array, params: dict):\n",
    "    a = params.get('a')\n",
    "    b = params.get('b')\n",
    "    shape = predict_data.shape\n",
    "    result = np.random.rand(*shape) * a + b\n",
    "    # Available output_type's 'table', 'ts', 'image', 'text'\n",
    "    return result, 'table'\n",
    "\n",
    "# Function for custom regression model imitation (fit)\n",
    "def custom_ml_model_imitation_fit(idx: np.array, features: np.array, target: np.array, params: dict):\n",
    "    alpha = params.get('alpha')\n",
    "    reg = Ridge(alpha=alpha)\n",
    "    reg.fit(features, target)\n",
    "    return reg\n",
    "\n",
    "# Function for custom regression model imitation (predict)\n",
    "def custom_ml_model_imitation_predict(fitted_model: any, idx: np.array, features: np.array, params: dict):\n",
    "    res = fitted_model.predict(features)\n",
    "    return res, 'table'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Including custom model into pipeline is provided by using custom parameters of node. Also there should be indicated parameters of model for tune and initial approximation for them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's prepare a function for pipeline with custom node without fitting\n",
    "def get_domain_pipeline():\n",
    "    \"\"\"\n",
    "        Pipeline looking like this\n",
    "        lagged -> custom -> ridge\n",
    "    \"\"\"\n",
    "    lagged_node = PrimaryNode('lagged')\n",
    "    lagged_node.parameters = {'window_size': 10}\n",
    "\n",
    "    # For custom model params as initial approximation and model as function is necessary\n",
    "    custom_node = SecondaryNode('custom', nodes_from=[lagged_node])\n",
    "    custom_node.parameters = {\"a\": -50, \"b\": 500, 'model_predict': domain_model_imitation_predict}\n",
    "\n",
    "    node_final = SecondaryNode('ridge', nodes_from=[custom_node])\n",
    "    pipeline = Pipeline(node_final)\n",
    "\n",
    "    return pipeline\n",
    "\n",
    "# Function for pipeline with custom node with fitting\n",
    "def get_fitting_custom_pipeline():\n",
    "    \"\"\"\n",
    "        Pipeline looking like this\n",
    "        lagged -> custom -> ridge\n",
    "    \"\"\"\n",
    "    lagged_node = PrimaryNode('lagged')\n",
    "    lagged_node.parameters = {'window_size': 10}\n",
    "\n",
    "    # For custom model params as initial approximation and model as function is necessary\n",
    "    custom_node = SecondaryNode('custom', nodes_from=[lagged_node])\n",
    "    custom_node.parameters = {'alpha': 5,\n",
    "                                 'model_predict': custom_ml_model_imitation_predict,\n",
    "                                 'model_fit': custom_ml_model_imitation_fit}\n",
    "\n",
    "    node_final = SecondaryNode('lasso', nodes_from=[custom_node])\n",
    "    pipeline = Pipeline(node_final)\n",
    "\n",
    "    return pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For pipeline tuning search space of custom model parameters should be specified. Hyperopt wrapper is used for that."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Function for prediction with/without fitting custom model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder\n",
    "from fedot.core.pipelines.tuning.unified import PipelineTuner\n",
    "from fedot.core.repository.quality_metrics_repository import \\\n",
    "    MetricsRepository, RegressionMetricsEnum\n",
    "\n",
    "\n",
    "def run_pipeline_tuning(pipeline_type):\n",
    "\n",
    "    if pipeline_type == 'with_fit':\n",
    "        pipeline = get_fitting_custom_pipeline()\n",
    "        # Setting custom search space for tuner (necessary)\n",
    "        # model and output_type should be wrapped into hyperopt\n",
    "        custom_search_space = {'custom': {\n",
    "            'alpha': (hp.uniform, [0.01, 10]),\n",
    "            'model_predict': (hp.choice, [[custom_ml_model_imitation_predict]]),\n",
    "            'model_fit': (hp.choice, [[custom_ml_model_imitation_fit]])}}\n",
    "    elif pipeline_type == 'without_fit':\n",
    "        pipeline = get_domain_pipeline()\n",
    "        # Setting custom search space for tuner (necessary)\n",
    "        # model and output_type should be wrapped into hyperopt\n",
    "        custom_search_space = {'custom': {'a': (hp.uniform, [-100, 100]),\n",
    "                                          'b': (hp.uniform, [0, 1000]),\n",
    "                                          'model_predict': (hp.choice, [[domain_model_imitation_predict]])}}\n",
    "    pipeline.fit_from_scratch(train_input)\n",
    "    pipeline.print_structure()\n",
    "    # Get prediction with initial approximation\n",
    "    predicted_before_tuning = pipeline.predict(predict_input).predict\n",
    "\n",
    "    replace_default_search_space = True\n",
    "\n",
    "    # Start tuning all nodes in the pipeline \n",
    "    tuner = TunerBuilder(train_input.task)\\\n",
    "            .with_tuner(PipelineTuner)\\\n",
    "            .with_metric(RegressionMetricsEnum.MSE)\\\n",
    "            .with_iterations(50) \\\n",
    "            .with_cv_folds(None) \\\n",
    "            .with_validation_blocks(3) \\\n",
    "            .with_search_space(SearchSpace(custom_search_space=custom_search_space,\n",
    "                                                                replace_default_search_space=replace_default_search_space))\\\n",
    "            .build(train_input)\n",
    "    tuned_pipeline = tuner.tune(pipeline)\n",
    "    \n",
    "    # Fit pipeline on the entire train data\n",
    "    pipeline.fit(train_input)\n",
    "    # Predict tuned pipeline\n",
    "    predicted_values = pipeline.predict(predict_input).predict\n",
    "    pipeline.print_structure()\n",
    "\n",
    "    plt.plot(np.arange(len(predicted_before_tuning[0])), predicted_before_tuning[0], label='Before tuning')\n",
    "    plt.plot(np.arange(len(predicted_values[0])), predicted_values[0], label='After tuning')\n",
    "    plt.plot(np.arange(len(predict_input.target)), predict_input.target, label='Real')\n",
    "    plt.legend()\n",
    "    plt.grid()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Case with using model with fitting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline structure:\n",
      "{'depth': 3, 'length': 3, 'nodes': [lasso, custom, lagged]}\n",
      "lasso - {}\n",
      "custom - {'alpha': 5, 'model_predict': <function custom_ml_model_imitation_predict at 0x0000020A83C7C3A0>, 'model_fit': <function custom_ml_model_imitation_fit at 0x0000020A83C7C1F0>}\n",
      "lagged - {'window_size': 10}\n",
      "2023-02-24 11:30:12,943 - DataSourceSplitter - Hold out validation is applied.\n",
      "2023-02-24 11:30:12,944 - PipelineTuner - Hyperparameters optimization start: estimation of metric for initial pipeline\n",
      "2023-02-24 11:30:13,089 - PipelineTuner - Initial pipeline: {'depth': 3, 'length': 3, 'nodes': [lasso, custom, lagged]}\n",
      "lasso - {}\n",
      "custom - {'alpha': 5, 'model_predict': <function custom_ml_model_imitation_predict at 0x0000020A83C7C3A0>, 'model_fit': <function custom_ml_model_imitation_fit at 0x0000020A83C7C1F0>}\n",
      "lagged - {'window_size': 10} \n",
      "Initial metric: 241.516\n",
      "  0%|                                                                            | 0/5 [00:00<?, ?trial/s, best loss=?]2023-02-24 11:30:13,095 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:13,097 - TPE using 0 trials\n",
      " 20%|██████████▏                                        | 1/5 [00:00<00:00,  8.06trial/s, best loss: 242.1024028324349]2023-02-24 11:30:13,220 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:13,222 - TPE using 1/1 trials with best loss 242.102403\n",
      "2023-02-24 11:30:13,304 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:13,306 - TPE using 2/2 trials with best loss 242.102403\n",
      " 60%|██████████████████████████████▌                    | 3/5 [00:00<00:00,  9.85trial/s, best loss: 242.1024028324349]2023-02-24 11:30:13,408 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:13,409 - TPE using 3/3 trials with best loss 242.102403\n",
      " 80%|████████████████████████████████████████          | 4/5 [00:00<00:00,  7.64trial/s, best loss: 240.99145557415207]2023-02-24 11:30:13,595 - build_posterior_wrapper took 0.001930 seconds\n",
      "2023-02-24 11:30:13,596 - TPE using 4/4 trials with best loss 240.991456\n",
      "100%|██████████████████████████████████████████████████| 5/5 [00:00<00:00,  8.20trial/s, best loss: 240.99145557415207]\n",
      " 10%|███████▌                                                                   | 5/50 [00:00<?, ?trial/s, best loss=?]2023-02-24 11:30:13,709 - build_posterior_wrapper took 0.001994 seconds\n",
      "2023-02-24 11:30:13,710 - TPE using 5/5 trials with best loss 240.991456\n",
      "2023-02-24 11:30:13,714 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 481 to 240.\n",
      " 12%|█████▉                                           | 6/50 [00:00<00:14,  3.10trial/s, best loss: 240.99145557415207]2023-02-24 11:30:14,032 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:14,034 - TPE using 6/6 trials with best loss 240.991456\n",
      " 14%|██████▊                                          | 7/50 [00:00<00:08,  5.02trial/s, best loss: 240.99145557415207]2023-02-24 11:30:14,146 - build_posterior_wrapper took 0.001986 seconds\n",
      "2023-02-24 11:30:14,146 - TPE using 7/7 trials with best loss 240.991456\n",
      " 16%|███████▊                                         | 8/50 [00:00<00:07,  5.81trial/s, best loss: 240.99145557415207]2023-02-24 11:30:14,286 - build_posterior_wrapper took 0.001997 seconds\n",
      "2023-02-24 11:30:14,286 - TPE using 8/8 trials with best loss 240.991456\n",
      "2023-02-24 11:30:14,289 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 370 to 240.\n",
      " 18%|████████▊                                        | 9/50 [00:00<00:11,  3.71trial/s, best loss: 240.99145557415207]2023-02-24 11:30:14,705 - build_posterior_wrapper took 0.001991 seconds\n",
      "2023-02-24 11:30:14,706 - TPE using 9/9 trials with best loss 240.991456\n",
      "2023-02-24 11:30:14,709 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 396 to 240.\n",
      " 20%|█████████▌                                      | 10/50 [00:01<00:11,  3.45trial/s, best loss: 240.99145557415207]2023-02-24 11:30:15,030 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:15,031 - TPE using 10/10 trials with best loss 240.991456\n",
      "2023-02-24 11:30:15,034 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 436 to 240.\n",
      " 22%|██████████▌                                     | 11/50 [00:01<00:11,  3.30trial/s, best loss: 240.99145557415207]2023-02-24 11:30:15,359 - build_posterior_wrapper took 0.001006 seconds\n",
      "2023-02-24 11:30:15,359 - TPE using 11/11 trials with best loss 240.991456\n",
      "2023-02-24 11:30:15,363 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 412 to 240.\n",
      " 24%|███████████▌                                    | 12/50 [00:01<00:11,  3.30trial/s, best loss: 240.99145557415207]2023-02-24 11:30:15,662 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:15,663 - TPE using 12/12 trials with best loss 240.991456\n",
      "2023-02-24 11:30:15,751 - build_posterior_wrapper took 0.002001 seconds\n",
      "2023-02-24 11:30:15,752 - TPE using 13/13 trials with best loss 240.991456\n",
      "2023-02-24 11:30:15,755 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 444 to 240.\n",
      " 28%|█████████████▍                                  | 14/50 [00:02<00:09,  3.88trial/s, best loss: 240.99145557415207]2023-02-24 11:30:16,079 - build_posterior_wrapper took 0.000994 seconds\n",
      "2023-02-24 11:30:16,080 - TPE using 14/14 trials with best loss 240.991456\n",
      "2023-02-24 11:30:16,160 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:16,162 - TPE using 15/15 trials with best loss 165.660176\n",
      "2023-02-24 11:30:16,166 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 424 to 240.\n",
      " 32%|███████████████▋                                 | 16/50 [00:02<00:07,  4.35trial/s, best loss: 165.6601756513094]2023-02-24 11:30:16,460 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:16,461 - TPE using 16/16 trials with best loss 165.660176\n",
      "2023-02-24 11:30:16,464 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 407 to 240.\n",
      " 34%|████████████████▋                                | 17/50 [00:03<00:08,  3.75trial/s, best loss: 165.6601756513094]2023-02-24 11:30:16,852 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:16,853 - TPE using 17/17 trials with best loss 165.660176\n",
      "2023-02-24 11:30:16,856 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 304 to 240.\n",
      " 36%|█████████████████▋                               | 18/50 [00:03<00:08,  3.62trial/s, best loss: 165.6601756513094]2023-02-24 11:30:17,159 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:17,159 - TPE using 18/18 trials with best loss 165.660176\n",
      " 38%|██████████████████▌                              | 19/50 [00:03<00:08,  3.51trial/s, best loss: 165.6601756513094]2023-02-24 11:30:17,468 - build_posterior_wrapper took 0.000995 seconds\n",
      "2023-02-24 11:30:17,469 - TPE using 19/19 trials with best loss 165.660176\n",
      "2023-02-24 11:30:17,473 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 254 to 240.\n",
      " 40%|███████████████████▌                             | 20/50 [00:04<00:08,  3.35trial/s, best loss: 165.6601756513094]2023-02-24 11:30:17,803 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:17,805 - TPE using 20/20 trials with best loss 165.660176\n",
      " 42%|████████████████████▌                            | 21/50 [00:04<00:09,  3.17trial/s, best loss: 165.6601756513094]2023-02-24 11:30:18,163 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:18,164 - TPE using 21/21 trials with best loss 165.660176\n",
      "2023-02-24 11:30:18,249 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:18,250 - TPE using 22/22 trials with best loss 165.660176\n",
      " 46%|██████████████████████▌                          | 23/50 [00:04<00:06,  4.22trial/s, best loss: 165.6601756513094]2023-02-24 11:30:18,438 - build_posterior_wrapper took 0.001002 seconds\n",
      "2023-02-24 11:30:18,440 - TPE using 23/23 trials with best loss 165.660176\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 48%|███████████████████████▌                         | 24/50 [00:04<00:05,  4.49trial/s, best loss: 165.6601756513094]2023-02-24 11:30:18,617 - build_posterior_wrapper took 0.000997 seconds\n",
      "2023-02-24 11:30:18,618 - TPE using 24/24 trials with best loss 165.660176\n",
      " 50%|████████████████████████▌                        | 25/50 [00:05<00:05,  4.75trial/s, best loss: 165.6601756513094]2023-02-24 11:30:18,792 - build_posterior_wrapper took 0.001002 seconds\n",
      "2023-02-24 11:30:18,793 - TPE using 25/25 trials with best loss 165.660176\n",
      " 52%|█████████████████████████▍                       | 26/50 [00:05<00:04,  4.95trial/s, best loss: 165.6601756513094]2023-02-24 11:30:18,970 - build_posterior_wrapper took 0.001002 seconds\n",
      "2023-02-24 11:30:18,971 - TPE using 26/26 trials with best loss 165.660176\n",
      " 54%|██████████████████████████▍                      | 27/50 [00:05<00:04,  5.69trial/s, best loss: 165.6601756513094]2023-02-24 11:30:19,077 - build_posterior_wrapper took 0.001011 seconds\n",
      "2023-02-24 11:30:19,078 - TPE using 27/27 trials with best loss 165.660176\n",
      " 56%|███████████████████████████▍                     | 28/50 [00:05<00:04,  4.56trial/s, best loss: 165.6601756513094]2023-02-24 11:30:19,407 - build_posterior_wrapper took 0.002002 seconds\n",
      "2023-02-24 11:30:19,408 - TPE using 28/28 trials with best loss 165.660176\n",
      " 58%|████████████████████████████▍                    | 29/50 [00:05<00:04,  4.27trial/s, best loss: 165.6601756513094]2023-02-24 11:30:19,678 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:19,679 - TPE using 29/29 trials with best loss 165.660176\n",
      " 60%|█████████████████████████████▍                   | 30/50 [00:06<00:04,  4.76trial/s, best loss: 165.6601756513094]2023-02-24 11:30:19,830 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:19,832 - TPE using 30/30 trials with best loss 165.660176\n",
      " 62%|██████████████████████████████▍                  | 31/50 [00:06<00:04,  4.69trial/s, best loss: 165.6601756513094]2023-02-24 11:30:20,049 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:20,050 - TPE using 31/31 trials with best loss 165.660176\n",
      " 64%|███████████████████████████████▎                 | 32/50 [00:06<00:03,  5.17trial/s, best loss: 165.6601756513094]2023-02-24 11:30:20,197 - build_posterior_wrapper took 0.001161 seconds\n",
      "2023-02-24 11:30:20,198 - TPE using 32/32 trials with best loss 165.660176\n",
      "2023-02-24 11:30:20,208 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 320 to 240.\n",
      " 66%|████████████████████████████████▎                | 33/50 [00:06<00:04,  3.82trial/s, best loss: 165.6601756513094]2023-02-24 11:30:20,620 - build_posterior_wrapper took 0.002012 seconds\n",
      "2023-02-24 11:30:20,620 - TPE using 33/33 trials with best loss 165.660176\n",
      "2023-02-24 11:30:20,706 - build_posterior_wrapper took 0.001098 seconds\n",
      "2023-02-24 11:30:20,707 - TPE using 34/34 trials with best loss 165.660176\n",
      " 70%|██████████████████████████████████▎              | 35/50 [00:07<00:03,  4.55trial/s, best loss: 165.6601756513094]2023-02-24 11:30:20,962 - build_posterior_wrapper took 0.001998 seconds\n",
      "2023-02-24 11:30:20,962 - TPE using 35/35 trials with best loss 165.660176\n",
      "2023-02-24 11:30:20,972 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 257 to 240.\n",
      " 72%|███████████████████████████████████▎             | 36/50 [00:07<00:03,  4.10trial/s, best loss: 165.6601756513094]2023-02-24 11:30:21,277 - build_posterior_wrapper took 0.001160 seconds\n",
      "2023-02-24 11:30:21,278 - TPE using 36/36 trials with best loss 165.660176\n",
      "2023-02-24 11:30:21,367 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:21,368 - TPE using 37/37 trials with best loss 165.660176\n",
      " 76%|█████████████████████████████████████▏           | 38/50 [00:07<00:02,  5.42trial/s, best loss: 165.6601756513094]2023-02-24 11:30:21,479 - build_posterior_wrapper took 0.001994 seconds\n",
      "2023-02-24 11:30:21,480 - TPE using 38/38 trials with best loss 165.660176\n",
      " 78%|██████████████████████████████████████▏          | 39/50 [00:07<00:01,  5.79trial/s, best loss: 165.6601756513094]2023-02-24 11:30:21,612 - build_posterior_wrapper took 0.002000 seconds\n",
      "2023-02-24 11:30:21,612 - TPE using 39/39 trials with best loss 165.660176\n",
      "2023-02-24 11:30:21,623 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 350 to 240.\n",
      " 80%|███████████████████████████████████████▏         | 40/50 [00:08<00:02,  4.86trial/s, best loss: 165.6601756513094]2023-02-24 11:30:21,919 - build_posterior_wrapper took 0.000994 seconds\n",
      "2023-02-24 11:30:21,920 - TPE using 40/40 trials with best loss 165.660176\n",
      " 82%|████████████████████████████████████████▏        | 41/50 [00:08<00:01,  5.57trial/s, best loss: 165.6601756513094]2023-02-24 11:30:22,023 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:22,024 - TPE using 41/41 trials with best loss 165.660176\n",
      " 84%|█████████████████████████████████████████▏       | 42/50 [00:08<00:01,  5.23trial/s, best loss: 165.6601756513094]2023-02-24 11:30:22,247 - build_posterior_wrapper took 0.001006 seconds\n",
      "2023-02-24 11:30:22,248 - TPE using 42/42 trials with best loss 165.660176\n",
      " 86%|██████████████████████████████████████████▏      | 43/50 [00:08<00:01,  5.42trial/s, best loss: 165.6601756513094]2023-02-24 11:30:22,413 - build_posterior_wrapper took 0.001011 seconds\n",
      "2023-02-24 11:30:22,414 - TPE using 43/43 trials with best loss 165.660176\n",
      "2023-02-24 11:30:22,424 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 497 to 240.\n",
      " 88%|███████████████████████████████████████████      | 44/50 [00:09<00:01,  4.50trial/s, best loss: 165.6601756513094]2023-02-24 11:30:22,731 - build_posterior_wrapper took 0.002013 seconds\n",
      "2023-02-24 11:30:22,732 - TPE using 44/44 trials with best loss 165.660176\n",
      "2023-02-24 11:30:22,815 - build_posterior_wrapper took 0.001129 seconds\n",
      "2023-02-24 11:30:22,816 - TPE using 45/45 trials with best loss 165.214025\n",
      "2023-02-24 11:30:22,826 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 278 to 240.\n",
      " 92%|█████████████████████████████████████████████    | 46/50 [00:09<00:00,  4.33trial/s, best loss: 165.2140246915824]2023-02-24 11:30:23,214 - build_posterior_wrapper took 0.001547 seconds\n",
      "2023-02-24 11:30:23,215 - TPE using 46/46 trials with best loss 165.214025\n",
      " 94%|██████████████████████████████████████████████   | 47/50 [00:09<00:00,  4.83trial/s, best loss: 165.2140246915824]2023-02-24 11:30:23,346 - build_posterior_wrapper took 0.001152 seconds\n",
      "2023-02-24 11:30:23,347 - TPE using 47/47 trials with best loss 165.214025\n",
      " 96%|███████████████████████████████████████████████  | 48/50 [00:09<00:00,  4.55trial/s, best loss: 165.2140246915824]2023-02-24 11:30:23,602 - build_posterior_wrapper took 0.000998 seconds\n",
      "2023-02-24 11:30:23,603 - TPE using 48/48 trials with best loss 165.214025\n",
      "2023-02-24 11:30:23,614 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 460 to 240.\n",
      " 98%|████████████████████████████████████████████████ | 49/50 [00:10<00:00,  4.01trial/s, best loss: 165.2140246915824]2023-02-24 11:30:23,931 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:23,932 - TPE using 49/49 trials with best loss 165.214025\n",
      "100%|█████████████████████████████████████████████████| 50/50 [00:10<00:00,  4.28trial/s, best loss: 165.2140246915824]\n",
      "2023-02-24 11:30:24,305 - PipelineTuner - Hyperparameters optimization finished\n",
      "2023-02-24 11:30:24,306 - PipelineTuner - Return tuned pipeline due to the fact that obtained metric 165.214 equal or better than initial (+ 0.05% deviation) 241.395\n",
      "2023-02-24 11:30:24,307 - PipelineTuner - Final pipeline: {'depth': 3, 'length': 3, 'nodes': [lasso, custom, lagged]}\n",
      "lasso - {'alpha': 5.43409465776688}\n",
      "custom - {'alpha': 6.362843506702346, 'model_fit': <function custom_ml_model_imitation_fit at 0x0000020A83C7C1F0>, 'model_predict': <function custom_ml_model_imitation_predict at 0x0000020A83C7C3A0>}\n",
      "lagged - {'window_size': 31}\n",
      "2023-02-24 11:30:24,307 - PipelineTuner - Final metric: 165.214\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline structure:\n",
      "{'depth': 3, 'length': 3, 'nodes': [lasso, custom, lagged]}\n",
      "lasso - {'alpha': 5.43409465776688}\n",
      "custom - {'alpha': 6.362843506702346, 'model_fit': <function custom_ml_model_imitation_fit at 0x0000020A83C7C1F0>, 'model_predict': <function custom_ml_model_imitation_predict at 0x0000020A83C7C3A0>}\n",
      "lagged - {'window_size': 31}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_pipeline_tuning(pipeline_type='with_fit')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline structure:\n",
      "{'depth': 3, 'length': 3, 'nodes': [ridge, custom, lagged]}\n",
      "ridge - {}\n",
      "custom - {'a': -50, 'b': 500, 'model_predict': <function domain_model_imitation_predict at 0x0000020A48A709D0>}\n",
      "lagged - {'window_size': 10}\n",
      "2023-02-24 11:30:24,613 - DataSourceSplitter - Hold out validation is applied.\n",
      "2023-02-24 11:30:24,614 - PipelineTuner - Hyperparameters optimization start: estimation of metric for initial pipeline\n",
      "2023-02-24 11:30:24,663 - PipelineTuner - Initial pipeline: {'depth': 3, 'length': 3, 'nodes': [ridge, custom, lagged]}\n",
      "ridge - {}\n",
      "custom - {'a': -50, 'b': 500, 'model_predict': <function domain_model_imitation_predict at 0x0000020A48A709D0>}\n",
      "lagged - {'window_size': 10} \n",
      "Initial metric: 38850.116\n",
      "  0%|                                                                            | 0/5 [00:00<?, ?trial/s, best loss=?]2023-02-24 11:30:24,669 - build_posterior_wrapper took 0.001999 seconds\n",
      "2023-02-24 11:30:24,669 - TPE using 0 trials\n",
      "2023-02-24 11:30:24,719 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:24,720 - TPE using 1/1 trials with best loss 46360.100629\n",
      " 40%|████████████████████▍                              | 2/5 [00:00<00:00, 19.92trial/s, best loss: 46360.10062907752]2023-02-24 11:30:24,770 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:24,771 - TPE using 2/2 trials with best loss 46360.100629\n",
      "2023-02-24 11:30:24,820 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:24,821 - TPE using 3/3 trials with best loss 32910.286786\n",
      " 80%|████████████████████████████████████████          | 4/5 [00:00<00:00, 19.51trial/s, best loss: 32910.286786416844]2023-02-24 11:30:24,874 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:24,875 - TPE using 4/4 trials with best loss 32910.286786\n",
      "100%|██████████████████████████████████████████████████| 5/5 [00:00<00:00, 19.65trial/s, best loss: 32910.286786416844]\n",
      " 10%|███████▌                                                                   | 5/50 [00:00<?, ?trial/s, best loss=?]2023-02-24 11:30:24,928 - build_posterior_wrapper took 0.000988 seconds\n",
      "2023-02-24 11:30:24,930 - TPE using 5/5 trials with best loss 32910.286786\n",
      "2023-02-24 11:30:25,003 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:25,004 - TPE using 6/6 trials with best loss 30726.606227\n",
      "2023-02-24 11:30:25,008 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 428 to 240.\n",
      " 14%|███████                                           | 7/50 [00:00<00:08,  5.37trial/s, best loss: 9983.237307291918]2023-02-24 11:30:25,301 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:25,302 - TPE using 7/7 trials with best loss 9983.237307\n",
      " 16%|████████▏                                          | 8/50 [00:00<00:07,  5.30trial/s, best loss: 5941.93650741053]2023-02-24 11:30:25,493 - build_posterior_wrapper took 0.000808 seconds\n",
      "2023-02-24 11:30:25,494 - TPE using 8/8 trials with best loss 5941.936507\n",
      "2023-02-24 11:30:25,498 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 435 to 240.\n",
      " 18%|█████████▏                                         | 9/50 [00:00<00:10,  3.85trial/s, best loss: 5941.93650741053]2023-02-24 11:30:25,874 - build_posterior_wrapper took 0.001553 seconds\n",
      "2023-02-24 11:30:25,874 - TPE using 9/9 trials with best loss 5941.936507\n",
      "2023-02-24 11:30:25,877 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 292 to 240.\n",
      " 20%|██████████                                        | 10/50 [00:01<00:10,  3.71trial/s, best loss: 5941.93650741053]2023-02-24 11:30:26,162 - build_posterior_wrapper took 0.002006 seconds\n",
      "2023-02-24 11:30:26,162 - TPE using 10/10 trials with best loss 5941.936507\n",
      "2023-02-24 11:30:26,256 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:26,257 - TPE using 11/11 trials with best loss 5941.936507\n",
      "2023-02-24 11:30:26,261 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 473 to 240.\n",
      " 24%|████████████                                      | 12/50 [00:01<00:08,  4.30trial/s, best loss: 5941.93650741053]2023-02-24 11:30:26,551 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:26,551 - TPE using 12/12 trials with best loss 5941.936507\n",
      "2023-02-24 11:30:26,556 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 375 to 240.\n",
      " 26%|█████████████                                     | 13/50 [00:01<00:09,  4.02trial/s, best loss: 5036.90362247122]2023-02-24 11:30:26,847 - build_posterior_wrapper took 0.001002 seconds\n",
      "2023-02-24 11:30:26,849 - TPE using 13/13 trials with best loss 5036.903622\n",
      "2023-02-24 11:30:26,918 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:26,919 - TPE using 14/14 trials with best loss 5036.903622\n",
      " 30%|███████████████                                   | 15/50 [00:02<00:06,  5.16trial/s, best loss: 5036.90362247122]2023-02-24 11:30:27,089 - build_posterior_wrapper took 0.001995 seconds\n",
      "2023-02-24 11:30:27,090 - TPE using 15/15 trials with best loss 5036.903622\n",
      "2023-02-24 11:30:27,093 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 483 to 240.\n",
      " 32%|████████████████▎                                  | 16/50 [00:02<00:07,  4.53trial/s, best loss: 591.11704221822]2023-02-24 11:30:27,396 - build_posterior_wrapper took 0.002005 seconds\n",
      "2023-02-24 11:30:27,397 - TPE using 16/16 trials with best loss 591.117042\n",
      "2023-02-24 11:30:27,463 - build_posterior_wrapper took 0.000991 seconds\n",
      "2023-02-24 11:30:27,464 - TPE using 17/17 trials with best loss 591.117042\n",
      "2023-02-24 11:30:27,467 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 294 to 240.\n",
      " 36%|██████████████████▎                                | 18/50 [00:02<00:07,  4.47trial/s, best loss: 591.11704221822]2023-02-24 11:30:27,851 - build_posterior_wrapper took 0.001993 seconds\n",
      "2023-02-24 11:30:27,851 - TPE using 18/18 trials with best loss 591.117042\n",
      "2023-02-24 11:30:27,854 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 267 to 240.\n",
      " 38%|███████████████████▍                               | 19/50 [00:03<00:07,  4.01trial/s, best loss: 591.11704221822]2023-02-24 11:30:28,192 - build_posterior_wrapper took 0.002003 seconds\n",
      "2023-02-24 11:30:28,193 - TPE using 19/19 trials with best loss 591.117042\n",
      "2023-02-24 11:30:28,196 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 278 to 240.\n",
      " 40%|████████████████████▍                              | 20/50 [00:03<00:07,  3.78trial/s, best loss: 591.11704221822]2023-02-24 11:30:28,504 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:28,505 - TPE using 20/20 trials with best loss 591.117042\n",
      " 42%|█████████████████████▍                             | 21/50 [00:03<00:07,  3.89trial/s, best loss: 591.11704221822]2023-02-24 11:30:28,739 - build_posterior_wrapper took 0.002007 seconds\n",
      "2023-02-24 11:30:28,739 - TPE using 21/21 trials with best loss 591.117042\n",
      "2023-02-24 11:30:28,749 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 499 to 240.\n",
      " 44%|██████████████████████▍                            | 22/50 [00:04<00:07,  3.66trial/s, best loss: 591.11704221822]2023-02-24 11:30:29,058 - build_posterior_wrapper took 0.001004 seconds\n",
      "2023-02-24 11:30:29,058 - TPE using 22/22 trials with best loss 591.117042\n",
      "2023-02-24 11:30:29,069 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 330 to 240.\n",
      " 46%|███████████████████████▍                           | 23/50 [00:04<00:07,  3.52trial/s, best loss: 591.11704221822]2023-02-24 11:30:29,368 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:29,369 - TPE using 23/23 trials with best loss 591.117042\n",
      " 48%|███████████████████████▌                         | 24/50 [00:04<00:08,  3.16trial/s, best loss: 533.9222647608327]2023-02-24 11:30:29,765 - build_posterior_wrapper took 0.001000 seconds\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-02-24 11:30:29,766 - TPE using 24/24 trials with best loss 533.922265\n",
      " 50%|████████████████████████                        | 25/50 [00:05<00:07,  3.30trial/s, best loss: 496.36891911231294]2023-02-24 11:30:30,036 - build_posterior_wrapper took 0.000997 seconds\n",
      "2023-02-24 11:30:30,038 - TPE using 25/25 trials with best loss 496.368919\n",
      " 52%|████████████████████████▉                       | 26/50 [00:05<00:07,  3.39trial/s, best loss: 496.36891911231294]2023-02-24 11:30:30,311 - build_posterior_wrapper took 0.001008 seconds\n",
      "2023-02-24 11:30:30,312 - TPE using 26/26 trials with best loss 496.368919\n",
      " 54%|█████████████████████████▉                      | 27/50 [00:05<00:05,  4.04trial/s, best loss: 496.36891911231294]2023-02-24 11:30:30,444 - build_posterior_wrapper took 0.000987 seconds\n",
      "2023-02-24 11:30:30,445 - TPE using 27/27 trials with best loss 496.368919\n",
      " 56%|██████████████████████████▉                     | 28/50 [00:05<00:05,  3.85trial/s, best loss: 496.36891911231294]2023-02-24 11:30:30,733 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:30,734 - TPE using 28/28 trials with best loss 496.368919\n",
      " 58%|███████████████████████████▊                    | 29/50 [00:06<00:05,  3.76trial/s, best loss: 496.36891911231294]2023-02-24 11:30:31,014 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:31,014 - TPE using 29/29 trials with best loss 496.368919\n",
      " 60%|████████████████████████████▊                   | 30/50 [00:06<00:04,  4.35trial/s, best loss: 496.36891911231294]2023-02-24 11:30:31,160 - build_posterior_wrapper took 0.001998 seconds\n",
      "2023-02-24 11:30:31,160 - TPE using 30/30 trials with best loss 496.368919\n",
      "2023-02-24 11:30:31,214 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:31,215 - TPE using 31/31 trials with best loss 496.368919\n",
      "2023-02-24 11:30:31,226 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 339 to 240.\n",
      " 64%|██████████████████████████████▋                 | 32/50 [00:06<00:03,  4.82trial/s, best loss: 496.36891911231294]2023-02-24 11:30:31,521 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:31,522 - TPE using 32/32 trials with best loss 496.368919\n",
      " 66%|███████████████████████████████▋                | 33/50 [00:06<00:03,  4.29trial/s, best loss: 496.36891911231294]2023-02-24 11:30:31,832 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:31,833 - TPE using 33/33 trials with best loss 496.368919\n",
      "2023-02-24 11:30:31,843 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 359 to 240.\n",
      " 68%|████████████████████████████████▋               | 34/50 [00:07<00:04,  3.94trial/s, best loss: 496.36891911231294]2023-02-24 11:30:32,144 - build_posterior_wrapper took 0.001005 seconds\n",
      "2023-02-24 11:30:32,146 - TPE using 34/34 trials with best loss 496.368919\n",
      " 70%|█████████████████████████████████▌              | 35/50 [00:07<00:03,  4.41trial/s, best loss: 496.36891911231294]2023-02-24 11:30:32,299 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:32,299 - TPE using 35/35 trials with best loss 496.368919\n",
      " 72%|██████████████████████████████████▌             | 36/50 [00:07<00:03,  3.98trial/s, best loss: 496.36891911231294]2023-02-24 11:30:32,614 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:32,615 - TPE using 36/36 trials with best loss 496.368919\n",
      "2023-02-24 11:30:32,625 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 306 to 240.\n",
      " 74%|███████████████████████████████████▌            | 37/50 [00:07<00:03,  3.73trial/s, best loss: 496.36891911231294]2023-02-24 11:30:32,924 - build_posterior_wrapper took 0.001008 seconds\n",
      "2023-02-24 11:30:32,925 - TPE using 37/37 trials with best loss 496.368919\n",
      " 76%|████████████████████████████████████▍           | 38/50 [00:08<00:02,  4.53trial/s, best loss: 496.36891911231294]2023-02-24 11:30:33,028 - build_posterior_wrapper took 0.001008 seconds\n",
      "2023-02-24 11:30:33,029 - TPE using 38/38 trials with best loss 496.368919\n",
      "2023-02-24 11:30:33,039 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 410 to 240.\n",
      " 78%|█████████████████████████████████████▍          | 39/50 [00:08<00:02,  4.03trial/s, best loss: 496.36891911231294]2023-02-24 11:30:33,343 - build_posterior_wrapper took 0.002003 seconds\n",
      "2023-02-24 11:30:33,344 - TPE using 39/39 trials with best loss 496.368919\n",
      " 80%|██████████████████████████████████████▍         | 40/50 [00:08<00:02,  3.93trial/s, best loss: 496.36891911231294]2023-02-24 11:30:33,611 - build_posterior_wrapper took 0.001010 seconds\n",
      "2023-02-24 11:30:33,612 - TPE using 40/40 trials with best loss 496.368919\n",
      " 82%|███████████████████████████████████████▎        | 41/50 [00:08<00:02,  4.24trial/s, best loss: 496.36891911231294]2023-02-24 11:30:33,805 - build_posterior_wrapper took 0.002002 seconds\n",
      "2023-02-24 11:30:33,808 - TPE using 41/41 trials with best loss 496.368919\n",
      " 84%|████████████████████████████████████████▎       | 42/50 [00:09<00:01,  4.91trial/s, best loss: 496.36891911231294]2023-02-24 11:30:33,932 - build_posterior_wrapper took 0.002000 seconds\n",
      "2023-02-24 11:30:33,932 - TPE using 42/42 trials with best loss 496.368919\n",
      "2023-02-24 11:30:33,943 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 259 to 240.\n",
      " 86%|█████████████████████████████████████████▎      | 43/50 [00:09<00:01,  3.70trial/s, best loss: 496.36891911231294]2023-02-24 11:30:34,357 - build_posterior_wrapper took 0.001001 seconds\n",
      "2023-02-24 11:30:34,359 - TPE using 43/43 trials with best loss 496.368919\n",
      "2023-02-24 11:30:34,371 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 313 to 240.\n",
      " 88%|██████████████████████████████████████████▏     | 44/50 [00:09<00:01,  3.30trial/s, best loss: 496.36891911231294]2023-02-24 11:30:34,739 - build_posterior_wrapper took 0.000999 seconds\n",
      "2023-02-24 11:30:34,740 - TPE using 44/44 trials with best loss 496.368919\n",
      " 90%|███████████████████████████████████████████▏    | 45/50 [00:10<00:01,  3.70trial/s, best loss: 496.36891911231294]2023-02-24 11:30:34,932 - build_posterior_wrapper took 0.001006 seconds\n",
      "2023-02-24 11:30:34,933 - TPE using 45/45 trials with best loss 496.368919\n",
      "2023-02-24 11:30:34,944 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 449 to 240.\n",
      " 92%|████████████████████████████████████████████▏   | 46/50 [00:10<00:01,  3.51trial/s, best loss: 496.36891911231294]2023-02-24 11:30:35,251 - build_posterior_wrapper took 0.001002 seconds\n",
      "2023-02-24 11:30:35,252 - TPE using 46/46 trials with best loss 496.368919\n",
      "2023-02-24 11:30:35,310 - build_posterior_wrapper took 0.000993 seconds\n",
      "2023-02-24 11:30:35,311 - TPE using 47/47 trials with best loss 496.368919\n",
      "2023-02-24 11:30:35,322 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 406 to 240.\n",
      " 96%|██████████████████████████████████████████████  | 48/50 [00:10<00:00,  3.99trial/s, best loss: 496.36891911231294]2023-02-24 11:30:35,672 - build_posterior_wrapper took 0.001000 seconds\n",
      "2023-02-24 11:30:35,673 - TPE using 48/48 trials with best loss 496.368919\n",
      " 98%|███████████████████████████████████████████████ | 49/50 [00:10<00:00,  4.65trial/s, best loss: 496.36891911231294]2023-02-24 11:30:35,778 - build_posterior_wrapper took 0.001006 seconds\n",
      "2023-02-24 11:30:35,779 - TPE using 49/49 trials with best loss 496.368919\n",
      "2023-02-24 11:30:35,790 - LaggedTransformationImplementation - Warning: window size of lagged transformation was changed from 354 to 240.\n",
      "100%|████████████████████████████████████████████████| 50/50 [00:11<00:00,  4.03trial/s, best loss: 496.36891911231294]\n",
      "2023-02-24 11:30:36,481 - PipelineTuner - Hyperparameters optimization finished\n",
      "2023-02-24 11:30:36,482 - PipelineTuner - Return tuned pipeline due to the fact that obtained metric 495.893 equal or better than initial (+ 0.05% deviation) 38830.691\n",
      "2023-02-24 11:30:36,483 - PipelineTuner - Final pipeline: {'depth': 3, 'length': 3, 'nodes': [ridge, custom, lagged]}\n",
      "ridge - {'alpha': 6.590651023353968}\n",
      "custom - {'a': -8.776146179870658, 'b': 89.47931668156521, 'model_predict': <function domain_model_imitation_predict at 0x0000020A48A709D0>}\n",
      "lagged - {'window_size': 218}\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-02-24 11:30:36,484 - PipelineTuner - Final metric: 495.893\n",
      "Pipeline structure:\n",
      "{'depth': 3, 'length': 3, 'nodes': [ridge, custom, lagged]}\n",
      "ridge - {'alpha': 6.590651023353968}\n",
      "custom - {'a': -8.776146179870658, 'b': 89.47931668156521, 'model_predict': <function domain_model_imitation_predict at 0x0000020A48A709D0>}\n",
      "lagged - {'window_size': 218}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_pipeline_tuning(pipeline_type='without_fit')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thus, we demonstrated the use of imitation of custom model with FEDOT for providing the hybrid approach in composition with AutoML."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}