{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Meta-Model Structure Selection (MetaMSS) algorithm for building Polynomial NARX models\n",
    "\n",
    "Example created by Wilson Rocha Lacerda Junior"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sysidentpy.model_structure_selection import MetaMSS, FROLS\n",
    "from sysidentpy.metrics import root_relative_squared_error\n",
    "from sysidentpy.basis_function._basis_function import Polynomial\n",
    "from sysidentpy.utils.display_results import results\n",
    "from sysidentpy.utils.plotting import plot_residues_correlation, plot_results\n",
    "from sysidentpy.residues.residues_correlation import compute_residues_autocorrelation, compute_cross_correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = pd.read_csv('examples/datasets/x_cc.csv')\n",
    "df2 = pd.read_csv('examples/datasets/y_cc.csv')\n",
    "\n",
    "df2[5000:80000].plot(figsize=(10, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we will decimate the data using d=500 in this example\n",
    "x_train, x_test = np.split(df1.iloc[::500].values, 2)\n",
    "y_train, y_test = np.split(df2.iloc[::500].values, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\narmax_base.py:796: RuntimeWarning: overflow encountered in power\n",
      "  np.power(raw_regressor, model_exponents[j])\n",
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\core\\fromnumeric.py:87: RuntimeWarning: overflow encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\model_structure_selection\\meta_model_structure_selection.py:421: RuntimeWarning: overflow encountered in square\n",
      "  sum_of_squared_residues = np.sum(residues ** 2)\n",
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\core\\fromnumeric.py:87: RuntimeWarning: invalid value encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\metrics\\_regression.py:215: RuntimeWarning: overflow encountered in square\n",
      "  numerator = np.sum(np.square((y_predicted - y)))\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\metrics\\_regression.py:216: RuntimeWarning: overflow encountered in square\n",
      "  denominator = np.sum(np.square((y_predicted - np.mean(y, axis=0))))\n",
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\linalg\\linalg.py:2567: RuntimeWarning: divide by zero encountered in power\n",
      "  absx **= ord\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<sysidentpy.model_structure_selection.meta_model_structure_selection.MetaMSS at 0x284fd469a90>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basis_function = Polynomial(degree=2)\n",
    "\n",
    "model = MetaMSS(\n",
    "    norm=-2,\n",
    "    xlag=3,\n",
    "    ylag=3,\n",
    "    estimator=\"recursive_least_squares\",\n",
    "    k_agents_percent=10,\n",
    "    estimate_parameter=True,\n",
    "    maxiter=30,\n",
    "    n_agents=10,\n",
    "    loss_func='metamss_loss',\n",
    "    basis_function=basis_function\n",
    ")\n",
    "model.fit(X_train=x_train, y_train=y_train, X_test=x_test, y_test=y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.042484059098656546\n",
      "        Regressors   Parameters             ERR\n",
      "0           y(k-1)   1.1373E+00  0.00000000E+00\n",
      "1           y(k-3)  -3.5811E-01  0.00000000E+00\n",
      "2          x1(k-1)   5.8621E+02  0.00000000E+00\n",
      "3          x1(k-2)   7.3266E-02  0.00000000E+00\n",
      "4          x1(k-3)   1.1304E+01  0.00000000E+00\n",
      "5         y(k-1)^2  -4.9046E-05  0.00000000E+00\n",
      "6     y(k-3)y(k-1)   1.3034E-04  0.00000000E+00\n",
      "7    x1(k-1)y(k-1)  -1.6871E-01  0.00000000E+00\n",
      "8    x1(k-2)y(k-1)   1.0762E-01  0.00000000E+00\n",
      "9    x1(k-3)y(k-1)  -1.6445E-01  0.00000000E+00\n",
      "10        y(k-2)^2  -4.6619E-05  0.00000000E+00\n",
      "11   x1(k-1)y(k-2)   9.8404E-02  0.00000000E+00\n",
      "12   x1(k-2)y(k-2)  -9.8212E-02  0.00000000E+00\n",
      "13   x1(k-3)y(k-2)   1.5368E-01  0.00000000E+00\n",
      "14        y(k-3)^2  -1.3976E-05  0.00000000E+00\n",
      "15   x1(k-1)y(k-3)  -1.9331E-02  0.00000000E+00\n",
      "16   x1(k-3)y(k-3)  -5.1422E-02  0.00000000E+00\n",
      "17  x1(k-3)x1(k-1)   4.4025E+00  0.00000000E+00\n",
      "18       x1(k-2)^2   3.6633E-01  0.00000000E+00\n",
      "19  x1(k-3)x1(k-2)   8.7208E+00  0.00000000E+00\n",
      "20       x1(k-3)^2   5.6522E+01  0.00000000E+00\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yhat = model.predict(X_test=x_test, y_test=y_test)\n",
    "rrse = root_relative_squared_error(y_test, yhat)\n",
    "print(rrse)\n",
    "\n",
    "r = pd.DataFrame(\n",
    "    results(\n",
    "        model.final_model, model.theta, model.err,\n",
    "        model.n_terms, err_precision=8, dtype='sci'\n",
    "        ),\n",
    "    columns=['Regressors', 'Parameters', 'ERR'])\n",
    "print(r)\n",
    "\n",
    "plot_results(y=y_test, yhat = yhat, n=1000)\n",
    "ee = compute_residues_autocorrelation(y_test, yhat)\n",
    "plot_residues_correlation(data=ee, title=\"Residues\", ylabel=\"$e^2$\")\n",
    "x1e = compute_cross_correlation(y_test, yhat, x_test)\n",
    "plot_residues_correlation(data=x1e, title=\"Residues\", ylabel=\"$x_1e$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.005137296582679524"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ploting the evolution of the agents\n",
    "plt.plot(model.best_by_iter)\n",
    "model.best_by_iter[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# You have access to all tested models\n",
    "# model.tested_models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-14 20:43:29 - INFO - Training the model\n",
      "10-14 20:43:29 - INFO - Creating the regressor matrix\n",
      "10-14 20:43:29 - INFO - The regressor matrix have 21 features\n",
      "10-14 20:43:29 - INFO - Done! Model is built!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\utils\\deprecation.py:27: FutureWarning: Function __init__ has been deprecated since v0.1.7.\n",
      " Use NARXNN(ylag=2, xlag=2, basis_function='Some basis function') instead.This module was deprecated in favor of NARXNN(ylag=2, xlag=2, basis_function='Some basis function') module into which all the refactored classes and functions are moved.\n",
      " This feature will be removed in version v0.2.0.\n",
      "  warnings.warn(message, FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NARX_KNeighborsRegressor 1.833\n",
      "10-14 20:43:29 - INFO - Training the model\n",
      "10-14 20:43:29 - INFO - Creating the regressor matrix\n",
      "10-14 20:43:29 - INFO - The regressor matrix have 21 features\n",
      "10-14 20:43:29 - INFO - Done! Model is built!\n",
      "NARX_DecisionTreeRegressor 0.277\n",
      "10-14 20:43:29 - INFO - Training the model\n",
      "10-14 20:43:29 - INFO - Creating the regressor matrix\n",
      "10-14 20:43:29 - INFO - The regressor matrix have 21 features\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\general_estimators\\narx.py:161: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  self.base_estimator.fit(X, y, **self.fit_params)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-14 20:43:30 - INFO - Done! Model is built!\n",
      "NARX_RandomForestRegressor 0.194\n",
      "10-14 20:43:34 - INFO - Training the model\n",
      "10-14 20:43:34 - INFO - Creating the regressor matrix\n",
      "10-14 20:43:34 - INFO - The regressor matrix have 21 features\n",
      "10-14 20:43:36 - INFO - Done! Model is built!\n",
      "NARX_Catboost 0.179\n",
      "10-14 20:43:37 - INFO - Training the model\n",
      "10-14 20:43:37 - INFO - Creating the regressor matrix\n",
      "10-14 20:43:37 - INFO - The regressor matrix have 231 features\n",
      "10-14 20:43:37 - INFO - Done! Model is built!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\sklearn\\utils\\validation.py:63: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  return f(*args, **kwargs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NARX_ARD 0.074\n",
      "FROLS-Polynomial_NARX 0.047\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\core\\fromnumeric.py:87: RuntimeWarning: overflow encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\narmax_base.py:796: RuntimeWarning: overflow encountered in power\n",
      "  np.power(raw_regressor, model_exponents[j])\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\model_structure_selection\\meta_model_structure_selection.py:421: RuntimeWarning: overflow encountered in square\n",
      "  sum_of_squared_residues = np.sum(residues ** 2)\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\model_structure_selection\\meta_model_structure_selection.py:431: RuntimeWarning: invalid value encountered in sqrt\n",
      "  se_theta = np.sqrt(var_e)\n",
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\core\\fromnumeric.py:87: RuntimeWarning: invalid value encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\metrics\\_regression.py:215: RuntimeWarning: overflow encountered in square\n",
      "  numerator = np.sum(np.square((y_predicted - y)))\n",
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\metrics\\_regression.py:216: RuntimeWarning: overflow encountered in square\n",
      "  denominator = np.sum(np.square((y_predicted - np.mean(y, axis=0))))\n",
      "C:\\Users\\wilso\\miniconda3\\envs\\sysidentpy\\lib\\site-packages\\numpy\\linalg\\linalg.py:2567: RuntimeWarning: divide by zero encountered in power\n",
      "  absx **= ord\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MetaMSS 0.030\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.svm import SVC, LinearSVC, NuSVC\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor, AdaBoostRegressor, GradientBoostingRegressor\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from catboost import CatBoostRegressor\n",
    "from sklearn.linear_model import BayesianRidge, ARDRegression\n",
    "from sysidentpy.general_estimators import NARX\n",
    "\n",
    "xlag = ylag = 10\n",
    "\n",
    "estimators = [\n",
    "    ('NARX_KNeighborsRegressor', NARX(\n",
    "        base_estimator=KNeighborsRegressor(),\n",
    "        xlag=xlag,\n",
    "        ylag=ylag)),\n",
    "    ('NARX_DecisionTreeRegressor', NARX(\n",
    "        base_estimator=DecisionTreeRegressor(),\n",
    "        xlag=xlag,\n",
    "        ylag=ylag)),\n",
    "    ('NARX_RandomForestRegressor', NARX(\n",
    "        base_estimator=RandomForestRegressor(\n",
    "            n_estimators=200),\n",
    "        xlag=xlag,\n",
    "        ylag=ylag,\n",
    "    )),\n",
    "    ('NARX_Catboost', NARX(\n",
    "        base_estimator=CatBoostRegressor(\n",
    "        iterations=800,\n",
    "        learning_rate=0.1,\n",
    "        depth=8),\n",
    "        xlag=xlag,\n",
    "        ylag=ylag,\n",
    "        non_degree=1,\n",
    "        fit_params={'verbose': False}\n",
    "    )),\n",
    "    ('NARX_ARD', NARX(\n",
    "        base_estimator=ARDRegression(),\n",
    "        xlag=xlag,\n",
    "        ylag=ylag,\n",
    "        non_degree=2\n",
    "    )),\n",
    "    ('FROLS-Polynomial_NARX', FROLS(\n",
    "        order_selection=True,\n",
    "        n_info_values=50,\n",
    "        extended_least_squares=False,\n",
    "        ylag=ylag, xlag=xlag,\n",
    "        info_criteria='bic',\n",
    "        estimator='recursive_least_squares',\n",
    "        basis_function=basis_function\n",
    "        )\n",
    "    ),\n",
    "    ('MetaMSS', MetaMSS(norm=-2,\n",
    "                xlag=xlag,\n",
    "                ylag=ylag,\n",
    "                estimator=\"recursive_least_squares\",\n",
    "                k_agents_percent=10,\n",
    "                estimate_parameter=True,\n",
    "                maxiter=20,\n",
    "                n_agents=15,\n",
    "                loss_func='metamss_loss',\n",
    "                basis_function=basis_function)\n",
    "    )\n",
    "    \n",
    "    ]\n",
    "\n",
    "\n",
    "resultados = {}\n",
    "for nome_do_modelo, modelo in estimators:\n",
    "    resultados['%s' % (nome_do_modelo)] = []\n",
    "    if nome_do_modelo == 'MetaMSS':\n",
    "        modelo.fit(X_train=x_train, y_train=y_train, X_test=x_test, y_test=y_test)\n",
    "        yhat = modelo.predict(X_test=x_test,  y_test=y_test)\n",
    "    else:\n",
    "        modelo.fit(X=x_train, y=y_train)\n",
    "        yhat = modelo.predict(X=x_test,  y=y_test)\n",
    "    if nome_do_modelo in ['MetaMSS', 'FROLS-Polynomial_NARX']:\n",
    "        result = root_relative_squared_error(y_test[modelo.max_lag:], yhat[modelo.max_lag:])\n",
    "    else:\n",
    "        result = root_relative_squared_error(y_test, yhat)\n",
    "    resultados['%s' % (nome_do_modelo)].append(result)\n",
    "    print(nome_do_modelo, '%.3f' % np.mean(result))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MetaMSS 0.03020874227035109\n",
      "FROLS-Polynomial_NARX 0.04663897799085836\n",
      "NARX_ARD 0.07413356855178779\n",
      "NARX_Catboost 0.17923040407121107\n",
      "NARX_RandomForestRegressor 0.19361475059211708\n",
      "NARX_DecisionTreeRegressor 0.2765294836744295\n",
      "NARX_KNeighborsRegressor 1.833370478725381\n"
     ]
    }
   ],
   "source": [
    "for aux_results, results in sorted(resultados.items(), key=lambda x: np.mean(x[1]), reverse=False):\n",
    "    print(aux_results, np.mean(results))"
   ]
  }
 ],
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