examples/FuzzyGMDH.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from copy import deepcopy\n",
    "from itertools import combinations\n",
    "import typing as tp\n",
    "\n",
    "# For soliving lin prog task interior-point algorithm\n",
    "# is used, it will raise lots of warnings for `bad` matrices\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from numpy.linalg import lstsq\n",
    "from scipy.optimize import linprog\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "from citk.layer import Dense, FuzzyGMDHLayer\n",
    "from citk.model import FFN, GMDH\n",
    "from citk.functions import ReLU, Linear, BellMembership, GaussianMembership, Poly\n",
    "from citk.losses import MSE, FMSE\n",
    "from citk.optimisers import SGDOptimizer\n",
    "\n",
    "from utils import get_and_process_boston_dataset, visualise_boston, seed_everything\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAEICAYAAABGaK+TAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAQGklEQVR4nO3df4zkdX3H8edLDoMV7EHZnCegZ5XWEq2H2Z4orT9ADQoWTEgj9QdNNaeNNJBQ6ymplaS0mCpWo9WchXqpVEoUAhVtRaS1NIru4YHAaUU9C/TkFgWBatCDd/+Y79nNuXsztzOzc5/b5yOZ7Pf7+X5nvq/v3eaV737n+51JVSFJas9jJh1AkrQ4FrgkNcoCl6RGWeCS1CgLXJIaZYFLUqMscElqlAWufUKSh+Y8Hk3ykznzr1nE6/1bkjfuYfmaJJVkxXDJF2fS29f+wV8e7ROq6uBd00m2AW+sqs9PLtGeJVlRVTsnnUPLm0fg2qcleUySDUm+neQHSS5Pcli37KAkH+/G70/y1SSrklwA/A7wwe4I/oPzvPQXu5/3d+s8L8nTknyhe717k1yaZOWcLNuSvC3JLcD/JlmR5PVJvtc958+6dV7SL/t82x/Hv5/2bxa49nV/DJwGvBB4EnAf8KFu2ZnALwNHAb8CvBn4SVWdB/wHcFZVHVxVZ83zui/ofq7s1vkSEOCvuu38Rve679rteWcAJwMrgV8D/hZ4DbC6y3LEgNnn2760Vyxw7eveDJxXVXdV1cP0CvX07tzxz+gV99Or6pGq2lxVDyx2Q1V1R1VdW1UPV9UscBG98p3rA1V1Z1X9BDgd+OequqGqfgq8E5j74UJ7yi4NzV8k7eueAlyZ5NE5Y48Aq4B/oHeUfFl3quPj9ArzZ4vZUJJVwPvpnX45hN4Bzn27rXbnnOknzZ2vqh8n+cGA2aWheQSufd2dwMurauWcx0FVdXdV/ayqzq+qY4DnA6cAr++e1+9jNudb/pfd+LOq6gnAa+mdVlnoeduBI3fNJHkcvb8I+mYfIJ/UlwWufd1HgAuSPAUgyVSSU7vpFyd5VpIDgAfonVLZdbR7D/Cre3jd2W7duescAjwE/CjJEcBb+2T7JPDKJM9P8lh6p0jmFv6C2RfYvrRXLHDt694PXA18LsmDwJeB53bLnkivRB8AtgL/Tu+0yq7nnZ7kviQf2P1Fq+rHwAXAf3ZXsBwHnA88B/gRcA1wxZ6CVdVt9N6ovIze0fhDwA7g4X7ZF9i+tFfiFzpIo5HkYOB+4Oiq+u6E42gZ8AhcGkKSVyb5pSSPB94DfB3YNtlUWi4scGk4pwL/0z2OBl5d/lmrJeIpFElqlEfgktSoJb2R5/DDD681a9Ys5SYlqXmbN2++t6qmdh9f0gJfs2YNMzMzS7lJSWpeku/NN+4pFElqlAUuSY2ywCWpURa4JDXKApekRlngktQoC1ySGmWBS1KjLHBJapTfial9ypoN10xku9suPHki25WG4RG4JDXKApekRlngktQoC1ySGmWBS1KjLHBJapQFLkmN6lvgSQ5K8pUkNye5Lcn53fjHknw3yZbusXbsaSVJPzfIjTwPAydU1UNJDgRuSPLZbtlbq+qT44snSVpI3wKvqgIe6mYP7B41zlCSpP4GupU+yQHAZuDpwIeq6sYkfwRckOSdwHXAhqp6eJ7nrgfWAzz5yU8eWXBplCZ1Cz94G78Wb6A3MavqkapaCxwJrEvyTODtwDOA3wIOA962wHM3VtV0VU1PTU2NJrUkae+uQqmq+4HrgZOqanv1PAz8PbBuDPkkSQsY5CqUqSQru+nHAS8FvpFkdTcW4DTg1vHFlCTtbpBz4KuBTd158McAl1fVp5N8IckUEGAL8ObxxZQk7W6Qq1BuAY6dZ/yEsSSSJA3EOzElqVEWuCQ1ygKXpEZZ4JLUKAtckhplgUtSoyxwSWqUBS5JjbLAJalRFrgkNcoCl6RGWeCS1CgLXJIaZYFLUqMscElqlAUuSY2ywCWpURa4JDXKApekRg3yrfQHJflKkpuT3Jbk/G78qUluTHJHkn9K8tjxx5Uk7TLIEfjDwAlV9WxgLXBSkuOAdwPvq6qnA/cBbxhbSknSL+hb4NXzUDd7YPco4ATgk934JuC0cQSUJM1voHPgSQ5IsgXYAVwLfBu4v6p2dqvcBRyxwHPXJ5lJMjM7OzuCyJIkGLDAq+qRqloLHAmsA54x6AaqamNVTVfV9NTU1OJSSpJ+wV5dhVJV9wPXA88DViZZ0S06Erh7tNEkSXsyyFUoU0lWdtOPA14KbKVX5Kd3q50JXDWmjJKkeazovwqrgU1JDqBX+JdX1aeT3A5cluQvgK8BF48xpyRpN30LvKpuAY6dZ/w79M6HS5ImwDsxJalRFrgkNcoCl6RGWeCS1CgLXJIaZYFLUqMscElqlAUuSY2ywCWpURa4JDXKApekRlngktQoC1ySGmWBS1KjLHBJapQFLkmNssAlqVEWuCQ1ygKXpEYN8q30RyW5PsntSW5LcnY3/q4kdyfZ0j1eMf64kqRdBvlW+p3AuVV1U5JDgM1Jru2Wva+q3jO+eJKkhQzyrfTbge3d9INJtgJHjDuYJGnP9uoceJI1wLHAjd3QWUluSXJJkkMXeM76JDNJZmZnZ4dLK0n6uYELPMnBwKeAc6rqAeDDwNOAtfSO0N873/OqamNVTVfV9NTU1PCJJUnAgAWe5EB65X1pVV0BUFX3VNUjVfUo8FFg3fhiSpJ2N8hVKAEuBrZW1UVzxlfPWe1VwK2jjydJWsggV6EcD7wO+HqSLd3YO4AzkqwFCtgGvGkM+SRJCxjkKpQbgMyz6DOjjyNJGpR3YkpSoyxwSWqUBS5JjbLAJalRFrgkNcoCl6RGWeCS1CgLXJIaZYFLUqMscElqlAUuSY2ywCWpURa4JDXKApekRlngktQoC1ySGmWBS1KjLHBJapQFLkmNGuRb6Y9Kcn2S25PcluTsbvywJNcm+Vb389Dxx5Uk7TLIEfhO4NyqOgY4DnhLkmOADcB1VXU0cF03L0laIn0LvKq2V9VN3fSDwFbgCOBUYFO32ibgtDFllCTNY6/OgSdZAxwL3Aisqqrt3aLvA6sWeM76JDNJZmZnZ4fJKkmaY+ACT3Iw8CngnKp6YO6yqiqg5nteVW2squmqmp6amhoqrCTp/w1U4EkOpFfel1bVFd3wPUlWd8tXAzvGE1GSNJ9BrkIJcDGwtaoumrPoauDMbvpM4KrRx5MkLWTFAOscD7wO+HqSLd3YO4ALgcuTvAH4HvB7Y0koSZpX3wKvqhuALLD4xNHGkSQNyjsxJalRFrgkNcoCl6RGWeCS1CgLXJIaZYFLUqMscElqlAUuSY2ywCWpURa4JDXKApekRlngktQoC1ySGmWBS1KjLHBJapQFLkmNssAlqVEWuCQ1ygKXpEYN8q30lyTZkeTWOWPvSnJ3ki3d4xXjjSlJ2t0gR+AfA06aZ/x9VbW2e3xmtLEkSf30LfCq+iLwwyXIIknaC8OcAz8ryS3dKZZDF1opyfokM0lmZmdnh9icJGmuxRb4h4GnAWuB7cB7F1qxqjZW1XRVTU9NTS1yc5Kk3S2qwKvqnqp6pKoeBT4KrBttLElSP4sq8CSr58y+Crh1oXUlSeOxot8KST4BvAg4PMldwJ8DL0qyFihgG/Cm8UWUJM2nb4FX1RnzDF88hiySpL3gnZiS1CgLXJIaZYFLUqMscElqlAUuSY2ywCWpURa4JDXKApekRlngktQoC1ySGmWBS1Kj+n4WipafNRuumXSEZWVS/97bLjx5ItvV6HgELkmNssAlqVEWuCQ1ygKXpEZZ4JLUKAtckhplgUtSo/oWeJJLkuxIcuucscOSXJvkW93PQ8cbU5K0u0GOwD8GnLTb2Abguqo6Grium5ckLaG+BV5VXwR+uNvwqcCmbnoTcNpoY0mS+lnsOfBVVbW9m/4+sGqhFZOsTzKTZGZ2dnaRm5Mk7W7oNzGrqoDaw/KNVTVdVdNTU1PDbk6S1Flsgd+TZDVA93PH6CJJkgax2AK/Gjizmz4TuGo0cSRJgxrkMsJPAF8Cfj3JXUneAFwIvDTJt4CXdPOSpCXU9/PAq+qMBRadOOIskqS94J2YktQoC1ySGmWBS1KjLHBJapQFLkmNssAlqVEWuCQ1ygKXpEZZ4JLUKAtckhplgUtSoyxwSWqUBS5JjbLAJalRFrgkNcoCl6RGWeCS1CgLXJIaZYFLUqP6fifmniTZBjwIPALsrKrpUYSSJPU3VIF3XlxV947gdSRJe8FTKJLUqGELvIDPJdmcZP18KyRZn2Qmyczs7OyQm5Mk7TJsgf92VT0HeDnwliQv2H2FqtpYVdNVNT01NTXk5iRJuwxV4FV1d/dzB3AlsG4UoSRJ/S26wJM8Pskhu6aBlwG3jiqYJGnPhrkKZRVwZZJdr/OPVfUvI0klSepr0QVeVd8Bnj3CLJKkveBlhJLUKAtckhplgUtSoyxwSWqUBS5JjRrFh1lJUhPWbLhmYtveduHJI39Nj8AlqVEWuCQ1ygKXpEZZ4JLUKAtckhrlVSj7sEm+Yy5p3+cRuCQ1ygKXpEZZ4JLUKAtckhrVzJuY+9stsJI0LI/AJalRFrgkNWqoAk9yUpJvJrkjyYZRhZIk9bfoAk9yAPAh4OXAMcAZSY4ZVTBJ0p4NcwS+Drijqr5TVT8FLgNOHU0sSVI/w1yFcgRw55z5u4Dn7r5SkvXA+m72oSTfHGKbE5F3/8LQ4cC9S59kIpbLvi6X/YRuX+f5vd7f7FP/p0P+ez9lvsGxX0ZYVRuBjePezlJKMlNV05POsRSWy74ul/2E5bOvy2E/hzmFcjdw1Jz5I7sxSdISGKbAvwocneSpSR4LvBq4ejSxJEn9LPoUSlXtTHIW8K/AAcAlVXXbyJLt2/arU0J9LJd9XS77CctnX/f7/UxVTTqDJGkRvBNTkhplgUtSoyzwISU5N0klOXzSWcYlyV8n+UaSW5JcmWTlpDON0nL4SIgkRyW5PsntSW5LcvakM41bkgOSfC3JpyedZVws8CEkOQp4GfDfk84yZtcCz6yq3wT+C3j7hPOMzDL6SIidwLlVdQxwHPCW/XQ/5zob2DrpEONkgQ/nfcCfAvv1O8FV9bmq2tnNfpneNf/7i2XxkRBVtb2qbuqmH6RXbEdMNtX4JDkSOBn4u0lnGScLfJGSnArcXVU3TzrLEvtD4LOTDjFC830kxH5bbABJ1gDHAjdOOMo4/Q29g6tHJ5xjrJr5Rp5JSPJ54InzLDoPeAe90yf7hT3ta1Vd1a1zHr0/xS9dymwanSQHA58CzqmqByadZxySnALsqKrNSV404ThjZYHvQVW9ZL7xJM8CngrcnAR6pxRuSrKuqr6/hBFHZqF93SXJHwCnACfW/nXzwLL5SIgkB9Ir70ur6opJ5xmj44HfTfIK4CDgCUk+XlWvnXCukfNGnhFIsg2Yrqp95pPPRinJScBFwAuranbSeUYpyQp6b8yeSK+4vwr8/v52V3F6RxqbgB9W1TkTjrNkuiPwP6mqUyYcZSw8B65BfBA4BLg2yZYkH5l0oFHp3pzd9ZEQW4HL97fy7hwPvA44ofs/3NIdoaphHoFLUqM8ApekRlngktQoC1ySGmWBS1KjLHBJapQFLkmNssAlqVH/B/LtTElV44N+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "RANDOM_SEED = 42\n",
    "\n",
    "seed_everything(RANDOM_SEED)\n",
    "\n",
    "X_train, X_test, y_train, y_test = get_and_process_boston_dataset(random_state=RANDOM_SEED)\n",
    "\n",
    "visualise_boston(X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GMDH "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = GMDH(\n",
    "            method_type='fuzzy', \n",
    "            poli_type='quadratic',\n",
    "            loss=MSE, \n",
    "            confidence=0.9,\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "27e43499de994d8c8b8304566faf7fa5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Training :   0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "116a5a2365ce495c96c72e1080848745",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/78 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 0. Metric: 0.9608228957546737\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b0597da2acda4d2982f6d6ebfe11ee84",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/190 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 1. Metric: 0.7895005687370932\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "824d8457c6914ccca2c83fc620d2aaeb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/190 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 2. Metric: 0.6601221089461191\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5502c2f460704ca89b0b3f72dc1a0a04",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/190 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 3. Metric: 0.5485473540159781\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7cbe2772b0344a628150cc76c9261c01",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/190 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 4. Metric: 0.4981718167990625\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7055df8a9a27412aa8b9ef59769ed944",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "One fit:   0%|          | 0/190 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer: 5. Metric: 0.4326555373591404\n"
     ]
    }
   ],
   "source": [
    "model, history  = model.fit(\n",
    "    (X_train, y_train),\n",
    "    (X_test, y_test),\n",
    "    max_gmdh_layers=6,\n",
    "    n_best_to_take=20,\n",
    "    batch_size=64,\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'pairs': [[(4, 12),\n",
       "   (7, 12),\n",
       "   (8, 12),\n",
       "   (10, 12),\n",
       "   (2, 12),\n",
       "   (1, 12),\n",
       "   (5, 9),\n",
       "   (9, 12),\n",
       "   (5, 8),\n",
       "   (5, 10),\n",
       "   (1, 12),\n",
       "   (5, 12),\n",
       "   (10, 12),\n",
       "   (10, 12),\n",
       "   (3, 12),\n",
       "   (4, 5),\n",
       "   (5, 12),\n",
       "   (5, 10),\n",
       "   (1, 5),\n",
       "   (5, 7)],\n",
       "  [(0, 16),\n",
       "   (1, 9),\n",
       "   (1, 7),\n",
       "   (2, 9),\n",
       "   (2, 16),\n",
       "   (0, 12),\n",
       "   (4, 8),\n",
       "   (1, 2),\n",
       "   (1, 8),\n",
       "   (4, 12),\n",
       "   (0, 8),\n",
       "   (4, 16),\n",
       "   (3, 4),\n",
       "   (1, 12),\n",
       "   (0, 17),\n",
       "   (0, 2),\n",
       "   (0, 1),\n",
       "   (5, 16),\n",
       "   (1, 11),\n",
       "   (4, 7)],\n",
       "  [(1, 3),\n",
       "   (1, 4),\n",
       "   (0, 1),\n",
       "   (4, 10),\n",
       "   (1, 16),\n",
       "   (2, 4),\n",
       "   (1, 17),\n",
       "   (0, 4),\n",
       "   (4, 13),\n",
       "   (1, 5),\n",
       "   (1, 7),\n",
       "   (0, 8),\n",
       "   (1, 15),\n",
       "   (3, 13),\n",
       "   (2, 3),\n",
       "   (3, 8),\n",
       "   (1, 14),\n",
       "   (4, 8),\n",
       "   (5, 18),\n",
       "   (4, 18)],\n",
       "  [(6, 18),\n",
       "   (16, 18),\n",
       "   (0, 11),\n",
       "   (13, 15),\n",
       "   (3, 9),\n",
       "   (3, 6),\n",
       "   (6, 14),\n",
       "   (1, 7),\n",
       "   (5, 19),\n",
       "   (6, 17),\n",
       "   (8, 11),\n",
       "   (8, 16),\n",
       "   (0, 6),\n",
       "   (1, 18),\n",
       "   (1, 6),\n",
       "   (5, 18),\n",
       "   (13, 18),\n",
       "   (7, 18),\n",
       "   (6, 8),\n",
       "   (0, 5)],\n",
       "  [(0, 8),\n",
       "   (5, 15),\n",
       "   (9, 15),\n",
       "   (0, 11),\n",
       "   (0, 18),\n",
       "   (1, 5),\n",
       "   (0, 14),\n",
       "   (0, 19),\n",
       "   (15, 18),\n",
       "   (1, 6),\n",
       "   (6, 8),\n",
       "   (5, 10),\n",
       "   (14, 15),\n",
       "   (5, 16),\n",
       "   (8, 9),\n",
       "   (1, 11),\n",
       "   (1, 7),\n",
       "   (1, 14),\n",
       "   (5, 7),\n",
       "   (4, 13)],\n",
       "  [(3, 10),\n",
       "   (13, 14),\n",
       "   (10, 17),\n",
       "   (5, 14),\n",
       "   (3, 19),\n",
       "   (0, 6),\n",
       "   (0, 14),\n",
       "   (0, 3),\n",
       "   (5, 10),\n",
       "   (1, 9),\n",
       "   (6, 14),\n",
       "   (11, 19),\n",
       "   (1, 18),\n",
       "   (1, 16),\n",
       "   (4, 14),\n",
       "   (1, 13),\n",
       "   (0, 11),\n",
       "   (1, 15),\n",
       "   (3, 18),\n",
       "   (6, 16)]],\n",
       " 'weights': [[array([ 3.91221966e-01, -1.22918652e+00, -3.12715538e-01, -6.24873544e-02,\n",
       "           6.29155808e-03,  1.78000394e-01,  4.44644552e-12,  6.40679525e-12,\n",
       "           1.27423934e-11,  1.15913066e-11,  1.26541039e-01,  9.95344022e-01]),\n",
       "   array([-3.64033327e-01, -9.22653540e-01,  4.58044338e-01,  1.57072459e-01,\n",
       "          -4.57610162e-02,  2.19732398e-03,  2.82628001e-01,  1.67501363e-11,\n",
       "           3.97173200e-11,  1.73233917e-11,  1.30632101e-01,  7.70926084e-01]),\n",
       "   array([ 2.80867196e-01, -8.93250862e-01, -1.60850785e-01, -4.24682174e-01,\n",
       "          -2.95352404e-02,  4.65175481e-01,  7.12547052e-12,  3.37718865e-12,\n",
       "           5.91049747e-11,  4.66426121e-12,  1.18651786e-01,  1.02888927e+00]),\n",
       "   array([-2.12612391e-01, -8.86333099e-01,  8.40970172e-02, -1.06469544e-01,\n",
       "          -1.84530401e-01,  2.41482333e-01,  3.92477656e-13,  5.73103421e-13,\n",
       "           7.93123172e-13,  8.29836379e-02,  1.91068670e-01,  7.09162800e-01]),\n",
       "   array([-5.12719860e-02, -7.73137763e-01, -3.53114643e-01,  2.95443234e-01,\n",
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       "           1.53517724e-14,  3.16063842e-13,  1.44283605e-01,  8.67239988e-01]),\n",
       "   array([ 4.40559585e-01, -9.17665775e-01,  2.33456574e-01, -1.23227047e-01,\n",
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       "           7.57854246e-11,  3.67181315e-10,  1.77833144e-01,  9.14816275e-01]),\n",
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       "           1.26040005e-02,  1.09186183e-01,  1.41121089e-10,  6.06561430e-01]),\n",
       "   array([-1.34405782e-01, -7.30994575e-01, -5.71916993e-01,  4.67780174e-01,\n",
       "           6.60542404e-04, -2.68108620e-01,  3.01252917e-02,  3.36261574e-11,\n",
       "           1.29433022e-10,  3.63722666e-11,  1.35799745e-01,  8.73515496e-01]),\n",
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       "          -4.23422994e-01,  1.84535826e-01,  1.14905322e-11,  9.10633882e-02,\n",
       "           9.41329026e-03,  1.03222315e-01,  2.64674971e-11,  7.40847020e-01]),\n",
       "   array([ 4.91851835e-01, -8.32456765e-01, -2.96880075e-01,  1.62883398e-01,\n",
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       "           2.52721331e-14,  9.80842530e-15,  2.33473105e-14,  7.65820501e-01]),\n",
       "   array([-6.88626392e-01, -1.70779467e+00, -8.80993832e-01, -5.00753277e-02,\n",
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       "           1.62911879e-12,  4.42841581e-02,  1.24231310e-13,  8.76156961e-01]),\n",
       "   array([ 5.33413502e-01, -9.32260007e-01,  2.09758045e-01,  2.17029964e-01,\n",
       "          -1.78057049e-02,  1.50330789e-01,  3.10493058e-13,  2.64192154e-13,\n",
       "           2.74678734e-13,  1.36174476e-13,  1.62418165e-01,  9.00246879e-01]),\n",
       "   array([-3.83620772e-01, -6.69963818e-01,  3.66638303e-01,  1.84647881e-01,\n",
       "           1.95244799e-01, -2.28633774e-01,  5.10190733e-01,  7.07529699e-01,\n",
       "           6.45539569e-12,  3.50051679e-12,  1.04886976e-12,  2.74402202e-01]),\n",
       "   array([ 1.47936679e-01, -1.28242882e+00,  5.55196191e-01,  2.29227565e-01,\n",
       "           4.02976488e-01, -6.53604959e-01,  5.07331661e-13,  5.99723150e-02,\n",
       "           2.77256504e-01,  1.69458590e-14,  3.80641268e-13,  8.62488636e-01]),\n",
       "   array([-2.55387781e-02, -6.66013833e-01, -2.08753178e-01,  5.19915475e-02,\n",
       "          -3.22006986e-01,  1.37543163e-01,  1.32661567e-13,  1.23742976e-13,\n",
       "           3.64111253e-13,  3.73989986e-13,  1.14012721e-01,  1.06021237e+00]),\n",
       "   array([-7.81525662e-01,  6.03441461e-01, -1.97338578e-01,  2.47350534e-01,\n",
       "           2.17134331e-01, -4.06906223e-01,  5.05304136e-02,  4.60426001e-10,\n",
       "           4.25599057e-10,  2.80626112e-02,  1.08816406e-01,  7.46775458e-01]),\n",
       "   array([-1.41529195e-02, -1.76453707e+00, -1.85175553e-01,  1.08389714e-02,\n",
       "           4.99387312e-01, -1.79824770e-01,  4.75024378e-12,  1.53219239e+00,\n",
       "           4.33380002e-02,  3.80163833e-13,  1.05932221e-12,  2.69550677e-01]),\n",
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       "           1.91362271e-03,  5.31690759e-11,  4.65829887e-11,  6.07207665e-01]),\n",
       "   array([ 6.38347934e-01,  4.45152532e-01,  2.20141704e-01, -1.46667795e-01,\n",
       "           1.68745713e-01, -1.38636263e-01,  1.23275441e-10,  2.38547920e-11,\n",
       "           1.64011484e-10,  2.16178257e-11,  4.69782278e-10,  1.28221460e+00]),\n",
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       "          -2.02204109e-01, -6.15359850e-02,  6.50704434e-14,  3.61337059e-01,\n",
       "           6.57186222e-14,  4.14806875e-14,  9.48409200e-14,  7.10640720e-01])],\n",
       "  [array([ 9.22234866e-01, -1.05615103e-01,  1.22823155e-01,  3.86444279e-02,\n",
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       "           3.48102222e-12,  5.39956129e-02,  2.31696404e-11,  8.61994096e-01]),\n",
       "   array([ 1.00623511e+00,  1.62201666e-01,  4.62075113e-02, -2.52945377e-02,\n",
       "           4.46488126e-02,  1.52389669e-01,  9.69290775e-13,  4.24912743e-13,\n",
       "           3.74632258e-13,  5.48002579e-02,  9.71370592e-13,  1.17974851e+00]),\n",
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       "           9.52738716e-13,  5.90120426e-13,  7.37748620e-02,  9.53096428e-01]),\n",
       "   array([ 1.07144359e+00,  2.61108853e-03,  1.37086178e-01,  1.73282101e-02,\n",
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       "           1.45399930e-10,  5.11564253e-02,  1.03015819e-10,  1.04732663e+00]),\n",
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       "           3.37888120e-11,  3.26779358e-02,  2.52148916e-10,  1.05210884e+00]),\n",
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       "           6.68065445e-13,  3.66024828e-02,  3.96445330e-12,  1.04296242e+00]),\n",
       "   array([ 1.15247721e+00, -2.71915136e-02,  2.90171277e-02,  5.63808667e-02,\n",
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       "           1.67680396e-01,  8.18035671e-02,  1.76720414e-14,  8.50111326e-01]),\n",
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       "           5.46275563e-12,  7.13107063e-02,  2.28743739e-13,  1.01656040e+00]),\n",
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       "           5.34163369e-14,  5.46478367e-02,  1.96067004e-13,  1.19736902e+00]),\n",
       "   array([ 1.23723223e+00, -1.82127158e-01,  2.59695345e-01,  8.41365332e-02,\n",
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       "           6.25139035e-09,  9.10834288e-03,  7.71633018e-11,  9.20688480e-01]),\n",
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       "           3.61715574e-13,  7.85071134e-02,  2.27154844e-13,  1.00847457e+00]),\n",
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       "           2.70469511e-02,  1.89476725e-02,  2.70998782e-13,  7.51994250e-01]),\n",
       "   array([ 9.75059563e-02,  9.15775254e-01, -2.18889662e+00,  1.31721431e+00,\n",
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       "           1.38046143e-12,  3.08493022e-13,  1.03032166e-01,  8.29905503e-01]),\n",
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       "           1.91243427e-09,  2.96918447e-02,  4.93584880e-10,  1.17321630e+00]),\n",
       "   array([ 8.84556021e-01,  4.56280157e-02, -1.41935597e-01,  3.54390282e-02,\n",
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       "           2.12149762e-12,  7.83997794e-02,  1.41443691e-13,  1.00486483e+00]),\n",
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       "           4.48337903e-12,  6.62691081e-02,  1.40490086e-12,  1.01176081e+00]),\n",
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       "           4.57424441e-13,  1.29047351e-13,  7.69005188e-02,  1.00527446e+00]),\n",
       "   array([ 1.05193440e+00, -2.87941814e-02,  6.42377789e-02,  1.82545957e-02,\n",
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       "           2.18163179e-12,  7.90599645e-02,  1.21273331e-13,  8.96663944e-01]),\n",
       "   array([ 4.71920637e-01,  3.44426941e-01, -3.60541168e-01,  2.87244916e-01,\n",
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       "           4.48105373e-12,  1.07411656e-01,  8.03356431e-13,  8.26343529e-01]),\n",
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       "           3.71848011e-11,  1.61312561e-12,  2.91868264e-02,  8.41945290e-01])],\n",
       "  [array([ 4.41211814e-01,  5.72623438e-01, -3.14449341e-02,  1.65854611e-01,\n",
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       "           1.73509877e-09,  4.81822545e-02,  5.42061074e-11,  1.01988552e+00]),\n",
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       "           2.79202343e-02,  2.48784447e-11,  1.07600843e-12,  1.01728343e+00]),\n",
       "   array([ 9.04831141e-01,  7.58427494e-02, -1.18285686e+00,  4.76160600e-01,\n",
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       "           3.30088847e-02,  1.52293413e-12,  1.49154860e-12,  1.04386490e+00]),\n",
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       "           3.03605555e-02,  2.97912205e-11,  9.98088753e-12,  1.02332548e+00]),\n",
       "   array([-4.81182507e-02,  1.03492212e+00, -7.85067526e-01,  5.23306959e-01,\n",
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       "           7.64642182e-02,  2.09725329e-10,  1.85937120e-09,  1.00083923e+00]),\n",
       "   array([ 6.57365806e-01,  3.74426836e-01, -6.84560791e-01,  4.58638174e-01,\n",
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       "           4.01058908e-02,  5.22143650e-11,  2.45131526e-12,  9.35419553e-01]),\n",
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       "           4.00922777e-03,  1.23446461e-09,  1.60760203e-10,  8.10754006e-01]),\n",
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       "           4.27605988e-10,  3.31525009e-02,  2.18000003e-11,  1.02641958e+00]),\n",
       "   array([ 5.90516625e-01,  4.49694250e-01, -4.73596186e-01,  2.19306723e-01,\n",
       "           2.82095286e-01, -1.00384671e-01,  5.46989834e-12,  1.09923772e-12,\n",
       "           4.17328587e-02,  9.05610458e-13,  2.13696380e-11,  1.00204412e+00]),\n",
       "   array([-1.59324184e-01,  1.04325147e+00, -1.27789205e+00,  8.92577562e-01,\n",
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       "           1.10639131e-14,  2.17726097e-14,  5.33790227e-14,  1.04044756e+00]),\n",
       "   array([ 9.38821337e-03,  9.66652414e-01, -1.18854405e+00,  7.31919947e-01,\n",
       "           4.51707226e-01, -2.50425048e-02,  1.12415276e-11,  4.84079319e-12,\n",
       "           2.04864562e-11,  6.74917890e-02,  4.91499941e-12,  1.00913551e+00]),\n",
       "   array([ 9.28030114e-01,  5.27008153e-02, -1.18715961e+00,  4.85794860e-01,\n",
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       "           3.29027660e-02,  1.20301542e-09,  2.32809348e-08,  1.03970627e+00]),\n",
       "   array([-1.37672440e-01,  1.08908838e+00, -5.79079228e-01,  5.95500258e-01,\n",
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       "           7.02635168e-02,  2.73567228e-10,  1.27564933e-10,  1.00550655e+00]),\n",
       "   array([ 4.36843126e-01,  5.78662518e-01, -7.53447938e-01,  3.53409928e-01,\n",
       "           4.22835939e-01, -1.22588816e-01,  1.24514992e-13,  1.31959610e-14,\n",
       "           6.21515164e-14,  7.47022024e-15,  5.29455150e-02,  1.00075484e+00]),\n",
       "   array([ 7.00285598e-01,  3.26864467e-01, -5.42826130e-01,  4.55381556e-01,\n",
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       "           7.25392532e-12,  5.33865948e-02,  6.32044407e-13,  9.31609140e-01]),\n",
       "   array([ 5.69405545e-01,  4.00919073e-01, -3.09115762e-01,  9.70030340e-03,\n",
       "           2.99043755e-01, -9.70247399e-02,  5.29601500e-13,  1.16307745e-12,\n",
       "           2.94280063e-12,  6.54409624e-13,  4.72706705e-02,  1.01606085e+00]),\n",
       "   array([-2.33118324e-01,  1.09372759e+00, -3.91105892e-01,  5.46910234e-01,\n",
       "          -2.45039929e-01,  2.31401938e-02,  1.37374499e-13,  2.50906899e-13,\n",
       "           7.03696870e-02,  3.93962915e-13,  1.71920097e-12,  1.00610878e+00]),\n",
       "   array([ 6.22557906e-01,  3.41820524e-01, -5.78062670e-01,  1.99121829e-01,\n",
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       "           2.91068059e-02,  1.41822171e-14,  8.63324378e-14,  1.01148997e+00]),\n",
       "   array([-5.27459053e-01,  1.60810783e+00, -2.93181603e+00,  9.97087283e-01,\n",
       "           2.00564052e+00,  8.18595644e-03,  1.83102496e-11,  2.09643149e-09,\n",
       "           2.96738243e-10,  1.10468181e-11,  6.04206078e-02,  8.21975888e-01]),\n",
       "   array([ 5.45602056e-02,  1.02629421e+00, -9.62954153e-01,  2.81352724e-01,\n",
       "           6.96337635e-01, -4.69409676e-02,  4.61263741e-13,  1.19255438e-01,\n",
       "           4.61990827e-12,  2.31191892e-12,  3.82608775e-11,  7.94745306e-01])],\n",
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       "           1.79189235e-11,  1.00973491e-10,  6.12372758e-02,  7.86979472e-01]),\n",
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       "           2.70382195e-02,  4.78390924e-10,  9.65722960e-10,  8.18974594e-01]),\n",
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       "           2.23297319e-02,  3.28356064e-13,  4.19316899e-12,  1.02124545e+00]),\n",
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       "           3.97277704e-10,  2.50793408e-11,  4.25325861e-02,  1.00618613e+00]),\n",
       "   array([ 7.26335740e-01,  2.43636364e-01, -9.62247418e-01,  5.61173120e-01,\n",
       "           3.98131752e-01, -7.59287431e-03,  1.62235635e-10,  1.61958618e-10,\n",
       "           7.54379230e-12,  1.07914440e-10,  2.30231744e-10,  1.02641742e+00]),\n",
       "   array([ 3.99399492e-01,  6.00634425e-01,  1.24272060e+00, -8.05087112e-01,\n",
       "          -4.17384803e-01,  7.87258112e-04,  4.63145017e-13,  8.46220298e-14,\n",
       "           7.54696987e-11,  4.00254735e-02,  6.20826217e-13,  8.96632397e-01]),\n",
       "   array([ 7.28879987e-01,  2.58954473e-01, -3.53215291e-01,  9.41802514e-02,\n",
       "           2.65104136e-01, -2.34127384e-02,  1.12704462e-14,  1.38888462e-14,\n",
       "           1.78609601e-13,  6.41039942e-14,  6.63188135e-02,  8.44753030e-01]),\n",
       "   array([ 1.20420204e+00, -2.11826034e-01, -8.61802552e-01,  2.78582000e-01,\n",
       "           5.93504189e-01, -1.88461169e-04,  3.70593511e-12,  2.76903159e-12,\n",
       "           2.13582313e-11,  2.96374688e-02,  6.09298366e-12,  1.01545756e+00]),\n",
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       "           2.34996017e-13,  5.18285609e-14,  1.28318882e-16,  8.31530406e-01]),\n",
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       "           2.81138042e-13,  1.04167928e-13,  4.32608772e-02,  8.69300663e-01]),\n",
       "   array([ 8.93567197e-01,  9.46040602e-02,  2.46008786e+00, -1.12114742e+00,\n",
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       "           5.47917051e-11,  1.22786626e-11,  3.58292482e-02,  1.00763795e+00]),\n",
       "   array([ 3.06903377e-01,  7.48809051e-01, -4.17424620e-01,  2.63249277e-01,\n",
       "           1.43966207e-01,  7.48974553e-03,  1.54033033e-10,  2.22429335e-10,\n",
       "           2.46681803e-09,  2.38986528e-10,  4.55926795e-02,  9.97132160e-01]),\n",
       "   array([ 4.65948450e-01,  4.81287349e-01, -9.31144912e-01,  4.24996038e-01,\n",
       "           4.99422452e-01, -2.60210268e-02,  7.89220543e-13,  2.29534491e-13,\n",
       "           1.96414759e-12,  5.87028190e-02,  6.71325169e-13,  9.01351848e-01]),\n",
       "   array([ 3.01350062e-01,  7.98699842e-01, -8.67071670e-01,  4.13919304e-01,\n",
       "           3.21311170e-01, -1.24523521e-02,  7.78920770e-13,  1.07488285e-11,\n",
       "           1.11645801e-12,  2.01659977e-13,  3.16137939e-13,  8.29657726e-01]),\n",
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       "           2.77281262e-02,  5.18579501e-10,  1.09144418e-10,  9.09014284e-01]),\n",
       "   array([ 5.32286318e-01,  6.10265377e-01, -8.05692582e-01,  4.51010484e-01,\n",
       "           2.32344292e-01, -8.02792759e-02,  1.81307482e-14,  3.52875260e-02,\n",
       "           2.74080222e-14,  1.40285478e-14,  4.52894454e-13,  7.61987842e-01]),\n",
       "   array([-1.49512577e-02,  9.58168559e-01,  6.79259369e-01, -1.37751780e-01,\n",
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       "           2.33513262e-11,  1.39756738e-11,  4.35224124e-11,  7.85201416e-01]),\n",
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       "           3.33848721e-01, -8.73155156e-02,  2.27009963e-13,  6.38841668e-13,\n",
       "           1.69528211e-13,  7.77466352e-14,  7.38219022e-13,  8.06818609e-01]),\n",
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       "           2.44033167e-02,  3.81332813e-02,  6.48136226e-12,  8.39996019e-01]),\n",
       "   array([ 1.77170165e-02,  9.89991849e-01,  1.70264984e-02,  1.27076651e-02,\n",
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       "           4.55326819e-14,  3.57352771e-14,  3.99164601e-02,  9.36361965e-01])],\n",
       "  [array([ 7.61015570e-01,  2.53079727e-01, -4.56593507e-01,  2.13674016e-01,\n",
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       "           5.08944691e-12,  1.24466781e-11,  4.44037493e-12,  8.00009929e-01]),\n",
       "   array([ 1.95551886e-01,  7.62984948e-01, -1.52538336e-01,  1.09466309e-01,\n",
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       "           3.04790573e-09,  3.60546094e-10,  1.37650541e-11,  7.78868560e-01]),\n",
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       "           6.06925429e-11,  3.57331914e-11,  2.39016455e-11,  7.69089682e-01]),\n",
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       "           8.36111773e-12,  7.98764996e-03,  1.30516607e-12,  7.40284926e-01]),\n",
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       "           1.35942973e-10,  6.72382516e-02,  5.48084985e-12,  7.88656967e-01]),\n",
       "   array([ 7.39971132e-01,  2.34436930e-01,  1.76823387e-01, -2.00072775e-01,\n",
       "           1.77322201e-02, -8.94731566e-03,  7.30819359e-02,  7.43480060e-12,\n",
       "           4.08433806e-11,  5.13911347e-11,  3.38237365e-11,  7.94524181e-01]),\n",
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       "           1.33548207e-12,  3.63410765e-13,  6.55932685e-14,  7.75003650e-01]),\n",
       "   array([ 7.41268784e-01,  3.61667293e-01, -6.32374611e-01,  2.76354012e-01,\n",
       "           2.37953618e-01, -6.19484579e-02,  2.64415780e-11,  5.17759382e-12,\n",
       "           1.45176856e-10,  4.19466531e-11,  3.72863083e-12,  7.70180914e-01]),\n",
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       "           1.16040525e-01, -2.03837522e-02,  1.61391854e-02,  7.03599640e-14,\n",
       "           3.35550560e-13,  5.57839189e-15,  7.23730427e-14,  7.65264750e-01]),\n",
       "   array([ 6.99057391e-01,  3.33183177e-01, -1.68364147e-01,  6.99973763e-04,\n",
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       "           5.01066540e-11,  3.03864947e-12,  9.36184988e-13,  7.81398994e-01]),\n",
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       "           1.23700191e-13,  5.16815243e-15,  5.72874659e-15,  8.28963895e-01]),\n",
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       "           2.39056350e-02,  1.52062695e-10,  2.04125722e-09,  9.13078064e-01]),\n",
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       "           6.49399673e-02, -2.46073056e-02,  3.93323635e-10,  1.51077463e-02,\n",
       "           3.13170946e-09,  1.00979851e-10,  1.04204268e-10,  7.71389940e-01]),\n",
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       "           3.60791543e-10,  1.79348818e-11,  1.97931945e-11,  8.50823042e-01]),\n",
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       "           4.06063935e-11,  1.22102785e-10,  2.60710528e-10,  8.35938418e-01]),\n",
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       "           3.91803838e-12,  2.48726880e-11,  9.55072006e-12,  8.10443641e-01]),\n",
       "   array([ 1.00073339e+00,  4.67616696e-02, -1.83164832e-01,  9.32541098e-02,\n",
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       "           1.71282603e-13,  3.50627491e-15,  1.89936341e-14,  8.14040525e-01]),\n",
       "   array([ 6.90471365e-01,  3.33680675e-01, -4.02671304e-01,  2.15758664e-01,\n",
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       "           4.82365944e-12,  5.79940547e-12,  7.59587026e-13,  7.93536273e-01]),\n",
       "   array([ 1.06966654e+00, -5.95168872e-02, -6.96374439e-01,  4.21662122e-01,\n",
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       "           8.17756508e-10,  1.36979323e-10,  3.31454356e-02,  8.92693287e-01]),\n",
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       "           3.13347591e-13,  4.39404207e-12,  1.89432641e-12,  8.22460181e-01])],\n",
       "  [array([ 7.64067809e-01,  2.90562907e-01, -6.28673197e-01,  2.85557912e-01,\n",
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       "           1.60675570e-11,  1.98097886e-11,  2.18606802e-11,  7.74449681e-01]),\n",
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       "           5.04200612e-11,  3.27436481e-11,  3.03499841e-10,  8.15456203e-01]),\n",
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       "           2.88102158e-12,  1.23510455e-11,  5.92131792e-12,  8.10563955e-01]),\n",
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       "           4.82942778e-13,  1.64353400e-12,  7.20294214e-13,  8.17168685e-01]),\n",
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       "           1.30108712e-11,  1.04477317e-10,  7.55354638e-12,  7.81247840e-01]),\n",
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       "           1.03587953e-13,  1.50933942e-14,  1.95458146e-15,  8.00009929e-01]),\n",
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       "           1.21933058e-13,  3.01114505e-13,  1.56906963e-13,  8.00009929e-01]),\n",
       "   array([ 4.02463891e-01,  6.19670837e-01, -8.72973143e-01,  4.29591021e-01,\n",
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       "           1.14399406e-11,  1.54166957e-11,  9.86597188e-12,  8.10445864e-01]),\n",
       "   array([ 9.78881070e-01,  1.88629535e-02, -6.80061899e-02,  6.36062627e-02,\n",
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       "           1.23195031e-13,  1.40492018e-13,  2.47231934e-14,  7.79640550e-01]),\n",
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       "           7.14648502e-11,  9.71054296e-11,  1.50748815e-10,  8.00425621e-01]),\n",
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       "           3.84131220e-14,  3.61626101e-14,  3.48802065e-13,  8.17100132e-01]),\n",
       "   array([ 9.91714900e-01,  5.89606419e-03, -9.09209721e-03,  3.12625900e-03,\n",
       "           5.62458056e-03,  1.98169361e-04,  8.43370091e-13,  1.31779104e-12,\n",
       "           5.40844048e-14,  1.87063643e-14,  1.74400515e-13,  7.80574434e-01]),\n",
       "   array([ 9.89965270e-01,  8.31643748e-03, -3.78234453e-02,  3.71238325e-02,\n",
       "           2.44361913e-03, -1.52827439e-04,  1.65883251e-12,  7.82540343e-13,\n",
       "           8.24598713e-13,  1.34786904e-13,  5.21249285e-13,  7.79794149e-01]),\n",
       "   array([ 7.80541670e-01,  2.37567758e-01, -5.39774745e-01,  2.52622330e-01,\n",
       "           2.10892540e-01,  1.18535469e-02,  4.63348532e-12,  1.03499232e-11,\n",
       "           2.30773316e-12,  5.82043360e-12,  1.95389330e-12,  8.01136004e-01]),\n",
       "   array([ 1.00293772e+00, -2.69716670e-03, -8.49288286e-04,  1.74806768e-03,\n",
       "          -7.74799318e-04,  7.97320870e-05,  2.64675390e-13,  2.23053159e-03,\n",
       "           2.99156256e-14,  8.57285915e-15,  1.47944370e-14,  7.78965844e-01]),\n",
       "   array([ 1.25028813e+00, -2.41501504e-01,  4.42449970e-01, -2.69886214e-01,\n",
       "          -1.83272199e-01,  2.84647156e-02,  8.62015626e-13,  9.06857530e-13,\n",
       "           2.36357748e-12,  4.51424560e-13,  5.02923627e-13,  7.96130192e-01]),\n",
       "   array([ 9.88457816e-01,  9.54619468e-03, -3.54940659e-02,  3.40670508e-02,\n",
       "           3.51089867e-03, -1.62239794e-04,  1.54799607e-13,  2.05551582e-13,\n",
       "           3.19131294e-12,  1.18667014e-13,  3.09913808e-13,  7.79776858e-01]),\n",
       "   array([ 1.06626183e+00, -6.95379366e-02, -1.22172503e-01,  1.08659697e-01,\n",
       "           6.93648851e-03,  6.50510712e-03,  7.91566693e-02,  4.70329938e-11,\n",
       "           2.41962294e-10,  6.36767492e-03,  8.88226146e-11,  7.40512372e-01]),\n",
       "   array([ 1.12102967e+00, -1.24111767e-01, -2.18241726e+00,  1.04604385e+00,\n",
       "           1.13941653e+00, -4.63811117e-03,  1.75670400e-12,  7.04107508e-02,\n",
       "           1.38831409e-12,  6.02188214e-13,  1.14455434e-12,  7.69143029e-01])]]}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict_history"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predict and Visualise losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('GMDH history')\n",
    "plt.plot(history['validation_loss'], label='validation')\n",
    "plt.plot(history['train_loss'], label='train')\n",
    "plt.xlabel('layer')\n",
    "plt.ylabel('loss')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = model.predict(X_test)\n",
    "prediction_train = model.predict(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test MSE: 0.43265553736951806\n",
      "Train MSE: 94.08146264586175\n"
     ]
    }
   ],
   "source": [
    "print(f\"Test MSE: {MSE(y_test, prediction)[0]}\")\n",
    "print(f\"Train MSE: {MSE(y_train, prediction_train)[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Validation Target')\n",
    "plt.plot(prediction, label='prediction')\n",
    "plt.plot(y_test, label='ground truth')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Validation Prediction Distribution')\n",
    "plt.hist(prediction)\n",
    "plt.show()\n",
    "\n",
    "plt.title('Validation Target Distribution')\n",
    "plt.hist(y_test)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}