{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PV forecasting benchmark\n",
    "\n",
    "Example created by Wilson Rocha Lacerda Junior"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Note\n",
    "\n",
    "The following example is **not** intended to say that one library is better than another. The main focus of these examples is to show that SysIdentPy can be a good alternative for people looking to model time series.\n",
    "\n",
    "We will compare the results obtained against **neural prophet** library.\n",
    "\n",
    "For the sake of brevity, from **SysIdentPy** only the **MetaMSS**, **AOLS** and **FROLS** (with polynomial base function) methods will be used. See the SysIdentPy documentation to learn other ways of modeling with the library."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "We will compare a 1-step ahead forecaster on solar irradiance data (that can be a proxy for solar PV production). The config of the neuralprophet model was taken from the neuralprophet documentation (https://neuralprophet.com/html/example_links/energy_data_example.html)\n",
    "\n",
    "The training will occur on 80% of the data, reserving the last 20% for the validation.\n",
    "\n",
    "Note: the data used in this example can be found in neuralprophet github."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from warnings import simplefilter\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sysidentpy.model_structure_selection import FROLS\n",
    "from sysidentpy.model_structure_selection import AOLS\n",
    "from sysidentpy.model_structure_selection import MetaMSS\n",
    "from sysidentpy.basis_function import Polynomial\n",
    "from sysidentpy.utils.plotting import plot_results\n",
    "from sysidentpy.neural_network import NARXNN\n",
    "from sysidentpy.metrics import mean_squared_error\n",
    "\n",
    "from sktime.datasets import load_airline\n",
    "from neuralprophet import NeuralProphet\n",
    "from neuralprophet import set_random_seed \n",
    "\n",
    "\n",
    "simplefilter(\"ignore\", FutureWarning)\n",
    "np.seterr(all=\"ignore\")\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "loss = mean_squared_error\n",
    "\n",
    "data_location = r\"energy\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FROLS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\sysidentpy\\sysidentpy\\model_structure_selection\\forward_regression_orthogonal_least_squares.py:478: UserWarning: n_info_values is greater than the maximum number of all regressors space considering the chosen y_lag, u_lag, and non_degree. We set as 5 \n",
      "  self.info_values = self.information_criterion(reg_matrix, y)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "169.1363985943965\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "files = ['\\SanFrancisco_PV_GHI.csv', '\\SanFrancisco_Hospital.csv']\n",
    "raw = pd.read_csv(data_location + files[0])\n",
    "df=pd.DataFrame()\n",
    "df['ds'] = pd.date_range('1/1/2015 1:00:00', freq=str(60) + 'Min',\n",
    "                               periods=(8760)) \n",
    "df['y'] = raw.iloc[:,0].values\n",
    "\n",
    "df_train, df_val = df.iloc[:7008, :], df.iloc[7008:, :]\n",
    "\n",
    "y = df['y'].values.reshape(-1, 1)\n",
    "y_train = df_train['y'].values.reshape(-1, 1)\n",
    "y_test = df_val['y'].values.reshape(-1, 1)\n",
    "\n",
    "x_train = df_train['ds'].dt.hour.values.reshape(-1, 1)\n",
    "x_test = df_val['ds'].dt.hour.values.reshape(-1, 1)\n",
    "\n",
    "basis_function = Polynomial(degree=1)\n",
    "sysidentpy = FROLS(\n",
    "    order_selection=True,\n",
    "    ylag=2, xlag=2,\n",
    "    info_criteria='bic',\n",
    "    estimator='recursive_least_squares',\n",
    "    basis_function=basis_function,\n",
    "    model_type='NARMAX'\n",
    ")\n",
    "sysidentpy.fit(X=x_train, y=y_train)\n",
    "x_test = np.concatenate([x_train[-sysidentpy.max_lag:], x_test])\n",
    "y_test = np.concatenate([y_train[-sysidentpy.max_lag:], y_test])\n",
    "\n",
    "yhat = sysidentpy.predict(X=x_test, y=y_test, steps_ahead=1)\n",
    "sysidentpy_loss = loss(pd.Series(y_test.flatten()[-sysidentpy.max_lag:]), pd.Series(yhat.flatten()[-sysidentpy.max_lag:]))\n",
    "print(sysidentpy_loss)\n",
    "\n",
    "\n",
    "plot_results(y=y_test[-104:], yhat=yhat[-104:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MetaMSS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set_random_seed(42)\n",
    "files = ['\\SanFrancisco_PV_GHI.csv', '\\SanFrancisco_Hospital.csv']\n",
    "raw = pd.read_csv(data_location + files[0])\n",
    "df=pd.DataFrame()\n",
    "df['ds'] = pd.date_range('1/1/2015 1:00:00', freq=str(60) + 'Min',\n",
    "                               periods=(8760)) \n",
    "df['y'] = raw.iloc[:,0].values\n",
    "\n",
    "df_train, df_val = df.iloc[:7008, :], df.iloc[7008:, :]\n",
    "\n",
    "y = df['y'].values.reshape(-1, 1)\n",
    "y_train = df_train['y'].values.reshape(-1, 1)\n",
    "y_test = df_val['y'].values.reshape(-1, 1)\n",
    "\n",
    "x_train = df_train['ds'].dt.hour.values.reshape(-1, 1)\n",
    "x_test = df_val['ds'].dt.hour.values.reshape(-1, 1)\n",
    "basis_function = Polynomial(degree=1)\n",
    "sysidentpy_metamss = MetaMSS(\n",
    "    basis_function=basis_function,\n",
    "    norm=-2,\n",
    "    xlag=2,\n",
    "    ylag=2,\n",
    "    estimator=\"least_squares\",\n",
    "    k_agents_percent=2,\n",
    "    estimate_parameter=True,\n",
    "    maxiter=10,\n",
    "    steps_ahead=1,\n",
    "    n_agents=15,\n",
    "    p_value=0.05,\n",
    "    loss_func='metamss_loss',\n",
    "    p_ones=0.5,\n",
    "    p_zeros=0.5,\n",
    "    model_type='NARMAX'\n",
    "    )\n",
    "sysidentpy_metamss.fit(X_train=x_train, X_test=x_test, y_train=y_train, y_test=y_test)\n",
    "x_test = np.concatenate([x_train[-sysidentpy_metamss.max_lag:], x_test])\n",
    "y_test = np.concatenate([y_train[-sysidentpy_metamss.max_lag:], y_test])\n",
    "\n",
    "yhat = sysidentpy_metamss.predict(X_test=x_test, y_test=y_test, steps_ahead=1)\n",
    "metamss_loss = loss(pd.Series(y_test.flatten()[-sysidentpy_metamss.max_lag:]), pd.Series(yhat.flatten()[-sysidentpy_metamss.max_lag:]))\n",
    "print(metamss_loss)\n",
    "\n",
    "\n",
    "plot_results(y=y_test[-104:], yhat=yhat[-104:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AOLS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set_random_seed(42)\n",
    "files = ['\\SanFrancisco_PV_GHI.csv', '\\SanFrancisco_Hospital.csv']\n",
    "raw = pd.read_csv(data_location + files[0])\n",
    "df=pd.DataFrame()\n",
    "df['ds'] = pd.date_range('1/1/2015 1:00:00', freq=str(60) + 'Min',\n",
    "                               periods=(8760)) \n",
    "df['y'] = raw.iloc[:,0].values\n",
    "\n",
    "df_train, df_val = df.iloc[:7008, :], df.iloc[7008:, :]\n",
    "\n",
    "y = df['y'].values.reshape(-1, 1)\n",
    "y_train = df_train['y'].values.reshape(-1, 1)\n",
    "y_test = df_val['y'].values.reshape(-1, 1)\n",
    "\n",
    "x_train = df_train['ds'].dt.hour.values.reshape(-1, 1)\n",
    "x_test = df_val['ds'].dt.hour.values.reshape(-1, 1)\n",
    "basis_function = Polynomial(degree=1)\n",
    "sysidentpy_AOLS = AOLS(\n",
    "    ylag=2, xlag=2,\n",
    "    k=2,\n",
    "    L=1,\n",
    "    model_type=\"NARMAX\",\n",
    "    basis_function=basis_function\n",
    ")\n",
    "sysidentpy_AOLS.fit(X=x_train, y=y_train)\n",
    "x_test = np.concatenate([x_train[-sysidentpy_AOLS.max_lag:], x_test])\n",
    "y_test = np.concatenate([y_train[-sysidentpy_AOLS.max_lag:], y_test])\n",
    "\n",
    "yhat = sysidentpy_metamss.predict(X_test=x_test, y_test=y_test, steps_ahead=1)\n",
    "aols_loss = loss(pd.Series(y_test.flatten()[-sysidentpy_AOLS.max_lag:]), pd.Series(yhat.flatten()[-sysidentpy_AOLS.max_lag:]))\n",
    "print(aols_loss)\n",
    "\n",
    "\n",
    "plot_results(y=y_test[-104:], yhat=yhat[-104:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Neural Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: nprophet - fit: Parts of code may break if using other than daily data.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:44 - WARNING - Parts of code may break if using other than daily data.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: nprophet.utils - set_auto_seasonalities: Disabling yearly seasonality. Run NeuralProphet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:44 - INFO - Disabling yearly seasonality. Run NeuralProphet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: nprophet.config - set_auto_batch_epoch: Auto-set batch_size to 32\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:44 - INFO - Auto-set batch_size to 32\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: nprophet.config - set_auto_batch_epoch: Auto-set epochs to 7\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:44 - INFO - Auto-set epochs to 7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 87%|████████▋ | 87/100 [00:00<00:00, 762.47it/s]\n",
      "INFO: nprophet - _lr_range_test: learning rate range test found optimal lr: 1.87E-01\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:44 - INFO - learning rate range test found optimal lr: 1.87E-01\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch[7/7]: 100%|██████████| 7/7 [00:02<00:00,  2.87it/s, SmoothL1Loss=0.0031, MAE=51.3, RegLoss=0.0102]\n",
      "INFO: nprophet - _evaluate: Validation metrics:    SmoothL1Loss    MAE\n",
      "1         0.002 44.072\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-16 15:25:47 - INFO - Validation metrics:    SmoothL1Loss    MAE\n",
      "1         0.002 44.072\n",
      "3679.9220330403255\n"
     ]
    }
   ],
   "source": [
    "set_random_seed(42)\n",
    "\n",
    "# set_log_level(\"ERROR\")\n",
    "files = ['\\SanFrancisco_PV_GHI.csv', '\\SanFrancisco_Hospital.csv']\n",
    "raw = pd.read_csv(data_location + files[0])\n",
    "df=pd.DataFrame()\n",
    "df['ds'] = pd.date_range('1/1/2015 1:00:00', freq=str(60) + 'Min',\n",
    "                               periods=(8760)) \n",
    "df['y'] = raw.iloc[:,0].values\n",
    "\n",
    "m = NeuralProphet(\n",
    "    n_lags=24,\n",
    "    ar_sparsity=0.5,\n",
    "    #num_hidden_layers = 2,\n",
    "    #d_hidden=20,\n",
    ")\n",
    "metrics = m.fit(df, freq='H', valid_p = 0.2)\n",
    "\n",
    "df_train, df_val = m.split_df(df,valid_p=0.2)\n",
    "m.test(df_val)\n",
    "\n",
    "future = m.make_future_dataframe(df_val, n_historic_predictions=True)\n",
    "forecast = m.predict(future)\n",
    "# fig = m.plot(forecast)\n",
    "print(loss(forecast['y'][24:-1], forecast['yhat1'][24:-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2300ff35fd0>]"
      ]
     },
     "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": [
    "plt.plot(forecast['y'][-104:], 'ro-')\n",
    "plt.plot(forecast['yhat1'][-104:], 'k*-')"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "d637594906b92e2064a8978fcd7d47bb213aa9d5bb48152798bc86e8ea48bb1d"
  },
  "kernelspec": {
   "display_name": "Python 3.8.11 64-bit ('neural_prophet': conda)",
   "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": "3.8.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
