Deleted empty folders

lstm_energy.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,9 +25,115 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\levim\\AppData\\Local\\Temp\\ipykernel_12184\\1569659483.py:5: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  extended_energy_data['date'] = pd.to_datetime(extended_energy_data['date'])\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>hvac_N</th>\n",
+       "      <th>hvac_S</th>\n",
+       "      <th>air_temp_set_1</th>\n",
+       "      <th>solar_radiation_set_1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2018-01-01 00:00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11.5400</td>\n",
+       "      <td>51.4075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2018-01-01 01:00:00</td>\n",
+       "      <td>37.525001</td>\n",
+       "      <td>19.395</td>\n",
+       "      <td>10.8900</td>\n",
+       "      <td>2.1250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2018-01-01 02:00:00</td>\n",
+       "      <td>37.750001</td>\n",
+       "      <td>22.775</td>\n",
+       "      <td>10.7550</td>\n",
+       "      <td>0.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2018-01-01 03:00:00</td>\n",
+       "      <td>37.550001</td>\n",
+       "      <td>18.920</td>\n",
+       "      <td>10.4775</td>\n",
+       "      <td>0.0000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2018-01-01 04:00:00</td>\n",
+       "      <td>36.675001</td>\n",
+       "      <td>21.600</td>\n",
+       "      <td>9.9925</td>\n",
+       "      <td>0.0000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 date     hvac_N  hvac_S  air_temp_set_1  \\\n",
+       "0 2018-01-01 00:00:00        NaN     NaN         11.5400   \n",
+       "1 2018-01-01 01:00:00  37.525001  19.395         10.8900   \n",
+       "2 2018-01-01 02:00:00  37.750001  22.775         10.7550   \n",
+       "3 2018-01-01 03:00:00  37.550001  18.920         10.4775   \n",
+       "4 2018-01-01 04:00:00  36.675001  21.600          9.9925   \n",
+       "\n",
+       "   solar_radiation_set_1  \n",
+       "0                51.4075  \n",
+       "1                 2.1250  \n",
+       "2                 0.0000  \n",
+       "3                 0.0000  \n",
+       "4                 0.0000  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Prepar energy data set with extended features\n",
     "feature_list = ['date', 'hvac_N', 'hvac_S', 'air_temp_set_1', 'solar_radiation_set_1']\n",
@@ -36,7 +142,7 @@
     "extended_energy_data['date'] = pd.to_datetime(extended_energy_data['date'])\n",
     "extended_energy_data.set_index('date', inplace=True)\n",
     "\n",
-    "extended_energy_data = extended_energy_data.resample('15T').mean()\n",
+    "extended_energy_data = extended_energy_data.resample('60T').mean()\n",
     "# extended_energy_data = extended_energy_data.interpolate(method='linear')\n",
     "\n",
     "extended_energy_data = extended_energy_data.reset_index(drop=False)\n",
@@ -45,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,9 +172,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "testdataset_df = df_filtered[(df_filtered.date.dt.date <date(2019, 2, 20))]\n",
     "\n",
@@ -84,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,15 +218,52 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/5\n",
+      "56/56 [==============================] - ETA: 0s - loss: 0.0359\n",
+      "Epoch 1: val_loss improved from inf to 0.02863, saving model to lstm_energy_01.keras\n",
+      "56/56 [==============================] - 14s 157ms/step - loss: 0.0359 - val_loss: 0.0286\n",
+      "Epoch 2/5\n",
+      "56/56 [==============================] - ETA: 0s - loss: 0.0185\n",
+      "Epoch 2: val_loss improved from 0.02863 to 0.02514, saving model to lstm_energy_01.keras\n",
+      "56/56 [==============================] - 8s 138ms/step - loss: 0.0185 - val_loss: 0.0251\n",
+      "Epoch 3/5\n",
+      "56/56 [==============================] - ETA: 0s - loss: 0.0170\n",
+      "Epoch 3: val_loss improved from 0.02514 to 0.02490, saving model to lstm_energy_01.keras\n",
+      "56/56 [==============================] - 8s 142ms/step - loss: 0.0170 - val_loss: 0.0249\n",
+      "Epoch 4/5\n",
+      "56/56 [==============================] - ETA: 0s - loss: 0.0159\n",
+      "Epoch 4: val_loss did not improve from 0.02490\n",
+      "56/56 [==============================] - 8s 141ms/step - loss: 0.0159 - val_loss: 0.0278\n",
+      "Epoch 5/5\n",
+      "56/56 [==============================] - ETA: 0s - loss: 0.0148\n",
+      "Epoch 5: val_loss did not improve from 0.02490\n",
+      "56/56 [==============================] - 9s 158ms/step - loss: 0.0148 - val_loss: 0.0255\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<keras.callbacks.History at 0x1e461cb04f0>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "train,test = traindataset,testdataset\n",
-    "steps_in_past = 24*4\n",
-    "time_step = 1\n",
-    "no_inputs = 5\n",
-    "no_outputs = 5\n",
+    "steps_in_past   = 3   \n",
+    "time_step       = 24\n",
+    "no_inputs       = 5\n",
+    "no_outputs      = 2\n",
     "def create_dataset(dataset,time_step):\n",
     "    x = [[] for _ in range(no_inputs)] \n",
     "    Y = [[] for _ in range(no_outputs)]\n",
@@ -202,9 +356,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "18/18 [==============================] - 2s 32ms/step - loss: 0.0255\n",
+      "18/18 [==============================] - 2s 32ms/step\n",
+      "Loss:  0.02554473653435707\n"
+     ]
+    }
+   ],
    "source": [
     "loss            = model.evaluate(X_test, y_test)\n",
     "test_predict1   = model.predict(X_test)\n",
@@ -217,7 +381,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -229,8 +393,8 @@
     "# Loop over the value index\n",
     "for i, ax in enumerate(axes.flat):\n",
     "    # Plot your data or perform any other operations\n",
-    "    ax.plot(y_test1[i,0:time_step], label='Original Testing Data', color='blue')\n",
-    "    ax.plot(test_predict2[i,0:time_step], label='Predicted Testing Data', color='red',alpha=0.8)\n",
+    "    ax.plot(y_test[i,0:time_step], label='Original Testing Data', color='blue')\n",
+    "    ax.plot(test_predict1[i,0:time_step], label='Predicted Testing Data', color='red',alpha=0.8)\n",
     "    # ax.set_title(f'Plot {i+1}')\n",
     "    ax.set_title('Testing Data - Predicted vs Actual')\n",
     "    ax.set_xlabel('Time [hours]')\n",