NN Model-Train2-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "Train = pd.read_csv(\"DataSets/Train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>is_holiday</th>\n",
       "      <th>air_pollution_index</th>\n",
       "      <th>humidity</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>visibility_in_miles</th>\n",
       "      <th>dew_point</th>\n",
       "      <th>temperature</th>\n",
       "      <th>rain_p_h</th>\n",
       "      <th>snow_p_h</th>\n",
       "      <th>clouds_all</th>\n",
       "      <th>weather_type</th>\n",
       "      <th>weather_description</th>\n",
       "      <th>traffic_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-10-02 09:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>121</td>\n",
       "      <td>89</td>\n",
       "      <td>2</td>\n",
       "      <td>329</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>288.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>scattered clouds</td>\n",
       "      <td>5545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-10-02 10:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>178</td>\n",
       "      <td>67</td>\n",
       "      <td>3</td>\n",
       "      <td>330</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>289.36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>4516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-10-02 11:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>113</td>\n",
       "      <td>66</td>\n",
       "      <td>3</td>\n",
       "      <td>329</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>289.58</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>4767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-10-02 12:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>3</td>\n",
       "      <td>329</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>290.13</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>5026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-10-02 13:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>281</td>\n",
       "      <td>65</td>\n",
       "      <td>3</td>\n",
       "      <td>329</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>291.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>4918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date_time is_holiday  air_pollution_index  humidity  wind_speed  \\\n",
       "0  2012-10-02 09:00:00       None                  121        89           2   \n",
       "1  2012-10-02 10:00:00       None                  178        67           3   \n",
       "2  2012-10-02 11:00:00       None                  113        66           3   \n",
       "3  2012-10-02 12:00:00       None                   20        66           3   \n",
       "4  2012-10-02 13:00:00       None                  281        65           3   \n",
       "\n",
       "   wind_direction  visibility_in_miles  dew_point  temperature  rain_p_h  \\\n",
       "0             329                    1          1       288.28       0.0   \n",
       "1             330                    1          1       289.36       0.0   \n",
       "2             329                    2          2       289.58       0.0   \n",
       "3             329                    5          5       290.13       0.0   \n",
       "4             329                    7          7       291.14       0.0   \n",
       "\n",
       "   snow_p_h  clouds_all weather_type weather_description  traffic_volume  \n",
       "0       0.0          40       Clouds    scattered clouds            5545  \n",
       "1       0.0          75       Clouds       broken clouds            4516  \n",
       "2       0.0          90       Clouds     overcast clouds            4767  \n",
       "3       0.0          90       Clouds     overcast clouds            5026  \n",
       "4       0.0          75       Clouds       broken clouds            4918  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {'traffic_volume':Train['traffic_volume'], 'date_time':Train['date_time']}\n",
    "target = pd.DataFrame(data).set_index('date_time')\n",
    "Train.drop(columns =[\"traffic_volume\"], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(target[:200])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preProcessingScript(dataFrame):\n",
    "    import pickle\n",
    "    dataFrame['is_holiday'] = np.where(dataFrame['is_holiday'] == \"None\", \"Working Day\", dataFrame['is_holiday'])\n",
    "    dateTimeSplits = dataFrame[\"date_time\"].str.split(\" \")\n",
    "    dataFrame[\"Year\"] = pd.DataFrame([ item[0].split(\"-\")[0] for item in dateTimeSplits ])\n",
    "    dataFrame[\"Month\"] = pd.DataFrame([ item[0].split(\"-\")[1] for item in dateTimeSplits ])\n",
    "    dataFrame[\"Day\"] = pd.DataFrame([ item[0].split(\"-\")[2] for item in dateTimeSplits ])\n",
    "    dataFrame[\"hour\"] = pd.DataFrame([ item[1].split(\":\")[0] for item in dateTimeSplits ])\n",
    "    dataFrame.drop(columns =[\"date_time\"], inplace = True)\n",
    "    mapper_fit = pickle.load(open('fitted_mapper.pkl', 'rb'))\n",
    "    return mapper_fit.transform(dataFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, LSTM, Dropout, Activation, Flatten, TimeDistributed, AveragePooling1D\n",
    "from tensorflow.keras.callbacks import TensorBoard\n",
    "import time\n",
    "\n",
    "def baseline_model():\n",
    "    model = Sequential()\n",
    "    model.add(Dense(330, input_dim=17, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(316, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(240, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(346, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Flatten())\n",
    "    model.add(Dropout(0.2))\n",
    "    model.add(Dense(60, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(54, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(45, kernel_initializer='normal', activation='relu'))\n",
    "    model.add(Dense(1, kernel_initializer='normal'))\n",
    "    model.compile(loss='mean_squared_error', optimizer='rmsprop')\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model = baseline_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 330)               5940      \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 316)               104596    \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 240)               76080     \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 346)               83386     \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 346)               0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 346)               0         \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 60)                20820     \n",
      "_________________________________________________________________\n",
      "dense_5 (Dense)              (None, 54)                3294      \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 45)                2475      \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 1)                 46        \n",
      "=================================================================\n",
      "Total params: 296,637\n",
      "Trainable params: 296,637\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataForT = preProcessingScript(Train)\n",
    "targetForT = target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>is_holiday</th>\n",
       "      <th>air_pollution_index</th>\n",
       "      <th>humidity</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>visibility_in_miles</th>\n",
       "      <th>dew_point</th>\n",
       "      <th>temperature</th>\n",
       "      <th>rain_p_h</th>\n",
       "      <th>snow_p_h</th>\n",
       "      <th>clouds_all</th>\n",
       "      <th>weather_type</th>\n",
       "      <th>weather_description</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11</td>\n",
       "      <td>-0.404153</td>\n",
       "      <td>1.055720</td>\n",
       "      <td>-0.670405</td>\n",
       "      <td>1.297362</td>\n",
       "      <td>-1.552441</td>\n",
       "      <td>-1.552441</td>\n",
       "      <td>0.612030</td>\n",
       "      <td>-0.008384</td>\n",
       "      <td>-0.032546</td>\n",
       "      <td>-0.269063</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>-1.678399</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.391304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11</td>\n",
       "      <td>0.276572</td>\n",
       "      <td>-0.249763</td>\n",
       "      <td>-0.183967</td>\n",
       "      <td>1.307378</td>\n",
       "      <td>-1.552441</td>\n",
       "      <td>-1.552441</td>\n",
       "      <td>0.692536</td>\n",
       "      <td>-0.008384</td>\n",
       "      <td>-0.032546</td>\n",
       "      <td>0.631348</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>-1.678399</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.434783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>-0.499693</td>\n",
       "      <td>-0.309103</td>\n",
       "      <td>-0.183967</td>\n",
       "      <td>1.297362</td>\n",
       "      <td>-1.163334</td>\n",
       "      <td>-1.163334</td>\n",
       "      <td>0.708936</td>\n",
       "      <td>-0.008384</td>\n",
       "      <td>-0.032546</td>\n",
       "      <td>1.017238</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1.678399</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.478261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11</td>\n",
       "      <td>-1.610349</td>\n",
       "      <td>-0.309103</td>\n",
       "      <td>-0.183967</td>\n",
       "      <td>1.297362</td>\n",
       "      <td>0.003989</td>\n",
       "      <td>0.003989</td>\n",
       "      <td>0.749934</td>\n",
       "      <td>-0.008384</td>\n",
       "      <td>-0.032546</td>\n",
       "      <td>1.017238</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>-1.678399</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.521739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>1.506654</td>\n",
       "      <td>-0.368443</td>\n",
       "      <td>-0.183967</td>\n",
       "      <td>1.297362</td>\n",
       "      <td>0.782204</td>\n",
       "      <td>0.782204</td>\n",
       "      <td>0.825223</td>\n",
       "      <td>-0.008384</td>\n",
       "      <td>-0.032546</td>\n",
       "      <td>0.631348</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>-1.678399</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.565217</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   is_holiday  air_pollution_index  humidity  wind_speed  wind_direction  \\\n",
       "0          11            -0.404153  1.055720   -0.670405        1.297362   \n",
       "1          11             0.276572 -0.249763   -0.183967        1.307378   \n",
       "2          11            -0.499693 -0.309103   -0.183967        1.297362   \n",
       "3          11            -1.610349 -0.309103   -0.183967        1.297362   \n",
       "4          11             1.506654 -0.368443   -0.183967        1.297362   \n",
       "\n",
       "   visibility_in_miles  dew_point  temperature  rain_p_h  snow_p_h  \\\n",
       "0            -1.552441  -1.552441     0.612030 -0.008384 -0.032546   \n",
       "1            -1.552441  -1.552441     0.692536 -0.008384 -0.032546   \n",
       "2            -1.163334  -1.163334     0.708936 -0.008384 -0.032546   \n",
       "3             0.003989   0.003989     0.749934 -0.008384 -0.032546   \n",
       "4             0.782204   0.782204     0.825223 -0.008384 -0.032546   \n",
       "\n",
       "   clouds_all  weather_type  weather_description      Year     Month  \\\n",
       "0   -0.269063             1                   24 -1.678399  0.818182   \n",
       "1    0.631348             1                    2 -1.678399  0.818182   \n",
       "2    1.017238             1                   19 -1.678399  0.818182   \n",
       "3    1.017238             1                   19 -1.678399  0.818182   \n",
       "4    0.631348             1                    2 -1.678399  0.818182   \n",
       "\n",
       "        Day      hour  \n",
       "0  0.033333  0.391304  \n",
       "1  0.033333  0.434783  \n",
       "2  0.033333  0.478261  \n",
       "3  0.033333  0.521739  \n",
       "4  0.033333  0.565217  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataForT.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Execute from here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "fieTime = int(time.time())\n",
    "NAME = \"Traffic-{}\".format(fieTime)\n",
    "modelFilename = \"Train2\\DLModel-{}.h5\".format(fieTime)\n",
    "LRfilename = \"Train2\\LRModel{}.pkl\".format(fieTime)\n",
    "outfilename = \"Train2\\Prediction{}.csv\".format(fieTime)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 33412 samples, validate on 338 samples\n",
      "Epoch 1/500\n",
      "33412/33412 - 0s - loss: 18227.8592 - val_loss: 1769204.1250\n",
      "Epoch 2/500\n",
      "33412/33412 - 0s - loss: 13351.9591 - val_loss: 2014898.7500\n",
      "Epoch 3/500\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 441/500\n",
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      "Epoch 498/500\n",
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      "Epoch 499/500\n",
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      "Epoch 500/500\n",
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     ]
    }
   ],
   "source": [
    "tensorboard = TensorBoard(log_dir=\"logs\\{}\".format(NAME))\n",
    "fM= model.fit(dataForT, targetForT, epochs=500, batch_size=1100, validation_split=0.01, verbose=2,callbacks=[tensorboard] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(modelFilename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from tensorflow import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model = keras.models.load_model(\"Train2/DLModel-1564833055.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rcmodel = keras.models.load_model(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "orig = pd.Series(list(target[\"traffic_volume\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = pd.Series([p[0] for p in model.predict(dataForT)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Comaprison of flow Between Original and predictions')"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(orig[:400],label=\"Original Data\")\n",
    "plt.plot(predictions[:400],label=\"Predictions\")\n",
    "plt.legend(loc='upper left')\n",
    "plt.title(\"Comaprison of flow Between Original and predictions\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Comaprison of flow Between Original and predictions')"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.plot(orig[-1000:],label=\"Original Data\")\n",
    "plt.plot(predictions[-1000:],label=\"Predictions\")\n",
    "plt.legend(loc='upper left')\n",
    "plt.title(\"Comaprison of flow Between Original and predictions\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "LRmodel = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n",
       "         normalize=False)"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LRmodel.fit(np.array(predictions.tolist()).reshape(-1, 1),np.array(orig.tolist()).reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "pickle.dump(LRmodel, open(LRfilename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "# RCLRModel = pickle.load(open(filename, 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "Test_data = pd.read_csv(\"DataSets/Test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "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_time</th>\n",
       "      <th>is_holiday</th>\n",
       "      <th>air_pollution_index</th>\n",
       "      <th>humidity</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>visibility_in_miles</th>\n",
       "      <th>dew_point</th>\n",
       "      <th>temperature</th>\n",
       "      <th>rain_p_h</th>\n",
       "      <th>snow_p_h</th>\n",
       "      <th>clouds_all</th>\n",
       "      <th>weather_type</th>\n",
       "      <th>weather_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-05-18 00:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>73</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>285.15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>Rain</td>\n",
       "      <td>moderate rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-05-18 00:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>251</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>285.15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>Mist</td>\n",
       "      <td>mist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-05-18 00:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>75</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>285.15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>Drizzle</td>\n",
       "      <td>light intensity drizzle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-05-18 01:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>98</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>351</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>284.79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>Rain</td>\n",
       "      <td>heavy intensity rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-05-18 01:00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>283</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>351</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>284.79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>Mist</td>\n",
       "      <td>mist</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date_time is_holiday  air_pollution_index  humidity  wind_speed  \\\n",
       "0  2017-05-18 00:00:00       None                   73        63           1   \n",
       "1  2017-05-18 00:00:00       None                  251        63           1   \n",
       "2  2017-05-18 00:00:00       None                   75        56           1   \n",
       "3  2017-05-18 01:00:00       None                   98        56           1   \n",
       "4  2017-05-18 01:00:00       None                  283        56           1   \n",
       "\n",
       "   wind_direction  visibility_in_miles  dew_point  temperature  rain_p_h  \\\n",
       "0              27                    4          4       285.15       0.0   \n",
       "1              27                    4          4       285.15       0.0   \n",
       "2               0                    1          1       285.15       0.0   \n",
       "3             351                    2          2       284.79       0.0   \n",
       "4             351                    1          1       284.79       0.0   \n",
       "\n",
       "   snow_p_h  clouds_all weather_type      weather_description  \n",
       "0         0          90         Rain            moderate rain  \n",
       "1         0          90         Mist                     mist  \n",
       "2         0          90      Drizzle  light intensity drizzle  \n",
       "3         0          90         Rain     heavy intensity rain  \n",
       "4         0          90         Mist                     mist  "
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Test_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(model,data):\n",
    "    outputDate = data[\"date_time\"]\n",
    "    preprocessedData = pd.DataFrame(preProcessingScript(data))\n",
    "    return postProcessingScript(model.predict(preprocessedData),outputDate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "def postProcessingScript(predictions,index):\n",
    "    import pandas as pd\n",
    "    import numpy as np\n",
    "    RCLRModel = pickle.load(open(LRfilename, 'rb'))\n",
    "    filteredPredictionsIntList = [int(round(item[0])) for item in RCLRModel.predict(predictions)]\n",
    "#     filteredPredictionsIntList = [int(round(item[0])) for item in predictions]\n",
    "    data = {'date_time': index,'traffic_volume':filteredPredictionsIntList}\n",
    "    output = pd.DataFrame(data)\n",
    "    output[\"traffic_volume\"] = np.where(output['traffic_volume']  <= 0 , output['traffic_volume'].rolling(2).median(), output['traffic_volume'])\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictionDataFrame = predict(model,Test_data)\n",
    "predictionDataFrame.to_csv(outfilename, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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