examples/Two Layers Lat Lng Location.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('../')\n",
    "import logging\n",
    "\n",
    "import pandas as pd\n",
    "from sklearn.cluster import DBSCAN\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from lstm_mobility_model.two_layer_latlng_location import TwoLayerLstmModelBuilder\n",
    "from lstm_mobility_model.load import DataPreprocessor\n",
    "\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.INFO)\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_data(dataframe):\n",
    "    processor = DataPreprocessor()\n",
    "    return processor.preprocess_traces_to_dict(dataframe)\n",
    "\n",
    "dataframe = pd.read_csv('../sample_data/sample_data_0.csv')\n",
    "preprocessed_data = preprocess_data(dataframe)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LSTM mobility model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "lstm_model = \\\n",
    "    TwoLayerLstmModelBuilder(\n",
    "        model_path='lstm_model_weights/',\n",
    "        model_name='two_layer_categorical_location',\n",
    "        learning_rate=0.01,\n",
    "        training_epochs=1000,\n",
    "        lstm_dropout=0.0,\n",
    "        lstm_units=16,\n",
    "        number_of_mixtures=40,\n",
    "        sampling_bias=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:Epoch: 100 Loss: [  4.3427057 -22.658133 ]\n",
      "INFO:root:Epoch: 200 Loss: [  2.6329496 -40.425007 ]\n",
      "INFO:root:Epoch: 300 Loss: [  2.0191128 -42.27963  ]\n",
      "INFO:root:Epoch: 400 Loss: [  1.5961597 -48.27694  ]\n",
      "INFO:root:Epoch: 500 Loss: [  1.3852612 -51.632248 ]\n",
      "INFO:root:Epoch: 600 Loss: [  1.2561041 -54.401836 ]\n",
      "INFO:root:Epoch: 700 Loss: [  1.1560509 -55.232548 ]\n",
      "INFO:root:Epoch: 800 Loss: [  1.0856735 -56.66521  ]\n",
      "INFO:root:Epoch: 900 Loss: [  1.0438473 -57.086002 ]\n",
      "INFO:root:Epoch: 1000 Loss: [  1.0092837 -58.01385  ]\n",
      "INFO:root:Saved model to lstm_model_weights/two_layer_categorical_location\n"
     ]
    }
   ],
   "source": [
    "lstm_model.train(preprocessed_data,\n",
    "                 batch_size=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "generated_traces = lstm_model.generate(\n",
    "    preprocessed_data,\n",
    "    method='complete')\n",
    "generated_traces_df = pd.concat(list(generated_traces.values()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d058be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d8a74e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.figure()\n",
    "_ = generated_traces_df[generated_traces_df['start_hour_since_day'] != 0][\n",
    "    'start_hour_since_day'].hist(bins=30)\n",
    "_ = plt.title('Generated Activity Start Time Histogram')\n",
    "_ = plt.xlim(0, 25)\n",
    "\n",
    "_ = plt.figure()\n",
    "_ = dataframe[dataframe['start_hour_since_day'] != 0][\n",
    "    'start_hour_since_day'].hist(bins=30)\n",
    "_ = plt.title('Observed Activity Start Time Histogram')\n",
    "_ = plt.xlim(0, 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d0589e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEXCAYAAABCjVgAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3XmYXGWZ9/HvXdVLYjqE0MGQhSRgFA0YAkYCbwDZdFAEVJARUEDHYXTAXQluLEaQRVFHGGZkERgWBQIkEkQZCLIISIKdkIQtA4EsEJImIemQdLq77vePc6q6urqquqq7a/99rquu7jrrU6dOPfd5lvMcc3dEREQAIqVOgIiIlA8FBRERSVBQEBGRBAUFERFJUFAQEZEEBQUREUlQUKhCZnaBmd1c6nTkw8zOMLPHSp2O/jKzU83sL6VOR6Uzsz+Z2emlTkctU1CoQGEG+qyZvWNmb5jZ1Wa2c6nTVUhm9i9m9ryZbTGzdWZ2n5kND+fdYGY/HeD2swYlM1tmZm3hq8vMtie9/4G73+LuHxtIGkrJzFaa2bbw+G4ys7+Z2VfMrGB5RLqLF3f/uLvfWKh9St8UFCqMmX0HuBT4HjACOBCYCDxgZg1FTEddEff1EeBi4GR3Hw58APjDIG6/z8/i7nu7e5O7NwGPAmfH37v7xYOVlhI7Njy+E4FLgFnAdf3ZUDHPDxlk7q5XhbyAnYA24KSU6U3AeuBL4fsLgDsJMs4twDPAvknLzwLWhPNeAI4Mp0eAc4H/A1qB24FdwnmTAAf+BXgNeAT4E0HmmJyWxcBnwv/fDzwAvBXu56Sk5ZqBecBm4O/AbOCxDJ/7u8A9GeadCXQAO8Jj88dwevxzbAGWA59OWucM4HHgl+HnnANsB7rCbWzq43t4GPhyyrQzktMfHqt/B14K0zAbeA/wt/Az3w40JC3/SaAF2BQuMzXDvq8Gfp4ybS7w7WzfbQ7n1krgqJRpBwAxYJ90nzvDZz4r/MyvhNN+DawKP/Mi4JBw+tHhd9YRHvPFqfsgOB9/BLwKvAncBIxIOR9PJzgfNwA/LPVvtBpeJU+AXnl8WcEPqROoSzPvRuC28P8Lwh/biUB9mKm+Ev6/V/gjHRsuOwl4T/j/N4AngfFAI/DfSduM/whvAoYBQ4HTgMeT0jAlzNQaw2VWAV8E6oD9wh/ulHDZ34cZ4zBgnzAjyxQUDgG2ARcCM4HGlPk3AD9NmfZZYGyYsfwzsBUYE847IzyOXwvTNjQ1g+vje+iROSZtMzWDnEsQyPcG2oEHgT0JSnjLgdPDZfcLM70ZQDTM6Famfs5w2UPD42rh+5HhsRmb7bvN4TOtJCUohNNfA76a7nNn+MwPALsAQ8Npnye4AKgDvgO8AQxJOk9vznRsgS8BK8Jj1gTcBfxPyvl4Tfj97Rse4w+U+nda6S9VH1WWUcAGd+9MM+/1cH7cIne/0907gCuAIQRVTV0EmfYUM6t395Xu/n/hOl8huNpa7e7tBD/aE1OqAi5w963uvg24G5hmZhPDeacCd4XrfhJY6e6/c/dOd/8HwRX5Z80sCpwAnBduaylBUEvL3R8FPgPsD8wHWs3sinA7mda5w93XunvM3f9AcPV6QNIia939N2HatmXazgBd5u6b3X0ZsBT4i7u/7O5vE5Sy9guXOxP4b3d/yt27PKhTbyf4vlI9SpAZHhK+PxF4wt3Xkv277a+1BJl8rn7m7m/Fj6m73+zureFx/kWYvr1y3NapwBXhMWsDvg98LuV8vNDdt7n7YoJS6r55pFXSUFCoLBuAURnqa8eE8+NWxf9x9xiwmuAKcgXwTYIM/00z+72ZjQ0XnQjcHTY0bgKeI8hoRmfY7haCTPpz4aSTgVuStjUjvq1we6cCuwG7Elw5JrZFUEWQkbv/yd2PJcigjie4Sv1ypuXN7DQza0na9z70DJqrMqw6mNYl/b8tzfum8P+JwHdSjtXuBFf/Pbi7E5SyTg4nnUJ4zPv4bvtrHEH1X656HFcz+66ZPWdmb4efawQ9v4dsxtLzvHiV4LxJPh/fSPr/HbqPqfSTgkJleYLgCvIzyRPNrAn4OEH1RNzuSfMjBFVCawHc/VZ3P5ggM3KChmsIftAfd/edk15D3H1N0nZTh9W9DTjZzA4iKI0sSNrWX1O21eTuXyVo/+hMTiMwIZcDEF75Pwg8RJDR90pTWHK5BjgbaHb3nQmu1C3L5yjlcMGrgItSjtW73P22DMvfRlCCm0hQ5TQnPiPLd5s3M/swQVCI98raCrwraZHd0qyWOI5mdghwDnASMDL8Ht6m+3vo65ivJfgccRMIzpt16ReXwaCgUEHCaocLgd+Y2dFmVm9mkwjq5lcD/5O0+IfM7DNhqeKbBMHkSTPby8yOMLNGgsbVbQSNiQD/BVwUrw4ys13N7Pg+knUfwQ/3J8AfwlIJwL3A+8zsC2E6683sw2b2AXfvIqgfvsDM3mVmUwjq0dMys+PN7HNmNtICBwAfIWj/gCCT2DNplWEEGc76cP0v0h1AMlkHjC9mD64k1wBfMbMZ4ecbZmbHxLvcpgqr4jYA1wJ/dvdNAH18tzkzs53M7JMEJZKb3f3ZcFYL8JnwO5tM0Okgm+EEmfh6oM7MziNoY4lbB0zK0u31NuBbZrZHeOFzMcE5lq76VAaJgkKFcffLgB8APyfo0fEUwZXmkWFdftxcggbWjcAXCHoEdRDU6V5CkKm8AbyboK4Wgp4i84C/mNkWgkx3Rh/paSfI4I8Cbk2avgX4GEHV0tpwX5eG+4fgKr4pnH4D8Lssu9kI/CtBu8Bm4GbgcnePV1VdR1CPvsnM7nH35cAvCEpW64APEvQ2yuYhYBnwhplt6GPZQeXuCwk+35UEn3UFQfVYNreScszJ8t1acHPdsj62+cfwe18F/JCgLeqLSfN/SdBjaB1BG9AtvbbQ05+B+4EXCap+ttOzeumO8G+rmT2TZv3rCS50HiHoKLGdoHOAFFC8B4OIiIhKCiIi0k1BQUREEhQUREQkQUFBREQSKmLQqlGjRvmkSZNKnQwRkYqyaNGiDe6+az7rVERQmDRpEgsXLix1MkREKoqZZR0pIB1VH4mISIKCgoiIJCgoiIhIgoKCiIgkKCiIiEiCgoKI1LzWtnYWr9pEa1t73wtXuYrokioiUihzW9Ywa84S6iMROmIxLjthKsdNG1fqZJWMSgoiUrNa29qZNWcJ2ztibGnvZHtHjHPmLKnpEoOCgojUrNUbt1Ef6ZkN1kcirN5YqMd2lz8FBRGpWeNHDqUj1vPhdB2xGONHDi1RikpPQUFEalZzUyOXnTCVIfURhjfWMaQ+wmUnTKW5qbHvlauUGppFpKYdN20cMyePYvXGbYwfObSmAwIoKIiI0NzUWPPBIE7VRyIikqCgICIiCQoKIiKSoKAgIiIJCgoiIpKgoCAiIgkKCiIikqCgICIiCQoKIiKSoKAgIiIJCgoiIpKgoCAiIgkKCiIikqCgICIiCQoKIiKSoKAgIiIJCgoiIpKgoCAiIgkKCiIikqCgICIiCQoKImWita2dxas20drWXuqkSA2rK3UCRATmtqxh1pwl1EcidMRiXHbCVI6bNq7UyZIaVLCSgpntbmYLzGy5mS0zs2+E03cxswfM7KXw78hCpUGkErS2tTNrzhK2d8TY0t7J9o4Y58xZohKDlEQhq486ge+4+xTgQOAsM5sCnAs86O7vBR4M34vUrNUbt1Ef6flTrI9EWL1xW4lSJLWsYEHB3V9392fC/7cAzwHjgOOBG8PFbgQ+Vag0iFSC8SOH0hGL9ZjWEYsxfuTQEqVIallRGprNbBKwH/AUMNrdXw9nvQGMzrDOmWa20MwWrl+/vhjJFCmJ5qZGLjthKkPqIwxvrGNIfYTLTphKc1NjqZMmNcjcvbA7MGsC/gpc5O53mdkmd985af5Gd8/arjB9+nRfuHBhQdMpUmqtbe2s3riN8SOHKiDIoDCzRe4+PZ91Ctr7yMzqgTnALe5+Vzh5nZmNcffXzWwM8GYh0yBSKZqbGhUMpOQK2fvIgOuA59z9iqRZ84DTw/9PB+YWKg0iIpKfQpYUZgJfAJ41s5Zw2g+AS4DbzexfgFeBkwqYBhERyUPBgoK7PwZYhtlHFmq/IiLSfxrmQkREEhQUREQkQUFBREQSFBRERCRBQUFERBIUFEREJEFBQUREEhQUREQkQUFBREQSFBRERCRBQUFERBIUFEREJEFBQUREEhQUREQkQUFBREQSFBRERCRBQUFERBIUFEREJEFBQUREEhQUREQkQUFBREQSFBRERCRBQUFERBIUFEREJEFBQUREEhQURKQgWtvaWbxqE61t7aVOiuShrtQJEJHqM7dlDbPmLKE+EqEjFuOyE6Zy3LRxpU6W5EAlBREZVK1t7cyas4TtHTG2tHeyvSPGOXOWqMRQIRQURGRQrd64jfpIz6ylPhJh9cZtJUqR5ENBQUQG1fiRQ+mIxXpM64jFGD9yaIlSJPlQUBCRQdXc1MhlJ0xlSH2E4Y11DKmPcNkJU2luaix10iQHamgWkUF33LRxzJw8itUbtzF+5FAFhAqioCAiBdHc1KhgUIEKVn1kZteb2ZtmtjRp2gVmtsbMWsLXJwq1fxERyV8h2xRuAI5OM/2X7j4tfN1XwP2LiEieChYU3P0R4K1CbV9ERAZfKXofnW1mS8LqpZGZFjKzM81soZktXL9+fTHTJyJSs4odFK4G3gNMA14HfpFpQXf/rbtPd/fpu+66a7HSJyJS04oaFNx9nbt3uXsMuAY4oJj7FxGR7IoaFMxsTNLbTwNLMy0rIiLFV7D7FMzsNuAwYJSZrQbOBw4zs2mAAyuBfyvU/kVEJH8FCwrufnKaydcVan8iIjJwGvtIRKqGHuwzcBrmQkSqgh7sMzhUUhCRiqcH+wyenEsKZjYOmJi8TnjXsohIScUf7LOd7uc4xB/s09zUSGtbu0ZszVFOQcHMLgX+GVgOdIWTHVBQEJGSy/ZgH1Ur5SfXksKngL3cXWUxESk78Qf7nDNnCVEzOrpi/PiYKQCJaqV4KeKcOUuYOXmUSgwZ5BoUXgbqAQUFqWiqRqhex00bx5btnVx473Ia6iLMnr+ct7buyFqtJL3lGhTeAVrM7EGSAoO7f70gqRIpAFUjVLfWtnZmz1/Ojs4YOzqDaVcuWEFQ091Nz4vOLtegMC98iVSk5N4pqkaoTukamxuiEc48dE+uenhFj4sBfeeZ5RQU3P1GM2sA3hdOesHdOwqXLJHB1VfvFKl86Rqbd3TFOGXGBE6ZMUHVhjnK6T4FMzsMeAm4CvhP4EUzO7SA6RIZVNl6p0h1iDc210ctMa0rFuPxFRtobmpk3913VkDIQa43r/0C+Ji7f8TdDwX+Cfhl4ZIlMrjiGcaQ+gjDG+sYUh9RNUIVmjl5FJHumEBnDN3Elqdc2xTq3f2F+Bt3f9HM6guUJpGCOG7aOGZOHqVqhArWV++x1Ru3YWakNi6rmjB3uQaFhWZ2LXBz+P5UYGFhkiRSOM1NjcocKlQuvceGNUTZ3tGzmnB7R4xhDdFiJrWi5Vp99FWCu5m/Hr6Wh9NERAou17GNtu7oojGpTQGgMWps3dGF5CbX3kftwBXhS0SkqHLtPTZ+5FAsYtDVXX1kEevRoSCXGxhr+SbHrEHBzG5395PM7FlSK+kAd59asJSJiIRy7T2WPNxFuvsScqmCSl5mR1eMsw+fzCkzJgDURKAw9155ffdMszHu/rqZTUw3391fLVjKkkyfPt0XLlQThkgtm9eypldmn+mO9HRX+q1t7cy89KEebQ5D6iM8PuuIrMtAUM9uERhSF6XLvWLuhjezRe4+PZ91spYU3P318N9/d/dZKTu7FJjVey0RkcGXT++xdB0KcqmCSrcMELyLkWib+O6dS5gyZicmjx4+OB+ujOTa0PzRNNM+PpgJERHpy0BuQsulCirdMuns6Ixx9K8f4Yd3PcuKdVvyTks5yxoUzOyrYXvCXma2JOn1CrCkOEkUERm4XG5gjC/TWNf39XJnDG75+2sc9ctHOG/us4VMelH11aYwAhgJ/Aw4N2nWFnd/q8BpS1CbgogMllx7H9361Gv85qEXybU3653/diB77NqU2DaUvmG6P20KWYNCmh28GxgSf+/ur+Wzs/5SUBCRUogHhysXrCBixraOzBHCDOoixpC6KNs7u3B3htbXlXSY9v4EhVwHxDvWzF4CXgH+CqwE/pR3CkVEKkhzUyNfO/K9/O3cI5h9/N401lnGZd2ho8vZ0t5JR5fTGSPrjXblKteG5p8CBwIvuvsewJHAkwVLlVSk1rZ2Fq/aVPCTv1j7EYlrbmrk8Pe/OxxXKX/RiLF647ZBTlVh5Dr2UYe7t5pZxMwi7r7AzH5V0JRJRSnWU8309DQpleQb4yIY72SpSkq1tb2Lp15pZd/ddy5gCgdHriWFTWbWBDwC3GJmvwa2Fi5ZUklyHZemEPv53p2LVWKQojlu2jgen3UE//WFD6XtoVQfNYY31vV4pkPcxfc9zy1PFuV+3wHJNSgcT/Cc5m8B9wP/BxxbqERJZYnf8JMsflPQYO+nLtLzx9be6dz6VFH6O4gAQYnh0PftyuUnBt1bhzVGaaiLcNGn9+HJ7x/JzV+ewXWnf5hhDb2z1wv/uIwV67aUdfVnn9VHZhYF7nX3wwlu7Lux4KmSilKsp5otXfM2be29i+xXLljBKTMmVPV4NFJ+Mt1h3dzUSGtbOx0Z7oH7xG8eozFavtWffZYU3L0LiIX3LIj0UoynmrW2tTN7/vK089o7Y1z76MuDti+RXGW6w7q5qZHzj53Sa/kdXc6OzsJWsw5Urg3NbcCzZvYASW0J7v71gqRKKk6hn2qWaUyauKv/+jIjhzUwY4/mqh/FUirDqTMmggdVRvXRCB1dMSIR6zHYXrrhv0st16BwV/gSyaiQTzXLZUyai+97nqbGKJ2xyhnFUqrbqQdO5Oh9dmPZ2s1s3raD79zRc3SgQlSzDlSuD9lRO4KUVHJ3wKhlfpJWvM3hnDlLmDl5VFldgUltemzFhkQ36q5YjPpocNdz6rMeykVOQSEcAC/dQ3b2zLLO9cAngTfdfZ9w2i7AH4BJBHdFn+TuG/NOtdSkeBXVsrWbue/Ztfz+6dUZly3HYrnUnuRu1PGqz8Y6uOrU/dh77Ihe5+eKdVtoWbWJabvvXLJhuXOtPkoeO2MI8Flglz7WuQG4Ergpadq5wIPufomZnRu+1zMZJGePrdjAd25vobOP0Y3LsVgutSddW1hDNMqIoQ29AsJ59zzLTU92d68+7aAJ/OT4DxYtrXE53afg7q1JrzXu/ivgmD7WeQRIHUn1eLq7tN4IfCrfBEvtam1r55w7F/cZEBqiVpbFcqk9uXbXXrFuS4+AAHDTE6+V5FkNuQ6It3/Sa7qZfYXcSxnJRic9ze0NYHSWfZ5pZgvNbOH69ev7sSupNqs3bsPIPvZMfcS49vQPq5FZykKu3bVbVm1Ku36m6YWUa8b+C7rbFDoJ2gM+O5Adu7ubWcZxu939t8BvIRg6eyD7kuowfuRQOruyFxOiUWPvsTsVKUUifculu/a0DGMiZZpeSH09ee3bZvZt4N7wNR/4M/A8QSNyvtaZ2Zhw22OAN/uxDalRzU2NfP7AiWnnNUYpyE1zIoOhr8eITh49nNMOmtBj2mkHTShJY3NfJYV4ivYCPgzMBYxg3KO/92N/84DTgUvCv3P7sQ2pYUd8YDQ3PNF7ULGOLvj01N2YMkalBKlMPzn+g5x24KSS9z7K6clrZvYIcIy7bwnfDwfmu/uhWda5DTgMGAWsA84H7gFuByYArxJ0Se3zsZ568prEtba1M+Pi/83a2FyqXhsi5aZgT14jaBDekfR+B1kaiQHc/WR3H+Pu9e4+3t2vC3svHenu73X3o4r5nGepDs1NjVxx0jTqs5y5peq1IVINcm1ovgn4u5ndHb7/FMF9CCJFd9y0cUwZsxOf+M1j7MhQZGhZtalkxW+RSpbrfQoXAV8ENoavL7r7zwqZMJFsJo8ezs9PnEpDmoeZQGl6bYhUg5zvNXD3Z4BnCpgWkbzEu/qdd89S5i99IzG9VL02RKpBf25AEykbzU2NXPX5D/GtdVt4bMUGRjU1ctB7mkudLJGKpaAgVWHZ65u55P7nqY+U7xOtRCpBrr2PRMpW8kiU5fxEK5FKUDNBobWtvawfli39Fx+JMll86Oxc6fwQCdRE9dHcljWJh1yoaqH65DoSZSY6P0S6VX1JQVUL1S/XkSjT0fkh0lPVlxTSPeRCT+WqPrmMRJmOzg+Rnqq+pDDQqgWpHPGRKIGc2wd0foj0VPVBYSBVC1J55rasYealD/H5a59i5qUPMa9lTdbldX6I9JTTKKmlNhijpLa2teddtSCVpbWtnZmXPsT2ju4r/yH1ER6fdUSf37nOD6lG/RklterbFOKamxr1Y69yA2kf0PkhEqj66iOpHWofEBk4BQWpGmofEBm4mqk+ktrQ366pydS+ILVMQUGqzkDaB3R3s9Q6VR+JhHR3s4iCgkjCYAysJ1LpFBREQuq9JKKgIJKg3ksiamgW6WEwei+JVDIFBRF6d0NVMJBapaAgNU/dUEW6qU1Bapq6oYr0pKAgNU3dUEV6UlCQstPa1p7zQ3IGSt1QRXpSm4KUlWLX78e7oZ6Tsk81NEutUlCQspFcvx9/JsI5c5Ywc/KogmbS6oYq0k1BQcrGQB6SM1DqhioSUJuClA3V74uUnoKClA0NMyFSeiWpPjKzlcAWoAvozPfB0lK9VL9ffvTQodpSyjaFw919Qwn3L2Wqv/X7yrwGn+72rj1qaJaqoMxr8JWqN5iUVqnaFBz4i5ktMrMz0y1gZmea2UIzW7h+/foiJ08qiYaqKAzd7V2bShUUDnb3/YGPA2eZ2aGpC7j7b919urtP33XXXYufQqkYyrwKQ73BalNJgoK7rwn/vgncDRxQinRIdVDmVRjqDVabit6mYGbDgIi7bwn//xjwk2KnQ6qHhqooHPUGqz2laGgeDdxtZvH93+ru95cgHVJFlHkVju72ri1FDwru/jKwb7H3K9VPmZfIwOmOZhERSVBQEBGRBAUFqUnFfJBPqdXSZ5WB0x3NUnNq6e7nWvqsMjhUUpCaUkt3P9fSZ02mktHAqKQgNaWUD/IplvjAgG9v66j6z5pKJaOBU1CQmlLtdz8nZ4o7umJ0VfFnTaUB/AaHqo+kplTz0A2p1UXtnTHMjMY6q7rPmo7GwBocKilIzanWu5/TVY0NqYty1an7MWJoQ1V91nSqvRRYLCopSE1qbmpk3913rqpMMlOmuPfYEVX3WdOp5lJgMamkIFIlNDBg9ZYCi0lBQaSKKFPUGFgDpaAgUmWUKcpAqE1BREQSFBRERCRBQUFEylq6YSs0lEXhqE1BRMpWumErHDSURQEpKIhIWUo3bMX37lwMGO2d+Q1lER8PqlZ7ZOVDQUFEylK6O7SjFgHruVzyUBbxjD/5/8dWbMirZFHrAURBQUTKUro7tLs8Bt4zKnTEYixd8zb//NsngiDS2YW7M7S+LjEoYGeMnEoWGmVVDc1ShdQIWR3SDVtx+Yn7cvmJPaf9+JgpzJ6/PDEQYEeX0xkjMShgZ8+4knGQvFp9/kQqlRSkquhKr7pkukM7eVq6aqZsOmIxhjVEWbxqU49t1sKzNnKhoCBVQ+Pp56bS6szT3aGdOi21milZfdSIGDREo3TEYhw3dQyf+I9HqY9G6HJPXDholNWAgoJUDV3p9a0aS1KpAwEmtynEP2O8ZPHQc+v49UMrANjR1QX0vHCo9QEFQUFBysxArmJ1pZddNZekUquZgF7n0f1L30gEhGRRs8SFgwYUVFCQMjLQq1hd6WVX6SWpbBcM6eYlL9Pa1s6Ff1yWdrsdXf27cKi0arhcKShIWcjnKjbbj7GWrvTyzZSKWZIa7Awz2wVDLhcTqzduoz4aSVQZJTv/2L0Tacz1wqQaq+HiFBSkLCxbu5lIyl1J6a5ic/kx1sLQ0f3JlIpVkhrsDDPbBQOQ9q7n1IuJ8SOH0uWedvsvrNvc535SSx3VWg0HFXqfgvqhV5e5LWv415sW8k5Hz6u41KvYfPqRl9M5MthpGUh/+uOmjePxWUdw85dn8PisIwb96rYQff3j1V7J4u0A6ea1dzq3PvVaj2nxgNgQ7b39m554jRXrtqTdVrp7GnJdrlJVXEmhmotttSieibSn3GHUWGe9rmJzrRMvp3Mk37TkUu0y0LaBQpakCtFuka7aa+uOLpaufZuj994tbZXQlQtWcMqMCT32edy0cby1tZ0L/vhcr+VbVm3i8Pe/O6fqtWrv0FBRJQXdcVh90l11vashyjWnTe+VeebyYyzFOZKpJJBvWua2rGHmpQ/x+WufYualDzGvZU3a5co5UypE2pqbGvnxMVN6TZ9973IAzj78vb3m1UWNBc+/2etYHzx517T7mLb7zmnvoE5XvZbrcpWqooJCtRfbalG6TCTmzt5jR/RaNpcfY7HPkWwZeT5pySeA5JMp5Vp1NVhVXIXKMFu37ug1LX4sT5kxgca6nsd5a3sX589b1us7mTx6OKcdNKHHsqcdNIHJo4cDuVevHTdtHPeefTDnHzuFe88+uKpqKyqq+qicr5Ck/846bDJXLlhBQzR94+eKdVtoWbWJSc3vYmLzMG7+0gEsXbuZzq4Yb23dwYp1WxI/6mENUdq7itfDJluDYz7na77VLrn0sip2T5p41dfMyaN4fNYRg9b7qLWtnasWvNRr+vbOrsSxPPvwyVy54CXqohG2tgfVSVt39L45DeAbR76PAyY1s6GtnYMnj2Ly6OG9qu36SnM5VVEOtpIEBTM7Gvg1EAWudfdLcllP/dCrS/IPC5wzD90zUQ8c/5Fe99jLzFv8ep/bOmaf3fh/k0cxe/5yLOxlMqQ+uHoczHMkOfPoKyPP53ztzwVPtsyr2D1pBjuwpI5JFDUDevYeisWc+5e+wU/uXU40YoBx/L5jmduyNhEQAKKR7pvT0qXzqVfe4sJ7l9MQNTpjnjbtyemC3j2ekntDVXp36KIHBTOLAlcBHwVWA0+b2Tx3X57L+rXUD72apcuMrno4aByM/3BCmtf6AAAKXElEQVTd6dUAncn8pW8wf+kbPabFYs59Xz8kUYoYqNQM5cfHTOkzI8/1fB3sC55cSx6D0TBc6MCydM3bvNPR+zxorI9w/rxldMa6g8Udi1YTSXnewtb2LpaueZvxI4f2Sue3/tBCV7j6jk7Spj01XWcdNjntMbvlqdf4z4dXVHzpoRQlhQOAFe7+MoCZ/R44HsgpKEBt9EOvdpkyo2VrNyd+uAPVWBftccU4EOkyvtnzl/PjT05h9r3Ls2bkuZ6vg3nBk2vJYzCqZAsZWKaM2YnZ89NnDcEQ2d5r2hn/byI3/O3VHtNnz1/O7rsM7ZXOrjS3LiSXLNKl68oFL5H6pJ8dXTGuWvAS7Z1e8fculKKheRywKun96nCa1JBMmRF4r8bZ/hrMtoRMjcb7jB0xqP3+m5sa2TfsCTPQ7RSrJ81gBpZk9ZEILas2pT0fGqLGlw/eI+22JjUPY1jKDQnBNizraKqJtHd5j/GTUvffEI1y9uGTexyzsw+fTEO09z4rsRNM2TY0m9mZwJkAEyZM6GNpqTSZqkv2Hjsipx9uNsMao3SFdcODdZWWLeMr15JrriWPgZZQBqPqK9Pxnbb7zr2mN9RFuO9rBzNyWAPXPPpyj4fo1EXg4MmjuOT+53tta++xO/VI546uLmIeBIFk5x87JZH2TOk6ZcYETpkxoUc7w1UPr+i1XCV2gjHPcOt3wXZodhBwgbv/U/j++wDu/rNM60yfPt0XLlxYpBRKMaVrWJzXsoZz5iwBYHtHjKilL+YnixrU1wVP4dpn3IiCtDfF01XpdcaFMtDxjjId32zHfV7LGr5352KiFqHLY1x+4r59rpOczsdXbOCcOUuImtHRFeP8Y/fm1AMn5pSuXNNfSma2yN2n57VOCYJCHfAicCSwBngaOMXd0w9hiIJCLYr/cIc1BO0CwxqirH17O+CMHTGUp1e+xaJX32L0TkM4fK93U18XLUrHg2odGbNcZDq++Y6Q2tc6uayf7zL5LFcsFREUAMzsE8CvCLqkXu/uF2VbXkFBRCR//QkKJWlTcPf7gPtKsW8REcmsooa5EBGRwlJQEBGRBAUFERFJUFAQEZGEkvQ+ypeZbQFeKHU6ysQoYEOpE1EmdCy66Vh007Hotpe75zX4V9ne0ZzihXy7VVUrM1uoYxHQseimY9FNx6KbmeXdl1/VRyIikqCgICIiCZUSFH5b6gSUER2LbjoW3XQsuulYdMv7WFREQ7OIiBRHpZQURESkCBQUREQkoayDgpkdbWYvmNkKMzu31OkpNTNbaWbPmllLf7qaVTIzu97M3jSzpUnTdjGzB8zspfDvyFKmsVgyHIsLzGxNeG60hCMRVzUz293MFpjZcjNbZmbfCKfX3HmR5VjkfV6UbZuCmUUJnrvwUYJHdj4NnOzuOT/LudqY2UpgurvX3I05ZnYo0Abc5O77hNMuA95y90vCi4aR7j6rlOkshgzH4gKgzd1/Xsq0FZOZjQHGuPszZjYcWAR8CjiDGjsvshyLk8jzvCjnksIBwAp3f9nddwC/B44vcZqkRNz9EeCtlMnHAzeG/99I8COoehmORc1x99fd/Znw/y3AcwTPe6+58yLLschbOQeFccCqpPer6eeHrCIO/MXMFoXPsK51o9399fD/N4DRpUxMGTjbzJaE1UtVX2WSzMwmAfsBT1Hj50XKsYA8z4tyDgrS28Huvj/wceCssBpBAA/qQcuzLrQ4rgbeA0wDXgd+UdrkFI+ZNQFzgG+6++bkebV2XqQ5FnmfF+UcFNYAuye9Hx9Oq1nuvib8+yZwN0EVWy1bF9alxutU3yxxekrG3de5e5e7x4BrqJFzw8zqCTLBW9z9rnByTZ4X6Y5Ff86Lcg4KTwPvNbM9zKwB+Bwwr8RpKhkzGxY2IGFmw4CPAUuzr1X15gGnh/+fDswtYVpKKp4Jhj5NDZwbZmbAdcBz7n5F0qyaOy8yHYv+nBdl2/sIIOw+9SsgClzv7heVOEklY2Z7EpQOIBjd9tZaOh5mdhtwGMGwyOuA84F7gNuBCcCrwEnuXvUNsBmOxWEEVQQOrAT+LalevSqZ2cHAo8CzQCyc/AOCuvSaOi+yHIuTyfO8KOugICIixVXO1UciIlJkCgoiIpKgoCAiIgkKCiIikqCgICIiCQoKIiKSoKAgJWdm3zSzd/VjvTPMbGwfy6w0s1H9T93AmdlPzOyoIu/zMDO7t5j7lOqgoCDl4JtAXkEhHFr9DCBrUCgEC+T823H389z9fwuZJpHBoqAgRRUO1zHfzBab2VIzO58gY19gZgvCZa42s4Xhw0IuTFp3pZldambPENypOR24JXx4yNAsu/2amT0TPqDo/eG2djGze8LRI580s6nh9AvM7LtJ+1xqZpPC1wtmdhPBUAG7p+7EzKJmdkO4zrNm9q1w+g1mdmLSZ7gwTXqazOx34bQlZnZCOP1jZvZEuPwd4YBnmY7t0Wb2fHh8PpM0/YBwG/8ws7+Z2V7h9EfMbFrSco+Z2b5ZjqPUAAUFKbajgbXuvm/4gJhfAWuBw9398HCZH7r7dGAq8JF4hh1qdff93f1mYCFwqrtPc/dtWfa5IRxd9mognuFfCPzD3acSDAdwUw5pfy/wn+6+t7u/mmb+NGCcu+/j7h8EfpdHen4MvO3uHwzT9FBY7fUj4Khw+YXAt9Nt0MyGEAx4dizwIWC3pNnPA4e4+37AecDF4fTrCEpbmNn7gCHuvrivgyDVTUFBiu1Z4KPhFf8h7v52mmVOCq92/wHsDUxJmveHfuwzPnrmImBS+P/BwP8AuPtDQLOZ7dTHdl519yezzH8Z2NPMfmNmRwObMyyXLj1HAVfFF3D3jcCBBJ/9cTNrIRjcbWKGbb4feMXdXwqHi745ad4I4A4LHt/5S4JjCnAH8MlwdM0vATdk+WxSI+pKnQCpLe7+opntD3wC+KmZPZg838z2ILh6/rC7bzSzG4AhSYts7cdu28O/XfR9znfS82Ip532H6d0X+CfgKwSPQvzSANJjwAPufnIfae7LbGCBu3/aggewPBym9x0ze4DgSWUnEZQwpMappCBFFfYWeies/rkc2B/YAgwPF9mJIPN928xGEzxQKJPk9fL1KHBqmKbDCKp0NhOMJLl/OH1/YI9cNxhW90TcfQ5Btc/+eaTnAeCspG2NBJ4EZprZ5HDasLCaJ53ngUlm9p7wfXIgGUH3s0jOSFnvWuA/gKfD0onUOJUUpNg+CFxuZjGgA/gqcBBwv5mtdffDzewfBJncKuDxLNu6AfgvM9sGHNRHu0KqC4DrzWwJ8A7d4+/PAU4zs2UEQzC/mMc2xwG/S+qZ9P081v0pcFVYxdMFXOjud5nZGcBtZtYYLvejdGly9+0WPKJ1vpm9QxD04gHzMuBGM/sRMD9lvUVmtpnM7R9SYzR0tkgNC0tuDwPvD5/OJTVO1UciNcrMTiMoDf1QAUHiVFKQqmBmd9O7/n+Wu/+5QPt7CmhMmfwFd3+2EPtL2XdRP6vUFgUFERFJUPWRiIgkKCiIiEiCgoKIiCQoKIiISML/B5eGeWMEI1CKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d5e1f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = generated_traces_df[generated_traces_df['start_hour_since_day'] != 0].plot.scatter(\n",
    "    x='start_hour_since_day',\n",
    "    y='duration')\n",
    "_ = plt.title('Generated Start Time vs. Duration')\n",
    "_ =plt.xlim(0, 25)\n",
    "\n",
    "_ = dataframe[dataframe['start_hour_since_day'] != 0].plot.scatter(\n",
    "    x='start_hour_since_day',\n",
    "    y='duration')\n",
    "_ = plt.title('Observed Start Time vs. Duration')\n",
    "_ = plt.xlim(0, 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d685860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d37e0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = generated_traces_df[generated_traces_df['start_hour_since_day'] != 0].plot.scatter(\n",
    "    x='lon',\n",
    "    y='lat')\n",
    "_ = plt.title('Generated Lat Lon')\n",
    "\n",
    "_ = dataframe[dataframe['start_hour_since_day'] != 0].plot.scatter(\n",
    "    x='lon',\n",
    "    y='lat')\n",
    "_ = plt.title('Observed Lat Lon')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "model3",
   "language": "python",
   "name": "model3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}