eyn-pre-unravel-df.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['train_data.npy', 'trn_index_list.npy', 'custom.css', 'val_index_list.npy', '__results__.html', 'train_targets_inside.npy', 'submission.csv', 'train_targets.npy', 'test_ids.npy', '__output__.json', 'test_data.npy', '__notebook__.ipynb']\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from tqdm import tqdm\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt\n",
    "pd.set_option('display.float_format', '{:.2f}'.format)\n",
    "print(os.listdir(\"../input/eyn-original\"))\n",
    "x_min, x_max = -1., 1.\n",
    "y_min, y_max = -.3, .3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2815323, 11) (703815, 11)\n"
     ]
    },
    {
     "data": {
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       "      <th>y_exit</th>\n",
       "      <th>vmax</th>\n",
       "      <th>vmin</th>\n",
       "      <th>vmean</th>\n",
       "      <th>tid_0</th>\n",
       "      <th>tid_1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seq</th>\n",
       "      <th>traj</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.67</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry  y_entry  ...    vmin  vmean  tid_0  tid_1\n",
       "seq traj                                     ...                             \n",
       "0   0        0.00    0.03    -1.60    -0.43  ...     nan    nan   5.00   1.00\n",
       "    1       -0.04   -0.04    -1.60    -0.47  ...     nan    nan   4.00   1.00\n",
       "    2       -0.67   -0.64    -1.60    -0.53  ...     nan    nan   3.00   1.00\n",
       "    3       -0.71   -0.69    -1.60    -0.55  ...     nan    nan   2.00   1.00\n",
       "    4       -0.77   -0.76    -1.70    -0.84  ...     nan    nan   1.00   1.00\n",
       "\n",
       "[5 rows x 11 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = pd.read_pickle(\"../input/eyn-original-df/df_train.pickle\")\n",
    "df_test = pd.read_pickle(\"../input/eyn-original-df/df_test.pickle\")\n",
    "print(df_train.shape, df_test.shape)\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>vmean</th>\n",
       "      <th>tid_0</th>\n",
       "      <th>tid_1</th>\n",
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       "      <th>seq</th>\n",
       "      <th>traj</th>\n",
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       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
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       "      <td>0.00</td>\n",
       "      <td>nan</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.67</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry   ...     tid_1  entry_in  exit_in\n",
       "seq traj                             ...                             \n",
       "0   0        0.00    0.03    -1.60   ...      1.00      0.00      nan\n",
       "    1       -0.04   -0.04    -1.60   ...      1.00      0.00     0.00\n",
       "    2       -0.67   -0.64    -1.60   ...      1.00      0.00     0.00\n",
       "    3       -0.71   -0.69    -1.60   ...      1.00      0.00     0.00\n",
       "    4       -0.77   -0.76    -1.70   ...      1.00      0.00     0.00\n",
       "\n",
       "[5 rows x 13 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def is_inside(arr_x, arr_y):\n",
    "    inside = ((arr_x > x_min) & \n",
    "             (arr_x < x_max) & \n",
    "             (arr_y > y_min) & \n",
    "             (arr_y < y_max)).astype(float)\n",
    "    inside[np.isnan(arr_x)] = np.nan  # replace nan position with nan judgement\n",
    "    return inside\n",
    "\n",
    "df_train['entry_in'] = is_inside(df_train['x_entry'], df_train['y_entry'])\n",
    "df_train['exit_in'] = is_inside(df_train['x_exit'], df_train['y_exit'])\n",
    "df_test['entry_in'] = is_inside(df_test['x_entry'], df_test['y_entry'])\n",
    "df_test['exit_in'] = is_inside(df_test['x_exit'], df_test['y_exit'])\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>tid_1</th>\n",
       "      <th>entry_in</th>\n",
       "      <th>exit_in</th>\n",
       "      <th>dur</th>\n",
       "      <th>dur_a</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seq</th>\n",
       "      <th>traj</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.94</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>5.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.94</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>4.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.24</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.09</td>\n",
       "      <td>1.28</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.26</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>1.23</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.23</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.33</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.41</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.94</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry  ...    exit_in  dur  dur_a\n",
       "seq traj                            ...                       \n",
       "0   0        0.01    0.02     1.22  ...        nan 0.01   0.13\n",
       "    1       -0.16   -0.13     1.25  ...       0.00 0.03   0.02\n",
       "    2       -0.24   -0.18     0.29  ...       0.00 0.07   0.02\n",
       "    3       -0.26   -0.26     1.23  ...       0.00 0.00   0.05\n",
       "    4       -0.33   -0.32     1.25  ...       0.00 0.01    nan\n",
       "\n",
       "[5 rows x 15 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def calc_diff_alt(arr_entry, arr_exit):\n",
    "    return np.append(np.array(arr_entry)[:-1] - np.array(arr_exit)[1:], np.nan)\n",
    "\n",
    "df_train['dur'] = df_train['t_exit'] - df_train['t_entry']\n",
    "df_test['dur'] = df_test['t_exit'] - df_test['t_entry']\n",
    "df_train['dur_a'] = calc_diff_alt(df_train['t_entry'], df_train['t_exit'])\n",
    "df_test['dur_a'] = calc_diff_alt(df_test['t_entry'], df_test['t_exit'])\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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></th>\n",
       "      <th>t_entry</th>\n",
       "      <th>t_exit</th>\n",
       "      <th>x_entry</th>\n",
       "      <th>y_entry</th>\n",
       "      <th>x_exit</th>\n",
       "      <th>y_exit</th>\n",
       "      <th>vmax</th>\n",
       "      <th>vmin</th>\n",
       "      <th>vmean</th>\n",
       "      <th>tid_0</th>\n",
       "      <th>tid_1</th>\n",
       "      <th>entry_in</th>\n",
       "      <th>exit_in</th>\n",
       "      <th>dur</th>\n",
       "      <th>dur_a</th>\n",
       "      <th>dist</th>\n",
       "      <th>dist_a</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seq</th>\n",
       "      <th>traj</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.04</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.67</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry  y_entry   ...    dur  dur_a  dist  dist_a\n",
       "seq traj                                      ...                            \n",
       "0   0        0.00    0.03    -1.60    -0.43   ...   0.03   0.04   nan    0.04\n",
       "    1       -0.04   -0.04    -1.60    -0.47   ...   0.00   0.60  0.00    0.05\n",
       "    2       -0.67   -0.64    -1.60    -0.53   ...   0.03   0.02  0.02    0.01\n",
       "    3       -0.71   -0.69    -1.60    -0.55   ...   0.02   0.05  0.01    0.26\n",
       "    4       -0.77   -0.76    -1.70    -0.84   ...   0.01   0.02  0.11    1.97\n",
       "\n",
       "[5 rows x 17 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def calc_dist(x1, x2, y1, y2):\n",
    "    x1, x2, y1, y2 = [np.array(arr) for arr in [x1, x2, y1, y2]]\n",
    "    return np.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2)\n",
    "    \n",
    "df_train['dist'] = calc_dist(df_train['x_entry'], df_train['x_exit'], df_train['y_entry'], df_train['y_exit'])\n",
    "df_test['dist'] = calc_dist(df_test['x_entry'], df_test['x_exit'], df_test['y_entry'], df_test['y_exit'])\n",
    "df_train['dist_a'] = np.append(calc_dist(df_train['x_entry'][:-1], df_train['x_exit'][1:], \n",
    "                                         df_train['y_entry'][:-1], df_train['y_exit'][1:]),np.nan)\n",
    "df_test['dist_a'] = np.append(calc_dist(df_test['x_entry'][:-1], df_test['x_exit'][1:], \n",
    "                                        df_test['y_entry'][:-1], df_test['y_exit'][1:]),np.nan)\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>nan</td>\n",
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       "      <td>nan</td>\n",
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       "      <td>0.04</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.04</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.93</td>\n",
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       "      <td>-1.60</td>\n",
       "      <td>-0.47</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
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       "      <td>1.00</td>\n",
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       "      <td>0.00</td>\n",
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       "      <td>0.00</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.67</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
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       "      <td>0.01</td>\n",
       "      <td>0.60</td>\n",
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       "      <th>3</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.54</td>\n",
       "      <td>5.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
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       "      <td>1.97</td>\n",
       "      <td>12.56</td>\n",
       "      <td>98.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry   ...     dist_a  speed  speed_a\n",
       "seq traj                             ...                           \n",
       "0   0        0.00    0.03    -1.60   ...       0.04    nan     0.93\n",
       "    1       -0.04   -0.04    -1.60   ...       0.05   0.00     0.08\n",
       "    2       -0.67   -0.64    -1.60   ...       0.01   0.60     0.35\n",
       "    3       -0.71   -0.69    -1.60   ...       0.26   0.54     5.63\n",
       "    4       -0.77   -0.76    -1.70   ...       1.97  12.56    98.12\n",
       "\n",
       "[5 rows x 19 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def nan_divide(numerator, denominator):\n",
    "    result = np.divide(numerator, denominator, \n",
    "                       out=np.zeros_like(denominator), where=denominator!=0)\n",
    "    result[np.isnan(numerator)] = np.nan\n",
    "    return result\n",
    "\n",
    "df_train['speed'] = nan_divide(df_train['dist'], df_train['dur'])\n",
    "df_test['speed']= nan_divide(df_test['dist'], df_test['dur'])\n",
    "df_train['speed_a'] = nan_divide(df_train['dist_a'], df_train['dur_a'])\n",
    "df_test['speed_a'] = nan_divide(df_test['dist_a'], df_test['dur_a'])\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>-0.47</td>\n",
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       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.60</td>\n",
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       "      <td>0.08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.98</td>\n",
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       "      <th>2</th>\n",
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       "      <td>-0.53</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.52</td>\n",
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       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
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       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.35</td>\n",
       "      <td>-0.37</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.61</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.54</td>\n",
       "      <td>5.63</td>\n",
       "      <td>-0.59</td>\n",
       "      <td>0.81</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>-1.59</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.97</td>\n",
       "      <td>12.56</td>\n",
       "      <td>98.12</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.26</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-0.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          t_entry  t_exit  x_entry   ...     dir_y  dir_x_a  dir_y_a\n",
       "seq traj                             ...                            \n",
       "0   0        0.00    0.03    -1.60   ...       nan     0.09     1.00\n",
       "    1       -0.04   -0.04    -1.60   ...      0.00     0.20     0.98\n",
       "    2       -0.67   -0.64    -1.60   ...      0.93     0.76     0.65\n",
       "    3       -0.71   -0.69    -1.60   ...      0.81    -0.04     1.00\n",
       "    4       -0.77   -0.76    -1.70   ...      0.26    -0.32    -0.95\n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train['dir_x'] = nan_divide(df_train['x_exit'] - df_train['x_entry'], df_train['dist'])\n",
    "df_train['dir_y'] = nan_divide(df_train['y_exit'] - df_train['y_entry'], df_train['dist'])\n",
    "df_test['dir_x'] = nan_divide(df_test['x_exit'] - df_test['x_entry'], df_test['dist'])\n",
    "df_test['dir_y'] = nan_divide(df_test['y_exit'] - df_test['y_entry'], df_test['dist'])\n",
    "df_train['dir_x_a'] = nan_divide(calc_diff_alt(df_train['x_entry'], df_train['x_exit']), df_train['dist_a'])\n",
    "df_train['dir_y_a'] = nan_divide(calc_diff_alt(df_train['y_entry'], df_train['y_exit']), df_train['dist_a'])\n",
    "df_test['dir_x_a'] = nan_divide(calc_diff_alt(df_test['x_entry'], df_test['x_exit']), df_test['dist_a'])\n",
    "df_test['dir_y_a'] = nan_divide(calc_diff_alt(df_test['y_entry'], df_test['y_exit']), df_test['dist_a'])\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.to_pickle(\"df_train.pickle\")\n",
    "df_test.to_pickle(\"df_test.pickle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2815323, 23) (703815, 23)\n"
     ]
    }
   ],
   "source": [
    "# to load\n",
    "df_train = pd.read_pickle(\"df_train.pickle\")\n",
    "df_test = pd.read_pickle(\"df_test.pickle\")\n",
    "print(df_train.shape, df_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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