Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "72f56ad3",
   "metadata": {},
   "source": [
    "## Importing the Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a6e3626e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import cv2\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0350b163",
   "metadata": {},
   "source": [
    "## Getting the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9cc01e6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "seq_hotel = \"datasets/ewap_dataset/seq_hotel\"\n",
    "seq_eth   = \"datasets/ewap_dataset/seq_eth\"\n",
    "\n",
    "hotel_obsmat = seq_hotel + \"/obsmat.txt\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3d391145",
   "metadata": {},
   "outputs": [],
   "source": [
    "f_obsmat = open(hotel_obsmat,\"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f8bca9a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6544"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f_obsmat.seek(0)\n",
    "len(f_obsmat.readlines())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc844f4c",
   "metadata": {},
   "source": [
    "The actual annotation is stored in the obsmat.txt file. Each line has this format\n",
    "\n",
    "*[frame_number pedestrian_ID pos_x pos_z pos_y v_x v_z v_y ]*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "257e542f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_obsmat = pd.read_csv(hotel_obsmat, delimiter=r\"\\s+\", header = None)\n",
    "df_obsmat.columns = [\"frame_number\", \"pedestrian_ID\", \"pos_x\", \"pos_z\", \"pos_y\", \"v_x\", \"v_z\", \"v_y\"]\n",
    "df_obsmat = df_obsmat.drop([\"pos_z\", \"v_z\"], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b5790da0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-0.65218834,\n",
       " -0.43194664,\n",
       " -0.27115282,\n",
       " -0.072714103,\n",
       " 0.065694252,\n",
       " 0.16238537,\n",
       " 0.27899983,\n",
       " 0.26068875,\n",
       " 0.30032937,\n",
       " 0.26308032,\n",
       " 0.26370402,\n",
       " 0.30107617,\n",
       " 0.2592225,\n",
       " 0.3511434,\n",
       " 0.36728377,\n",
       " 0.42126177,\n",
       " 0.51411648,\n",
       " 0.54798662,\n",
       " 0.67720055,\n",
       " 0.71214431,\n",
       " 0.80459493,\n",
       " 0.89691052,\n",
       " 0.87550639,\n",
       " 0.94675676,\n",
       " 0.92424993,\n",
       " 0.9767384,\n",
       " 0.99398095,\n",
       " 0.97261657,\n",
       " 1.0835117,\n",
       " 1.1392725,\n",
       " 1.2334458]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pedestrian = df_obsmat[df_obsmat.pedestrian_ID == 25]\n",
    "list(pedestrian.pos_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "07f7bb5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1168"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_obsmat.frame_number.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "760e16d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.head of       frame_number  pedestrian_ID     pos_x     pos_y       v_x       v_y\n",
       "0              1.0            1.0  1.398378 -5.743303 -0.327083 -1.680286\n",
       "1              1.0            2.0  0.517796 -7.003832  0.097997 -1.629874\n",
       "2              1.0            3.0  2.259814 -4.546597 -0.901111  1.187025\n",
       "3              1.0            4.0  2.740179 -2.423851  0.053061  1.815625\n",
       "4              1.0            5.0 -1.585502  0.927584  0.000000  0.000000\n",
       "...            ...            ...       ...       ...       ...       ...\n",
       "6539       18051.0          420.0  3.617401 -6.192644  0.014910  1.543804\n",
       "6540       18061.0          416.0  1.132991 -8.158643 -0.034447 -1.460363\n",
       "6541       18061.0          417.0  2.695246 -8.296147  0.194425 -1.452633\n",
       "6542       18061.0          419.0  3.353155 -1.422939  0.002049  1.712019\n",
       "6543       18061.0          420.0  3.615008 -5.564871 -0.005983  1.569430\n",
       "\n",
       "[6544 rows x 6 columns]>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_obsmat.head"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ee8f3d3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[36,\n",
       " 37,\n",
       " 38,\n",
       " 39,\n",
       " 40,\n",
       " 82,\n",
       " 83,\n",
       " 84,\n",
       " 85,\n",
       " 86,\n",
       " 207,\n",
       " 208,\n",
       " 209,\n",
       " 225,\n",
       " 226,\n",
       " 227,\n",
       " 228,\n",
       " 229,\n",
       " 236,\n",
       " 237,\n",
       " 238,\n",
       " 239,\n",
       " 240,\n",
       " 241,\n",
       " 242,\n",
       " 243,\n",
       " 244,\n",
       " 245,\n",
       " 246,\n",
       " 247,\n",
       " 248,\n",
       " 249,\n",
       " 250,\n",
       " 251,\n",
       " 252,\n",
       " 253,\n",
       " 254,\n",
       " 255,\n",
       " 256,\n",
       " 257,\n",
       " 258,\n",
       " 259,\n",
       " 260,\n",
       " 261,\n",
       " 262,\n",
       " 263,\n",
       " 264,\n",
       " 265,\n",
       " 266,\n",
       " 267,\n",
       " 268,\n",
       " 269,\n",
       " 270,\n",
       " 271,\n",
       " 272,\n",
       " 273,\n",
       " 274,\n",
       " 275,\n",
       " 276,\n",
       " 299,\n",
       " 300,\n",
       " 301,\n",
       " 302,\n",
       " 303,\n",
       " 304,\n",
       " 305,\n",
       " 306,\n",
       " 307,\n",
       " 308,\n",
       " 309,\n",
       " 331,\n",
       " 332,\n",
       " 333,\n",
       " 334,\n",
       " 335,\n",
       " 336,\n",
       " 337,\n",
       " 338,\n",
       " 339,\n",
       " 340,\n",
       " 359,\n",
       " 360,\n",
       " 361,\n",
       " 362,\n",
       " 363,\n",
       " 364,\n",
       " 365,\n",
       " 366,\n",
       " 367,\n",
       " 368,\n",
       " 369,\n",
       " 370,\n",
       " 371,\n",
       " 372,\n",
       " 373,\n",
       " 374,\n",
       " 375,\n",
       " 376,\n",
       " 377,\n",
       " 378,\n",
       " 379,\n",
       " 380,\n",
       " 381,\n",
       " 382,\n",
       " 383,\n",
       " 384,\n",
       " 385,\n",
       " 386,\n",
       " 387,\n",
       " 388,\n",
       " 389,\n",
       " 390,\n",
       " 391,\n",
       " 392,\n",
       " 393,\n",
       " 394,\n",
       " 395,\n",
       " 396,\n",
       " 397,\n",
       " 398,\n",
       " 399,\n",
       " 427,\n",
       " 428,\n",
       " 429,\n",
       " 430,\n",
       " 431,\n",
       " 432,\n",
       " 433,\n",
       " 434,\n",
       " 435,\n",
       " 436,\n",
       " 437,\n",
       " 438,\n",
       " 439,\n",
       " 440,\n",
       " 441,\n",
       " 442,\n",
       " 502,\n",
       " 503,\n",
       " 504,\n",
       " 505,\n",
       " 506,\n",
       " 507,\n",
       " 508,\n",
       " 509,\n",
       " 510,\n",
       " 511,\n",
       " 512,\n",
       " 513,\n",
       " 514,\n",
       " 515,\n",
       " 516,\n",
       " 517,\n",
       " 518,\n",
       " 519,\n",
       " 520,\n",
       " 521,\n",
       " 522,\n",
       " 523,\n",
       " 538,\n",
       " 539,\n",
       " 540,\n",
       " 541,\n",
       " 542,\n",
       " 543,\n",
       " 544,\n",
       " 545,\n",
       " 546,\n",
       " 547,\n",
       " 548,\n",
       " 549,\n",
       " 550,\n",
       " 551,\n",
       " 552,\n",
       " 553,\n",
       " 554,\n",
       " 555,\n",
       " 556,\n",
       " 557,\n",
       " 558,\n",
       " 559,\n",
       " 560,\n",
       " 561,\n",
       " 562,\n",
       " 563,\n",
       " 564,\n",
       " 565,\n",
       " 566,\n",
       " 567,\n",
       " 591,\n",
       " 592,\n",
       " 593,\n",
       " 594,\n",
       " 595,\n",
       " 596,\n",
       " 597,\n",
       " 598,\n",
       " 599,\n",
       " 600,\n",
       " 601,\n",
       " 602,\n",
       " 603,\n",
       " 604,\n",
       " 605,\n",
       " 606,\n",
       " 607,\n",
       " 608,\n",
       " 609,\n",
       " 610,\n",
       " 611,\n",
       " 612,\n",
       " 613,\n",
       " 614,\n",
       " 615,\n",
       " 616,\n",
       " 617,\n",
       " 618,\n",
       " 619,\n",
       " 620,\n",
       " 621,\n",
       " 622,\n",
       " 623,\n",
       " 624,\n",
       " 625,\n",
       " 626,\n",
       " 627,\n",
       " 628,\n",
       " 629,\n",
       " 630,\n",
       " 631,\n",
       " 645,\n",
       " 646,\n",
       " 647,\n",
       " 648,\n",
       " 649,\n",
       " 650,\n",
       " 651,\n",
       " 652,\n",
       " 653,\n",
       " 654,\n",
       " 655,\n",
       " 656,\n",
       " 657,\n",
       " 658,\n",
       " 659,\n",
       " 660,\n",
       " 661,\n",
       " 662,\n",
       " 663,\n",
       " 664,\n",
       " 665,\n",
       " 666,\n",
       " 667,\n",
       " 738,\n",
       " 739,\n",
       " 740,\n",
       " 741,\n",
       " 742,\n",
       " 743,\n",
       " 744,\n",
       " 745,\n",
       " 746,\n",
       " 747,\n",
       " 768,\n",
       " 769,\n",
       " 770,\n",
       " 771,\n",
       " 772,\n",
       " 773,\n",
       " 774,\n",
       " 775,\n",
       " 776,\n",
       " 777,\n",
       " 778,\n",
       " 779,\n",
       " 780,\n",
       " 781,\n",
       " 782,\n",
       " 783,\n",
       " 784,\n",
       " 785,\n",
       " 786,\n",
       " 787,\n",
       " 788,\n",
       " 789,\n",
       " 790,\n",
       " 791,\n",
       " 792,\n",
       " 793,\n",
       " 794,\n",
       " 795,\n",
       " 796,\n",
       " 797,\n",
       " 798,\n",
       " 799,\n",
       " 800,\n",
       " 801,\n",
       " 802,\n",
       " 803,\n",
       " 804,\n",
       " 816,\n",
       " 817,\n",
       " 818,\n",
       " 819,\n",
       " 820,\n",
       " 821,\n",
       " 822,\n",
       " 823,\n",
       " 824,\n",
       " 825,\n",
       " 826,\n",
       " 827,\n",
       " 828,\n",
       " 829,\n",
       " 830,\n",
       " 831,\n",
       " 832,\n",
       " 833,\n",
       " 834,\n",
       " 835,\n",
       " 836,\n",
       " 837,\n",
       " 838,\n",
       " 839,\n",
       " 840,\n",
       " 841,\n",
       " 842,\n",
       " 843,\n",
       " 844,\n",
       " 845,\n",
       " 846,\n",
       " 847,\n",
       " 848,\n",
       " 849,\n",
       " 850,\n",
       " 851,\n",
       " 852,\n",
       " 853,\n",
       " 854,\n",
       " 855,\n",
       " 856,\n",
       " 857,\n",
       " 858,\n",
       " 859,\n",
       " 860,\n",
       " 861,\n",
       " 862,\n",
       " 863,\n",
       " 864,\n",
       " 865,\n",
       " 866,\n",
       " 867,\n",
       " 868,\n",
       " 869,\n",
       " 870,\n",
       " 871,\n",
       " 872,\n",
       " 873,\n",
       " 874,\n",
       " 875,\n",
       " 876,\n",
       " 877,\n",
       " 878,\n",
       " 879,\n",
       " 880,\n",
       " 881,\n",
       " 882,\n",
       " 883,\n",
       " 884,\n",
       " 885,\n",
       " 886,\n",
       " 887,\n",
       " 888,\n",
       " 889,\n",
       " 890,\n",
       " 891,\n",
       " 892,\n",
       " 893,\n",
       " 894,\n",
       " 895,\n",
       " 896,\n",
       " 897,\n",
       " 898,\n",
       " 899,\n",
       " 900,\n",
       " 901,\n",
       " 902,\n",
       " 903,\n",
       " 904,\n",
       " 905,\n",
       " 906,\n",
       " 907,\n",
       " 908,\n",
       " 909,\n",
       " 910,\n",
       " 911,\n",
       " 912,\n",
       " 913,\n",
       " 914,\n",
       " 915,\n",
       " 916,\n",
       " 917,\n",
       " 918,\n",
       " 919,\n",
       " 920,\n",
       " 921,\n",
       " 922,\n",
       " 923,\n",
       " 924,\n",
       " 925,\n",
       " 1155,\n",
       " 1156,\n",
       " 1157,\n",
       " 1158,\n",
       " 1159,\n",
       " 1160,\n",
       " 1175,\n",
       " 1176,\n",
       " 1200,\n",
       " 1201,\n",
       " 1202,\n",
       " 1203,\n",
       " 1204,\n",
       " 1205,\n",
       " 1206,\n",
       " 1207,\n",
       " 1208,\n",
       " 1209,\n",
       " 1210,\n",
       " 1211,\n",
       " 1212,\n",
       " 1213,\n",
       " 1214,\n",
       " 1215,\n",
       " 1216,\n",
       " 1217,\n",
       " 1218,\n",
       " 1219,\n",
       " 1220,\n",
       " 1221,\n",
       " 1222,\n",
       " 1223,\n",
       " 1224,\n",
       " 1225,\n",
       " 1226,\n",
       " 1227,\n",
       " 1228,\n",
       " 1229,\n",
       " 1230,\n",
       " 1231,\n",
       " 1232,\n",
       " 1233,\n",
       " 1234,\n",
       " 1235,\n",
       " 1236,\n",
       " 1237,\n",
       " 1238,\n",
       " 1239,\n",
       " 1240,\n",
       " 1241,\n",
       " 1242,\n",
       " 1243,\n",
       " 1360,\n",
       " 1361,\n",
       " 1362,\n",
       " 1363,\n",
       " 1364,\n",
       " 1365,\n",
       " 1366,\n",
       " 1367,\n",
       " 1368,\n",
       " 1369,\n",
       " 1370,\n",
       " 1371,\n",
       " 1372,\n",
       " 1389,\n",
       " 1390,\n",
       " 1391,\n",
       " 1392,\n",
       " 1393,\n",
       " 1394,\n",
       " 1395,\n",
       " 1396,\n",
       " 1397,\n",
       " 1398,\n",
       " 1399,\n",
       " 1400,\n",
       " 1401,\n",
       " 1402,\n",
       " 1403,\n",
       " 1404,\n",
       " 1405,\n",
       " 1406,\n",
       " 1407,\n",
       " 1408,\n",
       " 1409,\n",
       " 1410,\n",
       " 1411,\n",
       " 1412,\n",
       " 1413,\n",
       " 1414,\n",
       " 1415,\n",
       " 1430,\n",
       " 1431,\n",
       " 1432,\n",
       " 1433,\n",
       " 1461,\n",
       " 1462,\n",
       " 1463,\n",
       " 1464,\n",
       " 1465,\n",
       " 1466,\n",
       " 1467,\n",
       " 1468,\n",
       " 1469,\n",
       " 1470,\n",
       " 1471,\n",
       " 1472,\n",
       " 1473,\n",
       " 1474,\n",
       " 1475,\n",
       " 1476,\n",
       " 1477,\n",
       " 1478,\n",
       " 1479,\n",
       " 1526,\n",
       " 1527,\n",
       " 1528,\n",
       " 1529,\n",
       " 1530,\n",
       " 1531,\n",
       " 1532,\n",
       " 1533,\n",
       " 1534,\n",
       " 1535,\n",
       " 1536,\n",
       " 1537,\n",
       " 1538,\n",
       " 1539,\n",
       " 1540,\n",
       " 1541,\n",
       " 1542,\n",
       " 1543,\n",
       " 1544,\n",
       " 1545,\n",
       " 1546,\n",
       " 1547,\n",
       " 1548,\n",
       " 1549,\n",
       " 1550,\n",
       " 1551,\n",
       " 1552,\n",
       " 1553,\n",
       " 1554,\n",
       " 1555,\n",
       " 1556,\n",
       " 1557,\n",
       " 1558,\n",
       " 1559,\n",
       " 1560,\n",
       " 1561,\n",
       " 1562,\n",
       " 1563,\n",
       " 1564,\n",
       " 1565,\n",
       " 1566,\n",
       " 1567,\n",
       " 1568,\n",
       " 1569,\n",
       " 1570,\n",
       " 1571,\n",
       " 1572,\n",
       " 1573,\n",
       " 1574,\n",
       " 1575,\n",
       " 1576,\n",
       " 1577,\n",
       " 1578,\n",
       " 1579,\n",
       " 1580,\n",
       " 1689,\n",
       " 1690,\n",
       " 1691,\n",
       " 1692,\n",
       " 1693,\n",
       " 1694,\n",
       " 1695,\n",
       " 1696,\n",
       " 1697,\n",
       " 1698,\n",
       " 1699,\n",
       " 1700,\n",
       " 1701,\n",
       " 1702,\n",
       " 1703,\n",
       " 1704,\n",
       " 1705,\n",
       " 1706,\n",
       " 1707,\n",
       " 1708,\n",
       " 1709,\n",
       " 1710,\n",
       " 1711,\n",
       " 1712,\n",
       " 1713,\n",
       " 1714,\n",
       " 1715,\n",
       " 1716,\n",
       " 1717,\n",
       " 1718,\n",
       " 1719,\n",
       " 1720,\n",
       " 1721,\n",
       " 1722,\n",
       " 1723,\n",
       " 1724,\n",
       " 1725,\n",
       " 1733,\n",
       " 1734,\n",
       " 1735,\n",
       " 1736,\n",
       " 1737,\n",
       " 1738,\n",
       " 1739,\n",
       " 1740,\n",
       " 1741,\n",
       " 1742,\n",
       " 1743,\n",
       " 1744,\n",
       " 1745,\n",
       " 1746,\n",
       " 1747,\n",
       " 1748,\n",
       " 1749,\n",
       " 1750,\n",
       " 1751,\n",
       " 1752,\n",
       " 1753,\n",
       " 1754]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing = []\n",
    "prev = -1\n",
    "for x in df_obsmat.frame_number.unique():\n",
    "    x -= 1\n",
    "    x = int(x/10)\n",
    "    if x != prev + 1:\n",
    "        for i in range(prev+1, x):\n",
    "            missing.append(i)\n",
    "            \n",
    "    prev = x\n",
    "            \n",
    "missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "eb368005",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(df_obsmat)):\n",
    "    df_obsmat.iloc[i,0] -= 1\n",
    "    df_obsmat.iloc[i,0] = int(df_obsmat.iloc[i,0]/10)\n",
    "#     print(df_obsmat.iloc[i,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f1fc39d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_obsmat = df_obsmat.astype({'frame_number': int, 'pedestrian_ID' : int})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "96a39530",
   "metadata": {
    "scrolled": true
   },
   "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>frame_number</th>\n",
       "      <th>pedestrian_ID</th>\n",
       "      <th>pos_x</th>\n",
       "      <th>pos_y</th>\n",
       "      <th>v_x</th>\n",
       "      <th>v_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.398378</td>\n",
       "      <td>-5.743303</td>\n",
       "      <td>-0.327083</td>\n",
       "      <td>-1.680286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.517796</td>\n",
       "      <td>-7.003832</td>\n",
       "      <td>0.097997</td>\n",
       "      <td>-1.629874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.259814</td>\n",
       "      <td>-4.546597</td>\n",
       "      <td>-0.901111</td>\n",
       "      <td>1.187025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2.740179</td>\n",
       "      <td>-2.423851</td>\n",
       "      <td>0.053061</td>\n",
       "      <td>1.815625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>-1.585502</td>\n",
       "      <td>0.927584</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6539</th>\n",
       "      <td>1805</td>\n",
       "      <td>420</td>\n",
       "      <td>3.617401</td>\n",
       "      <td>-6.192644</td>\n",
       "      <td>0.014910</td>\n",
       "      <td>1.543804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6540</th>\n",
       "      <td>1806</td>\n",
       "      <td>416</td>\n",
       "      <td>1.132991</td>\n",
       "      <td>-8.158643</td>\n",
       "      <td>-0.034447</td>\n",
       "      <td>-1.460363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6541</th>\n",
       "      <td>1806</td>\n",
       "      <td>417</td>\n",
       "      <td>2.695246</td>\n",
       "      <td>-8.296147</td>\n",
       "      <td>0.194425</td>\n",
       "      <td>-1.452633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6542</th>\n",
       "      <td>1806</td>\n",
       "      <td>419</td>\n",
       "      <td>3.353155</td>\n",
       "      <td>-1.422939</td>\n",
       "      <td>0.002049</td>\n",
       "      <td>1.712019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6543</th>\n",
       "      <td>1806</td>\n",
       "      <td>420</td>\n",
       "      <td>3.615008</td>\n",
       "      <td>-5.564871</td>\n",
       "      <td>-0.005983</td>\n",
       "      <td>1.569430</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6544 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      frame_number  pedestrian_ID     pos_x     pos_y       v_x       v_y\n",
       "0                0              1  1.398378 -5.743303 -0.327083 -1.680286\n",
       "1                0              2  0.517796 -7.003832  0.097997 -1.629874\n",
       "2                0              3  2.259814 -4.546597 -0.901111  1.187025\n",
       "3                0              4  2.740179 -2.423851  0.053061  1.815625\n",
       "4                0              5 -1.585502  0.927584  0.000000  0.000000\n",
       "...            ...            ...       ...       ...       ...       ...\n",
       "6539          1805            420  3.617401 -6.192644  0.014910  1.543804\n",
       "6540          1806            416  1.132991 -8.158643 -0.034447 -1.460363\n",
       "6541          1806            417  2.695246 -8.296147  0.194425 -1.452633\n",
       "6542          1806            419  3.353155 -1.422939  0.002049  1.712019\n",
       "6543          1806            420  3.615008 -5.564871 -0.005983  1.569430\n",
       "\n",
       "[6544 rows x 6 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_obsmat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "70f7a36f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_obsmat.to_csv(\"datasets/ewap_dataset/obsmat_hotel.csv\")"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f0b58e7c30d35075fa2d9a6cac586973685553f3fa1d9d8f126c6f6f5c7ee6b3"
  },
  "kernelspec": {
   "display_name": "Python 3.9.12 ('tensorflow-gpu')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}