playground/dtw_modelling_data_experiments.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DTW Data generation and visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0,'..')\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from generate_segment_trajectories import GenerateSegmentTrajectories, get_agent_ids,get_max_frame_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dtw import dtw\n",
    "\n",
    "# Here, we use L2 norm as the element comparison distance\n",
    "l2_norm = lambda x, y: np.linalg.norm((x - y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO\n",
    "# for each round, get all agent IDs\n",
    "# for each agent ID, get the segment trajectories of FRAME_LENGTH duration, for simplicity take N random durations or TotalLength%Frame_length(ie. zero overlap) - possibly optimize this to choose \"interesting\" segments, ie the ones which have multiple vehicles interacting\n",
    "# for each agent_segment, generate a set of DTW maps\n",
    "# the DTW maps will be W,H,* where * will vary across different cases, pad the * to be a max of 10, hence we have a W,H,10 tensor for each scenario. \n",
    "#    due to dtw, W = H = Frame duration\n",
    "\n",
    "def get_dtw_maps():\n",
    "    FRAME_LENGTH = 25 # how long should one unit of the scenario be/ what duration is enough to identify an anomaly\n",
    "    RADIUS = 15 # how far should we look\n",
    "    rounds = [0]\n",
    "    max_channels = 10\n",
    "    agent_map_folder=\"../agent_maps\"\n",
    "\n",
    "    dtw_result = []\n",
    "    for round_id in rounds:\n",
    "        # Todo: add logic to pick agents that are present for the longest time (currently all agents are present always)\n",
    "        # also possibly sample agents? maybe we dont need all agents?\n",
    "        agent_ids = get_agent_ids(agent_map_folder,round_number=round_id)\n",
    "        max_frame = get_max_frame_value(agent_map_folder,round_number=round_id)\n",
    "        for agent_id in agent_ids:\n",
    "            # the below range function samples all non overlapping segments in the recording, can have some smart sampling here\n",
    "            for start_index in range(0,max_frame,FRAME_LENGTH):\n",
    "                dtw_maps = []\n",
    "                if start_index+FRAME_LENGTH>max_frame:\n",
    "                    continue\n",
    "                gen = GenerateSegmentTrajectories(round_number=round_id, agent_id=agent_id, radius=RADIUS, start_index=start_index, frame_length=FRAME_LENGTH,agent_map_folder=\"../agent_maps\")\n",
    "                gen.generate()\n",
    "                data = gen.get_trajectory_data()\n",
    "                for other_agent in data[\"sorted_agent_ids\"]:\n",
    "                    if(other_agent==agent_id): continue\n",
    "                    if(len(dtw_maps)==max_channels):break # since sorted_agent_ids is sorted by agent's length, we will get the N longest dtw maps\n",
    "                    dist, cost_matrix, acc_cost_matrix, path = dtw(data[\"agent_tracks\"][agent_id], data[\"agent_tracks\"][other_agent], dist=l2_norm)\n",
    "                    dtw_maps.append(np.expand_dims(acc_cost_matrix.T,axis=0))             \n",
    "                # merge 10 dtw maps and make a 10,w,h tensor here and append to parent data list\n",
    "                dtw_tensor = np.vstack(dtw_maps)\n",
    "                if dtw_tensor.shape[0]<max_channels:\n",
    "                    # padding missing channels with zeros here\n",
    "                    pad_size = max_channels-dtw_tensor.shape[0]\n",
    "                    pad_obj = np.zeros((pad_size,dtw_tensor.shape[1],dtw_tensor.shape[2]))\n",
    "                    dtw_tensor = np.vstack([dtw_tensor,pad_obj])\n",
    "                dtw_result.append(dtw_tensor)\n",
    "                if(len(dtw_result)>4):\n",
    "                    return dtw_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10, 25, 25)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# res = get_dtw_maps()\n",
    "res[1].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Playground/experiments below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "FRAME_LENGTH = 25 # how long should one unit of the scenario be/ what duration is enough to identify an anomaly\n",
    "RADIUS = 15 # how far should we look\n",
    "\n",
    "\n",
    "gen = GenerateSegmentTrajectories(round_number=0, agent_id=324, radius=RADIUS, start_index=50, frame_length=FRAME_LENGTH,agent_map_folder=\"../agent_maps\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen.generate()\n",
    "\n",
    "data = gen.get_trajectory_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen.generate_basic_frame_level_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame_wise_dfs = gen.frame_id_wise_df\n",
    "basic_stats = gen.basic_frame_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>frame_id</th>\n",
       "      <th>round_id</th>\n",
       "      <th>ego_agent_id</th>\n",
       "      <th>num_vehicles</th>\n",
       "      <th>max_velocity_x</th>\n",
       "      <th>max_velocity_y</th>\n",
       "      <th>max_velocity_z</th>\n",
       "      <th>max_ang_velocity_x</th>\n",
       "      <th>max_ang_velocity_y</th>\n",
       "      <th>max_ang_velocity_z</th>\n",
       "      <th>...</th>\n",
       "      <th>min_velocity_z</th>\n",
       "      <th>min_ang_velocity_x</th>\n",
       "      <th>min_ang_velocity_y</th>\n",
       "      <th>min_ang_velocity_z</th>\n",
       "      <th>max_acc_x</th>\n",
       "      <th>max_acc_y</th>\n",
       "      <th>max_acc_z</th>\n",
       "      <th>min_acc_x</th>\n",
       "      <th>min_acc_y</th>\n",
       "      <th>min_acc_z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.626305</td>\n",
       "      <td>-0.020333</td>\n",
       "      <td>3.108460e-06</td>\n",
       "      <td>0.002033</td>\n",
       "      <td>0.009757</td>\n",
       "      <td>0.004870</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.051249e-07</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>-0.080103</td>\n",
       "      <td>-0.000123</td>\n",
       "      <td>0.202999</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>9.535153e-07</td>\n",
       "      <td>-0.046940</td>\n",
       "      <td>-0.000768</td>\n",
       "      <td>-1.334922e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.710058</td>\n",
       "      <td>-0.020370</td>\n",
       "      <td>8.772341e-07</td>\n",
       "      <td>0.000759</td>\n",
       "      <td>-0.028987</td>\n",
       "      <td>0.012879</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.716328e-07</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>-0.164853</td>\n",
       "      <td>-0.000298</td>\n",
       "      <td>0.418763</td>\n",
       "      <td>-0.000186</td>\n",
       "      <td>4.672225e-06</td>\n",
       "      <td>-0.040572</td>\n",
       "      <td>-0.000582</td>\n",
       "      <td>-1.201429e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.777140</td>\n",
       "      <td>-0.019461</td>\n",
       "      <td>-2.288437e-07</td>\n",
       "      <td>0.004831</td>\n",
       "      <td>0.013016</td>\n",
       "      <td>0.042348</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.430273e-06</td>\n",
       "      <td>-0.000393</td>\n",
       "      <td>-0.120655</td>\n",
       "      <td>0.000402</td>\n",
       "      <td>0.335412</td>\n",
       "      <td>0.004543</td>\n",
       "      <td>-5.530389e-06</td>\n",
       "      <td>-0.073071</td>\n",
       "      <td>-0.001179</td>\n",
       "      <td>-8.963044e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.793020</td>\n",
       "      <td>-0.018174</td>\n",
       "      <td>4.195468e-07</td>\n",
       "      <td>0.005326</td>\n",
       "      <td>0.044811</td>\n",
       "      <td>0.069348</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.535154e-07</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>-0.023796</td>\n",
       "      <td>-0.000429</td>\n",
       "      <td>0.079401</td>\n",
       "      <td>0.006439</td>\n",
       "      <td>7.532772e-06</td>\n",
       "      <td>-0.067945</td>\n",
       "      <td>-0.000885</td>\n",
       "      <td>1.620976e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.771416</td>\n",
       "      <td>-0.016925</td>\n",
       "      <td>-3.623358e-07</td>\n",
       "      <td>0.003271</td>\n",
       "      <td>0.161876</td>\n",
       "      <td>0.084707</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.148983e-07</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>-0.021185</td>\n",
       "      <td>-0.000153</td>\n",
       "      <td>-0.023708</td>\n",
       "      <td>0.006243</td>\n",
       "      <td>2.193085e-06</td>\n",
       "      <td>-0.108023</td>\n",
       "      <td>-0.000493</td>\n",
       "      <td>-4.672225e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.750421</td>\n",
       "      <td>-0.015033</td>\n",
       "      <td>4.059325e-03</td>\n",
       "      <td>0.005236</td>\n",
       "      <td>0.145408</td>\n",
       "      <td>0.114028</td>\n",
       "      <td>...</td>\n",
       "      <td>1.907031e-08</td>\n",
       "      <td>-0.317570</td>\n",
       "      <td>-0.018135</td>\n",
       "      <td>-0.000112</td>\n",
       "      <td>0.010796</td>\n",
       "      <td>0.009457</td>\n",
       "      <td>2.029920e-02</td>\n",
       "      <td>-0.104976</td>\n",
       "      <td>-0.000264</td>\n",
       "      <td>2.669843e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.755912</td>\n",
       "      <td>-0.013050</td>\n",
       "      <td>5.037324e-02</td>\n",
       "      <td>0.004797</td>\n",
       "      <td>1.241950</td>\n",
       "      <td>0.142359</td>\n",
       "      <td>...</td>\n",
       "      <td>8.581638e-07</td>\n",
       "      <td>-1.135468</td>\n",
       "      <td>0.007987</td>\n",
       "      <td>0.002892</td>\n",
       "      <td>0.073879</td>\n",
       "      <td>0.042891</td>\n",
       "      <td>2.315696e-01</td>\n",
       "      <td>-0.017018</td>\n",
       "      <td>0.000439</td>\n",
       "      <td>4.195468e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.784440</td>\n",
       "      <td>-0.010949</td>\n",
       "      <td>4.087077e-02</td>\n",
       "      <td>0.868177</td>\n",
       "      <td>1.061273</td>\n",
       "      <td>0.169627</td>\n",
       "      <td>...</td>\n",
       "      <td>1.907031e-07</td>\n",
       "      <td>-0.062909</td>\n",
       "      <td>-0.049261</td>\n",
       "      <td>-0.056296</td>\n",
       "      <td>0.142639</td>\n",
       "      <td>0.050057</td>\n",
       "      <td>1.993130e-01</td>\n",
       "      <td>0.035124</td>\n",
       "      <td>-0.035870</td>\n",
       "      <td>-8.131826e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.814078</td>\n",
       "      <td>-0.008558</td>\n",
       "      <td>9.119764e-03</td>\n",
       "      <td>0.004295</td>\n",
       "      <td>0.410429</td>\n",
       "      <td>0.198291</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.725857e-07</td>\n",
       "      <td>-0.111888</td>\n",
       "      <td>-0.059334</td>\n",
       "      <td>-0.025854</td>\n",
       "      <td>0.148191</td>\n",
       "      <td>0.011958</td>\n",
       "      <td>-5.816444e-06</td>\n",
       "      <td>-0.070581</td>\n",
       "      <td>-0.035932</td>\n",
       "      <td>-1.587550e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.826777</td>\n",
       "      <td>-0.005856</td>\n",
       "      <td>1.469615e-03</td>\n",
       "      <td>0.022676</td>\n",
       "      <td>0.129841</td>\n",
       "      <td>0.226993</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.705311e-04</td>\n",
       "      <td>-0.011766</td>\n",
       "      <td>-0.005139</td>\n",
       "      <td>-0.021715</td>\n",
       "      <td>0.063498</td>\n",
       "      <td>0.013509</td>\n",
       "      <td>1.306316e-05</td>\n",
       "      <td>-0.104792</td>\n",
       "      <td>-0.008377</td>\n",
       "      <td>-4.332354e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.821908</td>\n",
       "      <td>-0.002960</td>\n",
       "      <td>4.195468e-07</td>\n",
       "      <td>0.028684</td>\n",
       "      <td>0.051083</td>\n",
       "      <td>0.252938</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.743988e-03</td>\n",
       "      <td>0.003911</td>\n",
       "      <td>-0.019868</td>\n",
       "      <td>-0.020386</td>\n",
       "      <td>-0.024345</td>\n",
       "      <td>0.014478</td>\n",
       "      <td>-6.102498e-06</td>\n",
       "      <td>-0.064604</td>\n",
       "      <td>-0.002378</td>\n",
       "      <td>-1.170173e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.812358</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>2.097734e-07</td>\n",
       "      <td>0.026661</td>\n",
       "      <td>0.062057</td>\n",
       "      <td>0.277691</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.618296e-03</td>\n",
       "      <td>0.003513</td>\n",
       "      <td>-0.113759</td>\n",
       "      <td>-0.020363</td>\n",
       "      <td>0.014262</td>\n",
       "      <td>0.015386</td>\n",
       "      <td>6.284611e-04</td>\n",
       "      <td>-0.047753</td>\n",
       "      <td>-0.000019</td>\n",
       "      <td>-2.011918e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.810717</td>\n",
       "      <td>0.003314</td>\n",
       "      <td>8.371655e-03</td>\n",
       "      <td>0.003109</td>\n",
       "      <td>0.029512</td>\n",
       "      <td>0.300658</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.166337e-04</td>\n",
       "      <td>-0.405547</td>\n",
       "      <td>-0.653786</td>\n",
       "      <td>-0.017973</td>\n",
       "      <td>0.068929</td>\n",
       "      <td>0.015987</td>\n",
       "      <td>5.494975e-02</td>\n",
       "      <td>-0.008702</td>\n",
       "      <td>0.001235</td>\n",
       "      <td>-1.315851e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.819407</td>\n",
       "      <td>0.007023</td>\n",
       "      <td>3.753565e-02</td>\n",
       "      <td>0.523711</td>\n",
       "      <td>-0.010369</td>\n",
       "      <td>0.332584</td>\n",
       "      <td>...</td>\n",
       "      <td>4.195468e-07</td>\n",
       "      <td>0.004745</td>\n",
       "      <td>-2.099771</td>\n",
       "      <td>-0.007699</td>\n",
       "      <td>0.068169</td>\n",
       "      <td>0.018542</td>\n",
       "      <td>1.458200e-01</td>\n",
       "      <td>0.013404</td>\n",
       "      <td>0.004454</td>\n",
       "      <td>1.420738e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.831545</td>\n",
       "      <td>0.010374</td>\n",
       "      <td>8.849385e-03</td>\n",
       "      <td>0.004822</td>\n",
       "      <td>-0.024968</td>\n",
       "      <td>0.347574</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.907031e-07</td>\n",
       "      <td>0.001875</td>\n",
       "      <td>-0.689428</td>\n",
       "      <td>0.000695</td>\n",
       "      <td>0.060687</td>\n",
       "      <td>0.016759</td>\n",
       "      <td>-3.051249e-06</td>\n",
       "      <td>-0.028441</td>\n",
       "      <td>-0.014164</td>\n",
       "      <td>-1.434313e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.838933</td>\n",
       "      <td>0.013890</td>\n",
       "      <td>7.569005e-04</td>\n",
       "      <td>0.013928</td>\n",
       "      <td>-0.010279</td>\n",
       "      <td>0.363043</td>\n",
       "      <td>...</td>\n",
       "      <td>4.576874e-07</td>\n",
       "      <td>0.001648</td>\n",
       "      <td>-0.140834</td>\n",
       "      <td>-0.000010</td>\n",
       "      <td>0.036941</td>\n",
       "      <td>0.017579</td>\n",
       "      <td>3.241952e-06</td>\n",
       "      <td>-0.067112</td>\n",
       "      <td>-0.002414</td>\n",
       "      <td>-4.046242e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.838996</td>\n",
       "      <td>0.017495</td>\n",
       "      <td>1.258640e-06</td>\n",
       "      <td>0.015743</td>\n",
       "      <td>0.053662</td>\n",
       "      <td>0.377441</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.532108e-03</td>\n",
       "      <td>0.001505</td>\n",
       "      <td>0.006719</td>\n",
       "      <td>-0.000498</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>0.018024</td>\n",
       "      <td>4.004764e-06</td>\n",
       "      <td>-0.056751</td>\n",
       "      <td>-0.001257</td>\n",
       "      <td>-1.144504e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.835407</td>\n",
       "      <td>0.021101</td>\n",
       "      <td>3.051249e-07</td>\n",
       "      <td>0.014233</td>\n",
       "      <td>0.069767</td>\n",
       "      <td>0.388764</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.776304e-03</td>\n",
       "      <td>0.001034</td>\n",
       "      <td>0.024228</td>\n",
       "      <td>-0.000275</td>\n",
       "      <td>-0.003073</td>\n",
       "      <td>0.018032</td>\n",
       "      <td>-4.767577e-06</td>\n",
       "      <td>-0.017943</td>\n",
       "      <td>-0.000102</td>\n",
       "      <td>-1.220977e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.833549</td>\n",
       "      <td>0.024702</td>\n",
       "      <td>3.432655e-07</td>\n",
       "      <td>0.011624</td>\n",
       "      <td>0.035330</td>\n",
       "      <td>0.397377</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.435441e-03</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>0.016263</td>\n",
       "      <td>-0.000573</td>\n",
       "      <td>0.038502</td>\n",
       "      <td>0.018004</td>\n",
       "      <td>1.704313e-03</td>\n",
       "      <td>-0.009289</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>1.907030e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.835793</td>\n",
       "      <td>0.028322</td>\n",
       "      <td>5.721092e-07</td>\n",
       "      <td>0.008355</td>\n",
       "      <td>0.021435</td>\n",
       "      <td>0.404344</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.027966e-03</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>0.000376</td>\n",
       "      <td>-0.000477</td>\n",
       "      <td>0.038776</td>\n",
       "      <td>0.018100</td>\n",
       "      <td>2.037376e-03</td>\n",
       "      <td>-0.003755</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>1.144218e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.840441</td>\n",
       "      <td>0.031880</td>\n",
       "      <td>1.811679e-06</td>\n",
       "      <td>0.005504</td>\n",
       "      <td>0.033307</td>\n",
       "      <td>0.407800</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.037516e-04</td>\n",
       "      <td>-0.000066</td>\n",
       "      <td>-0.009104</td>\n",
       "      <td>-0.000785</td>\n",
       "      <td>0.023236</td>\n",
       "      <td>0.017792</td>\n",
       "      <td>1.621071e-03</td>\n",
       "      <td>-0.002205</td>\n",
       "      <td>0.000107</td>\n",
       "      <td>6.197850e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.844164</td>\n",
       "      <td>0.036513</td>\n",
       "      <td>-4.004764e-07</td>\n",
       "      <td>0.005201</td>\n",
       "      <td>0.051086</td>\n",
       "      <td>0.439302</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.786456e-04</td>\n",
       "      <td>0.002190</td>\n",
       "      <td>-0.006621</td>\n",
       "      <td>-0.000070</td>\n",
       "      <td>0.018616</td>\n",
       "      <td>0.023164</td>\n",
       "      <td>1.125530e-03</td>\n",
       "      <td>-0.030708</td>\n",
       "      <td>-0.000397</td>\n",
       "      <td>-1.106078e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.845149</td>\n",
       "      <td>0.039612</td>\n",
       "      <td>-1.220500e-06</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.047825</td>\n",
       "      <td>0.422762</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.221928e-04</td>\n",
       "      <td>-0.003089</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.004923</td>\n",
       "      <td>0.015496</td>\n",
       "      <td>7.822641e-04</td>\n",
       "      <td>-0.037494</td>\n",
       "      <td>-0.000522</td>\n",
       "      <td>-4.100116e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.844110</td>\n",
       "      <td>0.042902</td>\n",
       "      <td>-1.029797e-06</td>\n",
       "      <td>0.004082</td>\n",
       "      <td>0.021546</td>\n",
       "      <td>0.414874</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.107078e-04</td>\n",
       "      <td>-0.002455</td>\n",
       "      <td>0.002706</td>\n",
       "      <td>-0.000462</td>\n",
       "      <td>-0.003035</td>\n",
       "      <td>0.016449</td>\n",
       "      <td>5.574250e-04</td>\n",
       "      <td>-0.015221</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>9.535154e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>324</td>\n",
       "      <td>4.843107</td>\n",
       "      <td>0.046224</td>\n",
       "      <td>1.010726e-06</td>\n",
       "      <td>0.004661</td>\n",
       "      <td>0.007729</td>\n",
       "      <td>0.410140</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.509796e-04</td>\n",
       "      <td>-0.001564</td>\n",
       "      <td>-0.008788</td>\n",
       "      <td>-0.000299</td>\n",
       "      <td>0.013385</td>\n",
       "      <td>0.016609</td>\n",
       "      <td>2.986410e-04</td>\n",
       "      <td>-0.005012</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>1.020262e-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    frame_id  round_id  ego_agent_id  num_vehicles  max_velocity_x  \\\n",
       "0         50         0             3           324        4.626305   \n",
       "1         51         0             3           324        4.710058   \n",
       "2         52         0             3           324        4.777140   \n",
       "3         53         0             3           324        4.793020   \n",
       "4         54         0             3           324        4.771416   \n",
       "5         55         0             3           324        4.750421   \n",
       "6         56         0             3           324        4.755912   \n",
       "7         57         0             3           324        4.784440   \n",
       "8         58         0             3           324        4.814078   \n",
       "9         59         0             3           324        4.826777   \n",
       "10        60         0             3           324        4.821908   \n",
       "11        61         0             3           324        4.812358   \n",
       "12        62         0             3           324        4.810717   \n",
       "13        63         0             3           324        4.819407   \n",
       "14        64         0             3           324        4.831545   \n",
       "15        65         0             3           324        4.838933   \n",
       "16        66         0             3           324        4.838996   \n",
       "17        67         0             3           324        4.835407   \n",
       "18        68         0             3           324        4.833549   \n",
       "19        69         0             3           324        4.835793   \n",
       "20        70         0             3           324        4.840441   \n",
       "21        71         0             3           324        4.844164   \n",
       "22        72         0             3           324        4.845149   \n",
       "23        73         0             3           324        4.844110   \n",
       "24        74         0             3           324        4.843107   \n",
       "\n",
       "    max_velocity_y  max_velocity_z  max_ang_velocity_x  max_ang_velocity_y  \\\n",
       "0        -0.020333    3.108460e-06            0.002033            0.009757   \n",
       "1        -0.020370    8.772341e-07            0.000759           -0.028987   \n",
       "2        -0.019461   -2.288437e-07            0.004831            0.013016   \n",
       "3        -0.018174    4.195468e-07            0.005326            0.044811   \n",
       "4        -0.016925   -3.623358e-07            0.003271            0.161876   \n",
       "5        -0.015033    4.059325e-03            0.005236            0.145408   \n",
       "6        -0.013050    5.037324e-02            0.004797            1.241950   \n",
       "7        -0.010949    4.087077e-02            0.868177            1.061273   \n",
       "8        -0.008558    9.119764e-03            0.004295            0.410429   \n",
       "9        -0.005856    1.469615e-03            0.022676            0.129841   \n",
       "10       -0.002960    4.195468e-07            0.028684            0.051083   \n",
       "11        0.000117    2.097734e-07            0.026661            0.062057   \n",
       "12        0.003314    8.371655e-03            0.003109            0.029512   \n",
       "13        0.007023    3.753565e-02            0.523711           -0.010369   \n",
       "14        0.010374    8.849385e-03            0.004822           -0.024968   \n",
       "15        0.013890    7.569005e-04            0.013928           -0.010279   \n",
       "16        0.017495    1.258640e-06            0.015743            0.053662   \n",
       "17        0.021101    3.051249e-07            0.014233            0.069767   \n",
       "18        0.024702    3.432655e-07            0.011624            0.035330   \n",
       "19        0.028322    5.721092e-07            0.008355            0.021435   \n",
       "20        0.031880    1.811679e-06            0.005504            0.033307   \n",
       "21        0.036513   -4.004764e-07            0.005201            0.051086   \n",
       "22        0.039612   -1.220500e-06            0.002447            0.047825   \n",
       "23        0.042902   -1.029797e-06            0.004082            0.021546   \n",
       "24        0.046224    1.010726e-06            0.004661            0.007729   \n",
       "\n",
       "    max_ang_velocity_z  ...  min_velocity_z  min_ang_velocity_x  \\\n",
       "0             0.004870  ...   -3.051249e-07            0.000451   \n",
       "1             0.012879  ...   -1.716328e-07            0.000396   \n",
       "2             0.042348  ...   -1.430273e-06           -0.000393   \n",
       "3             0.069348  ...   -9.535154e-07            0.000009   \n",
       "4             0.084707  ...   -5.148983e-07            0.000109   \n",
       "5             0.114028  ...    1.907031e-08           -0.317570   \n",
       "6             0.142359  ...    8.581638e-07           -1.135468   \n",
       "7             0.169627  ...    1.907031e-07           -0.062909   \n",
       "8             0.198291  ...   -9.725857e-07           -0.111888   \n",
       "9             0.226993  ...   -6.705311e-04           -0.011766   \n",
       "10            0.252938  ...   -2.743988e-03            0.003911   \n",
       "11            0.277691  ...   -2.618296e-03            0.003513   \n",
       "12            0.300658  ...   -5.166337e-04           -0.405547   \n",
       "13            0.332584  ...    4.195468e-07            0.004745   \n",
       "14            0.347574  ...   -1.907031e-07            0.001875   \n",
       "15            0.363043  ...    4.576874e-07            0.001648   \n",
       "16            0.377441  ...   -1.532108e-03            0.001505   \n",
       "17            0.388764  ...   -1.776304e-03            0.001034   \n",
       "18            0.397377  ...   -1.435441e-03            0.000557   \n",
       "19            0.404344  ...   -1.027966e-03            0.000453   \n",
       "20            0.407800  ...   -7.037516e-04           -0.000066   \n",
       "21            0.439302  ...   -4.786456e-04            0.002190   \n",
       "22            0.422762  ...   -3.221928e-04           -0.003089   \n",
       "23            0.414874  ...   -2.107078e-04           -0.002455   \n",
       "24            0.410140  ...   -1.509796e-04           -0.001564   \n",
       "\n",
       "    min_ang_velocity_y  min_ang_velocity_z  max_acc_x  max_acc_y  \\\n",
       "0            -0.080103           -0.000123   0.202999   0.001129   \n",
       "1            -0.164853           -0.000298   0.418763  -0.000186   \n",
       "2            -0.120655            0.000402   0.335412   0.004543   \n",
       "3            -0.023796           -0.000429   0.079401   0.006439   \n",
       "4            -0.021185           -0.000153  -0.023708   0.006243   \n",
       "5            -0.018135           -0.000112   0.010796   0.009457   \n",
       "6             0.007987            0.002892   0.073879   0.042891   \n",
       "7            -0.049261           -0.056296   0.142639   0.050057   \n",
       "8            -0.059334           -0.025854   0.148191   0.011958   \n",
       "9            -0.005139           -0.021715   0.063498   0.013509   \n",
       "10           -0.019868           -0.020386  -0.024345   0.014478   \n",
       "11           -0.113759           -0.020363   0.014262   0.015386   \n",
       "12           -0.653786           -0.017973   0.068929   0.015987   \n",
       "13           -2.099771           -0.007699   0.068169   0.018542   \n",
       "14           -0.689428            0.000695   0.060687   0.016759   \n",
       "15           -0.140834           -0.000010   0.036941   0.017579   \n",
       "16            0.006719           -0.000498   0.000315   0.018024   \n",
       "17            0.024228           -0.000275  -0.003073   0.018032   \n",
       "18            0.016263           -0.000573   0.038502   0.018004   \n",
       "19            0.000376           -0.000477   0.038776   0.018100   \n",
       "20           -0.009104           -0.000785   0.023236   0.017792   \n",
       "21           -0.006621           -0.000070   0.018616   0.023164   \n",
       "22            0.002264           -0.000396   0.004923   0.015496   \n",
       "23            0.002706           -0.000462  -0.003035   0.016449   \n",
       "24           -0.008788           -0.000299   0.013385   0.016609   \n",
       "\n",
       "       max_acc_z  min_acc_x  min_acc_y     min_acc_z  \n",
       "0   9.535153e-07  -0.046940  -0.000768 -1.334922e-06  \n",
       "1   4.672225e-06  -0.040572  -0.000582 -1.201429e-05  \n",
       "2  -5.530389e-06  -0.073071  -0.001179 -8.963044e-06  \n",
       "3   7.532772e-06  -0.067945  -0.000885  1.620976e-06  \n",
       "4   2.193085e-06  -0.108023  -0.000493 -4.672225e-06  \n",
       "5   2.029920e-02  -0.104976  -0.000264  2.669843e-06  \n",
       "6   2.315696e-01  -0.017018   0.000439  4.195468e-06  \n",
       "7   1.993130e-01   0.035124  -0.035870 -8.131826e-02  \n",
       "8  -5.816444e-06  -0.070581  -0.035932 -1.587550e-01  \n",
       "9   1.306316e-05  -0.104792  -0.008377 -4.332354e-02  \n",
       "10 -6.102498e-06  -0.064604  -0.002378 -1.170173e-02  \n",
       "11  6.284611e-04  -0.047753  -0.000019 -2.011918e-03  \n",
       "12  5.494975e-02  -0.008702   0.001235 -1.315851e-05  \n",
       "13  1.458200e-01   0.013404   0.004454  1.420738e-05  \n",
       "14 -3.051249e-06  -0.028441  -0.014164 -1.434313e-01  \n",
       "15  3.241952e-06  -0.067112  -0.002414 -4.046242e-02  \n",
       "16  4.004764e-06  -0.056751  -0.001257 -1.144504e-02  \n",
       "17 -4.767577e-06  -0.017943  -0.000102 -1.220977e-03  \n",
       "18  1.704313e-03  -0.009289   0.000029  1.907030e-07  \n",
       "19  2.037376e-03  -0.003755   0.000022  1.144218e-06  \n",
       "20  1.621071e-03  -0.002205   0.000107  6.197850e-06  \n",
       "21  1.125530e-03  -0.030708  -0.000397 -1.106078e-05  \n",
       "22  7.822641e-04  -0.037494  -0.000522 -4.100116e-06  \n",
       "23  5.574250e-04  -0.015221  -0.000214  9.535154e-07  \n",
       "24  2.986410e-04  -0.005012  -0.000033  1.020262e-05  \n",
       "\n",
       "[25 rows x 22 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basic_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[287, 289, 324]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['sorted_agent_ids']# data['agent_metadata_dfs']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame_wise_dfs.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>level_0</th>\n",
       "      <th>index</th>\n",
       "      <th>frame_id</th>\n",
       "      <th>id</th>\n",
       "      <th>type_id</th>\n",
       "      <th>pos_x</th>\n",
       "      <th>pos_y</th>\n",
       "      <th>pos_z</th>\n",
       "      <th>roll</th>\n",
       "      <th>pitch</th>\n",
       "      <th>...</th>\n",
       "      <th>angular_vel_x</th>\n",
       "      <th>angular_vel_y</th>\n",
       "      <th>angular_vel_z</th>\n",
       "      <th>bbox3d_offset_x</th>\n",
       "      <th>bbox3d_offset_y</th>\n",
       "      <th>bbox3d_offset_z</th>\n",
       "      <th>bbox3d_extent_x</th>\n",
       "      <th>bbox3d_extent_y</th>\n",
       "      <th>bbox3d_extent_z</th>\n",
       "      <th>traffic_light_color</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>70</td>\n",
       "      <td>5516</td>\n",
       "      <td>50</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>11.738648</td>\n",
       "      <td>-11.330558</td>\n",
       "      <td>0.035445</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.033202</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>-0.034525</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.710000</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>72</td>\n",
       "      <td>5518</td>\n",
       "      <td>50</td>\n",
       "      <td>289</td>\n",
       "      <td>vehicle.chevrolet.impala</td>\n",
       "      <td>11.963082</td>\n",
       "      <td>-14.826639</td>\n",
       "      <td>-0.048051</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.024548</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001158</td>\n",
       "      <td>-0.080103</td>\n",
       "      <td>-0.000123</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.710000</td>\n",
       "      <td>2.684597</td>\n",
       "      <td>1.026368</td>\n",
       "      <td>0.707550</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>107</td>\n",
       "      <td>5553</td>\n",
       "      <td>50</td>\n",
       "      <td>324</td>\n",
       "      <td>vehicle.mustang.mustang</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.006685</td>\n",
       "      <td>-0.000153</td>\n",
       "      <td>0.019377</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002033</td>\n",
       "      <td>0.009757</td>\n",
       "      <td>0.004870</td>\n",
       "      <td>0.060645</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.747342</td>\n",
       "      <td>2.452351</td>\n",
       "      <td>1.030329</td>\n",
       "      <td>0.739199</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   level_0  index  frame_id   id                   type_id      pos_x  \\\n",
       "0       70   5516        50  287      vehicle.toyota.prius  11.738648   \n",
       "1       72   5518        50  289  vehicle.chevrolet.impala  11.963082   \n",
       "2      107   5553        50  324   vehicle.mustang.mustang   0.000000   \n",
       "\n",
       "       pos_y     pos_z      roll     pitch  ...  angular_vel_x  angular_vel_y  \\\n",
       "0 -11.330558  0.035445  0.000015  0.033202  ...       0.000451      -0.034525   \n",
       "1 -14.826639 -0.048051  0.000021  0.024548  ...       0.001158      -0.080103   \n",
       "2   0.000000 -0.006685 -0.000153  0.019377  ...       0.002033       0.009757   \n",
       "\n",
       "   angular_vel_z  bbox3d_offset_x  bbox3d_offset_y  bbox3d_offset_z  \\\n",
       "0       0.000406         0.000000              0.0         0.710000   \n",
       "1      -0.000123         0.000000              0.0         0.710000   \n",
       "2       0.004870         0.060645              0.0         0.747342   \n",
       "\n",
       "   bbox3d_extent_x  bbox3d_extent_y  bbox3d_extent_z  traffic_light_color  \n",
       "0         2.269167         1.000565         0.768681                  NaN  \n",
       "1         2.684597         1.026368         0.707550                  NaN  \n",
       "2         2.452351         1.030329         0.739199                  NaN  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame_wise_dfs[50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['level_0', 'index', 'frame_id', 'id', 'type_id', 'pos_x', 'pos_y',\n",
       "       'pos_z', 'roll', 'pitch', 'yaw', 'velocity_x', 'velocity_y',\n",
       "       'velocity_z', 'acc_x', 'acc_y', 'acc_z', 'angular_vel_x',\n",
       "       'angular_vel_y', 'angular_vel_z', 'bbox3d_offset_x', 'bbox3d_offset_y',\n",
       "       'bbox3d_offset_z', 'bbox3d_extent_x', 'bbox3d_extent_y',\n",
       "       'bbox3d_extent_z', 'traffic_light_color'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame_wise_dfs[50].columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>level_0</th>\n",
       "      <th>index</th>\n",
       "      <th>frame_id</th>\n",
       "      <th>id</th>\n",
       "      <th>type_id</th>\n",
       "      <th>pos_x</th>\n",
       "      <th>pos_y</th>\n",
       "      <th>pos_z</th>\n",
       "      <th>roll</th>\n",
       "      <th>pitch</th>\n",
       "      <th>...</th>\n",
       "      <th>angular_vel_x</th>\n",
       "      <th>angular_vel_y</th>\n",
       "      <th>angular_vel_z</th>\n",
       "      <th>bbox3d_offset_x</th>\n",
       "      <th>bbox3d_offset_y</th>\n",
       "      <th>bbox3d_offset_z</th>\n",
       "      <th>bbox3d_extent_x</th>\n",
       "      <th>bbox3d_extent_y</th>\n",
       "      <th>bbox3d_extent_z</th>\n",
       "      <th>traffic_light_color</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>70</td>\n",
       "      <td>5516</td>\n",
       "      <td>50</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>11.738648</td>\n",
       "      <td>-11.330558</td>\n",
       "      <td>0.035445</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.033202</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>-0.034525</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>5624</td>\n",
       "      <td>51</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>10.799512</td>\n",
       "      <td>-11.339936</td>\n",
       "      <td>0.035478</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.030087</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000587</td>\n",
       "      <td>-0.029146</td>\n",
       "      <td>-0.000298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>70</td>\n",
       "      <td>5732</td>\n",
       "      <td>52</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>9.851180</td>\n",
       "      <td>-11.349789</td>\n",
       "      <td>0.035506</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.027348</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>-0.026119</td>\n",
       "      <td>0.000474</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>70</td>\n",
       "      <td>5840</td>\n",
       "      <td>53</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>8.898015</td>\n",
       "      <td>-11.360060</td>\n",
       "      <td>0.035532</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>0.024862</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000519</td>\n",
       "      <td>-0.023796</td>\n",
       "      <td>-0.000302</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>70</td>\n",
       "      <td>5948</td>\n",
       "      <td>54</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>7.944973</td>\n",
       "      <td>-11.370479</td>\n",
       "      <td>0.035556</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.022628</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>-0.021185</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>70</td>\n",
       "      <td>6056</td>\n",
       "      <td>55</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>6.993459</td>\n",
       "      <td>-11.381090</td>\n",
       "      <td>0.035576</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.020689</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>-0.018135</td>\n",
       "      <td>-0.000112</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>70</td>\n",
       "      <td>6164</td>\n",
       "      <td>56</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>6.041590</td>\n",
       "      <td>-11.391827</td>\n",
       "      <td>0.035605</td>\n",
       "      <td>-0.001617</td>\n",
       "      <td>0.019466</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.098251</td>\n",
       "      <td>0.007987</td>\n",
       "      <td>0.003873</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>70</td>\n",
       "      <td>6272</td>\n",
       "      <td>57</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>5.086700</td>\n",
       "      <td>-11.402581</td>\n",
       "      <td>0.037241</td>\n",
       "      <td>-0.088440</td>\n",
       "      <td>0.074108</td>\n",
       "      <td>...</td>\n",
       "      <td>0.868177</td>\n",
       "      <td>1.049767</td>\n",
       "      <td>-0.056296</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>70</td>\n",
       "      <td>6380</td>\n",
       "      <td>58</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>4.128369</td>\n",
       "      <td>-11.412943</td>\n",
       "      <td>0.038386</td>\n",
       "      <td>-0.109650</td>\n",
       "      <td>0.120225</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.111888</td>\n",
       "      <td>0.289344</td>\n",
       "      <td>-0.025854</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>70</td>\n",
       "      <td>6488</td>\n",
       "      <td>59</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>3.167264</td>\n",
       "      <td>-11.423146</td>\n",
       "      <td>0.038620</td>\n",
       "      <td>-0.113770</td>\n",
       "      <td>0.136139</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011766</td>\n",
       "      <td>0.092497</td>\n",
       "      <td>-0.021715</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>70</td>\n",
       "      <td>6596</td>\n",
       "      <td>60</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>2.204869</td>\n",
       "      <td>-11.433006</td>\n",
       "      <td>0.038562</td>\n",
       "      <td>-0.113068</td>\n",
       "      <td>0.140306</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014354</td>\n",
       "      <td>0.013645</td>\n",
       "      <td>-0.020386</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>70</td>\n",
       "      <td>6704</td>\n",
       "      <td>61</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>1.242380</td>\n",
       "      <td>-11.442367</td>\n",
       "      <td>0.038454</td>\n",
       "      <td>-0.111328</td>\n",
       "      <td>0.139227</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018539</td>\n",
       "      <td>-0.023625</td>\n",
       "      <td>-0.020363</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>70</td>\n",
       "      <td>6812</td>\n",
       "      <td>62</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>0.279723</td>\n",
       "      <td>-11.451111</td>\n",
       "      <td>0.038389</td>\n",
       "      <td>-0.110352</td>\n",
       "      <td>0.135204</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.030107</td>\n",
       "      <td>-0.074888</td>\n",
       "      <td>-0.017973</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>70</td>\n",
       "      <td>6920</td>\n",
       "      <td>63</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-0.683304</td>\n",
       "      <td>-11.459157</td>\n",
       "      <td>0.039926</td>\n",
       "      <td>-0.147766</td>\n",
       "      <td>0.069190</td>\n",
       "      <td>...</td>\n",
       "      <td>0.039264</td>\n",
       "      <td>-0.861874</td>\n",
       "      <td>0.011560</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>70</td>\n",
       "      <td>7028</td>\n",
       "      <td>64</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-1.647961</td>\n",
       "      <td>-11.466232</td>\n",
       "      <td>0.041052</td>\n",
       "      <td>-0.148407</td>\n",
       "      <td>0.017738</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002689</td>\n",
       "      <td>-0.325109</td>\n",
       "      <td>0.001174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>70</td>\n",
       "      <td>7136</td>\n",
       "      <td>65</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-2.614338</td>\n",
       "      <td>-11.472481</td>\n",
       "      <td>0.041347</td>\n",
       "      <td>-0.147858</td>\n",
       "      <td>0.000683</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010477</td>\n",
       "      <td>-0.087202</td>\n",
       "      <td>-0.000010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>70</td>\n",
       "      <td>7244</td>\n",
       "      <td>66</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-3.581644</td>\n",
       "      <td>-11.477784</td>\n",
       "      <td>0.041340</td>\n",
       "      <td>-0.146820</td>\n",
       "      <td>-0.001769</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009521</td>\n",
       "      <td>0.006719</td>\n",
       "      <td>-0.000498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>70</td>\n",
       "      <td>7352</td>\n",
       "      <td>67</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-4.549186</td>\n",
       "      <td>-11.482087</td>\n",
       "      <td>0.041250</td>\n",
       "      <td>-0.146057</td>\n",
       "      <td>0.000785</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005901</td>\n",
       "      <td>0.033339</td>\n",
       "      <td>-0.000159</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>70</td>\n",
       "      <td>7460</td>\n",
       "      <td>68</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-5.516782</td>\n",
       "      <td>-11.485348</td>\n",
       "      <td>0.041160</td>\n",
       "      <td>-0.145447</td>\n",
       "      <td>0.004084</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004964</td>\n",
       "      <td>0.030972</td>\n",
       "      <td>-0.000573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>70</td>\n",
       "      <td>7568</td>\n",
       "      <td>69</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-6.484655</td>\n",
       "      <td>-11.487551</td>\n",
       "      <td>0.041094</td>\n",
       "      <td>-0.144989</td>\n",
       "      <td>0.006632</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003772</td>\n",
       "      <td>0.021435</td>\n",
       "      <td>-0.000477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>70</td>\n",
       "      <td>7676</td>\n",
       "      <td>70</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-7.453078</td>\n",
       "      <td>-11.488691</td>\n",
       "      <td>0.041051</td>\n",
       "      <td>-0.144623</td>\n",
       "      <td>0.008251</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002901</td>\n",
       "      <td>0.012951</td>\n",
       "      <td>-0.000785</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>70</td>\n",
       "      <td>7784</td>\n",
       "      <td>71</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-8.422508</td>\n",
       "      <td>-11.488511</td>\n",
       "      <td>0.041024</td>\n",
       "      <td>-0.144379</td>\n",
       "      <td>0.009207</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002190</td>\n",
       "      <td>0.007730</td>\n",
       "      <td>-0.000070</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>70</td>\n",
       "      <td>7892</td>\n",
       "      <td>72</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-9.392088</td>\n",
       "      <td>-11.487296</td>\n",
       "      <td>0.041007</td>\n",
       "      <td>-0.144165</td>\n",
       "      <td>0.009801</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001223</td>\n",
       "      <td>0.004629</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>8000</td>\n",
       "      <td>73</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-10.361472</td>\n",
       "      <td>-11.485162</td>\n",
       "      <td>0.040997</td>\n",
       "      <td>-0.144073</td>\n",
       "      <td>0.010143</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000581</td>\n",
       "      <td>0.002706</td>\n",
       "      <td>-0.000462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>70</td>\n",
       "      <td>8108</td>\n",
       "      <td>74</td>\n",
       "      <td>287</td>\n",
       "      <td>vehicle.toyota.prius</td>\n",
       "      <td>-11.330689</td>\n",
       "      <td>-11.482074</td>\n",
       "      <td>0.040992</td>\n",
       "      <td>-0.144043</td>\n",
       "      <td>0.010341</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000209</td>\n",
       "      <td>0.001552</td>\n",
       "      <td>-0.000299</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>2.269167</td>\n",
       "      <td>1.000565</td>\n",
       "      <td>0.768681</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    level_0  index  frame_id   id               type_id      pos_x      pos_y  \\\n",
       "0        70   5516        50  287  vehicle.toyota.prius  11.738648 -11.330558   \n",
       "3        70   5624        51  287  vehicle.toyota.prius  10.799512 -11.339936   \n",
       "6        70   5732        52  287  vehicle.toyota.prius   9.851180 -11.349789   \n",
       "9        70   5840        53  287  vehicle.toyota.prius   8.898015 -11.360060   \n",
       "12       70   5948        54  287  vehicle.toyota.prius   7.944973 -11.370479   \n",
       "15       70   6056        55  287  vehicle.toyota.prius   6.993459 -11.381090   \n",
       "18       70   6164        56  287  vehicle.toyota.prius   6.041590 -11.391827   \n",
       "21       70   6272        57  287  vehicle.toyota.prius   5.086700 -11.402581   \n",
       "24       70   6380        58  287  vehicle.toyota.prius   4.128369 -11.412943   \n",
       "27       70   6488        59  287  vehicle.toyota.prius   3.167264 -11.423146   \n",
       "30       70   6596        60  287  vehicle.toyota.prius   2.204869 -11.433006   \n",
       "33       70   6704        61  287  vehicle.toyota.prius   1.242380 -11.442367   \n",
       "36       70   6812        62  287  vehicle.toyota.prius   0.279723 -11.451111   \n",
       "39       70   6920        63  287  vehicle.toyota.prius  -0.683304 -11.459157   \n",
       "42       70   7028        64  287  vehicle.toyota.prius  -1.647961 -11.466232   \n",
       "45       70   7136        65  287  vehicle.toyota.prius  -2.614338 -11.472481   \n",
       "48       70   7244        66  287  vehicle.toyota.prius  -3.581644 -11.477784   \n",
       "51       70   7352        67  287  vehicle.toyota.prius  -4.549186 -11.482087   \n",
       "54       70   7460        68  287  vehicle.toyota.prius  -5.516782 -11.485348   \n",
       "57       70   7568        69  287  vehicle.toyota.prius  -6.484655 -11.487551   \n",
       "60       70   7676        70  287  vehicle.toyota.prius  -7.453078 -11.488691   \n",
       "63       70   7784        71  287  vehicle.toyota.prius  -8.422508 -11.488511   \n",
       "66       70   7892        72  287  vehicle.toyota.prius  -9.392088 -11.487296   \n",
       "69       70   8000        73  287  vehicle.toyota.prius -10.361472 -11.485162   \n",
       "72       70   8108        74  287  vehicle.toyota.prius -11.330689 -11.482074   \n",
       "\n",
       "       pos_z      roll     pitch  ...  angular_vel_x  angular_vel_y  \\\n",
       "0   0.035445  0.000015  0.033202  ...       0.000451      -0.034525   \n",
       "3   0.035478  0.000036  0.030087  ...       0.000587      -0.029146   \n",
       "6   0.035506  0.000016  0.027348  ...       0.000170      -0.026119   \n",
       "9   0.035532  0.000038  0.024862  ...       0.000519      -0.023796   \n",
       "12  0.035556  0.000028  0.022628  ...       0.000207      -0.021185   \n",
       "15  0.035576  0.000035  0.020689  ...       0.000407      -0.018135   \n",
       "18  0.035605 -0.001617  0.019466  ...      -0.098251       0.007987   \n",
       "21  0.037241 -0.088440  0.074108  ...       0.868177       1.049767   \n",
       "24  0.038386 -0.109650  0.120225  ...      -0.111888       0.289344   \n",
       "27  0.038620 -0.113770  0.136139  ...      -0.011766       0.092497   \n",
       "30  0.038562 -0.113068  0.140306  ...       0.014354       0.013645   \n",
       "33  0.038454 -0.111328  0.139227  ...       0.018539      -0.023625   \n",
       "36  0.038389 -0.110352  0.135204  ...      -0.030107      -0.074888   \n",
       "39  0.039926 -0.147766  0.069190  ...       0.039264      -0.861874   \n",
       "42  0.041052 -0.148407  0.017738  ...       0.002689      -0.325109   \n",
       "45  0.041347 -0.147858  0.000683  ...       0.010477      -0.087202   \n",
       "48  0.041340 -0.146820 -0.001769  ...       0.009521       0.006719   \n",
       "51  0.041250 -0.146057  0.000785  ...       0.005901       0.033339   \n",
       "54  0.041160 -0.145447  0.004084  ...       0.004964       0.030972   \n",
       "57  0.041094 -0.144989  0.006632  ...       0.003772       0.021435   \n",
       "60  0.041051 -0.144623  0.008251  ...       0.002901       0.012951   \n",
       "63  0.041024 -0.144379  0.009207  ...       0.002190       0.007730   \n",
       "66  0.041007 -0.144165  0.009801  ...       0.001223       0.004629   \n",
       "69  0.040997 -0.144073  0.010143  ...       0.000581       0.002706   \n",
       "72  0.040992 -0.144043  0.010341  ...       0.000209       0.001552   \n",
       "\n",
       "    angular_vel_z  bbox3d_offset_x  bbox3d_offset_y  bbox3d_offset_z  \\\n",
       "0        0.000406              0.0              0.0             0.71   \n",
       "3       -0.000298              0.0              0.0             0.71   \n",
       "6        0.000474              0.0              0.0             0.71   \n",
       "9       -0.000302              0.0              0.0             0.71   \n",
       "12       0.000130              0.0              0.0             0.71   \n",
       "15      -0.000112              0.0              0.0             0.71   \n",
       "18       0.003873              0.0              0.0             0.71   \n",
       "21      -0.056296              0.0              0.0             0.71   \n",
       "24      -0.025854              0.0              0.0             0.71   \n",
       "27      -0.021715              0.0              0.0             0.71   \n",
       "30      -0.020386              0.0              0.0             0.71   \n",
       "33      -0.020363              0.0              0.0             0.71   \n",
       "36      -0.017973              0.0              0.0             0.71   \n",
       "39       0.011560              0.0              0.0             0.71   \n",
       "42       0.001174              0.0              0.0             0.71   \n",
       "45      -0.000010              0.0              0.0             0.71   \n",
       "48      -0.000498              0.0              0.0             0.71   \n",
       "51      -0.000159              0.0              0.0             0.71   \n",
       "54      -0.000573              0.0              0.0             0.71   \n",
       "57      -0.000477              0.0              0.0             0.71   \n",
       "60      -0.000785              0.0              0.0             0.71   \n",
       "63      -0.000070              0.0              0.0             0.71   \n",
       "66      -0.000396              0.0              0.0             0.71   \n",
       "69      -0.000462              0.0              0.0             0.71   \n",
       "72      -0.000299              0.0              0.0             0.71   \n",
       "\n",
       "    bbox3d_extent_x  bbox3d_extent_y  bbox3d_extent_z  traffic_light_color  \n",
       "0          2.269167         1.000565         0.768681                  NaN  \n",
       "3          2.269167         1.000565         0.768681                  NaN  \n",
       "6          2.269167         1.000565         0.768681                  NaN  \n",
       "9          2.269167         1.000565         0.768681                  NaN  \n",
       "12         2.269167         1.000565         0.768681                  NaN  \n",
       "15         2.269167         1.000565         0.768681                  NaN  \n",
       "18         2.269167         1.000565         0.768681                  NaN  \n",
       "21         2.269167         1.000565         0.768681                  NaN  \n",
       "24         2.269167         1.000565         0.768681                  NaN  \n",
       "27         2.269167         1.000565         0.768681                  NaN  \n",
       "30         2.269167         1.000565         0.768681                  NaN  \n",
       "33         2.269167         1.000565         0.768681                  NaN  \n",
       "36         2.269167         1.000565         0.768681                  NaN  \n",
       "39         2.269167         1.000565         0.768681                  NaN  \n",
       "42         2.269167         1.000565         0.768681                  NaN  \n",
       "45         2.269167         1.000565         0.768681                  NaN  \n",
       "48         2.269167         1.000565         0.768681                  NaN  \n",
       "51         2.269167         1.000565         0.768681                  NaN  \n",
       "54         2.269167         1.000565         0.768681                  NaN  \n",
       "57         2.269167         1.000565         0.768681                  NaN  \n",
       "60         2.269167         1.000565         0.768681                  NaN  \n",
       "63         2.269167         1.000565         0.768681                  NaN  \n",
       "66         2.269167         1.000565         0.768681                  NaN  \n",
       "69         2.269167         1.000565         0.768681                  NaN  \n",
       "72         2.269167         1.000565         0.768681                  NaN  \n",
       "\n",
       "[25 rows x 27 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# for id in data['sorted_agent_ids']\n",
    "data['agent_metadata_dfs'][287]\n",
    "#  for each frame, get the min and max velocities, min, max acceleration, angular velocities, number of agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dtw import dtw\n",
    "\n",
    "# Here, we use L2 norm as the element comparison distance\n",
    "l2_norm = lambda x, y: np.linalg.norm((x - y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAADG1JREFUeJzt3U+IXeUZx/Hfz/gnk5iFIW0I1jatSCGbxjKIUCkRW7FuohupSMlCiAsFBTfBjW4KbtRuihBRkoVaBLW6kNYQhLRQpKOIRm1RRKkxJpUgxiT+ydynizmxY8zMeWfue889N8/3A2HunPvmnIdLfjn33vc573FECEA+54y7AADjQfiBpAg/kBThB5Ii/EBShB9IivADSRF+ICnCDyR1bpcHW7duXWzcuHHRMYPBYKjnS8eUdDa2jal1nC72UXM/fWF73CV8o1Ytw+7no48+0qefflq0k07Dv3HjRs3MzCw65vjx44s+f+LEidbjlIz54osvWsd89dVXQz0vSV9//XXrmJMnTy76/OzsbOs+uvqPqE9KglJrTJsVK1a0jjnnnPY32m37aXv+lltuaT3GN/UUjwRwViH8QFKEH0iK8ANJEX4gKcIPJEX4gaQ6necfDAat8/g15vlL5vBrzPOXzOHXmOfvU2NTV7psmmkbUzI/39WY1atXt+6jFGd+ICnCDyRF+IGkCD+QFOEHkiL8QFKEH0iq83n+Y8eOLTqmbR6/1jz/l19+2Tqmxjx/2xx+yZiS6/knaQ6/lq6u1e9ynn/VqlVFNdXAmR9IivADSRF+ICnCDyRF+IGkCD+QFOEHkiL8QFK9W8yjRpNPSQNPyZi2Jp6umny6XMyjL87GxTympqZax3SJMz+QFOEHkiL8QFKEH0iK8ANJEX4gKcIPJEX4gaTOypV82lbgKR1To8mnZBWetjEljUIlJqnJp0StRqC2Bp2S43S5Ak8trWd+25fYfsn2W7bftH1ns32t7T2232l+XjT6cgHUUvK2/6SkuyNik6QrJd1ue5OkHZL2RsRlkvY2vwOYEK3hj4iDEfFq8/iopLclXSxpq6TdzbDdkm4YVZEA6lvSF362N0q6XNLLktZHxMHmqY8lrV/g72y3PWN75siRI0OUCqCm4vDbvlDS05LuiojP5j8Xc98knfHbpIjYGRHTETG9du3aoYoFUE9R+G2fp7ngPx4RzzSbD9ne0Dy/QdLh0ZQIYBRKvu23pEclvR0RD8576nlJ25rH2yQ9V788AKNSMs//C0m/k/SG7deabfdIul/SU7ZvlfSBpJtGUyKAUWgNf0T8XdJCXQ7XLOVgs7OzrU0+bbfaKlmBp+R2XSUNOm1jaqzSI7WvwsNKPqPdT9uYvq3AUwvtvUBShB9IivADSRF+ICnCDyRF+IGkCD+QVO/u2FNjnr+rxTxK5vBLFvPoap4/o5I76axcubKDSvqHMz+QFOEHkiL8QFKEH0iK8ANJEX4gKcIPJEX4gaR6d8eetiaeWk0+JYt5tDXxlOyjRoNOrYU6Mi7mcbYuxFEDZ34gKcIPJEX4gaQIP5AU4QeSIvxAUoQfSIrwA0lNXJNPrQaeGk0+Jav0sJLP6NDAMxzO/EBShB9IivADSRF+ICnCDyRF+IGkCD+QVO/u2NPVPH/J3XZqzPPXmKOvtVDHJC3mccEFF4y7hLNe65nf9mO2D9veP2/bfbYP2H6t+XP9aMsEUFvJ2/5dkq47w/aHImJz8+eFumUBGLXW8EfEPklHOqgFQIeG+cLvDtuvNx8LLqpWEYBOLDf8D0u6VNJmSQclPbDQQNvbbc/Ynjl69OgyDwegtmWFPyIORcRsRAwkPSLpikXG7oyI6YiYXrNmzXLrBFDZssJve8O8X2+UtH+hsQD6qXWe3/aTkrZIWmf7Q0n3Stpie7OkkPS+pNtGWCOAEWgNf0TcfIbNjy7nYCWLebQ18ZQ0+dRo4CkZU2uRja6afPqEJp7xo70XSIrwA0kRfiApwg8kRfiBpAg/kBThB5Ii/EBSna7kMzs729rk07YKT6278dS4205Jo1CNBp1aDTxdNQKtXLmyk+NgOJz5gaQIP5AU4QeSIvxAUoQfSIrwA0kRfiApwg8kNXG36yppzilp8ilZYaftWCW19KnJpwZW4Dl7cOYHkiL8QFKEH0iK8ANJEX4gKcIPJEX4gaQ6n+cfdjGPWnfjqTHPX7KPru62U6sXgIU48uDMDyRF+IGkCD+QFOEHkiL8QFKEH0iK8ANJEX4gqc6bfD7//PNFx7Q11nS1UEfpmDZdNfmUYCEOzNd65rf9mO3DtvfP27bW9h7b7zQ/LxptmQBqK3nbv0vSdadt2yFpb0RcJmlv8zuACdIa/ojYJ+nIaZu3StrdPN4t6YbKdQEYseV+4bc+Ig42jz+WtH6hgba3256xPXPixIllHg5AbUN/2x9z31Yt+I1VROyMiOmImJ6amhr2cAAqWW74D9neIEnNz8P1SgLQheWG/3lJ25rH2yQ9V6ccAF0pmep7UtI/JP3U9oe2b5V0v6Rf235H0q+a3wFMkNYmn4i4eYGnrlnqwQaDgdq+9GtbhaerVXpK99OmqyYfVuDBUtHeCyRF+IGkCD+QFOEHkiL8QFKEH0iK8ANJEX4gqd7drqutiWfSVumpsR8aeDAKnPmBpAg/kBThB5Ii/EBShB9IivADSRF+IKlO5/lnZ2db79jTNo9fMs9fa0yNefySfTCPj3HgzA8kRfiBpAg/kBThB5Ii/EBShB9IivADSRF+IKnOF/MY9o49JU0zNRbqKEEDDyYZZ34gKcIPJEX4gaQIP5AU4QeSIvxAUoQfSIrwA0kN1eRj+31JRyXNSjoZEdOLjR8MBq0r+bQ1ztRq4KmxSg8NPJhkNTr8ro6ITyrsB0CHeNsPJDVs+EPSi7Zfsb29RkEAujHs2/6rIuKA7e9L2mP7XxGxb/6A5j+F7ZJ0/vnnD3k4ALUMdeaPiAPNz8OSnpV0xRnG7IyI6YiYPvfcTi8iBLCIZYff9mrba049lnStpP21CgMwWsOcitdLetb2qf08ERF/qVIVgJFbdvgj4j1JP1vK3xkMBjp+/HjrmJbjltS2lLIWNDU1VWU/QB8x1QckRfiBpAg/kBThB5Ii/EBShB9IivADSRF+IKnO79jTRZNPCRp4kB1nfiApwg8kRfiBpAg/kBThB5Ii/EBShB9IivADSXXe5HPs2LFFx9Ro4qGBB2jHmR9IivADSRF+ICnCDyRF+IGkCD+QFOEHkiL8QFK9a/Jps2rVqkrVALlx5geSIvxAUoQfSIrwA0kRfiApwg8kRfiBpHp3xx7m8YFuDHXmt32d7X/bftf2jlpFARi9ZYff9gpJf5T0G0mbJN1se1OtwgCM1jBn/iskvRsR70XEV5L+JGlrnbIAjNow4b9Y0n/m/f5hs+1bbG+3PWN7ZohjAahs5F/4RcROSTslyXad+2sDGNowZ/4Dki6Z9/sPmm0AJsAw4f+npMts/9j2+ZJ+K+n5OmUBGLVlv+2PiJO275D0V0krJD0WEW9WqwzASLnGHXKKD2b/V9IH8zatk/RJZwUMb5LqnaRapcmqt8+1/igivlcysNPwf+fg9kxETI+tgCWapHonqVZpsuqdpFoXQ28/kBThB5Iad/h3jvn4SzVJ9U5SrdJk1TtJtS5orJ/5AYzPuM/8AMZkbOGfpMuBbb9v+w3br/XxGgXbj9k+bHv/vG1rbe+x/U7z86Jx1jjfAvXeZ/tA8xq/Zvv6cdZ4iu1LbL9k+y3bb9q+s9ne29e31FjCP6GXA18dEZt7OsWzS9J1p23bIWlvRFwmaW/ze1/s0nfrlaSHmtd4c0S80HFNCzkp6e6I2CTpSkm3N/9W+/z6FhnXmZ/LgSuKiH2Sjpy2eauk3c3j3ZJu6LSoRSxQby9FxMGIeLV5fFTS25q7erW3r2+pcYW/6HLgHglJL9p+xfb2cRdTaH1EHGwefyxp/TiLKXSH7debjwW9extte6OkyyW9rMl8fb+FL/zKXBURP9fcx5Tbbf9y3AUtRcxN6fR9WudhSZdK2izpoKQHxlvOt9m+UNLTku6KiM/mPzchr+93jCv8E3U5cEQcaH4elvSs5j629N0h2xskqfl5eMz1LCoiDkXEbEQMJD2iHr3Gts/TXPAfj4hnms0T9fqeybjCPzGXA9tebXvNqceSrpW0f/G/1QvPS9rWPN4m6bkx1tLqVJAaN6onr7FtS3pU0tsR8eC8pybq9T2TsTX5NFM5f9D/Lwf+/VgKaWH7J5o720tzl0A/0bdabT8paYvmrjY7JOleSX+W9JSkH2ruSsqbIqIXX7ItUO8Wzb3lD0nvS7pt3mfqsbF9laS/SXpD0qDZfI/mPvf38vUtRYcfkBRf+AFJEX4gKcIPJEX4gaQIP5AU4QeSIvxAUoQfSOp/oasROv5q/kIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist, cost_matrix, acc_cost_matrix, path = dtw(data[\"agent_tracks\"][287], data[\"agent_tracks\"][324], dist=l2_norm)\n",
    "plt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n",
    "# plt.plot(path[0], path[1], 'w')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist, cost_matrix, acc_cost_matrix, path = dtw(data[\"agent_tracks\"][289], data[\"agent_tracks\"][324], dist=l2_norm)\n",
    "plt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n",
    "plt.plot(path[0], path[1], 'w')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dist, cost_matrix, acc_cost_matrix, path = dtw(data[\"agent_tracks\"][289], data[\"agent_tracks\"][287], dist=l2_norm)\n",
    "plt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n",
    "plt.plot(path[0], path[1], 'w')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen = GenerateSegmentTrajectories(round_number=0, agent_id=324, radius=15, start_index=290, frame_length=25,agent_map_folder=\"../agent_maps\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{51: 10, 262: 25, 275: 25, 314: 23, 324: 25}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gen.generate()\n",
    "\n",
    "data2 = gen.get_trajectory_data()\n",
    "data2[\"agent_track_lens\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[262, 275, 324, 314, 51]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2[\"sorted_agent_ids\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_dtw_map(agent1,agent2,data):\n",
    "    l2_norm = lambda x, y: np.linalg.norm((x - y))\n",
    "    dist, cost_matrix, acc_cost_matrix, path = dtw(data[\"agent_tracks\"][agent1], data[\"agent_tracks\"][agent2], dist=l2_norm)\n",
    "    plt.imshow(acc_cost_matrix.T, origin='lower', cmap='gray', interpolation='nearest')\n",
    "    plt.plot(path[0], path[1], 'w')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_dtw_map(324,262,data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_dtw_map(324,275,data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_dtw_map(324,314,data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25, 25)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acc_cost_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "N=Number of agents in the scenario\n",
    "\n",
    "Autoencoder\n",
    "[N,25,25]->[encoder]->vector->[decoder]->[N,25,25]\n",
    "\n",
    "Classifier\n",
    "[N,25,25]->[encoder]->vector->classifier"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (argoverse)",
   "language": "python",
   "name": "argoverse"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}