Figures for paper.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we are going to load the data from the csv files in the flight data folder\n",
    "# the csv file contains columns of data for each variable\n",
    "# we will load the data into a dict with the key being the variable name\n",
    "# and the value being a np array of the data\n",
    "\n",
    "import numpy as np\n",
    "import csv\n",
    "import pandas as pd\n",
    "\n",
    "def Rmat(phi, theta, psi):\n",
    "    Rx = np.array([[1, 0, 0], [0, np.cos(phi), -np.sin(phi)], [0, np.sin(phi), np.cos(phi)]])\n",
    "    Ry = np.array([[np.cos(theta), 0, np.sin(theta)],[0, 1, 0],[-np.sin(theta), 0, np.cos(theta)]])\n",
    "    Rz = np.array([[np.cos(psi), -np.sin(psi), 0],[np.sin(psi), np.cos(psi), 0], [0, 0, 1]])\n",
    "    R = Rz@Ry@Rx\n",
    "    return R\n",
    "\n",
    "\n",
    "def load_log_file(log_file):\n",
    "    # read rows of the csv file\n",
    "    df = pd.read_csv(log_file)\n",
    "    # convert to dictionary\n",
    "    log_dict = dict()\n",
    "    for key in df.columns:\n",
    "        log_dict.update({key: np.array(df[key])})\n",
    "\n",
    "    # rename the variables\n",
    "    rename_dict = {\n",
    "        'time': 't',\n",
    "        'pos_x': 'x',\n",
    "        'pos_y': 'y',\n",
    "        'pos_z': 'z',\n",
    "        'vel_x': 'vx',\n",
    "        'vel_y': 'vy',\n",
    "        'vel_z': 'vz',\n",
    "        'att_phi': 'phi',\n",
    "        'att_theta': 'theta',\n",
    "        'att_psi': 'psi',\n",
    "        'rate_p': 'p',\n",
    "        'rate_q': 'q',\n",
    "        'rate_r': 'r',\n",
    "        'rpm_obs_1': 'w1',\n",
    "        'rpm_obs_2': 'w2',\n",
    "        'rpm_obs_3': 'w3',\n",
    "        'rpm_obs_4': 'w4',\n",
    "        'rpm_ref_1': 'u1',\n",
    "        'rpm_ref_2': 'u2',\n",
    "        'rpm_ref_3': 'u3',\n",
    "        'rpm_ref_4': 'u4',\n",
    "    }\n",
    "    log_dict.update({rename_dict[key]: log_dict.pop(key) for key in rename_dict.keys()})\n",
    "\n",
    "    # extra variables\n",
    "\n",
    "    # u = normalized rpm commands\n",
    "    log_dict['u'] = np.stack([log_dict['u1'], log_dict['u2'], log_dict['u3'], log_dict['u4']]).T\n",
    "    umin = log_dict['u'].min()\n",
    "    umax = log_dict['u'].max()\n",
    "    log_dict['u'] = (log_dict['u']-umin)/(umax-umin)\n",
    "\n",
    "    # vbx, vby, vbz = body frame velocity\n",
    "    v_body = np.stack([\n",
    "        Rmat(phi, theta, psi).T@[vx, vy, vz]\n",
    "        for vx, vy, vz, phi, theta, psi\n",
    "        in zip(log_dict['vx'],log_dict['vy'],log_dict['vz'],log_dict['phi'],log_dict['theta'],log_dict['psi'])\n",
    "    ])\n",
    "    log_dict['vbx'], log_dict['vby'], log_dict['vbz'] = v_body.T\n",
    "\n",
    "    # speed\n",
    "    log_dict['V'] = np.linalg.norm(v_body, axis=1)\n",
    "\n",
    "    # abx, aby, abz = accelerometer readings body frame\n",
    "    log_dict['abx'] = log_dict['ekf_U1']-log_dict['ekf_X10']\n",
    "    log_dict['aby'] = log_dict['ekf_U2']-log_dict['ekf_X11']\n",
    "    log_dict['abz'] = log_dict['ekf_U3']-log_dict['ekf_X12']\n",
    "\n",
    "    # only log when netork is active\n",
    "    indices = log_dict['autopilot_mode']>0\n",
    "    log_dict = {key: log_dict[key][indices] for key in log_dict.keys()}\n",
    "\n",
    "    # set t=0\n",
    "    log_dict['t'] = log_dict['t']-log_dict['t'][0]\n",
    "\n",
    "    return log_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 'gcnet_switch_1.2m_heavy_bumper.csv'),\n",
       " (1, 'gcnet_switch_1.2m_light_bumper.csv'),\n",
       " (2, 'gcnet_switch_1.2m_no_bumper.csv'),\n",
       " (3, 'min_snap_alpha=1.0_heavy_bumpers_ADAPTIVE_TRUE.csv'),\n",
       " (4, 'min_snap_heavy_bumbers.csv'),\n",
       " (5, 'min_snap_light_bumber.csv'),\n",
       " (6, 'min_snap_no_bumpers.csv')]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "# list all files in flight_data folder\n",
    "folder = '/mnt/c/Users/robinferede/Desktop/flight_data/ppo_network/9sep'\n",
    "folder = '/mnt/c/Users/robinferede/Desktop/flight_data/gcnet_vs_min_snap'\n",
    "# folder = 'flight_data/2sep'\n",
    "files = os.listdir(folder)\n",
    "list(enumerate(files))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "folder = '/mnt/c/Users/robinferede/Desktop/flight_data/ppo_network/'\n",
    "\n",
    "# E2E flights\n",
    "# log_e2e_sim = dict(np.load('flight_data/simulation_logs/E2E_NET_sim.npz'))\n",
    "# log_e2e1 = load_log_file(folder+'2sep/new_drone_ppo_end_to_end.csv')\n",
    "# log_e2e2 = load_log_file(folder+'8sep/SuccesfullE2E_with_nn_drone_model.csv') \n",
    "# log_e2e3 = load_log_file(folder+'9sep/E2E_test1.csv') \n",
    "# log_e2e4 = load_log_file(folder+'9sep/E2E_test2.csv') \n",
    "# log_e2e5 = load_log_file(folder+'9sep/E2E_test3[new_drone].csv') # FASTEST\n",
    "\n",
    "# ALTERNATIVE E2E flights\n",
    "log_e2e_sim = dict(np.load('flight_data/simulation_logs/E2E_NET_sim_with_gate_penalty.npz'))\n",
    "log_e2e1 = load_log_file(folder+'11sep/E2E1.csv')\n",
    "log_e2e2 = load_log_file(folder+'11sep/E2E2.csv')\n",
    "log_e2e3 = load_log_file(folder+'11sep/E2E3.csv')\n",
    "log_e2e4 = load_log_file(folder+'11sep/E2E4.csv')\n",
    "log_e2e5 = load_log_file(folder+'11sep/E2E5.csv')\n",
    "\n",
    "\n",
    "# INDI flights\n",
    "# log_INDI_sim = dict(np.load('flight_data/simulation_logs/INDI_NET_sim.npz'))\n",
    "# log_INDI1 = load_log_file(folder+'7sep/INDInet_no_rate_penalty_pq3.csv')\n",
    "# log_INDI2 = load_log_file(folder+'7sep/new_drone_INDI_low_lim.csv') # FASTEST\n",
    "# log_INDI3 = load_log_file(folder+'8sep/INDI_net_pqlim=3.csv')\n",
    "# log_INDI4 = load_log_file(folder+'9sep/INDI_test1.csv')\n",
    "# log_INDI5 = load_log_file(folder+'9sep/INDI_test_2[new_drone].csv')\n",
    "\n",
    "# ALTERNATIVE INDI flights\n",
    "log_INDI_sim = dict(np.load('flight_data/simulation_logs/INDI_NET_sim_with_gate_penalty.npz'))\n",
    "log_INDI1 = load_log_file(folder+'11sep/INDI1.csv')\n",
    "log_INDI2 = load_log_file(folder+'11sep/INDI2.csv')\n",
    "log_INDI3 = load_log_file(folder+'11sep/INDI3.csv')\n",
    "log_INDI4 = load_log_file(folder+'11sep/INDI4.csv')\n",
    "log_INDI5 = load_log_file(folder+'11sep/INDI5.csv')\n",
    "\n",
    "# MIN_SNAP flight\n",
    "# npz_file = folder+'9sep/min_snap_fastest.npz'\n",
    "# log_MIN_SNAP = dict(np.load(npz_file))\n",
    "# log_MIN_SNAP['z'] -= .5\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib as mpl\n",
    "\n",
    "from quadcopter_animation import animation\n",
    "\n",
    "# color map\n",
    "norm_ = mpl.colors.Normalize(0, 7)\n",
    "cmap_ = cm.jet\n",
    "\n",
    "# hard coded gate pos, yaw\n",
    "gate_pos = np.array([\n",
    "    [ 2,-1.5,-1.5],\n",
    "    [ 2, 1.5,-1.5],\n",
    "    [-2, 1.5,-1.5],\n",
    "    [-2,-1.5,-1.5]\n",
    "])\n",
    "\n",
    "gate_yaw = np.array([\n",
    "    1*np.pi/4,\n",
    "    3*np.pi/4,\n",
    "    5*np.pi/4,\n",
    "    7*np.pi/4\n",
    "])\n",
    "\n",
    "def color_plot(x_axis, y_axis, color_axis, step=10):\n",
    "    for i in reversed(range(step,len(x_axis),step)):\n",
    "        ax = plt.gca()\n",
    "        ax.plot([x_axis[i-step], x_axis[i]], [y_axis[i-step], y_axis[i]], color=cmap_(norm_(color_axis[i])))\n",
    "\n",
    "def plot_gate(x,y,yaw):\n",
    "    r = 0.5\n",
    "    right_side = np.array([x+r*np.cos(yaw+np.pi/2), y+r*np.sin(yaw+np.pi/2)])\n",
    "    left_side = np.array([x+r*np.cos(yaw-np.pi/2), y+r*np.sin(yaw-np.pi/2)])\n",
    "\n",
    "    plt.scatter(right_side[0], right_side[1], color='k', zorder=3)\n",
    "    plt.scatter(left_side[0], left_side[1], color='k', zorder=3)\n",
    "    plt.plot([right_side[0], left_side[0]], [right_side[1], left_side[1]], color='k', linestyle='--')\n",
    "\n",
    "def top_view_plot(log_dict, title='', step=10, color_bar=True):\n",
    "    # plt.figure(figsize=(5,5))\n",
    "    color_plot(log_dict['y'], log_dict['x'], log_dict['V'], step=step)\n",
    "    \n",
    "    # hard coded gate visualisation\n",
    "    plot_gate(-1.5, 2, 1*np.pi/4)\n",
    "    plot_gate( 1.5, 2, 3*np.pi/4)\n",
    "    plot_gate( 1.5,-2, 5*np.pi/4)\n",
    "    plot_gate(-1.5,-2, 7*np.pi/4)\n",
    "\n",
    "    plt.xlabel('y [m]')\n",
    "    plt.ylabel('x [m]')\n",
    "    plt.axis('equal')\n",
    "    plt.grid(True)\n",
    "    plt.title(title, fontweight='bold')\n",
    "\n",
    "    # colorbar\n",
    "    sm = plt.cm.ScalarMappable(cmap=cmap_, norm=norm_)\n",
    "    sm.set_array([])\n",
    "    if color_bar == 'left':\n",
    "        plt.colorbar(sm, label='V [m/s]', location='left')\n",
    "    elif color_bar:\n",
    "        plt.colorbar(sm, label='V [m/s]')\n",
    "    # plt.show()\n",
    "\n",
    "def animate_side_by_side(*trajs, **kwargs):\n",
    "    import importlib\n",
    "    importlib.reload(animation)    \n",
    "    animation.animate(\n",
    "        [traj['t'] for traj in trajs],\n",
    "        [traj['x'] for traj in trajs],\n",
    "        [traj['y'] for traj in trajs],\n",
    "        [traj['z'] for traj in trajs],\n",
    "        [traj['phi'] for traj in trajs],\n",
    "        [traj['theta'] for traj in trajs],\n",
    "        [traj['psi'] for traj in trajs],\n",
    "        [traj['u'] for traj in trajs],\n",
    "        multiple_trajectories=True,\n",
    "        simultaneous=True,\n",
    "        **kwargs\n",
    "    )\n",
    "\n",
    "def get_gate_passage_times(traj, num_gates=4*6):\n",
    "    t = traj['t']\n",
    "    x = traj['x']\n",
    "    y = traj['y']\n",
    "    target = 0\n",
    "    gate_passage_times = [0]\n",
    "    for i in range(1, len(t)):\n",
    "        target_pos = gate_pos[target][0:2]\n",
    "        target_yaw = gate_yaw[target]\n",
    "\n",
    "        pos_new = np.array([x[i], y[i]])\n",
    "        pos_old = np.array([x[i-1], y[i-1]])\n",
    "\n",
    "        # check if the drone passed the gate\n",
    "        normal = np.array([np.cos(target_yaw), np.sin(target_yaw)])\n",
    "        if np.dot(normal, pos_new-target_pos) > 0 and np.dot(normal, pos_old-target_pos) < 0:\n",
    "            gate_passage_times.append(t[i])\n",
    "            target += 1\n",
    "            target = target%len(gate_pos)\n",
    "        \n",
    "        # stop after passing num_laps gates\n",
    "        if len(gate_passage_times) > num_gates:\n",
    "            break\n",
    "    return gate_passage_times\n",
    "\n",
    "def get_lap_times(traj):\n",
    "    gate_passage_times = np.array(get_gate_passage_times(traj))\n",
    "    lap_times = gate_passage_times[4::4] - gate_passage_times[:-4:4]\n",
    "    return lap_times\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.227534, 2.793943, 2.806637, 2.835934, 2.8418  , 2.831055])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_lap_times(log_e2e1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cut the trajectories to 6 laps\n",
    "indices_e2e_sim = log_e2e_sim['t'] <= get_gate_passage_times(log_e2e_sim)[-1]\n",
    "indices_e2e1 = log_e2e1['t'] <= get_gate_passage_times(log_e2e1)[-1]\n",
    "indices_e2e2 = log_e2e2['t'] <= get_gate_passage_times(log_e2e2)[-1]\n",
    "indices_e2e3 = log_e2e3['t'] <= get_gate_passage_times(log_e2e3)[-1]\n",
    "indices_e2e4 = log_e2e4['t'] <= get_gate_passage_times(log_e2e4)[-1]\n",
    "indices_e2e5 = log_e2e5['t'] <= get_gate_passage_times(log_e2e5)[-1]\n",
    "\n",
    "indices_INDI_sim = log_INDI_sim['t'] <= get_gate_passage_times(log_INDI_sim)[-1]\n",
    "indices_INDI1 = log_INDI1['t'] <= get_gate_passage_times(log_INDI1)[-1]\n",
    "indices_INDI2 = log_INDI2['t'] <= get_gate_passage_times(log_INDI2)[-1]\n",
    "indices_INDI3 = log_INDI3['t'] <= get_gate_passage_times(log_INDI3)[-1]\n",
    "indices_INDI4 = log_INDI4['t'] <= get_gate_passage_times(log_INDI4)[-1]\n",
    "indices_INDI5 = log_INDI5['t'] <= get_gate_passage_times(log_INDI5)[-1]\n",
    "\n",
    "# cut the trajectories to 6 laps\n",
    "log_e2e_sim = {key: log_e2e_sim[key][indices_e2e_sim] for key in log_e2e_sim.keys()}\n",
    "log_e2e1 = {key: log_e2e1[key][indices_e2e1] for key in log_e2e1.keys()}\n",
    "log_e2e2 = {key: log_e2e2[key][indices_e2e2] for key in log_e2e2.keys()}\n",
    "log_e2e3 = {key: log_e2e3[key][indices_e2e3] for key in log_e2e3.keys()}\n",
    "log_e2e4 = {key: log_e2e4[key][indices_e2e4] for key in log_e2e4.keys()}\n",
    "log_e2e5 = {key: log_e2e5[key][indices_e2e5] for key in log_e2e5.keys()}\n",
    "\n",
    "log_INDI_sim = {key: log_INDI_sim[key][indices_INDI_sim] for key in log_INDI_sim.keys()}\n",
    "log_INDI1 = {key: log_INDI1[key][indices_INDI1] for key in log_INDI1.keys()}\n",
    "log_INDI2 = {key: log_INDI2[key][indices_INDI2] for key in log_INDI2.keys()}\n",
    "log_INDI3 = {key: log_INDI3[key][indices_INDI3] for key in log_INDI3.keys()}\n",
    "log_INDI4 = {key: log_INDI4[key][indices_INDI4] for key in log_INDI4.keys()}\n",
    "log_INDI5 = {key: log_INDI5[key][indices_INDI5] for key in log_INDI5.keys()}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "animate_side_by_side(\n",
    "    log_e2e1,\n",
    "    log_e2e2,\n",
    "    log_e2e3,\n",
    "    log_e2e4,\n",
    "    log_e2e5,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(255,0,0), (0,255,0), (0,0,255), (255,255,0), (0,255,255)],\n",
    "    names=['E2E1', 'E2E2', 'E2E3', 'E2E4', 'E2E5'],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# E2E2 wins, 6 laps\n",
    "log_e2e_fastest = log_e2e2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "animate_side_by_side(\n",
    "    log_INDI1,\n",
    "    log_INDI2,\n",
    "    log_INDI3,\n",
    "    log_INDI4,\n",
    "    log_INDI5,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(255,0,0), (0,255,0), (0,0,255), (255,255,0), (0,255,255)],\n",
    "    names=['INDI1', 'INDI2', 'INDI3', 'INDI4', 'INDI5'],\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# INDI2 wins, 6 laps\n",
    "log_INDI_fastest = log_INDI2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n",
      "QObject::moveToThread: Current thread (0x19f3f40) is not the object's thread (0xf52920).\n",
      "Cannot move to target thread (0x19f3f40)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "animate_side_by_side(\n",
    "    log_e2e_fastest, log_INDI_fastest,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(255,0,0),(0,255,0)],\n",
    "    names=['E2E Net', 'INDI'],\n",
    ")\n",
    "\n",
    "animate_side_by_side(\n",
    "    log_e2e_fastest, log_e2e_sim,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(255,0,0),(0,255,0)],\n",
    "    names=['E2E Net', 'E2E Net Sim'],\n",
    ")\n",
    "\n",
    "animate_side_by_side(\n",
    "    log_INDI_fastest, log_INDI_sim,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(255,0,0),(0,255,0)],\n",
    "    names=['INDI Net', 'INDI Net Sim'],\n",
    ")\n",
    "\n",
    "animate_side_by_side(\n",
    "    log_e2e_sim, log_INDI_sim,\n",
    "    gate_pos=gate_pos,\n",
    "    gate_yaw=gate_yaw,\n",
    "    colors=[(0,255,0), (255,0,0)],\n",
    "    names=['E2E Net', 'INDI Net'],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top view plots fastest networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_615/1974450401.py:60: MatplotlibDeprecationWarning: Unable to determine Axes to steal space for Colorbar. Using gca(), but will raise in the future. Either provide the *cax* argument to use as the Axes for the Colorbar, provide the *ax* argument to steal space from it, or add *mappable* to an Axes.\n",
      "  plt.colorbar(sm, label='V [m/s]', location='left')\n",
      "/tmp/ipykernel_615/2641298080.py:42: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2 x 2 subplots\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12,8), constrained_layout=True, gridspec_kw={'width_ratios': [3,3]})\n",
    "plt.sca(axs[0,0])\n",
    "T = get_lap_times(log_e2e_sim).sum()\n",
    "top_view_plot(log_e2e_sim, title=f'E2E Sim' , step=1, color_bar='left')\n",
    "plt.text(0.99, 0.99, f'Total time: {T:.2f} s', horizontalalignment='right', verticalalignment='top', transform=axs[0,0].transAxes)\n",
    "plt.sca(axs[0,1])\n",
    "T = get_lap_times(log_INDI_sim).sum()\n",
    "top_view_plot(log_INDI_sim, title=f'INDI Sim', step=1, color_bar=False)\n",
    "plt.text(0.99, 0.99, f'Total time: {T:.2f} s', horizontalalignment='right', verticalalignment='top', transform=axs[0,1].transAxes)\n",
    "plt.sca(axs[1,0])\n",
    "T = get_lap_times(log_e2e_fastest).sum()\n",
    "top_view_plot(log_e2e_fastest, title=f'E2E Real [fastest]', step=1, color_bar='left')\n",
    "plt.text(0.99, 0.99, f'Total time: {T:.2f} s', horizontalalignment='right', verticalalignment='top', transform=axs[1,0].transAxes)\n",
    "plt.sca(axs[1,1])\n",
    "T = get_lap_times(log_INDI_fastest).sum()\n",
    "top_view_plot(log_INDI_fastest, title=f'INDI Real [fastest]', step=1, color_bar=False)\n",
    "plt.text(0.99, 0.99, f'Total time: {T:.2f} s', horizontalalignment='right', verticalalignment='top', transform=axs[1,1].transAxes)\n",
    "# plt.sca(axs[0,2])\n",
    "# boxsplot of laptimes ALSO SHOW DATAPOINTS\n",
    "# plt.boxplot(\n",
    "#     [get_lap_times(log_e2e_sim), get_lap_times(log_INDI_sim)],\n",
    "#     labels=['E2E', 'INDI'],\n",
    "# )\n",
    "# plt.ylabel('t [s]')\n",
    "# plt.grid(True)\n",
    "# plt.title('Lap times Sim', fontweight='bold')\n",
    "# plt.sca(axs[1,2])\n",
    "# plt.boxplot(\n",
    "#     [get_lap_times(log_e2e_fastest), get_lap_times(log_INDI_fastest)],\n",
    "#     labels=['E2E', 'INDI'],\n",
    "# )\n",
    "# plt.ylabel('t [s]')\n",
    "# plt.grid(True)\n",
    "# plt.title('Lap times Real', fontweight='bold')\n",
    "\n",
    "# axs[0,2] and axs[1,2] share y axis\n",
    "# axs[0,2].get_shared_y_axes().join(axs[0,2], axs[1,2])\n",
    "\n",
    "# save into figures folder\n",
    "fig.savefig('Figures/top_view_comparison.pdf')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot showing all performed flights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_615/2201227245.py:136: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def progress_comparison_plot(*trajs, **kwargs):\n",
    "    gate_passage_times = []\n",
    "    for traj in trajs:\n",
    "        gate_passage_times.append(get_gate_passage_times(traj, num_gates=kwargs['num_laps']*4))\n",
    "    gate_passage_times = np.array(gate_passage_times).T\n",
    "    gate_passage_times_relative = np.array([gt - min(gt) for gt in gate_passage_times])\n",
    "\n",
    "    # for i in range(len(kwargs['names'])):\n",
    "    #     name = kwargs['names'][i]\n",
    "    #     alpha = kwargs['alphas'][i]\n",
    "    #     if alpha == 1:\n",
    "    #         kwargs['names'][i] += ' [fastest]'\n",
    "\n",
    "    # subplots\n",
    "    fig, ax = plt.subplots(1,4, figsize=kwargs['figsize'], gridspec_kw={'width_ratios': [1,1,1,5]}, constrained_layout=True)\n",
    "\n",
    "    # box plots of laptimes\n",
    "    lap_times = np.array([get_lap_times(traj) for traj in trajs])\n",
    "\n",
    "    lap_tiems_E2E = np.array([lap_times[i] for i in range(len(lap_times)) if kwargs['names'][i].startswith('E2E')])\n",
    "    lap_tiems_INDI = np.array([lap_times[i] for i in range(len(lap_times)) if kwargs['names'][i].startswith('INDI')])\n",
    "\n",
    "    # ax[0] will show a box plot of the first lap times (include scatter plot of data points)\n",
    "    alpha_scatter = 0.2\n",
    "    ax[0].scatter(np.ones(len(lap_tiems_E2E[:,0]))*0, lap_tiems_E2E[:,0], color='b', alpha=alpha_scatter)\n",
    "    ax[0].scatter(np.ones(len(lap_tiems_INDI[:,0]))*1, lap_tiems_INDI[:,0], color='g', alpha=alpha_scatter)\n",
    "    ax[0].boxplot(lap_tiems_E2E[:,0], positions=[0], labels=['E2E'])\n",
    "    ax[0].boxplot(lap_tiems_INDI[:,0], positions=[1], labels=['INDI'])\n",
    "    ax[0].set_ylabel('time [s]')\n",
    "    ax[0].grid(True)\n",
    "    # sub title\n",
    "    ax[0].set_title('Lap 1', fontweight='bold')\n",
    "\n",
    "    # ax[1] will show a box plot of the lap 2-6 lumped together\n",
    "    ax[1].scatter(np.ones(len(lap_tiems_E2E[:,1:].flatten()))*0, lap_tiems_E2E[:,1:].flatten(), color='b', alpha=alpha_scatter)\n",
    "    ax[1].scatter(np.ones(len(lap_tiems_INDI[:,1:].flatten()))*1, lap_tiems_INDI[:,1:].flatten(), color='g', alpha=alpha_scatter)\n",
    "    ax[1].boxplot(lap_tiems_E2E[:,1:].flatten(), positions=[0], labels=['E2E'])\n",
    "    ax[1].boxplot(lap_tiems_INDI[:,1:].flatten(), positions=[1], labels=['INDI'])\n",
    "    ax[1].set_ylabel('time [s]')\n",
    "    ax[1].grid(True)\n",
    "    # sub title\n",
    "    ax[1].set_title('Lap 2-6', fontweight='bold')\n",
    "\n",
    "    # ax[2] will show a box plot of the lap completion times (sum of lap times)\n",
    "    ax[2].scatter(np.ones(len(lap_tiems_E2E.sum(axis=1)))*0, lap_tiems_E2E.sum(axis=1), color='b', alpha=alpha_scatter)\n",
    "    ax[2].scatter(np.ones(len(lap_tiems_INDI.sum(axis=1)))*1, lap_tiems_INDI.sum(axis=1), color='g', alpha=alpha_scatter)\n",
    "    ax[2].boxplot(lap_tiems_E2E.sum(axis=1), positions=[0], labels=['E2E'])\n",
    "    ax[2].boxplot(lap_tiems_INDI.sum(axis=1), positions=[1], labels=['INDI'])\n",
    "    ax[2].set_ylabel('time [s]')\n",
    "    ax[2].grid(True)\n",
    "    # sub title\n",
    "    ax[2].set_title('Total time', fontweight='bold')\n",
    "\n",
    "    # box plots of laptimes\n",
    "    # lap_times = np.array([get_lap_times(traj) for traj in trajs])\n",
    "\n",
    "    # lap_tiems_E2E = np.array([lap_times[i] for i in range(len(lap_times)) if kwargs['names'][i].startswith('E2E')])\n",
    "    # lap_tiems_INDI = np.array([lap_times[i] for i in range(len(lap_times)) if kwargs['names'][i].startswith('INDI')])\n",
    "    # for i in range(kwargs['num_laps']):\n",
    "    #     # no outliers\n",
    "    #     ax[0].scatter(np.ones(len(lap_tiems_E2E[:,i]))*2*i, lap_tiems_E2E[:,i], color='b', alpha=0.5)\n",
    "    #     ax[0].scatter(np.ones(len(lap_tiems_INDI[:,i]))*2*i+1, lap_tiems_INDI[:,i], color='g', alpha=0.5)\n",
    "    #     ax[0].boxplot(lap_tiems_E2E[:,i], positions=[2*i], labels=['E2E'])\n",
    "    #     ax[0].boxplot(lap_tiems_INDI[:,i], positions=[2*i+1], labels=['INDI'])\n",
    "    #     # vertical line at 2i+1.5 to separate the boxplots (dotted line)\n",
    "    #     ax[0].axvline(2*i+1.5, color='k', linestyle='--', zorder=0)\n",
    "    #     ymin, ymax = ax[0].get_ylim()\n",
    "    #     ypos = ymin + (ymax-ymin)*.8\n",
    "    #     ax[0].text(i*2, ypos, f'lap {i+1}', rotation=0, verticalalignment='bottom', fontweight='bold')\n",
    "\n",
    "    # ax[0].set_ylabel('lap time [s]')\n",
    "    # # set ylim to 0, 3.4\n",
    "    # ax[0].grid(True)\n",
    "    # # ax[0].legend()\n",
    "\n",
    "    # time plot\n",
    "    # for i in range(len(trajs)):\n",
    "    #     ax[0].plot(gate_passage_times[:,i], label=kwargs['names'][i], color=kwargs['colors'][i], alpha=kwargs['alphas'][i], linestyle=kwargs['line_style'][i])\n",
    "    # for i in range(1, kwargs['num_laps']+1):\n",
    "    #     ax[0].axvline(i*4, color='k', linestyle='--', zorder=0)\n",
    "    #     ymin, ymax = ax[0].get_ylim()\n",
    "    #     ypos = ymin + (ymax-ymin)*.8\n",
    "    #     ax[0].text(i*4-1, ypos, f'lap {i}', rotation=90, verticalalignment='bottom', fontweight='bold')\n",
    "    # ax[0].set_xlabel('number of gates passed')\n",
    "    # ax[0].set_ylabel('time [s]')\n",
    "    # ax[0].set_xticks(np.arange(0, kwargs['num_laps']*4+1, 4))\n",
    "    # ax[0].grid(True)\n",
    "    # handles, labels = ax[0].get_legend_handles_labels()\n",
    "    # by_label = dict(zip(labels, handles))\n",
    "    # # put the legend on the bottom right\n",
    "    # ax[0].legend(by_label.values(), by_label.keys(), loc='lower right')\n",
    "\n",
    "    # relative time plot\n",
    "    axi = ax[3]\n",
    "    for i in range(len(trajs)):\n",
    "        axi.plot(gate_passage_times_relative[:,i], label=kwargs['names'][i], color=kwargs['colors'][i], alpha=kwargs['alphas'][i], linestyle=kwargs['line_style'][i])\n",
    "    for i in range(1, kwargs['num_laps']+1):\n",
    "        axi.axvline(i*4, color='k', linestyle='--', zorder=0)\n",
    "        ymin, ymax = axi.get_ylim()\n",
    "        ypos = ymin + (ymax-ymin)*.9\n",
    "        axi.text(i*4-3, ypos, f'lap {i}', rotation=0, verticalalignment='bottom', fontweight='bold')\n",
    "    axi.set_xlabel('number of gates passed')\n",
    "    axi.set_ylabel('time behind fastest drone [s]')\n",
    "    axi.set_xticks(np.arange(0, kwargs['num_laps']*4+1, 4))\n",
    "    axi.grid(True)\n",
    "    \n",
    "    # update names\n",
    "    # lap time boxplot\n",
    "    lap_times = gate_passage_times[4::4] - gate_passage_times[:-4:4]\n",
    "    lap_times_dict = {}\n",
    "    for name in kwargs['names']:\n",
    "        # if name ends with \" [fastest]\" remove it\n",
    "        if name.endswith(' [fastest]'):\n",
    "            name = name[:-10]\n",
    "        if name in lap_times_dict.keys():\n",
    "            lap_times_dict[name] += list(lap_times[:,kwargs['names'].index(name)])\n",
    "        else:\n",
    "            lap_times_dict[name] = list(lap_times[:,kwargs['names'].index(name)])\n",
    "    handles, labels = axi.get_legend_handles_labels()\n",
    "    by_label = dict(zip(labels, handles))\n",
    "    # put the legend on the top left (move the legend down)\n",
    "    axi.legend(by_label.values(), by_label.keys(), loc='upper left', bbox_to_anchor=(0,1.1-0.3))\n",
    "    # sub title\n",
    "    axi.set_title('Relative progress', fontweight='bold')\n",
    "\n",
    "    # pos = 0\n",
    "    # for name in lap_times_dict.keys():\n",
    "    #     ax[2].boxplot(lap_times_dict[name], positions=[pos], labels=[name])\n",
    "    #     pos += 1\n",
    "    # ax[2].set_ylabel('lap time [s]')\n",
    "    # ax[2].grid(True)\n",
    "    # ax[2].legend()\n",
    "    fig.suptitle('E2E vs INDI real flights', fontweight='bold')\n",
    "    # save\n",
    "    fig.savefig('Figures/performance_comparison_plot.pdf')\n",
    "    fig.show()\n",
    "\n",
    "la = 0.3\n",
    "\n",
    "progress_comparison_plot(\n",
    "    log_e2e1, log_e2e2, log_e2e3, log_e2e4, log_e2e5,\n",
    "    log_INDI1, log_INDI2, log_INDI3, log_INDI4, log_INDI5,\n",
    "    num_laps=6,\n",
    "    names=['E2E', 'E2E [fastest]', 'E2E', 'E2E', 'E2E', 'INDI', 'INDI [fastest]', 'INDI', 'INDI', 'INDI'],\n",
    "    alphas=[la, 1, la, la, la, la, 1, la, la, la],\n",
    "    line_style = ['solid', 'solid', 'solid', 'solid', 'solid', 'solid', 'solid', 'solid', 'solid', 'solid'],\n",
    "    colors=['b']*6+['g']*6,\n",
    "    figsize=(12,4)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Table of all laptimes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "lap_times_dict = {\n",
    "    'e2e_sim': get_lap_times(log_e2e_sim),\n",
    "    'e2e1': get_lap_times(log_e2e1),\n",
    "    'e2e2': get_lap_times(log_e2e2),\n",
    "    'e2e3': get_lap_times(log_e2e3),\n",
    "    'e2e4': get_lap_times(log_e2e4),\n",
    "    'e2e5': get_lap_times(log_e2e5),\n",
    "    'INDI_sim': get_lap_times(log_INDI_sim),\n",
    "    'INDI1': get_lap_times(log_INDI1),\n",
    "    'INDI2': get_lap_times(log_INDI2),\n",
    "    'INDI3': get_lap_times(log_INDI3),\n",
    "    'INDI4': get_lap_times(log_INDI4),\n",
    "    'INDI5': get_lap_times(log_INDI5),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>lap1</th>\n",
       "      <th>lap2</th>\n",
       "      <th>lap3</th>\n",
       "      <th>lap4</th>\n",
       "      <th>lap5</th>\n",
       "      <th>lap6</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>E2E Sim</th>\n",
       "      <td>2.97</td>\n",
       "      <td>2.51</td>\n",
       "      <td>2.56</td>\n",
       "      <td>2.55</td>\n",
       "      <td>2.59</td>\n",
       "      <td>2.57</td>\n",
       "      <td>15.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E1</th>\n",
       "      <td>3.23</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.81</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.83</td>\n",
       "      <td>17.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E2</th>\n",
       "      <td>3.22</td>\n",
       "      <td>2.74</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.79</td>\n",
       "      <td>17.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E3</th>\n",
       "      <td>3.20</td>\n",
       "      <td>2.73</td>\n",
       "      <td>2.91</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.85</td>\n",
       "      <td>2.83</td>\n",
       "      <td>17.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E4</th>\n",
       "      <td>3.22</td>\n",
       "      <td>2.85</td>\n",
       "      <td>2.89</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.81</td>\n",
       "      <td>17.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E5</th>\n",
       "      <td>3.24</td>\n",
       "      <td>2.81</td>\n",
       "      <td>2.85</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.88</td>\n",
       "      <td>17.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI Sim</th>\n",
       "      <td>3.20</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.81</td>\n",
       "      <td>2.76</td>\n",
       "      <td>17.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI1</th>\n",
       "      <td>3.30</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.91</td>\n",
       "      <td>2.79</td>\n",
       "      <td>17.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI2</th>\n",
       "      <td>3.26</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.77</td>\n",
       "      <td>17.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI3</th>\n",
       "      <td>3.25</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.83</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.84</td>\n",
       "      <td>17.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI4</th>\n",
       "      <td>3.27</td>\n",
       "      <td>2.78</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.83</td>\n",
       "      <td>2.83</td>\n",
       "      <td>17.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI5</th>\n",
       "      <td>3.31</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.81</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.94</td>\n",
       "      <td>17.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E2E mean</th>\n",
       "      <td>3.22</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.85</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.83</td>\n",
       "      <td>17.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDI mean</th>\n",
       "      <td>3.28</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.83</td>\n",
       "      <td>17.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           lap1  lap2  lap3  lap4  lap5  lap6  total\n",
       "E2E Sim    2.97  2.51  2.56  2.55  2.59  2.57  15.75\n",
       "E2E1       3.23  2.79  2.81  2.84  2.84  2.83  17.34\n",
       "E2E2       3.22  2.74  2.79  2.80  2.76  2.79  17.09\n",
       "E2E3       3.20  2.73  2.91  2.76  2.85  2.83  17.28\n",
       "E2E4       3.22  2.85  2.89  2.87  2.87  2.81  17.50\n",
       "E2E5       3.24  2.81  2.85  2.86  2.87  2.88  17.52\n",
       "INDI Sim   3.20  2.82  2.75  2.80  2.81  2.76  17.14\n",
       "INDI1      3.30  2.86  2.80  2.86  2.91  2.79  17.51\n",
       "INDI2      3.26  2.79  2.80  2.79  2.84  2.77  17.26\n",
       "INDI3      3.25  2.80  2.83  2.86  2.76  2.84  17.35\n",
       "INDI4      3.27  2.78  2.82  2.76  2.83  2.83  17.29\n",
       "INDI5      3.31  2.80  2.86  2.81  2.87  2.94  17.58\n",
       "E2E mean   3.22  2.79  2.85  2.82  2.84  2.83  17.35\n",
       "INDI mean  3.28  2.80  2.82  2.82  2.84  2.83  17.40"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a table showing the lap times\n",
    "import pandas as pd\n",
    "df = pd.DataFrame(lap_times_dict)\n",
    "df = df[['e2e_sim', 'e2e1', 'e2e2', 'e2e3', 'e2e4', 'e2e5', 'INDI_sim', 'INDI1', 'INDI2', 'INDI3', 'INDI4', 'INDI5']]\n",
    "# the first column should show the lap1, lap2, lap3, etc\n",
    "df.index = ['lap'+str(i) for i in range(1,7)]\n",
    "# add one row with the total time called 'total'\n",
    "df.loc['total'] = df.sum()\n",
    "\n",
    "\n",
    "# rename the columns\n",
    "df = df.rename(columns={\n",
    "    'e2e_sim': 'E2E Sim',\n",
    "    'e2e1': 'E2E1',\n",
    "    'e2e2': 'E2E2',\n",
    "    'e2e3': 'E2E3',\n",
    "    'e2e4': 'E2E4',\n",
    "    'e2e5': 'E2E5',\n",
    "    'INDI_sim': 'INDI Sim',\n",
    "    'INDI1': 'INDI1',\n",
    "    'INDI2': 'INDI2',\n",
    "    'INDI3': 'INDI3',\n",
    "    'INDI4': 'INDI4',\n",
    "    'INDI5': 'INDI5',\n",
    "})\n",
    "\n",
    "# transpose table\n",
    "df = df.T\n",
    "\n",
    "# add row E2Emean and INDI mean\n",
    "df.loc['E2E mean'] = df.loc[['E2E1', 'E2E2', 'E2E3', 'E2E4', 'E2E5']].mean()\n",
    "df.loc['INDI mean'] = df.loc[['INDI1', 'INDI2', 'INDI3', 'INDI4', 'INDI5']].mean()\n",
    "\n",
    "# show everythign with 2 decimals\n",
    "df = df.round(2)\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|c|}\n",
      "\\toprule\n",
      " & lap1 & lap2 & lap3 & lap4 & lap5 & lap6 & total \\\\\n",
      "\\midrule\n",
      "E2E Sim & 2.97 & 2.51 & 2.56 & 2.55 & 2.59 & 2.57 & 15.75 \\\\\n",
      "E2E1 & 3.23 & 2.79 & 2.81 & 2.84 & 2.84 & 2.83 & 17.34 \\\\\n",
      "E2E2 & 3.22 & 2.74 & 2.79 & 2.80 & 2.76 & 2.79 & 17.09 \\\\\n",
      "E2E3 & 3.20 & 2.73 & 2.91 & 2.76 & 2.85 & 2.83 & 17.28 \\\\\n",
      "E2E4 & 3.22 & 2.85 & 2.89 & 2.87 & 2.87 & 2.81 & 17.50 \\\\\n",
      "E2E5 & 3.24 & 2.81 & 2.85 & 2.86 & 2.87 & 2.88 & 17.52 \\\\\n",
      "INDI Sim & 3.20 & 2.82 & 2.75 & 2.80 & 2.81 & 2.76 & 17.14 \\\\\n",
      "INDI1 & 3.30 & 2.86 & 2.80 & 2.86 & 2.91 & 2.79 & 17.51 \\\\\n",
      "INDI2 & 3.26 & 2.79 & 2.80 & 2.79 & 2.84 & 2.77 & 17.26 \\\\\n",
      "INDI3 & 3.25 & 2.80 & 2.83 & 2.86 & 2.76 & 2.84 & 17.35 \\\\\n",
      "INDI4 & 3.27 & 2.78 & 2.82 & 2.76 & 2.83 & 2.83 & 17.29 \\\\\n",
      "INDI5 & 3.31 & 2.80 & 2.86 & 2.81 & 2.87 & 2.94 & 17.58 \\\\\n",
      "E2E mean & 3.22 & 2.79 & 2.85 & 2.82 & 2.84 & 2.83 & 17.35 \\\\\n",
      "INDI mean & 3.28 & 2.80 & 2.82 & 2.82 & 2.84 & 2.83 & 17.40 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# latex table with 2 decimals and use lines between rows\n",
    "latex_table = df.to_latex(float_format=\"%.2f\", multirow=True, multicolumn=True, multicolumn_format='c', column_format='|c|c|c|c|c|c|c|c|c|c|c|c|')\n",
    "\n",
    "print(latex_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reality Gap plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# E2E actuator modeling error\n",
    "\n",
    "def first_order_delay(u, x0, dt, tau):\n",
    "    x = np.zeros(len(u))\n",
    "    x[0] = x0\n",
    "    for i in range(1, len(u)):\n",
    "        x[i] = x[i-1] + (u[i-1] - x[i-1]) * dt / tau\n",
    "    return x\n",
    "\n",
    "tau = 0.06\n",
    "a=0.5\n",
    "def plot_actuator_model_error(log_dict):\n",
    "    t = log_dict['t']\n",
    "    dt = np.mean(np.gradient(t))\n",
    "    # 4x1 subplot showing command, obsevered and modeled rpm of each prop\n",
    "    fig, axs = plt.subplots(4, 1, figsize=(6,4), sharex=True)\n",
    "    plt.sca(axs[0])\n",
    "    plt.plot(t, log_dict['u1'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['w1'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['u1'], log_dict['w1'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('rpm')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[1])\n",
    "    plt.plot(t, log_dict['u2'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['w2'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['u2'], log_dict['w2'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('rpm')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[2])\n",
    "    plt.plot(t, log_dict['u3'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['w3'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['u3'], log_dict['w3'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('rpm')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[3])\n",
    "    plt.plot(t, log_dict['u4'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['w4'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['u4'], log_dict['w4'][0], dt, tau), label='modeled')\n",
    "    plt.xlabel('time [s]')\n",
    "    plt.ylabel('rpm')\n",
    "    \n",
    "    plt.legend(loc='lower right')\n",
    "    # set xlim\n",
    "    plt.xlim([0,2])\n",
    "    fig.suptitle('Actuator modeling error', fontweight='bold')\n",
    "    fig.savefig('Figures/actuator_modeling_error.pdf')\n",
    "    fig.show()\n",
    "\n",
    "plot_actuator_model_error(log_e2e_fastest)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import signal\n",
    "# INDI modeling errors\n",
    "tau=0.03\n",
    "a=0.5\n",
    "def plot_INDI_model_error(log_dict):\n",
    "    t = log_dict['t']\n",
    "    dt = np.mean(np.gradient(t))\n",
    "\n",
    "    # get thrust\n",
    "    T = -log_dict['abz']\n",
    "    cutoff_freq = 16 #Hz\n",
    "    sos = signal.butter(2, cutoff_freq, fs=1/dt, output='sos')\n",
    "    T = signal.sosfiltfilt(sos, T)\n",
    "\n",
    "    # 4x1 subplot showing command, obsevered and modeled p,q,r and T\n",
    "    fig, axs = plt.subplots(4, 1, figsize=(6,4), sharex=True)\n",
    "    # let axs[0], axs[1], axs[2] share x\n",
    "    axs[0].get_shared_y_axes().join(axs[0], axs[1], axs[2])\n",
    "\n",
    "    plt.sca(axs[0])\n",
    "    plt.plot(t, log_dict['indi_p'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['p'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['indi_p'], log_dict['p'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('p [rad/s]')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[1])\n",
    "    plt.plot(t, log_dict['indi_q'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['q'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['indi_q'], log_dict['q'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('q [rad/s]')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[2])\n",
    "    plt.plot(t, log_dict['indi_r'], label='command', alpha=a)\n",
    "    plt.plot(t, log_dict['r'], label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['indi_r'], log_dict['r'][0], dt, tau), label='modeled')\n",
    "    plt.ylabel('r [rad/s]')\n",
    "    # plt.legend()\n",
    "    plt.sca(axs[3])\n",
    "    plt.plot(t, log_dict['indi_thrust'], label='command', alpha=a)\n",
    "    plt.plot(t, T, label='observed')\n",
    "    plt.plot(t, first_order_delay(log_dict['indi_thrust'], T[0], dt, tau), label='modeled')\n",
    "    plt.xlabel('time [s]')\n",
    "    plt.ylabel('T [N]')\n",
    "    \n",
    "    plt.legend(loc='lower right')\n",
    "    # set xlim\n",
    "    plt.xlim([0,5])\n",
    "    fig.suptitle('INDI modeling error', fontweight='bold')\n",
    "    fig.savefig('Figures/INDI_modeling_error.pdf')\n",
    "    fig.show()\n",
    "\n",
    "plot_INDI_model_error(log_INDI_fastest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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