uitb-vr_testing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a8013c1-a744-433d-a429-c5635ec7a3f3",
   "metadata": {
    "init_cell": true,
    "scene__Default Scene": true,
    "scene__Legacy Init": true,
    "tags": [
     "ActiveScene"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "env: MUJOCO_GL=egl\n"
     ]
    }
   ],
   "source": [
    "%env MUJOCO_GL=egl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "51dc7365",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d0ad0bdd-1986-41cc-be75-f4f0284b5958",
   "metadata": {
    "init_cell": true,
    "scene__Legacy Init": true,
    "tags": [
     "ActiveScene"
    ]
   },
   "outputs": [],
   "source": [
    "import uitb\n",
    "assert \"user-in-the-box-private/\" in uitb.__file__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "beb4137f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from uitb.simulator import Simulator\n",
    "\n",
    "import numpy as np\n",
    "import os, re, glob\n",
    "from collections import defaultdict\n",
    "import logging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cb944c23-58ab-4193-a35d-a33a78274b8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import time\n",
    "\n",
    "# import mujoco\n",
    "# import mujoco.viewer\n",
    "\n",
    "# m = mujoco.MjModel.from_xml_path('/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained/unity_hard_pretrained/simulation.xml')\n",
    "# d = mujoco.MjData(m)\n",
    "\n",
    "# with mujoco.viewer.launch_passive(m, d) as viewer:\n",
    "#   # Close the viewer automatically after 30 wall-seconds.\n",
    "#   start = time.time()\n",
    "#   while viewer.is_running() and time.time() - start < 30:\n",
    "#     step_start = time.time()\n",
    "\n",
    "#     # mj_step can be replaced with code that also evaluates\n",
    "#     # a policy and applies a control signal before stepping the physics.\n",
    "#     mujoco.mj_step(m, d)\n",
    "\n",
    "#     # Example modification of a viewer option: toggle contact points every two seconds.\n",
    "#     with viewer.lock():\n",
    "#       viewer.opt.flags[mujoco.mjtVisFlag.mjVIS_CONTACTPOINT] = int(d.time % 2)\n",
    "\n",
    "#     # Pick up changes to the physics state, apply perturbations, update options from GUI.\n",
    "#     viewer.sync()\n",
    "\n",
    "#     # Rudimentary time keeping, will drift relative to wall clock.\n",
    "#     time_until_next_step = m.opt.timestep - (time.time() - step_start)\n",
    "#     if time_until_next_step > 0:\n",
    "#       time.sleep(time_until_next_step)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f69bd336",
   "metadata": {},
   "outputs": [],
   "source": [
    "from stable_baselines3 import PPO\n",
    "\n",
    "class EvaluationLogs(object):\n",
    "    def __init__(self, env, log_variables: dict[str, tuple[str]]):\n",
    "        #stores references to env variables in self._objects, which are evaluated and copied to self._logs when self.log() is called\n",
    "        self._env = env\n",
    "        self._log_variables = log_variables\n",
    "\n",
    "        self._logs = {}\n",
    "        self.log_counter = 0\n",
    "        \n",
    "    def log(self, use_timestamps=True, id=None):\n",
    "        # Collect logs\n",
    "        _new_log = {}\n",
    "        for log_name, log_var in self._log_variables.items():\n",
    "            _object = self._env\n",
    "            for _key in log_var:\n",
    "                _object = getattr(_object, _key)\n",
    "            if hasattr(_object, \"copy\"):\n",
    "                _new_log[log_name] = _object.copy()\n",
    "            else:\n",
    "                _new_log[log_name] = _object\n",
    "        \n",
    "        # Get index\n",
    "        if id is not None:\n",
    "            _idx = id\n",
    "        elif use_timestamps:\n",
    "            if hasattr(self._env, \"_data\") and hasattr(self._env._data, \"time\"):\n",
    "                _idx = self._env._data.time\n",
    "            else:\n",
    "                logging.warning(\"Could not read time from env._data object. Will use integer indices instead.\")\n",
    "        else:\n",
    "            _idx = self.log_counter\n",
    "        \n",
    "        # Store logs\n",
    "        self._logs[_idx] = _new_log\n",
    "        self.log_counter += 1\n",
    "        \n",
    "    def get_logs(self, variable=None, indices=None):\n",
    "        if variable is not None:\n",
    "            assert variable in self._log_variables, f\"Invalid variable '{variable}'. Valid variables are {self._log_variables.keys()}.\"\n",
    "            if indices is not None:\n",
    "                return {k: v[variable][indices] for k, v in self._logs.items()}\n",
    "            else:\n",
    "                return {k: v[variable] for k, v in self._logs.items()}\n",
    "        else:\n",
    "            return self._logs\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6414f4a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "REMOTE_DISPLAY = True\n",
    "\n",
    "if REMOTE_DISPLAY:\n",
    "    process = os.popen(\"hostname --ip-address\")\n",
    "    _myipaddress = process.read().split()[0]\n",
    "    process.close()\n",
    "\n",
    "    # os.environ[\"DISPLAY\"] = f\"{_myipaddress}:1\"  #run remotely (X server needs to be configured to accept remote connections, see https://askubuntu.com/a/34663)\n",
    "    os.environ[\"DISPLAY\"] = f\":1\"  #run remotely (X server needs to be configured to accept remote connections, see https://askubuntu.com/a/34663)\n",
    "\n",
    "    process = os.popen(\"echo /run/user/$(id -u)\")\n",
    "    _pam = process.read().split(\"\\n\")[0]\n",
    "    process.close()\n",
    "\n",
    "    os.environ[\"XDG_RUNTIME_DIR\"] = _pam\n",
    "else:\n",
    "    # use X11 forwarding (e.g., using MobaXterm)\n",
    "    os.environ[\"DISPLAY\"] = \"localhost:10.0\"  #forward to localhost:10.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a055088",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Graphics-related imports\n",
    "import matplotlib\n",
    "import matplotlib.animation as animation\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import HTML\n",
    "import PIL.Image, PIL.ImageDraw, PIL.ImageFont\n",
    "# Internal loading of video libraries.\n",
    "\n",
    "# Use svg backend for figure rendering\n",
    "%config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f89c65b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def natural_sort(l):\n",
    "    convert = lambda text: int(text) if text.isdigit() else text.lower()\n",
    "    alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)]\n",
    "    return sorted(l, key=alphanum_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e9b2151b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_logdir(filepath):\n",
    "    \"\"\"Get latest subdir in logging filepath that was created by Unity App.\"\"\"\n",
    "    \n",
    "    filepath = os.path.expanduser(filepath)\n",
    "    \n",
    "    subdirs = natural_sort(os.listdir(filepath))\n",
    "    \n",
    "    # only consider directories that contain a non-empty states.csv file, excluding hidden directories (e.g. '.ipynb_checkpoints')\n",
    "    subdirs = [i for i in subdirs if os.path.isdir(os.path.join(os.path.expanduser(filepath), i)) and ((not os.path.isfile(os.path.join(os.path.expanduser(filepath), i, \"states.csv\"))) or (os.path.getsize(os.path.join(os.path.expanduser(filepath), i, \"states.csv\")) > 0)) and (not i.startswith('.')) and (len(os.listdir(os.path.join(filepath, i))) > 0)]\n",
    "    \n",
    "    if len(subdirs) > 0:\n",
    "        last_subdir = subdirs[-1]\n",
    "        filepath_new = os.path.join(filepath, last_subdir)\n",
    "        if os.path.isdir(filepath_new):\n",
    "            return get_logdir(filepath_new)\n",
    "    \n",
    "    return filepath\n",
    "\n",
    "# # copy logged pickles to logging dir\n",
    "# _SIMULATION_USER_ID = 91  #fake simulation user ID used for testing\n",
    "\n",
    "# _evaluation_dir = f\"~/uitb-sim2vr/user-in-the-box-private/{_TASK_CONDITION}/evaluate/\"\n",
    "# _latest_logdir_condition = get_logdir(os.path.join(_evaluation_dir, \"logging\"))\n",
    "# # _latest_logdir = os.path.dirname(os.path.expanduser(_latest_logdir_condition))\n",
    "# os.popen(f'cp {_evaluation_dir}/*_log.pickle {_latest_logdir_condition}') #copy uitb/MuJoCo logs (pickle files) to recent unity logdir (containing the csv files)\n",
    "# if len(glob.glob(os.path.expanduser(f'{_evaluation_dir}/*.mp4'))) > 0:\n",
    "#     os.popen(f'ln -sf {_evaluation_dir}/*.mp4 {_latest_logdir_condition}') #link generated video to recent unity logdir\n",
    "# os.popen(f'mkdir -p ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{_SIMULATION_USER_ID}/')\n",
    "# os.popen(f'cp -r {_latest_logdir_condition} ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{_SIMULATION_USER_ID}/') #copy (unity) logdir to datasets\n",
    "\n",
    "def _copy_to_dataset(TASK_CONDITION, SIMULATION_USER_ID, record=True, logging=True):\n",
    "    # copy logged pickles to logging dir\n",
    "    _evaluation_dir = f\"~/uitb-sim2vr/user-in-the-box-private/{TASK_CONDITION}/evaluate/\"\n",
    "    _latest_logdir_condition = get_logdir(os.path.join(_evaluation_dir, \"logging\"))\n",
    "    # _latest_logdir = os.path.dirname(os.path.expanduser(_latest_logdir_condition))\n",
    "    os.popen(f'mkdir -p {_evaluation_dir}').read()\n",
    "    if logging:\n",
    "        # print(f\"cp {_evaluation_dir}/*_log.pickle {_latest_logdir_condition}\")\n",
    "        os.popen(f'cp {_evaluation_dir}/*_log.pickle {_latest_logdir_condition}').read() #copy uitb/MuJoCo logs (pickle files) to recent unity logdir (containing the csv files)\n",
    "    if record:\n",
    "        if len(glob.glob(os.path.expanduser(f'{_evaluation_dir}/*.mp4'))) > 0:\n",
    "            # os.popen(f'ln -sf {_evaluation_dir}/*.mp4 {_latest_logdir_condition}') #link generated video to recent unity logdir\n",
    "            os.popen(f'cp {_evaluation_dir}/evaluate*.mp4 {_latest_logdir_condition}/').read() #copy generated video to recent unity logdir\n",
    "    if os.path.isdir(os.path.expanduser(f'{_evaluation_dir}/recording/')):\n",
    "        # print(f'cp {_evaluation_dir}/recording/*.mp4 {_latest_logdir_condition}/')\n",
    "        os.popen(f'cp {_evaluation_dir}/recording/*.mp4 {_latest_logdir_condition}/').read() #copy generated video to recent unity logdir\n",
    "    \n",
    "    os.popen(f'mkdir -p ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{SIMULATION_USER_ID}/').read()\n",
    "    \n",
    "    # print(f'cp -r {_latest_logdir_condition} ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{SIMULATION_USER_ID}/') #copy (unity) logdir to datasets\n",
    "    # os.popen(f'cp -r {_latest_logdir_condition} ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{SIMULATION_USER_ID}/').read() #copy (unity) logdir to datasets\n",
    "    os.popen(f'ln -sf {_latest_logdir_condition} ~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{SIMULATION_USER_ID}/').read() #link (unity) logdir to datasets\n",
    "\n",
    "    print(f\"NEW [{SIMULATION_USER_ID}]: {_latest_logdir_condition} successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/{SIMULATION_USER_ID}/'.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "84338950",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Custom video functions\n",
    "\n",
    "def display_video(frames, framerate=30):\n",
    "    anim = _create_animation(frames, framerate=framerate)\n",
    "    return HTML(anim.to_html5_video())\n",
    "\n",
    "def _create_animation(frames, framerate=30):\n",
    "    height, width, _ = frames[0].shape\n",
    "    dpi = 70\n",
    "    orig_backend = matplotlib.get_backend()\n",
    "    matplotlib.use('Agg')  # Switch to headless 'Agg' to inhibit figure rendering.\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(width / dpi, height / dpi), dpi=dpi)\n",
    "    matplotlib.use(orig_backend)  # Switch back to the original backend.\n",
    "    ax.set_axis_off()\n",
    "    ax.set_aspect('equal')\n",
    "    ax.set_position([0, 0, 1, 1])\n",
    "    im = ax.imshow(frames[0])\n",
    "    def update(frame):\n",
    "        im.set_data(frame)\n",
    "        return [im]\n",
    "    interval = 1000/framerate\n",
    "    return animation.FuncAnimation(fig=fig, func=update, frames=frames,\n",
    "                                   interval=interval, blit=True, repeat=False)\n",
    "\n",
    "def store_video(filename, frames, framerate=30):\n",
    "    anim = _create_animation(frames, framerate=framerate)\n",
    "    \n",
    "    if filename.endswith(\".gif\"):\n",
    "        writer = animation.PillowWriter(fps=framerate)\n",
    "    elif filename.endswith(\".mp4\") or filename.endswith(\".avi\") or filename.endswith(\".mov\"):\n",
    "        writer = animation.FFMpegWriter(fps=framerate) \n",
    "    \n",
    "    filepath = os.path.dirname(filename)\n",
    "    if not os.path.exists(filepath):\n",
    "        os.makedirs(filepath)\n",
    "    \n",
    "    anim.save(filename, writer=writer)\n",
    "    \n",
    "    print(f\"Animation stored at '{filename}'.\")\n",
    "\n",
    "def add_text_to_frame(frame, text, font=\"dejavu/DejaVuSans.ttf\", pos=(20, 20), color=(255, 0, 0), fontsize=12):\n",
    "    if isinstance(frame, np.ndarray):\n",
    "        frame = PIL.Image.fromarray(frame)\n",
    "    \n",
    "    draw = PIL.ImageDraw.Draw(frame)\n",
    "    draw.text(pos, text, fill=color, font=PIL.ImageFont.truetype(font, fontsize))\n",
    "    return frame\n",
    "\n",
    "def display_video_with_rewards(frames, rewards, framerate=30):\n",
    "    assert len(frames) == len(rewards), f\"Size of frames and rewards does not match ({len(frames)}, {len(rewards)})!\"\n",
    "    \n",
    "    for frame_id, reward in enumerate(rewards):\n",
    "        frames[frame_id] = np.array(add_text_to_frame(frames[frame_id],\n",
    "                        f\"#{frame_id}\",\n",
    "                        pos=(5, 5), color=(0, 0, 0), fontsize=18))\n",
    "        frames[frame_id] = np.array(add_text_to_frame(frames[frame_id],\n",
    "                        f\"Reward {reward:.2f}\",\n",
    "                        pos=(15, 25), color=(99, 207, 163), fontsize=24))\n",
    "\n",
    "    anim = _create_animation(frames, framerate=framerate)\n",
    "    return HTML(anim.to_html5_video())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9210fec3",
   "metadata": {},
   "outputs": [],
   "source": [
    "## for coordinate transformations\n",
    "from scipy.spatial.transform import Rotation\n",
    "def transformation_matrix(pos, quat):\n",
    "  quat = np.roll(quat, -1)\n",
    "  matrix = Rotation.from_quat(quat).as_matrix()\n",
    "\n",
    "  # Create the matrix\n",
    "  T = np.eye(4)\n",
    "  T[:3, :3] = matrix\n",
    "  T[:3, 3] = pos\n",
    "  return T"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ce656483-f380-4c01-beec-8f9f8d5fc869",
   "metadata": {},
   "source": [
    "## Test Unity Environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4aea8ca2-b354-4de8-bba4-c836ee28b333",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import subprocess\n",
    "# import socket\n",
    "# import os\n",
    "\n",
    "# with socket.socket() as s:\n",
    "#     s.bind(('', 0))\n",
    "#     port =  s.getsockname()[1]\n",
    "    \n",
    "# env_with_display = os.environ.copy()\n",
    "# # if \"DISPLAY\" not in env_with_display:\n",
    "# #     env_with_display[\"DISPLAY\"] = \":10.0\"\n",
    "\n",
    "# unity_executable = \"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained/unity_hard_pretrained/tasks/unity/build/build.x86_64\"\n",
    "# subprocess.Popen([unity_executable,\n",
    "#                                     '-simulated',\n",
    "#                                     '-port', f'{port}',\n",
    "#                                     '-logFile', \"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained/unity_hard_pretrained/tasks/unity/build/test.log\"] + [], env=env_with_display)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "efc8120a-2988-46bf-a681-8b80369cca91",
   "metadata": {},
   "outputs": [],
   "source": [
    "env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_adaptive_3ccr_1e1_v115\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=True)\n",
    "# env._data.body(\"headset\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dict('proprioception': Box(-inf, inf, (44,), float32), 'stateful_information': Box(-inf, inf, (2,), float32), 'vision': Box(-inf, inf, (1, 80, 120), float32))"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env = uitb.Simulator.get(\"/home/florian/user-in-the-box/simulators/mobl_arms_index_pointing\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=True)\n",
    "env.observation_space"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d13ec812",
   "metadata": {},
   "source": [
    "### Distance test\n",
    "(adapted from reacher_sg's reacherutils.py and ReacherSG_trajectory-analysis.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f7bc8de8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempting to connect to Unity app on port 38735\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb Cell 17\u001b[0m line \u001b[0;36m1\n\u001b[1;32m      <a href='vscode-notebook-cell://tunnel%2Bbtn6xb/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb#X22sdnNjb2RlLXJlbW90ZQ%3D%3D?line=8'>9</a>\u001b[0m     \u001b[39mdel\u001b[39;00m test_env\n\u001b[1;32m     <a href='vscode-notebook-cell://tunnel%2Bbtn6xb/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb#X22sdnNjb2RlLXJlbW90ZQ%3D%3D?line=9'>10</a>\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mtest_env\u001b[39m\u001b[39m\"\u001b[39m \u001b[39min\u001b[39;00m \u001b[39mlocals\u001b[39m():\n\u001b[0;32m---> <a href='vscode-notebook-cell://tunnel%2Bbtn6xb/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb#X22sdnNjb2RlLXJlbW90ZQ%3D%3D?line=10'>11</a>\u001b[0m     test_env \u001b[39m=\u001b[39m uitb\u001b[39m.\u001b[39;49mSimulator\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39m/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115\u001b[39;49m\u001b[39m\"\u001b[39;49m, run_parameters\u001b[39m=\u001b[39;49m{\u001b[39m\"\u001b[39;49m\u001b[39maction_sample_freq\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39m20\u001b[39;49m,\u001b[39m\"\u001b[39;49m\u001b[39mevaluate\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mTrue\u001b[39;49;00m}, render_mode\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mrgb_array\u001b[39;49m\u001b[39m\"\u001b[39;49m, use_cloned\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n\u001b[1;32m     <a href='vscode-notebook-cell://tunnel%2Bbtn6xb/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb#X22sdnNjb2RlLXJlbW90ZQ%3D%3D?line=12'>13</a>\u001b[0m welded_body \u001b[39m=\u001b[39m test_env\u001b[39m.\u001b[39mconfig[\u001b[39m\"\u001b[39m\u001b[39msimulation\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mtask\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mkwargs\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mright_controller_body\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[1;32m     <a href='vscode-notebook-cell://tunnel%2Bbtn6xb/home/florian/uitb-sim2vr/user-in-the-box-private/uitb-vr_testing.ipynb#X22sdnNjb2RlLXJlbW90ZQ%3D%3D?line=13'>14</a>\u001b[0m relpose \u001b[39m=\u001b[39m test_env\u001b[39m.\u001b[39mconfig[\u001b[39m\"\u001b[39m\u001b[39msimulation\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mtask\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mkwargs\u001b[39m\u001b[39m\"\u001b[39m][\u001b[39m\"\u001b[39m\u001b[39mright_controller_relpose\u001b[39m\u001b[39m\"\u001b[39m]\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:312\u001b[0m, in \u001b[0;36mSimulator.get\u001b[0;34m(cls, simulator_folder, render_mode, render_mode_perception, render_show_depths, run_parameters, use_cloned)\u001b[0m\n\u001b[1;32m    310\u001b[0m   _simulator \u001b[39m=\u001b[39m gen_cls(simulator_folder, run_parameters\u001b[39m=\u001b[39mrun_parameters)\n\u001b[1;32m    311\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 312\u001b[0m   _simulator \u001b[39m=\u001b[39m gen_cls(simulator_folder, render_mode\u001b[39m=\u001b[39;49mrender_mode, render_mode_perception\u001b[39m=\u001b[39;49mrender_mode_perception, render_show_depths\u001b[39m=\u001b[39;49mrender_show_depths,\n\u001b[1;32m    313\u001b[0m                       run_parameters\u001b[39m=\u001b[39;49mrun_parameters)\n\u001b[1;32m    315\u001b[0m \u001b[39m# Return Simulator object\u001b[39;00m\n\u001b[1;32m    316\u001b[0m \u001b[39mreturn\u001b[39;00m _simulator\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:348\u001b[0m, in \u001b[0;36mSimulator.__init__\u001b[0;34m(self, simulator_folder, render_mode, render_mode_perception, render_show_depths, run_parameters)\u001b[0m\n\u001b[1;32m    344\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_run_parameters\u001b[39m.\u001b[39mupdate(run_parameters \u001b[39mor\u001b[39;00m {})\n\u001b[1;32m    346\u001b[0m \u001b[39m# Initialise simulation\u001b[39;00m\n\u001b[1;32m    347\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_model, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_data, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtask, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbm_model, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mperception, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcallbacks \u001b[39m=\u001b[39m \\\n\u001b[0;32m--> 348\u001b[0m   \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_initialise(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_config, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_simulator_folder, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_run_parameters)\n\u001b[1;32m    350\u001b[0m \u001b[39m# Set action space TODO for now we assume all actuators have control signals between [-1, 1]\u001b[39;00m\n\u001b[1;32m    351\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39maction_space \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_initialise_action_space()\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:248\u001b[0m, in \u001b[0;36mSimulator._initialise\u001b[0;34m(cls, config, simulator_folder, run_parameters)\u001b[0m\n\u001b[1;32m    244\u001b[0m   callbacks[cb[\u001b[39m\"\u001b[39m\u001b[39mname\u001b[39m\u001b[39m\"\u001b[39m]] \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mget_class(cb[\u001b[39m\"\u001b[39m\u001b[39mcls\u001b[39m\u001b[39m\"\u001b[39m])(cb[\u001b[39m\"\u001b[39m\u001b[39mname\u001b[39m\u001b[39m\"\u001b[39m], \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcb[\u001b[39m\"\u001b[39m\u001b[39mkwargs\u001b[39m\u001b[39m\"\u001b[39m])\n\u001b[1;32m    246\u001b[0m \u001b[39m# Now initialise the actual classes; model and data are input to the inits so that stuff can be modified if needed\u001b[39;00m\n\u001b[1;32m    247\u001b[0m \u001b[39m# (e.g. move target to a specific position wrt to a body part)\u001b[39;00m\n\u001b[0;32m--> 248\u001b[0m task \u001b[39m=\u001b[39m task_cls(model, data, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49m{\u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mtask_kwargs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mcallbacks, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mrun_parameters})\n\u001b[1;32m    249\u001b[0m bm_model \u001b[39m=\u001b[39m bm_cls(model, data, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39m{\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mbm_kwargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcallbacks, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mrun_parameters})\n\u001b[1;32m    250\u001b[0m perception \u001b[39m=\u001b[39m Perception(model, data, bm_model, perception_modules, {\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcallbacks, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mrun_parameters})\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/base.py:70\u001b[0m, in \u001b[0;36mBaseTask.__init_subclass__.<locals>.init_with_hook\u001b[0;34m(self, model, data, init, **init_kwargs)\u001b[0m\n\u001b[1;32m     69\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39minit_with_hook\u001b[39m(\u001b[39mself\u001b[39m, model, data, init\u001b[39m=\u001b[39m\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__init__\u001b[39m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39minit_kwargs):\n\u001b[0;32m---> 70\u001b[0m   init(\u001b[39mself\u001b[39;49m, model, data, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49minit_kwargs)\n\u001b[1;32m     72\u001b[0m   \u001b[39m# Set stateful information shape\u001b[39;00m\n\u001b[1;32m     73\u001b[0m   \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stateful_information_shape \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mget_stateful_information(model, data)\u001b[39m.\u001b[39mshape\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/Unity.py:66\u001b[0m, in \u001b[0;36mUnity.__init__\u001b[0;34m(self, model, data, gear, left_controller_enabled, **kwargs)\u001b[0m\n\u001b[1;32m     63\u001b[0m \u001b[39m# Wait until app is up and running. Send time options to unity app\u001b[39;00m\n\u001b[1;32m     64\u001b[0m time_options \u001b[39m=\u001b[39m {\u001b[39m\"\u001b[39m\u001b[39mtimestep\u001b[39m\u001b[39m\"\u001b[39m: model\u001b[39m.\u001b[39mopt\u001b[39m.\u001b[39mtimestep, \u001b[39m\"\u001b[39m\u001b[39msampleFrequency\u001b[39m\u001b[39m\"\u001b[39m: kwargs[\u001b[39m\"\u001b[39m\u001b[39maction_sample_freq\u001b[39m\u001b[39m\"\u001b[39m],\n\u001b[1;32m     65\u001b[0m                 \u001b[39m\"\u001b[39m\u001b[39mtimeScale\u001b[39m\u001b[39m\"\u001b[39m: kwargs[\u001b[39m\"\u001b[39m\u001b[39mtime_scale\u001b[39m\u001b[39m\"\u001b[39m]}\n\u001b[0;32m---> 66\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39minitial_state \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_unity_client\u001b[39m.\u001b[39;49mhandshake(time_options)\n\u001b[1;32m     68\u001b[0m \u001b[39m# Used for logging states\u001b[39;00m\n\u001b[1;32m     69\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_info \u001b[39m=\u001b[39m {\u001b[39m\"\u001b[39m\u001b[39mterminated\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39mFalse\u001b[39;00m,\n\u001b[1;32m     70\u001b[0m             \u001b[39m\"\u001b[39m\u001b[39mtruncated\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39mFalse\u001b[39;00m, \u001b[39m\"\u001b[39m\u001b[39munity_image\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39mNone\u001b[39;00m}\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/utils/unity.py:88\u001b[0m, in \u001b[0;36mUnityClient.handshake\u001b[0;34m(self, time_options)\u001b[0m\n\u001b[1;32m     86\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mAttempting to connect to Unity app on port \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mport\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[1;32m     87\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_client\u001b[39m.\u001b[39msend_json(time_options)\n\u001b[0;32m---> 88\u001b[0m msg \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_client\u001b[39m.\u001b[39;49mrecv_json()\n\u001b[1;32m     89\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mConnection confirmed\u001b[39m\u001b[39m\"\u001b[39m)\n",
      "File \u001b[0;32m/opt/conda/envs/uitb_gymnasium/lib/python3.11/site-packages/zmq/sugar/socket.py:1017\u001b[0m, in \u001b[0;36mSocket.recv_json\u001b[0;34m(self, flags, **kwargs)\u001b[0m\n\u001b[1;32m    997\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mrecv_json\u001b[39m(\u001b[39mself\u001b[39m, flags: \u001b[39mint\u001b[39m \u001b[39m=\u001b[39m \u001b[39m0\u001b[39m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Union[List, \u001b[39mstr\u001b[39m, \u001b[39mint\u001b[39m, \u001b[39mfloat\u001b[39m, Dict]:\n\u001b[1;32m    998\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Receive a Python object as a message using json to serialize.\u001b[39;00m\n\u001b[1;32m    999\u001b[0m \n\u001b[1;32m   1000\u001b[0m \u001b[39m    Keyword arguments are passed on to json.loads\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1015\u001b[0m \u001b[39m        for any of the reasons :func:`~Socket.recv` might fail\u001b[39;00m\n\u001b[1;32m   1016\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1017\u001b[0m     msg \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrecv(flags)\n\u001b[1;32m   1018\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_deserialize(msg, \u001b[39mlambda\u001b[39;00m buf: jsonapi\u001b[39m.\u001b[39mloads(buf, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs))\n",
      "File \u001b[0;32mzmq/backend/cython/socket.pyx:805\u001b[0m, in \u001b[0;36mzmq.backend.cython.socket.Socket.recv\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mzmq/backend/cython/socket.pyx:841\u001b[0m, in \u001b[0;36mzmq.backend.cython.socket.Socket.recv\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mzmq/backend/cython/socket.pyx:194\u001b[0m, in \u001b[0;36mzmq.backend.cython.socket._recv_copy\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m/opt/conda/envs/uitb_gymnasium/lib/python3.11/site-packages/zmq/backend/cython/checkrc.pxd:13\u001b[0m, in \u001b[0;36mzmq.backend.cython.checkrc._check_rc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import mujoco\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "USE_VR_CONTROLLER = True  #whether to use VR controller position or that of the welded body ##(the latter does not require calling mj_step, and thus results in the hypothetical reach envelope of the hand, ignoring the offset to the VR controller)\n",
    "\n",
    "\n",
    "if \"test_env\" in locals():\n",
    "    del test_env\n",
    "if not \"test_env\" in locals():\n",
    "    test_env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115\", run_parameters={\"action_sample_freq\": 20,\"evaluate\": True}, render_mode=\"rgb_array\", use_cloned=False)\n",
    "\n",
    "welded_body = test_env.config[\"simulation\"][\"task\"][\"kwargs\"][\"right_controller_body\"]\n",
    "relpose = test_env.config[\"simulation\"][\"task\"][\"kwargs\"][\"right_controller_relpose\"]\n",
    "endeffector_name = \"controller-right\" if USE_VR_CONTROLLER else welded_body\n",
    "\n",
    "video_output = True\n",
    "num_episodes = 1\n",
    "video_filename = f'/home/florian/uitb-sim2vr/user-in-the-box-private/uitb_distance_{endeffector_name}_test.mp4'\n",
    "figure_filename = f'/home/florian/uitb-sim2vr/user-in-the-box-private/uitb_distance_{endeffector_name}_test.png'\n",
    "table_filename = f'/home/florian/uitb-sim2vr/user-in-the-box-private/uitb_distance_{endeffector_name}_test.csv'\n",
    "trajectories_table_columns = ['elv_angle_pos', 'shoulder_elv_pos'] + ['end-effector_xpos' + suffix for\n",
    "                                                                        suffix in ('_x', '_y', '_z')]\n",
    "trajectories_table = pd.DataFrame(columns=trajectories_table_columns)\n",
    "#with imageio.get_writer(video_filename, fps=int(1 / (test_env._model.opt.timestep))) as video:\n",
    "video = []\n",
    "\n",
    "for video_episode_index in range(num_episodes):\n",
    "    print('Video - Episode {}/{}'.format(video_episode_index + 1, num_episodes))\n",
    "    obs, info = test_env.reset()\n",
    "    print(\"Successfully reset.\")\n",
    "    if video_output:\n",
    "        video.append(test_env.render())\n",
    "\n",
    "    nsteps_to_test = 100\n",
    "    range_elevation_angle = np.linspace(\n",
    "        test_env._model.joint('elv_angle').range[0],\n",
    "        test_env._model.joint('elv_angle').range[1], nsteps_to_test)\n",
    "    range_elevation = np.linspace(\n",
    "        test_env._model.joint('shoulder_elv').range[0],\n",
    "        test_env._model.joint('shoulder_elv').range[1], nsteps_to_test)\n",
    "    _steps = 0\n",
    "    for i in range(nsteps_to_test):\n",
    "        for j in range(nsteps_to_test):\n",
    "            if (100*(_steps+1)/(nsteps_to_test**2) % 10) == 0:\n",
    "                print(f\"{100*(_steps+1)/(nsteps_to_test**2)}% reached.\")\n",
    "            \n",
    "            # if USE_VR_CONTROLLER:\n",
    "            #     obs, info = test_env.reset()\n",
    "            test_env._data.joint('elv_angle').qpos = range_elevation_angle[i]\n",
    "            test_env._data.joint('shoulder_elv').qpos = range_elevation[j]\n",
    "            \n",
    "            # maximally extend the arm:\n",
    "            test_env._data.joint(\"elbow_flexion\").qpos = test_env._model.joint(\"elbow_flexion\").range[0]\n",
    "\n",
    "            # adjust virtual joints according to active constraints:\n",
    "            for (virtual_joint_id, physical_joint_id, poly_coefs) in zip(\n",
    "                    test_env._model.eq_obj1id[\n",
    "                        (test_env._model.eq_type == 2) & (test_env._model.eq_active == 1)],\n",
    "                    test_env._model.eq_obj2id[\n",
    "                        (test_env._model.eq_type == 2) & (test_env._model.eq_active == 1)],\n",
    "                    test_env._model.eq_data[(test_env._model.eq_type == 2) &\n",
    "                                                (test_env._model.eq_active == 1), 4::-1]):\n",
    "                if physical_joint_id >= 0:\n",
    "                    test_env._data.joint(virtual_joint_id).qpos = np.polyval(poly_coefs, test_env._data.joint(physical_joint_id).qpos)\n",
    "            # qpos[test_env._model.joint_name2id('shoulder1_r2')] = -qpos[test_env._model.joint_name2id(\n",
    "            #     'elv_angle')]  # joint equality constraint between \"elv_angle\" and \"shoulder1_r2\"\n",
    "\n",
    "            #test_env._data.qpos[:] = qpos\n",
    "            # if USE_VR_CONTROLLER:\n",
    "            #     mujoco.mj_step(test_env._model, test_env._data)\n",
    "            # else:\n",
    "            #     mujoco.mj_forward(test_env._model, test_env._data)\n",
    "            mujoco.mj_forward(test_env._model, test_env._data)\n",
    "            if video_output:\n",
    "                video.append(test_env.render())\n",
    "            trajectories_table.loc[len(trajectories_table), :\"shoulder_elv_pos\"] = np.concatenate((test_env._data.joint('elv_angle').qpos, test_env._data.joint('shoulder_elv').qpos))\n",
    "            if USE_VR_CONTROLLER:\n",
    "                #manually compute VR controller position using \"right_controller_relpose\" from config file and current position of the aux body/welded body\n",
    "                T1 = transformation_matrix(pos=test_env._data.body(welded_body).xpos, quat=test_env._data.body(welded_body).xquat)\n",
    "                T2 = transformation_matrix(pos=relpose[:3], quat=relpose[3:])\n",
    "                T = np.matmul(T1, np.linalg.inv(T2))\n",
    "                T[:3, 3]\n",
    "                trajectories_table.loc[len(trajectories_table) - 1,\n",
    "                            \"end-effector_xpos_x\":\"end-effector_xpos_z\"] = T[:3, 3]\n",
    "                # _controller_quat = np.roll(Rotation.from_matrix(T[:3, :3]).as_quat(), 1)\n",
    "            else:\n",
    "                trajectories_table.loc[len(trajectories_table) - 1,\n",
    "                    \"end-effector_xpos_x\":\"end-effector_xpos_z\"] = test_env._data.body(endeffector_name).xpos\n",
    "            # print(test_env._data.body(endeffector_name).xpos)\n",
    "\n",
    "            _steps += 1\n",
    "## -> Store csv file\n",
    "trajectories_table.to_csv(table_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6c2b917a",
   "metadata": {},
   "outputs": [],
   "source": [
    "## -> Store mp4 file\n",
    "# temporarily override fps\n",
    "_orig_fps = test_env._GUI_camera._fps\n",
    "test_env._GUI_camera._fps = 100\n",
    "\n",
    "test_env._GUI_camera.write_video_set_path(video_filename)\n",
    "\n",
    "# Write the video\n",
    "# simulator._camera.write_video(imgs, os.path.join(evaluate_dir, args.out_file))\n",
    "for _img in video:\n",
    "    test_env._GUI_camera.write_video_add_frame(_img)\n",
    "\n",
    "test_env._GUI_camera.write_video_close()\n",
    "\n",
    "# reset to original fps from env\n",
    "test_env._GUI_camera._fps = _orig_fps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1efe6412",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>j</th>\n",
       "      <th>i</th>\n",
       "      <th>local_x</th>\n",
       "      <th>local_y</th>\n",
       "      <th>global_x</th>\n",
       "      <th>global_y</th>\n",
       "      <th>global_z</th>\n",
       "      <th>task_condition</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>0.940631</td>\n",
       "      <td>0.594708</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
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       "      <td>13-01-15-low-medium</td>\n",
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       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>0.763854</td>\n",
       "      <td>0.417931</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>0.940631</td>\n",
       "      <td>0.594708</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>0.852242</td>\n",
       "      <td>0.506320</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>0.763854</td>\n",
       "      <td>0.417931</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>0.940631</td>\n",
       "      <td>0.594708</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>0.852242</td>\n",
       "      <td>0.506320</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>0.763854</td>\n",
       "      <td>0.417931</td>\n",
       "      <td>13-01-15-low-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>1.194920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>1.069920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>0.944920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>1.194920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>1.069920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>0.944920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>1.194920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>1.069920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
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       "      <td>0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>0.944920</td>\n",
       "      <td>0.563642</td>\n",
       "      <td>13-01-55-mid-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>1.475986</td>\n",
       "      <td>0.367931</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>1.387598</td>\n",
       "      <td>0.456320</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.026594</td>\n",
       "      <td>1.299209</td>\n",
       "      <td>0.544708</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>1.475986</td>\n",
       "      <td>0.367931</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>1.387598</td>\n",
       "      <td>0.456320</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.151594</td>\n",
       "      <td>1.299209</td>\n",
       "      <td>0.544708</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>1.475986</td>\n",
       "      <td>0.367931</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>1.387598</td>\n",
       "      <td>0.456320</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.125</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>0.276594</td>\n",
       "      <td>1.299209</td>\n",
       "      <td>0.544708</td>\n",
       "      <td>13-02-34-high-medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  j  i  local_x  local_y  global_x  global_y  global_z  \\\n",
       "0   0  0  0   -0.125    0.125  0.026594  0.940631  0.594708   \n",
       "1   3  1  0   -0.125    0.000  0.026594  0.852242  0.506320   \n",
       "2   6  2  0   -0.125   -0.125  0.026594  0.763854  0.417931   \n",
       "3   1  0  1    0.000    0.125  0.151594  0.940631  0.594708   \n",
       "4   4  1  1    0.000    0.000  0.151594  0.852242  0.506320   \n",
       "5   7  2  1    0.000   -0.125  0.151594  0.763854  0.417931   \n",
       "6   2  0  2    0.125    0.125  0.276594  0.940631  0.594708   \n",
       "7   5  1  2    0.125    0.000  0.276594  0.852242  0.506320   \n",
       "8   8  2  2    0.125   -0.125  0.276594  0.763854  0.417931   \n",
       "0   0  0  0   -0.125    0.125  0.026594  1.194920  0.563642   \n",
       "1   3  1  0   -0.125    0.000  0.026594  1.069920  0.563642   \n",
       "2   6  2  0   -0.125   -0.125  0.026594  0.944920  0.563642   \n",
       "3   1  0  1    0.000    0.125  0.151594  1.194920  0.563642   \n",
       "4   4  1  1    0.000    0.000  0.151594  1.069920  0.563642   \n",
       "5   7  2  1    0.000   -0.125  0.151594  0.944920  0.563642   \n",
       "6   2  0  2    0.125    0.125  0.276594  1.194920  0.563642   \n",
       "7   5  1  2    0.125    0.000  0.276594  1.069920  0.563642   \n",
       "8   8  2  2    0.125   -0.125  0.276594  0.944920  0.563642   \n",
       "0   0  0  0   -0.125    0.125  0.026594  1.475986  0.367931   \n",
       "1   3  1  0   -0.125    0.000  0.026594  1.387598  0.456320   \n",
       "2   6  2  0   -0.125   -0.125  0.026594  1.299209  0.544708   \n",
       "3   1  0  1    0.000    0.125  0.151594  1.475986  0.367931   \n",
       "4   4  1  1    0.000    0.000  0.151594  1.387598  0.456320   \n",
       "5   7  2  1    0.000   -0.125  0.151594  1.299209  0.544708   \n",
       "6   2  0  2    0.125    0.125  0.276594  1.475986  0.367931   \n",
       "7   5  1  2    0.125    0.000  0.276594  1.387598  0.456320   \n",
       "8   8  2  2    0.125   -0.125  0.276594  1.299209  0.544708   \n",
       "\n",
       "         task_condition  \n",
       "0   13-01-15-low-medium  \n",
       "1   13-01-15-low-medium  \n",
       "2   13-01-15-low-medium  \n",
       "3   13-01-15-low-medium  \n",
       "4   13-01-15-low-medium  \n",
       "5   13-01-15-low-medium  \n",
       "6   13-01-15-low-medium  \n",
       "7   13-01-15-low-medium  \n",
       "8   13-01-15-low-medium  \n",
       "0   13-01-55-mid-medium  \n",
       "1   13-01-55-mid-medium  \n",
       "2   13-01-55-mid-medium  \n",
       "3   13-01-55-mid-medium  \n",
       "4   13-01-55-mid-medium  \n",
       "5   13-01-55-mid-medium  \n",
       "6   13-01-55-mid-medium  \n",
       "7   13-01-55-mid-medium  \n",
       "8   13-01-55-mid-medium  \n",
       "0  13-02-34-high-medium  \n",
       "1  13-02-34-high-medium  \n",
       "2  13-02-34-high-medium  \n",
       "3  13-02-34-high-medium  \n",
       "4  13-02-34-high-medium  \n",
       "5  13-02-34-high-medium  \n",
       "6  13-02-34-high-medium  \n",
       "7  13-02-34-high-medium  \n",
       "8  13-02-34-high-medium  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read Unity target coordinates from event files\n",
    "task_condition_list = [\"13-01-15-low-medium\", \"13-01-55-mid-medium\", \"13-02-34-high-medium\"]\n",
    "_target_info = pd.DataFrame()\n",
    "for _task_condition in task_condition_list:\n",
    "    with open(f\"datasets/vr-uitb-experiment/85/{_task_condition}/events.csv\", \"r\") as f:\n",
    "        _lines = f.read().split(\"\\n\")\n",
    "    _firstrowindex = np.where([\"grid mapping\" in _l for _l in _lines])[0][-1] + 1\n",
    "    _target_info_new = pd.DataFrame(np.vstack([np.fromstring(_i.replace(\"[\", \"\").strip(), dtype=float, sep=\" \") for _i in _lines[_firstrowindex-1].split(\"grid mapping\")[-1].split(\"]\")[:-1]]), columns=[\"id\", \"j\", \"i\", \"local_x\", \"local_y\", \"global_x\", \"global_y\", \"global_z\"]).astype(dict(zip([\"id\", \"j\", \"i\", \"local_x\", \"local_y\", \"global_x\", \"global_y\", \"global_z\"], [int, int, int, float, float, float, float, float])))\n",
    "    _target_info_new[\"task_condition\"] = _task_condition\n",
    "    _target_info = pd.concat((_target_info, _target_info_new))\n",
    "_target_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e1bb0fda",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "sns.set_theme(style=\"white\")  #, palette=None)\n",
    "sns.reset_orig()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ad62781a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a4aa48f5fa354e71a7dfe413f6b1c1b7",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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egE6ng3PuCq/qiYOIMB6POX/+PHNzc0RRdKWXZFxlmBG0YRiGcVUiIpw9e5b19fUrvZQnLHNzc+zdu9fEs/F5mAA0DMMwrmrquqYsyyu9jCccSZJY5M/4opgANAzDMAzD2GFYE4hhGIZhGMYOwwSgYRiGYRjGDsMEoGEYhmEYxg7DBKBhGIZhGMYOwwSgYRiGYRjGDsMEoGEYhmEYxg7DBKBhGIZhGMYOwwSgYRiGYXwRRISyLKmq6kovxTAeV0wAGoZhGMYXQESYTqd85jOfMQFoXHOYADQMwzCMz6Gua/I8p6oqDh8+fKWXYxiPOyYADcMwDKNhK+U7nU556KGHsGmpxrWKCUDDMAzD4LH1fiEEDh8+bALQuGYxAWgYhmHseLZSvmVZ8sgjj1zp5RjGJccEoGEYhrFj+dyUb13XPPLII4QQrvTSDOOSYgLQMAzD2JFYytfYyZgANAzDMHYclvI1djomAA3DMIwdg6V8DUOJr/QCDGMnISJsbGzQ6/Vwzl3p5RjGjkJEqKoKEdlO+V533XVXelmGcUUwAWgYl5HBYMD8/DxHjx5lZmbmK37e4cOH6ff7LC0tXcLVfe2UZcmnP/1pbr/99qtW2J45c4ayLK/qH/xPfepT3HjjjXS73Su9lC/IxsYGZ8+e5dZbb73SS/miPPLII8zOzrK4uPh5j4kIdV1z9uxZbrjhhsu/OMO4ijABaBhXAO893n/lFRiTyYRWq/VVPedy4pxjc3MT59xVu8attN/Vuj6A4XCIiFy1a6zrmtFodNWuD/S70u12v+AaQwjUdW2RP8PABKBhXBG+WgHonLuqxdXWur7a13U5udrP4RZX+zkErtr1wZd+n63D1zAucvV+iw3DMAzDMIxLgkUADcO4YohIE5URRALOuea+8KhaQg/o9a3oztVaZ2hcu9R1faWXYBiPKyYADcO45JTH/ycc/zNIOtDdD+sPw+gUJD1I+zA6A/UYoh74GMpNBAHfAgFkAnjwHQg5ECDqgPP6uE/1eXGmlyiDuK3bxC1wCclaQZCEcn4C2Tyks7isRxynV/bkGFc1w+EQ0EasZzzjGVd4NYbx+GEC0DCMS0oIJRz/E9h8GIhg4yGoNvTBegOmDlVxQL0Gjw60hOJzdpZfvF5PH3W9+Tfni7KwdeWjb9++T4ASgD7M3wYz18HS34EIovnbrupaN+PSshXx++hHPwrAjTfeeCWXYxiPOyYADcO4pHifUO96NkzXIEoh3QWjs1CtAQm4Nsjqo57xKEF42RjA2of1cuy/AVDToiaDzm7Y/00QKtj3DSSzhy7z2owrwYc//GEAnv3sZ/ORj3yEOLafS+Pawj7RhmFccpKnvJr6lu9B6hwXSiBAXROqsUb5QgHVVKN65RTqHIoB1BMoxzDd0OhfPYXhBZAxULAVv7s0TPUy3oCHH9K7Dv8OJX3VqLufDws3g4vhwAtJks4lXItxubj//vsBOHToEA899BC9Xu8Kr8gwLg0mAA3DuCxEUQzRY//Lib7E9hIqqKeEukQGR6EYIKOz0DsJ5Qgmy/pvNYEwAapLufxHMdAA5bn36QXgM79LmfW17vCGV8DCreBTkvb8ZVqT8fVy+vRp4KJVzIEDB3jooYeu5JIM45JiAtAwjKsGkRqmq4QQCJtHYXIO8g2YnIFiqIKvnkBdQSihFpAAJM2lRqOClzmFHNZgsqbXP/lZNEQYUS48G+aeqkr34J0k7YUvsRPjSjAajQA4duwYAE972tO4++67r+CKDOPyYALQMIwrTpguI/kGId+AzcNQDiFfU/EXKpBKRZ8EcAnEEZA2QrCtYtA3ok+CCsNQgQsgNVATCFy+KKHosVb/Vi8AD7+Tcu4mcAL7XoTf/wJ83DZLmyvEVpPHvffeC8Dznvc8/uIv/uJKLskwLismAA3DuOxIqEFqwvqDBCLYeFAjaGEK5QbUNYiAjyAI+ARcBc5BCCrucBAJ1CV4r0LPiQYBk7oRjbUG45xHphMCOSoCA+ovGNjyGNQnbkUOXfPYo29/nVFFWYM1FRus3kf47NsIPsDCU+FJ/yveooOXla0mjzvuuIN7772XKPpSBQmGce1hAtAwLiEiwmAw2L69vLzMi170Io4ePUq73abb7X5FEaDpdMrm5iZnzpy5lMv9mqkqjaydPXv2i78eCQD4fAWfnwMgHj6EEOGrARIqvAtIcDin5tDUASECV4NEqEiL8SEgPsFLQJxDxIF4XK0izgWHRBkkAlUNBEoCQkK+LQJTHCWuiQ06IsAhOBw1gsdR43AI0sjELVHoPudfFYe6XWNszUVp+fkEqLTmjLNnqc9+GIdwCy3WH3oF44UnIem8ehteRQwGA8qyvGo/h6DflY2NjS86C3h5eRm42OTR7/cv9xIN46rg6vrfxTCuMQaDAbOzs593/zd90zcB8K53vYtut/tl95PnOXVdUxTFl932ShCCirsvKABFRVOrOIWTmrReI62WqemQhhUqOkSMqcmIpaB2KV5yRBKcqxBizeR6gAgnNQ4PEvRxiXBUIB5xDieAE1wIiDicRCCOmlYj7zwRIwRPoE3EFCFGEGIqaiIgJqKmJmrmZUojDC8KPJrrsi0Rt18w7jFCMbAlHB8tSR59liL0j4QeQ1rn3oqcc0DKavt5jDpPofY9Qtx+nN6tr52iKKiqirNnz17ppXxR8jxHRMjzzzeFFJFtOxdr8jB2OiYADeMS0u/32djY2L69ubnJoUOHeOCBB+j3+/T7/a8oAviJT3yC+fl5Dh26Oj3oiqLggx/8IM961rMeE3mRYkDYPEJwCWwErdljFvIKWrtgEkNrN+QXIO5rg4dLNMXrm/MijZCqS639qysg0hQvEUiu0UEnmiKWCo0eojWAAKFiczihDhUz7QSm5zW9HM9Avqr7z2ag2Gz204IwVtXpI6jyRrFFQPWoDHEN0tyQSrdtRtupIgx6O4juN2wJw0f/G9hysi6BmIIEgJzO5AOQ36vZ6sXn4J78SsgWiLMrE7W6cOECR44c4Y477rgix/9K+PjHP87i4iIHDhz4vMfqumY6nW5HAQ1jJ2M294YBfOADH+AVr3gF+/fvxznHO97xji/7nDzP+af/9J9y/fXXk2UZN9xwA7/1W7/1mG2cc8zMzDzmAioMZ2ZmrtkGgDA+T1j7DGF4grD6AAyOaT1enatViovVADrOVCAlfa3jS3o63i3t6TZxG1wz5i1tnhd39d+kC1EE6QzEiY58i1LdR9zV+6KOjp9LWkicIVEbsr5u4zNIO5DNqT2NTyGdbY7RgmRW9x+1dFxd0m4uXRWISbs5VgZxR9ccN6Pnokz37zt6X9b8m7T1NSVt8FuXLtAB1yZ8XtK4hLAO1Tqc/Z/IB38WuefHKT/8/6PcOEZdTi77e2sYxrWBRQANA7WCuP3223nta1/Ld37nd35Fz/nu7/5uzp07x2/+5m/y5Cc/mTNnzmynQnckIoTRGXAQxmdh4xGkd6hpxpiq8KmnKtKiTBs44r5GxnxfjZ+TPjBSwedj7e7N2lA1DSASVCjGiUbTXKzROJ9s1xg2XSB6nK28rI+BmtqVKvqqLuSb+rzWAkxK3X9rF0yaxpF0AUoPoYZ0DqpR02jSgyhXQRtHTUOKgIs0Sgm6xtDMpwulilpP05EsGjWMqsdGBl2gLBzZtgjcigxupf0FWNbyxQt/BYMThCgidPbDza8inj2Ac9bIYBjGV4YJQMMAXvayl/Gyl73sK97+Pe95D/fccw+HDx9mYUG7N2+44YZLtLqrG/XuWyGVIbJ5GKknSDrXdPSOIZtXW5f2Lk2xgkbaqkL/LRshlnQ07evaWt/nE229EDRiVucQtUFKwKtwihox5XiUANxKyW6lhGuQGPETTenGXUhmdOKIA9J5KNYB0Shj1Vex5xxkCzBd0f1l87pWBKIZVKh6iHpQj3VNcdpYzwCR0wknPtPj1AXQ0vV7BxLreqTWDmdAqJp9eG182ep4li07m5zt9PH0hL7c0VEYnaJq7YXuItz4HSS9fZf4XTcM44mOpYAN42vgv//3/85zn/tc/uW//JccOHCAW265hZ/8yZ9kMtk5KTkRQcoxMl2F9c/Src9BEMJU66tcuoCrp5pKpbFraS+qmXM204gc9PFQqjAT0X99gjjfRAq1Io640wiuJr0axZridWjala3HfJM2ToEmtRu1EZcQfKJRw3QGkkSjdD7SCJ9D/QO7ezR6GEoVh+mMirC4q9el1n225oAmIpnOqGCMEhWp3mnUMWrpfT6GtAtx3KSM9TWSdpr5yF2IW9Sk+prSdpM+7mrKOe5qitnPgpsButBUCgIwPgWrfwMn/gT+9ucpP/NWyhPvp5xuXq6Pg2EYTzAsAmgYXwOHDx/mgx/8IK1Wiz/6oz9ieXmZf/gP/yErKyu85S1vudLLuzxMLxAGxwlxD8ohqQwg60HZhXKAZAu48VkVda0lFYPpDBJKjeZtpVV92qSHS0i6uLrQWj2pcN7paC63lVKNmuulNotsiUTXCCuSJvqW4mSK+BauniJOU8pO6mZ7GvEY6e10TqN4rlYxGc9oBDNymiIen9fIXbbURBRLyBYB36S3m7pEmWpNn2TN9Z5GASU0a99qWAnNdk6PIUBcU9JSQRqlENVQB7b/m64riJvmGKkgtIAaKtFGmC2T6+lpOPwOfax7kPLmV+N6+/C9A3hvKWLDMBQTgIbxNRBCwDnHW9/61m2bl3/9r/813/Vd38Wv//qv025fecuOS4VMV5DJMsFFMDqj4qe1G+8egGqKay/BdBlJ55BsBhfGkM6p8AsVLp1RgRg5XNpB6rqp+dN6OolTFUbimxq/Jg0abUXsYqAxicapoBJUEOJxUYy4TIVX3EakgriDRBEhxDjnkKh70WRagqafi5buP+5AawamJZQFtBZ13nBdQCvRVHC+ocKvtUvH1dU5tOah2NBtsxkIKVRjPT+hgpBr6rku0MhhpNfjrKkdDAgtjRImXV2/C00aWyAq9V8RFaCNmfaWNyJ1psJQKjRVDIxOwH1vRuJAPXcL9W3/gKi7Fx8lX/C9NQxj52ApYMP4Gti3bx8HDhx4jMffU57yFESEkydPXsGVXTq20r1hcgHZfATKIZLtaurfYEofpqtI1MJlc7h8FdfapU+uJ9BewIVc3fOSWXyowKW4KNmu+XM+wW0LuRTxsYrBuAuhxsUtnEONon2K26oLRDRqFidN2tiD17Swure0cKHWFKtz2r2bdHRtzkE2q+naRqSSzmikrRqrCEtmVFgVg6Y7OIVqqmIsW1BBVk00ZeyTZjRdplHGUDY1jl2g1tR13GmaX7ImbR1B3CeA3o7bTUdzu0krN9ulHRWMUftRqeGONtOkPW2iiXvaqEILSIF17SJe/ih84t9Tf/gXKR9+B/VWw4phGDsSiwAaxtfAC1/4Qt72trcxHA7p9XoAPPjgg3jvOXjw4BVe3eOLiGijx+AIkm8grUVc1IZ8FddagjBFqgG1a0HSI/7QhOgdi7jxANlfUn37IvL0TSinuGxORVTURpIO1Lk2e0SZCqpIbWG8Dyok6xziTA2efQQ+w9U1IZ3Hf7Qgefc87kQbuXlCfecc9dNOI8ks1Dnimjo8F+soOJ/gxGvKuRFclLlGAeOkqUVsxsSlM5Du0qaPh2KSD+5GcofsmiC3zRKeFnRWseTQ2a+RuKBrpbOkEcIognRRfQadUxE5XdeUr8+gck23cKlC0Tu890jUB6qmeSRWgR23dS1uq8axGWHnS5CkSUs36W9K7XIOhe67Au0kdrD5sO579dOEjcOEpWfB3G0kM/uvzIfLMIwrhkUADQMYDofcd9993HfffQAcOXKE++67j+PHjwPwxje+ke/7vu/b3v5Vr3oVu3bt4vu///u5//77+cAHPsBP/dRP8drXvvaaSv+KBGTzCKx/lkCEFOuQryGdPRBKpJogrd0QanwoSf9oD9lveKJjBdGJOaKHalq/6PEfnAMCAfX6c85p/Z3TNK7bTu2iaeCtqJ7USKR1gSQz264u6bu7tH4Nok918JuC/9QM6c+1iT7QgrirZtRxT/fhmyYMETWklsZ8OUobs+laLV2y2WaWcNNlnPXhcEzyXwv8fXP4tTbuvCf+ozHRn+/TtYdG+LXm9XY10Chg3IJy0kQX5/WY1USbYMSp2M3m9fhRsu0/WEuCRE0Di28imVHjg7jlLxhnGr2MUo1aJo3HoNuy12mihGlXU9HtBa1djGe5+Dd/AefuhU/9R/jbN1Eeew/VZOXyfbAMw7jimAA0DOAjH/kId9xxx/aEg9e//vXccccdvOlNbwLgzJkz22IQoNfr8d73vpf19XWe+9zn8upXv5pXvOIV/Lt/9++uyPovBVJsIpNlpBwi43MqYjr71dKlLqG9F1duapSutUA7L4n/7xq3uoRkU0hK3Pk9kFQkv+PAzem2OCTpqiCKWoSopbN30xmco0lxZk1KdRYXJiCiEcFqgFRd4t8DcY5oMAutKW7SwnlH8kctfNlCQoWLYpxPVJh5jSJKY/LsfKKNH6Ii1EHTyRtfTNnSIf5QG+kN8eLwoy5SOaQzJP5ToJhTAViOVIjFPRV99UQFoU80EuhTtYqpCm0MSfoagSxHEHWBCMIEvHYpu5BrNDLWVDjpbNMY0lIR6JvGlTjRc+W3hGCTFt4Sh3FbU8RRq7m/pSIwWmxsbCpgAsUFePgdyIf/BeXHf41ysnplPnCGYVxWLAVsGMCdd96p3aZfhLvuuuvz7rvtttt473vfewlXdeWQukQ2jyL1VFO+5UBTnp09mrYtN5DWHhVo9RSiPu0j+3BJAXlKNJ6FeIq0xri8jS8r3OEcuaUFiIqfdB5HhWtqCV091hRstguKDVzcReIWrhwg7QVcqHE+wX9mF86v4gezBF8jUYnfnEOWzuFyj/tUjNxWIr6DK9cao+gm2igO5zw4p1HGJk0sElSwZbPabesEf6aNPz9PPbuK+AK3vouoN0CiCu9romP7qW8bqxiOEujs0jrBcgAzT4Kq1LRtqKC3D0YnNd2czWoatxw1NjCJXo9bVJLqOpy/mL7eGj8XNZFln6iwm66rsCtGTTdz0yxCBEnTWSy17r+eNkKw0HWFJiVcN93J+Sbkp2H4EIzPUx58EczeSjJzdY4eNAzj68cigIZhbCMSCJtHCRuPEHyKFEOtYWvvAQQ3Xca3FiHu4KYXIJtF0j5ML1C7DLcxjyyswSRDNuZx7RzJM5j08GnARRngcV4neEg5RaI2TiooR0g6ox21odDrxRicx8V9XKWRNokhJDlszuLSAle0cKXOz3Br87gs4KIU4ua+KMM1UT5xEYJHqlzHuyEq0JzT676rEU5iSBxu1MXhCJ0xLu/ghjOID9SdIZJ6TfcSVITFvaZZpFYB217QZpNycLFZBKBYUwuZuNVECJvO4nqCdwFJF5tOXtSORoqLo+9C0Zhh0zSHpJBspYQ7je9gkz6O0+Z62kQCU404pv2LqeHufmjPaqqZpqt68zB88rfgb3+W8th7CdX48n4IDcO4LJgANAwDAKlzpNhA8g2YruB8Cu0lTduGAtdaAJxu41sQt3HTNZwEyBYY3HwGWRjBqQNIZwy9Ae7MAcgKwk3r1LcsIlWJq6ZIaxfUBd47aC2pfUzcwSUzuGqsVjEuhmqEZPNINdUJI9k8cus6dD1MuoT2GJdnSBURkhLpZISn5OAi9bxzTvfjYw2O4TU16mN8lD2qg7iDdwKdBW3eqCZwQxd2RbhRH3pDXJHhJz1cmeI6BeHWSusEm3Vqo0dbBVe5qY0tSWNUXY0vpmKrKWoD09Tq1eNmBnLWvBFVczvS7dImrSulppajTEVma64x0266pF3dCMGmXnC7JjB+1Pi9pKkvbEyofUvnEWfzkOzV6GtdAUMoluGRP6K+91e0a7jKr8TH0jCMS4QJQMMwtNlj4zBsHFHrlqgF4zO4dAbJFmFyXseyddTQ2UmBtBY1lSkVxD1CDPk/LHQ8mxdcmRC6Q6RdUv5vLRV2IW9SykNcKJDWHlyxqXV37SWNliFItqj1hT6BbA5XbkIyg4s7wITytT1cVkNa4gZz0JkiDor/PUXcRLOfUabC0YnOyFU/GByCkwrZsliRJgIYymbaSAL1hOBiir8PPmQQV0g2xq2prU357YKLR9pJnM2rIKsmuLS5XU8bT8TdTbfxpqZ0W4sq1vIVaPWhtbupG8yhs4S4BFcPobU1jaQ5hs+gyjWC56Pmkjb+gN3GLzC5GMncssKJsuY5W9NHGouZpKf3J831tA+t9sWpJL4HtGG6ASsfhgd/j3D/b+E3H24EomEYT3SsBtAwdjhSbCLFAKExGM5XVRCUwOSs1uJ19uKKgTY4dPdDvoYbn8W1F5FQw+AkFS2ql8zDwRNEfzqHP7KL+unHqb81Qq6fg+EpXKyRQ8ZrjdhySDnAJX1tzs03cNksTmqkGOI6i7hKJ4f47j6knoJUyAtmGP/OKvGfV8gDbcKTlqm+VZBbHAzRFLVIE/FqN93DEeJpRsRNcHgkbut8Yp8hZaGWNL6jhs7ZHPLkFfKfCEQfcYQ9K0TpTZR/L4X5AUSzOCmRdFbPWTlB0gXwTXNHNUKSvkbtxmc08pd0dLLI5ELTCTynzShhAlJR+J6OwCvWmvRuH6bL2hTS2qVdxiHo84qhRgDTntbwpR10EkrV1BG6i+nt7T/1m+iheNiaO1x7QFRA+g4ktYrhutAZyZUAJZz/KFn4GIfqWcrRrSTdXZfxU3rlyfOcVqt1pZdhGI8bJgANY4cjw1MqMvrXa1p3eAJpL0FnL258GqkLXDrXGB8HFXw+BpwKslBpM4g7BdMVwo0zyI+lyPQY+AjX2oUbn9XhHp19uk+a65MzGpjr7MWNz2hHbmcPMj6P8zEuW0DG55t5vTPI+CzOxRB3CXsuUHx3wC3EyNo60PgEhhyijvr+haA1hM4jjiYlHIGIWtFELWBDx85FidYlph31OKxG+NYC9XxO/ZIC/Cb1/BhX7EXWNrSZwlcqltM+VEPdTzaL1GNNC9dTFXzFAMp1jbi1F6Fc07RwMgPdfTA4AklERQsXRyq0447ud7rcjK7rNdHKSlO3LketcpwKOX2BmkqOWxpNTbbWlYAPjQVOC6hAUjQV3UwViWoopyCxblu7pjO68R7Mh3gGzHABPv0fKfc+D7f0bOL2wuX/0F5GPvOZzwDqBPBo43fDeKJjKWDD2KFIvkZY/TREKZIt6EizYoTM3AjlGMZnob0Xkg5ueEz9+7p7cdPzEALSPQBVrjWC7T06zaMutH5P1MOPuIeEUsfApbNIOSJUU8gWcOVQmyfaiyp4ypFGtkQa8dJtvPVGOsrNp7iqEUbe40KJz+ZAahwBl3a1mQQHUaa1iQ6tgQM1gcZDlGjK28fN9I8KogxxnlDlzRoCUuVIrCbfagvj9fjpvEYRq6l2KUuhDR6h0nq+tK+1hS6FctwI3N0qvupcI3itJV1LvqKvJ1uAUJOGASFdappHNrTZo7WoayhWNDVMBPm6ppDjFKpNcC09ZrmpgrOaXhyv52M9B66pT4xSPXbcTEXxTeo36mgjS9rVc5AtaE1ge66xlUmBGMHD8mfggbcgH/0lysGpL9lB/0QjhADARz/6UQD9QwG44YYbrtSSDOOSYALQMHYgUueEfB2ma4jUOqGDpp4Pv21FInXjwZf01aB5cl5TnkkXPz6tAqJ7ECZniCmgd0ibSUbnoFzEhRmN7MVtpL0Hl69q80V7twqcJsq33USRzasQlACtBaQcISFv0p9jvZ7NaxdvKDXVulZBUauYk9BYn2xdp5kRjNbJCTgX47yaT/ukrRHCaghRW32ho1QjkeU6JF1cnOp+phEyGWgaO51t0rGCw+HSrtbbTZYRPK41o6IrTJsZwD0VWNUIR6Fp360UbahwWR+imIRxI3ybDt9qpILSp/q6fNSMiYshoCll32lG30XNCDs0Ypc2tYlR4wdIU+PoVARDetFuxjfPjxL9V6SZWOKbzuI2dJaoW4eYMAeuhHoIGw/Dp36L6rN/QDU8e7k/xo8rea5NLn/1V38FwNLSEgC33nrrFVuTYVxKTAAaxg5Dik1k9QGtWZu5SaNw43O47n5IZ3Cbh1VY9K7DFRsa9epdDwRcOcals7goQeoc4pY2h9QVtUsBh/v0hPQt87TfMEv6z9bx7+zhp3two9MqeDr7Na1ZTXHtJaDWiFbSwyUdKFZVdKRzWmsYtfHZPOTrOJfg0z6UI/wDMekvzNN6IyS/nhC/fRY3aiKAcYZzonWNUYrzkaadG5EjUoNzhLjbZFEjXJw1nn4z4JrX52KiT/SJ3uZJ39Il/g8p0btzyPapwAyFdvvWlYpUCfhqqI0zaLpZqpyIoCn2coqUU7WpyeZVzI1O6vi3bJeev2JNrV1auzV9Ww01EusTyJf1385uTSPXBXT3asQ2VOoxWOVqHZPoedJ0vTRiL2oEYJPWjdrN9WaCSJSpiEz6KnKjlqap065u672+lqQLUR9owdoDcPjtyMf/PeXmqe0I2hOF9fV1AP76r/8aUH9PgEOHzAPRuLYxAWgYOwgpR0gxaBoBar0zShEfIeUI6gLJFnACjE4hcV8tW4bHVFjM3KSTQUZnce0lXLaAGx0HHzFgN/4zqyRvy4k/dAPEIMkG6Z8tkP7KDIyHKvCStqZ4o1iFRjEEHK61CykGhKqA1gIuFFonl/a1iaMeQ5wRojb+oxOSt7eIPtUndAe4SUz6hzMkd1WqdaIW1IVG51zUpIk9TkOCOBcjdYlziQqhaqLNFwjOo0KoHBC/NyJ92wJ+INAu8BMhfk9B+ieLuk2+gsRtnG+iag7CdB0fZbj2okYA65KAayJ0XSgHGnVtNSPinOglSqh8plE/39Z0bKgheKBWQUYzui7uXRwRVxfNGDu/XY9J1L04oi5u63udzjcC0G2n0dVAuhGFAAQVwVI1gtFftJGJW4jvkjMHvQP6R0FnHp0oUsDgGHz6P1Lf/1+o8vXL96H+Gjl9+jQAn/rUpwB43vOeB8CuXTurucXYuVgTiGFcQkSEwWCwfXt5eZmXvOQlHDlyhFarRbfb3a4x+lJMp1M2NjZ0xu3XSihIRkcgVNTtfbhyRFQcps72EtI54tHD4DxV5wZ8cYGouECd7Uf8lCg/Dz6hGsZExQpOSsIogfoMrh5S+T4t2aD48xn8IwfID2wgM6egzvDtLvHJowz/dsDo2R38+oNE0zPU2W7C6ALJ5CjiEsoyJxkdwcmUqljAlQ8T5cvUrRZh4zjJ+BwhnqUan2H3+zdxGzNMlgpob0JU6+jfj+UMnjVkfNsaPl8jyteoylVcnTOeTJj4nHMXVojHa9TjFuIisuGYUF6gLBaIJ2uEqMKXAT8ZMP8nm8igS5k6TXumMb67iXvvLga3RrjOWab1PqJqqGnkGvzwHPUkIcQd0s0RIQIZA9QE1yUZHSFMHFVrL8loDAgMH6ROFxnLPJPNZSZ1jMSzuDLFj1dxq6cpuzcTTTfw9SZ1VkOI8GEDV5+mbB8kLsb4ao0qPYivp7iwAS6ljgPJ9BxltpeoGoIUBF/j6zHiYoQK7zwiJU50xJ5rRKcj0j8KcDipqCtBvDCdDFVU1pqGd3WLEDzR2qdwaw+Qr51luv/bCK3dX/vn9WtkOp1uR/U+FxFhc3MTuCgAX/CCF/AXf/EX19QMb8P4SjABaBiXkMFg8AU7B1/0ohcB8O53v5tut/tl95PnOSEEqupr82DzIceHEUm9iROhHp7ENRFAGa8ShdMEFxNci3jj0zhqingeN1ohrdeofJci6tCqHsRJxTTdjx+t0y5OUsS7mHjIGOGOQ5n3qeScqp7BjM6/9UPKYzHLN2yQlRfwkpNPC3w4TlqtkcdLyOgk7fIclesxnWzQKU9CqBjnJVl1mqTeYJr2iM6fZvcFoZSIqhppA0mRUsUjsjqnOOFYWVwhrVZI6hGTfAUXpviiJHc5qytrtMsB0zhDXMLsJKearjHOV8iqIbUricOUzsaYerxJ6fYRcg/ZEKoexEI2yZmcbuH2rjMqj1FFcyTVgLie4ghUk9Pk6R5auSetTzNNIoKLcZKTVQKTs0ySCCcZreoMIjF5khFCzaCI8eUKVVwTXEKr2gSBcblOVo9xQWB8nirq46lI6zHjYoM0TCHESH5B31fXIqnXKV2Np4UrVnBSU7kOsWzgQqDykMqY2iV4qbbrJH3IERcRSak1oA4IgVAHitDCF2iaXDLi0MKREzFCE+0lDO4nfugMo/YtrPe/USOJl4miKBgMBpRl+XmPiQhRFAHwnOc8h3vuuWf7tmHsNEwAGsYlpN/vs7GxsX17c3OTQ4cO8cADD9Dv9+n3+19RBPATn/gE8/PzX3NdUth4BEYlzDxX04ebD+oEi7lbkfE53Og00r8Ol3SRzeOa0uwdhHwNyTfVpNnp9A0Xd3UE3PgcuD24zh6qwRk+vSp0erfh21DvmeLLg/jkBsKuB+F8xu4bbmPXbSNko0ba+/D9Q8ja/SALuPmnEibnYehw/eu1Y3hNU5Vu7jZk7QGop/j5W5HxgGTuFH59L26hT9Vv4Se7cK0lgjvD4g172HX7M7RBIV/HLT4dma5z4ZEhUTTPk558K7KWaO1ctotwYlWbPg4+C7d+GPExEgo4f4J01pGu9ymivYT2caJyBiYxfu+YfTc/g7o3YXdnHr/rdmTzMKEYaFOJBHz/EEEOIhc+Av19+HQWyiHB3QCDk/juAvRvQFY+iQS12nnwwQ2WbnwOrfyonue522DjQUQER43rPEMnmqw9gHSW8J0lwsZhAFw8p93cGw9rird7EDYeaFK/mQrleqSdxPmKpp+zRRif1vrF6Zo2i4SS7ZrBUKLNQTmIMB5tMthYZ9figk5LCQXUEUgEoQV1D2ohKccQTjCXDzhwwy34vc8nyi6PhcrHP/5xFhcXOXDgwOc9Vtc10+mU5eXlr+h7ZxjXMlYDaBjABz7wAV7xilewf/9+nHO84x3v+Iqf+6EPfYg4jnnWs571eY8555iZmXnMBVQYzszMXPIfIQk1Mj6r3n0t7QqVyRkknUNaS8jguM6+nblJa+U2j6iH3MxNMD6LTFZwvQO4pIsbHteZurM3IfkAV6zjWwuNJcoIcZ76m1uQjXEDcPkMIjksF9DtUj/PE4oNJOrg27sI0zXtGM4WtcYv39Cmg/aSNomECtdawNUjraWLUiTuQFijvt0RbfS0K9dXUKZEZ0rYE+C2CEdT4+gitYORgDinnbPO60XARXEzPaPGhVrr3SToa+qAPHMTzrbwgx74gEhBdD6hvq4kPCmGpI1M1ggS1K5Fam2a8QlSjrTmMZ2B0SmtxUt76rUXpYRqrLOWe4egzpFqzNTNqIVL3ENw2rDTPQQIUlWEqKcWNqnW/IV6qh3VPlF7lrijIi7pay1ha782d9RjaO/Sho5ypHWCyawaXiez2vVL0DWGCXinNYRSqpfh1jhAaDqEU63lzHapkG7tUyug9h7IMvACeH3u4T8m3PdvKNcfuaSfdcMwvjpMABoGMBqNuP322/m1X/u1r+p56+vrfN/3fR9/7+/9vUu0sq+TchPZPIqrJ7i5W1RUTS7gk56OLaunmgpOOtrRCtrtWedIqHFpD3yETFdUfLV3a+Sv3ITuQb1veAyAkVuketEa5befxW3OE318L250krCron7VEizmuOmqdttmc2q2LKJdvbVO+3BxR1OL1QSiBBd3VLyGSkUNDgk19Ysi6jtTXB7gZEJ0dJZwHZT/6wTpZDifqVBxgkQtbbIQmlSk014KqVDz6KQRiI0ligScj8ElVC/JqV+0iTs/g1v2uGFOvb9L/coBztUaOaOCYoBLOjgfI1F60cIFh2vvgbom1DnOJ2o4nc3ray43oDWPy2agnhJJofvt7geCiu50ppmNLLj8PF4K6B6CYh03PIXv7QNE9zVd0VF+odDIXjaDdlmvXbTDCdNGHDsgNE0hLT0vcUsjw3FPfQyTWZ13nM1DuoC4NpVr/BnjTmMYXatYrMcq+Hyq3o7dG1QgTk7DyifhM79LtfogIdSX8QtgGMYXw1LAhgG87GUv42Uve9lX/bwf+ZEf4VWvehVRFH1VUcPLgeTrhHytsRtpIRtHNYoz8yQVelvRvs4BGJ9Bio1tKxjWHwQczD5Z5/COz0BnrwrAtftxIdeJFwS1S4lSKhKQCfXLAvKCjPqRDUIyItya4fYlyHgZ8Sm+s1fHr1VjJJvXCR+bR1WwdXbjqmEjADONdG08BAgu7TeNFlNod8l/ssZ9ahlOl0i/on76OjINOFzT4RzAJzpWTlwjeFDxgt52UaKir6rVysW3cYxVDMYpEhUU/58c/9ke1bkM19qA22ukaqnpdNwFREe7dfepdc3wGPgUSVq4fE27m6PDsHmYsPsbtJt6eEI7ckOpU0I6+2HlU6SyibSehas39dzGXU1jp3NQjpB8E5m7BVdPtXM77iLFWI9RjSDkSHevevjV00aotTQdXI5V7Paug9FpFdTZogrHMtfO63KgBtku0khglGlEEtcI5hLvm9q6EBqRGFQMBrXNQUqNMtYTGI2b8x1gcAL51K9T73sR7snfaSlYw7jCWATQML5G3vKWt3D48GF++qd/+kov5QsiozO44Ul8ax6X7cKVmzomLZ1t7EVKnM9w3iOhxEWZpgALFQGutQB1TpiuIq3dmt4bHNV0YO8g4lIYnAA8dG8gZQKT8yosbtlL/Q3HkKeP8Ut7dFJHvop3Hpf0kGqsNi2N6TJbET+fIqG6aPIMetunWp8oQhCQpIvznnAwUD87pXpBG8maUWdpDzX3a4ygo0xvA2oBI40Jc60TLHzjXyiVjp+TWkfF+QTnApTryNMd8rSEcGiCRIJ3Ma4cNAbPWRNVq9Qk2qWIi1UcVRMVcelCI0prfJTq8+IuUldqddNaxGXzRGGKhCYCmS6Ad7jRSVw2g+ssqZF0Ezl12S4g4NY/g2vN4ZIebnwelw/xvqWva3QcV071j4DxmeY8t/WYoWzOQ2hsX5p1CypsfaqR4SjTc5r2CVGXkl4zMWSmsaLJgFKjq+XGRfEXArRmoXs99G5Ub8LhcTj2LqpTf0Fdji/3V8IwjEdhAtAwvgYeeugh3vCGN/C7v/u7xPHVFUiXUBGGJxHnke51iAiyeQRJ+riZG2FyDpmc14hVewnZeETFQP8GnAgMjqn46d+gacbpBZ10EXeQcqhiLumDlNq8EGcQJUQUKhyz2WZqR0CSGUi6hHydEAQ6e7S2bbICcaYzgPM1FZVJH0l6Gk1zHtfWcXGuHjcjzDLI1/Ahb3z+ptrd6536+9X51hm46HHoomb+rdqbCE5FThMB1FFpqYpBAiQdNYWOUiRqI0GbISTuNCPuUFGXzSFB8FGCS/pIvoFUU1z3QLPOCxpJ8wmuGuh4tnIEg6M6AznOYLqitXYScOUQaS8Suyl+eg56BzVClm8iSV9rBV2sU1Cma0jUUoFeFUg6Q0CjdtJe0tF7eOgsQdTWlHTcU6/AdFY9GLv7m3FzQ72eNrV/SV/H6JVrWi9Yj9E0caxpbgKJm2hTyNYcaBEg1vOYzmtavHtQaznbe6Dd15Q0AE3U88G3ET71G9Tl8HJ+NQzDeBQmAA3jq6Sua171qlfxsz/7s9xyyy1XejmfTzWG0SlcNcb39iOh0uifj5Goi1S5FvPHHainCIKLdSSalEMVYdkuyFeRYoh0Dupc2OEx/fHuHlRxMzypzRT9G6Ac0gobEHfw3f3I+nncqTX8uV2wluKmq3hqbYqoCwgTnE814lcXKoIi9WGTulDhFGWaBg1Bo2VEGgGMutvm0DIUONvDHesg46oZldZToSaVCsCtur4mCOgkoJ2tdVMniOrBaoJzTiOA1VAFmPOQD3BnSvyZGLdeQT5RgRwmms6N2oDoBA8f45NWU0eY4LzHVWM9f3FHRaL32uEbtXSGL04je+29Wl9XDtV3b0t0RjEuX9H99a7T9HmxBlFbI6g+xm0e0bX3DupM5+l5XGt3Y6Y9wE3OaG1gncPopK6nnmgdZpyqmKumGhn2sU53wTVm1NKMg+sgvk1FW1PdaV+FbdxphGNyMaJYDfV9Lje01jHraVd5/2Y9X9NTcO5vCYf/O9V07XJ/QwzDwGoADeOrZjAY8JGPfISPfexj/NiP/RigA+RFhDiO+bM/+zP+7t/9u1dkbVIOCdMLkM3j0lnC+Ix21/au05TdxoMatZm5sXkxR/XHffZJMD4Pw+O47gF8dy9h7bO4Yg3X2Y1sdbWCpmJDpWnjuNXU0E0IeG0sOVEQ/XWA9V1E+QLSnVA+KcDTdyNxDxmebOr99gABmS7rPtpLuGIdCVOIu5oq3ngEFyptRgkFlJs4Lzhx+E9Okc9U+BFEeQK7S8KtHjfbpDRpZtkKgNMuYFwz5xiNMvpII12gPn1xG/EpEnV1jVUMH3XExzMkHKDsHcWdLZHnaxpUHEjah2KDUAzx/VijXqPzuHwN6e6D6QqegLQWkMkyYXwB1zuEmywj45PI7JNVkJcjSt/GlRswOgPdQ0ixCcOThP5N+td6nUM2h0zXtdGidx1sPqw1h+kCUo80kurSRnjthmqASGgieoVefDMNpLMPKccQ9SBd1PFycUfP0fgMJK2mc3kd4jbOrRNRoE0nAyDS61uTQ5zTMoIaSCJgXkVlXajgnK6xVZuJc3DqQ8jgGNVt/4C4t/8yfUsMwwCLABrGV83MzAyf/OQnue+++7YvP/IjP8Ktt97Kfffdx/Of//wrtjaZruAGJ3BRpqPayiGuGmvkzTmNBnqvoq+aIEQajaoKjQamC7jWAmF8Xps7etch6Yw2LYRKa/98qrVcoPOCqwlMzxFIcG4//i83kdFZZG+KPKlL3VkleniIP9VRwVWNdERblDYdvqWmHb1XoSJBxZVoyE58AkkXwRHEI3EXd7qLv1fHr8nBOeqbSpgI/v4EGXaakyEaHfPahLAVAdTI31btW1AD5FDhiw2trXOoCBPBn6zwJ6fI4ibheoGZEreySXyvw4WAK4aNNUrQ81xPNQUsFaHU1LULVWPt0lXRU4201jBqqU1N053r6ikFs0jcgnKIi2J8oql314hs58D1DkFoOqqzBY2iSgXlOj7f0EhbPcJtfBY/c50eq1iHaqT1h1EGm8d0Al17AQbHVVwnPZiuNmKOphGkUnHuM035+w5CorezWa3xS5tmkrirtYYOtYgBbQypBhoJrEYQeZ1j3L0RWntheg4u3Iccfif1dP1yfEUMw2iwCKBhAMPhkIcffnj79pEjR7jvvvtYWFjguuuu441vfCOnTp3it3/7t/He8/SnP/0xz9+9ezetVuvz7r+cyHSlEW2HcOkssnFYDYRnbtK6t80j+mM+8yRcuYkMT2jn58yNyOCopo1nnoTL5pHVT+OKTVx3n44LK4e4JlUsoULqChelKuJyFUu1y3CnHKzmyHVdIreEyBTpT3CTRfzRRepbNlV4pnO4dFb98UKF6+zVqNBkGYjUFqWaQL6x3anryk18NYR4Dn8kRmQTmZlo/Z+rYXeJOxkRnRJCv5mYIjr9ARHEP6rub6sB1TlCMqtd0kkX4jbiYkKUQBHhzxSEfoJrRzgWkWSBMAfRqRbuKfNIV2v0yGYRIFS5vpb2VuRNmnTrVFPrcVejYL1DMHsTTC+oTcrszdrtSw3xLJKvECYrTc3mCrJ5GBaeoq+1moJPCMU6XiZI7xCsP4jk60j/Rlw5QvBInKq4jttImYJU2pASasg1zY5vvAkbGyDX3ovEbT333X3NnOZaSwJGx3F4KpdpbaBPGn/AJtpaT9CflEqtYXzSzCCeg0zUg1Eq7UZ2Ixhv6OfRAcufJBSbyK2vIu5/bWbnhmF8dVgE0DCAj3zkI9xxxx3ccccdALz+9a/njjvu4E1vehMAZ86c4fjx41dyiV8SCTUyOoWbLOOzeZxPoNjEhaJJn5ZN9C/WGq86R3yq0b96AqFCsgVc2lchKaLRvuSiSKN7AInaGv1zoiJGarUUcTETN4vLR0hyFuc80AeGwCokghttNW6UOB/hnNd6v61ooKCRLB/rbee0BjDSjlZxDokyyBZwE0fIHNADNIUrCEiClJ3metDIonPqodekgreaQpoThw9TFTyT8xrJcw5fjvCTDZyMIV1H2MAheHJcuoqrN6AUXDXAlxv4oNYnLl9RexlqXDXE1VOtzSuH+DpXI+16AsWGRmkBKceIT3DURJQq0sTp++dj3FY0zcd67kIBnX24AIzP49u7NMJbTvGIRiJbc2oAvXY/rr0b19kHwxOI1PjWbPMZGGiKv71PG1SGJ5H+Qa0vLBr7oGqkdY5OmoYaUREaxSoko87FbuFsTj0Dk3kVjD7V2kCHblsO9FINgAJac9oh3D6gDTEXPooc+RPrDjaMy4QJQMMA7rzzTu2W/ZzLXXfdBcBdd93F3Xff/UWf/zM/8zPcd999l2Wtn4tI0IYNlyDdA4hPCMPTSNzSCFKda91d2m0iSue1vqu1gOvuR4anYXwO317EpTPI+CwuX9fpHz7SdCS11vtRI3WJc3GTegx6/KiJnPW0E5jpAkJMYAx08ev7kf0VYbquIq6zT61gioH6/WXzmnatppqebiJlri5wcVuF63RVDa2dJ+wp8PkmSImjAqa4ssJ5gblK066aNL4YAdz2AfQqZhyAJ6SzTZfsvApNnyFRgswt6vSMwSyOGGgDB2A4Q91NkYUFncyRziHt3Ug2iziPczHMPBnxHZ320d6DpF1C0kKyBYJPNT0ctWHuZk1FT5eR9n7ExTiXaZNLOUTKCczepudocJSQzmtErbGUCWWuVjKd/VBPCcMzSGe3+hkW69rM4dxF78N60jTGJBBqQghNuraZjkKk57+ZJOKSjlrUFAONakYaSSTby3ZOPemoSKzRf8NUu4u3zKH1pDcTSmY0Rd09pDWgaR+oYGse7+qnCPf/JtXowqX/4hjGDscEoGE80anGyOAorprgO7s1SpQvq1FxOoPUuRo3u6SJ/BSISxorlRwQNVyOO2pnAkh3v87jnZxHQgmd/WrpMjylRr+dfWrjMjihYqSzGwDpn0IOlsSn5vHnStxgGX+6htmUcPMEV400IrYVFdry3sM1NX+iXamgNYvOa9QRdO1xB4m7hCdB2JXgT8zAah8uxLizjrC/A9cnF4VP3G1OkjaAyPZ/ebI9/iwKhYqW8XmEWreUGlcsI9ev490IzmzAusOtTqA6jzzpGK7n1JJmchbKAW66oundchPvBFds4IYn1DYnVPjJqr4P1Vi9/Oqm67jagHwNF6dEkkO1gYti3XZ6Hhenas9TbEKU4kKBr0ZIMoejxm91+CZd7faOOxr1jFq49hKMz+nIu7mnwHRVmz5mbmk6pQt9H1rzmgrePIxrLaldzOC4jreLYmRyTn0NQ0XCtBkTF7R2MDRTRZxXgRil2nCULTQTROZU+GVdTb/XpU6SKdaasXMptPfrZ2q8Amf/BjnxHpsYYhiXGKsBNIwnMCI1UoyQqIPL+no7X1Xj584eyDeQ8VnIFvG9Q8jojM7Zbe/BdfZobdnkAn72Jlw6Q1j7DG66gpu7tanvW1N7lChrZs/mTX9A0kT/qsYMOMVJ0Dq4Z3aoF1PcQyUiMVw/S/2MjDC7hgzQlGTcIQxPqXhsLalFTb7aGDnP6b/5KrgIH7eRaqr1gKDipjsi3L6OP9HCnw5IOibcNEGelKqvcz5pZgCXgKhIATV21mtsFQJK1AaX6Vg7Ym06wRGyedyBmBDVxKciotWIqruPsOcs3NojSrpIojN78TFELcRFeruzH+kdxPkIidq49hIy3VQx5TOtPaynapA8uqB1lc4zjeaRdB6JI3CRdlbjYOEpsPJpZHia0DvY+PJtIlVBEKcp984e9XscndYZzXWhAt7FagZeV2oxUwzwnd0I0kxcGeF9rGOS6zHOO8TRWAR5vNSEZB4IiI8YuyUVgNmiCrq8qWkcnlTBHUpNqeM14ihVc/5rtZQJoibfSQ/Ea4dwMYR8WaOKIYdzH6eOMuSG7yBKWpft+2QYOwkTgIbxRKbYhOFRjfp0Dqi4G52G9m5cNksYnsaVYxVVPtFontOaO6Ta9thzUUtTsjikvU9Twfm6TqXo7lMD4sl5/UFvL+n+Rif1h76zD5IumWzgqh5uZjfy7IT6xuMwWIaFeXzPw/paEwFs0n3VGCcB5xshFtTHz/lIo3/Cto+f+EhTuD5Tf8C6QuYy6qUe8k0eKUHGGa49r/t2iUY54y5q/aIp0EDSpH+becA47Yp2QDXFIToGDsFXYxUvSyVh/4iyN4CpwPkcxseQuesa+5ZNPUY10ahi0oX+jer/V2zg+mchSvDFKkFE6wURPW5rF1INcZPzuJnrtSs7v4BzqdZxTlf0fKQzGi0bn8LN3ayRt+l5aO3SaOXoBD7bRfAnYXxBU/3TNX2/e/uRusDVBWHuVpiuINNVWHiaNo+EShs+aIyy85FG7Po3w/QCkvZxM9chw2O4UGmX8uR8Mwc5hmIdfAsXSh1H10RWcammuV3UpJeDPhYq/RxVuf5bDlT0eTTNXJY6x/jYnxI6+4gOvOgyfJEMY+dhAtAwnqCI1NrMEXV0Lm9daM1YZx++s0cF3HQF192ntX7jc1ps31pUb7/hSVy+gnQP4rI5wuYRmJzTTuC4TRidwRUr0JrXCF01wVU5uATnHKHW1J/zSdMcEJAow8UtRGqIPNKZw2czGuEiQLYL11rQddd5M1JsQc2rqwn4DElmcOVQxUHUhriFyzc0UpT0wcW4clXrzOI2LnVIPtQ6tWyXnpxqqCnUUIDU+i+Cp4lGCSpGtmxnAC1ik+16OXExzjcTQpzgWjGEjtrguExFZtJD6qk21Hj979T5VMV2ez/UFSFuEaV9QjYPzSg7nOB9omV0c7chIRDEUfou0p6FVqSdvCJ4l0C6gPRv1GhbPcF3ljRF2rwu8Zl2VbeWYHqeMF3DZXMqrvLVZpzbrL5f+SqCw3cP6DnNVyGbx9dTQig0jUylkdF8uZnC0tXu4qiPkw0ViHEHCNC/Caocae9VM+h8FVoHtHko7jR+gaLH2ko5h1Kjfz7SNDFALZqKH56BckU/Eyf+nDLtkSzdcbm+VoaxY7AaQMN4opKv69i2KMH3rsMV67jRcfXYS2eQUrs8t7tsQ67RoibFKaFGfIqPWxoFEtFmjLSvAk2Cdpu2FpByhJQD7RTuLKlBcbGuXaDtJSg3SRk3/nBz2twxubBdi0Y5VN86qQCv0bZqvBVzakaK1doli2gQCdmO3ImL1XS56eoVnyBRphYsAFGqfoXbt9tI0kXino5IixLExdQuvWhC3DSDSNy7WLu2Vccmovv0cTMft1aBGndU5FRDtU3xMV62hBi4UKqdSz0mavV1WsjGIzrZRHRaiK8GuGJTPfcm5/FxC1cPYe3ThKCv243P48Zn1MdxuozLl/FRihufxa0/BOk8Xkrc6LQeVyrc8LiO7JOAG53cbmpx+RqSzkOU4YtNpBlXJ5MLMHeLppyrEaF/E7SWkGQeSXfppX8jQgTeI7NPglASh5GOeisGWvMYtXD5WfX6y9c1Cj1Z1oaeeqrRVd9EA7PdWlfYux46u7ROMEqBoN3BxQq4oDWJrgPrD8PDb6Manb883ynD2EFYBNAwnoCICFKXGvmJO3q9LpHWEr69qxFsE1z3oNb65WuaEmwt4Tt71X9uugLteVx7UesEx2dxnT1NJ/A53LhJJcdtZHKhibCpxUwIA2gmgTjnm2ia6IzbbVkXQdzHuUgDblFLaxGjhFDWan3S3o2LEkK+rpG41q4m2jiEEHDprNrFlM3jWw0h+XpjJ+Mv3i7HOKlUuBbrWrsYcggprspxUuKlVBNlCY3orBq7lonO3W3G5AmoaK3HiDQ1fupn0tS0TfXfqIX4SE2hRZCtblsXaTTTJSoqfazRwmrUCNAEIei5S2eQdKHZfwTJrIpz0LrOUOl23f1qsO1jvIsg24VUBcQ9FcUSkPYemKwQqgIXanx7iZBvqDij04z8i3CDw/ouLTyVsPEgDE/gsnmox0ixhoQcH0WEqIObnoZ6gJ+5CV9tqHF2nKi4y+Y0XR/PNpG8ANmMRvjSXiOci4uRwVCq0JMmChjqxpgbjVLGe6DltHZz/YhOsRmcRE68j+rG7yDOepftO2YY1zoWATSMJyL5qqbYkrZOhshXYHRC58Vm80i+oQJuy7y5nGjEzTltTAg67UGjgU06ubFfEQlIKJF0VsWj1IRyrNG23gHddrqqwqZ7ABCtRwOt4QJkdIq1+hFO8gDDcE7FZTnEx3o8pqtNqrGxEqmGuGYmMNCYC19ExAEeH+nfrOITxMcUruLo9EOcqT9LHUVI3FGxlPRUcDVjzSRqE3yb4DLEt/T5cZOqzRaQZAZpzTYipK12gekMrrUbsjlG9VmOTT7AMmchmWumfYha4zQCUdJ+M0Ku0Oab9m5tiigHOgM46akYribgvb726QUVi+kMFGt05LweN05wxbKaJksNk/NaLxm3cMMTMDyJ6+7VyN/apwlNTaMfn1Rbl2qIGx7R98NH+pykr2bU0wsQ95Gog+SbKizjGUJdEXo3aBo56RBae/HtRaR9EIn6al+T7VEj6GqqtaFE2gXdWYR8GTc+q+V/g+PqLZivQ7mqfoL1VEfzxS1IFrSJpL0E7X3aRZ6pPyH1VCOInkZMAqfuQY6/+5J8lb4cRaHR3eFweEWObxiXCosAGsYTEJEawTVjxEQjRnFPo3d1qcbPnb349m6kmiDFAFqL+O5+9ZebnNfmj+4BTeeOz6lpcmdJa+vGZ7SWLe7oj/30AuDU4y5UuGoEbPfRqmBzDgesVo/w4fX/k6JaZTUIxRieVX0Td7S+k7gRmPgIyRa0Lk0ar760r+JVAlLlKgbSWd2+GsGWJYzUuHLI0fyv+MuVP2YSFeweelrS4pbWj3JD9FI1Ua5zFZU0RsxhivcFLkw1ghciqHMVouVQI3rVWNO4EvDFBlU95FODt3FWPstaEcgj4fbNvdyW/j3a5UA7WV0E9RhXDjQF7mM9F6HU1HAxRepSI594qEtcNd7uNsY5vPcEnIo9F+s8Ynwzti9Tw2wX4ZIuodgE5/E+xqU9QiggauPqMcHFmj7NN5EQ8A61dQlTJNQaBY3bBN+CfEUjpLM3wegcbuNB3J7nqsnz6LRG5aoU52qdBLP5MBLPEItGDGXuVhg/qFHPqKPp9Gwe0k7zbx9CCmFGPyOddhMN1PNOM4KPeqKTQ6Q5X06bY8gWdZv1z0KxCmf+hnLfN5P09lzS79bGxgYA999/PwB/+Zd/CagAXFxcvKTHNozLiUUADeMJhhQDGJ+FpIPrX6+NAePTELfwnd1amzc8oUYnab+pv7uAk1LtXOpC06cAuK3s7cXaQEHtTJK+Rsik1qhZa7dGb+pc43bt3SqAigHUOQUd6iTlfedeT1VuUHkoIiGr4cL4r3hw+qcaOavGMF3G1aXWCNa5Gk+HQkehhVo98ghaMyiitYt4nJqVcLb4FJ+evpOKQnWKh5ycu4f/ipX6iNYHxi2N5kUZkjQRQJ9ppDPpaZTQZxq5S7pI3MfFagcjXusLP1m8i2M8qClsoIrgXLTCZ6bv1fRu3G1GqqVIugs6e1WoFgON6nUPqCisc0h0/0SZ1iq2FlVM56swdwvEXRKZAIJrLULUQ/LBdprV5WtI76Aeb3RK06e963Qfg6Nav4ngyw2dnVysaSStd0Df0/UHIZ3X4+arGoFMurhQQ9LROsmqQNJZJGrpe5x0tFEnautrjNtU6G0fZbikB3GnGdHXA+dxw5PQ2a3zh+tSP7S5/gFBvqaijpomBK3iMZ3VS7sZo5e0gdDUBGo6nXwNPvvbVOPHxyR6a9b0uXPnALj33nsB+NSnPgVAp6MzpV/4whcCsHfv3sfluIZxtWARQMO4hIgIg8Fg+/by8jLf8i3fwuHDh2m1WnS7XRVBX4bJpDENdg5fbhBPThGiLtWwiyvXiKdrhCRQD0/gi2WiYko9yQnD4/j8Ar6qqYsIGR0jmpzG1WOqziyMThCPj+HqKWW3B8OTxOMj+HpK2Wkjg9PEo8P4cp2qcz1h0xFNThFPT1G1C+oNhy+W8cOzOOCjZ95BXm/Sw6uXHBAQhMBD0w/QP/X/wodAMt4gRG3q/AKEini6iZBS56sgNfF4BVxMlW+ArBCPzoFzVPk6yAoPT95DwFF5iASSCpphcNx77nd51vCbAaEa6o94MjrBZLTJxLU5c/wwyfgoEFEMdDRba3UZcQnTcBQfJsTjkxSu4FT0UTJxxOJIa8fYCYkIdb3OQyf/lF7rG0lG5/HVUG1qnP6XGuIR1WZMtn6CqLhAXi1Qt/aTjFfw0wvgzxKSOVyoqDcD4mJaayeIqoIL588zikuS4VlcPaEaNobIzhP8OungPBJtUBS7IBRk68uEaESZzxIXF5o0usMX64TRI5Stg6SbasKdywXicg2frxKiGdzmGeAUdbpEMj6DDO6j7N5KNIGoOErVOYRroqHihel0hTFdNtbXkPUPU7cOEE9O4Kipsj1Euf6hUY0T4nyZELURYuJQUk42iYIguY4DxMWI1CruQwHU6kMYSnyYNLWBCRItgYxIy/PIhU8wjN9Puesbv+h3ZTqdsra2ti3wHk0IgclkAsCHPvQhAE6ePAnAwYMHeeCBB/jGb/xG7rnnHm644QaOHj1KkiRf9vtpGE9ETAAaxiVkMBgwOzv7efe/733vA+BP//RP6Xa7n/f451KWJePxWH/wi3MgFXnSxk3OkBWnwTkmySLR8BSt8iSBhEm2iyicpl0cJ7iYybSLY5N2cQpwTPIZxEW08jUcNdNijUBGq9jEUZIXmwSXkxUjvATyKie4ZdJykygk5DWE0TJJeR5f1UzdDMPJx2lHEUhglARw0Ck9XhyjdMKF9TN0ipysvEAR76KYrhNX67SK01RRn2neI6oHtPOz1L7FZNojCjmtYhlxMZP8Ak4C09Yyzgvb0tk1zi4usF6fZnMwQhDyYgPB087HTIvA1NWsbIxo5SXiavJygKsnzE6m4Co219cQHK1CmPhV4j7ULlDhKCMVFLkXKmB1eoZiOiTNa5J6DC6idpqixldMJyu0ipTWtGJarzFtz5DkgawqCMTkSUwWRoTxeYp4kVa9QCXnKNfPMsoWaOcxSRWYhqAiql6jih1RvUCcb1AUJyjS3bSqBbLJMpNyDfEZUT0ECcR1IOQbFJM2PszTydcoLjxEke4jLRLicIGAo4561JNNOvkAR8mg3EVWjcnKNYpcG0GiagNHoK5rQugyHo9xoWBUztMpxyCBaT4mk4KaFPI1RFo4cpwUBJ+R1Beoox6xbGrKt5l9rFY8dTMdJiASgesgxLgwJQkD4mpKjSAhh7N/zThvM21d/wW/K1s1eyGEz3vs0aLwGc94Bh/72Md4znOew913382ePXt44IEHvqI/yAzjWsAEoGEAH/jAB/ilX/ol7r33Xs6cOcMf/dEf8cpXvvKLbv/2t7+dN7/5zdx3333kec7TnvY0fuZnfoaXvvSlj9mu3+9v1xQBbG5ucujQIR544AH6/T79fv8r+sH5xCc+wfz8PAd3zyDrtdbrzT8V6gmyEevtuduQaoRsaGrOzT4JKQbIoKM+b70DOupt1MW1mkkh0xXC0OE6e/HdfcjkAmFQQWuRaOYGZLqCbBaQzODmbtWGhrUC/BJu4SlqHbMWqIoe5z6zzi37n8unT/+ZWtE47ad1ouIs9X3uePrzYbKMDPu43iF8Zw8hX0M2utDdT9TdRyiGyGYf11rE9/ZrA8qGeh36/vVINWF44iAnwwPUHuLGvq/2EFzEdbNP4abe9eBi/PxtOhFjw3Pm7DkSN8ett9yErKvfn5u/Deqc+swaEHHwwO3a+btWUbCLh4cOL0KndITCMcqEMtYe55t338bi3mcSVhNk0mpSy31cPdIO2/lbCcM+4cIY39+F3/s0ZNBHNrRL2nV2Qz2jkz5mbkBWco4NjrK0b47egacTVgKyeRjXaasdzzhFWgswjZHhFDczh198KuFCjqyt4ObauJmbYPMhQlXinHbhus4skl2PnFmHpI3f9wxk4yFkeALpHsTHLaimBL8XxmfZ156F/jOR1ft1pvL8U2B6Hik2GQxLJufX2H/LM5HpeUhnccn1yOCYGj8nB7S7PEwhW4LxaZz32tgyzJHOIi5PdBpKnGkncJQ1HdkC1Nr4UozUaqcC6hjCAlRzMF2h7c6z0DpB8sxXfMHvysc//nEWFxc5cODA5z1W1zXT6ZSVlZUv+IeZYewkrAbQMIDRaMTtt9/Or/3ar31F23/gAx/gW7/1W3nXu97Fvffey0te8hJe8YpX8LGPfewx2znnmJmZecwFVBjOzMx8ddEGETUdjnvQO6jebBONjNG7HhCd1evQyQ4iWgsYcnzaB5z+IOdrOB+pdUixgStH25E0CbXW3jX/NQhe7Vyilm7vIq2vy+a0PhC0Pqy9REXGDcnzydwc09gxiQUfIKmh9sKTZ75Lj5OvAR6XNJHPyQpOKnxjpEy+qvVjovVjrhzo7UpTd1Rjnhy/kCSosozEEaEXj+Mp7Zern/OWoYuPml5j10wTSfR1uETTkDiknCD1BEKORG0k7hH7Djf755LUjmkkTGPdixfPDIvMRod0Pe1Fnf4Rcnw91m7bqKPH8LGOdAtBVXC2iCRt9epzHtpLWnsnIOk8les0tjFRM3+5T/AZtPdAexHxKaG1F+kdQuK+RhvnbkZ6NyBJF7I5pLMfuvuQ9h5CewmJMsiWkP71iEsIUuFau5D2kjYLVVOIM1w2gwsTNQ93kdZfTs7B9DwuVLh8BV8u065X1DqnGOA2D+uZr6a4ahPSOX1e0teawNYi0toH6Twyd4t2H/cPQdpqmkCCdgrnqzA5q81IxQYQtA6wvQ96N0HngN72tRpKrz9EtfLpr/y7YxjG52ERQMMAXvayl/Gyl73sK97+V37lVx5z+xd/8Rd55zvfyf/4H/+DO+64NFMLnBQwWlbrD39IoybFhtZQOQDRmqpmfqymRL12iEapioWohbQWcUlfrV5AI1GtXTqto9jUsV6N/QuT84Brxn6hdi7VRKeLOK92MNMLkO7Wbtaq4Jvar+Xe/P9mhaNEAqnE3Nh6Mbd1vgtAu3pxTcRHG05wybYlDVELibu4RMWy+FQtabLF5nbGfPsZPLPzv/GB6rep6wE1QDLD/2Ph/2A2up7AZ3U6h4sbzz4Vs+D1PNBEm2jShHFb73Pxxe5dB7fN/H3yoefC9MO0K2EgwmzrFm7iBbitBod6qp3TUQqtBaSc4PMVXLGo3npxS/dXjVQc1UGtdXyGqwvcdAWyBSTtqy9hvgzVRDuD6wKmF3D1dXpfKJB0BqlGuGINSTq49iKu3IB8Gens03q68RlNrboY/AgXtfAOZHpOjaR3PQM2juDyZWThaSr6x2cIrV1QTnHTZWTmJqQcaVNO/xASKkKxxjhKoLVb36dioM0hvUNqBVRNtMmk2MRNz2hzyeQcTgok2YUbHUfau3HVRGcmu1SbPNpLKuyipmGmLptRcQNtMiqGUI8gmQVJYLKCHH4nYeZGfNK5JN83w7jWMQFoGI8DIQQGgwELCwuX7Bgi0nj1tdXQtxojUYpL59W/b3JBhUZnPy7pIqOzmk7r7FGz6Ml59ZNr7dJxbfkabnzuUVYmU7VDcWg3LvF2bdaWX5+4SKdLbIu1WLuFs3ngNOI83daNfPP8L3F7OmZanGUhhaR9AJ901QMv1Cq4kp5a1lQjPX7cVnE4XdEU6lZYMl/VaFOn8QYsNnHFKtd3n8P3LrySlcHfEIfTzHSfSpw9Q19XyNXmpTF81i7iRvA1Lb3bJtL4i/6DEpoIYYwQ8CLc0fse8ta3MfBD2vO305tU1Gf/GqFpzkj66jdY59rdnM7rVJKohatzggQ1WPYZLmpDNoMrN1TodQ8g2S71byw2H1XLGOPSGUh6uHJEqCu1cynWEXHq7UgHFyU69STbpeclSiGdUyNwvHo+CioEuweQySoSZUTO4dvzBILa/VRjtfxxMeRH9Rz2b0Kcww2PQ2sBHwqiYplMGoEZau1grsYqEHOt7ZPZm2ByViOUySyUE23kSHs6Vi+ZQeICZKoCsNy8ODUkX29MopvpKlLp59NnwCKUUygfgXoTBsep14/gl552yb5zhnEtYylgw3gc+OVf/mWGwyHf/d3ffcmOEefncMUGPunptIzRGdx0Bee9ppLLAa4pyAeNtDknmmqkSef6TK1Ltm7HPaS91AiFoObI7b24uAPVpDGEnlN/wWqs6bko1R/xUML4HE6kmZSBpgzzNRzCfHwDe+V6kjLXaA6o5UuY4KQp/ido9Mm57e5VcV7T2k1HrUQtJG5fnAISt5BkBrI5Ipey2L6Due7T8O2lZvtM/QKzeZyPtke6Bd9qImKRTq8gUuHpRNPNUjbRQfS+0NwOgdT1WIpvoB/tAUTPeb3lrRdUINdTxLfVCqWaqHBNurru4DSNDc3EEK/iPcp0XNzkHLR2U7qeRiCny1qj2KTunQMfxeo1SK0eigQdtxdyXGev1oMOjuOyObVoKdebTtoal6/o58B7GDYmzZ29Oqd3cERTx0S4fFU/W6Iq2aUL6u+HQzp7CL5FTYakc5DNI9kcEnV04kt7Ny5u4aOWfn6cx1cjFZjlhppE+1jH1EnejJJb1vPdeBkSNzOL0zmNCraWGmEaaSS3XIM4agy2J3D8XdT5+uP9VTOMHYEJQMP4Ovm93/s9fvZnf5Y//MM/ZPfu3ZfuQM43ky1STc9GGdJa0lFiTTqXzh5ce0mNg4sNFUKdJRVrk3M6gaK1oJG20UlcmOCjTPc/uYCbLMP2dI6x1gc2c24RHXfmtkaiOa0PFJ9sizWdwTurNXGgs3TTBU0Loilp8ZmOmPMRhFrr3+KuRjW3069adyhSN6IHtkOC+RqunmqDAui4sHx1u0bQlSONphUbF19HNcKHqQqiOlfPwZBrdBCHS7oqWpq5tG5rfnLSb/wQ462MtYpm30KitJlzG+vjUbd5m5JmUknW+NxlQE1wkYrPpEk3V7nW4Pm2RgelJHIVhLHOznU6fk6qETI+vz3/mLrG5WtQDAmic5I1tZzrqDl1gETqSj0fGxGI801tX0DqQksFXBMh9Bm+GujraO2CcoSbnlMfQ6lhfBafzYOLicMQF6dakhBlECa4/IJOVMnXCZPzKi7zNUJdqZegVEgU6f6dB9/SGdFxW8VclOp131afQ+omBTzR9HrI9Q+EuKdegcms3rf+MGF48nH5ehnGTsMEoGF8HfzBH/wBr3vd6/jDP/xDvuVbvuWSHSeqh43ZbhuXzWqqbHJOmyqitpo9j8+pCHIeQqGj36TWCJ2AhK3mDo0KiotVIG4JQJ9qfWCm3ZEiopG27j59vC5UOLYXNQVcND/MzQ+5l0LFmaMxkA4aIayGTfoVfTxf03QfQK3+dC5MNeok1cWIWmP6LJqv1QtNTaDPLq471ppBEp0TK3FbU7BN3aJEHUhmCFFfo1lRW8VaOqMiD7QJpBprGtenem5CjZuu4co1TUluWWeHQiNnW/OLfQJ4KNfVhFsqwOOqEVIXeEIzEWSzicI1Iq4aqchz6kWIVFS0VBzlq3q4bL5Zj9OaSB/jCNoN3Duoxtj5KszcqI0iQZrxdvNqRB1lSGevRjslILM3qdH11lzn/nVAQMoB9LR0wNUF4jTy6qJIjcCLNW1owRPLBMk3mjLKUmshq/HFtH05aeYdB50q4pImEtrV19Za0Ahga1HPaTP9hHxdBV++rp8rqkb0tS4aRLcWNIoZChXT1RROfZC6nDxeXzXD2DFYDaBhfI38/u//Pq997Wv5gz/4A17+8pdf0mNtCSK3NXzNaeTNxR2ccwTnt0WP9xGhrJE4w7WWcFGGbE1gaO/WesB8Q8eRxR2IO0g51m5PvHbGhloFZjnUSRGgHcPVSKN0oKlFqdiKGAoecU1ECo9znhC10Jm5Tfo2aiGtXdocAYhLdIRda0m7jHWWBSRdfJQ1Y+2aZoYo07R2PVGTaRfpPotBI3Q19e3KoUaNyiYiVw2RYgNfj8DP6msoNyEUun+pVUxIY+RcF7h6qoIpm9HGkHLQjJArVVCms7i4r8JQms7prbRo1MaxBlKrME3ncXXOtoBEJ7RIrNM1NP0NxB0d5RZqRNTj0HkP3kE5Quqp9jVLrennfL2ZnVtqM0k1hHITKQfaVV1saqSvLgBBpk7F63RZawf7BzXSNz6Pa+8GPwfj801dYaZTRDp7obMfijVcNSV09lO505D2my5qr/OFnVPR2T2on5mkj2S7Nc3bSpCmo9glXf385OtIq4RyQ/+AcR6iRLuHq6mmfeuJnq1yoNHcYqA1raFopqMkmkJe+zQyOglzN1+Cb55hXLuYADQMdM7nww8/vH37yJEj3HfffSwsLHDdddfxxje+kVOnTvHbv/3bgKZ9/8E/+Af823/7b3n+85/P2bNnAWi324+7v5iI4KsxksVq7yEBxlvduQsaORue1kha1ETrJue0PnAr9VpOcOUIsmJrr4A8SlDGWncXpbhmlq1EHWiluKSnx3CJRtVa2ugS6hKIcW09RkwOdQXZHC5KkHLcRLk8uKTpKr6gXcRbtXb5Ki5f0R90UEFSDvT4orV5LuSA167nxmRam57D9tpxXtdNEyGMUh0xxsUawjpqUqNxWztuo47O5xXB+QxNa6vNDWlfu1LrEueDngvntWavmqg4rCcqdqNEbV+mGzhZbuoVE43shSkhTJFiqDV6IjrfuJ5CsY7v7tUo6/Scpqml0nRp3czJTeb0OdVI07XZLmR0TsVuOttI7xqXtKG9V7u4nYf2HvV8LMfQO4iXEkSQZB/UJcG3iFyEzDxZbWCSjjaddHYTxKtoxuGTTlPDNyEUQ8DpuLrhKVxrDpevInWTSg+l1haOz0I2CzhcsaFp5KitUejOHhV4W6PfkjmNuroEimVtRmnqJwnFxT82XKx1gdmSfnbzC1AN9D3LB8jKA8jsk83E2TC+CiwFbBjARz7yEe64445tC5fXv/713HHHHbzpTW8C4MyZMxw/fnx7+9/4jd+gqip+9Ed/lH379m1f/tE/+keP/+KkIpIhXoomGidN1EmatJvTWrtHp3OjltYHJjPb0w+ktaBpQkCqsdZ+dXbrj2axpoIn7qqQKjZwxZoKNR81Ha7noboYEXTFepO+1R9pT63zhrcbKZreYRc3wS/fNGi0HpW+bV9MV6JijXQG2hoRxCUq4NKZJorYNFD4RGvLQIWSc1o3B7pWYVsMqOCstPFk63ZTFyihxtWjJsK0AfVYI33FQFO2IdeIYLmJqzaaCFStjRf1VAVLnet5kAqiBN80iLhyoFHFqAVRrFFACfpcF2vKOp3Dhak27+Ap/AwSZ3iZQJ3jvcNFbZxrOrCrKb4ealrURXqc6dp2YwnTlcZ2pdLXOD0Pkwuash2fw+ermoYfPALjM7r/fBVW79/+nLjhEU3RS1C7lShFfATFOiFdoHR9jfR2r1OvwtYepHcdLpvXFHNnH8F3oKc+hlJNcVFH9zc8jcs3YLKMW7tf1zI6rs0ddaHR3qSrf2j0blB/y86BJhUe62zg0Sk1m/aJikip4fxHtPbQMIyvGIsAGgZw5513fsHZoVvcddddj7l99913X9oFPRoRgs+okgVIe1DlSKggncOnM1rPVY5UFMQdpBzqD6xvmg5CoRHBUDQpW1Tc1NNt8YYIzol2vwLi0iYi2MLhLwpMH6sFiYim6VqL2hEa0GaOqIVkCzw8+XMOb/53ksEFep1buSX8ADPsatK3WxHBANNVXdeWH1+xptGfpp6PcoDL19VCJNQQSk3xSiAvl/l08R42Vu8mq2E+upNb5v8+vul+3rZ28ZGmlbdSxlGq6cuohXNeI5ztJX0B6UyT1uw3QrXNhpzkocGfMKhPEKKDPLX1HextLwKJNnS4WOvpRAg+Joo7kM4DArE2N7hmXzivnoZpV0VmvqZip5oizhNLDtJCfNrU0XWaFPBY09btRQhTpBhp3WDSUxua7Uhkoq8j7iAtbcpwgCRzGhlMOrhsjtA0qbi4qwLcAVEL7zzS3q3vbaXpVtda1BRrNcZRUrtE1z25oDWc0/NNHeomPu4Qqglu8xFYeKpGOifnkJkb9Q+IqAPZjI6KYw6yWf08JH1tAqmmWuOXb4AbaTRQgop6vJ7PKAOZaSxhjmu94OgcYbJO1Nlzab+LhnENYQLQMK52inXSag0XepoGrJo0qW8EjYTt+jdo0rk+UgNoF2uyN26D62v9X9NBTGuXijcRJEy1WL8xW95qZnBJM6ou39DRXEm/8QycqAAgNKIyIZMhrhzw0Y3f4GPyLrp5xK7SsTo5zyeX/5JXzP4Su+RiMy+4poP40SbQbSTpaTqSiw0dLltQqxoHJH0KGfGOjX/CIJxjRoRMPA9M/gsPyt/y8uyNeCLcow2CHdoIAU1Dx0WBKMVQzZhF04mk3e3o3vLob7h3/PsIgrjAyuQMy8O/5cXDF7I3u10bYZKejsibnsO7BEm7jUitoNCJGZJvQHIB6utwda6ivdhEQomvp0i+AkDtYo2gTlc1fdp03oqownah1H05j3T2QjXBTZdxrXlcew+MTmlDB5reCVEMCD7JoKiQYoyks7rufAXXWdLO2skpfL6itivT1aY+tI/4BB8KgnPa3JHEVL6jM3sJWvOYr2vK2yeNIB0jIdcaznQGFyrEJc1IwKCvQQTqYVP3KZr+9W31hIz7TcNPrH/USHQxYlwXUBVQD6Ha1BfpG6Ptc39JmH/y1/11M4ydgqWADeMqR3xC5TuEpOnOdZHWWHWaej+pNIrSWtIu02JDa6eSro58K9ZxxaYKNRdpNGl6oZlM0TQxNOlOrbejafB4lEhy8WNHwvlU07mJGh4DVC5jM8n5RPUuAGoXyCNhmJbUFHx48z9qZ3Hc1UaDUDVdt77ppAWK9ca0uUlHFptq6VKN9fFyBPkahwfvYlydw4VAu/JklSMNcL68n+Oj92r6c7vTONcmCR7dvBKaqKNoRDDuajND0lJx5TwhSvlI9T8YpjXTqKZ2QuUDk1j4NH9DmfZVZPpIrWGyJegdgtZuJOkhUQeX6tg+6ewlpPMqZOKujnPLFnDpnD63aSCpGo89SZsIpE9UsG2JwKTT2NJk+HKg01viltYthgIpx1r353wzqWOijRKl1vSJlE06e6Bd3SHgZIqrpk3NY64CVUQ/O/kKUuWQLiAhx5Ur1FEfF6W4OsfHHY1uuqhp3CibtGxQS5psQVPAUun4wGKTECqNOIZCPwOAqwoVkRK0DjVqq/iL+lr36VKtL62nOhEkFE0KeL7xWcxh86jebxjGV4RFAA3jKkZEtHZrS7yBTmHI17VzE5Dpmv6oNzVuhK2O2KZ7t2nw0FoyR4hSxHcg7enkCKTxYmurp6CIio2otW0JQzXS7Rp/P1cO9MfYRyo26jGZDFmeHCGOPDWBbulIJ5BkjpzAWv5p6niVOGpq9QhNveBFoZnnFSnRRfPqRmhum1c3DR3Hx5+kSgI4mMZC5YQ8EsBxvP4kN7a+AUlmNP3ZjJaroxpqGo8+NRP2zutIsi0rkq2pyM4xqs5QV+ukW7aHaIY8Do52DeuTT7Kn+kZcmmjtY7mpUdIoU4/CkOsotck53OS8vqZqAi7CVxvI5CwynMPN3KhRsukyqQzwBbik1vc4m9Omk3JTU+PZnKa3qyHiY/yW6CrWm8kh/caeZarp7HQW8RHS3gv1CX2vOvtVUEYpnhpmbkPqnOATfGdJxWKu3bkSt3BxT216mlS6OK9R5HwdaS/qa61GakWUzeprLAbqKRllek7KgTbcOK+iuIy1AzzSFLd4NRcnK1TIUqvYD5WmhRvfSVysBtFB1C9xeBZc3URvVwmj04/3V9AwrllMABrGVY64SA2XGwEocQ9CUEsN0EhJa7dO7AD98YxaF9O55abWhW2Jt2JDoyjSUT/AfEOjRFFLi/AJzTZTtRCJ29oNG8rtiM3WdIjt1K2PqSUmRAlVk1f4m/escvjdm7zwZ/bSPZhSeu2ApbXUvDKnrynKcFGLkyeO87//8P+b17z6u/i27/kJ3aQaN/WJWw0dI6hzItHbcQ3tSnuZY4ESyIoaWFOBnHRUjOSrRHUCtBpBNW68CqUxih4CvrEgaeNChQ+BODgq39jwOId/dJmoU0/FrdeCSzSKFWVqF4PH+1gjesmMnken00ck6SHZvE7PiBKC1+jq1M0TsjlCnBJtTVdpL6oFTzrT5M+d2stEmUbpQqGWiYkKazW4rnGhxMsUKWu1fgmFpr+rMYxOq/jv7MFX64TBcf1MtReRfEU9Jan1/S2HGhGUGl+uESTWz5JUGp3M5hDnoHtA07vZLlyTypdsUesFfdI0rpxDpuuNf+E6jhWtLZ2c167eutTz6rNmXODMxWhf0dj3lAPIN9XqhwDxnKaFyxGy/Engxq/ti2YYOwxLARvG1UwoNFXXNGFINdGUrhMVEtV0+8fTSaVdrfmadqVupUBDhaPabrRQMRlv11VpZ25Hf8x9Myot7kHWNJ3QiNC4q1YcoOlCJ7BVI1hNiFzFnvSZBBeoJoGjfzogbAq/8w+PsH6m4nqeSlwMVHyCpqDLAa4ac+rEMb7jFf8L68tn+R/v/COmo83mBDTNKVtCy8UInn3Zc3B4ag+VE0on1OoNw+7u85B0RtcLkHSR1i7qeMsouqO2M9mCrj2dQ9r71C6lNa8p4ahNu/Vk6tYuxokwifU4lYcyEsaRY771VFzTSCKRGlNLpA0f4pspIbhG0DRRRqTxHBQ9h8W6imCnhsupDLUTuZ7q9BZQ0bbVdOFTxLdUtE7OI+WI4BK1MAylrqUuNFKXzhGibiPUY20gSft6Xjq7ob1b99Xepx29PbVrkdYS0jkAnf2EpK+p3e4+JNKZ0eJ1ogdVrjOaQ6GfudEpFZrDE8joNGw8jMvP44oN3PA4Qqx/QEhAWvPavNLZD91DMHMTdA6qZUzcVYFZ5frZHp+CjUdgfEIjjT6GbBH6N2g0MI7ZnhwyXXucv4CGce1iAtAwrmZCiavzx4zzElyTDlbzXImaurCoGT2W9LWzdCud20SMJNHGCuox4PSHHTR9XE+2LWUoh2q3UanliYRKZ8RWQ7VIAaSe4Kr84kQPVNP04/08s/v3iVueb/+nB0lmHWeO5Lz5ex9i7/g7tNYtbWoZozaks5xbL/n2/+U7eOTIUfrzu3nTz/0SWb/xL9yKfG51BUsNDm7uvZzZ+BBRcEQBXBMR3BffzvX+WSqGtgRUsYkrBvhmra4aqqDaGhU3XcaNTsDwJCHfgEotXHy+wjf4VzCTx/TKiKx2pHVEVjme6V5APF1Hik01p65GapszOYNMV3D1WGvpqinkm7h8Yzt6Sai1JrHO9XZd4kKBDwVbKWhHjavUN3DLDkeFY62zlJ3bntHsa/2jIMT9pmsbXDXQLm+nexSf6XmYXNAgYgjNNJmz2kRUj2FwnFBP9XMwPYcbn8KFoJ/B8Tnt+K2HOg6wqTkEdKJH3IZE6yBdZzd09iDZLn2sswdJZ4nSznbU2lWl1u3leu5dvoobn2jel5XGG7B531tL0N2vFkatRY1USw75SjONpVLR6IDBUXy59ceDYRhfCksBG8bVTDP/tYxmyXyqzR0SkLiHjxKk2NQf71iNiqlG6pHmGuNkF9RGJWhxP3FLIzdSXrSEcSqyXNNVLF4jWcQdnI81qpT2kSjFJX19TpQhaR/XmEJvRegk7vG8/g+zN7qNM3v+Gwv/5wHu/+G/5tgjK/z0T/wzfvVf/xxL3QN62HLAhdMP8ZP/3/+Lo0eP8rRbb+TX/80vsjjf1uil7+JK9d5z9QToqy1JXZDIDK/c9WY+O3g7G/k94CJunXkpN3e+HbdxXEXr1uuJdO6seK81gFFLo4CNIJZkRsVK1KQdfaz3xV3m/R6+sfckHp68l0F5nP2dgzyt+/9kMS4Q1IpHz8880i4gbuE7u6EaIeJwSQfX3Y+UA0LSwUUdfJN6lWoC7d34tKfizTkK11Pz5yS92IGdzau4cjHOx7rWJh0vdaEWNHH7/8/en0fbupbVvejvfb9ylLNca65y1xVbdIMoguYctV2UiJLgSTxEciww2k5s0o6R5JgYUXJTYHI9GnKNCSckSjiJ92iMGq/QNAlektiCRLEgwIbNLla95lyzHOVXvu9z/3jeORc7IIVhU2y+3tpqe84xxxzjG98YY48++/P03rFS4cKo3NsUm+iYWNpdbLWHpBtK6F2tGYgm0dxHY9REhAmjdqv7oFGuBNI3StyrCZQzLA3Eq7fbaXyFSIv4FmsLqCvdQXUFlAf6yigPcL4Nyucc6Z3Sx2IiJac+tK+ka0osoxTjlsH93OqI1xodA0u4HZtCYkGsRsZ4gWaCjZpn8A3ZocOzBx0B7NDhcxn1RPfXfBibuhBA7PKQW6jVadrxa8IYMg97daGjNh2BfERXrk11xJuOVB1yjaon8bE6s9DxZNRTctMuNbAXwj5WrDmD1RGmXerttiUxWkdmjOGO7EVcHK7DCL703wx52Te9gqeuXOeHX/d6/sZPvpXzd21yY2efv/Ejf4v3fvAKd911F//qX/8qG8MCCVmDQCBpctvQYTMk7mOyNVI74LnD/xnfPk+7iAf3Al4H3SY6cRYbX2vUSIAGMrcnCpZxRRhpBwNIW6pL1juIUkZmjeenfwqTOMzoQUQEX/6mGg+aKRJtaKNJcRMCeTZuruenOa0BxfOr2HQFM7ygRHR5U5WvKEGysRpI8PRkH1M0GMnVHDE4o+PVcgcWA1h/WJXL4kCfX2uh1b0+SbR9A1cpWUsG4ZzF+Gighg9fIvGK9js32sMsvTOqGLtKYyCzVfwyAwwmX0cqJXEmzsHUeEItH0bzC9NVzWhs5mDDPqBrg9Is4EUNSu1Sf8+FXUQJ2YxRrsQ0VMthU40mMjFIrbflK3CiJNDZoF6LGkVsoesIRqCtiZujT+tbsEOHZyu6EXCHZxXe+ta3srGxQVVVT7v8Fa94Bd/2bd/2WTqqPz4k6iHpKk0U1CqbaVxJvhHUGgmKoBo6aBYh8FlQU8NCx2SNKifiGx1VNlON/gDdxWur2yPT0MlLcOJi0xP37UnbRrqKZOu3x8pRTmM0GFpvw6q6Ew04f/Fu3v62t3HXxfPc3N7hz37Ln+Pd7343f+E7XsX+3i533nmBt7/97Zw/sxZ2F5cgLjhN99QscBwDU0+1uSJk3XHS6qG/g/farOEbJXUQdiAdJriij0nzyeMTr6PstlJlzSbafmFCA4qvEJOHppUQgxNlqlwl/ZNx7LFqaCKr8SfZCpIMMMkQ+qf1fMV9jE2Q3mmkdwbfPwPxEElXkGSFpdlA+hfxvTMaGG0T/XpwQSNmQO+rv4nPT0F+WtXBeKARNslQn6dgOBGjf+MbV+heILESs3JfiaQ4ff7LXUxxC+qpfl/sYZY3A9EP7SHtEtPsk/gp1kYa19MssCZSZTjO8dm6hlHnm0jvjEbEDM8haVAxU+0NxurOI81UMyebCdQHIbJmFoxLaPxLvqa7fv2zYbVhqHuk1b6+Pnytu6kmgaYg9fufnjdfhw7PcnQEsMOzCt/yLd+Cc45f/dVfPbns1q1bvO1tb+O7vuu7PotH9sdEPcG0c6KTfbZDTMh1A9QM4Mrbhg/dADtJM8FmGqUSRpvGJrobmK7f3quLB2qaOCZzwEk0DITstTp8IBtVe6p93Rt01clxpTJ7+nE1M923k5bzF87xD//BT3Dx/Bl2bl7j677u67h67Rqntk7z5n/yZi5cuKBE08RqTDBWQ6+Tkbqek6cbOgjxNBLrHiHZuhodjjP5jokQYeRrMrzRvEJtIkFJEuhYPBtD/5SOTQORxKZqnMg3sFbURCMOiTKMzTHpQONbRIKL2ECcIvHodtNKW2jciSsxUun33gUCPsc2Mx3PBydyLlNo9rHNEaaZaVB0dYApd2F2WZ9hX2GqCXZxXXf4XMhvrOeqJDZz/XfsUva1PodxDgbEaOSKxEPEpJikjwwuIPkGko6VZI3uRIYXkcE5JN/UHbzBWVx2CmfCvl+U4432RuN1rGyrA2w9g0IVTopbmMV1JZPzq7p+0C50BSFVs4fJN4MB5CKM7lGil66ryudrVTOXN2D+FMwvK1k0qV5ndA9kG9A2oTdYu5Q7dOjwidGNgDs8q9Dr9XjVq17Fz/7sz/It3/ItAPyLf/EvuOOOO/iar/maz/jxiAiz2ezk+93dXf7kn/yTPP744+R5zmAw+LgF9rY+ICqPWFaW+vAQakNctbTlHDm6gmlnxGWJWy7x0yuYdkG8vIVPN3DTq/p9cQOJctpphvENSfEUIDQTEJuTLB4naufURw6frBGVOyTlDdq8ps0rjFuSFLcQk9DMcsAQLw8xvqJd7CDRBCln1PS5uTtHJlfA18RFhcQRbnkTRIhNyiv/l7/A//3vfhAA74Vv+7Zvx5mUK1fCsRfbiB3QTjMQR7K8hKGlmakzNy6uE9W7tHmFy05jmyOS5SV8NKQZaEdvsnwCRGiOBIn6JPMniNoJ82aNwve5eWX2EY+vICp3yCeX8VFOUWxicCSBWIHmBh67edtpjnEF+dETiIkoqy0kGhAv94jK6xha2l4BxmDaGe2sT1zdIlnewKWr1MUGEk1JZrsk5R5tkVPPh8TlPkY8zsPR0YxlHOESaOfXiOojsnlNW5fUV64QlTtE1ULDqpc11k3AQNvLiBcNUdPS+lu0k4hktk9cF9TtEiZPERdX8bYHIlg3R+IjmsOGbPI4UTOhLNcAQzb9r4iNaPMjrNfOZNsuqOsFUo/ZvnaZbHqTdu6ohynZ7AjE0PSGWBe6ol2Kb1q87ZOWOc0RGFriwtE2h8TtEaadI9EhxhVYV+CjHtYVqh6bGOMdPu6Dz/DRCOsrTFthpcC2UyXOPnRkS4JtHdFym4P9fZxzH/V+EhGaRv+YunxZCfWlS5cAePLJJwF44oknAPjwhz8MwGOPPQbA/v4+58+f/1T/F9Chw+csOgLY4VmH7/me7+HLv/zLuX79OufPn+ctb3kL3/md3/lxidYzhdlsxsrKykdd/uu//usA/Nt/+28ZDAZ/5O8nzSFJs6BxA9qyZNlMSNwBdRnTJJDWO2TNTarEUaeGpD0kq/dpS0dZZVi3JK8XeNNS1hNAyGslNmW7BFOTNJbIWSppETshci1JY6gd+GqC8RV5tcRFA+p2DuLIywkGR9nOEFsRlztENMymB7gE4nZCVt/E2wFFlmGkodx5lJ97y//JqBdxtGhZG8T8wr98C//zd59h5eyDRG5OXs9wpqFsRnqslbaVVM0Mb2uSuiRxDZWrceUE4yryxms8i5uCeLIKMIbKV2Aa4gZiF7NoDI6GydKQtNHJ47NNw6gW2ihmMZtjENKqAgwGwZtQtWegapcY3zCoY4xY5rMCMS1pvSBuBB8NqMUS+xmRX1K1C4yL6TUprvVUMsObmqxsSduYyqTUfkFeLUA8leQsKqjqFh8vqZopcVswLGqqtqZgQlyXZGEE7mKHaAYMTX1ArzwkdkcspaSp5+RFSV5PqNptyvQcWas1fomfIsbQJAPqpmBQOSInzOdaCdivY8RYammJXIMnwUqGbyq890wWNcMmovaO2u3hywIRT90ckbp9PXdS4aICiDD1LnUlONujX+1QNPqaiH1DG2UYMowTnM+x3mB9C9YQ+RqpGiIpdIvT1zgMFg8SYdoMgyFyM1K0U1q8oyhLmEw+6v0kInivcUiLhe7VlqWq58fE8Jg4Hv//IorUTGRtNzDr8OxCRwA7POvw/Oc/n0ceeYS3vvWtfP3Xfz3vf//7edvb3vZxf+c//sf/yI//+I/znve8h5s3b/LLv/zLvOIVr/i4v/POd76T1772tbz//e/n4sWLvO51r+M7v/M7n3ad0WjE5CM+iKbTKRcvXuTRRx9lNBoxGo0+LjH100uw7FFfLxiePsv59TuQxXXs+C5MvoEvLyDzq5jhRWy+hm/mMNtUd2lvE2mX+MMc8lWi0Z3a+HCojQp27X7AIocfBDfCrNyLyVbx06dgXsP4DuzwPFLuI4c1ZGPM2sPqPj2yum+3+gAm6VMf9Hnf797gwYe+iKi/ia8XyGQI+TrR6A6uXb3KD/zgP2Ln1g4bWxf4V//nm/nhv/wX+cCT2/zg6/4Wv/BLb+Pc1r3IZIDpbWIH5xDf4o8y8B67/oDuw00vI+UYu3IPJltDij1kpk5Zu3Iv0iyQIwcmwqw9pI7egw9A0yOd5ixdxoPn8/D4LmCHF/GLG7ib1yHfIj7/iHb0HoUsvainjtR6po7YtfuRtsLfvAFRQnT2fh1LH0T4BWpeGd+BqY90/3J0D7LcQSa7mGwNu3k/JGP8rQKZTjDjIWbjfphoTmDxvvdxYWOVXm8F09/ErD4HmT6Ov/kEDIbEd34x/uhxZNYCRvfjvNPX0Pgu5KBFFmDWt7BrD+J3K/ysxqw9hM03YNLiE61yk/IAG/cwaw/i9hood7FbD2KMxe3XiDii9edoY4kHpGG2f53iMOL+Bx5Abh1Afppo68vxN1vd3Vu9F5qz4EoNr843dJVgEmMG51R9nDjM+C51StczbTdxNdLMMekQaSod/ca5jn+jXEOiTaItIyLBCdxA02oncCNQLKGtSCPh/Nktzl+886PeT845yrLk3e9+Nw8//DC3bt3ioYceYnt7mwcffJCbN2/ywAMPcOPGDe677z6uXbvGvffey9WrV1lbW/u4/z/o0OHzDd2fNB2elfju7/5u3vKWt/CzP/uzvOQlL+HixYsf9/qLxYJHHnmEn/7pn/6kbv+pp57iG7/xG/nar/1a/uAP/oC/9Jf+Et/93d/Nb/zGbzztesYYxuPx0/6BEsPxePyJVclkiMR9nA37bHLbyABoALQrTrpyTT3VRfrjjLtWnZ4mtDkQenYNIUrD2GB4SD7C4DEKS/uhfu04ODldV6OJjRCbI3EOcXZyqALqEAZwBZPmEjvV7/Hhy+/jz37zN1HOdnngrnP82r/5Jb7iK76Cf/HP/gFf8uAFJvs3ednLXsb21cf1+Ktw7L7RPTrRrDy9EzV04PU8tFKz13yY3eYxnDRK+IyaODCR7hHGAyTuqzsaNIA4XdG8xOPjFgm324a9wlWI+1i3gHbJMqrYNlc5lG20lsxoKHXcx5hIz1nUR0yiz0zYXZRkiIkzJB6FfUaN65F0Tf9lmmunOY0jCrOB5Gd17y5Z1ZaQfEtNICv3hOdnBfpnkME56J1TkpWtIvEIn64EV6/GrJCNgiFEj1WyFd0NrKeaERn1EECaKdLMb2f7tQtMdYhUBxjf6o5pPce2SxIpdQ/Rtbp7WE0Ar+fchno5m2CyNX1NxT01zcR9TNpX57PJ1KUt2gctvtXYmLYKeYMFNMGtHUWhqjAERKcDzUR0DbhZOGavrmIM1rQhdLtDhw4fD50C2OFZiVe96lX8lb/yV3jzm9/MW9/61k94/W/4hm/gG77hGz7p23/Tm97E3XffzU/8xE8A8JznPIff+q3f4u///b/PS1/60j/2cX8U6gmmPiQKhEfrvOrbH9RG3ao29OtKMkSSFa0NA3WH5muQrKhb1aZqAog0U+7YRfz0+5w/zeBhmjlSHTcsnNNF/hMXbqV1a64kQj/MD9tL/PrO36U+LLl2YHjTa36d5faS+77qfv72j/2/2ArKzOkLD/BXX/e3ede3/2Xe/6Gn+J9e+W38ylvfyOnVkC0YZUg8xFh7YtiQKAebQ9zn/fNf4z/c/EXyScx+khDPfpk/vfFK7mITrcZQw4o+DgmkwAaDRq3nEtQxbVPNPYwSqA6R+gixOT4b85+mP8f1/UuU0mdn/+3c1x/yp+QrSO1IGzskg/JAjQ3JWEnf7JI6k9sl3iRKZttSL4vB1AeqeNEEcnWEiJDJBJpUH7MRxJ/FLm/gF9cgSmH1PnW/zq/qHw/5XHm8sZh4iF3eQIoDJYi9dSj2MfU0hH2vKtkS3Wc0x8/9ceCyqyDuqxEnXcH0T2lDyvImkvXAV7RLobaVdgynQ8g2MdkoRBIJVlq8d6oGtoXGyLgFptjRc5yO1JWeHGCiGBELtg+Rhzj8UeEd4koghbJVA1J1pEzdzYMZKVFlMB6rq3l+XZ9faRFvb/8x06FDhz8SnQLY4VmJlZUV/syf+TMMh8NPOMr94+Bd73oXL3nJS5522Utf+lLe9a53fXrvKMSteHs7F0/iARJpi4c2gtxWEU8Us0b3m0y70Hqs+iD03oY2h2YWnL2iCk/48AQ0BoX4RM2TqK/3edLgkasLN1u57aRNRjQmw0Uxb73+d/nd3YtcubHFv3ndf2JyfcHKhVW+80f/NKdOnb792OoppzZW+Ne/8C+56667mB/c5O/+zR/i1rXH9eftEtMcqcLkSnXb1oeYZsa1+bv4l1ffwZW951AUZ1gsLvK+vUf4ucu/xqS+riHX8pHFvbchNjqpXwNUfZIa8a0GD0e5PkYDv7PzL/mD7ZpL8we5Xp7nyenzeN/2Or+//28Rp53L2Fhd1CJQ7mOahX6frWowdH0UlEWNaTmpc7MRuBZvU1UH09UQTxOczNm6RsakYyRbU3cuKPnqncJnW0h2WtXGZADZGr53FumfVpXQWHwSfndwRoOXicLj62lWJF5jcup5aCbRTl1T3IT5TWx5S6sH51dh+hRxdZPUz9XdW+5jyh2tJ8RjvNP4IBtr5E1+Sh/T8G4Y3QmjO6Af1M3hOVVejQWpNax8fg0zuwqzJzHza1Bua/5flEGyBuM7YHwfDO5UFdCXsLgKi2uAZjZCogrkRzTUdOjQ4WOjI4AdnrW4fv06f/7P/3myLPvEV/4Usb29zdbW1tMu29raYjqdUhTFp++O3AJTz4iO+3ObmeayHY94famVYy7cp4mURIQWDOI+kgxUFTRGR5DpqjZYxDnGRvrz41w7CCQEjoml8aVmvh2PmZ3Wm1FPdWwHUB2SScFT83fyxNF5TOm5/Na3kS6WjM6N+R//7l/gSXuI9/WJ4njs9Dx77iJvf/vbWT91jqeu3OC7/tf/Tc9h1FMilI6VrBijTRHZOv9p+m525/dhsymSTzD9A0bpLteKe/iD2fuQZKQKpwn3Y2MNwD6Bua0S+QZELR96zkvwjsYveO/siKIespHdYi3dZ7N3hcZbrpcZh+5miIypMc1cyVq2dntnsC0w4sPxp6q4uRDJIi0m6mnEjCs1T88XtCYonIiGNItAEzIObaTf1xNMW2B9ERywtRL4Zvb0iCDxGgtTHUF1RMgN19iZchfxtRJHY8FaxCY6/k4G2rWbr4fzv4r0zyO9s7hsncb0Twge/S1V5ELUkBirf3Q0E0xzpD3A08dheQNT7CDza5o5WO5rIDStdi9nqxr/MroDBnfreDvfhKivKnMzgdkVmD4JxU2o5/rHR/8M9M4omW+WYFtam5z0XHfo0OGPRkcAOzzrcHh4yC//8i/zzne+k+/7vu/7bB/OfxdMPECiFB/IGdlq2A8LGX7JSiAYQRG0qe6YHatfvgnkbYGIC+NGDd+VttDKtJMRYSB4vtT2jOOMP2ODWhNIZZQicR5UrECisjUq+lxtliybdZLhktUX30M1yHn5T7+ClXPCQTNgJpw0dJzk1NmICxcu8H//3Fs5e+4c3/1d30Gv1zvZBTMudBKLg+oAmim7izkCrLJkxbf0vSOJKvpSM1vOMM1E8wpdozuQbXF75NsW2kxx/PhsfDKeNMaGfUDhsJ2x367RpgUQSCvQT48o2j632kIfg7FKMH0d3ML2hHCKSFAw29uqqo1V0WznGnhsE8RGeCyZn2LaiZLS49DpdqGkrg2xNESqVLoq7H6G59qYcOyEcajTxxNlgUgtMM1SyVq2hkUwYRcQBGNirHioDrTjOLigTTODah/bzlQtxoc/Qg4Q1+rxN3MloggkY4zNdD0hC/uK8QhJVlW9zNZDzWB4TflWw6CrQyWry+v6eKsjfYxRqmsG2br2Ah/3XjdF6A4+1HMQpyBW20w6dOjwCdHtAHZ41uH5z38+h4eH/L2/9/d48MEHn5H7OHPmDDs7O0+7bGdnh/F4rOTl04XQ0Wq9Km0nBC7uQb6m5Kg60A/J3iY4VQSPTSFK3iyIUYUrypCkr0TBpqoA5mtIFUHUV/KQrugH+vF416qhQo5jMCTEopzs1cVQT0ioWOEMcEhfHHe++AJnXnQH28MRtvYMxRC3utMlUaaPxQcilgw5e/YMf/8nf4JsJRh2TKxNFiZRIoPVnUYR0vgsYChsxDyKWQTFszQJPj4dgqEjDX1OR6FazAK1jkzFQTLUx+tqdey2eo5VmbT0olVOuYolgrGGyhjEGPquYYSjZ0aBwDSh2syH2yr0vJyMmT23jSOR7m+aSIOO435QIAXinNqOkGh4EuANwYSTb0JvK9yW3G4YydaQ5S2Ih9ioh6TayGGz1fCcRVqTl6+q6SNbC8fb6H33TmGlpW1LwGhodqTmC9sW4Gs9jmDW0FaV0C4SCCLNDIMg0UDbZZqpBjXbBONqfKO3TdyDahek0caUYjeoh/ocYxodUR/nLuqjD8frwYTXig3h08GQRCtqGPEtmAgf5SecuEOHDn80OgLY4VmH42DXZxIvfvGLefvb3/60y/7dv/t3vPjFL/703pF3qrgc15hFme6SRcEUkYRdsdDiIYk2ephjhdBm+iFpCDtxouTNu1Bx1oN6dtJMQZyFUeI+pGN1/zp1fdIsTtSik3/HSmOc44h4ePwVrO4+xm6xxbpdUiYpIob95hRfsbLKYLBxMs6VdITgVQ0CxKakeX57r/BE2ToeSfug4gkvXH0h75n+F5I2JvUFmXiOXE7fN3xJ74ETlyvtUpUkLEZ6Ssyqfd15a5caNeIbNUUkx13IS2jmjLJ1+qO7uDqbcZe5Qk9UYTtwp7kvnXBhcK+SPt9gfINJejo2TYbB9KDHLzbHxLnmyEnYufNt8DIMgkrbgCuIjx22YvScg7Zo1EdYNwe/oaposa/K4rGxxFqkSjDTJ5Qwrz2gpG2xg2mmmufoSjWrxJkSXu/VZZ5o5qKJVLE0zQyTjpHeFhgdo5NuICbGJ4baqo9c0hXM4KL+YWBiTJTq7dUT7Sb2FZKOVdFstd7N1HMlyeUu+BCY7Z3eRjTU3T5x+hpwy7AnWYHUUPvb/cJOR+L6O5GO1UuNxmnsKkmX2dehwydERwA7dADm8zmPP/74yfdPPfUUf/AHf8D6+jp33HEHP/RDP8T169dPHMV/8S/+Rf7hP/yH/OAP/iDf9V3fxW/+5m/yC7/wC58wb/BThaSjENWho0lVR2wY6frQeVtAtY/0T4X4jKm6Iftbuu/l6qBQtZz03wYYY/DJQD9AbXZbAcw3TkikBJJgklFwEic6/vW1RqBAUBghN5ZX3/lKfunxX6ZanqJtYg7iTR7pb/G1K+c0H89VGhlShR2xZqEf+M1SR5TNDDh1Qqx0tOlvH7sIzxs/zNeddvzB9ZrM5ez5EWW8wjdufQl39GMkGWJNULTiwW01zAQFkAjioADaBBP3QuMHugeXrYGJeNn681i07+Xm4ixHccK+H/OltuRFo3PEaa7GCknwUQJVpY8vWw09wUOstJjqAN8ukXiAjVK8b/E+dC+3S+0BthmkK1jUiCK2h8mO3dCDj9jjjLU+bbCFYDHpqo5De5u6Mzm8ExNlSLICCNI7Bfk6dnBWMxN9q9eLcr3/eKivDwGJBlgbI20F9REmHqja1haYeo5UB0R1TeyHML+CWd5UN7N4fc7inlYVRgn+2GmcDFV5FQ/DO8G1qigPL+r4NukhCNSz8EdJAcUt3UP8iD8uiHWPEuOhqXXs20y109i1ISZI1UNjOvLXocMng44AdugA/O7v/i5f+7Vfe/L9a1/7WgC+4zu+g7e85S3cvHmTK1eunPz87rvv5m1vexs/8AM/wD/4B/+ACxcu8E//6T/99EbAQBjnLoj9QoNvj8evvkH35zLNVDMJBquhxNka2ARrEx2hZqsah2JijI3wUR/89GRXyhijZNIVwFDvs55BfAT5hipMte6lyeCMHkMbjscVEGmemzHalftFKxc4f9+f59LOb3NgMlbXv4wHhn168w+rSSDSD2nJ1lTjS45HzxoczXGETZTr+DPKlfggukdnLFGS8i0XvpIXp2e4efheFv0L3LP+CBejKWZ+WU0REPYIy0CcMyXBzQTjmqCwpZqbWE1uR9tURzpWT4aspil//uxXcHN6nWsmJV75Ir7EHzCY/qGqaADNHFNN8SL4ZIQVh6kngEMGZ0L+oIVmqee5nWO812y7bFMVyeoASfo0VsmqdQuMK/BtD2lmSrBtokSr2NPMvnxTj6Hc1ee9PFJSlm9gpEHqGWZ2WQlidYSpD5XoN3N9PpMVbJwhdegPzlcx1uKNQaKB7plGKSbbwNsEogQvDfXcQm+kTurBBaS4peS0f0abU6ojbaQ2QH2ILK7ra2hxA2ZPqlM4SnVcjP6BQbamz03vNCYZaC91eUtF4Hahaw/Ho2vxOjKOxzAYKhmcPKUqYZxTZmcZflrfhR06PDvREcAOHYCv+ZqvuW2c+Bh4y1ve8jF/5/d///efwaNClZDeKbw9CGG+A81fkzDKjRJVxj4iG9C4WpWlZq4j4GaOaQtotnQk5zSfDlfocr1Hd7mOR65RhsRZiNUAYs0WJMqwxypZvgZtoUoSQDrGS3Syt7bSS/ji1TOQrRGtrCCuQmj1LnyrI79mdmLQIO6rs7Pc12iV3uZt4hnXut8FwRBSgquI0oyLPbjIGcz4AqafIKXSxJNsQ2OR4907DGCVuFh0ZAn4bB16G5jhuZNzLskI8k3EFeTxkHsSy72D89jeJs1hiZRrmIH2wkqU606ejbAmRuIhpCuYfF0fm28h7mH6pzHG4qMcQTA2wrilKrz5BpiYzB+B9PHpaWwy1l1FVxKepJP7krbSHb0oQ5IxNh0jfk9VziiYc2yi6wBhZUBQQ4ikKwgWawHxiIl0fJ2MkLbE1BPEN/p81xOkXWKINH+wTUlcA9MdHdu3S0yxq2Pf+ggfDRCbqjM9SjGDC5hmqa+fwTlY3oR4qEaOZIbEPayr8PVUn6PyMY1+SabqNE/Genl+Whmlq3THsl2oG9jXqgBGmV7P5niTPzPvxQ4dnmXotPIOHT7X0SyI3VRdmNJimoUqTG2hapzxGN/qCM0E96kJy/THmWzxUI0XxkDvlLoyT5o/xoixeH8sCSpZMm0Z2kMadXi2c6Qt1V1bT3Sf7DhypJmTUITxLToeFm2KuE2szclUzxyPZ01820l8TLxOQqz7ShzSFVUNoyQQhxUd0x7/TqxxMYCGGBtOWkzChSHT0KKNEW2Qp4w6o4ttzUosQ7ROPVHndLGjitrixolhRcRjFpcx5a2wW4iqh9WRjjTbORS7+vy4UvfZQhwKQfGi3Fe1VdAdu3JXY2RMRCspxjtsiHYxx4aRZKQkuTrCtEsdz/dPA177bzGI92BzJF1V8lcdqkqbrYQxuub0mWauJCseqgq73EGchlirwcIGc0wV/uBY1dcRFon6tLanOZTxILzerKq3yVj3B/E6YvcNLHeQah9jE8z8CqY61NdrO1dl07cnKi/JAPpb+n08Dk0tXt2+zRSWO/r68qU+l9m6Xu/49eg8ZGu46I/u1u7QocNtdApghw6f07BIOsah41wTZbrbV08QG2OjTAledahmERtB0gu9qEtMloVds7mSkDjXy6s9qMYafeLL2x+ybIUxM8HhK2CSsB8XVCsb4dO1E+eqKoCr1GZ0YuA48kMuTXvUts89PcNmFiM2DkpecHge88IQQG18paShWUDvlJIuNwcaVaRCBh6+UmUtTdg5OmL3aEJTzHnozJC+KzQPrl5AH3A1RmpwEZBjxGPEcNvBHGnUTjLEpKH6DnVek68jboQn4trRhOtFwmBkeW7vjJov8k09/jjTPL10DP0tTJQjYYdOQ7M3kKiPSZWkeqM7lCZbVQIbZRD19PkzaMROlKlCeZy1aIZgNSTaew/NoSqC6FgfXyuRrQ8xbivs5c2VWDZTNfq0SyWc4pWoJf0Q96Pk1hgL5QFSz5FsBRv39XUS95UYJn0gJ5GJOrnHdxPFKW09VUd5lCqJa6YaRp6dwpsY2kq5ro3AGMQdx+VEuqvaOqAF01cSbXv6mrBWR72uDo7f+rZrXJwaQXwLSQ7L8LLK13Fm9Rl5J3bo8GxDRwA7dPgchjEGG/exOGwbFCpXQ7GnCsmwHwjdITSnNNrEt/oBGsamRJkSOBMFsraGZBMdDYIqPPn6bWdxHEgJJtSkRSfZdbhaF+19Da4KBg6tgktFs9vecXSKX3msYLNcUCDcuHKOb7nL8bKhqoL4OgQjO8Cf9PqehFgfL/Efh1PbXM0mxqhC6BK87fHWD8F7rq6S1y1X7Ii1y4bvu7fHF+drkB+3lmRI1MOkK2BaxNigOiqZBsEfE4yoF9RKrwaLdsmiavnXlyyXZ4YP+BxnW/6n/CbfsLlg9XiJsp6rUUJaiBJt2cCoQaTcg+lTSg5NpIpjdYA0M0w7QOoppl3qcfmGROZ6Tm2i/xrNQCTuA1YVRhsj+aYSKnFKLrMNJB4j2QZmeAcGj4t6Gq688gDGprpXlwzx9QwzyCBfx2M1rDo/pYpis0Rcgz0mayYNY979oJoOiN0cUy2gDn941FM9x8tbamDBgGuxVqv4SFcww4vIclsbSlbuhaPHNZA8yZX0eac7fO0M/VgyoQWkBzgNx05jvV5bBFfxTM99HYKyox7kZ6B6ht6MHTo8y9CNgDt0+HxBmJ+adKSL88ej096W7quZ8PdcfgqJMrxv9PtkCBhVkyDUdjVqJpAQrdLMoNwL6kyNcZWOCl2JRse0gVgex9EkOhI8/l9I1Kcl41Ix4M0fNGzXQ3r5KuP+iMIn/PMncz64XNGx7snId6gj21A5p5EjQZ0DJbAioaZOR7fGLTG+4j9cq/jly4Z1jniwP+X+wZKbBfx/PjhjNt1XEwvcHpfXExDB+grTzjTyxjcaFF0f6WNtZsHgEoKi25LfvNbwxGHJOHbcP6zZzA035p7/fAucC8cprWYO2kzHoohWrCEhpmcFGy4HECLtau5tqWIqTol5PKAxQ90nDDmL4huwESZb1fF9u9S6P1dqB7TUquBWB7C4pqHe0kCzxM4vY5Y3dFRdbOsfCcsb2NmTmPl1jfepp7C8hXELxDVQ3tLHEvf0nBmQ/Cw+7umeZ3oKT4yM7kBWH0bEIukGjO7E97ZCA40EF6+F4gammSL1BLO4ooaV6SUNfq4PlOwScgCzNW32GN6lY+v+WX09eK/O4OV1/VcdAFb3AvN1vT9fQZLCqS/9736bdejwhYJOAezQ4XMckq3hTIbxpdZnRXkY1+0i+RpGnC7hi9Pvfa2uThsh/bPBEauVZRKiZMTGQRE0qnylK4DRPDebQG9DTR4mwZoIyTYQt60TYdBmCRNUGgCjP/jArSnT+ixfNKrpuyVCyZ29gg9NE95/a8pzsoU6iKM0jCi1Mo1sVceYgZQdw4T8P4VFjI6i/387MdZAmg6oZIEzOXcO4OpkwPuXK7xoa6TnLtZwZJOtg6nwJoU00ZFrlCHikN5pTNzH52eJjNH9NhMzY8hvTxqIPSaqWJoRvUjIk4wPL1e5t97kIfGIMQgxEif4KMO0hSqP8RBml7QFJM2QeKQkul3cHoP6FhGQZIQt90n8FGRLR+AmwpcHOhKPYvBeI3iiTHMEQ7SM6Z0OCmYM8Spk69prnGocjU1XtXmkF0HUw5tUCX26ijfaY2x6m5gkx7s6ZDOOMUa0F3h5Q8e6dh3THjFor2CKLUw7hfkNHT3j1L1rrBI+myL9TSh2kd5pJbv10YmpQ8RB1EfaJbiFEsDJJd0NTIa6jhAdj56HSgjF3G4IqY4CqQ9/HNgY0jVsvoLOgzt06PCJ0BHADh0+x2HEYWmxvgwtElbHc8f9tXFfx3tRqlEw2Qr0ToXoE69EIFFCZIIjFZvqLpVTJ6kRp3ttzRSTraqDuDrC5BsQnwo1YiEuJBuHUe5H1KlhETFMGx1btyaloodBaEmJooibbg2JDdjeySiatkBi/V6ivn6d3K61k2NSaszxyQAjHFSQR5CYCiMQmxZrYGDmNE11clymXeiYMMqBhMiXUC0gaRDvdBQ7uwy+wjaHYFYw9RHia6riiHXv6EUQk5JREkvDRXuTI4SinIMfY+qZGj1aqzuRrgoj+BppixCsPAy7iE0wgAQlNfxcHbsDjXtxhRowQg6ixD1sMtQ9znJfz0m2riP4ag+Tr+ObSu8rP61RLMubsNzG5Gt67qp9wGjDS7GN6Z/VEOr996oqN7ojOMUXGuHSzpG4j+lt6ojWxNDbQooMRx/pn9FVgvgAeqdVrTuuG4x7mCiH2TVdVRiex0w+BNNLmOEFDB5fHKhxJB4DkY6G0zFynAkZ9dTA0iyhDYYagjocpcEAkul91Ee6T7h6HyZfA24+w+/IDh2eHegIYIcOn+MwUUYdbSDGIa7F5qv4dFUjU5oZpKsYG590/JIM1XHqDiFbw8T9QPZKjX9JBrrbJ8E5HIWKOFcq2QIk21AlLkqVrOWbunsVolPkxIkbqaoY5wiG831HtN/SeB0Nx1KT+ILKD7m3X4TYl5nufrnFSd4e2aoSn3p2olziq5PmD635sidj6AfHLb+xAxLDsUJYOmglZT2zJ33DclypFveBRg0YUQrJGGsjHUmn64DTGJQo1ZgVGbGSJZRxy0HTsh7HFGaAkZbLbosyzjm7uqoSZdxHemd1p7J3WvPrbAxxyLPrnUaGd4YdQx+ub7D9M/rYslXI16A4QEyC9M6oiieiO39JX4/NWCXy1VQz/eIBkm1qa8fRh1UpHOQ6nrfaF2y90zGysRoJ5KrQ8asuaIzGxtg4V1duqOUjHWHLXR1au2DSsRFRcZlEpph8E1sf4hbbWjXXLsJ1l0izxA4v4mtVoU2+rqaRbE1v21WQjzEmQdqpkuH6UI/f9vV1bC0QabxLMgh7f6W+Zso9aMPr4njtwSaw/kXYKHnm3ogdOjzL0O0AdujweQBjBNtMoND+YeMbVWyOFTgbhSQ/reWSbBzIT6jo6p0OO3dWyWLvVGgXaXWcnIxvu2wBa626cou9k/ujnkKxo3VhwYlr6sMTw4k1wiOrFfeMWp6cw6QxzBrhqTmc78OXnekpMQnkjCTsMsaq+MlxiHWyEmJieiG+pq8f8CbWka5JeMnFlNUMLi1i5q1lu0y4uoCHVhz3r3DSBmF8BeZ4Jw+sVBgJDSOgWYRuFuJWrO4MNjNMOyVpJ3zd6QkDmTCtCua1xxQ3WWtv8MLxAWd6oQGj3NfdtGJHK+CKPVVK2zlm9qTu5jVHqsSV+8j8svbgNjPNxSsP9bmsj0jlSEfjhGiTeoZxgcAtb+rOXtrHmyi4bZ2eG9coaeufUiW3OoR0FRndc1s9S8f6XIXQZvENUu4r2eyf1ehE8Rx/LMjxaLm4hdgMk61BWxOK4HRf0kb6uFwwYogB3+KbJaY6wKR9JbLzqyGaJ9J1BRJ9Xo9NRsmqHmMUTEBNyPoL9XW4KpDVgV43yrQKr9jV6w8uYAbnnqF3X4cOz050CmCHDp8HcHaAS7VBQcTB4BzSFkhbYvFhxyqQkXSMjYeI7MJiW0djoB/2UQ7pSGM/milSHekHu3glE8fOYZvovt1x1VvSV7IW9bRiLRmFBXyt/CLuUdNjlEa89rmGn79s2bk1IJclX3nK8fL7hdNRgsxRNSdbVRLmWyWW/dMa+9LOAYf4s6EFZQZYJQImUdOAK3l4teCvPDfltx8rmC9qBnHFy+8Y8q2bDan3Oj49Pnkfme9tdFR9ohwZq+YHazTnz6a6zxclGN/yZafAEvGbBwOWTcRGkvHwOOeLz43CLmWmpPRYrUpH+vjSdWw8wGVr2v3bP6v3F2VIvoXNRpjeJt63kInW77mSwqzpeDPKkUaDtumdwaYjXLmnUUC+xcd98LFGzrQlUh+pmhvieqhnmHIX8g11PEuLlLuwuIY1iY7v64l2PicjqOeY4qa+thAo9jHZWEOrjcFmK3jxGDenshvQP4efPqU1e/mGOp7riSq0wwuqcpYHmHSkz19b6Ok2EeIqaKtQ/Varw7dZQhLyCmOr57GeKiGtZ2gFXKGGEBOUv2RF1UAR2HiQaHTxGXr3dejw7ERHADt0+DyANymGhboh0zEm6oVYllINAxK6fl0B+KAIHrdfoOpfuqIGD1CSkU/REa5XFajc1b0177StwUbQqGEBE4VqrwnSLJVotIXef30ayIipMc2Mi6M5//uXZMz2KihKBusFdjDGzwO5OG7psIn2xNpAMuO+dgxHPY19iXMdoYoHm+nINl2BNkHiHl+6CY/kI+azinilx6APfpkj80TH3qgfFwhxIvNQI6Yjbz2xLow8NXjY1IcIDuxAya6r+PLTC770Akxzw3C5wB54TD5WlbI+0j0+12qOYL1QImusKnSLG/pQbayK2+KmEjNjtLqtPtLzUB9hjp4gkxABYyKYPqXByb0NfD3VuBWjYdZmuR1igNaUzLVLHTFnG1De0vy94UVs0tPnND+tul29xGQrmMEZ/Py6um7H92KSDI9Vwplvaj6gMfpHA6Jj6HqKrW4R0ejuZHlLzSxujknXlNBXu5h0gG/n+sdK7ww0U90ZzDd01Juf1jzK+gic1XF5cQNIlOi1hRpAvNNMy95ZoIW40JWBch/Ko6B+Wx2frz1we0+0Q4cOnxQ6AtihwzMIEWE2m518v7u7yzd90zfx4Q9/mDzPGQwGn9QH17IoOGwafFvSzq4j8Yio8th2Tju7gkQ5cdVi3E3aI4vYHnExxfg92oMaMQlJsYuRmzS9BWBJlpcAoekvAEOyvAZA03dgLPFSx83tRF3DyXIffE0707qvqFxg2ynNYhtHQmVG3DooaIttJJ5jmyVROeOo2sYnJaadkxR7uCOPyzXSJV7uInZB29dxbVLsIMbQHBoMQrK8DOJojnSfL1k8jnUlzaHDx2OSxeNE7ZR6Iewla8TLy8TNHs1EcOkmUXmTpNqmOfIcLVNsOWFXKlzW0OYNcXGDbPoUPh5RFhsYXxIXO2D3sa5Q0mQifNrQ5jHV7HGyxXXqZY96uYqt94nLW1hX4+Mp3vaxvqCda6ZiNt1HsNR+Gx9Niee7xPUSX0xp57tE9S0k6uHjlmRZ0ZBwa++Ag+oy8eyApPI0eNzyOsnyJiCI7YNzWPZoZynGlySzPVx2ivrqFZLlJZLiMi7ZwGWeuN7G2SGRX2CrXdrenTQTS370O0TtlHKRYfwTRPVBIOc38MkGbbJGtngCRCidI6qewpUREz9m58Y2tjV4M1RFGM1CtJLg2opk+ThIQ1MMyRYf1gbAZB3bTjDS0KYbWmWH0CaCdQmYTHdTvWDcAiMNkb+h1YYhm1FIEOkR+wVJtYvBU8ZnmM1GUFwGoCgK9vf3adv2o95H3nsN0oaP+fMOHb6Q0BHADh2eQcxmM1ZWVj7q8l/7tV8D4N//+3/PYPCJq6ucc8xNn6zcg+oyZXqRyDdk1S5tWVHld5BWM7J2l7JKaJJ18mqJ9QWVm+Bsn6xqiaSkcAslU3VM5AsqKRCTkjQ5kVtQ+zk+6pE0KXFzSO0OcdGQpBbidkHjdmnjVZK6Im1m1M1NqngDI456sUvTGOr0LEkzIav3aWqhymLidoKv5rgIymaI9UuyqkCso/RzjLTkVYFgKb2S0qxqML6lokKMJy3BilDRINGcpImI2ogKh0Rz4sYStzG1eHw9J24cSWOoEeq6xraeonZUYnDtnKhu8DXU9CiXFXEzJW1L6nidyLuTOrvaC66dkxU1rs1ZtgPa2Yy03iVqa7zN8T4h8gsMDaU4onYGRUOTrFAUjsjvkJVHtM5RkUFzSNwuaeI+kbuB1BMaSXBNSjrdZbi4RiWOZWUwxTZtW4CBuN3Fm5gmXqc2MYPFZUwzZWkvUM+npFVN2sY4X+PaKdCnjYdk1RHWpZR1D+cLpLYIqxRlRNqWRM7TRgOsb6Fd4ssW6pImGtHMDhkWjyFNg2eEmzwGvsCbhMYOEJOQV1eo4g2qdkS/nuHskHpR0/gxYiKksRg/UIG6LbBS4E1KUj6F9+gKoFQ0doCVlpYMzBiDEPs5UTslbvew0uDF4xAgYxLdybJ0gNYStm1LVVXM5/OPeh+JCFWle7O/9Vu/BcAHPvABAA4ODj7l93eHDp/P6Ahghw4BP/3TP82P//iPs729zSOPPMJP/dRP8cIXvvCPvP4b3/hG/vE//sdcuXKFzc1N/uyf/bP82I/9GHl+u4x+NBoxmUxOvp9Op1y8eJFHH32U0WjEaDT6pBTA9773vaytDDg/HKkJY/VBjLT4yQjiAXblLmjvxM+uYpIRZngOqe9EZpcgW8UOLyLVeWR6CZOvY8d34xebmlPXX8eO78JPL+n349PY0R346VMwtzC+gB2ex89GaloY3oEdnMUvNpD5VRicx6WbvPvWZc7ffTe/tzzDjz9xgScPl7woX+Wr71jlzzznIlZq5Giso9WVu0EEf9gHY7GrDwAGf5iAOOzaQ2Bi/GEMrsKu3acj4kNtwzArd/Ob+2v82/d9kNk841Z2J994/ybfdu5D2MJjVi9i+mfwR4/DssWs3MmlWyV+MufO0wMY34EdnscdfADZXYHxGaIzz0VmV2AR4eMhVmq8a/j9A3jTtXv4z7PTfHv/Bi9dH/LIPRewK/cgRzGy3FEDRLrKcY+uWb0ff/QYsp9jxmewW8+BZorfWyLVEXb1tMaslD0YnEeWt5B5xfTSIXfcdQejXoLb3gbAnn0OLG9ArXmNUh1qGHTvNLLyALK9C1WOPfMIiEcO9/HmTuzwvBooorCneLiHyS9gN74YOfogMskw6w9qHuACcEPdyUu3MKMLyOGHkHIVs/GlOordWzJbNhwdCGfvuU/39mjDnl8MxUhXCdoFFKcx43tg9iTiE2z/DL48VLNK70xYHyhgcE5jZrD6rznSnb5mqSYQ73SLwY6BNXUBT6/CchuiBE49j4sPfT1x/9TJe+UP//AP2dzc5Pz58x/1PnLOUZYl7373u3nxi1/Mu971Lvp9XRd47LHHAHjXu94FwKVLlwBOCGOHDs82dC7gDh2An//5n+e1r30tr3/96/m93/s9HnnkEV760pdy69atj3n9n/u5n+Ov/bW/xutf/3oeffRR/tk/+2f8/M//PH/9r//1p13PGMN4PH7aP1BiOB6PP7W9JZvC8KJ+QC63IR5g0jGm3lfnqU3VOLG8EZykokShOlQjAtoCIiFo2URpMD3oMZh8XV24x1VsvdPaMyxenZz5pgYRN4XuDSYj3Q1spuAdguU9u4b/43cOee9eo6plWfJvHjvgh95dY3yNcYU2c7jqJObFtKFiTpy2lIjTvTbD05tBMIiNEeD/ey3hu/6T5XeP+kxdyofmGX/j9w1v/NBY2zeioKqmQyRZ1Yw9wNlMY1dCLiI2QaJQuyaizSRxT38P+A83Lf/HowPedbRC6YQby4hfvj7kjY9vaoizd/h4hM82NFJGBElGmrEXZbqzOLwDEyX4Zo63OYzuQvItNZ3EQyRbRaxF4lWKaBOiPq460vHz6G69HcL+o6t1jTI/BcMLmOoA6imSDpFsDAjepjq+bgvN1MtWNF/PVRirvc5CcN9iQ8QOupdnrOYVes0xNFEfE6eYo8cQX+OydVI/VRdzW4DJgAQmT+iz1Dutpo2orzuc6QokA7yxumsZDzQ8XBrA6B8czVId0dUemFR3WY+jcRJ9v1DcgvklKPbDjqTR98PWVzyN/H0qyDLdA73rrrsAeNGLXgTAQw89BMByqYHSx4Tw+vXrf6z76dDhcxUdAezQAfjJn/xJvud7vodXv/rVPPzww7zpTW+i3+/zMz/zMx/z+v/5P/9nvuqrvopXvepV3HXXXXz913893/qt38p/+S//5Rk9TgP6Ad0uuG32sErIbIzka9pCIaJBu/2zGrviK1VnjsOX65l+yMaZBh83cyWQIhr70SwDgVzqh72rdBwqTnP8fIsxgjEgvgWEViz/11MxHkNDxJIeMxlSSsK/upLwoXlPQ6mjDDHBqJGuIFGCmEgJaTQI4c9WjSDHrlaRE7LsveGn3qf3mZsGa4SeUULxzqtzbs0rrUcDDbNu52rMAGI30xw9XylZa2Z628lIDc31QaiCa2kl4ZcuCwNKMlMzZMmK0dH0//VExK1ZqeenmWK9NntYV6iBoi2R+TWtmBOnAcn1VEOYyz2to2umek6ro2D4uBXaQRrM8iamPsC2c6gOMeUtNdz4CsodfUzG4qtDDXeO+5hWyb8xFt8/p9eRNvyRMNPg7ZV7tJ2j2EOG56F3Cl8vTuJbyNYxo7uQ5W7IFTyvBK5d6HNvglJnDEYaLJrLKLTq8J3f0BrBbAyzKxp8nQz1ttwS8lN6X2I0rNwk4fbikPU31dd2cUt/x3g16PQ21bhT7sP8mn69/pAqxZ9mrK2tAfDwww8D8D/8D//D0y7v0OHZgo4AdviCR13XvOc97+ElL3nJyWXWWl7ykpec/PX/3+Irv/Irec973nNC+J588kne/va387KXveyZPdh0BQYXlOBVR9A/B8kAKXahXWKzNY3imF8OjtcIU+4iyx2MMYHALYJbGAyR1ob5QCBDoLMcV8Rl67cVo2SoKiCR5gcmQ42G8S24in0/5EqRk5maFTOnIUIwDE3BhpnwrluoItlMNYJGnDaM1NrNq73ERYiDKXTUHUgnvg7HC9uFcFjpdzXqIG7CNstSMj4wiU/6hiXuI1Gu7lbA2VzzBuNeOB+oEnfsKI0HOmZ1FTcmRyydYVfWOJIRCQ0JDRUJJSm/s6/GFNKRKqu+UaWxfwZB9DymI3W/+lZDnvOzSP+Ufm1z6G/peDZZwYzuprYjJVRxD4Z3IuN79XFk65hsDW9SpHcO8i28TU+CtM3oLgC88+GPA0FsD2yGlIdIsYPBYW3ID6wOsE2h5LKZ6nNYHWiOobFIdagKYNqH6ZMYEyPDOzDtUhXhuK9kvnda3eP5aczK/Zh2Gs7JGhIqCY04VS6biR5vM9djrCYaLG5DLE++pQphHFS/toDlLZhdVeXP5ECq6mGUwR1fR9TffEbfbgBRpK+x41Fxhw7PFnQEsMMXPPb29nDOsbW19bTLt7a22A57WP8tXvWqV/E3/+bf5E/8iT9BkiTce++9fM3XfM1HjYA/3TBBGTPVAVLsnpAYzdRrwkgzU/IhHpONkewUYLQRYngeScf4Zq6T1cE5ZVXlnpLFbF1vp9jWkF+b6Mi23FP1xzeYWseOAEZ8qC4rSI1u8kc4LB7BUJEgAq1E5HGkDSJGx5DGRJBtIEkfsanefrquAdA2UcUvCQaCkNsnUUYWCS6MrY/H1zaMiXPTkkdanycimHZ5e6wsjtgtgrGjRVytJCXOMOmKEo7qSElqPCTKRqQ0DExBjKdvKmLjmfkBBT1W5EhHsAg+0ZBlU8+0Jq+aQjXBRBnWJnq+ljcxzT7GZhpAXR9prt3kKUy5o8TGWFX7jh6DZop1S927dLXm6k0fx9aH2HSgz8vihoYy2xgWV8EaJF1X1da3MDirO3k2wYzvQkTwzQJGdyPDO/S85mtI0tNsyZX7tcHDFUj/AmTrWttWT/S48WR+ilnewLqlhmYvt3W/sbiFNIUeS7mrimPvFJ5EQ6DH9+vY+bgxpT7Smr56BuW2NqgUu7onaPsaF5Nv6fWbGcwfBzfR8f3a/UTrDz+j77UOHZ7t6Ahghw5/DLzzne/kDW94A//oH/0jfu/3fo9f+qVf4m1vext/62/9rWf+zrNVGN6hTR7tEsZ3IVGKX6h6Y/pnVHGZX8UkQ23+WG6r2mNijKsx5R64QrU+8Xo7odkBYzULEFTli3NO8gTzU6qQHWf59c6ouuYaRlHLhfUNIoQhOio9lDHWOE5HR7z0gtaJGWnC4j+BUIYKO9Bjqo+UFIBm7LULTKv7WMbVbKaOL1utiIyQ4NQlGv6bWMcj6xJ2BwnRIcfBzxZPjJgoKE8x0pYhXNio0mkTvM2gnnI2KdnqW/ZlhZqYEXNyKhoTM0qELz8V4ZMRuFpbLzC6Q5mOlXRJrecm7qkiGPc14NjVOrrPN3U/z2hsj+Sn8BLr99nGybkVkyDJCEnHSLaJ9Db0Nl2NRD3oX4BkqOrfcZVeto61NhCn60rU01Wk3MdMPhwaUJbY5Q2knmImj2OW29hkAIvrOq5OR7C4rq+H3ha0MyQa0tgR0juLH1zEuwYZ3QXjB9VwYmLtBa4OMMVN3e8sb2ojSrEbepNnuueXrqhxZnABMt19xCZqBClvwPRJKLZBLGRr0DYaBt3bwtz1p7DHWY4dOnT4Y6EjgB2+4LG5uUkURezs7Dzt8p2dHc6cOfMxf+dHfuRH+LZv+za++7u/my/+4i/mm7/5m3nDG97Aj/3Yj53kjD1TMFGm/4ptDRY2sX7At7Ow6B8pGfFt2AUc65jRtWr66J9Rlc2V+iHc21LC10w1IDoeaHhvFdQWm+reWDPH2Fhr05Y7iKswOK0xq/ZBPH/tixvWEseqmRMZITJKHf/3L2pZz/TYxejeIgDpSEeV5jigehVJxyddvmQrSn6Ov09HiIn5q8+LGSdQSEqE4LBYA3/5uYZeEjpu8erOxSghlBZ7bD4AaJc6Eg9mCNPMVP0zgkQZ+Jq/cG/FKFadcc1qrMgRK/y/X1iRNnuq9h3X1blSK9xMpEHJWEzvlB7DYluV0mgASV8DnhHENcjiOtiIqLdJwhI7v6zXzVZ0X1BarDWY6ROYdoLJT2kt3uGjUB0i+RpmcU3vJ+5jljv6+8PzOq71FfRPI1GG9y3SP6/dzlGCP64I7J9H+heU0PlGA6J7m0ixF7qbRxjfYJdXyf0elhZTH2EO3g/NDOtmulZgPLgSydd1RJyuKpEd36dEMhloJ/HyphLB4ipMnlTy6EtVCvNN6J1T5a9dwuwyTK/o3mAygNNfSrx2/zP6HuvQ4QsBXQxMhy94pGnKC17wAt7xjnfwile8AtDA2He84x285jWv+Zi/s1wuVWH5CBzvConIx/qVTy/SMdLb0rGpNDC6E5lfQ4p9zPAC9LeUpC1uYAZntNFheROTDDBJH5lfgfl1JYDGYJoJUk10h9Ac7wU2GDNQc0a7BAET51oD16ob1aRjVauaCoPn/Noa/88X7fIftlv+U1FzKlvhW9cizo4LJRZxHpzDM8Q7DAasKJHpb+n+YrNUhbB/WgltPYF6RY0AbYFxBfeMF7zzZeu840MlR0ctLxzW/Mn7PHe4FqlFx9gQgo3VRIIxiFEvNGgDiXgPxPo4jNE+ZaMqpUQp58eWf/rVPX5hR4h3FtwXxXzrAwPOnDLIgdWbdcug4sWq8IlAsYfgieIeIiDG4l2L9UeqCtoMk65i3FJJTjI8aScRMTrK9zrGxsZgUzxxaESJ8b7Rx9LbwKZj7SH2lZI5cTo+F8FPrkBbYYYXVaU8+K9Iug4mxhT7ums4fQKTjLDrD+L3PwDLbWTtYaL6CGe1bg5X4gcXkMmMxvTx2Sl1cg8vQn4KX+5qpVs8gMUNVfjiEZRP6Sg6P6Uqr8m0wg2r0TJ+RXdZfeg+LvbCCNjcJoP1AqptrTE8/SLMha9+5t9fHTp8AaAjgB06AK997Wv5ju/4Dr7sy76MF77whbzxjW9ksVjw6le/GoBv//Zv5/z58/zYj/0YAC9/+cv5yZ/8SZ7//OfzFV/xFTz++OP8yI/8CC9/+ctPiOAzCZMMsNkqMnlCP/BHd6pRolxietr/SnCjGowqb74M5o0Rcrzr52rNk2uWiKt0JDo8D0dzpNzDZCv64T17SlWblfvUvVseQHlLiQVqIEjRfbth5PjGMwu+aU33weQw0jq5MFbWEbPG0hClJ5V11hh8MG0QTBxaYTfGHI/7UjWeGJuxmsE33ztA5jFmJcHmBjeJ0biYVA0ex+qfTXQPEDXGYGNVoJy6dK3USNvoz4l0FF0dQrbOWj/hf72/wPVn0BjsIMZUE3W1Hh9XdYCJetrB7GolzPFQR5fFrqqL2QoS9dQ5bGMl8bPL2qM7ugtsQu72MX6I9C9iTKxmid7p4IqdwfhefT7236vEaXxfMMx4xMaY+TU1hYzvVXd2c4jJ1zSSpVmomcRYQPDpWMfjto9NR3jXItJCbwubjvWPBOeQeKCu6tlTRPUurRlg6kOYXUIGd2KlwrcFYCE7h/FLJa7ZWHf+nI7vifs6om5Cv/Pyhjp8JfxhEJ3S8Xh1pDupy1s6nvcNxKmuPtz5DcT908/sm6tDhy8QdASwQwfgla98Jbu7u/zoj/4o29vbPO95z+PXf/3XT4whV65ceZri97rXvQ5jDK973eu4fv06p06d4uUvfzl/5+/8nc/cQcc9dZkK4D1meBG/3NWdrvw0DCooD5BiD0YX4XChERor92PzNeTow7onuPYQIi2mPIB8XTPsQJUp32Cs7tGJazSGJu7jo0QjY0AJSTlH5AgTpdA7hSx2wDfYdIxPV3RE7Cr9wI8yaEsdGdpU98ZcibQaPYMxum/mGjW3tCXUR4icg7bWncF0BpzWMe6Ja3hVcxDF6ZhaciUXgipS4p+mCIqIHkuc6H5dsa/XjVJAM+xs2BX0IupajnoapeOKcNqdVqElY4zVbDppZmooyVZVbW1meB96mrOwk2gTjHfI8ibiKqxNEO9DBt8C60rdVRQdP/tmAb7GGn0s4krAaLdzfaTnIRnhjWBdpQri9JKOtFcfwlQTZPpkyD80GGkRk2MmH9K+5ZX74PBRJfbju9E8wUR3AXtr+HQV5lcQm+GM1RF+rDmQUh1BlKuxZvKYGktsqjEwNlfiV96C/AxkiZ6HuAfLoNTWS/D7KDk3Spx7p1RJnT6lfzgMTsO5ryEa3/WZend16PCsR0cAO3QIeM1rXvNHjnzf+c53Pu37OI55/etfz+tf//rPwJF9bJh0jOmfhdmTMPfI6G6Mv65L/Inuypl2oQv/+XowPWjIr4l7SDpUIuRqzOAcXryOWLN16J/X3bTyUBsl0lWoDzWHLVuBRQblHpKvqzonjp5MEN9gjYV2ptfNNzB4JXHtMkSmGCVTvtV9MGvBVQj2ZEcQESWecR+JUjBpIFoDDVoOsS4kI23UiDOMMfioB6bQEavRPEGMPVHqDF7JiY01KLma6Bi8KULunNW9vsVNzd1LRhD1NB6lnuouHF4VKowqedW+KlX9LR3lzi6r0pqOVfks91WRjAeqgMUpJt9E8OqazdaR4UXM4jpWnMa8JGO9/3xDyWc900y+8b066q8map5Ix9BMNI5neRPikbp9XQPlLT03aR9pazxGH0O6golzPC7k9HES5UOU63mbXYYo193GtobqGtQTXO882cEHoUyhd0ZXK5uFHsfwnO7qWavfu0JzC9sIvKhLOemp89fVEGv4NoO+nvtqonuo89CsEgXzURTBxnOJ7nmZxth06NDh04LOBNKhw+cxTJTpB7WIqlv9LTVNtHMdPw4uIM1S96tGd6vCMr+iO2D5aQ2BXlyHeKhu4MUNJYxRrDtl1aHGydgoNF/USpKiLOyoOR3fxQMNVhbRcOdsTVVD36oiGPfwrapW5OsgHt8sMFGiCpF4Jasm0n++hWahES4Y3bNzx80hxW3XcLvUsOVG8+lMu9Tr+ErVS9+oUukajOjXBgeI7v9FeTj+/u12CpuqmzfqK5lBeQomxeQbWkkXmk+wET4eqbEjSsGgETtYTG9LxUbf6K6ftEgyUNOOjZHFtubkxQPdu3QViSz0OfEtVlrAYJY3NLfPiJLPak8fp3hMsaOP3yRINVV1NO4hyxtIu9A/EIpD3f/MNzFxCnGmTufpUzA4A6sP4o8+rOejr+TTG6vRL/mG7uK50KtrE8CpKucWGiCOgWaOzNTMgogqfskK2B6YVhXoOAOJ9JxXR1BOdA91fh2qmf4xkJ9S8lgeqDkkSmH1IexdL8Mek/4OHTp8WtARwA4dPo9h0hEM71SFbfo4ZGu66za9rLtmcYapDzX+w8aqqrlax6tRqpmBvtEUvXxTg6DbUseC/bMa91JPYHBWiU8ZRrm90+qlWNxUUhAPSKh0V80GV3K5Fyrp0Oy9ZqqkDFThaUMYtbHaYevbsK8XaxiysUrGTKzk0kS3g53tsQI4wMdqoDAmKIY2DXuE2jAiNlYVEa2Vk3ig9+mW6ty1uSpVrg3K4BJT7p84fLGRkmQ3V0LYzPUc2EhHrMVNHVXn60g913NAMDEUN5UQJSuYZq6GlmSoDtliV29jdFHDutuCyq4g8UhH4tkqZGN8s0D6Z5HV5yDlvjp1B+eRfAOSPj5b0z7idAXWHlIDz3JHyVfvNEQJ0i6Q5TaYBBtl6lIuDzDe6bFXR6paNhNMcQuINPTZeM1GjDIYXiAqryNiYXiHEuJ2AaO79L7bWahpi4OadwTtXI0ds6s6Xm9nEPWC+3wDsg29vD6C6SWYPBECzHVPkd4pzIOvIhpe+Ey9pTp0+IJBRwA7dPg8h4lSTKQdufgG8g3N6msKJB6qQ9g1uqs1ukcVtsUVVb3yU2p2WN7E5OtBBbyG8ZXebn2IFAeqWhkLbYm0tY4+TazGEfGQ9HEE5c7ESLahRMw7JUKhUxjf6g5drM5ScY2SAdCYGRMUInGYZqGE8KTBZKmKHtpmImFsaVttlpCgImrncKnkzjcnwc8m1LWZ0CqCqzgmhWrVbVF3cKLjUqJQPxeUTZtruLG4ENoca35fPAijU1XxEFEjTrqKNJUep7T4KNcGEhurclbt6WPNNpV0VockFBgTYfF6vuc3MfNrGGOwkeY5muUtTFtgy1uYZqFxM8sbmHaGzVaQ+XXdlczXMMttNfhkp5RYpWO8SWC5h6w9BL0z+Pk1fY4GF5D+WXw91ce3ci94ixQ31bQTZZhmSiJKkGnmOs5dXFeTSNRXB7eJdVyNhXRTnbyInup2CcUNKHZ0H7VdqHO4dwaykRLHgw8BXkfKF76eePXez/A7qkOHLwx0BLBDh89zmLgHK/drTtpEIz1MnMPskrpP44GGK5e3tO/XGqQp1XwQ56qSuUr/m65ppEmru2n0z6rhwBUa+WEsUtzSJf5sXUlUUJ+E+KTqy8a5GjKKm+j/ZgTTzLSGDK+kxdVaNwaq+LRVIFoRSrqCEmRiRFpVAqNwvNYqkY17uqcW5UqY4j7eZojNEJNqELTNIMpOYl5IRrd3EEFzB0FVxyjT45Iaolj3HZul7jNai81CbImgimpxQ/cmk4G2gUwv6x7b8Tl3he4fulLdwDbVHL75VXVg5xs6Hq5nSG9DSXQz0RF6flq7frNVGN2DVFN9bgbntaIvXcWlq/jyUEn1ygPq5C1vQRwjvbMQZ0i5B9UuNh1h44FGAy2vhVDwJaa8hWmX2OVNVWV9g6nniBhtfclPg82R8gifbrC0p8PzlKp7GY9UC3Ufuzksr+u+aL0PxXUdF/saTF/JYLah5xUJ3b5PaOizc0AE1KoS3vOnsRf+x8/gO6lDhy8sdASwQ4dnAUyUBBVQkFaVP0nHiCtViRvcofly1R4yvEd3q+bXlDz1Tmvu3mIb29/S+JT5VcCrW7XcRapDrYUzRhf2vY6QQZQgGktLEvIDVfWTZKT3GXLgfDTQPcAog0y7Yk/GzTZRkuBKTDIErBofgiJH6DA28hHk0RWq8PkSmpkSxnaJ9aUqmL7Uvb9Qk2edZhXiGyUlwXVsfaUEzbcY8RqF0taqPKI7fIjT8TBWI15MUApNFEh1rLl7x0pY75QaQEK9m9gUkiE2TsEYfLGru5TDi0q2m5nu3ImBKNWKv2ofM7+kdXL5qu5nLq5h2jm2OcRKgxXBTD6ojzXfxMwv6Sg77mOLbQ3ZjlPdkexthf1Ej6w8oA0jrkaSMTK8iM9PqTJnM2R0J9Qh6ifpY2lhcQXbHBJTKsmtdvW8CarueYf0z2lcS5RrjZv4MGqvYXkJFtvaStOEUOzhBSV7xT5MPgRSKkHcejHx+a8hipPPyvupQ4cvBHQEsEOHZwGMiTAr9+o4dX4Fg8cOzuiO3vImNl/BtHMdIUYWY4934Aps3NM4D1eqSpaO1MDRLDG9U0jvNFIv9EO+fw5wumPWO63ju+oI6hm1HevIdnldSUyU6Hi5OsDYCIvT7lwfyJVvoV1oHZ2Nweu41Birt+MbJZxxolNa0NxAE4WdwKAI2iy4fo8VwEQVQJsgRKrqRZorKETq1A1jXbEx0juj5haAdKikxkSqFCZjfLEfYl3W9XhcpZVxzQKqGSbOtDmj2lMCFWV6Tqt93bGUBrO4rqHXgwt6nXI/EF2vqmm+ASYhkTmSrELvNK7Y0/Fy/wxSz/S2sg19bOkaPhnhmxmSn9Ixvy/x5ZES5vyMqp7L61AtNXQ66akqXNzCpivYahcpdjDlPrZdAKLPF2grh0fJoXd4m8LwTny8RiQV9LbU5BE6pMHC7HElctVEVeG2CjudPXVIp6sQDZWglrc0W3L6pI6MTRTCu2O446XY+14Rxu8dOnR4ptARwA4dniUwNjkJTBZXKvlJxxqD5xpkcFHJw+IWDC8i8QhZXNe4mP4ZXcRf3MAOzqtzdn5FVSobY8pbUE8xcY7BI/VEzR1RFiJESryJwaR6X87pONkGlSnq61gzxM6Qbyihaeba0JGMT1Q54oGSAl8jbaEmDUR3zhCMNScVdMYfZwXOdSzZFljfqDnDBQVQGm0d8aoAGgmRJ80c46oQlRMMKa5Sl7ErVYVDdASM1xgaH8bWUarRL2EX0BiLbwq9LBmogaWtdKeRBDGJtrDYBCkP9L4G59VJXM9V7fQOT6LqbDPHTJ9QQ0z/LGZxHZY3MK7AugIbp7rXuP9ejLGYbB0zvRyIc4Vppvh8I5yzFvpb+OWe7oama3jAR7rTKMM7tUe4OgodxJuY+Q1wMyX5yx2YXtJ6ObcklRDXchLJ4tVx3junl+UbehxuoeakxVU1gRQHQK0B0b2zSvrmO3DwQR25pyM4/QKie/4UUbbymXvjdOjwBYqOAHbo8CyCGZyF4V2qyhXbMLigZor5ZUwyVENEsa2jVBtj2mXYU8uDClghaIuDgBKT3haSr+uumU30w9vXqi4NL+iuXHFLDyBfC4v+N7HpSJW94pYaMGyie4DVkUa7mCiETQdTCeh4FU5GwrprlgBGR8sm1tGl94hVdU9sgpg0qIU53qjrV8yxCzgPrlLC9z0dFwOSrih58Q2YCB8P8L7RHb5sQ9XKZgrG4vMzWkuGCa0WB1pr19/S/y6uqUzZO6UqmAHino5lATO6qI7exXUdLZtEFdF8UyNiyh3qaISka7jljmb4ZWvQTPHJSMf6ApKt4W2O1FMk39R/baUGlBClIibSLL+2wYTmDDP5ILQlJlvFVvswv45ZXsdkK0qCq4PQ3FGH7MVYR7jZCgzOB5U0pjJrqu6VEx3fLrZ1ZaCZa3tHs9Sxs1HySjLQ8+UqJYLTJ/X6cT+MjnWFgDtein3gz2GjbuzbocNnAh0B7NDhWQRjLCbpaSRKUKgkGShxC7Vikq7il7d0V6t/RvPoXIkZXtTrzK5A/5yOLOdXMTbCGN0FNM0Mk/S1xaKcIkShK7bWnbSkH6JUSh3RpiOtKXMV5Ov4ZKCuVJtAvqoEK7RmYCIlWAYlFj7s/UWJEpNWs/SMMeFnS3UH4zG+wLsW2jIogOoEPnb/incYaUKzRqsGlWamt+HKEOsSa1RNdaiKlNHIHNolRtDKu3YRiFFQK/GYONXH25YQ2dBsssDYBO9F7zvJNTuxOsL4Bumd0TF5u9T78g5jU1pyPZ6jxzSwun8eu7ihx1TPML7CDs9hil04/ACka0RRqqHPvsZUu9rkEvd0nJv2EYmDE1grAiXq4UGf+/wUstxFcDrGFlFyZjMwqUYLFbv6nNRH2PZIm0yMUXKYjLSz2SRh9y+DdgrVFBbXlYTWs7AHuqa5g97D5CocPBoicsZw5iuI7vlmot76Z+2906HDFxo6Atihw7MMJhlgVh9UgjG7hM03dFQ7eULHmnGGKW6CqzBxTwlSu9Tr20zNGb6CbFVdp9VEiWO2iS/3lbz1z4BfYsod3Wszhp4c6Yd5MsBUh5hmgs1WlWwtt9XMYCJMO1GSY2LwHl/PlGzaBHwRAppTzQZ0dciWC0HUWCTqAXLi8PVYvEQaVh3leBupKmg1GkeO2y2Cq1jiHt416mLN19Wg4fV7oh4Q6ePIVpFqoqpovqbOalcjcV/Hve1C1bZ0Az/XAG2yU5rD6FokXcHMr6i5ZHQ33tVKikR0D7OZ6e83c2R+FdM/i7M9KHcx6Uhr3toFvn8GwatLuXdKWz1cg6SrkGR4aZF2AVEfk59SpXRxA0Eww4tYN8PMnwJjsHGmRH76lKrB6Uh3EttSx83H+XuROqfpnVF12Aukp8BYUpnquWrnMHtCCXxzCOVhCH5OoH9eMxSjWH8+u6SktthV97i04Je6c3nnN2Dv/3PYOPssvms6dPjCQ1cF16HDMwgRYTabnXy/u7vLK17xCh577DGyLGMwGHxSy+7L5RIRoW3bT/q+43KPqJ3Q7mv4snUFfvJhxCQgCfbgA7qbZxKi+sMQXaVJ1knLG2BuUvcukpS7GH+VpncXtpmQ1Leoe0swEXG5jTcT2t4F7HJCJA1XnnqM2C+Jqlu0hw4frxKXcwwLmn0hchVRuUO7L7hkTLo4hP0Fdb8mKSfYdkJ7FCFYkmIPOaioexdIl7sYaWgmCdbNScptmonBxyskxQ6YfepJTFJexbZTmmkGCMnyJj4pafZbqukRzjmuPPUEUbVDPr+GT9aop48RNftINAR/may4Rpu1lNVl4vIG6fI6Eo9ophbbznDpBlFzQFrsUi/7VMtLZIsniOt92sSAPQIi2qQlX1xGxFP5A0x7g7S8gifBL4+wsouLVoiqXSJXULkK0y6Z37jMvHcKiQ3m4DHEJsTFTXzcp65Okxa/TdxMqJMzmMUNvMSk1VXEJFT9+0maJ7H1IZiUZn4ZIxVxfUSbJBhbgDhsY3HVPtbpONrbjOjgAzoij3rYww9iXUmbnsL6GbZd0qabtGWNbxv2DmYYsVg3w5mI1JeIX2iwtCyAFIzD0cPYFNPmxOVNrL8eQoFixIxZDJ5HET0PbuwD+5/KW+vjvlf29/ep6/qjfiYinbmkQ4eAjgB26PAMYjabsbLy0Qvtv/IrvwLAO97xDgaDwSe8HeccdV1TFMUnf+eyQiSWdLGDmIgmWScvruNsTpNsklVHeLOkTk6TtQ3SNNQux7UG40tad0AjKZEr8e0tXDQk9gPM7DpNukXkB8TNIY2LaBlpt+3sMvPsAlkj2GabMktJWkvS7NH4PrWJyZoa525RpSnSClamVExpnZDWJbVMcdEQXzeImVNKha+FyBWUlFgEXzU0lNRuSK9qERylqclqT9xWlKYBPFJXNN7RiI6DvcCyaMnKJbb2NCampSRtS8pklbQ5wrRCEec0RUFaHkHtaegjfo6VlgrDYHmLWgwz2SCa38SVB7QmxtUOYxxNvEZaXqat51TZHTRlSVbfoGkbfGRw1RIXrxGXt4jrayzTi7RVSexnVJIRlTPaNMOZAWmxg4ijthltcQS1o/EGZzzStBg/x0mCRBl+eYCtd6lsDx+PSRZXETE01tBITdruAIYi2VJi3h7S2DEuTknbGmdSvHNAjxiPrxZgU6xrMMtdGskwviRaXqaNRth2gtiKkpQIT2NH+lryjkTmxM0uxnicGdCSklEDhjI5x3LwCPPel0LVAp/8HzafCN77P/K9IiIsFgsAHn300ZPLOnT4QkRHADt0CPjpn/5pfvzHf5zt7W0eeeQRfuqnfooXvvCFf+T1j46O+OEf/mF+6Zd+iYODA+68807e+MY38rKXvezkOqPRiMlkcvL9dDrl4sWLPProo4xGI0aj0SelSLz3ve9lbW2NixcvfkqPSdoSmT6BeNR92W6i+X4Zxl5E6ikGQfK7NahYGmT0ICxuaMvE6sNaWVbcwqzeo3tu86vI8AwmHiKzpyDu47KzvPfW41w8fxq7djeUK/o7w7NIdB8yeVxH0+M7kelI8/pW70bqTWR2BTM6DekDyOH7IB5hVu9DDiKQBrt6J74caAbe+LxW2B1p5zDju+GwBTxm7W5kniBFD7t2D4jDHzbQP4cdbHHzA5epHNz50IP4vQUynWDHF5BkjGn6mP5Z/FGJFGuYU/djh2fwO4dI5WF0XvcNkx6SrCLblyA+xZnzDyPzK/hZCVECNtNw7eFFZK+EGsypL1Jz7rQCWQWTYpMe0j+NHLbQWMzm86GZ8eT++9g4fT+9/hCbjvFthcxuYQbPUcPN/n9FzApEZ4h6G7i2wBx9CBnfi83W8MsdqNYhW8UMLyCH6Gg3HunxVX1d/LEZNAmkd+roFsEk92gmYXWgWXxmrCPbdADRKah2WdQxuw7WNkMrSpEBje741SVEAuShR/kULHdhcgXaI21SiUbQ2yB9+C+wsfFFz4ga94d/+Idsbm5y/vz5j/qZc46yLHn3u99NHOvH3+/8zu8A0DTNp/1YOnT4XEa3A9ihA/DzP//zvPa1r+X1r389v/d7v8cjjzzCS1/6Um7duvUxr1/XNV/3dV/HpUuX+MVf/EU+9KEP8eY3v/mjPnSMMYzH46f9AyWG4/H4GR9HmTjHrD4EaR8zu6w7fxh1rB4HO7cLNTVE2rlrmmVo2Mh0/y8ZIvmmkovjzLtyH3Glxse0Cyh3KO2qmhnmV7Xhwkaw3MFEke531Ue6dxj1NEuvmetenTVIM1Ojh03BLREh1MVViLSYeKCXSaM7eBg1l9gMMVYbMEyk7ldEdxcB3WdL1IiBV9OK8eFnBm+zUAEX4eJeMHL0Mf1TUOyr8zUZhz5jjyTrSHFTCc/wTmgLpDxEXRKhneS4m7fch/4ZJazFntbstbWaWvpnNaOx2NHruEr3C02su4HpKs6k2r2cjHQPry1CB7KBdIivZ9qekm1A1NPnp56EGjaDTB4P1YCrGskyfQyiCBuPtJ/XFWjzhtH9wuNavkSfR0yqXzdLjbvxDba6RSbT0I6yp7uaNoXslB4nQLmr+36Hj4GETEdq/bQ5+yJ47l8k2XzuZ30Ue//99wNwxx13APCud70L0D/sOnT4QkBHADt0AH7yJ3+S7/me7+HVr341Dz/8MG9605vo9/v8zM/8zMe8/s/8zM9wcHDAr/zKr/BVX/VV3HXXXXz1V381jzzyyGf4yD8xjI2w6Upw3TaIGHz/LFIdqEmit6VZb1jIT2m3q6AVYIurStrSVUx9hNRTNXn4FuqpkjQTQ71Qd2g81Nw/VyPZOt7XSHWE9LcAgxS7SG8TbIIUe5pFZ3NoFprnlwzBNdhmokYMcRobEyVYm+h9SquxMa7WGjU0r08r3Jw6S32LuOOxogBOf2Ys3jlMHWJajFEDRBQr8a0nSoxtgjRLjU3BqUvYRErein3AYpK+5g/6NvQVa3C1RFlQ1awqb6G3WAAMSgh9g5RHWp+WriHNAin38Fit2YszWF6F+kjd2aDxKVJpPXK2jpR7asLpbSiJdZW6qm160syBTfV82BjSdRCDLw8gX1dSudzWcxD1lNAVO0rq6iPt7E16et5cAfk5MDGNT/Q5awsoD2B+Q0OdXaGX986pmWSxDYePghElkme+EvvQt5GsP/gZe+1/Mjhz5gwAL3jBCwB43/veB8DVq1c/a8fUocNnAh0B7PAFj7quec973sNLXvKSk8ustbzkJS85UQX+W/zqr/4qL37xi/m+7/s+tra2eO5zn8sb3vAGnHOfqcP+lGDydVh5QAOG6wNs3A8RKPXtSA/XAILEOeJqjDT4bEvJiVsigwvaWVvPkP7ZoPwdqJrlS3oygcGWZv4VNzHpGtZYVZtMoo0Z1URjQOK+xqi4KpC+SglXMgZc+LqvYdZtiY9yvDGad2dTJRi+VsXNaiyLIEpGjxGy/jCRPjYjeJtgfRn2viJ1RYvoSLQNtWbZiubytSGkOu6p+hiF61RHGnmSrSDFnqpsYtRknK9pVd7iurpdk4GqqL6B8kgz8XqnYX5N+3KzVazUiI3AFSQU+N4ZpJ5o1l4y0GBtEymhtRmSrqrCSIIkI3XdzoOi29tSIlfuK5HMV5TEVweQjlUJDEqsOq1bbYSJMj333unrIV8PUTcFIErmyluYdkHGXH8vzvU8JEM914tt2H8/TJ4K2Y0ecDC8A+5/JdHD30GUjj5TL/lPGce7uC9+8YsB2NvbA+ADH/gA0O0Kdnj2oSOAHb7gsbe3h3OOra2tp12+tbXF9vb2x/ydJ598kl/8xV/EOcfb3/52fuRHfoSf+Imf4G//7b/9mTjkPxZslIZQ51P4eqpByclQFa1srK0fxY7uf7kSiltaIecrJW5xjgGN/7AxxqZK1BCIhxhfg6vx2Tq+KZF2juSnNWOwPtLKMmkx5a6SIEHvr7ehJK3cw8Q9JSP1kQ5Vk57WxflaG0GkwbRlIBhOO2ZV7gpVYqJfi/+I/xJ6fgWw2u3bLsGGEaTUSJRDtQ9SY2Ktg5NmFuJnar1OMsaXe0qK0jGmWeKPCZNUmDjV3bfqAKzRnUdfKXl0SlZNPFAyXU80bDpdw7WFKrBiqNAeZDO/pmPX3pY+3mJHFbZsRXMZ55fBOEzU18tPRshRGGmHc9JUYAfarrLcA5MrMa2nUM0hGynRXN7Q67elqoK+BTEabZOuqVpoU3UIS6OPcXYV5pf0tRIP9XlsZlBcUzKYjGH1IXjo24nu+HpsnH/GXuv/PYgibTh5/vOfD0Caao3gU0899Vk7pg4dngl0BLBDhz8GvPecPn2af/JP/gkveMELeOUrX8kP//AP86Y3vemzfWgfF3ZwBtvfwrZzrTnDBIKjKqA3cVCHYt21Kw90L8ymyOIWkm8ABlPshK+9krh8A2s8ptzFZqtYvCp/cR8TJUh1GLLlEqQ+0n2/OEXquR5Y3MM3c23oiPr6NR5ve2pM8A4SzeHD1yGbzoE/VrJEd9jC/9JEfBj5SlALKx13mzRUu4mOK4MCauI+Uh2FDLvTqmx6IIp0rzHqY5JclbYoxwzOYao9HVuL13PW29Jjmz2lvbdJX2vlfBvO0Sr0TmFmV5U0RYmOl6NYVbkowpFhij0dpws6KvchqDpbVZJXTbT/uLeF1IdKzvM1NWsUO0pQ++c0VLu4obdvLLip3o8J+4rNVPP9spESPhMH9VOUFGJUSSx2NMy53IV2iUgEvU3d+WsqHU3v/lco1EwC6GO96xuwz//fSNbuw9rP34+a++67D+BTNmB16PC5js/fd2WHDp8mbG5uEkUROzs7T7t8Z2fnZD/ov8XZs2d54IEHTtQCgOc85zlsb29/zPyxzykkA8zobiUNjSpRSK1KW7aCqQ+0QSMdYav9QMp0dIq0Whl3THqiXIObmzm19BFX44sDpH9ayVB1oCYFV2ntWXZKd/fKQ61QcwWmOoJsQ40Q9QSTjjVMuZpg0wFGRImi7QFeQ4/jNBCv+qSZw4ju4on3Sm5F9GtjEddicAgRvi20+zdKwBWIN6oKNnMlqcZoBV4IdMZVmGyMr6a6I5iuIM0c72qESFs64gE26eHnNxGS0CLS6k5ffYTEQ0wyQKoDfDUDk2OyDaQptA/XWEg31EdSbYcatS0dJxf74Jzu1pUHeh6t1ccvrY51MWFcG1Ds6f5fsqpqX1upeQen36crgFVyF3YmWVzRx9ssdLwfBzdvPFSS7WpMMyd3O2ryaEutsfOAP9KxdzqC0f3w4P9CfN+fIeqd/sy/vp8hJElXUdfh2YWOAHb4gkeaprzgBS/gHe94x8ll3nve8Y53nOwD/bf4qq/6Kh5//HG89yeXPfbYY5w9e/ZkZPS5CmMspreJSUbqTDWRNlfYCPEOL+CjVLt/cyVvNHMkW9P9N0CSVczypu7yxT0obuGtOkJNMwGMEpBmGtS+XHfhbAxRhq8nQARRDykPIErDGPYAiXs64q2OwteRKldxFuri5qreYdRJHGX6tasxx00Wx6Tm+HtfaQC28Se1b3ine3tJX1XGZhEUMKffG4G21mNMBkpw8JCvaN0cVgm0b2BwFtcUmOI6xAlEGTaKdWS9vAn5uo6El+oqNzS6a+lrvY10DNKS+KWqsTZW0lcfKAlLgkmjXSD5lu4sLm7qPmXvfFD79nXsGo/099qFElrf6si2mgFWCWCxq9dzrZLobFPVT7ye52YGi1tQ3tLH7Yqwf7iOI1NF8PBDavIQr89lUP3M8/8SydkXaddzhw4dPmfREcAOHYDXvva1vPnNb+af//N/zqOPPsr3fu/3slgsePWrXw3At3/7t/NDP/RDJ9f/3u/9Xg4ODvj+7/9+HnvsMd72trfxhje8ge/7vu/7bD2ETx3ZGmb1Qa0Da5RU2XaONWBshqlniNhAlMJoT1wYvdb4eKCKmDhIxmQyU8JhUx2hZhp5Y8oDyNZ0FFofIr1T2HaBNLPbpgm3xGZj3c1rK1Ul24WSlygQEhOpstbMdX8RQdpCI198G0whx8qYR4mgQ+R4zK31cdQzNAsxxkithKc61PuKR5h6qoYS74AGk2gvMdVB6CjW2/XG3jZXmAhT7iISh6q3XOvmZleQ/LS6iqsJ0kzBggzOK2ErDwCr4+N2SeYnkPSVyLWLUJ02VkJcT4PLuQ3/rXXVr9oPKTSJfl1PlNC5Rr/P1gMZX9xW9NopmDAiX1zXnL56pscjKMHO1yEaKEksD+DoQ0TLx/E2AZMBhd5O0oPVL4LnfBfR3a8gHp77zL+WO3To8CmjC4Lu0AF45Stfye7uLj/6oz/K9vY2z3ve8/j1X//1E2PIlStXnrbHdPHiRX7jN36DH/iBH+BLvuRLOH/+PN///d/PX/2rf/Wz9RA+ZRhjdGQnLWQj7dUtZ/qBXi/UtYvu2Zl0HCJSUsSm2GoP6Z8LiqBT8hiy4rDxbYevzfDtUglFMkDKI4zNcPEIW+7j+2dUwSv3kewUcKDu2HQFqgmmmSPpGJlfx7SVEphmjvUlPu5jfKOjX5uCq/QyE4wevg0qlNPjMhHWN9pzDOCCCmcTJVo2UrJVTzEC4pZKJLNNDcNuK1U8DXiTBLOEg3wT41qNdZEKE2/qyHS5p+chX0dsDMUtVeyMwUQ5sriqo+t8TdXRttB+43igu3tilch5B8V2CFHe0uehXeqI2FUaORNlSvTKPfBzJbU2UmKPR0fE0xAJE+lF1RzicXA/J6rkukrV1mahY2hjleAmGdSXMPUuA/agHQOZEvt7vxm79QKifPOz8Cru0KHDHxcdAezQIeA1r3kNr3nNaz7mz975znd+1GUvfvGL+e3f/u1n+KieeZhsDdIxdn4dpMYzxLgZEgeTxLFZxDUawdIWQf2baThylEE5oTGZmjKIkXSMKfbwvU2MeEx9qGNQXyH1ESZdhWKpBCUdqdkgqZCor7l/6VijT8p9zOC8ErH6UEfC5R6ubTRipi3wYjDWgNfOYwARp3uAxiiBEkFshPESMv2ski8bqcpZz4KxxIOvVQFsClXBbKwGiLALaUykkSDLW5CNlMDWh7fjYLIVTD1TdTAZQdTDtAVSHEI6hN4pZHlLR9n5OpKswvwy+FbDn02sx5Ou6HG2BcFKrL8jql5qvI7RaJlmBuWOKqdNo6pefgZip7eVnwr7gEfq6sVBvQeup4TSB5JsUzWw2EyPf7kPsytKFIPD2oCel+FdcNfXk6w/5zP7gu3QocOnBR0B7NChgyplvU0lH22hI1ExStiIoCkw1iLGYts5km1imuBGFQcEwiUO8WpIkCjH1jOwCd4kGr4c9TSLsF0g8SjEw2xhovTEYEEzg2qqdWbFLvgak66oMjc4p6PgJtxWPdP4GROpQxY0akZcUAEb5S3tUqe+vlQXsOEk3JlmDu1Mg5J9hXftbQXz5HgmnGzMxCnMrgMOohHS1nq8bdgh9P5E0WNwRgllOdVxa5TrPl1xU/PzTKxftwvoncOyQ7S8AWmi6triht5nOgIiVQKTsRK9ehpyFDMlbPVcx7XxEPwUmoMwwm3092xPj8lYVRdtHNpWwoi7mYVWGKP7gL1T+ribPXBz3Rk0IxaySvbwdxGt3v95E+3SoUOHj0ZHADt06ACAifuYYV+bHZIeEiVIPdGwYVcgJsK4Ws0Uvgbx2sgR3LM2VKqJjbDNXAlMswjNHUrQsA4xVn8nGWrcSX2gFWfVgY6Y4xzTTDD5abBWHblRouNg32KiFONrPS7fIG2FMQm4EutbPAbv6qAGWoxUiBjEJpqpZwgRMbEqdOWBqmrJAONKJOmpIhdlmHQAxQEaWihhN68Jzt8epAOMLxE3V5WudwZTHWikTNJXAlkcqCkj21DCVexqxl+6ouPXehnCrD0Roc2EVBVG1yrhLCfheNeUpB1n70mjo+V0CEkK5VQfy7GqmspJvR5RIJyuVuLYzqA4AlolismKEsn5VWiOoLypx4HV/64+SNW7jyuzLbY2v/iz8RLt0KHDpxEdAezQocPTYAZnNHC43NfRJ2B8i09SaEvExpg2tGn4JpgvYmIqQJREWb3usSPX+AqxPainSDzAWDBO9/hsPUXSVGvRmpmSLFdo3EuUa4xKflrJTjPV2z7OJxTBtHMEvQ/vtYnFiDsJMxbxmreHYGnDuNNDYgCjTmXUeWsQvV9fQ29dR8fNPKiBI+1IXlzTvclorD8v9tQtnK9qo0l5EJoyNnUnr56o6hYPNEcQo7uM4lX9i4dKvuoDIqn18UWJPsZYA5ixtZI+8RBZ3d/ztf6uKXTMm41DpuBMj0WsqnqkquSJD7dhNFORsR53PdEoGgT6p0KUX6h/S/uQ3w1bL8Le9Q20swopukDkDh2eDegIYIcOHZ4GYywkAyyi7loE2glGWozxSsSITirWJOpBU+qoGINxFZKMMO0Cb3MlHcaAW6gdwZUIBpFWxbg415Fw1APxiK8Rk2HqsB/oZvrzZIxtFvhkrOpeU2DSoZLFqI8xEgweBqRVtRAPbaVdvGIw7VxdvK6EZKSPr9jVkaer8FEKy10liXEfKQ5UrXSNErhqopVuYtUQUh8q4TJGd+yW29CUSrDSPswuA/52DVu4X4xV5Y4wiq0OwXkaUiVedREaOw6VSMe9sA94BDJUdbE60uOMeroPGDIacXMobSDMtV7XZuFxNxoZs6z1uLJVHfWWh2oemc3A9oFcA7HvfBnm1POJh2f1xTHb/Yy+Fjt06PDMoSOAHTp0+JgwyRCzMkTKfaQ61F7eZh8xKcYvkCjVrDobmiWMqmtiY8TdJmLGe4h7GKduYCONxrGEijT92iF+oQ7Z6giJ+4ivMD5FohjjSmyUqxIXO0yU4l2pB+rUnSuuPgmBFqeKHwbENxpsTYwNRg11t4YYG9+okcJGOn6tp4E0RWFEe6T7bzYLbRiFtmcYG7qNa8i3VG1rpkroshWtQ2uL4OT1UO/rbUZ5iJ0JpNI3SvpMhGlr7We2FuQwNLS0waSSKFFtJoEQpno72ZreZ7NUA4e3qgr6oOI1V0OOX6pRMb0NJYzLa/p4ktAEAkACK/fD2v1w4f9BMvzYQegdOnT4/EdHADt06PDxka1j1jJsu0TaUN1mQkWaCdl6bYHxFtqpGkmMQcRBlKnKJm2YBrtg1KiBGPEOY1rExBqlYhPd8XOhn7dZgEm1V5iQ8ddMNYDbHSLpCNMudRSK0etjQkPIsXm20j06KgwN+Ah1hEQhg7DV/xPaVM0crgrBzAaqPb29uA9oOwlJpiPbE7PKGCKjI1tX6T5eNVFVLc71sVZTVO3rB+VP1JTRLFWpi3MQyKJCfxb1dG/Qxnrf1VSNKdmKunyrCuIVPbZ6psSwXejjckto0Z9FkR6vKzV3sJ3r+DlfJTBwdTsnA0jOwx0vITr3ldh87TP28urQocNnBx0B7NChw8eFMUYdq1EG47uVhM0uIRLiUk7iQRzqsDAYPGIiVcBsort7JlXjgUk4Dmk2UYy0DhMbJIyXxbvQXXusFNZgkhMDivEtYjNMq4qfGhvCCLpdak2dCVl/4rTFxDdYt9SYmlb0GCT0FUsd4l8aNV6I6G2etGeIErT5dVUEzVAVs3Jb/RE27N3V00BERQlglIQxcbgNY5TE4YKyt7wdvRL6iVuXKIGrtGZPHcqh+7g+JpWpGkskUmLnWyV1vtVjFwM+jJFdoY91cEa/p1KSuijQ//1nsPnFcP5PYDYeIc5XP8Ovrg4dOny20BHADh06fFIwNsEMLyC+Qdoltq3w1YG6WF0T9gMFaJXE2VjJmrEY75HIYcQgJtS0YZCmDu0elRJFVyjRPK5rk0bJoPeqHB6rehRa9tEWakZxBZpufEyCRMeoEFpBjB6LtKE+bU2JVRvGyOkwqIELDXGOc1juKMHKN/V4qpny22xFyWFTap+yq3UUa2M1YVSHeiwmD0St1ZGyOCWANjhrfSBvEkwprlCFUlBVDpS81Ufq5g3qJxJGtm0RDBvoWLhd6l6geN0f7GUwOQCO9L/mOLIlhsF5GN8FZ19EfPoF6ubu0KHDFxS6d32HDh0+JRire2IGMJMPI/YAV8/Vedsuw5VM6Bc2Yc9PoG0QHEisBMZGQW0Lfco+KIihtk3JEahaaDiub0M8tGGM61wgfEFVOyahxoOL9LohHdpQawyMP3b/zvRflITdv7mSqnisRolmpsdoEu3EdSEYuj7ScW/S19up9/U+o5G2bbTFbeXPN0EBnSsR5DjY2StBNTZUtKUQZaTsYmSge5XlgR6LOCV+JtVz4ypVCZsFOA/W6Y5iMtQxb7OvxxSvAs3tJy4dQrwFWy/EXPhabP801nZ9vR06fKGiI4AdOnT4lGGOicPoLkx/Czffw5sPBnXLB/IWHMTOqTJ2TIZOenoDyXOWY8OGNncQVD8HwSCCCdeREOMitV73mBwef+3hRBYzzW2FzHs1WEgBEiJY6tlHKI1oZAtJUPH2dSybrSipLY5UFTQ2uIYDeVvuBBNMGn5fglt3GUhueNzy/2/v7oOjqu89jr/P2YeEkIQEQx6AIAUhAQKhJZIbqzK30gu1Y3VuWzuUWnUo1im0FVqneFsvrVZLtdeh49UytTK2jhYtd9qxFmktlRYQARkRKDE2EASREMJTQp724fzuH2d3IZKQB0k24XxeMzuSs+dsvmezmA+/x0gsjFqJeog64I91h7edAX+q240eOh2b/RwGE9v5I9IM+N0xfFarGx79qeDE9u+lzl2WJrG9u+N2t9tD3J9JznQouAbrisn4gxl98pkQkcFFAVCkDxljaGxsTHxdV1fHF77wBaqqqkhJSWHo0KHuGLsuNDU14TgO4XC4y3OTwQm30WiP5IOWTIJtR7Fj+85aJuJuwWacWLdwENtpdccHEmvVw+fmOIy7j68JYxk/xnbHF1rEuoB9FpYTdRekNo67KwkODra7C0nstSyi5yaMWO4MZcuJ0NbSRDDczNmmCOHQUPzhemzTStTvxzT+C3+kAcdOxWlx8JkzbnYN+bAjx7FMG1F/FPvsGaxoM8YeijGN2KYVY6e6ewebCBY2DgbbMrGhkbEFpImNVSSCHdtaz0Qj2JZD1ApgOyGgEYco4eYGQq0hbNrcoGgsjM8iavwETAjMGXy0ESWViJVJCiH3hxA9DQQAiyiptKVMIJI2ltZhk3FS8qDFgvePA71fyqW5uZm2tjYOHDjQ69foa83NzdTX19PW1nbBc47j4POp1VMEFABFEp544gkeffRRamtrKS0t5fHHH2fmzJldXrdmzRrmzZvHzTffzB/+8Id2zzU2NjJs2LALrlm7di0AGzZsID09vcvv4TgOkUikw19qA4HjWLT6htNsDSdih7H8GfjCpwk6J91JHk6bG+WsNiKO4y7t4rjdswYb20RioZDYUjI+rGg8VPliW7fFxsFZNu5EE0PUcXAsG9tyoyIYbCdK1PbF2sKMOxzQcrCcs1hOG1EngBNuwkTO4lgWESeKL3waYzlEoxZW9DTGtBFlCEQbMKYFx0rBCjWD00rU8mM5zVgmjIPfnXARjWJiQd4yDo6xsSx3lq2xLCxjsDmLcfxEjYPPjmKsFBzTCiaCYxl8po0ADpYxEI3gWH5sE8GiDX+0BR8+wgzHh9uC6qMFnzn3eYiQRptvJKHUAprTpxEZMsqdrQ0QCl2Sn3M4HMYYM2A/h3DxvyvGGE6fPg2Q+K+IVykAigAvvPACS5cuZdWqVZSXl7Ny5UrmzJlDVVUVubm5nV538OBBvvvd73Ldddd1+HxGRgZnzpxJfN3Q0EBhYSGVlZVkZGSQkZHRrRbA3bt3k52dTWFhYc9vrh+EQiGOHTtGUfFkbLsEAKfpA0xTLSbchGmpjc2GjXWPxsfyxVvqMO4xK7aEix1wW86ioXMzdi2LxC4V+NznTdQ9Nz5eMPFeGve1iXc3+zgbPonlRBk6NA38ltsi5k93r/FZ7nZouDOKsdPc7+u0gBkSC1JhMKmxOiJggu4yK06YeMub220dG5/oxJaaIeLO2DXBWBd20J2lbEVjobY11qVsEQk5+G1DwGmKjSscHutSbgGipFDPuW5eIHiFu5hz9iQCI68lPXNsn+7Pe/z4cWpqapg0aVKffY+P6u233yYnJ4dRo0Zd8Fw0GqW5uZkdO3awe/dugAEdZkX6kgKgCPDYY4+xcOFC7rzzTgBWrVrFn/70J1avXs2yZcs6vCYajTJ//nx+9KMfsWnTpg5bFCzLIjMz84LjGRkZHR6/nNhDR2LS8iDSinNmP6b1FCa+AHJ8CzljA1E3VIWb3UBFbIs5Q2z8X2yiB44b+txJvbEgZiC+f25sbUJ8vnOh0jHuGD3H3TLONo77XPNJ9/v7DIRPgWkDAhA95dZDCjjNsdnEfnfGbjyw4m43h0MswMXGH1pObAxirEDjuKfasaVsolas1tbYeEjb7RZ2Im7QJIyNHxgGxIYNRI/TLvCR4obW1OGQPxNGTMfOuBKfP6XPfo6XGzs2O3zmzJm88cYbbN++HXBbDkW8RAFQPC8UCrFz507uu+++xDHbtpk9ezZbt27t9LoHHniA3NxcFixYwKZNm/qj1EHHsnzutnLDJ4Fl4zQchqbDOOGz0HTUXTvPxFr6TBTCsV/C7jA5EssMxv9MfGJI7JgV+xrcsIdxTzGJC9wg5kSwnWa3VS58NrZHrg2tZ9yg5wtCtPHcsjORMODEXiI+kzg+0SQ2YSUeCK3zJrTYsdpMfFILEImtMQiA3w2kJjaDF8tt5aMBgCARcE60fxPtoWCnumswFlRA9gR86aMTQUZ6JzXVbSmdMmUKu3fvZufOnUmuSKR/KQCK59XX1xONRsnLy2t3PC8vj3feeafDazZv3szTTz/Nrl27+qHCwc+yAwDYmWMgfRSWE8Kc/hdO63FobYCzh2Lr4jnu2nwmcm42cHyGsBNrVbPjM3/Ned/BxCZMcN44QdzXsWwIt+JzmnGw4OwJd4awHXDDn4Ub+M5fmiUa2xotnrGi5y0xkxBrZYyvM4OJLTHjroXoJlE/bvdwbO9dACfl3J8xED0X+NxXi83cHZIP+WWQdRXW8CL8ga7HikrPDR8+HIDc3Fxqamo6/TsvcrlRABTpocbGRm677TaeeuopcnJykl3OoGJZNvhsLF8Ac8VUbMvCtNRjzuzHiTRB4/vQcjS2uPIZd7Hm+G4g0fjizrHuYCc2KQTc3T38sfGE8ZBmW7Fr3B04LNrc1yK2JEs01ioX717GjvXuxpsdiX0dC3iJLmCHcwHO5ly3cDwcBojtxYa7Dt+HZ25/eMxZbLzhkCv4oHkEecUVBApK8acO79b4ULk0rrzySmpqaohE3J/dkSNHklyRSN9SABTPy8nJwefzcezYsXbHjx07Rn5+/gXn79+/n4MHD3LTTTcljsXHD/n9fqqqqhg/fnzfFn0ZiK8laKXlQloutnFwzr6P01znThQ5udfd2SLS7K51Z7W5LXXR0HmhLR7W7FjOSmyNcS7MnTe0y+Zi47yi3ag6HgLP//rDr9nFUj1WuruIdNpIyJ0OmeMg82MEUodxbPNm8nKmERhyeY8PHchKSkrYuHEjhw8fBmg3iUvkcqIAKJ4XDAaZMWMGGzZs4JZbbgHcQLdhwwYWL158wfnFxcXs2bOn3bEf/OAHNDY28vOf/3zAztQd6CzLxpcxBl/GGHe7uayrMNFWnMbDcKrK3Qu3pd5diDkSdvf1TXS1dvN7XJJKezJZwAeBHBgywh3Dd0UJZIzBHpqLzxe4JNVI37j66qvZtGkTb7/9NuCOFY6PGxS5HCgAigBLly7l9ttvp6ysjJkzZ7Jy5UqampoSs4K/+tWvMmrUKH7yk5+QmppKSUlJu+uzsrIALjguvWPZAayhIwGwM67E5M7AwcY01MCZA+6yKCd2x8Jgs7tDRg+CYB9UDKS6+wZnjoP0fMieAEPH4ku7QluuDULxBaOvvvpqtm3bxuHDh5kyZUqSqxK5dBQARYAvfelLHD9+nP/+7/+mtraW6dOns379+sTEkEOHDmnWZZJYlg8rkO52vF4xBa6YgjEOzuhZOKEmd0/co5uh5RQ0vgehWs51BV9qKRDMgdRMSBsNw8ZB+ijIvBI7mK5WvcvQkCFDABg3blySKxG5tBQARWIWL17cYZcvwMaNGy967TPPPHPpC5JOWZaNLy0PX1rswIipAETCzZjTNbDjeWBPp9d38IpAAOxhkJoBqVnuGL3UPEgrgMyRkJpNIDj00t6IDBqakCOXGwVAEbls+ANpMGIK3PgQ0WgE54Md0LAfAkM5cbqV1oiPsVdNhpRhEBwK/jT8/hT9chcRz1EAFJHLks/nx1dYAVQAEKmpIdLaSiB34G5jJiLSXzSoSURERMRjFABFREREPEZdwCL96OzZswAYYzCm5zNVe3NNf4jX1dv76g/x2gZqfXGDpcaB6mI/54Fct0h/UwAU6SPGGBobGxNfv/XWW9xxxx2Au/9wIBDo1uSDUChEY2MjmZmZtLa29lW5H0k82La1tQ3YCRXhcBjHcQbsexjX0tJCMBhMdhkdikQitLW10dTUlFgnb6AxxlBfX092dvYFSzcZY4hGk7lepMjAoQAo0kcaGxsZNmxYh899/OMf5/nnnyctLa3D5zty4MABDhw4cKnK6xNvvPFGskvoUl1dXbJLuKh9+/Ylu4Qubd++PdkldGnbtm2dPmfbdmLPXxGvUgAUucTiLX/GGP75z3/y3e9+l927d/PTn/6U0tJSHMchPT2djIyMi7aWnTp1isrKSgoLCxk9evSAbVl77733OHXqFNOmTRvQi2Vv376doqKiTkP5QFBbW0tdXR3Tpk1LdimdamtrY9euXYwZM4aCgoJkl9OhaDTK/v37OXXqFJMnTyYjIyPxnDEGy7ISATC+j7eI1ygAilwi8eDX0NDQ4X7AX/nKVwB63PJ36NAhDh06dMnq7Ctbt25Ndgld2rt3b7JL6JYtW7Yku4QuDYYWaYDdu3d3+pxt2wN+SIBIX1EAFLlELtblC/CrX/2KtLS0xNZSIpJcjuOwfft2dQmLJykAinxEnXX5PvLII5SWljJ0qLt9WFddvtFolMrKSlpaWpgyZUqPWgmTobq6mqamJqZNmzZgu6fj3nvvPVpaWiguLk52KV06cOAA4XCYoqKiZJdyUfHPO8CUKVMG9GegpaWFyspKfD4fxcXFpKSkJJ6LdwGrS1i8RgFQpJe66vKdP38+0PMuX4CdO3dekhr7w+bNm5NdQrcdP3482SV020CfrHK+wfQZuNgEFnUJi5coAIr0krp8RS4v6hIWL1EAFOmhS9XlC3Dy5EkqKysZPXo0Y8aMGdDdaHFVVVWEQiFKSkoGRb2tra3s2LGDiooK/P7B8b+8vXv3MmzYsA5blgeiI0eOcOjQIT7xiU+0614dqOIz7HNzcxk3bly72evqEhavsIyWRhfplq66fON60+UrIgOPbduUlZWxfft25syZQ2pqarJLErlkFABFuqmhoaHbXb6DoWVMRLrHsixmzJjByJEj9XdbLhsKgCLddH4L4C233MLOnTvx+XwEAoHEOd395ZCSkkJmZuagmpRgWRZZWVmcOnUq2aX0SEpKCsFgsN22fINBMBgkGo0Oqq3LcnNzqa+vH3TdpkVFRbz77rud7hUciUQIh8OcOXOGzMzMfq5OpG8oAIr0guM4if1ve8oYQ1NTE+np6Ze4qr5ljKG5uTkxxnGwMMYQiUTaBfXBoK2tbVCMp/uws2fPDrrPNriTus7fMaQj3RnXKzJYKACKiIiIeMzA3bhTRERERPqEAqCIiIiIxygAiuc98cQTjB07ltTUVMrLyy+6UwDA6dOnWbRoEQUFBaSkpDBx4kTWrVvXT9WKiIh8dINjVVSRPvLCCy+wdOlSVq1aRXl5OStXrmTOnDlUVVWRm5t7wfmhUIhPf/rT5ObmsnbtWkaNGsV7771HVlZW/xcvIiLSS2oBFM964okn+OpXv0okEmHVqlWcPXuWVatWkZaWxurVqzu8ZvXq1Rw6dIh169bx6KOPMnbsWGbNmkVpaWk/Vy8iItJ7CoDiSS+88AJLliwhEomwcuVKSktLmTNnDvX19cyePZutW7d2el1jYyP5+fmsX7+ekpISHn744UG1VpuIiIgCoHjO+S1/juOQlpbWruUvLy+P2tpaAJ566imuu+46y2m1vAAAEX5JREFUsrOzycrK4h//+AehUIj09HT+7d/+jfvvv5//+Z//4cc//nGS70pERKT7FADFE+ITPQKBAIsXLyYcDvPAAw8AcM8991zQ8nfy5EmKi4u5++672b9/Pw888ADz58/Htm0cx2H69OlkZWXxpS99ie9///usWrUqmbcnIiLSIwqActmLT/RYvnw5kyZNYsKECRhjKCkpSWzldn7L3549e6iurmbBggXs3buXBQsWsGTJEtauXUtZWRm2bSdaCAEmTZpEbW0toVAoiXcpIiLSfQqActl77LHHWLhwIfPnz2ffvn1kZ2cDcOutt5KdnU1OTk6i5c8Yw9///neKioq49957ycvLo66uDsdxqK+vZ+/evUSj0XbbQb377rsUFBQQDAaTcn8iIiI9pWVg5LIWCoXYuXMn9913H/X19USjUU6cOIFlWVx11VWcPHmS6upqIpEIAHV1dbS2tjJ//nwA7rjjDnbv3o0xBmNMYv/fTZs2AeDz+cjOzmbJkiXJuUEREZFeUAugXNbioe/JJ59k/PjxABQUFJCbm8uJEyd45plnMMbw/vvv89JLLxGNRrFtm6uuugqAhoaGRNduIBAgMzOTefPmAWDbNiNHjuTb3/42y5YtS84NioiI9IICoHhCTU0N99xzDwDV1dX4fD6OHz/OBx98AEBWVhZZWVm8+eab2LbNk08+yX333cfNN9/M9OnTAQiHw2zYsIFPfepTpKSkcNNNN3H48GHuv/9+fD5fku5MRESk59QFLJetkydP8rWvfQ2Aw4cP8+qrr5KSksLVV1/NH//4R4qLi/nRj34EuOFu/fr15OXlMXz4cN58801ef/11jDGMHj0agPz8fMaOHcvnP/95Jk6cmLT7EhER+ajUAiiD3rJly7As64LHFVdcwSuvvALA9ddfT01NDZZl8Ze//AWACRMmMHfuXCzLYtmyZZSXl/OZz3yGuro6xowZw9ixY/nc5z7H0aNHARg/fjyf/vSnGT9+PH//+9/5wx/+kKxbFhER+UgUAGXQ+853vkNlZWW7x8svvwzAvHnzGDFiBP/4xz8oKyujtbWVqVOnArBu3TreeustjDFs374dgC1btjBu3Dj+9a9/kZOTw44dOxITRLZs2cKuXbt47bXX+PnPf97t+k6ePMn8+fPJzMwkKyuLBQsWJCaTdHb+N7/5TYqKihgyZAhjxozhW9/6FmfOnOntW9Qt8bUSU1NTKS8vT7wnnfnd735HcXExqampTJ06lXXr1vVpfRfTk9rPX9w7Ozub2bNnd3mvfaWn73ncmjVrsCyLW265pW8L7ERP6z59+jSLFi2ioKCAlJQUJk6cmJTPS0/rXrlyZeLvYWFhIUuWLKG1tbWfqhXpY0ZkEPre975ngIs+MjIyzEMPPWQmTpxoHn/8cVNQUGAAU1hYaLKyssyTTz5p/vznPxvAfPGLXzTHjh0zgFm4cKEJBALG5/MZy7LMlVdeaQAzZcoU09TU1ONa586da0pLS80bb7xhNm3aZK666iozb968Ts/fs2eP+c///E/z0ksvmerqarNhwwYzYcIE8/nPf/6jvGUXtWbNGhMMBs3q1avNP//5T7Nw4UKTlZVljh071uH5W7ZsMT6fzzzyyCNm37595gc/+IEJBAJmz549fVZjZ3pa+5e//GXzxBNPmLfeestUVlaaO+64wwwbNsy8//77A7ruuJqaGjNq1Chz3XXXmZtvvrl/ij1PT+tua2szZWVl5sYbbzSbN282NTU1ZuPGjWbXrl0Duu7nnnvOpKSkmOeee87U1NSYP//5z6agoMAsWbKkX+sW6SsKgDIo1dXVmcrKyk4f99xzj5kwYYJ5+umnTVZWVuK6QCBgRo8ebWzbNg899JCZMGFCIoxt3brVAMayLAMYn8/XLlBalmUqKirM0aNHzdGjR00kEumyzn379hnA7NixI3HslVdeMZZlmSNHjnT7fl988UUTDAZNOBzuwbvUfTNnzjSLFi1KfB2NRs3IkSPNT37ykw7Pv/XWW81nP/vZdsfKy8vN17/+9T6p72J6WvuHRSIRk5GRYX7961/3VYkd6k3dkUjEXHPNNeZXv/qVuf3225MSAHta9y9+8Qszbtw4EwqF+qvEDvW07kWLFplPfepT7Y4tXbrUfPKTn+zTOkX6i7qAZVCJj/fLzc1l0qRJHT4ARowYgWVZVFRUcPr0aXbu3AlAZmYmQ4YMwXEcVqxYwbXXXssvf/lLABzHAdzFoFevXs2uXbtYvXp14nsbY9i6dSsFBQUUFBRw+PDhLuvdunUrWVlZlJWVJY7Nnj0b27bZtm1bt+/7zJkzZGZm4vdf+nlb8bUSZ8+enThm23a7rfE+bOvWre3OB5gzZ06n5/eV3tT+Yc3NzYTDYYYPH95XZV6gt3U/8MAD5ObmsmDBgv4o8wK9qfull16ioqKCRYsWkZeXR0lJCQ8//DDRaLS/yu5V3ddccw07d+5MdBMfOHCAdevWceONN/ZLzSJ9TbOAZVD5zne+wx133HHRc8aNG0d+fj51dXVMmjSJuXPnsnDhQv73f/+XU6dOEQwGmTdvHs8//zwAR44coaysjBUrVgDw7LPP8pWvfAWAkpIS1q9fz4svvsjvf//7Ho+5qq2tJTc3t90xv9/P8OHD220ndzH19fU8+OCD3HXXXT363t0VXysxLy+v3fG8vDzeeeedDq+pra3t8Pzu3tOl0pvaP+x73/seI0eOvCDQ9qXe1L1582aefvppdu3a1Q8Vdqw3dR84cIC//e1vzJ8/n3Xr1lFdXc03vvENwuEwy5cv74+ye1X3l7/8Zerr67n22msxxhCJRLj77rv5r//6r/4oWaTPKQDKgHbw4EE+9rGPXXB81qxZbNy4sdPrzm/5e+6551i8eDGzZ8/GcRyuv/76RKsfuEvAVFVVMWzYMEaOHElVVVW713r33XcveP1ly5bx05/+9KK1V1ZWdnF3XWtoaOCzn/0skydP5oc//OFHfj1pb8WKFaxZs4aNGzeSmpqa7HI61djYyG233cZTTz1FTk5OssvpEcdxyM3N5Ze//CU+n48ZM2Zw5MgRHn300X4LgL2xceNGHn74YZ588knKy8uprq7m29/+Ng8++CD3339/sssT+cgUAGVAKywsTCzDAm7L0+zZs7n++usvet35LX+rVq1i0aJFvPnmm5SVlbVr+bvhhhv4zW9+gzEGgHvvvZfly5dTWlrK9OnT+fWvf80777xDdXV1YicR6HlL5PkikQgnT54kPz//otc3NjYyd+5cMjIy+P3vf08gELjo+b2Vk5ODz+fj2LFj7Y4fO3as0xrz8/N7dH5f6U3tcT/72c9YsWIFf/3rX5k2bVpflnmBnta9f/9+Dh48yE033ZQ4Fh+y4Pf7qaqqavf57Cu9eb8LCgoIBALtFkufNGkStbW1hEKhftlDuzd133///dx2222JtUSnTp1KU1MTd911F9///vexbY2gksFNn2AZ0Hw+H/n5+eTn55OVlcXdd99NRUVFt1rDnnvuOYqLi7nhhhu48cYb2433g3Mtf83NzYlj99xzD/fddx9LliyhtLSUDRs28Oqrr17wy3XEiBEUFxdf9BEMBi8Ygwjwt7/9DcdxKC8v77T2hoYG/uM//oNgMMhLL73Up61TwWCQGTNmsGHDhsQxx3HYsGEDFRUVHV5TUVHR7nyAV199tdPz+0pvagd45JFHePDBB1m/fn278Zn9pad1FxcXs2fPHnbt2pV4fO5zn+Pf//3f2bVrF4WFhQOyboBPfvKTVFdXJwIruK3qBQUF/RL+oHd1Nzc3XxDy4iE2/g9GkUEtqVNQRHpg3rx5ZvLkyaahoSHZpfTI3Llzzcc//nGzbds2s3nz5nYzj40x5v333zdFRUVm27Ztxhhjzpw5Y8rLy83UqVNNdXV1YtZxd2ce98aaNWtMSkqKeeaZZ8y+ffvMXXfdZbKyskxtba0xxpjbbrvNLFu2LHH+li1bjN/vNz/72c9MZWWlWb58eVKXgelJ7StWrDDBYNCsXbu23Xvb2Ng4oOv+sGTNAu5p3YcOHTIZGRlm8eLFpqqqyrz88ssmNzfX/PjHPx7QdS9fvtxkZGSY3/72t+bAgQPmL3/5ixk/fry59dZb+7Vukb6iACiDwoMPPmiGDx9uqqurk11Kj504ccLMmzfPpKenm8zMTHPnnXe2Cxs1NTUGMK+99poxxpjXXnut07UNa2pq+qzOxx9/3IwZM8YEg0Ezc+ZM88YbbySemzVrlrn99tvbnf/iiy+aiRMnmmAwaKZMmWL+9Kc/9VltXelJ7fF1HT/8WL58+YCu+8OSFQCN6Xndr7/+uikvLzcpKSlm3Lhx5qGHHuqzf8xcTE/qDofD5oc//KEZP368SU1NNYWFheYb3/iGOXXqVL/XLdIXLGPUli0D2//93/8xb948XnnlFW644YZklyMiIjLoKQDKgLZ3717Ky8tZunQpixYtShwPBoP9um6biIjI5UQBUAa0Z555hjvvvPOC410tAyMiIiKdUwAUERER8RgtAyMiIiLiMQqAIiIXcfz4cfLz83n44YcTx15//XWCweAFayGKiAwW6gIWEenCunXruOWWW3j99dcpKipi+vTp3HzzzTz22GPJLk1EpFcUAEVEumHRokX89a9/paysjD179rBjxw5SUlKSXZaISK8oAIqIdENLSwslJSUcPnyYnTt3MnXq1GSXJCLSaxoDKCLSDfv37+eDDz7AcRwOHjyY7HJERD4StQCKiHQhFAoxc+ZMpk+fTlFREStXrmTPnj3k5uYmuzQRkV5RABQR6cK9997L2rVrefvtt0lPT2fWrFkMGzaMl19+OdmliYj0irqARUQuYuPGjaxcuZJnn32WzMxMbNvm2WefZdOmTfziF79IdnkiIr2iFkARERERj1ELoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeIwCoIiIiIjHKACKiIiIeMz/Az2FGtaM/PYNAAAAAElFTkSuQmCC",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_distance = plt.figure() #dpi=300)\n",
    "ax_distance = fig_distance.add_subplot(111, projection='3d')\n",
    "\n",
    "############################\n",
    "\n",
    "_gradual = False   #whether to gradually draw reach envelope lines\n",
    "\n",
    "############################\n",
    "\n",
    "ax_distance.clear()\n",
    "\n",
    "ax_distance.view_init(elev=0, azim=-90)\n",
    "#ax_distance.view_init(elev=-180, azim=-135)\n",
    "ax_distance.set_xlabel('x')\n",
    "ax_distance.set_ylabel('z')\n",
    "ax_distance.set_zlabel('y')\n",
    "\n",
    "distance_test = pd.read_csv(table_filename, index_col=0)\n",
    "\n",
    "#transfer reach envelope from MuJoCo to global Unity coordinates\n",
    "distance_test_unity = distance_test.copy()\n",
    "distance_test_unity.loc[:, \"end-effector_xpos_x\":\"end-effector_xpos_z\"] = np.array(distance_test_unity.apply(lambda x: np.array(list(test_env.task._transform_to_unity(x.loc[\"end-effector_xpos_x\":\"end-effector_xpos_z\"].values, test_env._data.body(\"controller-right\").xquat, apply_offset=True)[0].values())), axis=1).tolist())\n",
    "# ax_distance.invert_yaxis()\n",
    "\n",
    "# ax_distance.scatter(distance_test_unity[\"end-effector_xpos_x\"], distance_test_unity[\"end-effector_xpos_z\"], distance_test_unity[\"end-effector_xpos_y\"], c=\"#eda840\", s=0.8, alpha=0.2)\n",
    "if _gradual:\n",
    "    distance_lines, = ax_distance.plot(distance_test_unity[\"end-effector_xpos_x\"], distance_test_unity[\"end-effector_xpos_z\"], distance_test_unity[\"end-effector_xpos_y\"], c=\"#eda840\", alpha=0.2)\n",
    "else:\n",
    "    ax_distance.scatter(distance_test_unity[\"end-effector_xpos_x\"], distance_test_unity[\"end-effector_xpos_z\"], distance_test_unity[\"end-effector_xpos_y\"], c=\"#eda840\", s=0.8, alpha=0.2)\n",
    "\n",
    "#plot shoulder\n",
    "_shoulder_unity = np.array(list(test_env.task._transform_to_unity(test_env._data.body(\"clavicle\").xpos, test_env._data.body(\"clavicle\").xquat, apply_offset=True)[0].values()))\n",
    "# ax_distance.scatter(*_shoulder_unity, marker=\"x\", c=\"black\", s=100)\n",
    "ax_distance.scatter(_shoulder_unity[0], _shoulder_unity[2], _shoulder_unity[1], marker=\"x\", c=\"black\", s=100)\n",
    "\n",
    "# ax_distance.set_title(\"BioCheck: Reach Envelope\\n(MoblArmsWrist, Whac-a-mole)\")\n",
    "# ax_distance.set_yticklabels([])\n",
    "# ax_distance.grid(False)\n",
    "\n",
    "## plot targets from VR Application in global Unity coordinates\n",
    "_color_list = [\"#119bf4\", \"#8cda31\", \"#ff00ff\"]\n",
    "for _idx, _task_condition in enumerate(_target_info[\"task_condition\"].unique()):\n",
    "    _target_info_selected = _target_info[_target_info[\"task_condition\"] == _task_condition]\n",
    "    # ax_distance.scatter(_target_info_selected[\"global_x\"], _target_info_selected[\"global_y\"], _target_info_selected[\"global_z\"], label=_task_condition.lstrip('0123456789-').capitalize().split(\"-\")[0], c=_color_list[_idx])\n",
    "    ax_distance.scatter(_target_info_selected[\"global_x\"], _target_info_selected[\"global_z\"], _target_info_selected[\"global_y\"], label=_task_condition.lstrip('0123456789-').capitalize().split(\"-\")[0], c=_color_list[_idx])\n",
    "ax_distance.legend() #loc=\"right\")  #loc=3)\n",
    "fig_distance.savefig(figure_filename)\n",
    "\n",
    "## 3D rotation animation\n",
    "def init():\n",
    "    ax_distance.clear()\n",
    "    ax_distance.view_init(elev=10., azim=0)\n",
    "    \n",
    "    ax_distance.set_xlabel('x')\n",
    "    ax_distance.set_ylabel('z')\n",
    "    ax_distance.set_zlabel('y')\n",
    "    \n",
    "    if _gradual:\n",
    "        global distance_lines\n",
    "        distance_lines, = ax_distance.plot(distance_test_unity[\"end-effector_xpos_x\"], distance_test_unity[\"end-effector_xpos_z\"], distance_test_unity[\"end-effector_xpos_y\"], c=\"#eda840\", alpha=0.2)\n",
    "    else:\n",
    "        ax_distance.scatter(distance_test_unity[\"end-effector_xpos_x\"], distance_test_unity[\"end-effector_xpos_z\"], distance_test_unity[\"end-effector_xpos_y\"], c=\"#eda840\", s=0.8, alpha=0.2)\n",
    "\n",
    "    #plot shoulder\n",
    "    _shoulder_unity = np.array(list(test_env.task._transform_to_unity(test_env._data.body(\"clavicle\").xpos, test_env._data.body(\"clavicle\").xquat, apply_offset=True)[0].values()))\n",
    "    ax_distance.scatter(_shoulder_unity[0], _shoulder_unity[2], _shoulder_unity[1], marker=\"x\", c=\"black\", s=100)\n",
    "\n",
    "    for _idx, _task_condition in enumerate(_target_info[\"task_condition\"].unique()):\n",
    "        _target_info_selected = _target_info[_target_info[\"task_condition\"] == _task_condition]\n",
    "        ax_distance.scatter(_target_info_selected[\"global_x\"], _target_info_selected[\"global_z\"], _target_info_selected[\"global_y\"], label=_task_condition.lstrip('0123456789-').capitalize().split(\"-\")[0], c=_color_list[_idx])\n",
    "    ax_distance.legend()\n",
    "\n",
    "    return fig_distance,\n",
    "\n",
    "n_frames = 360\n",
    "def animate(i):\n",
    "    if _gradual:\n",
    "        distance_lines.set_data(distance_test_unity[\"end-effector_xpos_x\"][:int(distance_test_unity.shape[0]*i/n_frames)], distance_test_unity[\"end-effector_xpos_z\"][:int(distance_test_unity.shape[0]*i/n_frames)],)\n",
    "        distance_lines.set_3d_properties(distance_test_unity[\"end-effector_xpos_y\"][:int(distance_test_unity.shape[0]*i/n_frames)])\n",
    "\n",
    "    ax_distance.view_init(elev=10., azim=i)\n",
    "    return fig_distance,\n",
    "\n",
    "\n",
    "# Animate\n",
    "anim = animation.FuncAnimation(fig_distance, animate, init_func=init,\n",
    "                               frames=n_frames, interval=20, blit=True)\n",
    "\n",
    "# ## target region (from SciRep RL paper)\n",
    "\n",
    "# gphi = np.random.uniform(low=-1.57079633, high=0.698132, size=100000)\n",
    "# #gphi = np.random.uniform(low=-1.57079633, high=-0.0872665, size=100000)\n",
    "# gtheta = np.random.uniform(low=0, high=3.14159265, size=100000)\n",
    "# gr = np.random.uniform(low=0.2, high=0.735, size=100000)  #high=0.735\n",
    "# #ax_distance.scatter(gr*np.cos(gphi)*np.sin(gtheta), gr*np.sin(gphi)*np.sin(gtheta), gr*np.cos(gtheta), s=0.8)\n",
    "# ax_distance.scatter(gr*np.cos(gphi)*np.sin(gtheta), gr*np.cos(gtheta), -gr*np.sin(gphi)*np.sin(gtheta), s=0.1, alpha=0.1)\n",
    "\n",
    "# ## \"random_v2\":\n",
    "\n",
    "# thorax_offset = np.array([0.02153019919, 0.00858509793, -0.20849523568])  #for unscaled model: np.array([0.017555, 0.007, -0.17])\n",
    "\n",
    "# general_thorax_area = np.array([[-0.11157193, -0.32303762, -0.37799819], [0.12484449, 0.05684561, -0.03899228]])\n",
    "# general_thorax_threshold = np.array([[-0.1, -2, -0.1], [0.1, 0.3, 0.1]])\n",
    "# general_target_area = np.array([[0, -1, general_thorax_area[:, 2].mean()], [1, 1, 1]])\n",
    "\n",
    "# nsamples_randomv2 = 10000\n",
    "# new_target = np.zeros((nsamples_randomv2,3))\n",
    "# for i in range(nsamples_randomv2):\n",
    "#     draw_new_target = True\n",
    "#     while draw_new_target:\n",
    "#         new_target[i] = np.random.uniform(low=general_target_area[0], high=general_target_area[1], size=3)\n",
    "#         if (np.linalg.norm(new_target[i]) <= 0.735 + 0.05) & ((new_target[i] < (general_thorax_area[0] + general_thorax_threshold[0])) |\n",
    "#                 (new_target[i] > (general_thorax_area[1] + general_thorax_threshold[1]))).any():\n",
    "#             draw_new_target = False\n",
    "            \n",
    "# ax_distance.scatter(new_target[:, 0], new_target[:, 1], new_target[:, 2], s=0.1, alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8d9e4457",
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31mThe Kernel crashed while executing code in the the current cell or a previous cell. Please review the code in the cell(s) to identify a possible cause of the failure. Click <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. View Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
     ]
    }
   ],
   "source": [
    "anim.save(f'uitb-vr_biocheck_animation{\"_gradual\" if _gradual else \"\"}.mp4', fps=30, extra_args=['-vcodec', 'libx264'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c5209e7-03aa-48d9-961b-60a399163159",
   "metadata": {},
   "outputs": [],
   "source": [
    "#env.bm_model._effort_model._MA"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "12548be1",
   "metadata": {},
   "source": [
    "### Store policy params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60438d3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempting to connect to Unity app on port 35161\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "Policy: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v110l/checkpoints/model_15000000_steps.zip\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<stable_baselines3.ppo.ppo.PPO at 0x7fd9f8f64310>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v110l\"\n",
    "env = uitb.Simulator.get(simulator_dir, run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=True)\n",
    "_checkpoint_dir = f\"{simulator_dir}/checkpoints\"  #checkpoints_20230508_175546\n",
    "# _policy_path = os.path.join(_checkpoint_dir, \"model_100000000_steps\")\n",
    "_policy_path = os.path.join(_checkpoint_dir, natural_sort(os.listdir(_checkpoint_dir))[-1])\n",
    "_policy = PPO.load(_policy_path)  #use latest policy\n",
    "print(f\"Policy: {_policy_path}\")\n",
    "_policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7b972468",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/ True\n",
      "/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/ READ True\n",
      "/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/ WRITE True\n"
     ]
    }
   ],
   "source": [
    "dir_to_check = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/\"\n",
    "print(dir_to_check + \" \" + str(os.path.exists(dir_to_check)))\n",
    "print(dir_to_check + \" READ \" + str(os.access(dir_to_check, os.R_OK)))\n",
    "print(dir_to_check + \" WRITE \" + str(os.access(dir_to_check, os.W_OK)))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "433d3558",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New policy filename: /home/florian/uitb-sim2vr/user-in-the-box-private/uitb/rl/sb3/policies/unity_random_3ccr_1e1_v110l/parameters-15mil.npy\n"
     ]
    }
   ],
   "source": [
    "_policy_filepath = f'/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/rl/sb3/policies/{simulator_dir.split(\"/\")[-1]}'\n",
    "os.popen(f\"mkdir -p {_policy_filepath}\").read()\n",
    "_policy_filename = f\"parameters-{_policy_path.split('000000_steps')[0].split('_')[-1]}mil.npy\"\n",
    "_new_policy_path = os.path.join(_policy_filepath, _policy_filename)\n",
    "print(f\"New policy filename: {_new_policy_path}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f0b8f483",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(_new_policy_path, _policy.policy.parameters_to_vector())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3c909404",
   "metadata": {},
   "source": [
    "### Evaluations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1d51473c",
   "metadata": {},
   "outputs": [],
   "source": [
    "## UPDATE DEBUGGING SIMULATOR\n",
    "# simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_whacamole_DEBUG.yaml\")\n",
    "# simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_beatsvr_DEBUG.yaml\")\n",
    "simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_beatsvr_bimanual_DEBUG.yaml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a1a0522f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_low_easy_TEST.yaml\")\n",
    "#simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_high_easy_3CCr_0_v111.yaml\")\n",
    "# simulator_dir = uitb.Simulator.build(\"/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/configs/mobl_arms_unity_beatsvr_1e3.yaml\")\n",
    "\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115\"\n",
    "simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_beatsvr_1e3\"\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "abe66df5-5523-465a-bc96-15311ac4aca8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempting to connect to Unity app on port 54489\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "Load PPO policy /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_beatsvr_1e3/checkpoints/model_15000000_steps.zip.\n"
     ]
    }
   ],
   "source": [
    "# if not \"env\" in locals():\n",
    "#     env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\n",
    "# env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\n",
    "# env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_low_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=True)\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_easy\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_difficulty_easy_cumulativefatigue_v2\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/test_unity_difficulty_easy_3ccr\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_high_difficulty_easy_3ccr_0_10s\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_difficulty_easy\"\n",
    "\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_beatsvr_test\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_low_difficulty_easy_test\"\n",
    "\n",
    "env = uitb.Simulator.get(simulator_dir, run_parameters={\"action_sample_freq\": 20,\"evaluate\": True}, render_mode=\"rgb_array_list\", use_cloned=False)\n",
    "\n",
    "# ## TEST with different effort model:\n",
    "from uitb.bm_models.effort_models import CumulativeFatigue3CCr, ConsumedEndurance\n",
    "# env.bm_model._effort_model = CumulativeFatigue3CCr(env.bm_model, dt=env._run_parameters[\"dt\"])  #env.bm_model.get_effort_model({\"cls\": \"CumulativeFatigue3CCr\"}, dt=env._run_parameters[\"dt\"])\n",
    "log_variables = {\n",
    "                # \"3CCr_MA\": (\"bm_model\", \"_effort_model\", \"_MA\"),   #TODO: store in info returned by simulator.step()\n",
    "                # \"3CCr_MR\": (\"bm_model\", \"_effort_model\", \"_MR\"),\n",
    "                # \"3CCr_MF\": (\"bm_model\", \"_effort_model\", \"_MF\"),\n",
    "                # \"effort_cost\": (\"bm_model\", \"_effort_model\", \"_effort_cost\")\n",
    "                }\n",
    "# env.bm_model._effort_model = ConsumedEndurance(env.bm_model, dt=env._run_parameters[\"dt\"])  #env.bm_model.get_effort_model({\"cls\": \"ConsumedEndurance\"}, dt=env._run_parameters[\"dt\"])\n",
    "# log_variables = {\"endurance\": (\"bm_model\", \"_effort_model\", \"_endurance\"),\n",
    "#                 \"consumed_endurance\": (\"bm_model\", \"_effort_model\", \"_consumed_endurance\"),\n",
    "#                 \"act\": (\"_data\", \"act\"),\n",
    "#                 \"effort_cost\": (\"bm_model\", \"_effort_model\", \"_effort_cost\")}\n",
    "\n",
    "USE_POLICY = True\n",
    "\n",
    "# Number of steps you run the agent for \n",
    "num_steps = 5000\n",
    "\n",
    "#############################################################\n",
    "\n",
    "\n",
    "# Reset with some seed for debugging purposes\n",
    "# obs = env.reset()\n",
    "obs, info = env.reset()\n",
    "\n",
    "# Create instance for variables that should be additionally logged\n",
    "eval_logs = EvaluationLogs(env, log_variables)\n",
    "\n",
    "# Create empty list which all frames of the forward simulation will be appended to\n",
    "frame_collection = []\n",
    "\n",
    "# Create list which all rewards of the forward simulation will be appended to\n",
    "reward_collection = [np.nan]  #no reward available at initial state\n",
    "\n",
    "# obs_collection = [obs]\n",
    "obs_collection = defaultdict(list)\n",
    "for k, v in obs.items():\n",
    "    obs_collection[k].append(v)\n",
    "\n",
    "action_collection = []\n",
    "info_collection = defaultdict(list)\n",
    "\n",
    "if USE_POLICY:\n",
    "    _checkpoint_dir = f\"{simulator_dir}/checkpoints\"  #checkpoints_20230508_175546\n",
    "    # _policy_path = os.path.join(_checkpoint_dir, \"model_100000000_steps\")\n",
    "    _policy_path = os.path.join(_checkpoint_dir, natural_sort(os.listdir(_checkpoint_dir))[-1])  #use latest policy\n",
    "    print(f\"Load PPO policy {_policy_path}.\")\n",
    "\n",
    "    _policy = PPO.load(_policy_path)\n",
    "else:\n",
    "    _policy = None\n",
    "\n",
    "for step in range(num_steps):\n",
    "    if _policy is not None:\n",
    "        # get actions from policy\n",
    "        action, _internal_policy_state = _policy.predict(obs, deterministic=True)\n",
    "    else:\n",
    "        # choose random action from action space\n",
    "        action = env.action_space.sample()    \n",
    "    \n",
    "    # apply the action\n",
    "    # obs, reward, done, info = env.step(action)\n",
    "    obs, reward, terminated, truncated, info = env.step(action)\n",
    "    \n",
    "    # store received reward\n",
    "    reward_collection.append(reward)\n",
    "    \n",
    "    for k, v in obs.items():\n",
    "        obs_collection[k].append(v)\n",
    "    action_collection.append(action)\n",
    "    for k, v in info.items():\n",
    "        info_collection[k].append(v)\n",
    "    \n",
    "    # log additional variables\n",
    "    eval_logs.log()\n",
    "    \n",
    "    # If the epsiode is up, then stop\n",
    "    # if done:\n",
    "    if terminated or truncated:\n",
    "        frame_collection.extend(env.render()) #with render_mode=\"rgb_array_list\", env.render() returns a list of all frames since last call of reset()\n",
    "        break\n",
    "\n",
    "# Also store remaining frames of unfinished last episode\n",
    "frame_collection.extend(env.render())\n",
    "\n",
    "# Close the env\n",
    "env.close()\n",
    "\n",
    "# Show all simulated frames\n",
    "# display_video(frame_collection, framerate=env.fps)\n",
    "#display_video_with_rewards(frame_collection, reward_collection, framerate=env.fps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "25ef98fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1991.9222242105125"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(reward_collection[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "7c22ace4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(np.diff(info_collection[\"Points\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "179c76d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "AAKsAAADhAAAA+cAAAJAAAACegAAAkAAAAJuAAACNgAAAV8AAAIbAAAB6wAAAVcAAAJBAAACFgAA\n",
       "AcEAAAFcAAABqgAAAXAAAAE/AAABeQAAATAAAAEqAACzIQAAA5gAAAK/AAACZAAAAWMAAAERAAAA\n",
       "YQAAAaQAAAC8AAAApgAAADwAAAAUc3RjbwAAAAAAAAABAAAAMAAAAGJ1ZHRhAAAAWm1ldGEAAAAA\n",
       "AAAAIWhkbHIAAAAAAAAAAG1kaXJhcHBsAAAAAAAAAAAAAAAALWlsc3QAAAAlqXRvbwAAAB1kYXRh\n",
       "AAAAAQAAAABMYXZmNTguNzYuMTAw\n",
       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display_video(frame_collection, framerate=env.fps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0878fcdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1406.7753888200969"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#reward_collection[1:][np.argmax(reward_collection[1:])]\n",
    "sum(reward_collection[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2559fc03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.3917467476000605"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(eval_logs.get_logs(\"effort_cost\").values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9f843391",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/build.x86_64'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[38], line 11\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39m# if not \"env\" in locals():\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[39m#     env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[39m# env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[39m# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/test_unity_difficulty_easy_3ccr\"\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[39m# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_high_difficulty_easy_3ccr\"\u001b[39;00m\n\u001b[1;32m      9\u001b[0m simulator_dir \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_difficulty_easy\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m---> 11\u001b[0m env \u001b[39m=\u001b[39m uitb\u001b[39m.\u001b[39;49mSimulator\u001b[39m.\u001b[39;49mget(simulator_dir, run_parameters\u001b[39m=\u001b[39;49m{\u001b[39m\"\u001b[39;49m\u001b[39maction_sample_freq\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39m20\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mevaluate\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mTrue\u001b[39;49;00m}, use_cloned\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n\u001b[1;32m     13\u001b[0m \u001b[39m# ## TEST with different effort model:\u001b[39;00m\n\u001b[1;32m     14\u001b[0m \u001b[39m# from uitb.bm_models.effort_models import CumulativeFatigue3CCr, ConsumedEndurance\u001b[39;00m\n\u001b[1;32m     15\u001b[0m \u001b[39m# env.bm_model._effort_model = CumulativeFatigue3CCr(env.bm_model, dt=env._run_parameters[\"dt\"])  #env.bm_model.get_effort_model({\"cls\": \"CumulativeFatigue3CCr\"}, dt=env._run_parameters[\"dt\"])\u001b[39;00m\n\u001b[1;32m     16\u001b[0m log_variables \u001b[39m=\u001b[39m {\n\u001b[1;32m     17\u001b[0m                 \u001b[39m# \"3CCr_MA\": (\"bm_model\", \"_effort_model\", \"_MA\"), \u001b[39;00m\n\u001b[1;32m     18\u001b[0m                 \u001b[39m# \"3CCr_MR\": (\"bm_model\", \"_effort_model\", \"_MR\"),\u001b[39;00m\n\u001b[1;32m     19\u001b[0m                 \u001b[39m# \"3CCr_MF\": (\"bm_model\", \"_effort_model\", \"_MF\"),\u001b[39;00m\n\u001b[1;32m     20\u001b[0m                 \u001b[39m# \"effort_cost\": (\"bm_model\", \"_effort_model\", \"_effort_cost\")\u001b[39;00m\n\u001b[1;32m     21\u001b[0m                 }\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:310\u001b[0m, in \u001b[0;36mSimulator.get\u001b[0;34m(cls, simulator_folder, render_mode, render_show_depths, run_parameters, use_cloned)\u001b[0m\n\u001b[1;32m    308\u001b[0m   _simulator \u001b[39m=\u001b[39m gen_cls(simulator_folder, run_parameters\u001b[39m=\u001b[39mrun_parameters)\n\u001b[1;32m    309\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 310\u001b[0m   _simulator \u001b[39m=\u001b[39m gen_cls(simulator_folder, render_mode\u001b[39m=\u001b[39;49mrender_mode, render_show_depths\u001b[39m=\u001b[39;49mrender_show_depths,\n\u001b[1;32m    311\u001b[0m                       run_parameters\u001b[39m=\u001b[39;49mrun_parameters)\n\u001b[1;32m    313\u001b[0m \u001b[39m# Return Simulator object\u001b[39;00m\n\u001b[1;32m    314\u001b[0m \u001b[39mreturn\u001b[39;00m _simulator\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:345\u001b[0m, in \u001b[0;36mSimulator.__init__\u001b[0;34m(self, simulator_folder, render_mode, render_show_depths, run_parameters)\u001b[0m\n\u001b[1;32m    341\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_run_parameters\u001b[39m.\u001b[39mupdate(run_parameters \u001b[39mor\u001b[39;00m {})\n\u001b[1;32m    343\u001b[0m \u001b[39m# Initialise simulation\u001b[39;00m\n\u001b[1;32m    344\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_model, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_data, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtask, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbm_model, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mperception, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcallbacks \u001b[39m=\u001b[39m \\\n\u001b[0;32m--> 345\u001b[0m   \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_initialise(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_config, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_simulator_folder, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_run_parameters)\n\u001b[1;32m    347\u001b[0m \u001b[39m# Set action space TODO for now we assume all actuators have control signals between [-1, 1]\u001b[39;00m\n\u001b[1;32m    348\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39maction_space \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_initialise_action_space()\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/simulator.py:247\u001b[0m, in \u001b[0;36mSimulator._initialise\u001b[0;34m(cls, config, simulator_folder, run_parameters)\u001b[0m\n\u001b[1;32m    243\u001b[0m   callbacks[cb[\u001b[39m\"\u001b[39m\u001b[39mname\u001b[39m\u001b[39m\"\u001b[39m]] \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mget_class(cb[\u001b[39m\"\u001b[39m\u001b[39mcls\u001b[39m\u001b[39m\"\u001b[39m])(cb[\u001b[39m\"\u001b[39m\u001b[39mname\u001b[39m\u001b[39m\"\u001b[39m], \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcb[\u001b[39m\"\u001b[39m\u001b[39mkwargs\u001b[39m\u001b[39m\"\u001b[39m])\n\u001b[1;32m    245\u001b[0m \u001b[39m# Now initialise the actual classes; model and data are input to the inits so that stuff can be modified if needed\u001b[39;00m\n\u001b[1;32m    246\u001b[0m \u001b[39m# (e.g. move target to a specific position wrt to a body part)\u001b[39;00m\n\u001b[0;32m--> 247\u001b[0m task \u001b[39m=\u001b[39m task_cls(model, data, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49m{\u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mtask_kwargs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mcallbacks, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mrun_parameters})\n\u001b[1;32m    248\u001b[0m bm_model \u001b[39m=\u001b[39m bm_cls(model, data, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39m{\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mbm_kwargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcallbacks, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mrun_parameters})\n\u001b[1;32m    249\u001b[0m perception \u001b[39m=\u001b[39m Perception(model, data, bm_model, perception_modules, {\u001b[39m*\u001b[39m\u001b[39m*\u001b[39mcallbacks, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mrun_parameters})\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/base.py:64\u001b[0m, in \u001b[0;36mBaseTask.__init_subclass__.<locals>.init_with_hook\u001b[0;34m(self, model, data, init, **init_kwargs)\u001b[0m\n\u001b[1;32m     63\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39minit_with_hook\u001b[39m(\u001b[39mself\u001b[39m, model, data, init\u001b[39m=\u001b[39m\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__init__\u001b[39m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39minit_kwargs):\n\u001b[0;32m---> 64\u001b[0m   init(\u001b[39mself\u001b[39;49m, model, data, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49minit_kwargs)\n\u001b[1;32m     66\u001b[0m   \u001b[39m# Set stateful information shape\u001b[39;00m\n\u001b[1;32m     67\u001b[0m   \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stateful_information_shape \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mget_stateful_information(model, data)\u001b[39m.\u001b[39mshape\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/Unity.py:54\u001b[0m, in \u001b[0;36mUnity.__init__\u001b[0;34m(self, model, data, gear, left_controller_enabled, **kwargs)\u001b[0m\n\u001b[1;32m     51\u001b[0m   app_args\u001b[39m.\u001b[39mextend([\u001b[39m\"\u001b[39m\u001b[39m-fixedSeed\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mkwargs[\u001b[39m'\u001b[39m\u001b[39munity_random_seed\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m])\n\u001b[1;32m     53\u001b[0m \u001b[39m# Start a Unity client\u001b[39;00m\n\u001b[0;32m---> 54\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_unity_client \u001b[39m=\u001b[39m UnityClient(unity_executable\u001b[39m=\u001b[39;49mapp_path,\n\u001b[1;32m     55\u001b[0m                                  port\u001b[39m=\u001b[39;49mkwargs\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mport\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m     56\u001b[0m                                  standalone\u001b[39m=\u001b[39;49mkwargs\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mstandalone\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mTrue\u001b[39;49;00m),\n\u001b[1;32m     57\u001b[0m                                  app_args\u001b[39m=\u001b[39;49mkwargs\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mapp_args\u001b[39;49m\u001b[39m\"\u001b[39;49m, []))\n\u001b[1;32m     59\u001b[0m \u001b[39m# Wait until app is up and running. Send time options to unity app\u001b[39;00m\n\u001b[1;32m     60\u001b[0m time_options \u001b[39m=\u001b[39m {\u001b[39m\"\u001b[39m\u001b[39mtimestep\u001b[39m\u001b[39m\"\u001b[39m: model\u001b[39m.\u001b[39mopt\u001b[39m.\u001b[39mtimestep, \u001b[39m\"\u001b[39m\u001b[39msampleFrequency\u001b[39m\u001b[39m\"\u001b[39m: kwargs[\u001b[39m\"\u001b[39m\u001b[39maction_sample_freq\u001b[39m\u001b[39m\"\u001b[39m],\n\u001b[1;32m     61\u001b[0m                 \u001b[39m\"\u001b[39m\u001b[39mtimeScale\u001b[39m\u001b[39m\"\u001b[39m: kwargs[\u001b[39m\"\u001b[39m\u001b[39mtime_scale\u001b[39m\u001b[39m\"\u001b[39m]}\n",
      "File \u001b[0;32m~/uitb-sim2vr/user-in-the-box-private/uitb/utils/unity.py:44\u001b[0m, in \u001b[0;36mUnityClient.__init__\u001b[0;34m(self, unity_executable, port, standalone, app_args)\u001b[0m\n\u001b[1;32m     41\u001b[0m   os\u001b[39m.\u001b[39mmakedirs(log_path, exist_ok\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n\u001b[1;32m     43\u001b[0m   \u001b[39m# Open the app\u001b[39;00m\n\u001b[0;32m---> 44\u001b[0m   \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_app \u001b[39m=\u001b[39m subprocess\u001b[39m.\u001b[39;49mPopen([unity_executable,\n\u001b[1;32m     45\u001b[0m                                 \u001b[39m'\u001b[39;49m\u001b[39m-simulated\u001b[39;49m\u001b[39m'\u001b[39;49m,\n\u001b[1;32m     46\u001b[0m                                 \u001b[39m'\u001b[39;49m\u001b[39m-port\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39mf\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39m{\u001b[39;49;00m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mport\u001b[39m}\u001b[39;49;00m\u001b[39m'\u001b[39;49m,\n\u001b[1;32m     47\u001b[0m                                 \u001b[39m'\u001b[39;49m\u001b[39m-logFile\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39mf\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39m{\u001b[39;49;00mos\u001b[39m.\u001b[39;49mpath\u001b[39m.\u001b[39;49mjoin(log_path,\u001b[39m \u001b[39;49mlog_name)\u001b[39m}\u001b[39;49;00m\u001b[39m'\u001b[39;49m] \u001b[39m+\u001b[39;49m app_args, env\u001b[39m=\u001b[39;49menv_with_display)\n\u001b[1;32m     49\u001b[0m \u001b[39m# Create zmq client\u001b[39;00m\n\u001b[1;32m     50\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_context \u001b[39m=\u001b[39m zmq\u001b[39m.\u001b[39mContext()\n",
      "File \u001b[0;32m/opt/conda/envs/uitb_gymnasium/lib/python3.11/subprocess.py:1024\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize, process_group)\u001b[0m\n\u001b[1;32m   1020\u001b[0m         \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtext_mode:\n\u001b[1;32m   1021\u001b[0m             \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstderr \u001b[39m=\u001b[39m io\u001b[39m.\u001b[39mTextIOWrapper(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstderr,\n\u001b[1;32m   1022\u001b[0m                     encoding\u001b[39m=\u001b[39mencoding, errors\u001b[39m=\u001b[39merrors)\n\u001b[0;32m-> 1024\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_execute_child(args, executable, preexec_fn, close_fds,\n\u001b[1;32m   1025\u001b[0m                         pass_fds, cwd, env,\n\u001b[1;32m   1026\u001b[0m                         startupinfo, creationflags, shell,\n\u001b[1;32m   1027\u001b[0m                         p2cread, p2cwrite,\n\u001b[1;32m   1028\u001b[0m                         c2pread, c2pwrite,\n\u001b[1;32m   1029\u001b[0m                         errread, errwrite,\n\u001b[1;32m   1030\u001b[0m                         restore_signals,\n\u001b[1;32m   1031\u001b[0m                         gid, gids, uid, umask,\n\u001b[1;32m   1032\u001b[0m                         start_new_session, process_group)\n\u001b[1;32m   1033\u001b[0m \u001b[39mexcept\u001b[39;00m:\n\u001b[1;32m   1034\u001b[0m     \u001b[39m# Cleanup if the child failed starting.\u001b[39;00m\n\u001b[1;32m   1035\u001b[0m     \u001b[39mfor\u001b[39;00m f \u001b[39min\u001b[39;00m \u001b[39mfilter\u001b[39m(\u001b[39mNone\u001b[39;00m, (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdin, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstdout, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstderr)):\n",
      "File \u001b[0;32m/opt/conda/envs/uitb_gymnasium/lib/python3.11/subprocess.py:1917\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, gid, gids, uid, umask, start_new_session, process_group)\u001b[0m\n\u001b[1;32m   1915\u001b[0m     \u001b[39mif\u001b[39;00m errno_num \u001b[39m!=\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[1;32m   1916\u001b[0m         err_msg \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39mstrerror(errno_num)\n\u001b[0;32m-> 1917\u001b[0m     \u001b[39mraise\u001b[39;00m child_exception_type(errno_num, err_msg, err_filename)\n\u001b[1;32m   1918\u001b[0m \u001b[39mraise\u001b[39;00m child_exception_type(err_msg)\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/home/florian/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/build.x86_64'"
     ]
    }
   ],
   "source": [
    "# # if not \"env\" in locals():\n",
    "# #     env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\n",
    "# # env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_hard_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, render_mode=\"rgb_array_list\", render_show_depths=False, use_cloned=True)\n",
    "# # env = uitb.Simulator.get(\"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_low_pretrained\", run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=True)\n",
    "# # simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/trained/unity_easy\"\n",
    "# # simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_difficulty_easy_cumulativefatigue_v2\"\n",
    "# # simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/test_unity_difficulty_easy_3ccr\"\n",
    "# # simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_high_difficulty_easy_3ccr\"\n",
    "# simulator_dir = \"/home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_difficulty_easy\"\n",
    "\n",
    "# env = uitb.Simulator.get(simulator_dir, run_parameters={\"action_sample_freq\": 20, \"evaluate\": True}, use_cloned=False)\n",
    "\n",
    "# # ## TEST with different effort model:\n",
    "# # from uitb.bm_models.effort_models import CumulativeFatigue3CCr, ConsumedEndurance\n",
    "# # env.bm_model._effort_model = CumulativeFatigue3CCr(env.bm_model, dt=env._run_parameters[\"dt\"])  #env.bm_model.get_effort_model({\"cls\": \"CumulativeFatigue3CCr\"}, dt=env._run_parameters[\"dt\"])\n",
    "# log_variables = {\n",
    "#                 # \"3CCr_MA\": (\"bm_model\", \"_effort_model\", \"_MA\"), \n",
    "#                 # \"3CCr_MR\": (\"bm_model\", \"_effort_model\", \"_MR\"),\n",
    "#                 # \"3CCr_MF\": (\"bm_model\", \"_effort_model\", \"_MF\"),\n",
    "#                 # \"effort_cost\": (\"bm_model\", \"_effort_model\", \"_effort_cost\")\n",
    "#                 }\n",
    "\n",
    "# USE_POLICY = False\n",
    "\n",
    "# # Number of steps you run the agent for \n",
    "# num_steps = 50#00\n",
    "\n",
    "# #############################################################\n",
    "\n",
    "\n",
    "# # Reset with some seed for debugging purposes\n",
    "# # obs = env.reset()\n",
    "# obs, info = env.reset()\n",
    "\n",
    "# # Create instance for variables that should be additionally logged\n",
    "# eval_logs = EvaluationLogs(env, log_variables)\n",
    "\n",
    "# # Create empty list which all frames of the forward simulation will be appended to\n",
    "# frame_collection = []\n",
    "\n",
    "# # Create list which all rewards of the forward simulation will be appended to\n",
    "# reward_collection = [np.nan]  #no reward available at initial state\n",
    "\n",
    "# obs_collection = [obs]\n",
    "# info_collection = []\n",
    "\n",
    "# if USE_POLICY:\n",
    "#     _checkpoint_dir = f\"{simulator_dir}/checkpoints\"  #checkpoints_20230508_175546\n",
    "#     # _policy = PPO.load(os.path.join(_checkpoint_dir, \"model_100000000_steps\"))\n",
    "#     _policy = PPO.load(os.path.join(_checkpoint_dir, natural_sort(os.listdir(_checkpoint_dir))[-1]))  #use latest policy\n",
    "# else:\n",
    "#     _policy = None\n",
    "\n",
    "# for step in range(num_steps):\n",
    "#     if _policy is not None:\n",
    "#         # get actions from policy\n",
    "#         action, _internal_policy_state = _policy.predict(obs, deterministic=True)\n",
    "#     else:\n",
    "#         # choose random action from action space\n",
    "#         action = env.action_space.sample()    \n",
    "    \n",
    "#     # apply the action\n",
    "#     # obs, reward, done, info = env.step(action)\n",
    "#     obs, reward, terminated, truncated, info = env.step(action)\n",
    "    \n",
    "#     # store received reward\n",
    "#     reward_collection.append(reward)\n",
    "    \n",
    "#     obs_collection.append(obs)\n",
    "#     info_collection.append(info)\n",
    "    \n",
    "#     # log additional variables\n",
    "#     eval_logs.log()\n",
    "    \n",
    "#     # If the epsiode is up, then stop\n",
    "#     # if done:\n",
    "#     if terminated or truncated:\n",
    "#         # frame_collection.extend(env.render()) #with render_mode=\"rgb_array_list\", env.render() returns a list of all frames since last call of reset()\n",
    "#         break\n",
    "\n",
    "# # Close the env\n",
    "# env.close()\n",
    "\n",
    "# # Also store remaining frames of unfinished last episode\n",
    "# # frame_collection.extend(env.render())\n",
    "\n",
    "# # Show all simulated frames\n",
    "# # display_video(frame_collection, framerate=env.fps)\n",
    "# #display_video_with_rewards(frame_collection, reward_collection, framerate=env.fps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35552398-15fc-44e2-a157-c4d5533fcb49",
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_logs.get_logs(\"effort_cost\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34bcd019-1c43-4dfa-a3e0-0a43b5bb5e80",
   "metadata": {},
   "outputs": [],
   "source": [
    "lifting_muscles = [\"DELT1\", \"DELT2\", \"DELT3\", \"SUPSP\", \"INFSP\", \"SUBSC\", \"TMIN\", \"BIClong\", \"BICshort\", \"TRIlong\", \"TRIlat\", \"TRImed\"]  #muscles of the mobl_arms_wrist that act on the shoulder\n",
    "lifting_indices = [env._model.actuator(_i).id for _i in lifting_muscles]\n",
    "\n",
    "_logdata = eval_logs.get_logs(\"3CCr_MF\", indices=lifting_indices)\n",
    "\n",
    "plt.plot(_logdata.keys(), _logdata.values(), label=lifting_muscles)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "188eaf7b-48f3-4303-995e-929287c04420",
   "metadata": {},
   "outputs": [],
   "source": [
    "lifting_muscles = [\"DELT1\", \"DELT2\", \"DELT3\", \"SUPSP\", \"INFSP\", \"SUBSC\", \"TMIN\", \"BIClong\", \"BICshort\", \"TRIlong\", \"TRIlat\", \"TRImed\"]  #muscles of the mobl_arms_wrist that act on the shoulder\n",
    "lifting_indices = [env._model.actuator(_i).id for _i in lifting_muscles]\n",
    "\n",
    "_logdata = eval_logs.get_logs(\"3CCr_MA\", indices=lifting_indices)\n",
    "\n",
    "plt.plot(_logdata.keys(), _logdata.values(), label=lifting_muscles)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "489359de-4440-46e8-8178-fd86b8675a70",
   "metadata": {},
   "outputs": [],
   "source": [
    "#display_video([(np.concatenate((np.moveaxis(i[\"vision\"], 0, 2), 0*np.ones((80, 120, 1))), axis=-1)[..., [0, 2, 1]]/2 + 0.5) for i in obs_collection], framerate=100)\n",
    "display_video([i[\"unity_image\"] for i in info_collection], framerate=100)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e0b23bfc-cd0a-4aba-8163-478ecb744088",
   "metadata": {},
   "source": [
    "## Run Evaluations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "512d29f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "TASK CONDITION: simulators/unity_random_3ccr_1e1_v115\n",
      "\n",
      "APP CONDITION: easy\n",
      "\n",
      "Attempting to connect to Unity app on port 56695\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connection confirmed\n",
      "run parameters are: {'dt': 0.05, 'frame_skip': 25, 'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'unity_record_gameplay': True, 'action_sample_freq': 20, 'unity_logging': True, 'evaluate': True, 'app_args': ['-condition', 'easy', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'rendering_context': <uitb.utils.rendering.Context object at 0x7f522af9b390>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x555eb7059540] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x555eb7059540] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x555eb7059540] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=173 q=-1.0 Lsize=    3648kB time=00:00:59.90 bitrate= 498.9kbits/s speed=8.61x    \n",
      "video:3637kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.299096%\n",
      "[libx264 @ 0x555eb7059540] frame I:6     Avg QP: 3.55  size: 35831\n",
      "[libx264 @ 0x555eb7059540] frame P:828   Avg QP:13.07  size:  3683\n",
      "[libx264 @ 0x555eb7059540] frame B:367   Avg QP:13.90  size:  1253\n",
      "[libx264 @ 0x555eb7059540] consecutive B-frames: 53.0% 15.8%  8.5% 22.6%\n",
      "[libx264 @ 0x555eb7059540] mb I  I16..4: 57.0% 25.4% 17.6%\n",
      "[libx264 @ 0x555eb7059540] mb P  I16..4:  0.2%  0.7%  1.2%  P16..4:  1.2%  0.1%  0.1%  0.0%  0.0%    skip:96.5%\n",
      "[libx264 @ 0x555eb7059540] mb B  I16..4:  0.0%  0.0%  0.2%  B16..8:  3.1%  0.4%  0.1%  direct: 0.0%  skip:96.1%  L0:59.0% L1:40.5% BI: 0.5%\n",
      "[libx264 @ 0x555eb7059540] 8x8 transform intra:31.0% inter:29.0%\n",
      "[libx264 @ 0x555eb7059540] coded y,uvDC,uvAC intra: 52.4% 63.3% 57.7% inter: 0.2% 0.3% 0.2%\n",
      "[libx264 @ 0x555eb7059540] i16 v,h,dc,p: 64% 27%  1%  9%\n",
      "[libx264 @ 0x555eb7059540] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu:  7% 29% 47%  2%  3%  3%  3%  2%  4%\n",
      "[libx264 @ 0x555eb7059540] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 27% 19%  5%  6%  7%  7%  4%  5%\n",
      "[libx264 @ 0x555eb7059540] i8c dc,h,v,p: 56% 25% 12%  8%\n",
      "[libx264 @ 0x555eb7059540] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x555eb7059540] ref P L0: 25.4%  6.9% 58.6%  9.0%\n",
      "[libx264 @ 0x555eb7059540] ref B L0: 69.2% 30.0%  0.8%\n",
      "[libx264 @ 0x555eb7059540] ref B L1: 99.9%  0.1%\n",
      "[libx264 @ 0x555eb7059540] kb/s:496.10\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x555dc7757180] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x555dc7757180] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x555dc7757180] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=163 q=-1.0 Lsize=    5503kB time=00:00:59.95 bitrate= 752.0kbits/s speed=8.12x    \n",
      "video:5491kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.218399%\n",
      "[libx264 @ 0x555dc7757180] frame I:6     Avg QP: 3.99  size: 36031\n",
      "[libx264 @ 0x555dc7757180] frame P:688   Avg QP:12.22  size:  7147\n",
      "[libx264 @ 0x555dc7757180] frame B:508   Avg QP:15.80  size:   962\n",
      "[libx264 @ 0x555dc7757180] consecutive B-frames: 39.9%  7.2% 12.7% 40.3%\n",
      "[libx264 @ 0x555dc7757180] mb I  I16..4: 52.1% 25.0% 22.8%\n",
      "[libx264 @ 0x555dc7757180] mb P  I16..4:  0.5%  2.6%  2.6%  P16..4:  3.1%  0.3%  0.3%  0.0%  0.0%    skip:90.7%\n",
      "[libx264 @ 0x555dc7757180] mb B  I16..4:  0.0%  0.0%  0.1%  B16..8:  1.9%  0.2%  0.1%  direct: 0.2%  skip:97.4%  L0:49.0% L1:47.9% BI: 3.1%\n",
      "[libx264 @ 0x555dc7757180] 8x8 transform intra:42.5% inter:30.1%\n",
      "[libx264 @ 0x555dc7757180] coded y,uvDC,uvAC intra: 46.2% 60.7% 52.3% inter: 0.3% 0.8% 0.6%\n",
      "[libx264 @ 0x555dc7757180] i16 v,h,dc,p: 67% 17%  2% 14%\n",
      "[libx264 @ 0x555dc7757180] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 10% 17% 50%  4%  3%  1%  7%  4%  3%\n",
      "[libx264 @ 0x555dc7757180] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 21% 26% 20%  5%  6%  3% 10%  4%  3%\n",
      "[libx264 @ 0x555dc7757180] i8c dc,h,v,p: 59% 23% 10%  7%\n",
      "[libx264 @ 0x555dc7757180] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x555dc7757180] ref P L0: 27.3%  4.3% 62.4%  6.0%\n",
      "[libx264 @ 0x555dc7757180] ref B L0: 74.3% 19.8%  5.8%\n",
      "[libx264 @ 0x555dc7757180] ref B L1: 98.9%  1.1%\n",
      "[libx264 @ 0x555dc7757180] kb/s:748.36\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695061680/20-28-00-easy successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n",
      "APP CONDITION: medium\n",
      "\n",
      "Attempting to connect to Unity app on port 39365\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "run parameters are: {'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'dt': 0.05, 'unity_logging': True, 'evaluate': True, 'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'app_args': ['-condition', 'medium', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'action_sample_freq': 20, 'unity_record_gameplay': True, 'frame_skip': 25, 'rendering_context': <uitb.utils.rendering.Context object at 0x7f14063a3990>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x556080a36540] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x556080a36540] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x556080a36540] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=175 q=-1.0 Lsize=    4523kB time=00:00:59.90 bitrate= 618.6kbits/s speed=8.73x    \n",
      "video:4512kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.243272%\n",
      "[libx264 @ 0x556080a36540] frame I:5     Avg QP: 3.68  size: 37637\n",
      "[libx264 @ 0x556080a36540] frame P:825   Avg QP:13.70  size:  4626\n",
      "[libx264 @ 0x556080a36540] frame B:371   Avg QP:15.15  size:  1658\n",
      "[libx264 @ 0x556080a36540] consecutive B-frames: 52.0% 17.5%  8.5% 22.0%\n",
      "[libx264 @ 0x556080a36540] mb I  I16..4: 55.7% 26.5% 17.8%\n",
      "[libx264 @ 0x556080a36540] mb P  I16..4:  0.2%  0.7%  1.3%  P16..4:  1.5%  0.2%  0.2%  0.0%  0.0%    skip:95.9%\n",
      "[libx264 @ 0x556080a36540] mb B  I16..4:  0.0%  0.1%  0.2%  B16..8:  3.2%  0.4%  0.2%  direct: 0.1%  skip:95.9%  L0:57.2% L1:41.9% BI: 0.9%\n",
      "[libx264 @ 0x556080a36540] 8x8 transform intra:30.1% inter:31.9%\n",
      "[libx264 @ 0x556080a36540] coded y,uvDC,uvAC intra: 53.5% 65.4% 59.2% inter: 0.4% 0.7% 0.5%\n",
      "[libx264 @ 0x556080a36540] i16 v,h,dc,p: 62% 27%  1% 10%\n",
      "[libx264 @ 0x556080a36540] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu:  8% 30% 45%  2%  3%  4%  3%  2%  4%\n",
      "[libx264 @ 0x556080a36540] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 20% 26% 20%  4%  7%  7%  7%  4%  5%\n",
      "[libx264 @ 0x556080a36540] i8c dc,h,v,p: 54% 25% 13%  8%\n",
      "[libx264 @ 0x556080a36540] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x556080a36540] ref P L0: 33.4% 12.7% 45.3%  8.5%\n",
      "[libx264 @ 0x556080a36540] ref B L0: 68.4% 30.5%  1.1%\n",
      "[libx264 @ 0x556080a36540] ref B L1: 99.7%  0.3%\n",
      "[libx264 @ 0x556080a36540] kb/s:615.44\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x55e3fe0d1cc0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x55e3fe0d1cc0] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x55e3fe0d1cc0] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=159 q=-1.0 Lsize=    7941kB time=00:00:59.95 bitrate=1085.1kbits/s speed=7.95x    \n",
      "video:7929kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.149519%\n",
      "[libx264 @ 0x55e3fe0d1cc0] frame I:7     Avg QP: 4.44  size: 41049\n",
      "[libx264 @ 0x55e3fe0d1cc0] frame P:723   Avg QP:12.74  size:  9440\n",
      "[libx264 @ 0x55e3fe0d1cc0] frame B:472   Avg QP:17.39  size:  2132\n",
      "[libx264 @ 0x55e3fe0d1cc0] consecutive B-frames: 40.9% 15.1% 15.0% 29.0%\n",
      "[libx264 @ 0x55e3fe0d1cc0] mb I  I16..4: 56.1% 20.6% 23.3%\n",
      "[libx264 @ 0x55e3fe0d1cc0] mb P  I16..4:  0.7%  2.5%  2.8%  P16..4:  3.5%  0.5%  0.5%  0.0%  0.0%    skip:89.4%\n",
      "[libx264 @ 0x55e3fe0d1cc0] mb B  I16..4:  0.1%  0.1%  0.2%  B16..8:  2.3%  0.4%  0.3%  direct: 0.5%  skip:96.1%  L0:49.8% L1:44.8% BI: 5.4%\n",
      "[libx264 @ 0x55e3fe0d1cc0] 8x8 transform intra:38.2% inter:28.2%\n",
      "[libx264 @ 0x55e3fe0d1cc0] coded y,uvDC,uvAC intra: 46.0% 62.8% 53.4% inter: 0.8% 1.6% 1.4%\n",
      "[libx264 @ 0x55e3fe0d1cc0] i16 v,h,dc,p: 62% 17%  2% 20%\n",
      "[libx264 @ 0x55e3fe0d1cc0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 13% 18% 44%  4%  4%  2%  7%  4%  4%\n",
      "[libx264 @ 0x55e3fe0d1cc0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 21% 26% 21%  5%  7%  4%  9%  4%  3%\n",
      "[libx264 @ 0x55e3fe0d1cc0] i8c dc,h,v,p: 58% 24% 11%  8%\n",
      "[libx264 @ 0x55e3fe0d1cc0] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x55e3fe0d1cc0] ref P L0: 33.7% 10.8% 48.5%  7.0%\n",
      "[libx264 @ 0x55e3fe0d1cc0] ref B L0: 75.8% 20.1%  4.0%\n",
      "[libx264 @ 0x55e3fe0d1cc0] ref B L1: 98.6%  1.4%\n",
      "[libx264 @ 0x55e3fe0d1cc0] kb/s:1080.69\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695061838/20-30-38-medium successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n",
      "APP CONDITION: hard\n",
      "\n",
      "Attempting to connect to Unity app on port 35725\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "run parameters are: {'frame_skip': 25, 'unity_record_gameplay': True, 'unity_logging': True, 'evaluate': True, 'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'dt': 0.05, 'action_sample_freq': 20, 'app_args': ['-condition', 'hard', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'rendering_context': <uitb.utils.rendering.Context object at 0x7f21bc589ed0>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x55c9b9681540] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x55c9b9681540] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x55c9b9681540] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=174 q=-1.0 Lsize=    5176kB time=00:00:59.90 bitrate= 707.9kbits/s speed=8.69x    \n",
      "video:5165kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.212671%\n",
      "[libx264 @ 0x55c9b9681540] frame I:5     Avg QP: 3.59  size: 38175\n",
      "[libx264 @ 0x55c9b9681540] frame P:820   Avg QP:14.19  size:  5202\n",
      "[libx264 @ 0x55c9b9681540] frame B:376   Avg QP:15.60  size:  2213\n",
      "[libx264 @ 0x55c9b9681540] consecutive B-frames: 51.4% 16.2% 13.5% 19.0%\n",
      "[libx264 @ 0x55c9b9681540] mb I  I16..4: 55.5% 26.9% 17.6%\n",
      "[libx264 @ 0x55c9b9681540] mb P  I16..4:  0.2%  0.8%  1.3%  P16..4:  1.7%  0.2%  0.2%  0.0%  0.0%    skip:95.6%\n",
      "[libx264 @ 0x55c9b9681540] mb B  I16..4:  0.0%  0.1%  0.4%  B16..8:  3.4%  0.5%  0.2%  direct: 0.1%  skip:95.5%  L0:54.1% L1:45.1% BI: 0.9%\n",
      "[libx264 @ 0x55c9b9681540] 8x8 transform intra:30.7% inter:32.6%\n",
      "[libx264 @ 0x55c9b9681540] coded y,uvDC,uvAC intra: 53.6% 65.7% 59.7% inter: 0.5% 0.9% 0.8%\n",
      "[libx264 @ 0x55c9b9681540] i16 v,h,dc,p: 60% 28%  1% 10%\n",
      "[libx264 @ 0x55c9b9681540] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu:  9% 27% 47%  2%  3%  4%  3%  2%  3%\n",
      "[libx264 @ 0x55c9b9681540] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 20% 25% 20%  4%  7%  7%  7%  4%  5%\n",
      "[libx264 @ 0x55c9b9681540] i8c dc,h,v,p: 54% 25% 13%  8%\n",
      "[libx264 @ 0x55c9b9681540] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x55c9b9681540] ref P L0: 35.9% 17.4% 38.1%  8.7%\n",
      "[libx264 @ 0x55c9b9681540] ref B L0: 73.9% 24.0%  2.0%\n",
      "[libx264 @ 0x55c9b9681540] ref B L1: 99.7%  0.3%\n",
      "[libx264 @ 0x55c9b9681540] kb/s:704.51\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x558fd79a6cc0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x558fd79a6cc0] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x558fd79a6cc0] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=155 q=-1.0 Lsize=    9728kB time=00:00:59.95 bitrate=1329.3kbits/s speed=7.74x    \n",
      "video:9717kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.115821%\n",
      "[libx264 @ 0x558fd79a6cc0] frame I:6     Avg QP: 4.62  size: 41565\n",
      "[libx264 @ 0x558fd79a6cc0] frame P:792   Avg QP:13.48  size: 10829\n",
      "[libx264 @ 0x558fd79a6cc0] frame B:404   Avg QP:17.91  size:  2781\n",
      "[libx264 @ 0x558fd79a6cc0] consecutive B-frames: 46.8% 19.5% 17.5% 16.3%\n",
      "[libx264 @ 0x558fd79a6cc0] mb I  I16..4: 53.0% 24.1% 23.0%\n",
      "[libx264 @ 0x558fd79a6cc0] mb P  I16..4:  0.7%  2.6%  2.9%  P16..4:  3.7%  0.7%  0.7%  0.0%  0.0%    skip:88.6%\n",
      "[libx264 @ 0x558fd79a6cc0] mb B  I16..4:  0.1%  0.1%  0.3%  B16..8:  2.7%  0.5%  0.4%  direct: 0.8%  skip:95.1%  L0:50.3% L1:43.3% BI: 6.4%\n",
      "[libx264 @ 0x558fd79a6cc0] 8x8 transform intra:39.8% inter:28.6%\n",
      "[libx264 @ 0x558fd79a6cc0] coded y,uvDC,uvAC intra: 46.6% 64.7% 54.1% inter: 1.2% 2.2% 1.9%\n",
      "[libx264 @ 0x558fd79a6cc0] i16 v,h,dc,p: 51% 18%  2% 28%\n",
      "[libx264 @ 0x558fd79a6cc0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 13% 20% 44%  4%  5%  2%  6%  3%  4%\n",
      "[libx264 @ 0x558fd79a6cc0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 21% 25% 21%  5%  7%  5%  8%  4%  4%\n",
      "[libx264 @ 0x558fd79a6cc0] i8c dc,h,v,p: 57% 24% 12%  8%\n",
      "[libx264 @ 0x558fd79a6cc0] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x558fd79a6cc0] ref P L0: 36.9% 14.6% 40.5%  8.1%\n",
      "[libx264 @ 0x558fd79a6cc0] ref B L0: 77.2% 19.4%  3.5%\n",
      "[libx264 @ 0x558fd79a6cc0] ref B L1: 98.8%  1.2%\n",
      "[libx264 @ 0x558fd79a6cc0] kb/s:1324.34\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695061997/20-33-17-hard successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n",
      "APP CONDITION: low-medium\n",
      "\n",
      "Attempting to connect to Unity app on port 54783\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "run parameters are: {'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'unity_record_gameplay': True, 'dt': 0.05, 'evaluate': True, 'frame_skip': 25, 'action_sample_freq': 20, 'unity_logging': True, 'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'app_args': ['-condition', 'low-medium', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'rendering_context': <uitb.utils.rendering.Context object at 0x7fd09d2ffb10>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x563c5f585000] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x563c5f585000] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x563c5f585000] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=182 q=-1.0 Lsize=    5940kB time=00:00:59.90 bitrate= 812.4kbits/s speed=9.08x    \n",
      "video:5928kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.206115%\n",
      "[libx264 @ 0x563c5f585000] frame I:6     Avg QP: 3.54  size: 41026\n",
      "[libx264 @ 0x563c5f585000] frame P:706   Avg QP:13.76  size:  5474\n",
      "[libx264 @ 0x563c5f585000] frame B:489   Avg QP:17.27  size:  4005\n",
      "[libx264 @ 0x563c5f585000] consecutive B-frames: 33.5% 27.3% 28.2% 11.0%\n",
      "[libx264 @ 0x563c5f585000] mb I  I16..4: 57.8% 23.6% 18.7%\n",
      "[libx264 @ 0x563c5f585000] mb P  I16..4:  0.1%  0.5%  1.4%  P16..4:  1.8%  0.3%  0.3%  0.0%  0.0%    skip:95.6%\n",
      "[libx264 @ 0x563c5f585000] mb B  I16..4:  0.0%  0.1%  0.7%  B16..8:  4.1%  0.7%  0.4%  direct: 0.1%  skip:93.8%  L0:50.5% L1:48.5% BI: 1.0%\n",
      "[libx264 @ 0x563c5f585000] 8x8 transform intra:23.0% inter:25.1%\n",
      "[libx264 @ 0x563c5f585000] coded y,uvDC,uvAC intra: 61.3% 74.7% 69.2% inter: 0.7% 0.9% 0.6%\n",
      "[libx264 @ 0x563c5f585000] i16 v,h,dc,p: 55% 34%  1%  9%\n",
      "[libx264 @ 0x563c5f585000] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 12% 37% 26%  4%  3%  5%  2%  7%  4%\n",
      "[libx264 @ 0x563c5f585000] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 25% 21%  6%  6%  8%  5%  6%  5%\n",
      "[libx264 @ 0x563c5f585000] i8c dc,h,v,p: 48% 28% 14% 10%\n",
      "[libx264 @ 0x563c5f585000] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x563c5f585000] ref P L0: 35.3% 10.5% 37.8% 16.4%\n",
      "[libx264 @ 0x563c5f585000] ref B L0: 62.7% 26.8% 10.5%\n",
      "[libx264 @ 0x563c5f585000] ref B L1: 99.2%  0.8%\n",
      "[libx264 @ 0x563c5f585000] kb/s:808.62\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x5569ca14d640] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x5569ca14d640] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x5569ca14d640] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=142 q=-1.0 Lsize=   11463kB time=00:00:59.95 bitrate=1566.3kbits/s speed=7.08x    \n",
      "video:11452kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.094043%\n",
      "[libx264 @ 0x5569ca14d640] frame I:23    Avg QP: 5.08  size: 21991\n",
      "[libx264 @ 0x5569ca14d640] frame P:896   Avg QP:15.46  size: 10368\n",
      "[libx264 @ 0x5569ca14d640] frame B:283   Avg QP:18.96  size:  6821\n",
      "[libx264 @ 0x5569ca14d640] consecutive B-frames: 57.7% 28.1% 13.5%  0.7%\n",
      "[libx264 @ 0x5569ca14d640] mb I  I16..4: 62.2% 31.2%  6.6%\n",
      "[libx264 @ 0x5569ca14d640] mb P  I16..4:  1.0%  3.6%  2.7%  P16..4:  2.0%  0.8%  0.6%  0.0%  0.0%    skip:89.3%\n",
      "[libx264 @ 0x5569ca14d640] mb B  I16..4:  0.2%  1.0%  1.4%  B16..8:  3.0%  1.2%  0.7%  direct: 0.6%  skip:91.9%  L0:52.0% L1:45.2% BI: 2.8%\n",
      "[libx264 @ 0x5569ca14d640] 8x8 transform intra:44.1% inter:28.0%\n",
      "[libx264 @ 0x5569ca14d640] coded y,uvDC,uvAC intra: 38.1% 49.2% 44.3% inter: 1.3% 1.9% 1.4%\n",
      "[libx264 @ 0x5569ca14d640] i16 v,h,dc,p: 79% 15%  1%  5%\n",
      "[libx264 @ 0x5569ca14d640] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 11% 24% 41%  6%  2%  2%  2%  2% 10%\n",
      "[libx264 @ 0x5569ca14d640] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 21% 19% 25%  6%  7%  8%  5%  3%  5%\n",
      "[libx264 @ 0x5569ca14d640] i8c dc,h,v,p: 66% 18%  9%  7%\n",
      "[libx264 @ 0x5569ca14d640] Weighted P-Frames: Y:0.2% UV:0.1%\n",
      "[libx264 @ 0x5569ca14d640] ref P L0: 55.9% 14.2% 21.0%  8.9%  0.0%\n",
      "[libx264 @ 0x5569ca14d640] ref B L0: 80.3% 17.8%  1.9%\n",
      "[libx264 @ 0x5569ca14d640] ref B L1: 100.0%  0.0%\n",
      "[libx264 @ 0x5569ca14d640] kb/s:1560.85\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695062159/20-35-59-low-medium successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n",
      "APP CONDITION: medium\n",
      "\n",
      "Attempting to connect to Unity app on port 38285\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "run parameters are: {'unity_logging': True, 'evaluate': True, 'unity_record_gameplay': True, 'app_args': ['-condition', 'medium', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'dt': 0.05, 'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'action_sample_freq': 20, 'frame_skip': 25, 'rendering_context': <uitb.utils.rendering.Context object at 0x7f1b6a558810>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x564688d99000] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x564688d99000] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x564688d99000] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=181 q=-1.0 Lsize=    4562kB time=00:00:59.90 bitrate= 623.9kbits/s speed=9.02x    \n",
      "video:4551kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.241718%\n",
      "[libx264 @ 0x564688d99000] frame I:5     Avg QP: 3.93  size: 37209\n",
      "[libx264 @ 0x564688d99000] frame P:824   Avg QP:13.87  size:  4623\n",
      "[libx264 @ 0x564688d99000] frame B:372   Avg QP:15.08  size:  1785\n",
      "[libx264 @ 0x564688d99000] consecutive B-frames: 52.0% 17.2%  9.2% 21.6%\n",
      "[libx264 @ 0x564688d99000] mb I  I16..4: 56.7% 25.8% 17.5%\n",
      "[libx264 @ 0x564688d99000] mb P  I16..4:  0.2%  0.7%  1.3%  P16..4:  1.5%  0.2%  0.2%  0.0%  0.0%    skip:95.9%\n",
      "[libx264 @ 0x564688d99000] mb B  I16..4:  0.0%  0.1%  0.3%  B16..8:  3.3%  0.4%  0.2%  direct: 0.1%  skip:95.8%  L0:57.8% L1:41.3% BI: 0.8%\n",
      "[libx264 @ 0x564688d99000] 8x8 transform intra:30.6% inter:31.2%\n",
      "[libx264 @ 0x564688d99000] coded y,uvDC,uvAC intra: 53.3% 65.2% 59.2% inter: 0.4% 0.7% 0.6%\n",
      "[libx264 @ 0x564688d99000] i16 v,h,dc,p: 62% 27%  1% 10%\n",
      "[libx264 @ 0x564688d99000] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu:  9% 28% 46%  2%  3%  3%  3%  2%  4%\n",
      "[libx264 @ 0x564688d99000] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 20% 26% 20%  5%  7%  7%  7%  4%  5%\n",
      "[libx264 @ 0x564688d99000] i8c dc,h,v,p: 55% 25% 13%  8%\n",
      "[libx264 @ 0x564688d99000] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x564688d99000] ref P L0: 33.6% 12.8% 45.1%  8.6%\n",
      "[libx264 @ 0x564688d99000] ref B L0: 71.8% 26.9%  1.3%\n",
      "[libx264 @ 0x564688d99000] ref B L1: 99.7%  0.3%\n",
      "[libx264 @ 0x564688d99000] kb/s:620.72\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x5626722c3cc0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x5626722c3cc0] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x5626722c3cc0] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=153 q=-1.0 Lsize=    8050kB time=00:00:59.95 bitrate=1100.1kbits/s speed=7.65x    \n",
      "video:8039kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.146657%\n",
      "[libx264 @ 0x5626722c3cc0] frame I:8     Avg QP: 4.50  size: 42002\n",
      "[libx264 @ 0x5626722c3cc0] frame P:739   Avg QP:13.00  size:  9307\n",
      "[libx264 @ 0x5626722c3cc0] frame B:455   Avg QP:16.98  size:  2235\n",
      "[libx264 @ 0x5626722c3cc0] consecutive B-frames: 42.3% 16.6% 14.7% 26.3%\n",
      "[libx264 @ 0x5626722c3cc0] mb I  I16..4: 50.5% 26.9% 22.6%\n",
      "[libx264 @ 0x5626722c3cc0] mb P  I16..4:  0.7%  2.5%  2.7%  P16..4:  3.4%  0.5%  0.5%  0.0%  0.0%    skip:89.6%\n",
      "[libx264 @ 0x5626722c3cc0] mb B  I16..4:  0.1%  0.1%  0.2%  B16..8:  2.3%  0.4%  0.3%  direct: 0.6%  skip:96.0%  L0:51.9% L1:43.0% BI: 5.1%\n",
      "[libx264 @ 0x5626722c3cc0] 8x8 transform intra:39.2% inter:27.8%\n",
      "[libx264 @ 0x5626722c3cc0] coded y,uvDC,uvAC intra: 45.8% 62.6% 53.3% inter: 0.8% 1.6% 1.4%\n",
      "[libx264 @ 0x5626722c3cc0] i16 v,h,dc,p: 60% 18%  2% 20%\n",
      "[libx264 @ 0x5626722c3cc0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 12% 19% 45%  4%  4%  2%  6%  3%  4%\n",
      "[libx264 @ 0x5626722c3cc0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 21% 26% 21%  5%  7%  4%  9%  4%  3%\n",
      "[libx264 @ 0x5626722c3cc0] i8c dc,h,v,p: 58% 24% 11%  8%\n",
      "[libx264 @ 0x5626722c3cc0] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x5626722c3cc0] ref P L0: 34.4% 11.1% 47.9%  6.6%\n",
      "[libx264 @ 0x5626722c3cc0] ref B L0: 76.6% 19.7%  3.8%\n",
      "[libx264 @ 0x5626722c3cc0] ref B L1: 98.8%  1.2%\n",
      "[libx264 @ 0x5626722c3cc0] kb/s:1095.61\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695062317/20-38-37-medium successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n",
      "APP CONDITION: high-medium\n",
      "\n",
      "Attempting to connect to Unity app on port 44669\n",
      "[UnityMemory] Configuration Parameters - Can be set up in boot.config\n",
      "    \"memorysetup-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-main-allocator-block-size=16777216\"\n",
      "    \"memorysetup-gfx-thread-allocator-block-size=16777216\"\n",
      "    \"memorysetup-cache-allocator-block-size=4194304\"\n",
      "    \"memorysetup-typetree-allocator-block-size=2097152\"\n",
      "    \"memorysetup-profiler-bucket-allocator-granularity=16\"\n",
      "    \"memorysetup-profiler-bucket-allocator-bucket-count=8\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-size=4194304\"\n",
      "    \"memorysetup-profiler-bucket-allocator-block-count=1\"\n",
      "    \"memorysetup-profiler-allocator-block-size=16777216\"\n",
      "    \"memorysetup-profiler-editor-allocator-block-size=1048576\"\n",
      "    \"memorysetup-temp-allocator-size-main=4194304\"\n",
      "    \"memorysetup-job-temp-allocator-block-size=2097152\"\n",
      "    \"memorysetup-job-temp-allocator-block-size-background=1048576\"\n",
      "    \"memorysetup-job-temp-allocator-reduction-small-platforms=262144\"\n",
      "    \"memorysetup-temp-allocator-size-background-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-job-worker=262144\"\n",
      "    \"memorysetup-temp-allocator-size-preload-manager=262144\"\n",
      "    \"memorysetup-temp-allocator-size-nav-mesh-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-audio-worker=65536\"\n",
      "    \"memorysetup-temp-allocator-size-cloud-worker=32768\"\n",
      "    \"memorysetup-temp-allocator-size-gfx=262144\"\n",
      "Connection confirmed\n",
      "run parameters are: {'unity_logging': True, 'app_args': ['-condition', 'high-medium', '-outputFolder', 'simulators/unity_random_3ccr_1e1_v115/evaluate', '-record', '-resolution', '1280x960', '-logging'], 'evaluate': True, 'info_keywords': [['Points', 'final'], ['RewardUnsuccessfulContact', 'sum'], ['DistanceReward', 'sum'], ['EffortCost', 'sum'], ['failrateTarget0', 'final'], ['failrateTarget1', 'final'], ['failrateTarget2', 'final'], ['failrateTarget3', 'final'], ['failrateTarget4', 'final'], ['failrateTarget5', 'final'], ['failrateTarget6', 'final'], ['failrateTarget7', 'final'], ['failrateTarget8', 'final']], 'frame_skip': 25, 'unity_record_gameplay': True, 'unity_output_folder': 'simulators/unity_random_3ccr_1e1_v115/evaluate', 'dt': 0.05, 'action_sample_freq': 20, 'rendering_context': <uitb.utils.rendering.Context object at 0x7f515227cb10>}\n",
      "Loading model: simulators/unity_random_3ccr_1e1_v115/checkpoints/model_100000000_steps.zip\n",
      "\n",
      "Run episode 1/1.\n",
      "Log files have been saved files simulators/unity_random_3ccr_1e1_v115/evaluate/state_log.pickle and simulators/unity_random_3ccr_1e1_v115/evaluate/action_log.pickle\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate.mp4\n",
      "A recording has been saved to file simulators/unity_random_3ccr_1e1_v115/evaluate/evaluate_vision-UnityHeadset.mp4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera/image%d.png':\n",
      "  Duration: 00:01:00.05, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x5630cb9b7000] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x5630cb9b7000] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x5630cb9b7000] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/envCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1201 fps=169 q=-1.0 Lsize=    7112kB time=00:00:59.90 bitrate= 972.6kbits/s speed=8.43x    \n",
      "video:7102kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.139429%\n",
      "[libx264 @ 0x5630cb9b7000] frame I:6     Avg QP: 4.06  size: 40214\n",
      "[libx264 @ 0x5630cb9b7000] frame P:994   Avg QP:13.87  size:  6037\n",
      "[libx264 @ 0x5630cb9b7000] frame B:201   Avg QP:15.67  size:  5125\n",
      "[libx264 @ 0x5630cb9b7000] consecutive B-frames: 67.2% 31.1%  1.0%  0.7%\n",
      "[libx264 @ 0x5630cb9b7000] mb I  I16..4: 54.6% 25.6% 19.8%\n",
      "[libx264 @ 0x5630cb9b7000] mb P  I16..4:  0.1%  1.7%  1.7%  P16..4:  1.9%  0.4%  0.4%  0.0%  0.0%    skip:93.8%\n",
      "[libx264 @ 0x5630cb9b7000] mb B  I16..4:  0.1%  0.5%  1.3%  B16..8:  6.7%  0.8%  0.3%  direct: 0.1%  skip:90.2%  L0:24.3% L1:75.1% BI: 0.6%\n",
      "[libx264 @ 0x5630cb9b7000] 8x8 transform intra:42.5% inter:26.4%\n",
      "[libx264 @ 0x5630cb9b7000] coded y,uvDC,uvAC intra: 53.0% 64.3% 57.5% inter: 0.7% 0.9% 0.6%\n",
      "[libx264 @ 0x5630cb9b7000] i16 v,h,dc,p: 57% 32%  2%  9%\n",
      "[libx264 @ 0x5630cb9b7000] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 18% 18% 39%  7%  1%  1%  1%  9%  5%\n",
      "[libx264 @ 0x5630cb9b7000] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 19% 23% 22%  8%  6%  6%  7%  6%  5%\n",
      "[libx264 @ 0x5630cb9b7000] i8c dc,h,v,p: 57% 22% 11% 10%\n",
      "[libx264 @ 0x5630cb9b7000] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x5630cb9b7000] ref P L0: 38.9% 11.7% 41.6%  7.8%\n",
      "[libx264 @ 0x5630cb9b7000] ref B L0: 82.2% 17.8%  0.1%\n",
      "[libx264 @ 0x5630cb9b7000] ref B L1: 100.0%  0.0%\n",
      "[libx264 @ 0x5630cb9b7000] kb/s:968.77\n",
      "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
      "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
      "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
      "  libavutil      56. 70.100 / 56. 70.100\n",
      "  libavcodec     58.134.100 / 58.134.100\n",
      "  libavformat    58. 76.100 / 58. 76.100\n",
      "  libavdevice    58. 13.100 / 58. 13.100\n",
      "  libavfilter     7.110.100 /  7.110.100\n",
      "  libswscale      5.  9.100 /  5.  9.100\n",
      "  libswresample   3.  9.100 /  3.  9.100\n",
      "  libpostproc    55.  9.100 / 55.  9.100\n",
      "Input #0, image2, from 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera/image%d.png':\n",
      "  Duration: 00:01:00.10, start: 0.000000, bitrate: N/A\n",
      "  Stream #0:0: Video: png, rgb24(pc), 1280x960, 20 fps, 20 tbr, 20 tbn, 20 tbc\n",
      "Stream mapping:\n",
      "  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))\n",
      "Press [q] to stop, [?] for help\n",
      "[libx264 @ 0x55c7b5b7a640] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
      "[libx264 @ 0x55c7b5b7a640] profile High, level 3.2, 4:2:0, 8-bit\n",
      "[libx264 @ 0x55c7b5b7a640] 264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=30 lookahead_threads=5 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=20 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=15.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
      "Output #0, mp4, to 'simulators/unity_random_3ccr_1e1_v115/evaluate/recording/mainCamera.mp4':\n",
      "  Metadata:\n",
      "    encoder         : Lavf58.76.100\n",
      "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(tv, progressive), 1280x960, q=2-31, 20 fps, 10240 tbn\n",
      "    Metadata:\n",
      "      encoder         : Lavc58.134.100 libx264\n",
      "    Side data:\n",
      "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
      "frame= 1202 fps=160 q=-1.0 Lsize=    9613kB time=00:00:59.95 bitrate=1313.6kbits/s speed=7.96x    \n",
      "video:9601kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.123887%\n",
      "[libx264 @ 0x55c7b5b7a640] frame I:6     Avg QP: 6.07  size: 55089\n",
      "[libx264 @ 0x55c7b5b7a640] frame P:805   Avg QP:13.82  size:  9870\n",
      "[libx264 @ 0x55c7b5b7a640] frame B:391   Avg QP:17.36  size:  3977\n",
      "[libx264 @ 0x55c7b5b7a640] consecutive B-frames: 45.3% 29.0% 14.7% 11.0%\n",
      "[libx264 @ 0x55c7b5b7a640] mb I  I16..4: 25.9% 40.6% 33.5%\n",
      "[libx264 @ 0x55c7b5b7a640] mb P  I16..4:  1.1%  2.4%  3.5%  P16..4:  5.2%  0.8%  0.7%  0.0%  0.0%    skip:86.3%\n",
      "[libx264 @ 0x55c7b5b7a640] mb B  I16..4:  0.1%  0.4%  0.8%  B16..8:  5.2%  0.8%  0.4%  direct: 0.4%  skip:91.8%  L0:54.6% L1:41.8% BI: 3.7%\n",
      "[libx264 @ 0x55c7b5b7a640] 8x8 transform intra:35.1% inter:31.3%\n",
      "[libx264 @ 0x55c7b5b7a640] coded y,uvDC,uvAC intra: 52.3% 75.8% 63.4% inter: 0.9% 1.8% 1.4%\n",
      "[libx264 @ 0x55c7b5b7a640] i16 v,h,dc,p: 23% 37%  4% 36%\n",
      "[libx264 @ 0x55c7b5b7a640] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 30% 17% 18%  3%  9% 10%  7%  3%  4%\n",
      "[libx264 @ 0x55c7b5b7a640] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 27% 22% 20%  4%  7%  7%  6%  3%  3%\n",
      "[libx264 @ 0x55c7b5b7a640] i8c dc,h,v,p: 48% 26% 17%  9%\n",
      "[libx264 @ 0x55c7b5b7a640] Weighted P-Frames: Y:0.0% UV:0.0%\n",
      "[libx264 @ 0x55c7b5b7a640] ref P L0: 32.4%  6.6% 44.5% 16.6%\n",
      "[libx264 @ 0x55c7b5b7a640] ref B L0: 78.1% 18.0%  4.0%\n",
      "[libx264 @ 0x55c7b5b7a640] ref B L1: 99.1%  0.9%\n",
      "[libx264 @ 0x55c7b5b7a640] kb/s:1308.60\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEW [85-videofig]: /home/florian/uitb-sim2vr/user-in-the-box-private/simulators/unity_random_3ccr_1e1_v115/evaluate/logging/2023-09-18/1695062477/20-41-17-high-medium successfully registered at '~/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/85-videofig/'.\n"
     ]
    }
   ],
   "source": [
    "## EVALUATE LIST OF SIMULATION DIRS\n",
    "\n",
    "import uitb\n",
    "os.chdir(uitb.__path__[0])\n",
    "os.chdir(\"..\")\n",
    "\n",
    "SIMULATION_DIRS = [\n",
    "    # \"simulators/unity_low_difficulty_easy_3ccr_1e3\",  #low-easy\n",
    "    # \"simulators/unity_difficulty_easy_3ccr_1e3\",  #mid-easy\n",
    "    # \"simulators/unity_high_difficulty_easy_3ccr_1e3\",  #high-easy\n",
    "    # \"simulators/unity_low_difficulty_easy_ce\",  #low-easy\n",
    "    # \"simulators/unity_difficulty_easy_ce\",  #mid-easy\n",
    "    # \"simulators/unity_high_difficulty_easy_ce\",  #high-easy\n",
    "    # \"trained/unity_easy/\",\n",
    "    # \"trained/unity_medium_pretrained/\",\n",
    "    # \"trained/unity_hard_pretrained/\",\n",
    "    # \"trained/unity_low_pretrained/\",\n",
    "    # \"trained/unity_medium_pretrained/\",  #mid-medium\n",
    "    # \"trained/unity_high_pretrained/\",\n",
    "    # \"simulators/unity_high_difficulty_easy_3ccr_1e2_v110\",  #high-easy\n",
    "    # \"simulators/unity_difficulty_easy_3ccr_1e2_v110\",  #mid-easy\n",
    "    # \"simulators/unity_low_difficulty_easy_3ccr_1e2_v110\",  #low-easy\n",
    "    # \"simulators/unity_random_easy_3ccr_1e2_v110\",  #->82\n",
    "    # \"simulators/unity_random_3ccr_1e2_v110\"  #->83\n",
    "    # \"simulators/unity_random_3ccr_1e2_v110l\"  #->83l \n",
    "    # \"simulators/unity_random_3ccr_1e2_v110lc\"  #->83lc\n",
    "    # \"simulators/unity_random_3ccr_1e2_v112\"  #->83_112\n",
    "    # \"simulators/unity_random_easy_medium_3ccr_1e2_v110\"  #->84\n",
    "    # \"simulators/unity_random_3ccr_1e1_v110\"  #->085\n",
    "    # \"simulators/unity_random_3ccr_1e1_v110l\"  #->085l\n",
    "    # \"simulators/unity_random_3ccr_1e1_v110lc\"  #->085lc\n",
    "    # \"simulators/unity_largenet_random_3ccr_1e1_v110\"  #->085LN\n",
    "    # \"simulators/unity_random_easy_medium_3ccr_1e1_v110\"  #->086\n",
    "    # \"simulators/unity_random_3ccr_1e1_v113\"  #->087\n",
    "    # \"simulators/unity_largenet_random_adaptive_3ccr_1e1_v114\"  #->087LN\n",
    "    # \"simulators/unity_random_neural_1e3_v110\"  #->088\n",
    "    # \"simulators/unity_random_3ccr_0_v110\"  #->089\n",
    "    # \"simulators/unity_random_sparse_3ccr_1e1_v114\"  #->090\n",
    "\n",
    "    \"simulators/unity_random_3ccr_1e1_v115\"  #->85\n",
    "    # \"simulators/unity_random_unc_3ccr_1e1_v115\"  #->85unc\n",
    "    # \"simulators/unity_random_adaptive_3ccr_1e1_v115\"  #->87\n",
    "    # \"simulators/unity_random_adaptive_unc_3ccr_1e1_v115\"  #->87unc\n",
    "    # \"simulators/unity_random_neural_1e3_v115\"  #->88\n",
    "    # \"simulators/unity_random_3ccr_0_v115\"  #->89\n",
    "    # \"simulators/unity_random_sparse_3ccr_1e1_v115\"  #->90\n",
    "\n",
    "    # \"simulators/unity_beatsvr_1e3\"  #->beats01\n",
    "    ]\n",
    "\n",
    "# APP_CONDITIONS = [\"low-easy\", \"easy\", \"high-easy\"]\n",
    "# APP_CONDITIONS = [\"low-medium\", \"medium\", \"high-medium\"]\n",
    "# APP_CONDITIONS = [\"easy\", \"medium\", \"hard\"]\n",
    "# APP_CONDITIONS = [\"easy\", \"high-easy\"]\n",
    "# APP_CONDITIONS = [\"low-easy\", \"easy\", \"high-easy\", \"low-medium\", \"medium\", \"high-medium\"]\n",
    "APP_CONDITIONS = [\"easy\", \"medium\", \"hard\", \"low-medium\", \"medium\", \"high-medium\"]\n",
    "# APP_CONDITIONS = [\"easy-unconstrained\", \"medium-unconstrained\", \"hard-unconstrained\", \"low-medium-unconstrained\", \"mid-unconstrained\", \"high-medium-unconstrained\"]\n",
    "# APP_CONDITIONS = [\"easy\", \"medium\", \"hard\", \"low-medium\", \"mid\", \"high-medium\"]  #for multiple simulations (8501-8512 etc. ...)\n",
    "\n",
    "_RECORD = False  #True\n",
    "\n",
    "#_SIMULATION_USER_ID = 204  #fake simulation user ID used for testing\n",
    "for _SIMULATION_USER_ID in [\"85-videofig\"]:  #range(8551, 8563):\n",
    "    for _TASK_CONDITION in SIMULATION_DIRS:\n",
    "        print(f\"\\n\\nTASK CONDITION: {_TASK_CONDITION}\\n\")\n",
    "        # os.environ[\"_TASK_CONDITION\"] = _TASK_CONDITION\n",
    "        for _app_condition in APP_CONDITIONS:\n",
    "            print(f\"APP CONDITION: {_app_condition}\\n\")\n",
    "            # os.environ[\"_app_condition\"] = _app_condition\n",
    "\n",
    "            # %run uitb/test/evaluator_OLD.py $_TASK_CONDITION --num_episodes 1 --logging\n",
    "            # %run uitb/test/evaluator.py $_TASK_CONDITION --num_episodes 1 --record --logging\n",
    "            os.system(f\"python uitb/test/evaluator.py {_TASK_CONDITION} --num_episodes 1 {'--record' if _RECORD else ''} --logging --uncloned --app_condition {_app_condition} --checkpoint model_100000000_steps.zip\")\n",
    "            # os.system(f\"python uitb/test/evaluator.py {_TASK_CONDITION} --num_episodes 1 {'--record' if _RECORD else ''} --logging --app_condition {_app_condition}\")\n",
    "\n",
    "            _copy_to_dataset(TASK_CONDITION=_TASK_CONDITION, SIMULATION_USER_ID=_SIMULATION_USER_ID, record=_RECORD, logging=True)\n",
    "\n",
    "        if \"mid\" in APP_CONDITIONS or \"mid-unconstrained\" in APP_CONDITIONS:\n",
    "            os.system(f\"rename 's|low-medium|low|' datasets/vr-uitb-experiment/{_SIMULATION_USER_ID}/*\")\n",
    "            os.system(f\"rename 's|high-medium|high|' datasets/vr-uitb-experiment/{_SIMULATION_USER_ID}/*\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fcd99afe-06d2-4818-9694-d5ce3c79e774",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import uitb\n",
    "# os.chdir(uitb.__path__[0])\n",
    "# os.chdir(\"..\")\n",
    "\n",
    "# _TASK_CONDITION = \"trained/unity_high_pretrained\"  #OPTIONS: \"trained/unity_easy\", \"trained/unity_medium_pretrained\", \"trained/unity_hard_pretrained\", \"trained/unity_low_pretrained\", \"trained/unity_high_pretrained\"\n",
    "# _TASK_CONDITION = \"simulators/test_unity_difficulty_easy_3ccr\"\n",
    "\n",
    "# _TASK_CONDITION = \"simulators/unity_high_difficulty_easy_3ccr_1e5\"\n",
    "\n",
    "# os.environ[\"_TASK_CONDITION\"] = _TASK_CONDITION\n",
    "# %run uitb/test/evaluator.py $_TASK_CONDITION --num_episodes 1 --record --logging\n",
    "# # %run uitb/test/evaluator.py $_TASK_CONDITION --num_episodes 10 --logging"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9993d867-d33d-4800-a00e-63bbaa5fe985",
   "metadata": {},
   "source": [
    "Copy evaluation logs (including pickle files) to dataset directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d108d6d-1db9-481f-b880-b40e2a13fbe3",
   "metadata": {},
   "outputs": [],
   "source": [
    "_SIMULATION_USER_ID = 91  #fake simulation user ID used for testing\n",
    "_copy_to_dataset(TASK_CONDITION=_TASK_CONDITION, SIMULATION_USER_ID=_SIMULATION_USER_ID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7545f1e8-6f1d-4f00-8656-3896339173c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "_rng = np.random.default_rng()\n",
    "strength = _rng.uniform(0, 1, size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc9a6e5c-6b2f-4091-9d58-d4cf00e84e88",
   "metadata": {},
   "outputs": [],
   "source": [
    "# if strength > 0.15:\n",
    "#     endurance = (1236.5/((strength*100 - 15)**0.618)) - 72.5\n",
    "# else:\n",
    "#     endurance = np.inf\n",
    "endurance = np.inf * np.ones_like(strength)\n",
    "endurance[strength > 0.15] = (1236.5/((strength[strength > 0.15]*100 - 15)**0.618)) - 72.5\n",
    "0.02/np.min(endurance)*100, 0.02/endurance*100\n",
    "\n",
    "np.mean(endurance[endurance<np.inf]), (1236.5/((np.mean(strength)*100 - 15)**0.618)) - 72.5"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "7ba9120b-4a8c-4c5b-bdc2-451f0deadf23",
   "metadata": {},
   "source": [
    "**NOTES on simulation user IDs:**\n",
    "- 99: testing\n",
    "- 91: Aleksi's trained models evaluated with 3CCr costs\n",
    "- 92: Aleksi's trained models evaluated with CE costs\n",
    "- 901: trained with 3CCr costs (cost weight: 1e-3)\n",
    "- 902: trained with CE costs\n",
    "- ~~8501-8512: trained with 3ccr costs (cost weight: 1e-1), whac-a-mole v1.1.0, with special intermediate training on left targets (100M regul. + 15M left-only + 50M regul. training steps)~~\n",
    "- 8501-8512: unity_random_3ccr_1e1_v115, 100M\n",
    "- 8551-8562: unity_random_unc_3ccr_1e1_v115, 100M\n",
    "- 8701-8712: unity_random_adaptive_3ccr_1e1_v115, 100M\n",
    "- *8721-8732: unity_random_adaptive_3ccr_1e1_v115, 195M*\n",
    "- 8751-8762: unity_random_adaptive_unc_3ccr_1e1_v115, 100M"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d3559b9a-e378-4111-bb87-a3724f93a8a1",
   "metadata": {},
   "source": [
    "**Evaluate fatigue/effort metrics for different conditions.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7462318-39f4-478a-a918-21c47308d0df",
   "metadata": {},
   "outputs": [],
   "source": [
    "lifting_muscles = [\"DELT1\", \"DELT2\", \"DELT3\", \"SUPSP\", \"INFSP\", \"SUBSC\", \"TMIN\", \"BIClong\", \"BICshort\", \"TRIlong\", \"TRIlat\", \"TRImed\"]  #muscles of the mobl_arms_wrist that act on the shoulder\n",
    "lifting_indices = [0, 1, 2, 3, 4, 5, 6, 20, 21, 15, 16, 17]  #[env._model.actuator(_i).id for _i in lifting_muscles]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02093f58-4715-4126-b5b2-b504aff15da3",
   "metadata": {},
   "outputs": [],
   "source": [
    "_test = np.load(\"/home/florian/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/91/09-22-59-low/state_log.pickle\", allow_pickle=True)\n",
    "np.mean([np.mean(i[\"effort_cost\"][1:]) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(np.mean, i[\"3CCr_MF\"]))) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(lambda x: np.mean(x[lifting_indices]), i[\"3CCr_MF\"]))) for i in _test.values()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "578dce42-4830-4af9-9dc6-9e8bd0e16024",
   "metadata": {},
   "outputs": [],
   "source": [
    "_test = np.load(\"/home/florian/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/91/09-25-50-mid/state_log.pickle\", allow_pickle=True)\n",
    "_test[\"episode_00\"][\"effort_cost\"]\n",
    "np.mean([np.mean(i[\"effort_cost\"][1:]) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(np.mean, i[\"3CCr_MF\"]))) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(lambda x: np.mean(x[lifting_indices]), i[\"3CCr_MF\"]))) for i in _test.values()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84da1161-b617-4ee0-9335-45943e2e4af9",
   "metadata": {},
   "outputs": [],
   "source": [
    "_test = np.load(\"/home/florian/uitb-sim2vr/user-in-the-box-private/datasets/vr-uitb-experiment/91/09-29-58-high/state_log.pickle\", allow_pickle=True)\n",
    "_test[\"episode_00\"][\"effort_cost\"]\n",
    "np.mean([np.mean(i[\"effort_cost\"][1:]) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(np.mean, i[\"3CCr_MF\"]))) for i in _test.values()])\n",
    "np.mean([np.mean(list(map(lambda x: np.mean(x[lifting_indices]), i[\"3CCr_MF\"]))) for i in _test.values()])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "6d8f5abc-4351-47f0-acd7-41b33ba215f9",
   "metadata": {},
   "source": [
    "## Run Training"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "01404410-a184-4863-acea-186e20c09588",
   "metadata": {},
   "source": [
    "Run from command line with X11 (e.g., using MobaXterm):\n",
    "```python\n",
    "export DISPLAY=:1\n",
    "python uitb/train/trainer.py uitb/configs/mobl_arms_unity_test1.yaml\n",
    "```"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "644a3245-eb82-4106-8c5d-da52074e45fd",
   "metadata": {},
   "source": [
    "## Utils"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "83a9b942-2b9b-4aeb-9385-c87517d88376",
   "metadata": {},
   "source": [
    "Copy build files (i.e., a standalone Unity app for each task condition/target setup) to source dir."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a936d4df-e324-452b-b3f5-278c7d61358e",
   "metadata": {},
   "outputs": [],
   "source": [
    "for _cond in [\"unity_easy\", \"unity_medium_pretrained\", \"unity_hard_pretrained\", \"unity_low_pretrained\", \"unity_high_pretrained\"]:\n",
    "    os.popen(f\"mkdir ~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/{_cond.split('_')[1]}\")\n",
    "    os.popen(f\"cp ~/uitb-sim2vr/user-in-the-box-private/trained/{_cond}/{_cond}/tasks/unity/build/build.x86_64 ~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/{_cond.split('_')[1]}/build.x86_64\")\n",
    "    os.popen(f\"cp ~/uitb-sim2vr/user-in-the-box-private/trained/{_cond}/{_cond}/tasks/unity/build/UnityPlayer.so ~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/{_cond.split('_')[1]}/UnityPlayer.so\")\n",
    "    os.popen(f\"cp ~/uitb-sim2vr/user-in-the-box-private/trained/{_cond}/{_cond}/tasks/unity/build/build_Data ~/uitb-sim2vr/user-in-the-box-private/uitb/tasks/unity/build/{_cond.split('_')[1]}/ -r\")"
   ]
  }
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