examples/feature_overview.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d1a30695-34e1-4cdb-b066-f7ce39a1dce1",
   "metadata": {},
   "source": [
    "# BeamNGpy Feature Overview\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b31d13e9-c04d-4ced-9cf4-d4044a3b191d",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "This notebook is a non-exhaustive showcase of the things you can do with BeamNGpy, focused on customization of the vehicles, the environment and the sensor suite.\n",
    "\n",
    "To install BeamNGpy, follow the instructions listed [here](https://github.com/BeamNG/BeamNGpy#installation).\n",
    "Also be sure to study the complete documentation of [BeamNGpy](https://beamngpy.readthedocs.io) and [BeamNG.tech](https://documentation.beamng.com/beamng_tech/), if you want to familiarize yourself more with the library.\n",
    "\n",
    "Let's start!\n",
    "\n",
    "BeamNGpy is packaged as a Python module called `beamngpy`. All the imports that we will need in this notebook are listed in the following cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e9a04b32-9aae-4baf-b6a3-4e43bed15b69",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import colorsys\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from beamngpy import BeamNGpy, Scenario, Vehicle\n",
    "from beamngpy.sensors import (\n",
    "    AdvancedIMU,\n",
    "    Camera,\n",
    "    Damage,\n",
    "    Electrics,\n",
    "    Lidar,\n",
    "    State,\n",
    "    Timer,\n",
    "    Ultrasonic,\n",
    ")\n",
    "from IPython.display import clear_output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43cd3e95-94ab-4f9d-90c4-fb37e6cfd229",
   "metadata": {},
   "source": [
    "To start BeamNG.tech using BeamNGpy, you use the constructor of the class `BeamNGpy`. The `BeamNGpy` instance allows you to control the simulation. We call `BeamNGpy.open()` to start the simulation which is connected to the Python process using a TCP socket."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bf12820-7870-4f60-a931-723c0de04c2d",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2aa029d7-ce4e-49df-8a87-afd64dd1d962",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mBeamNGpy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mhost\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mport\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mhome\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mbinary\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0muser\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mquit_on_close\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcrash_lua_on_error\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The :class:`BeamNGpy` class is the backbone of communication with the BeamNG\n",
       "simulation and offers methods of starting, stopping, connecting to, and\n",
       "controlling the state of the simulator.\n",
       "\n",
       "Instantiates a BeamNGpy instance connecting to the simulator on the\n",
       "given host and port. The home directory of the simulator can be passed\n",
       "to this constructor. If ``None`` is given, this class tries to read a\n",
       "home path from the ``BNG_HOME`` environment variable.\n",
       "\n",
       "Args:\n",
       "    host: The host to connect to.\n",
       "    port: The port to connect to.\n",
       "    home: Path to the simulator's home directory.\n",
       "    binary: Optional custom path to the binary, relative to the simulator's\n",
       "            home directory. Default is ``Bin64/BeamNG.{tech/drive}.x64.exe``\n",
       "            for Windows hosts, ``BinLinux/BeamNG.{tech/drive}.x64`` for Linux\n",
       "            hosts.\n",
       "    user: Additional optional user path to set. This path can be\n",
       "          used to set where custom files created during executions\n",
       "          will be placed if the home folder shall not be touched.\n",
       "    quit_on_close: Whether the simulator should be closed when :func:`close()` is called.\n",
       "                   Defaults to True.\n",
       "    crash_lua_on_error: If True, then sets BeamNG to not respond to BeamNGpy requests when a Lua error\n",
       "                        happens and prints the stacktrace instead.\n",
       "                        Is applicable only when the process is launched by this instance of BeamNGpy,\n",
       "                        as it sets a launch argument of the process. Defaults to False.\n",
       "\n",
       "Attributes\n",
       "----------\n",
       "    camera: CameraApi\n",
       "        The API module to control the camera in the simulator.\n",
       "        See :class:`.CameraApi` for details.\n",
       "    control: ControlApi\n",
       "        The API module to control the flow of the simulation.\n",
       "        See :class:`.ControlApi` for details.\n",
       "    debug: DebugApi\n",
       "        The API module to control debug objects.\n",
       "        See :class:`.DebugApi` for details.\n",
       "    env: EnvironmentApi\n",
       "        The API module to control the simulation's environment.\n",
       "        See :class:`.EnvironmentApi` for details.\n",
       "    scenario: ScenarioApi\n",
       "        The API module to control the scenarios.\n",
       "        See :class:`.ScenarioApi` for details.\n",
       "    settings: SettingsApi\n",
       "        The API module to control the settings of the simulator.\n",
       "        See :class:`.SettingsApi` for details.\n",
       "    system: SystemApi\n",
       "        The API module for getting information about the host system.\n",
       "        See :class:`.SystemApi` for details.\n",
       "    traffic: TrafficApi\n",
       "        The API module to control the traffic.\n",
       "        See :class:`.TrafficApi` for details.\n",
       "    vehicles: VehiclesApi\n",
       "        The API module to control the vehicles in the scenario.\n",
       "        See :class:`.VehiclesApi` for details.\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\beamng\\beamng.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?BeamNGpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3709f351-48c5-45de-80b5-42b5cc19ef80",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mBeamNGpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mextensions\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'List[str] | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mlaunch\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcrash_lua_on_error\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mlisten_ip\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'127.0.0.1'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m**\u001b[0m\u001b[0mopts\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Starts a BeamNG.* process, opens a server socket, and waits for the spawned BeamNG.* process to connect.\n",
       "This method blocks until the process started and is ready.\n",
       "\n",
       "Args:\n",
       "    extensions: A list of non-default BeamNG Lua extensions to be loaded on start.\n",
       "    launch: Whether to launch a new process or connect to a running one on the configured host/port.\n",
       "            Defaults to True.\n",
       "    crash_lua_on_error: If True, then sets BeamNG to not respond to BeamNGpy requests when a Lua error\n",
       "                        happens and prints the stacktrace instead.\n",
       "                        Is applicable only when the process is launched by this instance of BeamNGpy,\n",
       "                        as it sets a launch argument of the process. Defaults to False.\n",
       "    listen_ip: The IP address that the BeamNG process will be listening on. Only relevant when ``launch`` is True.\n",
       "             Set to ``*`` if you want BeamNG to listen on ALL network interfaces.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\beamng\\beamng.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?BeamNGpy.open"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8ddebdf-0874-4a00-a337-bc89def69a25",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "023ab582-a62c-4ad2-9c6f-3f09a5aa16fb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<beamngpy.beamng.beamng.BeamNGpy at 0x231c3ba7d60>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beamng = BeamNGpy(\"localhost\", 64256)\n",
    "beamng.open()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92a55f65-1816-483b-a868-8b4d512eaf37",
   "metadata": {},
   "source": [
    "The main menu of BeamNG.tech pops up and we are ready to set up the simulation! We will start on the `italy` map. Let's generate a `Scenario` object, a single `Vehicle` and add the vehicle to the scenario."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "456ae5f4-7279-4ce8-b526-d1543f7da9f3",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "05e50ef6-568c-4acf-aaab-61786d38ef0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mScenario\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mlevel\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | Level'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpath\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mhuman_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdescription\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdifficulty\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mauthors\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m**\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Any'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The scenario class contains information for setting up and executing\n",
       "simulation scenarios along with methods to extract data during their\n",
       "execution.\n",
       "\n",
       "Instantiates a scenario instance with the given name taking place in\n",
       "the given level.\n",
       "\n",
       "Args:\n",
       "    level: Either the name of the level this scenario takes place in\n",
       "            as a string or as an instance of :class:`.Level`\n",
       "    name: The name of this scenario. Should be unique for the\n",
       "                level it's taking place in to avoid file collisions.\n",
       "    path: The path to an already existing scenario file (relative to\n",
       "          the home folder / user folder). If set, then :func:`Scenario.make`\n",
       "          should not be called, as the scenario is already made.\n",
       "    human_name: The human-readable name of the scenario. If None, it\n",
       "                will be set to ``name``.\n",
       "    description: The description of the scenario displayed in the simulator.\n",
       "    difficulty: The difficulty of the scenario displayed in the simulator.\n",
       "    authors: Names of the authors. Defaults to ``BeamNGpy``.\n",
       "    options: Other pptions of the scenario object, not used at the moment.\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\scenario\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Scenario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7ed1b033-3929-406f-96ea-743c3e73bfea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mVehicle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvid\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mmodel\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mport\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mlicense\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Color | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcolor2\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Color | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcolor3\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Color | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mextensions\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'List[str] | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpart_config\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[1;33m**\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Any'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The vehicle class represents a vehicle of the simulation that can be\n",
       "interacted with from BeamNGpy. This class offers methods to both control\n",
       "the vehicle's state as well as retrieve information about it through\n",
       "sensors the user can attach to the vehicle.\n",
       "\n",
       "Creates a vehicle with the given vehicle ID. The ID must be unique\n",
       "within the scenario.\n",
       "\n",
       "Args:\n",
       "    vid: The vehicle's ID.\n",
       "    model: Model of the vehicle.\n",
       "    port: The TCP port on which the vehicle should connect. If None, a\n",
       "          new port is requested from the simulator.\n",
       "    license: The license plate's text.\n",
       "    color: The primary vehicle color.\n",
       "    color2: The secondary vehicle color.\n",
       "    color3: The tertiary vehicle color.\n",
       "    extensions: A list of vehicle Lua extensions to load for the vehicle.\n",
       "    part_config: The path to the vehicle part configuration (a ``.pc`` file).\n",
       "    options: Other possible vehicle options.\n",
       "\n",
       "Attributes\n",
       "----------\n",
       "    sensors: Sensors\n",
       "        The sensors attached to the vehicle.\n",
       "    ai: AIApi\n",
       "        The API module to control the AI behavior of the vehicle.\n",
       "        See :class:`.AIApi` for details.\n",
       "    logging: LoggingApi\n",
       "        The API module to control the logging behavior of the vehicle inside the simulator.\n",
       "        See :class:`.LoggingApi` for details.\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Vehicle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "edf558b3-2452-4ea3-950b-4edcb5d1efaa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mScenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_vehicle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Vehicle'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpos\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrot_quat\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Quat'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mcling\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Adds a :class:`.Vehicle`: to this scenario at the given position with the given\n",
       "orientation.\n",
       "\n",
       "Args:\n",
       "    vehicle: The vehicle to spawn.\n",
       "    pos: ``(x, y, z)`` tuple specifying the position of the vehicle.\n",
       "    rot_quat: ``(x, y, z, w)`` tuple specifying the rotation as quaternion.\n",
       "    cling: If True, the z-coordinate of the vehicle's position will be set to the ground level at the given\n",
       "           position to avoid spawning the vehicle below ground or in the air.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\scenario\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Scenario.add_vehicle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2f721368-a7fd-4a70-81e3-0352eb11dc6e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mScenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbng\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Generates necessary files to describe the scenario in the simulation\n",
       "and outputs them to the simulator.\n",
       "\n",
       "Args:\n",
       "    bng: The BeamNGpy instance to generate the scenario for.\n",
       "\n",
       "Raises:\n",
       "    BNGError: If the scenario already has set its info .json file included.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\scenario\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Scenario.make"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bf89b6d-f567-495e-a654-853857ea1475",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "514eb6b5-9d09-4ac4-8ab4-6b9253f8d2df",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "scenario = Scenario(\"italy\", \"beamngpy_feature_overview\")\n",
    "\n",
    "ego = Vehicle(\"ego\", model=\"etk800\", color=\"White\", license=\"PYTHON\")\n",
    "scenario.add_vehicle(\n",
    "    ego, pos=(245.11, -906.94, 247.46), rot_quat=(0.0010, 0.1242, 0.9884, -0.0872)\n",
    ")\n",
    "scenario.make(beamng)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ab59a40-13c7-4c91-a88c-72c29534612c",
   "metadata": {},
   "source": [
    "Voilà, simple as that! To actually start the simulation, you need the following commands:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c7a974a-fa25-4e92-b298-9cfbfa3bb0ff",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2c79d364-c196-4401-9fa8-fc43ed6568e5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mscenario\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Scenario'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mprecompile_shaders\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mconnect_player_vehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mconnect_existing_vehicles\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Loads the given scenario in the simulation and returns once loading\n",
       "is finished.\n",
       "\n",
       "Args:\n",
       "    scenario: The scenario to load.\n",
       "    precompile_shaders: Whether the shaders should be compiled before the start of the scenario.\n",
       "                        If False, the first load of a map will take a longer time, but disabling\n",
       "                        the precompilation can lead to issues with the :class:`Camera` sensor.\n",
       "                        Defaults to True.\n",
       "    connect_player_vehicle: Whether the player vehicle should be connected\n",
       "                            to this (:class:``.Scenario``) instance. Defaults to True.\n",
       "    connect_existing_vehicles: Whether ALL vehicles spawned already in the scenario should be connected\n",
       "                               to this (:class:``.Scenario``) instance. Defaults to True.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.scenario.load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d6f5d28f-8eb0-4f10-a68a-22886092c253",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrestrict_actions\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Starts the scenario; equivalent to clicking the \"Start\" button in the\n",
       "game after loading a scenario. This method blocks until the countdown\n",
       "to the scenario's start has finished.\n",
       "\n",
       "Args:\n",
       "    restrict_actions: Whether to keep scenario restrictions,\n",
       "                    such as limited menu options and controls.\n",
       "                    Defaults to False.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.scenario.start"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "576ebbf8-2888-49ba-9661-dab3751ad191",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "095bff9a-c70a-4b77-9a9c-89f94acdb489",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.scenario.load(scenario)\n",
    "beamng.scenario.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d0901ab-d7c6-4600-bc22-7d23e04d003f",
   "metadata": {},
   "source": [
    "The scenario is now loaded and started. Get ready for the feature showcase! We start by using the `ai.set_mode` command on the vehicle. It will drive around through the whole map, using the road network data to navigate."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a45ce9d-745a-46d2-b782-899669be2e08",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "910eef88-9f63-42f1-ac9c-2a2896dd0c3c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mai\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_mode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the desired mode of the simulator's built-in AI for this vehicle.\n",
       "Possible values are:\n",
       "\n",
       " * ``disabled``: Turn the AI off (default state)\n",
       " * ``random``: Drive from random points to random points on the map\n",
       " * ``span``: Drive along the entire road network of the map\n",
       " * ``manual``: Drive to a specific waypoint, target set separately\n",
       " * ``chase``: Chase a target vehicle, target set separately\n",
       " * ``flee``: Flee from a vehicle, target set separately\n",
       " * ``stopping``: Make the vehicle come to a halt (AI disables itself once the vehicle stopped.)\n",
       "\n",
       "Note:\n",
       "    Some AI methods automatically set appropriate modes, meaning a call\n",
       "    to this method might be optional.\n",
       "\n",
       "Args:\n",
       "    mode: The AI mode to set.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\vehicle\\ai.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.ai.set_mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5e0b4abf-f8fb-4ce7-8ca1-e25732222ffc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mai\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrive_in_lane\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlane\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the drive in lane flag of the AI. If True, the AI only drives\n",
       "within the lane it can legally drive in.\n",
       "\n",
       "Args:\n",
       "    lane: Lane flag to set.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\vehicle\\ai.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.ai.drive_in_lane"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e2f606-c707-41b0-913d-5d06e49c3090",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ac5a8576-b6b8-4a2d-aee9-eb510244cb9c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ego.ai.set_mode(\"span\")\n",
    "ego.ai.drive_in_lane(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6b2a746-7912-4a2a-9b0e-c15c5ae71eef",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Customization options\n",
    "\n",
    "With BeamNGpy, we can set and tweak various parameters of the vehicles spawned and also of the whole simulation environment. Let's see a few examples of what is possible to do. This list is not exhaustive; consult the [documentation](https://beamngpy.readthedocs.io) to see all the available options."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b161c5ce-1e8e-4ac4-a507-6b2706d294e4",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "588d088e-b1b1-4051-8f47-9e3bc30b420a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_color\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrgba\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Color'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m1.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the color of this vehicle. Colour can be adjusted on the RGB\n",
       "spectrum and the \"shininess\" of the paint.\n",
       "\n",
       "Args:\n",
       "    rgba: The new colour given as a tuple of RGBA floats, where\n",
       "          the alpha channel encodes the shininess of the paint.\n",
       "          Also can be given in any format specified in :class:`~beamngpy.types.Color`.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.set_color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "539e845e-19f0-4a65-9123-be5bfd0c269b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_lights\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mleft_signal\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mright_signal\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mhazard_signal\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mheadlights\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mfog_lights\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mlightbar\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the vehicle's lights to given intensity values. The lighting\n",
       "system features lights that are simply binary on/off, but also ones\n",
       "where the intensity can be varied. Binary lights include:\n",
       "\n",
       "    * ``left_signal``\n",
       "    * ``right_signal``\n",
       "    * ``hazard_signal``\n",
       "\n",
       "Non-binary lights vary between 0 for off, 1 for on, 2 for higher\n",
       "intensity. For example, headlights can be turned on with 1 and set to\n",
       "be more intense with 2. Non-binary lights include:\n",
       "\n",
       "    * ``headlights``\n",
       "    * ``fog_lights``\n",
       "    * ``lightbar``\n",
       "\n",
       "Args:\n",
       "    left_signal: On/off state of the left signal\n",
       "    right_signal: On/off state of the right signal\n",
       "    hazard_signal: On/off state of the hazard lights\n",
       "    headlights: Value from 0 to 2 indicating headlight intensity\n",
       "    fog_lights: Value from 0 to 2 indicating fog light intensity\n",
       "    lightbar: Value from 0 to 2 indicating lightbar intensity\n",
       "\n",
       "Note:\n",
       "    Not every vehicle has every type of light. For example, the\n",
       "    `lightbar` refers to the kind of lights typically found on top of\n",
       "    police cars. Setting values for non-existent lights will not cause\n",
       "    an error, but also achieve no effect.\n",
       "\n",
       "    Note also that lights are not independent. For example, turning on\n",
       "    the hazard lights will make both signal indicators blink, meaning\n",
       "    they will be turned on as well. Opposing indicators also turn each\n",
       "    other off, i.e. turning on the left signal turns off the right one,\n",
       "    and turning on the left signal during\n",
       "\n",
       "Raises:\n",
       "    BNGValueError: If an invalid light value is given.\n",
       "\n",
       "Returns:\n",
       "    Nothing. To query light states, attach an\n",
       "    :class:`.sensors.Electrics` sensor and poll it.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.set_lights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2bb40b01-c028-4388-b66f-07a8794e18f6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_license_plate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the text of the vehicle's license plate.\n",
       "\n",
       "Args:\n",
       "    text: The vehicle plate text to be set.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.set_license_plate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a77d189a-eef9-4574-a87f-a93615908b2d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_tod\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mtod\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Time | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mplay\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mday_scale\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mnight_scale\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mday_length\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mazimuth_override\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the current time of day. The time of day value is given as a float\n",
       "between 0 and 1. How this value affects the lighting of the scene is\n",
       "dependant on the map's TimeOfDay object.\n",
       "\n",
       "Args:\n",
       "    tod: Time of day. Can be provided as a float between 0.0 and 1.0, or as a string in the format 'HH:MM:SS'.\n",
       "    play: False by default.\n",
       "    day_scale: How fast should the day be.\n",
       "    night_scale: How fast should the night be.\n",
       "    day_length: Length of the day (24 hours).\n",
       "    azimuth_override: Used to specify an azimuth that will stay constant throughout the day cycle.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\environment.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.env.set_tod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6cdb3ffb-588a-4fe4-afd8-d9ece7b86087",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpause\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sends a pause request to BeamNG.*, blocking until the simulation is\n",
       "paused.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\control.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.control.pause"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "544b973c-32cb-471d-87fc-00e7ac06aad1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresume\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sends a resume request to BeamNG.*, blocking until the simulation\n",
       "is resumed.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\control.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.control.resume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "42e68384-805d-4b74-a79e-177cfb2dcbf1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_gravity\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgravity\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m9.807\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the strength of gravity in the simulator.\n",
       "\n",
       "Args:\n",
       "    gravity: The gravity value to set. The default one is that of earth (-9.807).\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\environment.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.env.set_gravity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b70bae42-b246-44f7-93ed-e575ccd212cc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mui\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdisplay_message\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Displays a toast message in the user interface of the simulator.\n",
       "\n",
       "Args:\n",
       "    msg: The message to display.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\ui.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.ui.display_message"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01d42b0d-dec8-4a1e-9c09-ef486789e251",
   "metadata": {},
   "source": [
    "### Change color\n",
    "\n",
    "Cycles through 30 different colors and applies them to the vehicle in sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1d1706e3-64a6-43af-83a3-63c87a8857cd",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def generate_colors(n):\n",
    "    hue = 0.0\n",
    "    step_val = 1.0 / n\n",
    "    for _ in range(n):\n",
    "        rgb = colorsys.hsv_to_rgb(hue, 1, 1)\n",
    "        hue += step_val\n",
    "        hue %= 1.0\n",
    "        yield (*rgb, 1.0)\n",
    "\n",
    "\n",
    "for color in generate_colors(30):\n",
    "    ego.set_color(color)\n",
    "    time.sleep(0.1)\n",
    "ego.set_color((1.0, 0.5, 0.5, 1.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "642a7b17-79f9-43d7-b6fe-3aedc9e99331",
   "metadata": {},
   "source": [
    "### Change license plate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2a16563b-9e51-4fcc-ad97-a31bbdb4227e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ego.set_license_plate(\"ILOVEBNG\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc6cca84-7c90-4e36-b3ec-ec4dddc8c621",
   "metadata": {},
   "source": [
    "### Switch lights\n",
    "\n",
    "Switches all lights on and then resets them to the original state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ee4314f3-4449-4d33-9f33-2672273885ba",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ego.set_lights(\n",
    "    left_signal=True,\n",
    "    right_signal=True,\n",
    "    hazard_signal=True,\n",
    "    headlights=2,\n",
    "    fog_lights=2,\n",
    "    lightbar=2,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f5b89159-1b7b-483a-849b-d3d40247a00f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ego.set_lights(\n",
    "    left_signal=False,\n",
    "    right_signal=False,\n",
    "    hazard_signal=False,\n",
    "    headlights=1,\n",
    "    fog_lights=0,\n",
    "    lightbar=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5869734d-9bc2-4c19-b7dc-2d34e4b88b64",
   "metadata": {},
   "source": [
    "### Set time of day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1394f26f-d771-4390-af82-8a9cc9312cfc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for t in range(100):\n",
    "    beamng.env.set_tod(t / 100)\n",
    "    time.sleep(0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "266d8e01-7b76-432d-a91e-7f812a26016f",
   "metadata": {},
   "source": [
    "### Pause/resume simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e4ab53c7-c62c-430f-b8e5-af8e5f8fff54",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.control.pause()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ae0070ff-3512-4e5e-99de-3a38caaf53d9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.control.resume()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eea3270-b263-42e1-b416-8f45b42ffa37",
   "metadata": {},
   "source": [
    "### Set gravity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d1a9b3d2-1f73-44b9-acc3-068b2fdf5c94",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.env.set_gravity(0)\n",
    "beamng.ui.display_message(\"Space adventures await!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "338d8708-aa2f-4382-bc8f-d162be6cd982",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.env.set_gravity(-50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7a79113-d4be-4ff3-82ef-bf8c8b89a928",
   "metadata": {},
   "source": [
    "OK, that was too much gravity for the car. Let's reset it back. We will use the `ego.teleport` function, which resets the vehicle's physics state (repairs it) as a side effect."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7969169a-af2f-4417-b293-cba92f62b400",
   "metadata": {},
   "source": [
    "### Teleport vehicle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22be8846-ef17-4e30-b509-f15331ebe1af",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2e3ad518-2bdf-493a-8e5e-8636f2f08d0e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mScenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfind_waypoints\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'List[ScenarioObject]'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Finds waypoints placed in the world right now.\n",
       "\n",
       "Returns:\n",
       "    A list of :class:`.ScenarioObject` containing waypoints found in\n",
       "    the world.\n",
       "\n",
       "Raises:\n",
       "    BNGError: If the scenario is not currently loaded.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\scenario\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Scenario.find_waypoints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "153e6357-5dbe-4de4-890d-2da075c45a91",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mteleport\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpos\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrot_quat\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Quat | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mreset\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'bool'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Teleports the vehicle to the given position with the given\n",
       "rotation.\n",
       "\n",
       "Args:\n",
       "    pos: The target position as an (x,y,z) tuple containing world-space coordinates.\n",
       "    rot_quat: Optional tuple (x, y, z, w) specifying vehicle rotation as quaternion.\n",
       "    reset: Specifies if the vehicle will be reset to its initial state during teleport (including its velocity).\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.teleport"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4c6bbd32-f240-4793-bb3b-1c926aeed096",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_shift_mode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the shifting mode of the vehicle. This changes whether or not and\n",
       "how the vehicle shifts gears depending on the RPM. Available modes are:\n",
       "\n",
       " * ``realistic_manual``\n",
       "    Gears have to be shifted manually by the user, including engaging the clutch.\n",
       " * ``realistic_manual_auto_clutch``\n",
       "    Gears have to be shifted manually by the user, without having to use the clutch.\n",
       " * ``arcade``\n",
       "    Gears shift up and down automatically. If the brake is held, the vehicle automatically\n",
       "    shifts into reverse and accelerates backward until brake is released or throttle is engaged.\n",
       " * ``realistic_automatic``\n",
       "    Gears shift up automatically, but reverse and parking need to be shifted to manually.\n",
       "\n",
       "Args:\n",
       "    mode: The mode to set. Must be a string from the options listed above.\n",
       "\n",
       "Raises:\n",
       "    BNGValueError: If an invalid mode is given.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.set_shift_mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a2dd7470-c35e-4ccc-a957-36d5b4e5ba42",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0msteering\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mthrottle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mbrake\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mparkingbrake\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mclutch\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mgear\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sends a control message to the vehicle, setting vehicle inputs\n",
       "accordingly.\n",
       "\n",
       "Args:\n",
       "    steering: Rotation of the steering wheel, from -1.0 to 1.0.\n",
       "    throttle: Intensity of the throttle, from 0.0 to 1.0.\n",
       "    brake: Intensity of the brake, from 0.0 to 1.0.\n",
       "    parkingbrake: Intensity of the parkingbrake, from 0.0 to 1.0.\n",
       "    clutch: Clutch level, from 0.0 to 1.0.\n",
       "    gear: Gear to shift to, -1 eq backwards, 0 eq neutral, 1 to X eq nth gear\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1b50bdb0-7eaa-4b62-9078-9ef293df2d36",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_velocity\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvelocity\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdt\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Sets the velocity of this vehicle. The velocity is not achieved instantly,\n",
       "it is acquired gradually over the time interval set by the `dt` argument.\n",
       "\n",
       "As the method of setting velocity uses physical forces, at high velocities\n",
       "it is important to set ``dt`` to an appropriately high value. The default\n",
       "``dt`` value of 1.0 is suitable for velocities up to 30 m/s.\n",
       "\n",
       "Args:\n",
       "    velocity: The target velocity in m/s.\n",
       "    dt: The time interval over which the vehicle reaches the target velocity.\n",
       "        Defaults to 1.0.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.set_velocity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57dd1e4e-c919-4ea6-8417-7dc57b4d7ba8",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "770edd59-06ce-47f2-be10-54bfe4ad41cc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# reset gravity, disable AI\n",
    "beamng.env.set_gravity()\n",
    "ego.ai.set_mode(\"disabled\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8bfc6d12-8545-427a-8675-6715592aaf3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "waypoints = scenario.find_waypoints()  # get a list of locations from the simulation\n",
    "waypoints = {w.name: w for w in waypoints}\n",
    "\n",
    "ego.teleport(\n",
    "    waypoints[\"city_east_bridge1_b\"].pos, rot_quat=(0.0011, 0.0315, 0.9995, -0.0096)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437b2fb7-7e0d-434e-b5b3-101bd73a689c",
   "metadata": {},
   "source": [
    "If we need to teleport a moving vehicle to some position and keep it moving, we set the `reset` argument of `Vehicle.teleport` to `False`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "78e5b85f-4013-4660-83d7-1e43985e7b4e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# get the vehicle moving\n",
    "ego.set_shift_mode(\"arcade\")\n",
    "ego.control(throttle=0.1)\n",
    "ego.set_velocity(10)\n",
    "ego.sensors.poll()\n",
    "\n",
    "# wait some time\n",
    "time.sleep(2.0)\n",
    "\n",
    "# teleport the vehicle and enable AI again\n",
    "ego.teleport((244.87, -926.57, 251.89), ego.state[\"rotation\"], reset=False)\n",
    "ego.ai.set_mode(\"span\")\n",
    "ego.ai.drive_in_lane(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd2b943e-a09c-49d1-9e6d-3aec5103f344",
   "metadata": {},
   "source": [
    "## Traffic\n",
    "\n",
    "To enable traffic, we use the `traffic.spawn` function. With the traffic, we are no longer alone in this simulation!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13dbb455-4442-4ef8-a288-10954138509d",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "64c240de-a285-4b78-b912-227f604c7e9d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m\n",
       "\u001b[0mbeamng\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtraffic\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mspawn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mmax_amount\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpolice_ratio\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mextra_amount\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mparked_amount\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Enables traffic simulation with freshly spawned vehicles.\n",
       "\n",
       "Args:\n",
       "    max_amount: The maximum allowed vehicles to spawn. If None, defaults to in-game settings.\n",
       "    police_ratio: A number between 0.0 and 1.0 indicating the ratio of police vehicles in the traffic.\n",
       "    extra_amount: The maximum amount of inactive vehicles to spawn and swap in and out of the traffic system.\n",
       "                  If None, defaults to in-game settings.\n",
       "    parked_amount: The maximum amount of parked vehicles to spawn. If None, defaults to in-game settings.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\api\\beamng\\traffic.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?beamng.traffic.spawn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "61462d78-78a6-48d1-be13-02384926af37",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mswitch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Switches the simulator to this vehicle. This means that the simulator's main camera,\n",
       "inputs by the user, and so on will all focus on this vehicle from now on.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\vehicle.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.switch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e76e931b-91dc-496b-a68f-8d10ec47ba35",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "034eefe6-9a44-4e3a-9df3-6da76e0b9356",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "beamng.traffic.spawn(max_amount=10)\n",
    "time.sleep(15)\n",
    "ego.teleport((-696.25, -1330.46, 140.48), rot_quat=(0.0000, 0.0000, 0.8567, -0.5154))\n",
    "ego.switch()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bb41b9c-7060-45aa-9280-ebedf25e3e0a",
   "metadata": {},
   "source": [
    "## Sensors\n",
    "\n",
    "Vehicles can be provided with sensors, which capture the simulation and vehicle state data.\n",
    "There are currently two classes of sensor, which have slightly different APIs.\n",
    "\n",
    "The first class of sensors are our `Automated Sensors`. These sensors are created with parameters to allow them to update automatically in the simulator at a given time, and with a given priority.  This management is needed when we wish to run the simulation with many sensors.  These sensors (with the exception of the accelerometer) can be attached to fixed points on the map, as well as to positions on or relative to vehicles.\n",
    "These sensors can also be set to not update automatically, if desired.  We can poll these sensors in two ways: i) by getting the latest readings which were polled at the set update time for the sensor, or ii) by sending ad-hoc requests for data, which can be used if we only want occasional reading on-the-fly.\n",
    "- Camera (providing colour images, class annotation images, semantic annotation images, and depth images)\n",
    "- LiDAR (providing point cloud and/or annotation colour data)\n",
    "- Ultrasonic Sensor (eg can be used as a parking sensor)\n",
    "- Accelerometer (a tri-axial accelerometer, providing a vehicles acceleration in a local coordinate system)\n",
    "\n",
    "The second class of sensors are not automated currently, and use the older API.  These are polled in an ad-hoc fashion.\n",
    "- IMU (Inertial Measurement Unit)\n",
    "- Electrics\n",
    "- Vehicle state\n",
    "\n",
    "Let's see how we can use these sensors in BeamNGpy. We respawn our vehicle with multiple sensors and get data from them."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16265028-4c29-40d4-b08a-be1a8310fb75",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "26189871-923a-4f8c-a239-8c6f4fd91fbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msensors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mattach\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msensor\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Sensor'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Enters a sensor into this vehicle's map of known sensors and calls the\n",
       "attach-hook of said sensor. The sensor is identified using the given\n",
       "name, which has to be unique among the other sensors of the vehicle.\n",
       "\n",
       "Args:\n",
       "    name: The name of the sensor.\n",
       "    sensor: The sensor to attach to the vehicle.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\sensors.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.sensors.attach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0a0e27c4-0b75-4eb0-b23a-3a47cd42be5d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mego\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msensors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0msensor_names\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Updates the vehicle's sensor readings.\n",
       "\n",
       "Args:\n",
       "    sensor_names: Names of sensors to poll. If none are provided, then all attached sensors\n",
       "                  are polled.\n",
       "\n",
       "Returns:\n",
       "    Nothing. Use ``vehicle.sensors[<sensor_id>][<data_access_id>]`` to\n",
       "    access the polled sensor data.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\vehicle\\sensors.py\n",
       "\u001b[1;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?ego.sensors.poll"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6c21487-9b1f-4bb5-acaa-664446775910",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93980950-7485-49d9-b09f-516356eb095c",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Camera sensor\n",
    "\n",
    "Camera sensor provides visual information about the environment. Colour camera provides the same visuals as the simulation. Annotation camera provides object annotations - every object class is annotated with a different color. Instance camera provides instance annotation - every object instance is annotated with a different color. And the depth camera provides depth information of the environment."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25b14cad-73ad-4772-b61f-85ba60830a0d",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5579f187-4a56-44b6-9742-db5c695fcfa6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mCamera\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mbng\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Vehicle | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
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       "\u001b[0m    \u001b[0mpos\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdir\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mup\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mresolution\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Int2'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m512\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m512\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mfield_of_view_y\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m70\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mnear_far_planes\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float2'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0.05\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m100.0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_using_shared_memory\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_render_colours\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_render_annotations\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_render_instance\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_render_depth\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_depth_inverted\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_visualised\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_streaming\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_static\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_snapping_desired\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_force_inside_triangle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpostprocess_depth\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_dir_world_space\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "An interactive, automated camera sensor, which can produce regular colour images, depth images, or annotation images.\n",
       "This sensor can be attached to a vehicle, or can be fixed to a position in space. The dir and up parameters are used to set the local coordinate system.\n",
       "A requested update rate can be provided, to tell the simulator how often to read measurements for this sensor. If a negative value is provided, the sensor\n",
       "will not update automatically at all. However, ad-hoc polling requests can be sent at any time, even for non-updating sensors.\n",
       "\n",
       "Args:\n",
       "    name: A unique name for this camera sensor.\n",
       "    bng: The BeamNGpy instance, with which to communicate to the simulation.\n",
       "    vehicle: The vehicle to which this sensor should be attached, if any.\n",
       "    requested_update_time: The time which should pass between sensor reading updates, in seconds. This is just a suggestion to the manager.\n",
       "    update_priority: The priority which the sensor should ask for new readings. lowest -> 0, highest -> 1.\n",
       "    pos: (X, Y, Z) Coordinate triplet specifying the position of the sensor, in world space.\n",
       "    dir: (X, Y, Z) Coordinate triplet specifying the forward direction of the sensor.\n",
       "    up: (X, Y, Z) Coordinate triplet specifying the up direction of the sensor.\n",
       "    resolution: (X, Y) The resolution of the sensor images.\n",
       "    field_of_view_y: The sensor vertical field of view parameters.\n",
       "    near_far_planes: (X, Y) The sensor near and far plane distances.\n",
       "    is_using_shared_memory: A flag which indicates if we should use shared memory to send/recieve the sensor readings data.\n",
       "    is_render_colours: A flag which indicates if this sensor should render colour data.\n",
       "    is_render_annotations: A flag which indicates if this sensor should render semantic annotation data.\n",
       "    is_render_instance: A flag which indicates if this sensor should render instance annotation data.\n",
       "    is_render_depth: A flag which indicates if this sensor should render depth data.\n",
       "    is_depth_inverted: A flag which indicates if the depth values should be shown white->black or black->white, as distance increases.\n",
       "    is_visualised: A flag which indicates if this LiDAR sensor should appear visualised or not.\n",
       "    is_streaming: Whether or not to stream the data directly to shared memory (no poll required, for efficiency - BeamNGpy won't block.)\n",
       "    is_static: A flag which indicates whether this sensor should be static (fixed position), or attached to a vehicle.\n",
       "    is_snapping_desired: A flag which indicates whether or not to snap the sensor to the nearest vehicle triangle (not used for static sensors).\n",
       "    is_force_inside_triangle: A flag which indicates if the sensor should be forced inside the nearest vehicle triangle (not used for static sensors).\n",
       "    postprocess_depth: If True, the raw depth data will be postprocessed to better represent values with middle intensity. Defaults to False,\n",
       "                       as the postprocessing is computationally intensive.\n",
       "    is_dir_world_space: Flag which indicates if the direction is provided in world-space coordinates (True), or the default vehicle space (False).\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\camera\\camera.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Camera"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6859091a-b3e9-4263-a746-11c6d9e8dd76",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mCamera\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Gets the most-recent readings for this sensor as processed images.\n",
       "Note: if this sensor was created with a negative update rate, then there may have been no readings taken.\n",
       "\n",
       "Returns:\n",
       "    A dictionary with the values as processed images and the following keys\n",
       "\n",
       "    * ``colour``: The colour data.\n",
       "    * ``annotation``: The semantic annotation data.\n",
       "    * ``depth``: The depth camera data.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\camera\\camera.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Camera.poll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "85f46b06-ade2-4b58-9124-564bd98edff8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mCamera\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_full_poll_request\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'StrDict'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Gets a full camera request (semantic annotation and instance annotation data included).\n",
       "NOTE: this function blocks the simulation until the data request is completed.\n",
       "\n",
       "Returns:\n",
       "    The camera data, as images\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\camera\\camera.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Camera.get_full_poll_request"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d77873b-2ef1-4a4e-b8c0-dbf4b839108e",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3e8aeafc-cfed-4385-858a-6b746891cbfe",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'colour': <PIL.Image.Image image mode=RGBA size=512x512>,\n",
       " 'annotation': <PIL.Image.Image image mode=RGBA size=512x512>,\n",
       " 'instance': None,\n",
       " 'depth': <PIL.Image.Image image mode=L size=512x512>}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "camera = Camera(\n",
    "    \"camera1\",\n",
    "    beamng,\n",
    "    ego,\n",
    "    is_render_instance=True,\n",
    "    is_render_annotations=True,\n",
    "    is_render_depth=True,\n",
    ")\n",
    "time.sleep(2)\n",
    "data = camera.poll()\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5326cd6a-49ee-40dc-93f0-a4c18768bf5b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 2, figsize=(10, 10))\n",
    "[axi.set_axis_off() for axi in ax.ravel()]\n",
    "ax[0, 0].title.set_text(\"Camera\")\n",
    "ax[0, 1].title.set_text(\"Depth\")\n",
    "ax[1, 0].title.set_text(\"Class Annotation\")\n",
    "ax[1, 1].title.set_text(\"Instance Annotation\")\n",
    "\n",
    "for _ in range(10):\n",
    "    data = camera.get_full_poll_request()\n",
    "    ax[0, 0].imshow(np.asarray(data[\"colour\"].convert(\"RGB\")))\n",
    "    ax[0, 1].imshow(np.asarray(data[\"depth\"].convert(\"RGB\")))\n",
    "    ax[1, 0].imshow(np.asarray(data[\"annotation\"].convert(\"RGB\")))\n",
    "    ax[1, 1].imshow(np.asarray(data[\"instance\"].convert(\"RGB\")))\n",
    "    display(fig)\n",
    "    clear_output(wait=True)\n",
    "\n",
    "camera.remove()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5974415-e9dc-4196-a31e-44f0aa677837",
   "metadata": {
    "tags": []
   },
   "source": [
    "### LiDAR\n",
    "\n",
    "Another sensor provided by the simulation is LiDAR. The LiDAR sensor provides 3D point clouds representing the environment as detected by a pulsing laser emitted from the vehicle."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc2bb03d-c7c9-413d-993a-b98c40ccb8b7",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "252356b9-09ae-48cc-860a-e1629c9da6e8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mLidar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mbng\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Vehicle | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrequested_update_time\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mupdate_priority\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpos\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.7\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdir\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mup\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvertical_resolution\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'int'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m64\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvertical_angle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m26.9\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mfrequency\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m20\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mhorizontal_angle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m360\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mmax_distance\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m120\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_rotate_mode\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_360_mode\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_using_shared_memory\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_visualised\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_streaming\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_annotated\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_static\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_snapping_desired\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_force_inside_triangle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_dir_world_space\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "An automated LiDAR sensor, which produces raw LiDAR point clouds, ready for further processing by the user.\n",
       "\n",
       "This sensor runs in various modes, which are chosen using the two flag arguments 'is_rotate_mode' and 'is_360_mode':\n",
       "\n",
       "** MODE I: Full 360 Degrees Mode: **\n",
       "    The LiDAR will return a point cloud covering the full 360 degree sector around the provided 'up' vector, with the chosen parameters.\n",
       "    This mode should be used if fast, 360 degree updates are required.  For fastest results, use shared memory or see the 'stream()' functions.\n",
       "    Note: There is no need to provide a horizontal angle for this mode, since it will be fixed upon instantiation.\n",
       "    Likewise, the direction vector is meaningless when using this mode, since the full 360 degrees will be scanned with every reading.\n",
       "    [For this mode, leave the flags as default or switch is_360_mode=True, is_rotate_mode=False].\n",
       "\n",
       "** MODE II: LFO Mode: **\n",
       "    The LiDAR will operate in a low-frequency rotating mode and provide readings local to the sector at which it currently points.\n",
       "    For best results, the frequency should be in the range [1Hz, 8Hz].  Faster frequencies (on this mode) may cause undersampling in some sectors, so beware!\n",
       "    The horizontal angle defines the aperture of the returns in the currently-facing direction, as the LiDAR spins.\n",
       "    The direction vector will specify the starting direction only, for this mode.\n",
       "    [For this mode, set the flags as follows: is_360_mode=False, is_rotate_mode=True].\n",
       "\n",
       "** MODE III: Static Mode: **\n",
       "    The LiDAR will operate in a fixed static pose relative to the vehicle (ie it doesn't rotate). You can set the horizontal angle and direction and this\n",
       "    will remain so for the lifetime of the sensor.  The horizontal angle is supported in the range [1, 179] degrees (the full hemisphere, basically).\n",
       "    [For this mode, set the flags as follows: is_360_mode=False, is_rotate_mode=False].\n",
       "\n",
       "All three LiDAR modes also support the return of semantic annotations (segmentations).  This can be switched on with the similarly-named flag (see below).\n",
       "\n",
       "Shared memory can be used with all modes, if required.  This will be much faster than sending big LiDAR point clouds over the TCP socket, and is\n",
       "recommended (however, not everyone will be running BeamNGPy on the same machine as BeamNG.Tech, so this may not be an option).  See the provided 'stream()'\n",
       "functions for maximum speed here.\n",
       "\n",
       "This sensor can be attached to a vehicle, or can be fixed to a position in space. The dir and up parameters are used to set the local coordinate system.\n",
       "A requested update rate can be provided, to tell the simulator how often to read measurements for this sensor. If a negative value is provided, the sensor\n",
       "will not update automatically at all. However, ad-hoc polling requests can be sent at any time, even for non-updating sensors.\n",
       "\n",
       "Args:\n",
       "    name: A unique name for this LiDAR sensor.\n",
       "    bng: The BeamNGpy instance, with which to communicate to the simulation.\n",
       "    vehicle: The vehicle to which this sensor should be attached, if any.\n",
       "    requested_update_time: The time which should pass between sensor reading updates, in seconds. This is just a suggestion to the manager.\n",
       "    update_priority: The priority which the sensor should ask for new readings. lowest -> 0, highest -> 1.\n",
       "    pos: (X, Y, Z) coordinate triplet specifying the position of the sensor, in world space.\n",
       "    dir: (X, Y, Z) Coordinate triplet specifying the forward direction of the sensor.\n",
       "    up: (X, Y, Z) Coordinate triplet specifying the up direction of the sensor.\n",
       "    vertical_resolution: The vertical resolution of this LiDAR sensor.\n",
       "    vertical_angle: The vertical angle of this LiDAR sensor, in degrees.\n",
       "    frequency: The frequency of this LiDAR sensor.\n",
       "    horizontal_angle: The horizontal angle of this LiDAR sensor.\n",
       "    max_distance: The maximum distance which this LiDAR sensor will detect, in metres.\n",
       "    is_rotate_mode: Runs the LiDAR sensor in 'LFO rotate'.  Should be used with frequencies in the range [1Hz - 10Hz, or so, for best results].\n",
       "    is_360_mode: Runs the LiDAR sensor in 'Full 360 Degrees' mode. Note: there is no need to provide a horizontal angle for this mode.\n",
       "    is_using_shared_memory: A flag which indicates if we should use shared memory to send/recieve the sensor readings data.\n",
       "    is_visualised: A flag which indicates if this LiDAR sensor should appear visualised or not.\n",
       "    is_streaming: Whether or not to stream the data directly to shared memory (no poll required, for efficiency - BeamNGpy won't block.)\n",
       "    is_annotated: A flag which indicates if this LiDAR sensor should return annotation data instead of distance data.\n",
       "    is_static: A flag which indicates whether this sensor should be static (fixed position), or attached to a vehicle.\n",
       "    is_snapping_desired: A flag which indicates whether or not to snap the sensor to the nearest vehicle triangle (not used for static sensors).\n",
       "    is_force_inside_triangle: A flag which indicates if the sensor should be forced inside the nearest vehicle triangle (not used for static sensors).\n",
       "    is_dir_world_space: Flag which indicates if the direction is provided in world-space coordinates (True), or the default vehicle space (False).\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\lidar.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Lidar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ece8e836-e2de-4093-abce-3906d6226102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mLidar\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'StrDict'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Gets the most-recent readings for this sensor.\n",
       "Note: if this sensor was created with a negative update rate, then there may have been no readings taken.\n",
       "\n",
       "Returns:\n",
       "    A dictionary with the following keys:\n",
       "\n",
       "    * ``pointCloud``: The point cloud readings, as a dictionary of vectors.\n",
       "    * ``colours``: The semantic annotation data, as a dictionary of colours for each corresponding point in the point cloud.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\lidar.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Lidar.poll"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9eaab08d-e233-4ead-8cab-0564c00ab384",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "edd90bb2-c28c-4510-ba2e-057d71e7ba54",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'type': 'Lidar', 'pointCloud': array([0., 0., 0., ..., 0., 0., 0.], dtype=float32), 'colours': array([0, 0, 0, ..., 0, 0, 0], dtype=uint8)}\n"
     ]
    }
   ],
   "source": [
    "lidar = Lidar(\"lidar1\", beamng, ego)\n",
    "time.sleep(2)\n",
    "lidar_data = lidar.poll()\n",
    "print(lidar_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "418275dd-1b26-4915-98f6-24c88696eee8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "lidar.remove()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a81692b5-b4c5-4f56-acee-8d20fddac7e5",
   "metadata": {},
   "source": [
    "### Ultrasonic sensor\n",
    "\n",
    "An ultrasonic sensor measures the distance to a close object using ultrasonic waves and uses the echo-localization principle (for example, a parking sensor)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36014c28-01c3-4626-b160-d11ac4d3d202",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c21f6ed3-43cc-4542-880a-a29e74ad037c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m\n",
       "\u001b[0mUltrasonic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'str'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mbng\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'BeamNGpy'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mvehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Vehicle | None'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrequested_update_time\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mupdate_priority\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mpos\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.7\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mdir\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mup\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float3'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mresolution\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Int2'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m200\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mfield_of_view_y\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m5.7\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mnear_far_planes\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Float2'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m5.1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_roundness\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1.15\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_cutoff_sensitivity\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_shape\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_focus\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.376\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_min_cutoff\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mrange_direct_max_cutoff\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m5.0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0msensitivity\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m3.0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mfixed_window_size\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'float'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_visualised\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_streaming\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_static\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_snapping_desired\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_force_inside_triangle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m    \u001b[0mis_dir_world_space\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'bool'\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
       "\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "An interactive, automated ultrasonic sensor, which produces regular distance measurements, ready for further processing.\n",
       "This sensor can be attached to a vehicle, or can be fixed to a position in space. The dir and up parameters are used to set the local coordinate system.\n",
       "A requested update rate can be provided, to tell the simulator how often to read measurements for this sensor. If a negative value is provided, the sensor\n",
       "will not update automatically at all. However, ad-hoc polling requests can be sent at any time, even for non-updating sensors.\n",
       "\n",
       "Args:\n",
       "    name: A unique name for this ultrasonic sensor.\n",
       "    bng: The BeamNGpy instance, with which to communicate to the simulation.\n",
       "    vehicle: The vehicle to which this sensor should be attached, if any.\n",
       "    requested_update_time: The time which should pass between sensor reading updates, in seconds. This is just a suggestion to the manager.\n",
       "    update_priority: The priority which the sensor should ask for new readings. lowest -> 0, highest -> 1.\n",
       "    pos: (X, Y, Z) Coordinate triplet specifying the position of the sensor, in world space.\n",
       "    dir: (X, Y, Z) Coordinate triplet specifying the forward direction of the sensor.\n",
       "    up: (X, Y, Z) Coordinate triplet specifying the up direction of the sensor.\n",
       "    size: (X, Y) The resolution of the sensor (the size of the depth buffer image in the distance measurement computation).\n",
       "    field_of_view_y: The sensor vertical field of view parameters.\n",
       "    near_far_planes: (X, Y) The sensor near and far plane distances.\n",
       "    range_roundness: the general roudness of the ultrasonic sensor range-shape. Can be negative.\n",
       "    range_cutoff_sensitivity: a cutoff sensitivity parameter for the ultrasonic sensor range-shape.\n",
       "    range_shape: the shape of the ultrasonic sensor range-shape in [0, 1], from conical to circular.\n",
       "    range_focus: the focus parameter for the ultrasonic sensor range-shape.\n",
       "    range_min_cutoff: the minimum cut-off distance for the ultrasonic sensor range-shape. Nothing closer than this will be detected.\n",
       "    range_direct_max_cutoff: the maximum cut-off distance for the ultrasonic sensor range-shape. This parameter is a hard cutoff - nothing\n",
       "        further than this will be detected, although other parameters can also control the max distance.\n",
       "    sensitivity: an ultrasonic sensor sensitivity parameter.\n",
       "    fixed_window_size: an ultrasonic sensor sensitivity parameter.\n",
       "    is_visualised: Whether or not to render the ultrasonic sensor points in the simulator.\n",
       "    is_streaming: Whether or not to stream the data directly to shared memory (no poll required, for efficiency - BeamNGpy won't block.)\n",
       "    is_static: A flag which indicates whether this sensor should be static (fixed position), or attached to a vehicle.\n",
       "    is_snapping_desired: A flag which indicates whether or not to snap the sensor to the nearest vehicle triangle (not used for static sensors).\n",
       "    is_force_inside_triangle: A flag which indicates if the sensor should be forced inside the nearest vehicle triangle (not used for static sensors).\n",
       "    is_dir_world_space: Flag which indicates if the direction is provided in world-space coordinates (True), or the default vehicle space (False).\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\ultrasonic.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Ultrasonic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "79554245-730e-4890-9bc4-faae5503aee3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mUltrasonic\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'StrDict'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Gets the most-recent readings for this sensor.\n",
       "Note: if this sensor was created with a negative update rate, then there may have been no readings taken.\n",
       "\n",
       "Returns:\n",
       "    A dictionary containing the following keys:\n",
       "\n",
       "    distance: the latest distance measurement, in meters.\n",
       "    windowMin: (internal parameter) which indicates the minimum size of the data filtering window used in post-processing. This can usually be ignored.\n",
       "    windowMax: (internal parameter) which indicates the maximum size of the data filtering window used in post-processing. This can usually be ignored.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\ultrasonic.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Ultrasonic.poll"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84b51864-823d-4f5b-8992-81208b93dab3",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "724fd3d8-07c3-4df5-83a1-96131b163a3e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 9999.900390625\n",
      "Distance to obstacle: 2.03637433052063\n",
      "Distance to obstacle: 2.70043683052063\n",
      "Distance to obstacle: 2.27941632270813\n",
      "Distance to obstacle: 2.28185772895813\n",
      "Distance to obstacle: 2.150387763977051\n",
      "Distance to obstacle: 2.13903546333313\n",
      "Distance to obstacle: 2.143552303314209\n",
      "Distance to obstacle: 2.137571096420288\n"
     ]
    }
   ],
   "source": [
    "ultrasonic = Ultrasonic(\"ultrasonic1\", beamng, ego)\n",
    "\n",
    "ego.ai.set_mode(\"disabled\")\n",
    "ego.teleport(pos=(464.23, 1504.52, 139.23), rot_quat=(0, 0, 0, 1), reset=True)\n",
    "ego.set_shift_mode(\"arcade\")\n",
    "ego.control(throttle=0.1)\n",
    "\n",
    "for _ in range(20):\n",
    "    ultrasonic_data = ultrasonic.poll()\n",
    "    print(\"Distance to obstacle:\", ultrasonic_data[\"distance\"])\n",
    "    beamng.step(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "3be3e6cf-fd30-40b2-b346-bccf26392b36",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ultrasonic.remove()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ec29743-ea81-48a1-bf8c-d4836fe357b3",
   "metadata": {},
   "source": [
    "### Other sensors"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62f1df92-8eac-4506-8f25-0f1fd21b3513",
   "metadata": {},
   "source": [
    "These provide differents kinds of measurements of the vehicle and simulation state:\n",
    "- `State`: position, direction and velocity of the vehicle\n",
    "- `IMU`: inertial measurement unit, measures forces and rotational acceleration in the vehicle\n",
    "- `Electrics`: various values provided by the car's electric systems\n",
    "- `Damage`: provided exact data about damage of the vehicle parts in the simulation\n",
    "- `Timer`: provides the relative time since the start of the simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "681f6bde-c481-44b2-859e-3f4f569ac719",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "dd8b87da-34d2-4f22-9de7-c96edc19468b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m \u001b[0mState\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The state sensor monitors general stats of the vehicle, such as position,\n",
       "direction, velocity, etc.\n",
       "\n",
       "It contains the following:\n",
       "    * ``time``: The current simulation time in seconds.\n",
       "    * ``pos``: The vehicle's position as an ``(x, y, z)`` triplet\n",
       "    * ``dir``: The vehicle's direction vector as an ``(x, y, z)`` triplet\n",
       "    * ``up``: The vehicle's up vector as an ``(x, y, z)`` triplet\n",
       "    * ``vel``: The vehicle's velocity along each axis in metres per second as an ``(x, y, z)`` triplet\n",
       "    * ``rotation``: The vehicle's rotation as an ``(x, y, z, w)`` quaternion\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\state.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "30a7bd27-c9ec-46c3-8d05-963e8c15f41f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m \u001b[0mElectrics\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "This sensor is used to retrieve various values made available by the car's\n",
       "eletrics systems. These values include:\n",
       "\n",
       "# TODO: List all the electrics.lua values.\n",
       "- abs (int): ABS state\n",
       "- abs_active (bool):\n",
       "- airspeed (float): Airspeed\n",
       "- airflowspeed (float):\n",
       "- altitude (float): Z axis position\n",
       "- avg_wheel_av (float):\n",
       "- brake (int): Brake value\n",
       "- brake_lights (int):\n",
       "- brake_input (int): Brake input value\n",
       "- check_engine (bool): Check engine light state.\n",
       "- clutch (int): Clutch value\n",
       "- clutch_input (int): Clutch input value\n",
       "- clutch_ratio (int):\n",
       "- driveshaft (float): Driveshaft\n",
       "- engine_load (float):\n",
       "- engine_throttle (int): Engine throttle state\n",
       "- esc (int): ESC state. 0 = not present/inactive, 1 = disabled, Blink = active\n",
       "- esc_active (bool):\n",
       "- exhaust_flow (float):\n",
       "- fog_lights (int): Fog light state\n",
       "- fuel (float): Percentage of fuel remaining.\n",
       "- fuel_capacity (int): Total Fuel Capacity [L].\n",
       "- fuel_volume (float):\n",
       "- gear (int):\n",
       "- gear_a (int): Gear selected in automatic mode.\n",
       "- gear_index (int):\n",
       "- gear_m (int): Gear selected in manual mode.\n",
       "- hazard (int): Hazard light state\n",
       "- hazard_signal (bool):\n",
       "- headlights (int):\n",
       "- highbeam (int): High beam state\n",
       "- horn (int):\n",
       "- ignition (bool): Engine state\n",
       "- left_signal (bool):\n",
       "- lightbar (int): Lightbar state\n",
       "- lights (int): General light state. 1 = low, 2 = high\n",
       "- lowbeam (int): Low beam state\n",
       "- lowfuel (bool): Low fuel indicator\n",
       "- lowhighbeam (int): Low-high beam state\n",
       "- lowpressure (int): Low fuel pressure indicator\n",
       "- oil (int):\n",
       "- oil_temperature (float): Oil temperature [C].\n",
       "- parking (int): Parking lights on/off (not implemented yet)\n",
       "- parkingbrake (float): Parking brake state. 0.5 = halfway on\n",
       "- parkingbrake_input (int): Parking brake input state\n",
       "- radiator_fan_spin (int):\n",
       "- reverse (int): Reverse gear state\n",
       "- right_signal (bool):\n",
       "- rpm (float): Engine RPM\n",
       "- rpmspin (float):\n",
       "- rpm_tacho (float):\n",
       "- running (bool): Engine running state\n",
       "- signal_l (int): Left signal state. 0.5 = halfway to full blink\n",
       "- signal_r (int): Right signal state. 0.5 = halfway to full blink\n",
       "- steering (float): Angle of the steering wheel in degrees.\n",
       "- steering_input (int): Steering input state\n",
       "- tcs (int): TCS state. 0 = not present/inactive, 1 = disabled, Blink = active\n",
       "- tcs_active (bool):\n",
       "- throttle (int): Throttle state\n",
       "- throttle_factor (int):\n",
       "- throttle_input (int): Throttle input state\n",
       "- turnsignal (int): Turn signal value. -1 = Left, 1 = Right,\n",
       "gradually 'fades' between values. Use \"signal_L\" and \"signal_R\" for flashing indicators.\n",
       "- two_step (bool):\n",
       "- water_temperature (float): Water temperature [C].\n",
       "- wheelspeed (float): Wheel speed [m/s].\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\electrics.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Electrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "cbeabcf1-8d46-4814-b0a2-cf0ee166fb0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m \u001b[0mDamage\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The damage sensor retrieves information about how damaged the structure\n",
       "of the vehicle is. It's important to realise that this is a sensor that has\n",
       "no analogue in real life as it returns a perfect knowledge overview of how\n",
       "deformed the vehicle is. It's therefore more of a ground truth than\n",
       "simulated sensor data.\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\damage.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Damage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "19f59f35-9e87-40d9-96f3-476f3ce8390b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mInit signature:\u001b[0m \u001b[0mTimer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m     \n",
       "The timer sensor keeps track of the time that has passed since the\n",
       "simulation started. It provides that information in seconds relative to the\n",
       "scenario start and does not represent something like a day time or date. It\n",
       "properly handles pausing the simulation, meaning the value of the timer\n",
       "sensor does not progress while the simulation is paused.\n",
       "\n",
       "When polled, this sensor provides the time in seconds since the start of\n",
       "the scenario in a dictionary under the ``time`` key.\n",
       "\u001b[1;31mFile:\u001b[0m           c:\\dev\\beamngpy\\src\\beamngpy\\sensors\\timer.py\n",
       "\u001b[1;31mType:\u001b[0m           type\n",
       "\u001b[1;31mSubclasses:\u001b[0m     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Timer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "1ebff646-251c-4a12-b0c6-47add457e75d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[1;31mSignature:\u001b[0m \u001b[0mScenario\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove_vehicle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvehicle\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m'Vehicle'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;34m'None'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Removes the given :class:`.Vehicle`: from this scenario. If the\n",
       "scenario is currently loaded, the vehicle will be despawned.\n",
       "\n",
       "Args:\n",
       "    vehicle: The vehicle to remove.\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\dev\\beamngpy\\src\\beamngpy\\scenario\\scenario.py\n",
       "\u001b[1;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "?Scenario.remove_vehicle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f194eeb1-8153-46ec-b370-322c409d1ed2",
   "metadata": {},
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8ce6b7da-1e50-49b0-90c3-c1f306df4aff",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "scenario.remove_vehicle(ego)\n",
    "ego = Vehicle(\"ego\", model=\"etk800\", color=\"White\", licence=\"PYTHON\")\n",
    "electrics = Electrics()\n",
    "damage = Damage()\n",
    "timer = Timer()\n",
    "\n",
    "ego.sensors.attach(\"electrics\", electrics)\n",
    "ego.sensors.attach(\"damage\", damage)\n",
    "ego.sensors.attach(\"timer\", timer)\n",
    "\n",
    "scenario.add_vehicle(\n",
    "    ego, pos=(-696.25, -1330.46, 140.48), rot_quat=(0.0000, 0.0000, 0.8567, -0.5154)\n",
    ")\n",
    "ego.control(gear=1)\n",
    "ego.ai.set_mode(\"span\")\n",
    "ego.ai.drive_in_lane(True)\n",
    "\n",
    "imu = AdvancedIMU(\"imu\", beamng, ego, gfx_update_time=0.01, is_send_immediately=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "7ecfe81c-3d66-4340-8d5c-542645910ebe",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ego.sensors.poll()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4751cfce-9dbf-47c0-b68f-56bda12f7229",
   "metadata": {},
   "source": [
    "#### State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e26aa0ee-026b-493d-9028-87c516d7b0c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'up': [0.0074703083373606205, -0.018529828637838364, 0.9998003840446472],\n",
       " 'vel': [3.3725709915161133, 1.0400725603103638, 0.0028780384454876184],\n",
       " 'rotation': [-0.008879043161869049,\n",
       "  0.004981805104762316,\n",
       "  -0.7853167653083801,\n",
       "  0.6190106272697449],\n",
       " 'front': [-689.6612449884415, -1328.7114865779877, 141.09074926376343],\n",
       " 'pos': [-691.581647336483, -1329.5002255775034, 140.49982529559202],\n",
       " 'dir': [0.9722800254821777, 0.23379801213741302, -0.0031638022046536207],\n",
       " 'time': 100.11700475530233}"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ego.sensors[\"state\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bf54da2-3336-44ef-8a5b-314ba8b0256a",
   "metadata": {},
   "source": [
    "#### IMU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "6eb51666-f747-46d3-a088-f9c013109d74",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'dirZ': [0.9936841915415046, 0.07207603524925332, -0.08600449187836012],\n",
       " 'mass': 2.794199025431919,\n",
       " 'accSmooth': [0.7477169399866306, 0.7301470232084561, -8.724506010624207],\n",
       " 'dirX': [-0.07077745808569257, 0.9973286650221135, 0.018057833539404225],\n",
       " 'angAccel': [-2.6920722349674717, -0.3991826739334738, -3.1693455530600616],\n",
       " 'pos': [-682.9738345617269, -1307.1511914061591, 145.22422633939993],\n",
       " 'angVelSmooth': [0.015141539406154878,\n",
       "  -0.046572338619720946,\n",
       "  0.42094385060218853],\n",
       " 'time': 105.01900498813484,\n",
       " 'angVel': [0.01315772844730696, -0.05448438788569424, 0.4268599494451685],\n",
       " 'dirY': [0.08707628173068112, -0.011856598949534407, 0.9961310868662363],\n",
       " 'accRaw': [0.37071401449790586, -0.9750244670435054, -7.400014500361956]}"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imu.poll()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7ee17b5-8be6-466b-bb7b-a716be3b4d88",
   "metadata": {},
   "source": [
    "#### Electrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "08b4966e-a1eb-46c7-a051-c8d2f3a7e0f2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'lowhighbeam_signal_L': 0.0,\n",
       " 'hasESC': 1.0,\n",
       " 'lowhighbeam_signal_R': 0.0,\n",
       " 'wheelspeed': 3.5134394120688492,\n",
       " 'horn': 0.0,\n",
       " 'isYCBrakeActive': 0.0,\n",
       " 'lowpressure': 0.0,\n",
       " 'oil': 0.0,\n",
       " 'virtualAirspeed': 3.588113528053052,\n",
       " 'running': True,\n",
       " 'parking': 0.0,\n",
       " 'steering': 116.46030433207733,\n",
       " 'gear': 'D',\n",
       " 'turboBoost': -3.4999999999998437,\n",
       " 'boostMax': 26.509999999998815,\n",
       " 'turboRpmRatio': 0.0,\n",
       " 'smoothShiftLogicAV': 29.49897424420143,\n",
       " 'esc': 0.0,\n",
       " 'hoodLatchCoupler_notAttached': 0.0,\n",
       " 'throttle': 0.057985633322666444,\n",
       " ...}"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ego.sensors[\"electrics\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ec49069-49d9-4b76-92e0-081bd4afb0b7",
   "metadata": {},
   "source": [
    "#### Damage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "9563954b-bb3e-41f6-815a-128b27f73eeb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'lowpressure': False,\n",
       " 'deform_group_damage': {'mainEngine_accessories': {'invMaxEvents': 0.001,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1000.0,\n",
       "   'eventCount': 0.0},\n",
       "  'mainEngine_piping': {'invMaxEvents': 0.0008333333333333335,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1199.9999999999998,\n",
       "   'eventCount': 0.0},\n",
       "  'frontflashers_break': {'invMaxEvents': 0.0007142857142857144,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1399.9999999999998,\n",
       "   'eventCount': 0.0},\n",
       "  'wheelaxleRL': {'invMaxEvents': 0.01,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 100.0,\n",
       "   'eventCount': 0.0},\n",
       "  'suspensionF': {'invMaxEvents': 0.0025000000000000005,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 399.99999999999994,\n",
       "   'eventCount': 0.0},\n",
       "  'mainEngine_turbo': {'invMaxEvents': 0.000588235294117647,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1700.0,\n",
       "   'eventCount': 0.0},\n",
       "  'wheelaxleRR': {'invMaxEvents': 0.01,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 100.0,\n",
       "   'eventCount': 0.0},\n",
       "  'doorglass_FL_break': {'invMaxEvents': 0.0015151515151515154,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 659.9999999999999,\n",
       "   'eventCount': 0.0},\n",
       "  'fendersignal_R_break': {'invMaxEvents': 0.0007692307692307693,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1299.9999999999998,\n",
       "   'eventCount': 0.0},\n",
       "  'display_break': {'invMaxEvents': 0.0010204081632653062,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 979.9999999999999,\n",
       "   'eventCount': 0.0},\n",
       "  'radtube_break': {'invMaxEvents': 0.002,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 499.99999999999994,\n",
       "   'eventCount': 0.0},\n",
       "  'mainEngine_intercooler': {'invMaxEvents': 0.007692307692307693,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 130.0,\n",
       "   'eventCount': 0.0},\n",
       "  'windshield_break': {'invMaxEvents': 0.0001904761904761905,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 5249.999999999999,\n",
       "   'eventCount': 0.0},\n",
       "  'oilpan_damage': {'invMaxEvents': 0.00125,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 800.0,\n",
       "   'eventCount': 0.0},\n",
       "  'tailgateglass_break': {'invMaxEvents': 0.0011111111111111113,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 899.9999999999999,\n",
       "   'eventCount': 0.0},\n",
       "  'steeringF': {'invMaxEvents': 0.0033333333333333335,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 300.0,\n",
       "   'eventCount': 0.0},\n",
       "  'doorglass_RR_break': {'invMaxEvents': 0.0011363636363636365,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 879.9999999999999,\n",
       "   'eventCount': 0.0},\n",
       "  'driveshaft': {'invMaxEvents': 0.01,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 100.0,\n",
       "   'eventCount': 0.0},\n",
       "  'mainEngine_intake': {'invMaxEvents': 0.0007692307692307693,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 1299.9999999999998,\n",
       "   'eventCount': 0.0},\n",
       "  'doorglass_RL_break': {'invMaxEvents': 0.0025000000000000005,\n",
       "   'damage': 0.0,\n",
       "   'maxEvents': 399.99999999999994,\n",
       "   'eventCount': 0.0},\n",
       "  ...},\n",
       " 'type': 'Damage',\n",
       " 'damage': 0.0,\n",
       " 'part_damage': [],\n",
       " 'damage_ext': 0.0}"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ego.sensors[\"damage\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29b585ef-5c5b-41f0-818d-64b47f8a149e",
   "metadata": {},
   "source": [
    "#### Timer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "40e047cb-979c-4561-9319-d1b942599607",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'time': 98.0990023240447}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ego.sensors[\"timer\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ec4cc22-32fd-4ee4-99e6-6ccd1cd86428",
   "metadata": {},
   "source": [
    "### Where next"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "506acb22-16eb-468f-a3ad-e0015084aa38",
   "metadata": {},
   "source": [
    "And this is the end of the quick overview of BeamNGpy features! If you want to see more examples, please follow the [example guide](https://github.com/BeamNG/BeamNGpy/blob/master/examples/README.md)."
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}