Issue #144: TEMP ipynb example

examples/continuous_orbit_manuevers.ipynb

@@ -0,0 +1,185 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Getting Started\n",
+    "This tutorial demonstrates the configuration and use of a simple BSK-RL environment.\n",
+    "BSK-RL and dependencies should already be installed at this point (see [Installation](../install.rst)\n",
+    "if you haven't installed the package yet).\n",
+    "\n",
+    "## Load Modules\n",
+    "In this tutorial, the environment will be created with `gym.make`, so it is necessary to\n",
+    "import the top-level `bsk_rl` module as well as `gym` and `bsk_rl` components."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from functools import partial\n",
+    "from bsk_rl import act, obs, sats, ConstellationTasking\n",
+    "from bsk_rl.sim import dyn, fsw\n",
+    "from bsk_rl.utils.orbital import relative_to_chief, random_orbit\n",
+    "\n",
+    "from Basilisk.architecture import bskLogging\n",
+    "\n",
+    "bskLogging.setDefaultLogLevel(bskLogging.BSK_WARNING)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If no errors were raised, you have a functional installation of `bsk_rl`.\n",
+    "\n",
+    "## Configure the Satellite\n",
+    "[Satellites](../api_reference/sats/index.rst) are configurable agents in the environment.\n",
+    "To make a new environment, start by specifying the [observations](../api_reference/obs/index.rst)\n",
+    "and [actions](../api_reference/act/index.rst) of a satellite type, as well as the underlying\n",
+    "Basilisk [simulation](../api_reference/sim/index.rst) models used by the satellite."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class TumbleSat(sats.Satellite):\n",
+    "    observation_spec = [\n",
+    "        obs.SatProperties(dict(prop=\"r_BN_N\"), dict(prop=\"v_BN_N\")),\n",
+    "    ]\n",
+    "    action_spec = [act.Drift()]\n",
+    "    dyn_type = dyn.ConjunctionDynModel\n",
+    "    fsw_type = fsw.BasicFSWModel\n",
+    "\n",
+    "\n",
+    "class ThrustSat(sats.Satellite):\n",
+    "    observation_spec = [\n",
+    "        obs.SatProperties(dict(prop=\"r_BN_N\"), dict(prop=\"v_BN_N\")),\n",
+    "    ]\n",
+    "    action_spec = [act.MagicThrust(max_dv=100)]\n",
+    "    dyn_type = dyn.ConjunctionDynModel\n",
+    "    fsw_type = fsw.MagicOrbitalManeuverFSWModel\n",
+    "\n",
+    "\n",
+    "sat = ThrustSat(\"Thrusty\")\n",
+    "sat.action_space"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Making the Environment\n",
+    "For this example, we will be using the single-agent [SatelliteTasking](../api_reference/index.rst) \n",
+    "environment. Along with passing the satellite that we configured, the environment takes\n",
+    "a [scenario](../api_reference/scene/index.rst), which defines the environment the\n",
+    "satellite is acting in, and a [rewarder](../api_reference/data/index.rst), which defines\n",
+    "how data collected from the scenario is rewarded."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "env = ConstellationTasking(\n",
+    "    satellites=[\n",
+    "        TumbleSat(\"Tumbler\"),\n",
+    "        ThrustSat(\"Thrust-1\"),\n",
+    "        ThrustSat(\"Thrust-2\"),\n",
+    "    ],\n",
+    "    sat_arg_randomizer=relative_to_chief(\n",
+    "        chief_name=\"Tumbler\",\n",
+    "        chief_orbit=partial(random_orbit, i=None),\n",
+    "        deputy_relative_state={\n",
+    "            \"Thrust-1\": np.array([50, 0, 0, -3, 0, 0]),\n",
+    "            \"Thrust-2\": np.array([-50, 0, 0, 3, 0, 0]),\n",
+    "        },\n",
+    "    ),\n",
+    "    time_limit=5700.0 * 3,\n",
+    "    log_level=\"INFO\",\n",
+    ")\n",
+    "env.action_spaces"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Interacting with the Environment\n",
+    "\n",
+    "First, the environment is reset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "observation, info = env.reset(seed=0)\n",
+    "print(observation)\n",
+    "print(info)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we take the scan action (`action=0`) a few times. This allows for the satellite to\n",
+    "settle its attitude in the nadir pointing mode to satisfy imaging conditions. Note that \n",
+    "the logs show little or no data accumulated in the first two steps as it settles, but\n",
+    "achieves 60 reward (corresponding to 60 seconds of imaging) by the third step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for _ in range(20):\n",
+    "    actions = {}\n",
+    "    # for sat in env.satellites:\n",
+    "    #     if sat.requires_retasking:\n",
+    "    #         if isinstance(sat, TumbleSat):\n",
+    "    #             actions[sat.name] = 0\n",
+    "    #         else:\n",
+    "    #             actions[sat.name] = np.concatenate(\n",
+    "    #                 (np.random.uniform(-20, 20, 3), np.random.uniform(0, 200, 1))\n",
+    "    #             )\n",
+    "\n",
+    "    observation, reward, terminated, truncated, info = env.step(actions)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}