{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Usage\n",
    "\n",
    "This example demonstrates the basic usage and interface of a control environment in EPyT-Control."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, HTML\n",
    "display(HTML('<a target=\\\"_blank\\\" href=\\\"https://colab.research.google.com/github/WaterFutures/EPyT-Control/blob/main/docs/examples/basic_usage.ipynb\\\"><img src=\\\"https://colab.research.google.com/assets/colab-badge.svg\\\" alt=\\\"Open In Colab\\\"/></a>'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install epyt-control --quiet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import a pre-defined control environment where the chlorine injection is to be controlled\n",
    "from my_env import SimpleChlorineInjectionEnv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create new instance of the control environment\n",
    "env = SimpleChlorineInjectionEnv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspect the observation space (i.e. input to the agent/controller) by accessing the [observation_space](https://gymnasium.farama.org/api/env/#gymnasium.Env.observation_space) property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(env.observation_space)  # Observations: 34 dimension real-valued vector"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspect the observation space (i.e. input to the agent/controller) by accessing the [action_space](https://gymnasium.farama.org/api/env/#gymnasium.Env.action_space) property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(env.action_space)      # Action: A single scalar between 0 and 10000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reset the environment by calling the [reset()](https://epyt-control.readthedocs.io/en/stable/epyt_control.envs.html#epyt_control.envs.rl_env.RlEnv.reset) function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "obs, _ = env.reset()\n",
    "print(obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Execute some random actions by calling the [step()](https://epyt-control.readthedocs.io/en/stable/epyt_control.envs.html#epyt_control.envs.rl_env.RlEnv.step) function -- note that a random action can be generated by calling the [sample()](https://gymnasium.farama.org/api/spaces/#gymnasium.spaces.Space.sample) function of the environment's [action space](https://gymnasium.farama.org/api/env/#gymnasium.Env.action_space):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run some iterations -- note that autorest=True\n",
    "for _ in range(20):\n",
    "    # Pick a random action\n",
    "    act = env.action_space.sample()\n",
    "\n",
    "    # Apply the action, get a reward (to be maximized) and\n",
    "    # new observations (i.e. sensor readings)\n",
    "    obs, reward, terminated, _, _ = env.step(act)\n",
    "    print(f\"Action: {act}, Reward: {reward}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do not forget to close the environment by calling the [close()](https://epyt-flow.readthedocs.io/en/stable/epyt_flow.gym.html#epyt_flow.gym.scenario_control_env.ScenarioControlEnv.close) function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "env.close()"
   ]
  }
 ],
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