{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Basic Agent Sudy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is recommended to have a look at the [0_basic_functionalities](0_basic_functionalities.ipynb), [1_Observation_Agents](1_Observation_Agents.ipynb), [2_Action_GridManipulation](3_TrainingAnAgent.ipynb) and [3_TrainingAnAgent](3_TrainingAnAgent.ipynb) notebooks before getting into this one." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Objectives**\n", "\n", "In this notebook we will show how to study an Agent. We will use a dummy agent and then look at how to study its behaviour from the saved file.\n", "\n", "This notebook will also show you how to use the Graphical User Interface built for analyzing grid2Op agents, called \"Grid2Viz\".\n", "\n", "It is more than recommended to know how to define an Agent and use a Runner before doing this tutorial!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Evaluate the performance of a simple Agent" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import sys\n", "import grid2op\n", "import copy\n", "import numpy as np\n", "import shutil\n", "import plotly.graph_objects as go\n", "\n", "from tqdm.notebook import tqdm\n", "from grid2op.Agent import PowerLineSwitch\n", "from grid2op.Reward import L2RPNReward\n", "from grid2op.Runner import Runner\n", "from grid2op.Chronics import GridStateFromFileWithForecasts, Multifolder\n", "path_agents = \"study_agent_getting_started\"\n", "max_iter = 30" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the next cell we evaluate the agent \"PowerLineSwitch\" and save the results of this evaluation in the \"study_agent_getting_started\" directory." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/benjamin/Documents/grid2op_dev/getting_started/grid2op/MakeEnv/Make.py:240: UserWarning:\n", "\n", "You are using a development environment. This environment is not intended for training agents.\n", "\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4a9e3dd4b1954a2caf64b552c56627fc", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='episode', max=2.0, style=ProgressStyle(description_width=…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "6b15cef2e47549a7890648334a428cfe", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='episode', max=30.0, style=ProgressStyle(description_width…" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3e1b0575ecdb46ac80e58c749e9ef097", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='episode', max=30.0, style=ProgressStyle(description_width…" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "The results for the evaluated agent are:\n", "\tFor chronics with id 000\n", "\t\t - cumulative reward: 496.772949\n", "\t\t - number of time steps completed: 30 / 30\n", "\tFor chronics with id 001\n", "\t\t - cumulative reward: 515.620117\n", "\t\t - number of time steps completed: 30 / 30\n" ] } ], "source": [ "scoring_function = L2RPNReward\n", "env = grid2op.make(reward_class=L2RPNReward, test=True)\n", "# env.chronics_handler.set_max_iter(max_iter)\n", "shutil.rmtree(os.path.abspath(path_agents), ignore_errors=True)\n", "if not os.path.exists(path_agents):\n", " os.mkdir(path_agents)\n", "\n", "# make a runner for this agent\n", "path_agent = os.path.join(path_agents, \"PowerLineSwitch\")\n", "shutil.rmtree(os.path.abspath(path_agent), ignore_errors=True)\n", "\n", "runner = Runner(**env.get_params_for_runner(),\n", " agentClass=PowerLineSwitch\n", " )\n", "res = runner.run(path_save=path_agent, nb_episode=2, \n", " max_iter=max_iter,\n", " pbar=tqdm)\n", "print(\"The results for the evaluated agent are:\")\n", "for _, chron_id, cum_reward, nb_time_step, max_ts in res:\n", " msg_tmp = \"\\tFor chronics with id {}\\n\".format(chron_id)\n", " msg_tmp += \"\\t\\t - cumulative reward: {:.6f}\\n\".format(cum_reward)\n", " msg_tmp += \"\\t\\t - number of time steps completed: {:.0f} / {:.0f}\".format(nb_time_step, max_ts)\n", " print(msg_tmp)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Looking at the results and understanding the behaviour of the Agent" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The content of the folder is the following:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['000',\n", " 'dict_env_modification_space.json',\n", " '001',\n", " 'dict_action_space.json',\n", " 'dict_observation_space.json']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "os.listdir(path_agent)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can load the actions and observations corresponding to the episode 1 for example, and de-serialize them into proper objects: This is now automatically done with the class `EpisodeData` that can be used as follow:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from grid2op.Episode import EpisodeData\n", "episode_studied = \"001\"\n", "this_episode = EpisodeData.from_disk(path_agent, episode_studied)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspect the actions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can study the agent. For example, let's inspect its actions and see how many powerlines it has disconnected (this is probably not the best thing to do here)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total lines set to connected : 0\n", "Total lines set to disconnected : 0\n", "Total lines changed: 3\n" ] } ], "source": [ "line_disc = 0\n", "line_reco = 0\n", "line_changed = 0\n", "for act in this_episode.actions:\n", " dict_ = act.as_dict()\n", " if \"set_line_status\" in dict_:\n", " line_reco += dict_[\"set_line_status\"][\"nb_connected\"]\n", " line_disc += dict_[\"set_line_status\"][\"nb_disconnected\"]\n", " if \"change_line_status\" in dict_:\n", " line_changed += dict_[\"change_line_status\"][\"nb_changed\"]\n", "print(f'Total lines set to connected : {line_reco}')\n", "print(f'Total lines set to disconnected : {line_disc}')\n", "print(f'Total lines changed: {line_changed}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also wonder how many times this agent acted on the powerline with id $14$, and inspect how many times it changed its status:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total actions on powerline 14 : 1\n" ] } ], "source": [ "id_line_inspected = 13\n", "actions_on_line_14 = 0\n", "for act in this_episode.actions:\n", " dict_ = act.effect_on(line_id=id_line_inspected) # which effect has this action action on the substation with given id\n", " # other objects are: load_id, gen_id, line_id or substation_id\n", " if dict_['change_line_status'] or dict_[\"set_line_status\"] != 0:\n", " actions_on_line_14 += 1\n", "print(f'Total actions on powerline 14 : {actions_on_line_14}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspect the modifications of the environment" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For example, we might want to inspect the number of hazards and maintenances in a total scenario, to have an idea of how difficult it was." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total hazards : 0\n", "Total maintenances : 0\n" ] } ], "source": [ "nb_hazards = 0\n", "nb_maintenance = 0\n", "for act in this_episode.env_actions:\n", " dict_ = act.as_dict() # representation of an action as a dictionnary, see the documentation for more information\n", " if \"nb_hazards\" in dict_:\n", " nb_hazards += 1\n", " if \"nb_maintenance\" in dict_:\n", " nb_maintenance += 1\n", "print(f'Total hazards : {nb_hazards}')\n", "print(f'Total maintenances : {nb_maintenance}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspect the observations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For example, let's look at the consumption of load 1. 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.graph_objects as go\n", "load_id = 1\n", "# extract the data\n", "val_load1 = np.zeros(len(this_episode.observations))\n", "for i, obs in enumerate(this_episode.observations):\n", " dict_ = obs.state_of(load_id=load_id) # which effect has this action action on the substation with id 1\n", " # other objects are: load_id, gen_id, line_id or substation_id\n", " # see the documentation for more information.\n", " val_load1[i] = dict_['p']\n", "\n", "# plot it\n", "fig = go.Figure(data=[go.Scatter(x=[i for i in range(len(val_load1))],\n", " y=val_load1)])\n", "fig.update_layout(title=\"Consumption of load {}\".format(load_id),\n", " xaxis_title=\"Time step\",\n", " yaxis_title=\"Load (MW)\")\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We may also want to plot the power generated by generator 3 (it represents a solar energy source) :" ] }, { "cell_type": "code", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from_ = 3\n", "to_ = 4\n", "found_ids = this_episode.observations.helper.get_lines_id(from_=from_, to_=to_)\n", "line_id = found_ids[0]\n", "\n", "# extract the data\n", "val_l3_4 = np.zeros(len(this_episode.observations))\n", "for i, obs in enumerate(this_episode.observations):\n", " dict_ = obs.state_of(line_id=line_id) # which effect has this action action on the substation with id 1\n", " # other objects are: load_id, gen_id, line_id or substation_id\n", " # see the documentation for more information.\n", " val_l3_4[i] = dict_[\"origin\"]['a']\n", "\n", "# plot it\n", "fig = go.Figure(data=[go.Scatter(x=[i for i in range(len(val_l3_4))],\n", " y=val_l3_4)])\n", "fig.update_layout(title=\"Flow on powerline {} (going from {} to {})\".format(line_id, from_, to_),\n", " xaxis_title=\"Time step\",\n", " yaxis_title=\"Production (MW)\")\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quick display of a grid using an observation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below, you can find an example of how to plot an observation and the underlying powergrid. This is still in development so the appearance will be improved later. It uses plotly and requires the layout of the grid (eg the coordinates of the substations) to be specified.\n", "\n", "Note also that this code is not optimized at all." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ ":9: UserWarning:\n", "\n", "Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n", "\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from grid2op.PlotGrid import PlotMatplot\n", "obs = copy.deepcopy(this_episode.observations[-1])\n", "# and change the topology (just to have something to represent)\n", "obs.topo_vect[3:9] = [2,2,1,1,2,1]\n", "\n", "plot_helper = PlotMatplot(observation_space=this_episode.observation_space, width=900, height=600)\n", "plot_helper._line_bus_radius = 7\n", "fig = plot_helper.plot_obs(obs)\n", "fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Synchronizing Observations and Actions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As stated in the documentation, at row i, we can read the observation at time \"i\" (before he took the action at time \"i\"), and the action at time \"i\". This means that at row i of the numpy arrays, we can see what the agent saw at that time and what action he chose from that observation. We have \"an agent view\".\n", "\n", "In case we want to see the impact of an Action (see the action the agent took and the observation from the environment **after** the action has been taken), it is therefore then necessary to:\n", "\n", "- look at action i\n", "- look at observation i+1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Using the dedicated grid2viz framework\n", "\n", "Grid2viz is a package that has been developped to help you visualize the behaviour of your agent. This will be detailed in the notebook [7_PlottingCapabilities](7_PlottingCapabilities.ipynb)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.2" } }, "nbformat": 4, "nbformat_minor": 2 }