MakeOld.py

# Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-License-Identifier: MPL-2.0
# This file is part of Grid2Op, Grid2Op a testbed platform to model sequential decision making in power systems.

import os
import warnings
import pkg_resources

from grid2op.Environment import Environment
from grid2op.Backend import Backend, PandaPowerBackend
from grid2op.Parameters import Parameters
from grid2op.Chronics import ChronicsHandler, Multifolder, ChangeNothing
from grid2op.Chronics import GridStateFromFile, GridStateFromFileWithForecasts, GridValue
from grid2op.Action import BaseAction, TopologyAction, TopologyAndDispatchAction, DontAct
from grid2op.Exceptions import *
from grid2op.Observation import CompleteObservation, BaseObservation
from grid2op.Reward import BaseReward, L2RPNReward, RedispReward
from grid2op.Rules import BaseRules, AlwaysLegal, DefaultRules
from grid2op.VoltageControler import ControlVoltageFromFile
from grid2op.Opponent import BaseOpponent

from grid2op.Chronics.Settings_L2RPN2019 import L2RPN2019_CASEFILE, L2RPN2019_DICT_NAMES, ReadPypowNetData, CASE_14_L2RPN2019_LAYOUT
from grid2op.Chronics.Settings_5busExample import EXAMPLE_CHRONICSPATH, EXAMPLE_CASEFILE, CASE_5_GRAPH_LAYOUT
from grid2op.Chronics.Settings_case14_test import case14_test_CASEFILE, case14_test_CHRONICSPATH, case14_test_TH_LIM
from grid2op.Chronics.Settings_case14_redisp import case14_redisp_CASEFILE, case14_redisp_CHRONICSPATH, case14_redisp_TH_LIM
from grid2op.Chronics.Settings_case14_realistic import case14_real_CASEFILE, case14_real_CHRONICSPATH, case14_real_TH_LIM
from grid2op.MakeEnv.get_default_aux import _get_default_aux


data_folder = pkg_resources.resource_filename("grid2op", "data")
CASE_14_FILE = os.path.abspath(os.path.join(data_folder, "rte_case14_redisp", "grid.json"))
CHRONICS_FODLER = os.path.abspath(os.path.join(data_folder, "rte_case14_redisp", "chronics", "0"))
CHRONICS_MLUTIEPISODE = os.path.join(data_folder, "rte_case14_redisp", "chronics")

NAMES_CHRONICS_TO_BACKEND = {"loads": {"2_C-10.61": 'load_1_0', "3_C151.15": 'load_2_1',
                                       "14_C63.6": 'load_13_2', "4_C-9.47": 'load_3_3',
                                       "5_C201.84": 'load_4_4',
                                       "6_C-6.27": 'load_5_5', "9_C130.49": 'load_8_6',
                                       "10_C228.66": 'load_9_7',
                                       "11_C-138.89": 'load_10_8', "12_C-27.88": 'load_11_9',
                                       "13_C-13.33": 'load_12_10'},
                             "lines": {'1_2_1': '0_1_0', '1_5_2': '0_4_1', '9_10_16': '8_9_2',
                                       '9_14_17': '8_13_3',
                                       '10_11_18': '9_10_4', '12_13_19': '11_12_5', '13_14_20': '12_13_6',
                                       '2_3_3': '1_2_7', '2_4_4': '1_3_8', '2_5_5': '1_4_9',
                                       '3_4_6': '2_3_10',
                                       '4_5_7': '3_4_11', '6_11_11': '5_10_12', '6_12_12': '5_11_13',
                                       '6_13_13': '5_12_14', '4_7_8': '3_6_15', '4_9_9': '3_8_16',
                                       '5_6_10': '4_5_17',
                                       '7_8_14': '6_7_18', '7_9_15': '6_8_19'},
                             "prods": {"1_G137.1": 'gen_0_4', "3_G36.31": "gen_2_1", "6_G63.29": "gen_5_2",
                                       "2_G-56.47": "gen_1_0", "8_G40.43": "gen_7_3"},
                             }

ALLOWED_KWARGS_MAKE = {"param", "backend", "observation_class", "gamerules_class", "chronics_path", "reward_class",
                       "action_class", "grid_path", "names_chronics_to_backend", "data_feeding_kwargs",
                       "chronics_class", "volagecontroler_class", "other_rewards",
                       'opponent_action_class', "opponent_class", "opponent_init_budget"}

ERR_MSG_KWARGS = {
    "backend": "The backend of the environment (keyword \"backend\") must be an instance of grid2op.Backend",
    "observation_class": "The type of observation of the environment (keyword \"observation_class\")" \
    " must be a subclass of grid2op.BaseObservation",
    "param": "The parameters of the environment (keyword \"param\") must be an instance of grid2op.Parameters",
    "gamerules_class": "The type of rules of the environment (keyword \"gamerules_class\")" \
    " must be a subclass of grid2op.BaseRules",
    "reward_class": "The type of reward in the environment (keyword \"reward_class\") must be a subclass of grid2op.BaseReward",
    "action_class": "The type of action of the environment (keyword \"action_class\") must be a subclass of grid2op.BaseAction",
    "data_feeding_kwargs": "The argument to build the data generation process [chronics]" \
    "  (keyword \"data_feeding_kwargs\") should be a dictionnary.",
    "chronics_class": "The argument to build the data generation process [chronics] (keyword \"chronics_class\")" \
    " should be a class that inherit grid2op.Chronics.GridValue.",
    "chronics_handler": "The argument to build the data generation process [chronics] (keyword \"data_feeding\")" \
    " should be a class that inherit grid2op.ChronicsHandler.ChronicsHandler.",
    "voltagecontroler_class": "The argument to build the online controler for chronics (keyword \"volagecontroler_class\")" \
    " should be a class that inherit grid2op.VoltageControler.ControlVoltageFromFile.",
    "names_chronics_to_grid": "The converter between names (keyword \"names_chronics_to_backend\") should be a dictionnary.",
    "other_rewards": "The argument to build the online controler for chronics (keyword \"other_rewards\") "
                     "should be dictionnary.",
    "opponent_action_class": "The argument used to build the \"opponent_action_class\" should be a class that "
                             "inherit from \"BaseAction\"",
    "opponent_class": "The argument used to build the \"opponent_class\" should be a class that "
                             "inherit from \"BaseOpponent\"",
    "opponent_init_budget": "The initial budget of the opponent \"opponent_init_budget\" should be a float",
    "chronics_path": "The path where the data is located (keyword \"chronics_path\") should be a string.",
    "grid_path": "The path where the grid is located (keyword \"grid_path\") should be a string."
}


def make_old(name_env="case14_realistic", **kwargs):
    """
    .. warning:: /!\\\\ Internal, do not use unless you know what you are doing /!\\\\

    (DEPRECATED) This function is a shortcut to rapidly create some (pre defined) environments within the grid2op Framework.

    For now, only the environment corresponding to the IEEE "case14" powergrid, with some pre defined chronics
    is available.

    Other environments, with different powergrids will be made available in the future.

    It mimic the ``gym.make`` function.

    Parameters
    ----------
    name_env: ``str``
        Name of the environment to create.

    param: ``grid2op.Parameters.Parameters``, optional
        Type of parameters used for the Environment. Parameters defines how the powergrid problem is cast into an
        markov decision process, and some internal

    backend: ``grid2op.Backend.Backend``, optional
        The backend to use for the computation. If provided, it must be an instance of :class:`grid2op.Backend.Backend`.

    action_class: ``type``, optional
        Type of BaseAction the BaseAgent will be able to perform.
        If provided, it must be a subclass of :class:`grid2op.BaseAction.BaseAction`

    observation_class: ``type``, optional
        Type of BaseObservation the BaseAgent will receive.
        If provided, It must be a subclass of :class:`grid2op.BaseAction.BaseObservation`

    reward_class: ``type``, optional
        Type of reward signal the BaseAgent will receive.
        If provided, It must be a subclass of :class:`grid2op.BaseReward.BaseReward`

    gamerules_class: ``type``, optional
        Type of "Rules" the BaseAgent need to comply with. Rules are here to model some operational constraints.
        If provided, It must be a subclass of :class:`grid2op.RulesChecker.BaseRules`

    grid_path: ``str``, optional
        The path where the powergrid is located.
        If provided it must be a string, and point to a valid file present on the hard drive.

    data_feeding_kwargs: ``dict``, optional
        Dictionnary that is used to build the `data_feeding` (chronics) objects.

    chronics_class: ``type``, optional
        The type of chronics that represents the dynamics of the Environment created. Usually they come from different
        folders.

    data_feeding: ``type``, optional
        The type of chronics handler you want to use.

    chronics_path: ``str``
        Path where to look for the chronics dataset.

    volagecontroler_class: ``type``, optional
        The type of :class:`grid2op.VoltageControler.VoltageControler` to use, it defaults to

    other_rewards: ``dict``, optional
        Dictionnary with other rewards we might want to look at at during training. It is given as a dictionnary with
        keys the name of the reward, and the values a class representing the new variables.

    Returns
    -------
    env: :class:`grid2op.Environment.Environment`
        The created environment.
    """

    warnings.warn("make_old is deprecated. Please consider using make instead")
    for el in kwargs:
        if not el in ALLOWED_KWARGS_MAKE:
            raise EnvError("Unknown keyword argument \"{}\" used to create an Environement. "
                           "No Environment will be created. "
                           "Accepted keyword arguments are {}".format(el, sorted(ALLOWED_KWARGS_MAKE)))

    # first extract parameters that doesn't not depend on the powergrid

    ## the parameters of the game, thermal limits threshold, simulate cascading failure, powerflow mode etc. (the gamification of the game)
    msg_error = "The parameters of the environment (keyword \"param\") must be an instance of grid2op.Parameters"
    param = _get_default_aux('param', kwargs, defaultClass=Parameters, defaultClassApp=Parameters,
                             msg_error=msg_error)

    ## the backend use, to compute the powerflow
    msg_error = "The backend of the environment (keyword \"backend\") must be an instance of grid2op.Backend"
    backend = _get_default_aux("backend", kwargs, defaultClass=PandaPowerBackend,
                               defaultClassApp=Backend,
                               msg_error=msg_error)

    ## type of observation the agent will receive
    msg_error = "The type of observation of the environment (keyword \"observation_class\")"
    msg_error += " must be a subclass of grid2op.BaseObservation"
    observation_class = _get_default_aux("observation_class", kwargs, defaultClass=CompleteObservation,
                                         defaultClassApp=BaseObservation,
                                         msg_error=msg_error,
                                         isclass=True)

    ## type of rules of the game (mimic the operationnal constraints)
    msg_error = "The path where the data is located (keyword \"chronics_path\") should be a string."
    chronics_path = _get_default_aux("chronics_path", kwargs,
                                     defaultClassApp=str, defaultinstance='',
                                     msg_error=msg_error)

    # bulid the default parameters for each case file
    data_feeding_default_class = ChronicsHandler
    gamerules_class = AlwaysLegal
    defaultinstance_chronics_kwargs = {}
    if name_env.lower() == "case14_fromfile":
        default_grid_path = CASE_14_FILE
        if chronics_path == '':
            chronics_path = CHRONICS_MLUTIEPISODE

        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": GridStateFromFileWithForecasts}
        default_name_converter = {}
        default_action_class = TopologyAction
        default_reward_class = L2RPNReward
    elif name_env.lower() == "l2rpn_2019":
        warnings.warn("You are using the \"l2rpn_2019\" environmnet, which will be remove from this package in "
                      "future versions. Please use \"make_new\" to download the real l2rpn dataset.")
        if chronics_path == '':
            msg_error = "Default chronics (provided in this package) cannot be used with the environment "
            msg_error += "\"l2rpn_2019\". Please download the training data using either the method described in" \
                         "Grid2Op/l2rpn_2019/README.md (if you downloaded the github repository) or\n" \
                         "running the command line script (in a terminal):\n" \
                         "python -m grid2op.download --name \"l2rpn_2019\" --path_save PATH\WHERE\YOU\WANT\TO\DOWNLOAD"
            raise EnvError(msg_error)
        default_grid_path = L2RPN2019_CASEFILE
        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": ReadPypowNetData}
        default_name_converter = L2RPN2019_DICT_NAMES
        default_action_class = TopologyAction
        default_reward_class = L2RPNReward
        gamerules_class = DefaultRules
    elif name_env.lower() == "case5_example":
        if chronics_path == '':
            chronics_path = EXAMPLE_CHRONICSPATH

        default_grid_path = EXAMPLE_CASEFILE
        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": GridStateFromFileWithForecasts}
        default_name_converter = {}
        default_action_class = TopologyAction
        default_reward_class = L2RPNReward
        gamerules_class = DefaultRules
    elif name_env.lower() == "case14_test":
        if chronics_path == '':
            chronics_path = case14_test_CHRONICSPATH
            warnings.warn("Your are using a case designed for testing purpose. Consider using the \"case14_redisp\" "
                          "environment instead.")

        default_grid_path = case14_test_CASEFILE
        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": GridStateFromFileWithForecasts}
        default_name_converter = {}
        default_action_class = TopologyAndDispatchAction
        default_reward_class = RedispReward
        gamerules_class = DefaultRules
    elif name_env.lower() == "case14_redisp":
        if chronics_path == '':
            chronics_path = case14_redisp_CHRONICSPATH
            warnings.warn("Your are using only 2 chronics for this environment. More can be download by running, "
                          "from a command line:\n"
                          "python -m grid2op.download --name \"case14_redisp\" "
                          "--path_save PATH\WHERE\YOU\WANT\TO\DOWNLOAD\DATA")

        default_grid_path = case14_redisp_CASEFILE
        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": GridStateFromFileWithForecasts}
        default_name_converter = {}
        default_action_class = TopologyAndDispatchAction
        default_reward_class = RedispReward
        gamerules_class = DefaultRules
    elif name_env.lower() == "case14_realistic":
        if chronics_path == '':
            chronics_path = case14_real_CHRONICSPATH
            warnings.warn("Your are using only 2 chronics for this environment. More can be download by running, "
                          "from a command line:\n"
                          "python -m grid2op.download --name \"case14_realistic\" "
                          "--path_save PATH\WHERE\YOU\WANT\TO\DOWNLOAD\DATA")

        default_grid_path = case14_real_CASEFILE
        defaultinstance_chronics_kwargs = {"chronicsClass": Multifolder, "path": chronics_path,
                                           "gridvalueClass": GridStateFromFileWithForecasts}
        default_name_converter = {}
        default_action_class = TopologyAndDispatchAction
        default_reward_class = RedispReward
        gamerules_class = DefaultRules
    elif name_env.lower() == "blank":
        default_name_converter = {}
        default_grid_path = ""
        default_action_class = TopologyAction
        default_reward_class = L2RPNReward
        gamerules_class = AlwaysLegal
    else:
        raise UnknownEnv("Unknown Environment named \"{}\". Current known environments are \"case14_fromfile\" "
                         "(default), \"case5_example\", \"case14_redisp\", \"case14_realistic\" "
                         "and \"l2rpn_2019\"".format(name_env))

    if "chronicsClass" not in defaultinstance_chronics_kwargs:
        defaultinstance_chronics_kwargs["chronicsClass"] = ChangeNothing

    # extract powergrid dependant parameters
    ## type of rules of the game (mimic the operationnal constraints)
    msg_error = "The type of rules of the environment (keyword \"gamerules_class\")"
    msg_error += " must be a subclass of grid2op.BaseRules"
    gamerules_class = _get_default_aux("gamerules_class", kwargs, defaultClass=gamerules_class,
                                       defaultClassApp=BaseRules,
                                       msg_error=msg_error,
                                       isclass=True)

    ## type of reward the agent will receive
    msg_error = "The type of observation of the environment (keyword \"reward_class\")"
    msg_error += " must be a subclass of grid2op.BaseReward"
    reward_class = _get_default_aux("reward_class", kwargs, defaultClass=default_reward_class,
                                    defaultClassApp=BaseReward,
                                    msg_error=msg_error,
                                    isclass=True)

    ## type of action the BaseAgent can perform
    msg_error = "The type of action of the environment (keyword \"action_class\") must be a subclass of grid2op.BaseAction"
    action_class = _get_default_aux("action_class", kwargs, defaultClass=default_action_class,
                                    defaultClassApp=BaseAction,
                                    msg_error=msg_error,
                                    isclass=True)

    ## the powergrid path to use
    msg_error = "The path where the grid is located (keyword \"grid_path\") should be a string."
    grid_path = _get_default_aux("grid_path", kwargs,
                                 defaultClassApp=str, defaultinstance=default_grid_path,
                                 msg_error=msg_error)

    ##
    msg_error = "The converter between names (keyword \"names_chronics_to_backend\") should be a dictionnary."
    names_chronics_to_backend = _get_default_aux("names_chronics_to_backend", kwargs,
                                 defaultClassApp=dict, defaultinstance=default_name_converter,
                                 msg_error=msg_error)

    ## the chronics to use
    ### the arguments used to build the data, note that the arguments must be compatible with the chronics class
    msg_error = "The argument to build the data generation process [chronics] (keyword \"data_feeding_kwargs\")"
    msg_error += " should be a dictionnary."
    data_feeding_kwargs = _get_default_aux("data_feeding_kwargs", kwargs,
                                           defaultClassApp=dict,
                                           defaultinstance=defaultinstance_chronics_kwargs,
                                           msg_error=msg_error)
    for el in defaultinstance_chronics_kwargs:
        if not el in data_feeding_kwargs:
            data_feeding_kwargs[el] = defaultinstance_chronics_kwargs[el]

    ### the chronics generator
    msg_error = "The argument to build the data generation process [chronics] (keyword \"chronics_class\")"
    msg_error += " should be a class that inherit grid2op.ChronicsHandler.GridValue."
    chronics_class_used = _get_default_aux("chronics_class", kwargs,
                                           defaultClassApp=GridValue,
                                           defaultClass=data_feeding_kwargs["chronicsClass"],
                                           msg_error=msg_error,
                                           isclass=True)
    data_feeding_kwargs["chronicsClass"] = chronics_class_used

    ### the chronics generator
    msg_error = "The argument to build the data generation process [chronics] (keyword \"data_feeding\")"
    msg_error += " should be a class that inherit grid2op.ChronicsHandler.ChronicsHandler."
    data_feeding = _get_default_aux("data_feeding", kwargs,
                                    defaultClassApp=ChronicsHandler,
                                    defaultClass=data_feeding_default_class,
                                    build_kwargs=data_feeding_kwargs,
                                    msg_error=msg_error)

    ### controler for voltages
    msg_error = "The argument to build the online controler for chronics (keyword \"volagecontroler_class\")"
    msg_error += " should be a class that inherit grid2op.VoltageControler.ControlVoltageFromFile."
    volagecontroler_class = _get_default_aux("volagecontroler_class", kwargs,
                                             defaultClassApp=ControlVoltageFromFile,
                                             defaultClass=ControlVoltageFromFile,
                                             msg_error=msg_error,
                                             isclass=True)

    ### other rewards
    msg_error = "The argument to build the online controler for chronics (keyword \"other_rewards\")"
    msg_error += " should be dictionnary."
    other_rewards = _get_default_aux("other_rewards", kwargs,
                                     defaultClassApp=dict,
                                     defaultinstance={},
                                     msg_error=msg_error,
                                     isclass=False)

    # Opponent
    opponent_action_class = _get_default_aux("opponent_action_class",
                                             kwargs,
                                             defaultClassApp=BaseAction,
                                             defaultClass=DontAct,
                                             msg_error=ERR_MSG_KWARGS["opponent_action_class"],
                                             isclass=True)
    opponent_class = _get_default_aux("opponent_class",
                                      kwargs,
                                      defaultClassApp=BaseOpponent,
                                      defaultClass=BaseOpponent,
                                      msg_error=ERR_MSG_KWARGS["opponent_class"],
                                      isclass=True)
    opponent_init_budget = _get_default_aux("opponent_init_budget", kwargs,
                                            defaultClassApp=float,
                                            defaultinstance=0.,
                                            msg_error=ERR_MSG_KWARGS["opponent_init_budget"],
                                            isclass=False)
    if not os.path.exists(grid_path):
        raise EnvError("There is noting at \"{}\" where the powergrid should be located".format(
            os.path.abspath(grid_path)))

    env = Environment(init_grid_path=grid_path,
                      chronics_handler=data_feeding,
                      backend=backend,
                      parameters=param,
                      names_chronics_to_backend=names_chronics_to_backend,
                      actionClass=action_class,
                      observationClass=observation_class,
                      rewardClass=reward_class,
                      legalActClass=gamerules_class,
                      voltagecontrolerClass=volagecontroler_class,
                      other_rewards=other_rewards,
                      opponent_action_class=opponent_action_class,
                      opponent_class=opponent_class,
                      opponent_init_budget=opponent_init_budget,
                      name=name_env
                      )

    # update the thermal limit if any
    if name_env.lower() == "case14_test":
        env.set_thermal_limit(case14_test_TH_LIM)
        env.attach_layout(CASE_14_L2RPN2019_LAYOUT)
    elif name_env.lower() == "case14_redisp":
        env.set_thermal_limit(case14_redisp_TH_LIM)
        env.attach_layout(CASE_14_L2RPN2019_LAYOUT)
    elif name_env.lower() == "case14_realistic":
        env.set_thermal_limit(case14_real_TH_LIM)
        env.attach_layout(CASE_14_L2RPN2019_LAYOUT)
    elif name_env.lower() == "l2rpn_2019":
        env.attach_layout(CASE_14_L2RPN2019_LAYOUT)
    elif name_env.lower() == "case5_example":
        env.attach_layout(CASE_5_GRAPH_LAYOUT)
    return env