Revert to c6d862a

Author: kingsleynweye

.github/ISSUE_TEMPLATE/bug_report.md

@@ -26,7 +26,6 @@ Please provide detailed steps to reproduce the issue.
 ## Environment
 
 - CityLearn version:
-- Dataset name/link:
 - Operating System:
 - Python version:
 

.github/workflows/pypi_deploy.yml

@@ -1,15 +1,14 @@
 name: Upload Python Package
 
 on:
-  workflow_dispatch:
   release:
     types: [published]
 
 jobs:
   deploy:
 
     environment: pypi 
-    runs-on: ubuntu-24.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
         python-version: [3.11]

.github/workflows/run_tests.yml

@@ -9,7 +9,7 @@ jobs:
   update:
 
     environment: github-pages
-    runs-on: ubuntu-24.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
         python-version: [3.11]

.github/workflows/sphinx.yml

@@ -1 +1 @@
-__version__ = '2.4.2'
+__version__ = '2.3.0'

citylearn/__init__.py

@@ -18,7 +18,7 @@
 from citylearn.citylearn import CityLearnEnv
 from citylearn.data import DataSet, get_settings
 from citylearn.__init__ import __version__
-from citylearn.utilities import FileHandler
+from citylearn.utilities import read_pickle, write_json, write_pickle
 import pandas as pd
 import simplejson as json
 
@@ -291,7 +291,7 @@ def __train(self, episodes: int):
     def __save_agent(self):
         if isinstance(self.agent, CityLearnAgent):
             filepath = os.path.join(self.output_directory, f'{self.simulation_id}-agent.pkl')
-            FileHandler.write_pickle(filepath, self.agent)
+            write_pickle(filepath, self.agent)
 
         else:
             filepath = os.path.join(self.output_directory, f'{self.simulation_id}-agent')
@@ -307,7 +307,7 @@ def __set_agent(self) -> Union[CityLearnAgent, StableBaselines3Agent]:
 
         else:
             if str(self.agent_filepath).endswith('.pkl'):
-                agent = FileHandler.read_pickle(self.agent_filepath)
+                agent = read_pickle(self.agent_filepath)
                 agent.env = self.env
 
             else:
@@ -349,15 +349,15 @@ def evaluate(cls, evaluation_episode_time_steps: Tuple[int, int] = None, **kwarg
         simulator = cls(**kwargs)
         simulator.__evaluate()
         filepath = os.path.join(simulator.output_directory, f'{simulator.simulation_id}-evaluation.json')
-        FileHandler.write_json(filepath, simulator.__get_evaluation_summary())
+        write_json(filepath, simulator.__get_evaluation_summary())
 
     @classmethod
     def train(cls, episodes: int = None, evaluate: bool = None, evaluation_episode_time_steps: Tuple[int, int] = None, save_agent: bool = None, **kwargs):
         simulator = cls(**kwargs)
         episodes = 1 if episodes is None else episodes
         simulator.__train(episodes)
         filepath = os.path.join(simulator.output_directory, f'{simulator.simulation_id}-train.json')
-        FileHandler.write_json(filepath, simulator.__get_training_summary())
+        write_json(filepath, simulator.__get_training_summary())
 
         if save_agent:
             simulator.__save_agent()

citylearn/__main__.py

@@ -33,7 +33,6 @@ def __init__(self, env: CityLearnEnv, **kwargs: Any):
             seconds_per_time_step=self.env.unwrapped.seconds_per_time_step,
             random_seed=self.env.unwrapped.random_seed,
             episode_tracker=self.env.unwrapped.episode_tracker,
-            time_step_ratio=self.env.unwrapped.time_step_ratio
         )
         self.reset()
 

citylearn/agents/base.py

@@ -343,7 +343,7 @@ def action_map(self, action_map: Union[List[Mapping[str, Mapping[int, float]]],
 
             for n in action_names:
                 action_map[n] = {}
-
+                
                 if 'storage' in n:
                     for hour in Building.get_periodic_observation_metadata()['hour']:
                         if 6 <= hour <= 14:
@@ -387,100 +387,4 @@ def action_map(self, action_map: Union[List[Mapping[str, Mapping[int, float]]],
                 else:
                     raise ValueError(f'Unknown action name: {n}')
 
-        HourRBC.action_map.fset(self, action_map)
-
-class BasicElectricVehicleRBC_ReferenceController(BasicRBC): #change the name
-    r"""A rule-based controller that charges EVs to the maximum of the chargers and to the maximum of the battery upon connection.
-
-    The EV battery is charged at the maximum available charging power whenever it is connected.
-
-    Parameters
-    ----------
-    env: CityLearnEnv
-        CityLearn environment.
-
-    Other Parameters
-    ----------------
-    **kwargs: Any
-        Other keyword arguments used to initialize super class.
-    """
-
-    def __init__(self, env: CityLearnEnv, **kwargs: Any):
-        super().__init__(env, **kwargs)
-
-    @HourRBC.action_map.setter
-    def action_map(self, action_map: Union[
-        List[Mapping[str, Mapping[int, float]]], Mapping[str, Mapping[int, float]], Mapping[int, float]]):
-        if action_map is None:
-            action_map = {}
-            action_names = [a_ for a in self.action_names for a_ in a]
-            action_names = list(set(action_names))
-
-            for n in action_names:
-                action_map[n] = {}
-
-                if n == "electrical_storage":
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        if 9 <= hour <= 21:
-                            value = -0.08
-                        elif (1 <= hour <= 8) or (22 <= hour <= 24):
-                            value = 0.091
-                        else:
-                            value = 0.0
-
-                        action_map[n][hour] = value
-
-                elif n == 'cooling_device':
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        if 9 <= hour <= 21:
-                            value = 0.8
-                        elif (1 <= hour <= 8) or (22 <= hour <= 24):
-                            value = 0.4
-                        else:
-                            value = 0.0
-
-                        action_map[n][hour] = value
-
-                elif n == 'heating_device':
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        if 9 <= hour <= 21:
-                            value = 0.4
-                        elif (1 <= hour <= 8) or (22 <= hour <= 24):
-                            value = 0.8
-                        else:
-                            value = 0.0
-
-                        action_map[n][hour] = value
-
-                elif n == 'cooling_or_heating_device':
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        if hour < 7:
-                            value = 0.4
-
-                        elif hour < 21:
-                            value = -0.4
-
-                        else:
-                            value = 0.8
-
-                        action_map[n][hour] = value
-
-                elif "electric_vehicle" in n:
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        value = 1
-                        action_map[n][hour] = value
-
-                elif "dhw_storage" in n:
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        value = 1
-                        action_map[n][hour] = value
-
-                elif "washing_machine" in n:
-                    for hour in Building.get_periodic_observation_metadata()['hour']:
-                        value = 1
-                        action_map[n][hour] = value        
-
-                else:
-                    raise ValueError(f'Unknown action name: {n}')
-
-        HourRBC.action_map.fset(self, action_map)
+        HourRBC.action_map.fset(self, action_map)

citylearn/agents/rbc.py

@@ -153,13 +153,12 @@ class Environment:
     DEFAULT_SECONDS_PER_TIME_STEP = 3600.0
     DEFAULT_RANDOM_SEED_RANGE = (0, 100_000_000)
 
-    def __init__(self, seconds_per_time_step: float = None, random_seed: int = None, episode_tracker: EpisodeTracker = None, time_step_ratio: int = None):
+    def __init__(self, seconds_per_time_step: float = None, random_seed: int = None, episode_tracker: EpisodeTracker = None):
         self.seconds_per_time_step = seconds_per_time_step
         self.__uid = uuid.uuid4().hex
         self.random_seed = random_seed
         self.__time_step = None
         self.episode_tracker = episode_tracker
-        self.time_step_ratio = time_step_ratio
 
     @property
     def uid(self) -> str:
@@ -179,13 +178,6 @@ def episode_tracker(self) -> EpisodeTracker:
         current episode time steps for reading observations from data files."""
 
         return self.__episode_tracker
-    
-    @property
-    def time_step_ratio(self) -> int:
-        """:py:class:`citylearn.base.EpisodeTracker` object used to keep track of 
-        current episode time steps for reading observations from data files."""
-
-        return self.__time_step_ratio
 
     @property
     def time_step(self) -> int:
@@ -221,14 +213,6 @@ def seconds_per_time_step(self, seconds_per_time_step: float):
     @episode_tracker.setter
     def episode_tracker(self, episode_tracker: EpisodeTracker):
         self.__episode_tracker = episode_tracker
-    
-    @time_step_ratio.setter
-    def time_step_ratio(self, time_step_ratio: int):
-        self.__time_step_ratio = time_step_ratio
-
-    @time_step.setter
-    def time_step(self, time_step: int):
-        self.__time_step = time_step    
 
     def get_metadata(self) -> Mapping[str, Any]:
         """Returns general static information."""
@@ -237,8 +221,7 @@ def get_metadata(self) -> Mapping[str, Any]:
             'uid': self.uid,
             'random_seed': self.random_seed,
             'simulation_time_steps': self.episode_tracker.simulation_time_steps,
-            'seconds_per_time_step': self.seconds_per_time_step,
-            'time_step_ratio': self.time_step_ratio,
+            'seconds_per_time_step': self.seconds_per_time_step
         }
 
     def next_time_step(self):