Doors are now seperate

environments/factory/additional/_template/_collections.py

@@ -0,0 +1,38 @@
+from typing import Union
+
+from environments.factory.additional.doors.doors_entities import Door
+from environments.factory.base.registers import EntityCollection
+
+from environments.factory.additional.doors.doors_util import Constants as c
+
+
+class Doors(EntityCollection):
+
+    def __init__(self, *args, indicate_area=False, **kwargs):
+        self.indicate_area = indicate_area
+        self._area_marked = False
+        super(Doors, self).__init__(*args, is_blocking_light=True, can_collide=True, **kwargs)
+
+    _accepted_objects = Door
+
+    def get_near_position(self, position: (int, int)) -> Union[None, Door]:
+        try:
+            return next(door for door in self if position in door.tile.neighboring_floor_pos)
+        except StopIteration:
+            return None
+
+    def tick_doors(self):
+        for door in self:
+            door.tick()
+
+    def as_array(self):
+        if not self._area_marked and self.indicate_area:
+            for door in self:
+                for tile in door.tile.neighboring_floor:
+                    if self._individual_slices:
+                        pass
+                    else:
+                        pos = (0, *tile.pos)
+                    self._lazy_eval_transforms.append((pos, c.ACCESS_DOOR_CELL))
+            self._area_marked = True
+        return super(Doors, self).as_array()

environments/factory/additional/_template/_entities.py

@@ -0,0 +1,71 @@
+from environments.factory.base.objects import Entity
+from environments.factory.additional.doors.doors_util import Constants as c
+
+
+class Template(Entity):
+    """Template for new Entity"""
+
+    # How to define / override properties
+    @property
+    def is_blocking(self):
+        return False
+
+    @property
+    def can_collide(self):
+        return False if self.template_attr else True
+
+    @property
+    def encoding(self):
+        # This is important as it shadow is checked by occupation value
+        return c.CLOSED_DOOR_CELL if self.is_closed else c.OPEN_DOOR_CELL
+
+    @property
+    def str_state(self):
+        return 'open' if self.is_open else 'closed'
+
+    def __init__(self, *args, closed_on_init=True, auto_close_interval=10, indicate_area=False, **kwargs):
+        super(Template, self).__init__(*args, **kwargs)
+        self._state = c.CLOSED_DOOR
+        self.indicate_area = indicate_area
+        self.auto_close_interval = auto_close_interval
+        self.time_to_close = -1
+        if not closed_on_init:
+            self._open()
+
+    def summarize_state(self):
+        state_dict = super().summarize_state()
+        state_dict.update(state=str(self.str_state), time_to_close=int(self.time_to_close))
+        return state_dict
+
+    @property
+    def is_closed(self):
+        return self._state == c.CLOSED_DOOR
+
+    @property
+    def is_open(self):
+        return self._state == c.OPEN_DOOR
+
+    @property
+    def status(self):
+        return self._state
+
+    def use(self):
+        if self._state == c.OPEN_DOOR:
+            self._close()
+        else:
+            self._open()
+
+    def tick(self):
+        if self.is_open and len(self.tile) == 1 and self.time_to_close:
+            self.time_to_close -= 1
+        elif self.is_open and not self.time_to_close and len(self.tile) == 1:
+            self.use()
+
+    def _open(self):
+        self._state = c.OPEN_DOOR
+        self._collection.notify_change_to_value(self)
+        self.time_to_close = self.auto_close_interval
+
+    def _close(self):
+        self._state = c.CLOSED_DOOR
+        self._collection.notify_change_to_value(self)

environments/factory/additional/_template/_util.py

@@ -0,0 +1,31 @@
+
+from typing import NamedTuple
+
+from environments.helpers import Constants as BaseConstants, EnvActions as BaseActions
+
+
+class Constants(BaseConstants):
+    DOOR         = 'Door'   # Identifier of Single-Door Entities.
+    DOORS        = 'Doors'  # Identifier of Door-objects and sets (collections).
+    DOOR_SYMBOL  = 'D'                   # Door identifier for resolving the string based map files.
+
+    ACCESS_DOOR_CELL = 1 / 3  # Access-door-Cell value used in observation
+    OPEN_DOOR_CELL = 2 / 3  # Open-door-Cell value used in observation
+    CLOSED_DOOR_CELL = 3 / 3  # Closed-door-Cell value used in observation
+
+    CLOSED_DOOR         = 'closed'              # Identifier to compare door-is-closed state
+    OPEN_DOOR           = 'open'                # Identifier to compare door-is-open state
+    # ACCESS_DOOR         = 'access'            # Identifier to compare access positions
+
+
+class Actions(BaseActions):
+    USE_DOOR = 'use_door'
+
+
+class RewardsDoor(NamedTuple):
+    USE_DOOR_VALID: float  = -0.00
+    USE_DOOR_FAIL: float   = -0.01
+
+
+class DoorProperties(NamedTuple):
+    indicate_door_area: bool = True            # Wether the door area should be indicated in the agents' observation.

environments/factory/additional/_template/factory_template.py

@@ -0,0 +1,196 @@
+import time
+from typing import List, Union, Dict
+import random
+
+import numpy as np
+
+from environments.factory.additional.doors.doors_collections import Doors
+from environments.factory.additional.doors.doors_util import DoorProperties, RewardsDoor, Constants, Actions
+from environments.factory.base.base_factory import BaseFactory
+from environments.factory.base.objects import Agent, Action
+from environments.factory.base.registers import Entities
+
+from environments import helpers as h
+
+from environments.factory.base.renderer import RenderEntity
+from environments.utility_classes import ObservationProperties
+
+
+def softmax(x):
+    """Compute softmax values for each sets of scores in x."""
+    e_x = np.exp(x - np.max(x))
+    return e_x / e_x.sum()
+
+
+def entropy(x):
+    return -(x * np.log(x + 1e-8)).sum()
+
+
+c = Constants
+a = Actions
+
+
+# noinspection PyAttributeOutsideInit, PyAbstractClass
+class DoorFactory(BaseFactory):
+
+    @property
+    def actions_hook(self) -> Union[Action, List[Action]]:
+        super_actions = super().actions_hook
+        super_actions.append(Action(str_ident=a.USE_DOOR))
+        return super_actions
+
+    @property
+    def entities_hook(self) -> Dict[(str, Entities)]:
+        super_entities = super().entities_hook
+
+        parsed_doors = h.one_hot_level(self._parsed_level, c.DOOR_SYMBOL)
+        parsed_doors = np.pad(parsed_doors, self.obs_prop.pomdp_r, 'constant', constant_values=0)
+        if np.any(parsed_doors):
+            door_tiles = [self[c.FLOOR].by_pos(tuple(pos)) for pos in np.argwhere(parsed_doors == c.OCCUPIED_CELL)]
+            doors = Doors.from_tiles(door_tiles, self._level_shape, indicate_area=self.obs_prop.indicate_door_area,
+                                     entity_kwargs=dict()
+                                     )
+            super_entities.update(({c.DOORS: doors}))
+        return super_entities
+
+    def __init__(self, *args,
+                 door_properties: DoorProperties = DoorProperties(), rewards_door: RewardsDoor = RewardsDoor(),
+                 env_seed=time.time_ns(), **kwargs):
+        if isinstance(door_properties, dict):
+            door_properties = DoorProperties(**door_properties)
+        if isinstance(rewards_door, dict):
+            rewards_door = RewardsDoor(**rewards_door)
+        self.door_properties = door_properties
+        self.rewards_door = rewards_door
+        self._door_rng = np.random.default_rng(env_seed)
+        self._doors: Doors
+        kwargs.update(env_seed=env_seed)
+        # TODO: Reset ---> document this
+        super().__init__(*args, **kwargs)
+
+    def render_assets_hook(self, mode='human'):
+        additional_assets = super().render_assets_hook()
+        doors = []
+        for i, door in enumerate(self[c.DOORS]):
+            name, state = 'door_open' if door.is_open else 'door_closed', 'blank'
+            doors.append(RenderEntity(name, door.pos, 1, 'none', state, i + 1))
+        additional_assets.extend(doors)
+        return additional_assets
+
+
+    def step_hook(self) -> (List[dict], dict):
+        super_reward_info = super().step_hook()
+        # Step the door close intervall
+        # TODO: Maybe move this to self.post_step_hook? May collide with reward calculation.
+        if doors := self[c.DOORS]:
+            doors.tick_doors()
+        return super_reward_info
+
+    def do_additional_actions(self, agent: Agent, action: Action) -> (dict, dict):
+        action_result = super().do_additional_actions(agent, action)
+        if action_result is None:
+            if action == a.USE_DOOR:
+                return self.use_door_action(agent)
+            else:
+                return None
+        else:
+            return action_result
+
+    def use_door_action(self, agent: Agent):
+
+        # Check if agent really is standing on a door:
+        door = self[c.DOORS].get_near_position(agent.pos)
+        if door is not None:
+            door.use()
+            valid = c.VALID
+            self.print(f'{agent.name} just used a {door.name} at {door.pos}')
+            info_dict = {f'{agent.name}_door_use': 1, f'door_use': 1}
+        # When he doesn't...
+        else:
+            valid = c.NOT_VALID
+            info_dict = {f'{agent.name}_failed_door_use': 1, 'failed_door_use': 1}
+            self.print(f'{agent.name} just tried to use a door at {agent.pos}, but there is none.')
+
+        reward = dict(value=self.rewards_door.USE_DOOR_VALID if valid else self.rewards_door.USE_DOOR_FAIL,
+                      reason=a.USE_DOOR, info=info_dict)
+
+        return valid, reward
+
+    def reset_hook(self) -> None:
+        super().reset_hook()
+        # There is nothing to reset.
+
+    def check_additional_done(self) -> (bool, dict):
+        super_done, super_dict = super().check_additional_done()
+        return super_done, super_dict
+
+    def observations_hook(self) -> Dict[str, np.typing.ArrayLike]:
+        additional_observations = super().observations_hook()
+
+        additional_observations.update({c.DOORS: self[c.DOORS].as_array()})
+        return additional_observations
+
+    def post_step_hook(self) -> List[Dict[str, int]]:
+        super_post_step = super(DoorFactory, self).post_step_hook()
+        return super_post_step
+
+
+if __name__ == '__main__':
+    from environments.utility_classes import AgentRenderOptions as aro
+    render = True
+
+    door_props = DoorProperties(
+        indicate_door_area=True
+    )
+
+    obs_props = ObservationProperties(render_agents=aro.COMBINED, omit_agent_self=True,
+                                      pomdp_r=2, additional_agent_placeholder=None, cast_shadows=True
+                                      )
+
+    move_props = {'allow_square_movement': True,
+                  'allow_diagonal_movement': False,
+                  'allow_no_op': False}
+    import time
+    global_timings = []
+    for i in range(10):
+
+        factory = DoorFactory(n_agents=10, done_at_collision=False,
+                              level_name='rooms', max_steps=1000,
+                              obs_prop=obs_props, parse_doors=True,
+                              verbose=True,
+                              mv_prop=move_props, dirt_prop=door_props,
+                              # inject_agents=[TSPDirtAgent],
+                              )
+
+        # noinspection DuplicatedCode
+        n_actions = factory.action_space.n - 1
+        _ = factory.observation_space
+        obs_space = factory.observation_space
+        obs_space_named = factory.named_observation_space
+        action_space_named = factory.named_action_space
+        times = []
+        for epoch in range(10):
+            start_time = time.time()
+            random_actions = [[random.randint(0, n_actions) for _
+                               in range(factory.n_agents)] for _
+                              in range(factory.max_steps+1)]
+            env_state = factory.reset()
+            if render:
+                factory.render()
+            # tsp_agent = factory.get_injected_agents()[0]
+
+            rwrd = 0
+            for agent_i_action in random_actions:
+                # agent_i_action = tsp_agent.predict()
+                env_state, step_rwrd, done_bool, info_obj = factory.step(agent_i_action)
+                rwrd += step_rwrd
+                if render:
+                    factory.render()
+                if done_bool:
+                    break
+            times.append(time.time() - start_time)
+            # print(f'Factory run {epoch} done, reward is:\n    {r}')
+        print('Mean Time Taken: ', sum(times) / 10)
+        global_timings.extend(times)
+    print('Mean Time Taken: ', sum(global_timings) / len(global_timings))
+    print('Median Time Taken: ', global_timings[len(global_timings)//2])

environments/factory/additional/combined_factories.py

@@ -7,9 +7,17 @@ from environments.factory.additional.btry.factory_battery import BatteryFactory
 from environments.factory.additional.dest.factory_dest import DestFactory
 from environments.factory.additional.dirt.dirt_util import DirtProperties
 from environments.factory.additional.dirt.factory_dirt import DirtFactory
+from environments.factory.additional.doors.factory_doors import DoorFactory
 from environments.factory.additional.item.factory_item import ItemFactory
 
 
+# noinspection PyAbstractClass
+class DoorDirtFactory(DoorFactory, DirtFactory):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+
+# noinspection PyAbstractClass
 class DirtItemFactory(ItemFactory, DirtFactory):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -38,8 +46,6 @@ if __name__ == '__main__':
 
     render = True
 
-    dirt_props = DirtProperties(1, 0.05, 0.1, 3, 1, 20, 0)
-
     obs_props = ObservationProperties(render_agents=ARO.COMBINED, omit_agent_self=True,
                                       pomdp_r=2, additional_agent_placeholder=None)
 
@@ -47,13 +53,13 @@ if __name__ == '__main__':
                   'allow_diagonal_movement': False,
                   'allow_no_op': False}
 
-    factory = DirtBatteryFactory(n_agents=5, done_at_collision=False,
+    factory = DoorDirtFactory(n_agents=10, done_at_collision=False,
                                  level_name='rooms', max_steps=400,
                                  obs_prop=obs_props, parse_doors=True,
                                  record_episodes=True, verbose=True,
-                                 btry_prop=BatteryProperties(),
-                                 mv_prop=move_props, dirt_prop=dirt_props
-                                 )
+                                 dirt_prop=DirtProperties(),
+                                 mv_prop=move_props)
+
 
     # noinspection DuplicatedCode
     n_actions = factory.action_space.n - 1

environments/factory/additional/dirt/factory_dirt.py

@@ -44,7 +44,7 @@ class DirtFactory(BaseFactory):
     def entities_hook(self) -> Dict[(str, Entities)]:
         super_entities = super().entities_hook
         dirt_register = DirtPiles(self.dirt_prop, self._level_shape)
-        super_entities.update(({c.DIRT: dirt_register}))
+        super_entities.update({c.DIRT: dirt_register})
         return super_entities
 
     def __init__(self, *args,

environments/factory/additional/doors/doors_collections.py

@@ -0,0 +1,38 @@
+from typing import Union
+
+from environments.factory.additional.doors.doors_entities import Door
+from environments.factory.base.registers import EntityCollection
+
+from environments.factory.additional.doors.doors_util import Constants as c
+
+
+class Doors(EntityCollection):
+
+    def __init__(self, *args, indicate_area=False, **kwargs):
+        self.indicate_area = indicate_area
+        self._area_marked = False
+        super(Doors, self).__init__(*args, is_blocking_light=True, can_collide=True, **kwargs)
+
+    _accepted_objects = Door
+
+    def get_near_position(self, position: (int, int)) -> Union[None, Door]:
+        try:
+            return next(door for door in self if position in door.tile.neighboring_floor_pos)
+        except StopIteration:
+            return None
+
+    def tick_doors(self):
+        for door in self:
+            door.tick()
+
+    def as_array(self):
+        if not self._area_marked and self.indicate_area:
+            for door in self:
+                for tile in door.tile.neighboring_floor:
+                    if self._individual_slices:
+                        pass
+                    else:
+                        pos = (0, *tile.pos)
+                    self._lazy_eval_transforms.append((pos, c.ACCESS_DOOR_CELL))
+            self._area_marked = True
+        return super(Doors, self).as_array()

environments/factory/additional/doors/doors_entities.py

@@ -0,0 +1,69 @@
+from environments.factory.base.objects import Entity
+from environments.factory.additional.doors.doors_util import Constants as c
+
+
+class Door(Entity):
+
+    @property
+    def is_blocking(self):
+        return False if self.is_open else True
+
+    @property
+    def can_collide(self):
+        return False if self.is_open else True
+
+    @property
+    def encoding(self):
+        # This is important as it shadow is checked by occupation value
+        return c.CLOSED_DOOR_CELL if self.is_closed else c.OPEN_DOOR_CELL
+
+    @property
+    def str_state(self):
+        return 'open' if self.is_open else 'closed'
+
+    def __init__(self, *args, closed_on_init=True, auto_close_interval=10, indicate_area=False, **kwargs):
+        super(Door, self).__init__(*args, **kwargs)
+        self._state = c.CLOSED_DOOR
+        self.indicate_area = indicate_area
+        self.auto_close_interval = auto_close_interval
+        self.time_to_close = -1
+        if not closed_on_init:
+            self._open()
+
+    def summarize_state(self):
+        state_dict = super().summarize_state()
+        state_dict.update(state=str(self.str_state), time_to_close=int(self.time_to_close))
+        return state_dict
+
+    @property
+    def is_closed(self):
+        return self._state == c.CLOSED_DOOR
+
+    @property
+    def is_open(self):
+        return self._state == c.OPEN_DOOR
+
+    @property
+    def status(self):
+        return self._state
+
+    def use(self):
+        if self._state == c.OPEN_DOOR:
+            self._close()
+        else:
+            self._open()
+
+    def tick(self):
+        if self.is_open and len(self.tile) == 1 and self.time_to_close:
+            self.time_to_close -= 1
+        elif self.is_open and not self.time_to_close and len(self.tile) == 1:
+            self.use()
+
+    def _open(self):
+        self._state = c.OPEN_DOOR
+        self._collection.notify_change_to_value(self)
+        self.time_to_close = self.auto_close_interval
+
+    def _close(self):
+        self._state = c.CLOSED_DOOR
+        self._collection.notify_change_to_value(self)

environments/factory/additional/doors/doors_util.py

@@ -0,0 +1,31 @@
+
+from typing import NamedTuple
+
+from environments.helpers import Constants as BaseConstants, EnvActions as BaseActions
+
+
+class Constants(BaseConstants):
+    DOOR         = 'Door'   # Identifier of Single-Door Entities.
+    DOORS        = 'Doors'  # Identifier of Door-objects and sets (collections).
+    DOOR_SYMBOL  = 'D'                   # Door identifier for resolving the string based map files.
+
+    ACCESS_DOOR_CELL = 1 / 3  # Access-door-Cell value used in observation
+    OPEN_DOOR_CELL = 2 / 3  # Open-door-Cell value used in observation
+    CLOSED_DOOR_CELL = 3 / 3  # Closed-door-Cell value used in observation
+
+    CLOSED_DOOR         = 'closed'              # Identifier to compare door-is-closed state
+    OPEN_DOOR           = 'open'                # Identifier to compare door-is-open state
+    # ACCESS_DOOR         = 'access'            # Identifier to compare access positions
+
+
+class Actions(BaseActions):
+    USE_DOOR = 'use_door'
+
+
+class RewardsDoor(NamedTuple):
+    USE_DOOR_VALID: float  = -0.00
+    USE_DOOR_FAIL: float   = -0.01
+
+
+class DoorProperties(NamedTuple):
+    indicate_door_area: bool = True            # Wether the door area should be indicated in the agents' observation.

environments/factory/additional/doors/factory_doors.py

@@ -0,0 +1,196 @@
+import time
+from typing import List, Union, Dict
+import random
+
+import numpy as np
+
+from environments.factory.additional.doors.doors_collections import Doors
+from environments.factory.additional.doors.doors_util import DoorProperties, RewardsDoor, Constants, Actions
+from environments.factory.base.base_factory import BaseFactory
+from environments.factory.base.objects import Agent, Action
+from environments.factory.base.registers import Entities
+
+from environments import helpers as h
+
+from environments.factory.base.renderer import RenderEntity
+from environments.utility_classes import ObservationProperties
+
+
+def softmax(x):
+    """Compute softmax values for each sets of scores in x."""
+    e_x = np.exp(x - np.max(x))
+    return e_x / e_x.sum()
+
+
+def entropy(x):
+    return -(x * np.log(x + 1e-8)).sum()
+
+
+c = Constants
+a = Actions
+
+
+# noinspection PyAttributeOutsideInit, PyAbstractClass
+class DoorFactory(BaseFactory):
+
+    @property
+    def actions_hook(self) -> Union[Action, List[Action]]:
+        super_actions = super().actions_hook
+        super_actions.append(Action(str_ident=a.USE_DOOR))
+        return super_actions
+
+    @property
+    def entities_hook(self) -> Dict[(str, Entities)]:
+        super_entities = super().entities_hook
+
+        parsed_doors = h.one_hot_level(self._parsed_level, c.DOOR_SYMBOL)
+        parsed_doors = np.pad(parsed_doors, self.obs_prop.pomdp_r, 'constant', constant_values=0)
+        if np.any(parsed_doors):
+            door_tiles = [self[c.FLOOR].by_pos(tuple(pos)) for pos in np.argwhere(parsed_doors == c.OCCUPIED_CELL)]
+            doors = Doors.from_tiles(door_tiles, self._level_shape, indicate_area=self.obs_prop.indicate_door_area,
+                                     entity_kwargs=dict()
+                                     )
+            super_entities.update(({c.DOORS: doors}))
+        return super_entities
+
+    def __init__(self, *args,
+                 door_properties: DoorProperties = DoorProperties(), rewards_door: RewardsDoor = RewardsDoor(),
+                 env_seed=time.time_ns(), **kwargs):
+        if isinstance(door_properties, dict):
+            door_properties = DoorProperties(**door_properties)
+        if isinstance(rewards_door, dict):
+            rewards_door = RewardsDoor(**rewards_door)
+        self.door_properties = door_properties
+        self.rewards_door = rewards_door
+        self._door_rng = np.random.default_rng(env_seed)
+        self._doors: Doors
+        kwargs.update(env_seed=env_seed)
+        # TODO: Reset ---> document this
+        super().__init__(*args, **kwargs)
+
+    def render_assets_hook(self, mode='human'):
+        additional_assets = super().render_assets_hook()
+        doors = []
+        for i, door in enumerate(self[c.DOORS]):
+            name, state = 'door_open' if door.is_open else 'door_closed', 'blank'
+            doors.append(RenderEntity(name, door.pos, 1, 'none', state, i + 1))
+        additional_assets.extend(doors)
+        return additional_assets
+
+
+    def step_hook(self) -> (List[dict], dict):
+        super_reward_info = super().step_hook()
+        # Step the door close intervall
+        # TODO: Maybe move this to self.post_step_hook? May collide with reward calculation.
+        if doors := self[c.DOORS]:
+            doors.tick_doors()
+        return super_reward_info
+
+    def do_additional_actions(self, agent: Agent, action: Action) -> (dict, dict):
+        action_result = super().do_additional_actions(agent, action)
+        if action_result is None:
+            if action == a.USE_DOOR:
+                return self.use_door_action(agent)
+            else:
+                return None
+        else:
+            return action_result
+
+    def use_door_action(self, agent: Agent):
+
+        # Check if agent really is standing on a door:
+        door = self[c.DOORS].get_near_position(agent.pos)
+        if door is not None:
+            door.use()
+            valid = c.VALID
+            self.print(f'{agent.name} just used a {door.name} at {door.pos}')
+            info_dict = {f'{agent.name}_door_use': 1, f'door_use': 1}
+        # When he doesn't...
+        else:
+            valid = c.NOT_VALID
+            info_dict = {f'{agent.name}_failed_door_use': 1, 'failed_door_use': 1}
+            self.print(f'{agent.name} just tried to use a door at {agent.pos}, but there is none.')
+
+        reward = dict(value=self.rewards_door.USE_DOOR_VALID if valid else self.rewards_door.USE_DOOR_FAIL,
+                      reason=a.USE_DOOR, info=info_dict)
+
+        return valid, reward
+
+    def reset_hook(self) -> None:
+        super().reset_hook()
+        # There is nothing to reset.
+
+    def check_additional_done(self) -> (bool, dict):
+        super_done, super_dict = super().check_additional_done()
+        return super_done, super_dict
+
+    def observations_hook(self) -> Dict[str, np.typing.ArrayLike]:
+        additional_observations = super().observations_hook()
+
+        additional_observations.update({c.DOORS: self[c.DOORS].as_array()})
+        return additional_observations
+
+    def post_step_hook(self) -> List[Dict[str, int]]:
+        super_post_step = super(DoorFactory, self).post_step_hook()
+        return super_post_step
+
+
+if __name__ == '__main__':
+    from environments.utility_classes import AgentRenderOptions as aro
+    render = True
+
+    door_props = DoorProperties(
+        indicate_door_area=True
+    )
+
+    obs_props = ObservationProperties(render_agents=aro.COMBINED, omit_agent_self=True,
+                                      pomdp_r=2, additional_agent_placeholder=None, cast_shadows=True
+                                      )
+
+    move_props = {'allow_square_movement': True,
+                  'allow_diagonal_movement': False,
+                  'allow_no_op': False}
+    import time
+    global_timings = []
+    for i in range(10):
+
+        factory = DoorFactory(n_agents=10, done_at_collision=False,
+                              level_name='rooms', max_steps=1000,
+                              obs_prop=obs_props, parse_doors=True,
+                              verbose=True,
+                              mv_prop=move_props, dirt_prop=door_props,
+                              # inject_agents=[TSPDirtAgent],
+                              )
+
+        # noinspection DuplicatedCode
+        n_actions = factory.action_space.n - 1
+        _ = factory.observation_space
+        obs_space = factory.observation_space
+        obs_space_named = factory.named_observation_space
+        action_space_named = factory.named_action_space
+        times = []
+        for epoch in range(10):
+            start_time = time.time()
+            random_actions = [[random.randint(0, n_actions) for _
+                               in range(factory.n_agents)] for _
+                              in range(factory.max_steps+1)]
+            env_state = factory.reset()
+            if render:
+                factory.render()
+            # tsp_agent = factory.get_injected_agents()[0]
+
+            rwrd = 0
+            for agent_i_action in random_actions:
+                # agent_i_action = tsp_agent.predict()
+                env_state, step_rwrd, done_bool, info_obj = factory.step(agent_i_action)
+                rwrd += step_rwrd
+                if render:
+                    factory.render()
+                if done_bool:
+                    break
+            times.append(time.time() - start_time)
+            # print(f'Factory run {epoch} done, reward is:\n    {r}')
+        print('Mean Time Taken: ', sum(times) / 10)
+        global_timings.extend(times)
+    print('Mean Time Taken: ', sum(global_timings) / len(global_timings))
+    print('Median Time Taken: ', global_timings[len(global_timings)//2])

environments/factory/base/base_factory.py

@@ -16,7 +16,7 @@ from environments.helpers import Constants as c
 from environments.helpers import EnvActions as a
 from environments.helpers import RewardsBase
 from environments.factory.base.objects import Agent, Floor, Action
-from environments.factory.base.registers import Actions, Entities, Agents, Doors, Floors, Walls, PlaceHolders, \
+from environments.factory.base.registers import Actions, Entities, Agents, Floors, Walls, PlaceHolders, \
     GlobalPositions
 from environments.utility_classes import MovementProperties, ObservationProperties, MarlFrameStack
 from environments.utility_classes import AgentRenderOptions as a_obs
@@ -88,8 +88,8 @@ class BaseFactory(gym.Env):
                  mv_prop: MovementProperties = MovementProperties(),
                  obs_prop: ObservationProperties = ObservationProperties(),
                  rewards_base: RewardsBase = RewardsBase(),
-                 parse_doors=False, done_at_collision=False, inject_agents: Union[None, List] = None,
-                 verbose=False, doors_have_area=True, env_seed=time.time_ns(), individual_rewards=False,
+                 done_at_collision=False, inject_agents: Union[None, List] = None,
+                 verbose=False, env_seed=time.time_ns(), individual_rewards=False,
                  class_name='', **kwargs):
 
         if class_name:
@@ -105,8 +105,6 @@ class BaseFactory(gym.Env):
         assert obs_prop.frames_to_stack != 1 and \
                obs_prop.frames_to_stack >= 0, \
                "'frames_to_stack' cannot be negative or 1."
-        assert doors_have_area or not obs_prop.indicate_door_area, \
-            '"indicate_door_area" can only active, when "doors_have_area"'
         if kwargs:
             print(f'Following kwargs were passed, but ignored: {kwargs}')
 
@@ -133,9 +131,7 @@ class BaseFactory(gym.Env):
 
         self.done_at_collision = done_at_collision
         self._record_episodes = False
-        self.parse_doors = parse_doors
         self._injected_agents = inject_agents or []
-        self.doors_have_area = doors_have_area
         self.individual_rewards = individual_rewards
 
         # TODO: Reset ---> document this
@@ -174,20 +170,9 @@ class BaseFactory(gym.Env):
         # NOPOS
         self._NO_POS_TILE = Floor(c.NO_POS, None)
 
-        # Doors
-        if self.parse_doors:
-            parsed_doors = h.one_hot_level(self._parsed_level, c.DOOR)
-            parsed_doors = np.pad(parsed_doors, self.obs_prop.pomdp_r, 'constant', constant_values=0)
-            if np.any(parsed_doors):
-                door_tiles = [floor.by_pos(tuple(pos)) for pos in np.argwhere(parsed_doors == c.OCCUPIED_CELL)]
-                doors = Doors.from_tiles(door_tiles, self._level_shape, have_area=self.obs_prop.indicate_door_area,
-                                         entity_kwargs=dict(context=floor)
-                                         )
-                self._entities.add_additional_items({c.DOORS: doors})
-
         # Actions
         # TODO: Move this to Agent init, so that agents can have individual action sets.
-        self._actions = Actions(self.mv_prop, can_use_doors=self.parse_doors)
+        self._actions = Actions(self.mv_prop)
         if additional_actions := self.actions_hook:
             self._actions.add_additional_items(additional_actions)
 
@@ -263,8 +248,6 @@ class BaseFactory(gym.Env):
             elif a.NOOP == action_obj:
                 action_valid = c.VALID
                 reward = dict(value=self.rewards_base.NOOP, reason=a.NOOP, info={f'{agent.name}_NOOP': 1, 'NOOP': 1})
-            elif a.USE_DOOR == action_obj:
-                action_valid, reward = self._handle_door_interaction(agent)
             else:
                 # noinspection PyTupleAssignmentBalance
                 action_valid, reward = self.do_additional_actions(agent, action_obj)
@@ -282,12 +265,9 @@ class BaseFactory(gym.Env):
         for tile in tiles_with_collisions:
             guests = tile.guests_that_can_collide
             for i, guest in enumerate(guests):
-                # This does make a copy, but is faster than.copy()
-                this_collisions = guests[:]
-                del this_collisions[i]
-                assert hasattr(guest, 'step_result')
-                for collision in this_collisions:
-                    guest.step_result['collisions'].append(collision)
+                for j, collision in enumerate(guests):
+                    if j != i and hasattr(guest, 'step_result'):
+                        guest.step_result['collisions'].append(collision)
 
         done = False
         if self.done_at_collision:
@@ -299,11 +279,6 @@ class BaseFactory(gym.Env):
         done = done or additional_done
         info.update(additional_done_info)
 
-        # Step the door close intervall
-        if self.parse_doors:
-            if doors := self[c.DOORS]:
-                doors.tick_doors()
-
         # Finalize
         reward, reward_info = self.build_reward_result(rewards)
 
@@ -319,41 +294,14 @@ class BaseFactory(gym.Env):
             info.update(post_step_info)
 
         obs, _ = self._build_observations()
-
         return obs, reward, done, info
 
-    def _handle_door_interaction(self, agent) -> (bool, dict):
-        if doors := self[c.DOORS]:
-            # Check if agent really is standing on a door:
-            if self.doors_have_area:
-                door = doors.get_near_position(agent.pos)
-            else:
-                door = doors.by_pos(agent.pos)
-            if door is not None:
-                door.use()
-                valid = c.VALID
-                self.print(f'{agent.name} just used a {door.name} at {door.pos}')
-                info_dict = {f'{agent.name}_door_use': 1, f'door_use': 1}
-            # When he doesn't...
-            else:
-                valid = c.NOT_VALID
-                info_dict = {f'{agent.name}_failed_door_use': 1, 'failed_door_use': 1}
-                self.print(f'{agent.name} just tried to use a door at {agent.pos}, but there is none.')
-
-        else:
-            raise RuntimeError('This should not happen, since the door action should not be available.')
-        reward = dict(value=self.rewards_base.USE_DOOR_VALID if valid else self.rewards_base.USE_DOOR_FAIL,
-                      reason=a.USE_DOOR, info=info_dict)
-
-        return valid, reward
-
     def _build_observations(self) -> np.typing.ArrayLike:
         # Observation dict:
         per_agent_expl_idx = dict()
         per_agent_obsn = dict()
         # Generel Observations
         lvl_obs = self[c.WALLS].as_array()
-        door_obs = self[c.DOORS].as_array() if self.parse_doors else None
         if self.obs_prop.render_agents == a_obs.NOT:
             global_agent_obs = None
         elif self.obs_prop.omit_agent_self and self.n_agents == 1:
@@ -391,8 +339,6 @@ class BaseFactory(gym.Env):
                 obs_dict[c.AGENT] = agent_obs[:]
             if self[c.AGENT_PLACEHOLDER] and placeholder_obs is not None:
                 obs_dict[c.AGENT_PLACEHOLDER] = placeholder_obs
-            if self.parse_doors and door_obs is not None:
-                obs_dict[c.DOORS] = door_obs[:]
             obs_dict.update(add_obs_dict)
             obsn = np.vstack(list(obs_dict.values()))
             if self.obs_prop.pomdp_r:
@@ -430,33 +376,11 @@ class BaseFactory(gym.Env):
                     raise e
 
                 obs_block_light = obsn[light_block_obs] != c.OCCUPIED_CELL
-                door_shadowing = False
-                if self.parse_doors:
-                    if doors := self[c.DOORS]:
-                        if door := doors.by_pos(agent.pos):
-                            if door.is_closed:
-                                for group in door.connectivity_subgroups:
-                                    if agent.last_pos not in group:
-                                        door_shadowing = True
-                                        if self._pomdp_r:
-                                            blocking = [
-                                                tuple(np.subtract(x, agent.pos) + (self._pomdp_r, self._pomdp_r))
-                                                for x in group]
-                                            xs, ys = zip(*blocking)
-                                        else:
-                                            xs, ys = zip(*group)
-
-                                        # noinspection PyUnresolvedReferences
-                                        obs_block_light[:, xs, ys] = False
-
                 light_block_map = Map((np.prod(obs_block_light, axis=0) != True).astype(int).squeeze())
                 if self._pomdp_r:
                     light_block_map = light_block_map.do_fov(self._pomdp_r, self._pomdp_r, max(self._level_shape))
                 else:
                     light_block_map = light_block_map.do_fov(*agent.pos, max(self._level_shape))
-                if door_shadowing:
-                    # noinspection PyUnboundLocalVariable
-                    light_block_map[xs, ys] = 0
 
                 agent.step_result['lightmap'] = light_block_map
 
@@ -550,35 +474,13 @@ class BaseFactory(gym.Env):
         y_new = agent.y + y_diff
 
         new_tile = self[c.FLOOR].by_pos((x_new, y_new))
-        if new_tile:
+        if new_tile and not np.any([x.is_blocking for x in new_tile.guests]):
             valid = c.VALID
         else:
             tile = agent.tile
             valid = c.VALID
             return tile, valid
 
-        if self.parse_doors and agent.last_pos != c.NO_POS:
-            if doors := self[c.DOORS]:
-                if self.doors_have_area:
-                    if door := doors.by_pos(new_tile.pos):
-                        if door.is_closed:
-                            return agent.tile, c.NOT_VALID
-                        else:  # door.is_closed:
-                            pass
-
-                if door := doors.by_pos(agent.pos):
-                    if door.is_open:
-                        pass
-                    else:  # door.is_closed:
-                        if door.is_linked(agent.last_pos, new_tile.pos):
-                            pass
-                        else:
-                            return agent.tile, c.NOT_VALID
-                else:
-                    pass
-        else:
-            pass
-
         return new_tile, valid
 
     def build_reward_result(self, global_env_rewards: list) -> (int, dict):
@@ -649,14 +551,10 @@ class BaseFactory(gym.Env):
         for i, agent in enumerate(self[c.AGENT]):
             name, state = h.asset_str(agent)
             agents.append(RenderEntity(name, agent.pos, 1, 'none', state, i + 1, agent.step_result['lightmap']))
-        doors = []
-        if self.parse_doors:
-            for i, door in enumerate(self[c.DOORS]):
-                name, state = 'door_open' if door.is_open else 'door_closed', 'blank'
-                doors.append(RenderEntity(name, door.pos, 1, 'none', state, i + 1))
+
         additional_assets = self.render_assets_hook()
 
-        return self._renderer.render(walls + doors + additional_assets + agents)
+        return self._renderer.render(walls + additional_assets + agents)
 
     def save_params(self, filepath: Path):
         # noinspection PyProtectedMember

environments/factory/base/objects.py

@@ -1,12 +1,10 @@
 from collections import defaultdict
-from typing import Union
+from typing import Union, List
 
-import networkx as nx
 import numpy as np
 
 from environments import helpers as h
 from environments.helpers import Constants as c
-import itertools
 
 ##########################################################################
 # ##################### Base Object Building Blocks ######################### #
@@ -88,6 +86,10 @@ class EnvObject(Object):
 class Entity(EnvObject):
     """Full Env Entity that lives on the env Grid. Doors, Items, DirtPile etc..."""
 
+    @property
+    def is_blocking(self):
+        return False
+
     @property
     def can_collide(self):
         return False
@@ -226,6 +228,21 @@ class GlobalPosition(BoundingMixin, EnvObject):
 
 class Floor(EnvObject):
 
+    @property
+    def neighboring_floor_pos(self):
+        return [x.pos for x in self.neighboring_floor]
+
+    @property
+    def neighboring_floor(self):
+        if self._neighboring_floor:
+            pass
+        else:
+            self._neighboring_floor = [x for x in [self._collection.by_pos(np.add(self.pos, pos))
+                                                   for pos in h.POS_MASK.reshape(-1, 2)
+                                                   if not np.all(pos == [0, 0])]
+                                       if x]
+        return self._neighboring_floor
+
     @property
     def encoding(self):
         return c.FREE_CELL
@@ -254,6 +271,7 @@ class Floor(EnvObject):
         super(Floor, self).__init__(*args, **kwargs)
         self._guests = dict()
         self._pos = tuple(pos)
+        self._neighboring_floor: List[Floor] = list()
 
     def __len__(self):
         return len(self._guests)
@@ -298,94 +316,6 @@ class Wall(Floor):
     pass
 
 
-class Door(Entity):
-
-    @property
-    def can_collide(self):
-        if self.has_area:
-            return False if self.is_open else True
-        else:
-            return False
-
-    @property
-    def encoding(self):
-        # This is important as it shadow is checked by occupation value
-        return c.CLOSED_DOOR_CELL if self.is_closed else c.OPEN_DOOR_CELL
-
-    @property
-    def str_state(self):
-        return 'open' if self.is_open else 'closed'
-
-    @property
-    def access_area(self):
-        return [node for node in self.connectivity.nodes
-                if node not in range(len(self.connectivity_subgroups)) and node != self.pos]
-
-    def __init__(self, *args, context, closed_on_init=True, auto_close_interval=10, has_area=False, **kwargs):
-        super(Door, self).__init__(*args, **kwargs)
-        self._state = c.CLOSED_DOOR
-        self.has_area = has_area
-        self.auto_close_interval = auto_close_interval
-        self.time_to_close = -1
-        neighbor_pos = list(itertools.product([-1, 1, 0], repeat=2))[:-1]
-        neighbor_tiles = [context.by_pos(tuple([sum(x) for x in zip(self.pos, diff)])) for diff in neighbor_pos]
-        neighbor_pos = [x.pos for x in neighbor_tiles if x]
-        self.connectivity = h.points_to_graph(neighbor_pos)
-        self.connectivity_subgroups = list(nx.algorithms.components.connected_components(self.connectivity))
-        for idx, group in enumerate(self.connectivity_subgroups):
-            for tile_pos in group:
-                self.connectivity.add_edge(tile_pos, idx)
-        if not closed_on_init:
-            self._open()
-
-    def summarize_state(self):
-        state_dict = super().summarize_state()
-        state_dict.update(state=str(self.str_state), time_to_close=int(self.time_to_close))
-        return state_dict
-
-    @property
-    def is_closed(self):
-        return self._state == c.CLOSED_DOOR
-
-    @property
-    def is_open(self):
-        return self._state == c.OPEN_DOOR
-
-    @property
-    def status(self):
-        return self._state
-
-    def use(self):
-        if self._state == c.OPEN_DOOR:
-            self._close()
-        else:
-            self._open()
-
-    def tick(self):
-        if self.is_open and len(self.tile) == 1 and self.time_to_close:
-            self.time_to_close -= 1
-        elif self.is_open and not self.time_to_close and len(self.tile) == 1:
-            self.use()
-
-    def _open(self):
-        self.connectivity.add_edges_from([(self.pos, x) for x in range(len(self.connectivity_subgroups))])
-        self._state = c.OPEN_DOOR
-        self._collection.notify_change_to_value(self)
-        self.time_to_close = self.auto_close_interval
-
-    def _close(self):
-        self.connectivity.remove_node(self.pos)
-        self._state = c.CLOSED_DOOR
-        self._collection.notify_change_to_value(self)
-
-    def is_linked(self, old_pos, new_pos):
-        try:
-            _ = nx.shortest_path(self.connectivity, old_pos, new_pos)
-            return True
-        except nx.exception.NetworkXNoPath:
-            return False
-
-
 class Agent(MoveableEntity):
 
     @property

environments/factory/base/registers.py

@@ -6,7 +6,7 @@ from typing import List, Union, Dict, Tuple
 import numpy as np
 import six
 
-from environments.factory.base.objects import Entity, Floor, Agent, Door, Action, Wall, PlaceHolder, GlobalPosition, \
+from environments.factory.base.objects import Entity, Floor, Agent, Action, Wall, PlaceHolder, GlobalPosition, \
     Object, EnvObject
 from environments.utility_classes import MovementProperties
 from environments import helpers as h
@@ -452,38 +452,6 @@ class Agents(MovingEntityObjectCollection):
         self._collection[agent.name] = agent
 
 
-class Doors(EntityCollection):
-
-    def __init__(self, *args, have_area: bool = False, **kwargs):
-        self.have_area = have_area
-        self._area_marked = False
-        super(Doors, self).__init__(*args, is_blocking_light=True, can_collide=True, **kwargs)
-
-    _accepted_objects = Door
-
-    def get_near_position(self, position: (int, int)) -> Union[None, Door]:
-        try:
-            return next(door for door in self if position in door.access_area)
-        except StopIteration:
-            return None
-
-    def tick_doors(self):
-        for door in self:
-            door.tick()
-
-    def as_array(self):
-        if self.have_area and not self._area_marked:
-            for door in self:
-                for pos in door.access_area:
-                    if self._individual_slices:
-                        pass
-                    else:
-                        pos = (0, *pos)
-                    self._lazy_eval_transforms.append((pos, c.ACCESS_DOOR_CELL))
-            self._area_marked = True
-        return super(Doors, self).as_array()
-
-
 class Actions(ObjectCollection):
     _accepted_objects = Action
 
@@ -492,11 +460,10 @@ class Actions(ObjectCollection):
         return self._movement_actions
 
     # noinspection PyTypeChecker
-    def __init__(self, movement_properties: MovementProperties, can_use_doors=False):
+    def __init__(self, movement_properties: MovementProperties):
         self.allow_no_op = movement_properties.allow_no_op
         self.allow_diagonal_movement = movement_properties.allow_diagonal_movement
         self.allow_square_movement = movement_properties.allow_square_movement
-        self.can_use_doors = can_use_doors
         super(Actions, self).__init__()
 
         # Move this to Baseclass, Env init?
@@ -507,8 +474,6 @@ class Actions(ObjectCollection):
             self.add_additional_items([self._accepted_objects(str_ident=direction)
                                        for direction in h.EnvActions.diagonal_move()])
         self._movement_actions = self._collection.copy()
-        if self.can_use_doors:
-            self.add_additional_items([self._accepted_objects(str_ident=h.EnvActions.USE_DOOR)])
         if self.allow_no_op:
             self.add_additional_items([self._accepted_objects(str_ident=h.EnvActions.NOOP)])
 

environments/helpers.py

@@ -33,6 +33,10 @@ IGNORED_DF_COLUMNS = ['Episode', 'Run',          # For plotting, which values ar
                       'train_step', 'step', 'index', 'dirt_amount', 'dirty_tile_count', 'terminal_observation',
                       'episode']
 
+POS_MASK = np.asarray([[[-1, -1], [0, -1], [1, -1]],
+                       [[-1,  0], [0,  0], [1,  0]],
+                       [[-1,  1], [0,  1], [1,  1]]])
+
 
 class Constants:
 
@@ -42,12 +46,10 @@ class Constants:
     """
 
     WALL                = '#'                   # Wall tile identifier for resolving the string based map files.
-    DOOR                = 'D'                   # Door identifier for resolving the string based map files.
     DANGER_ZONE         = 'x'                   # Dange Zone tile identifier for resolving the string based map files.
 
     WALLS               = 'Walls'               # Identifier of Wall-objects and sets (collections).
     FLOOR               = 'Floor'               # Identifier of Floor-objects and sets (collections).
-    DOORS               = 'Doors'               # Identifier of Door-objects and sets (collections).
     LEVEL               = 'Level'               # Identifier of Level-objects and sets (collections).
     AGENT               = 'Agent'               # Identifier of Agent-objects and sets (collections).
     AGENT_PLACEHOLDER   = 'AGENT_PLACEHOLDER'   # Identifier of Placeholder-objects and sets (collections).
@@ -56,16 +58,9 @@ class Constants:
     FREE_CELL           = 0                     # Free-Cell value used in observation
     OCCUPIED_CELL       = 1                     # Occupied-Cell value used in observation
     SHADOWED_CELL       = -1                    # Shadowed-Cell value used in observation
-    ACCESS_DOOR_CELL    = 1/3                   # Access-door-Cell value used in observation
-    OPEN_DOOR_CELL      = 2/3                   # Open-door-Cell value used in observation
-    CLOSED_DOOR_CELL    = 3/3                   # Closed-door-Cell value used in observation
 
     NO_POS              = (-9999, -9999)        # Invalid Position value used in the environment (something is off-grid)
 
-    CLOSED_DOOR         = 'closed'              # Identifier to compare door-is-closed state
-    OPEN_DOOR           = 'open'                # Identifier to compare door-is-open state
-    # ACCESS_DOOR         = 'access'            # Identifier to compare access positions
-
     ACTION              = 'action'              # Identifier of Action-objects and sets (collections).
     COLLISION           = 'collision'           # Identifier to use in the context of collitions.
     VALID               = True                  # Identifier to rename boolean values in the context of actions.
@@ -90,7 +85,6 @@ class EnvActions:
     # Other
     # MOVE            = 'move'
     NOOP            = 'no_op'
-    USE_DOOR        = 'use_door'
 
     _ACTIONMAP = defaultdict(lambda: (0, 0),
                             {NORTH: (-1, 0),    NORTHEAST: (-1, 1),
@@ -100,6 +94,8 @@ class EnvActions:
                              }
                             )
 
+
+
     @classmethod
     def is_move(cls, action):
         """
@@ -166,8 +162,6 @@ class RewardsBase(NamedTuple):
     MOVEMENTS_VALID: float = -0.001
     MOVEMENTS_FAIL: float  = -0.05
     NOOP: float            = -0.01
-    USE_DOOR_VALID: float  = -0.00
-    USE_DOOR_FAIL: float   = -0.01
     COLLISION: float       = -0.5
 
 

quickstart/single_agent_train_dirt_env.py

@@ -68,7 +68,7 @@ if __name__ == '__main__':
                                       omit_agent_self=True,                  # This is default
                                       additional_agent_placeholder=None,     # We will not take care of future agents
                                       frames_to_stack=3,                     # To give the agent a notion of time
-                                      pomdp_r=2                              # the agents view-radius
+                                      pomdp_r=2                              # the agents' view-radius
                                       )
     #  'MovementProperties' are for specifying how the agent is allowed to move in the env.
     move_props = MovementProperties(allow_diagonal_movement=True,   # Euclidean style (vertices)
@@ -135,7 +135,7 @@ if __name__ == '__main__':
             env_recorder_callback = EnvRecorder(env_factory, freq=int(train_steps / 400 / 10))
 
             # Model Init
-            model = model_class("MlpPolicy", env_factory,verbose=1, seed=seed, device='cpu')
+            model = model_class("MlpPolicy", env_factory, verbose=1, seed=seed, device='cpu')
 
             # Model train
             model.learn(total_timesteps=int(train_steps), callback=[env_monitor_callback, env_recorder_callback])
@@ -166,7 +166,7 @@ if __name__ == '__main__':
 
         # retrieve model class
         model_cls = next(val for key, val in h.MODEL_MAP.items() if key in policy_path.parent.name)
-        # Load the agent agent
+        # Load the agent
         model = model_cls.load(policy_path / 'model.zip', device='cpu')
         # Load old env kwargs
         with next(policy_path.glob(env_params_json)).open('r') as f: