679 lines
26 KiB
Python
679 lines
26 KiB
Python
import abc
|
|
import time
|
|
from collections import defaultdict
|
|
from itertools import chain
|
|
from pathlib import Path
|
|
from typing import List, Union, Iterable, Dict
|
|
import numpy as np
|
|
|
|
import gym
|
|
from gym import spaces
|
|
from gym.wrappers import FrameStack
|
|
|
|
from environments.factory.base.shadow_casting import Map
|
|
from environments import helpers as h
|
|
from environments.helpers import Constants as c
|
|
from environments.factory.base.objects import Agent, Tile, Action
|
|
from environments.factory.base.registers import Actions, Entities, Agents, Doors, FloorTiles, WallTiles, PlaceHolders, \
|
|
GlobalPositions
|
|
from environments.utility_classes import MovementProperties, ObservationProperties, MarlFrameStack
|
|
from environments.utility_classes import AgentRenderOptions as a_obs
|
|
|
|
import simplejson
|
|
|
|
REC_TAC = 'rec_'
|
|
|
|
|
|
# noinspection PyAttributeOutsideInit
|
|
class BaseFactory(gym.Env):
|
|
|
|
@property
|
|
def action_space(self):
|
|
return spaces.Discrete(len(self._actions))
|
|
|
|
@property
|
|
def named_action_space(self):
|
|
return {x.identifier.value: idx for idx, x in enumerate(self._actions.values())}
|
|
|
|
@property
|
|
def observation_space(self):
|
|
obs, _ = self._build_observations()
|
|
if self.n_agents > 1:
|
|
shape = obs[0].shape
|
|
else:
|
|
shape = obs.shape
|
|
space = spaces.Box(low=0, high=1, shape=shape, dtype=np.float32)
|
|
return space
|
|
|
|
@property
|
|
def named_observation_space(self):
|
|
# Build it
|
|
_, named_obs = self._build_observations()
|
|
if self.n_agents > 1:
|
|
# Only return the first named obs space, as their structure at the moment is same.
|
|
return named_obs[list(named_obs.keys())[0]]
|
|
else:
|
|
return named_obs
|
|
|
|
@property
|
|
def pomdp_diameter(self):
|
|
return self._pomdp_r * 2 + 1
|
|
|
|
@property
|
|
def movement_actions(self):
|
|
return self._actions.movement_actions
|
|
|
|
@property
|
|
def params(self) -> dict:
|
|
d = {key: val for key, val in self.__dict__.items() if not key.startswith('_') and not key.startswith('__')}
|
|
return d
|
|
|
|
def __enter__(self):
|
|
return self if self.obs_prop.frames_to_stack == 0 else \
|
|
MarlFrameStack(FrameStack(self, self.obs_prop.frames_to_stack))
|
|
|
|
def __exit__(self, exc_type, exc_val, exc_tb):
|
|
self.close()
|
|
|
|
def __init__(self, level_name='simple', n_agents=1, max_steps=int(5e2),
|
|
mv_prop: MovementProperties = MovementProperties(),
|
|
obs_prop: ObservationProperties = ObservationProperties(),
|
|
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,
|
|
**kwargs):
|
|
|
|
if isinstance(mv_prop, dict):
|
|
mv_prop = MovementProperties(**mv_prop)
|
|
if isinstance(obs_prop, dict):
|
|
obs_prop = ObservationProperties(**obs_prop)
|
|
|
|
assert obs_prop.frames_to_stack != 1 and \
|
|
obs_prop.frames_to_stack >= 0, "'frames_to_stack' cannot be negative or 1."
|
|
if kwargs:
|
|
print(f'Following kwargs were passed, but ignored: {kwargs}')
|
|
|
|
# Attribute Assignment
|
|
self.env_seed = env_seed
|
|
self.seed(env_seed)
|
|
self._base_rng = np.random.default_rng(self.env_seed)
|
|
self.mv_prop = mv_prop
|
|
self.obs_prop = obs_prop
|
|
self.level_name = level_name
|
|
self._level_shape = None
|
|
self._obs_shape = None
|
|
self.verbose = verbose
|
|
self._renderer = None # expensive - don't use it when not required !
|
|
self._entities = Entities()
|
|
|
|
self.n_agents = n_agents
|
|
level_filepath = Path(__file__).parent.parent / h.LEVELS_DIR / f'{self.level_name}.txt'
|
|
self._parsed_level = h.parse_level(level_filepath)
|
|
|
|
self.max_steps = max_steps
|
|
self._pomdp_r = self.obs_prop.pomdp_r
|
|
|
|
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
|
|
|
|
# Reset
|
|
self.reset()
|
|
|
|
def __getitem__(self, item):
|
|
return self._entities[item]
|
|
|
|
def _base_init_env(self):
|
|
|
|
# All entities
|
|
# Objects
|
|
self._entities = Entities()
|
|
# Level
|
|
|
|
level_array = h.one_hot_level(self._parsed_level)
|
|
level_array = np.pad(level_array, self.obs_prop.pomdp_r, 'constant', constant_values=1)
|
|
|
|
self._level_shape = level_array.shape
|
|
self._obs_shape = self._level_shape if not self.obs_prop.pomdp_r else (self.pomdp_diameter, ) * 2
|
|
|
|
# Walls
|
|
walls = WallTiles.from_argwhere_coordinates(
|
|
np.argwhere(level_array == c.OCCUPIED_CELL),
|
|
self._level_shape
|
|
)
|
|
self._entities.register_additional_items({c.WALLS: walls})
|
|
|
|
# Floor
|
|
floor = FloorTiles.from_argwhere_coordinates(
|
|
np.argwhere(level_array == c.FREE_CELL),
|
|
self._level_shape
|
|
)
|
|
self._entities.register_additional_items({c.FLOOR: floor})
|
|
|
|
# NOPOS
|
|
self._NO_POS_TILE = Tile(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,
|
|
entity_kwargs=dict(context=floor)
|
|
)
|
|
self._entities.register_additional_items({c.DOORS: doors})
|
|
|
|
# Actions
|
|
self._actions = Actions(self.mv_prop, can_use_doors=self.parse_doors)
|
|
if additional_actions := self.additional_actions:
|
|
self._actions.register_additional_items(additional_actions)
|
|
|
|
# Agents
|
|
agents_to_spawn = self.n_agents-len(self._injected_agents)
|
|
agents_kwargs = dict(individual_slices=self.obs_prop.render_agents == a_obs.SEPERATE,
|
|
hide_from_obs_builder=self.obs_prop.render_agents in [a_obs.NOT, a_obs.LEVEL],
|
|
)
|
|
if agents_to_spawn:
|
|
agents = Agents.from_tiles(floor.empty_tiles[:agents_to_spawn], self._level_shape, **agents_kwargs)
|
|
else:
|
|
agents = Agents(**agents_kwargs)
|
|
if self._injected_agents:
|
|
initialized_injections = list()
|
|
for i, injection in enumerate(self._injected_agents):
|
|
agents.register_item(injection(self, floor.empty_tiles[agents_to_spawn+i+1], static_problem=False))
|
|
initialized_injections.append(agents[-1])
|
|
self._initialized_injections = initialized_injections
|
|
self._entities.register_additional_items({c.AGENT: agents})
|
|
|
|
if self.obs_prop.additional_agent_placeholder is not None:
|
|
# TODO: Make this accept Lists for multiple placeholders
|
|
|
|
# Empty Observations with either [0, 1, N(0, 1)]
|
|
placeholder = PlaceHolders.from_values(self.obs_prop.additional_agent_placeholder, self._level_shape,
|
|
entity_kwargs=dict(
|
|
fill_value=self.obs_prop.additional_agent_placeholder)
|
|
)
|
|
|
|
self._entities.register_additional_items({c.AGENT_PLACEHOLDER: placeholder})
|
|
|
|
# Additional Entitites from SubEnvs
|
|
if additional_entities := self.additional_entities:
|
|
self._entities.register_additional_items(additional_entities)
|
|
|
|
if self.obs_prop.show_global_position_info:
|
|
global_positions = GlobalPositions(self._level_shape)
|
|
obs_shape_2d = self._level_shape if not self._pomdp_r else ((self.pomdp_diameter,) * 2)
|
|
global_positions.spawn_global_position_objects(obs_shape_2d, self[c.AGENT])
|
|
self._entities.register_additional_items({c.GLOBAL_POSITION: global_positions})
|
|
|
|
# Return
|
|
return self._entities
|
|
|
|
def reset(self) -> (np.typing.ArrayLike, int, bool, dict):
|
|
_ = self._base_init_env()
|
|
self.do_additional_reset()
|
|
|
|
self._steps = 0
|
|
|
|
obs, _ = self._build_observations()
|
|
return obs
|
|
|
|
def step(self, actions):
|
|
|
|
if self.n_agents == 1 and not isinstance(actions, list):
|
|
actions = [int(actions)]
|
|
|
|
assert isinstance(actions, Iterable), f'"actions" has to be in [{int, list}]'
|
|
self._steps += 1
|
|
|
|
# Pre step Hook for later use
|
|
self.hook_pre_step()
|
|
|
|
# Move this in a seperate function?
|
|
for action, agent in zip(actions, self[c.AGENT]):
|
|
agent.clear_temp_state()
|
|
action_obj = self._actions[int(action)]
|
|
# cls.print(f'Action #{action} has been resolved to: {action_obj}')
|
|
if h.EnvActions.is_move(action_obj):
|
|
valid = self._move_or_colide(agent, action_obj)
|
|
elif h.EnvActions.NOOP == agent.temp_action:
|
|
valid = c.VALID
|
|
elif h.EnvActions.USE_DOOR == action_obj:
|
|
valid = self._handle_door_interaction(agent)
|
|
else:
|
|
valid = self.do_additional_actions(agent, action_obj)
|
|
assert valid is not None, 'This should not happen, every Action musst be detected correctly!'
|
|
agent.temp_action = action_obj
|
|
agent.temp_valid = valid
|
|
|
|
# In-between step Hook for later use
|
|
info = self.do_additional_step()
|
|
|
|
tiles_with_collisions = self.get_all_tiles_with_collisions()
|
|
for tile in tiles_with_collisions:
|
|
guests = tile.guests_that_can_collide
|
|
for i, guest in enumerate(guests):
|
|
this_collisions = guests[:]
|
|
del this_collisions[i]
|
|
guest.temp_collisions = this_collisions
|
|
|
|
done = self.done_at_collision and tiles_with_collisions
|
|
|
|
done = done or self.check_additional_done()
|
|
|
|
# Step the door close intervall
|
|
if self.parse_doors:
|
|
if doors := self[c.DOORS]:
|
|
doors.tick_doors()
|
|
|
|
# Finalize
|
|
reward, reward_info = self.calculate_reward()
|
|
info.update(reward_info)
|
|
if self._steps >= self.max_steps:
|
|
done = True
|
|
info.update(step_reward=reward, step=self._steps)
|
|
if self._record_episodes:
|
|
info.update(self._summarize_state())
|
|
|
|
# Post step Hook for later use
|
|
info.update(self.hook_post_step())
|
|
|
|
obs, _ = self._build_observations()
|
|
|
|
return obs, reward, done, info
|
|
|
|
def _handle_door_interaction(self, agent) -> c:
|
|
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()
|
|
return c.VALID
|
|
# When he doesn't...
|
|
else:
|
|
return c.NOT_VALID
|
|
else:
|
|
return c.NOT_VALID
|
|
|
|
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()
|
|
agent_obs = self[c.AGENT].as_array() if self.obs_prop.render_agents != a_obs.NOT else None
|
|
placeholder_obs = self[c.AGENT_PLACEHOLDER].as_array() if self[c.AGENT_PLACEHOLDER] else None
|
|
add_obs_dict = self._additional_observations()
|
|
|
|
for agent_idx, agent in enumerate(self[c.AGENT]):
|
|
obs_dict = dict()
|
|
# Build Agent Observations
|
|
if self.obs_prop.render_agents != a_obs.NOT:
|
|
if self.obs_prop.omit_agent_self:
|
|
if self.obs_prop.render_agents == a_obs.SEPERATE:
|
|
agent_obs = np.take(agent_obs, [x for x in range(self.n_agents) if x != agent_idx], axis=0)
|
|
else:
|
|
agent_obs = agent_obs.copy()
|
|
agent_obs[(0, *agent.pos)] -= agent.encoding
|
|
|
|
# Build Level Observations
|
|
if self.obs_prop.render_agents == a_obs.LEVEL:
|
|
lvl_obs = lvl_obs.copy()
|
|
lvl_obs += agent_obs
|
|
|
|
obs_dict[c.WALLS] = lvl_obs
|
|
if self.obs_prop.render_agents in [a_obs.SEPERATE, a_obs.COMBINED]:
|
|
obs_dict[c.AGENT] = agent_obs
|
|
if self[c.AGENT_PLACEHOLDER]:
|
|
obs_dict[c.AGENT_PLACEHOLDER] = placeholder_obs
|
|
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:
|
|
obsn = self._do_pomdp_cutout(agent, obsn)
|
|
|
|
raw_obs = self._additional_per_agent_raw_observations(agent)
|
|
obsn = np.vstack((obsn, *list(raw_obs.values())))
|
|
|
|
keys = list(chain(obs_dict.keys(), raw_obs.keys()))
|
|
idxs = np.cumsum([x.shape[0] for x in chain(obs_dict.values(), raw_obs.values())]) - 1
|
|
per_agent_expl_idx[agent.name] = {key: list(range(a, b)) for key, a, b in
|
|
zip(keys, idxs, list(idxs[1:]) + [idxs[-1]+1, ])}
|
|
|
|
# Shadow Casting
|
|
try:
|
|
light_block_obs = [obs_idx for key, obs_idx in per_agent_expl_idx[agent.name].items()
|
|
if self[key].is_blocking_light]
|
|
# Flatten
|
|
light_block_obs = [x for y in light_block_obs for x in y]
|
|
shadowed_obs = [obs_idx for key, obs_idx in per_agent_expl_idx[agent.name].items()
|
|
if self[key].can_be_shadowed]
|
|
# Flatten
|
|
shadowed_obs = [x for y in shadowed_obs for x in y]
|
|
except AttributeError as e:
|
|
print('Check your Keys! Only use Constants as Keys!')
|
|
print(e)
|
|
raise e
|
|
if self.obs_prop.cast_shadows:
|
|
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.temp_light_map = light_block_map.copy()
|
|
|
|
obsn[shadowed_obs] = ((obsn[shadowed_obs] * light_block_map) + 0.) - (1 - light_block_map)
|
|
else:
|
|
pass
|
|
|
|
per_agent_obsn[agent.name] = obsn
|
|
|
|
if self.n_agents == 1:
|
|
agent_name = self[c.AGENT][0].name
|
|
obs, explained_idx = per_agent_obsn[agent_name], per_agent_expl_idx[agent_name]
|
|
elif self.n_agents >= 2:
|
|
obs, explained_idx = np.stack(list(per_agent_obsn.values())), per_agent_expl_idx
|
|
else:
|
|
raise ValueError
|
|
|
|
return obs, explained_idx
|
|
|
|
def _do_pomdp_cutout(self, agent, obs_to_be_padded):
|
|
assert obs_to_be_padded.ndim == 3
|
|
r, d = self._pomdp_r, self.pomdp_diameter
|
|
x0, x1 = max(0, agent.x - r), min(agent.x + r + 1, self._level_shape[0])
|
|
y0, y1 = max(0, agent.y - r), min(agent.y + r + 1, self._level_shape[1])
|
|
oobs = obs_to_be_padded[:, x0:x1, y0:y1]
|
|
if oobs.shape[1:] != (d, d):
|
|
if xd := oobs.shape[1] % d:
|
|
if agent.x > r:
|
|
x0_pad = 0
|
|
x1_pad = (d - xd)
|
|
else:
|
|
x0_pad = r - agent.x
|
|
x1_pad = 0
|
|
else:
|
|
x0_pad, x1_pad = 0, 0
|
|
|
|
if yd := oobs.shape[2] % d:
|
|
if agent.y > r:
|
|
y0_pad = 0
|
|
y1_pad = (d - yd)
|
|
else:
|
|
y0_pad = r - agent.y
|
|
y1_pad = 0
|
|
else:
|
|
y0_pad, y1_pad = 0, 0
|
|
|
|
oobs = np.pad(oobs, ((0, 0), (x0_pad, x1_pad), (y0_pad, y1_pad)), 'constant')
|
|
return oobs
|
|
|
|
def get_all_tiles_with_collisions(self) -> List[Tile]:
|
|
tiles_with_collisions = list()
|
|
for tile in self[c.FLOOR]:
|
|
if tile.is_occupied():
|
|
guests = tile.guests_that_can_collide
|
|
if len(guests) >= 2:
|
|
tiles_with_collisions.append(tile)
|
|
return tiles_with_collisions
|
|
|
|
def _move_or_colide(self, agent: Agent, action: Action) -> bool:
|
|
new_tile, valid = self._check_agent_move(agent, action)
|
|
if valid:
|
|
# Does not collide width level boundaries
|
|
return agent.move(new_tile)
|
|
else:
|
|
# Agent seems to be trying to collide in this step
|
|
return c.NOT_VALID
|
|
|
|
def _check_agent_move(self, agent, action: Action) -> (Tile, bool):
|
|
# Actions
|
|
x_diff, y_diff = h.ACTIONMAP[action.identifier]
|
|
x_new = agent.x + x_diff
|
|
y_new = agent.y + y_diff
|
|
|
|
new_tile = self[c.FLOOR].by_pos((x_new, y_new))
|
|
if new_tile:
|
|
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_open:
|
|
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 calculate_reward(self) -> (int, dict):
|
|
# Returns: Reward, Info
|
|
per_agent_info_dict = defaultdict(dict)
|
|
reward = {}
|
|
|
|
for agent in self[c.AGENT]:
|
|
per_agent_reward = 0
|
|
if self._actions.is_moving_action(agent.temp_action):
|
|
if agent.temp_valid:
|
|
# info_dict.update(movement=1)
|
|
per_agent_reward -= 0.001
|
|
pass
|
|
else:
|
|
per_agent_reward -= 0.05
|
|
self.print(f'{agent.name} just hit the wall at {agent.pos}.')
|
|
per_agent_info_dict[agent.name].update({f'{agent.name}_vs_LEVEL': 1})
|
|
|
|
elif h.EnvActions.USE_DOOR == agent.temp_action:
|
|
if agent.temp_valid:
|
|
# per_agent_reward += 0.00
|
|
self.print(f'{agent.name} did just use the door at {agent.pos}.')
|
|
per_agent_info_dict[agent.name].update(door_used=1)
|
|
else:
|
|
# per_agent_reward -= 0.00
|
|
self.print(f'{agent.name} just tried to use a door at {agent.pos}, but failed.')
|
|
per_agent_info_dict[agent.name].update({f'{agent.name}_failed_door_open': 1})
|
|
elif h.EnvActions.NOOP == agent.temp_action:
|
|
per_agent_info_dict[agent.name].update(no_op=1)
|
|
# per_agent_reward -= 0.00
|
|
|
|
# EnvMonitor Notes
|
|
if agent.temp_valid:
|
|
per_agent_info_dict[agent.name].update(valid_action=1)
|
|
per_agent_info_dict[agent.name].update({f'{agent.name}_valid_action': 1})
|
|
else:
|
|
per_agent_info_dict[agent.name].update(failed_action=1)
|
|
per_agent_info_dict[agent.name].update({f'{agent.name}_failed_action': 1})
|
|
|
|
additional_reward, additional_info_dict = self.calculate_additional_reward(agent)
|
|
per_agent_reward += additional_reward
|
|
per_agent_info_dict[agent.name].update(additional_info_dict)
|
|
|
|
if agent.temp_collisions:
|
|
self.print(f't = {self._steps}\t{agent.name} has collisions with {agent.temp_collisions}')
|
|
per_agent_info_dict[agent.name].update(collisions=1)
|
|
|
|
for other_agent in agent.temp_collisions:
|
|
per_agent_info_dict[agent.name].update({f'{agent.name}_vs_{other_agent.name}': 1})
|
|
reward[agent.name] = per_agent_reward
|
|
|
|
# Combine the per_agent_info_dict:
|
|
combined_info_dict = defaultdict(lambda: 0)
|
|
for info_dict in per_agent_info_dict.values():
|
|
for key, value in info_dict.items():
|
|
combined_info_dict[key] += value
|
|
combined_info_dict = dict(combined_info_dict)
|
|
|
|
if self.individual_rewards:
|
|
self.print(f"rewards are {reward}")
|
|
reward = list(reward.values())
|
|
return reward, combined_info_dict
|
|
else:
|
|
reward = sum(reward.values())
|
|
self.print(f"reward is {reward}")
|
|
return reward, combined_info_dict
|
|
|
|
# noinspection PyGlobalUndefined
|
|
def render(self, mode='human'):
|
|
if not self._renderer: # lazy init
|
|
from environments.factory.base.renderer import Renderer, RenderEntity
|
|
global Renderer, RenderEntity
|
|
height, width = self._level_shape
|
|
self._renderer = Renderer(width, height, view_radius=self._pomdp_r, fps=5)
|
|
|
|
# noinspection PyUnboundLocalVariable
|
|
walls = [RenderEntity('wall', wall.pos) for wall in self[c.WALLS]]
|
|
|
|
agents = []
|
|
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.temp_light_map))
|
|
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_additional_assets()
|
|
|
|
return self._renderer.render(walls + doors + additional_assets + agents)
|
|
|
|
def save_params(self, filepath: Path):
|
|
# noinspection PyProtectedMember
|
|
d = self.params
|
|
filepath.parent.mkdir(parents=True, exist_ok=True)
|
|
with filepath.open('w') as f:
|
|
simplejson.dump(d, f, indent=4, namedtuple_as_object=True)
|
|
|
|
def get_injected_agents(self) -> list:
|
|
if hasattr(self, '_initialized_injections'):
|
|
return self._initialized_injections
|
|
else:
|
|
return []
|
|
|
|
def _summarize_state(self):
|
|
summary = {f'{REC_TAC}step': self._steps}
|
|
|
|
for entity_group in self._entities:
|
|
summary.update({f'{REC_TAC}{entity_group.name}': entity_group.summarize_states(n_steps=self._steps)})
|
|
|
|
return summary
|
|
|
|
def print(self, string):
|
|
if self.verbose:
|
|
print(string)
|
|
|
|
# Properties which are called by the base class to extend beyond attributes of the base class
|
|
@property
|
|
def additional_actions(self) -> Union[Action, List[Action]]:
|
|
"""
|
|
When heriting from this Base Class, you musst implement this methode!!!
|
|
|
|
:return: A list of Actions-object holding all additional actions.
|
|
:rtype: List[Action]
|
|
"""
|
|
return []
|
|
|
|
@property
|
|
def additional_entities(self) -> Dict[(str, Entities)]:
|
|
"""
|
|
When heriting from this Base Class, you musst implement this methode!!!
|
|
|
|
:return: A single Entites collection or a list of such.
|
|
:rtype: Union[Entities, List[Entities]]
|
|
"""
|
|
return {}
|
|
|
|
# Functions which provide additions to functions of the base class
|
|
# Always call super!!!!!!
|
|
@abc.abstractmethod
|
|
def do_additional_reset(self) -> None:
|
|
pass
|
|
|
|
@abc.abstractmethod
|
|
def do_additional_step(self) -> dict:
|
|
return {}
|
|
|
|
@abc.abstractmethod
|
|
def do_additional_actions(self, agent: Agent, action: Action) -> Union[None, c]:
|
|
return None
|
|
|
|
@abc.abstractmethod
|
|
def check_additional_done(self) -> bool:
|
|
return False
|
|
|
|
@abc.abstractmethod
|
|
def _additional_observations(self) -> Dict[str, np.typing.ArrayLike]:
|
|
return {}
|
|
|
|
@abc.abstractmethod
|
|
def _additional_per_agent_raw_observations(self, agent) -> Dict[str, np.typing.ArrayLike]:
|
|
additional_raw_observations = {}
|
|
if self.obs_prop.show_global_position_info:
|
|
additional_raw_observations.update({c.GLOBAL_POSITION: self[c.GLOBAL_POSITION].by_entity(agent).as_array()})
|
|
return additional_raw_observations
|
|
|
|
@abc.abstractmethod
|
|
def calculate_additional_reward(self, agent: Agent) -> (int, dict):
|
|
return 0, {}
|
|
|
|
@abc.abstractmethod
|
|
def render_additional_assets(self):
|
|
return []
|
|
|
|
# Hooks for in between operations.
|
|
# Always call super!!!!!!
|
|
@abc.abstractmethod
|
|
def hook_pre_step(self) -> None:
|
|
pass
|
|
|
|
@abc.abstractmethod
|
|
def hook_post_step(self) -> dict:
|
|
return {}
|