116 lines
3.7 KiB
Python
116 lines
3.7 KiB
Python
import time
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from collections import deque
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from typing import List, Union, NamedTuple
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import numpy as np
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from environments.helpers import Constants as c
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from environments import helpers as h
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from environments.factory.base.base_factory import BaseFactory
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from environments.factory.base.objects import Agent, Action, Object, Slice, Entity
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from environments.factory.base.registers import Entities
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from environments.factory.renderer import Renderer
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from environments.utility_classes import MovementProperties
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ITEM = 'item'
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INVENTORY = 'inventory'
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PICK_UP = 'pick_up'
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DROP_DOWN = 'drop_down'
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ITEM_ACTION = 'item_action'
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NO_ITEM = 0
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ITEM_DROP_OFF = -1
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def inventory_slice_name(agent):
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return f'{agent.name}_{INVENTORY}'
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class DropOffLocation(Entity):
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def __init__(self, *args, storage_size_until_full: int = 5, **kwargs):
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super(DropOffLocation, self).__init__(*args, **kwargs)
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self.storage = deque(maxlen=storage_size_until_full)
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def place_item(self, item):
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self.storage.append(item)
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return True
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@property
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def is_full(self):
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return self.storage.maxlen == len(self.storage)
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class ItemProperties(NamedTuple):
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n_items: int = 1 # How many items are there at the same time
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spawn_frequency: int = 5 # Spawn Frequency in Steps
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max_dropoff_storage_size: int = 5 # How many items are needed until the drop off is full
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max_agent_storage_size: int = 5 # How many items are needed until the agent inventory is full
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# noinspection PyAttributeOutsideInit
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class ItemFactory(BaseFactory):
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def __init__(self, item_properties: ItemProperties, *args, **kwargs):
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self.item_properties = item_properties
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self._item_rng = np.random.default_rng(kwargs.get('seed', default=time.time_ns()))
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super(ItemFactory, self).__init__(*args, **kwargs)
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@property
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def additional_actions(self) -> Union[str, List[str]]:
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return [ITEM_ACTION]
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@property
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def additional_entities(self) -> Union[Entities, List[Entities]]:
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return []
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@property
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def additional_slices(self) -> Union[Slice, List[Slice]]:
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return [Slice(ITEM, np.zeros(self._level_shape))] + [
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Slice(inventory_slice_name(agent), np.zeros(self._level_shape)) for agent in self._agents]
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def _is_item_action(self, action):
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if isinstance(action, str):
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action = self._actions.by_name(action)
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return self._actions[action].name == ITEM_ACTION
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def do_item_action(self, agent):
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item_slice = self._slices.by_name(ITEM).slice
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inventory_slice = self._slices.by_name(inventory_slice_name(agent)).slice
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if item := item_slice[agent.pos]:
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if item == ITEM_DROP_OFF:
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valid = self._item_drop_off.place_item(inventory_slice.sum())
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item_slice[agent.pos] = NO_ITEM
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return True
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else:
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return False
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def do_additional_actions(self, agent: Agent, action: int) -> bool:
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if self._is_item_action(action):
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valid = self.do_item_action(agent)
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return valid
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else:
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raise RuntimeError('This should not happen!!!')
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def do_additional_reset(self) -> None:
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self.spawn_drop_off_location()
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self.spawn_items(self.n_items)
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if self.n_items > 1:
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self._next_item_spawn = self.item_properties.spawn_frequency
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def spawn_drop_off_location(self):
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single_empty_tile = self._tiles.empty_tiles[0]
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self._item_drop_off = DropOffLocation(storage_size_until_full=self.item_properties.max_dropoff_storage_size)
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def calculate_reward(self) -> (int, dict):
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pass
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def render(self, mode='human'):
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pass
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