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Adapted commit: "started visualization of routes in plot single runs, assets missing."

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Chanumask
2024-05-02 17:07:33 +02:00
committed by Julian Schönberger
parent 4571dc1cd1
commit 0d5b20a16f
13 changed files with 253 additions and 66 deletions
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8
marl_factory_grid/algorithms/static/TSP_base_agent.py
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@ -33,9 +33,11 @@ class TSPBaseAgent(ABC):
self.local_optimization = True
self._env = state
self.state = self._env.state[c.AGENT][agent_i]
self.spawn_position = np.array(self.state.pos)
self._position_graph = self.generate_pos_graph()
self._static_route = None
self.cached_route = None
self.action_list = []
@abstractmethod
def predict(self, *_, **__) -> int:
@ -78,7 +80,7 @@ class TSPBaseAgent(ABC):
start_time = time.time()
if self.cached_route is not None:
print(f" Used cached route: {self.cached_route}")
#print(f" Used cached route: {self.cached_route}")
return copy.deepcopy(self.cached_route)
else:
@ -99,11 +101,11 @@ class TSPBaseAgent(ABC):
route = tsp.traveling_salesman_problem(self._position_graph,
nodes=nodes, cycle=True, method=tsp.greedy_tsp)
self.cached_route = copy.deepcopy(route)
print(f"Cached route: {self.cached_route}")
#print(f"Cached route: {self.cached_route}")
end_time = time.time()
duration = end_time - start_time
print("TSP calculation took {:.2f} seconds to execute".format(duration))
#print("TSP calculation took {:.2f} seconds to execute".format(duration))
return route
def _door_is_close(self, state):

1
marl_factory_grid/algorithms/static/TSP_dirt_agent.py
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@ -28,6 +28,7 @@ class TSPDirtAgent(TSPBaseAgent):
action = self._use_door_or_move(door, di.DIRT)
else:
action = self._predict_move(di.DIRT)
self.action_list.append(action)
# Translate the action_object to an integer to have the same output as any other model
try:
action_obj = next(action_i for action_i, a in enumerate(self.state.actions) if a.name == action)

1
marl_factory_grid/algorithms/static/TSP_item_agent.py
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@ -36,6 +36,7 @@ class TSPItemAgent(TSPBaseAgent):
action = self._use_door_or_move(door, i.DROP_OFF if self.mode == MODE_BRING else i.ITEM)
else:
action = self._choose()
self.action_list.append(action)
# Translate the action_object to an integer to have the same output as any other model
try:
action_obj = next(action_i for action_i, a in enumerate(self.state.actions) if a.name == action)

1
marl_factory_grid/algorithms/static/TSP_target_agent.py
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@ -35,6 +35,7 @@ class TSPTargetAgent(TSPBaseAgent):
action = self._use_door_or_move(door, d.DESTINATION)
else:
action = self._predict_move(d.DESTINATION)
self.action_list.append(action)
# Translate the action_object to an integer to have the same output as any other model
try:
action_obj = next(action_i for action_i, a in enumerate(self.state.actions) if a.name == action)

92
marl_factory_grid/configs/test_config.yaml
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@ -1,45 +1,45 @@
Agents:
Clean test agent:
Actions:
- Noop
- Charge
- Clean
- DoorUse
- Move8
Observations:
- Combined:
- Other
- Walls
- GlobalPosition
- Battery
- ChargePods
- DirtPiles
- Destinations
- Doors
- Maintainers
Clones: 0
Item test agent:
Actions:
- Noop
- Charge
- DestAction
- DoorUse
- ItemAction
- Move8
Observations:
- Combined:
- Other
- Walls
- GlobalPosition
- Battery
- ChargePods
- Destinations
- Doors
- Items
- Inventory
- DropOffLocations
- Maintainers
Clones: 0
# Clean test agent:
# Actions:
# - Noop
# - Charge
# - Clean
# - DoorUse
# - Move8
# Observations:
# - Combined:
# - Other
# - Walls
# - GlobalPosition
# - Battery
# - ChargePods
# - DirtPiles
# - Destinations
# - Doors
# - Maintainers
# Clones: 0
# Item test agent:
# Actions:
# - Noop
# - Charge
# - DestAction
# - DoorUse
# - ItemAction
# - Move8
# Observations:
# - Combined:
# - Other
# - Walls
# - GlobalPosition
# - Battery
# - ChargePods
# - Destinations
# - Doors
# - Items
# - Inventory
# - DropOffLocations
# - Maintainers
# Clones: 0
Target test agent:
Actions:
- Noop
@ -55,7 +55,7 @@ Agents:
- Destinations
- Doors
- Maintainers
Clones: 0
Clones: 1
Entities:
@ -118,7 +118,7 @@ Rules:
max_steps: 500
Tests:
MaintainerTest: {}
DirtAgentTest: {}
ItemAgentTest: {}
TargetAgentTest: {}
# MaintainerTest: {}
# DirtAgentTest: {}
# ItemAgentTest: {}
# TargetAgentTest: {}

2
marl_factory_grid/utils/level_parser.py
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@ -42,6 +42,7 @@ class LevelParser(object):
level_array = h.one_hot_level(self._parsed_level, c.SYMBOL_WALL)
self.level_shape = level_array.shape
self.size = self.pomdp_r ** 2 if self.pomdp_r else np.prod(self.level_shape)
self.walls = None
def get_coordinates_for_symbol(self, symbol, negate=False) -> np.ndarray:
"""
@ -74,6 +75,7 @@ class LevelParser(object):
# Walls
walls = Walls.from_coordinates(self.get_coordinates_for_symbol(c.SYMBOL_WALL), self.size)
entities.add_items({c.WALLS: walls})
self.walls = self.get_coordinates_for_symbol(c.SYMBOL_WALL)
# Agents
entities.add_items({c.AGENT: Agents(self.size)})

2
marl_factory_grid/utils/logging/recorder.py
View File

@ -48,7 +48,7 @@ class EnvRecorder(Wrapper):
"""
obs_type, obs, reward, done, info = self.env.step(actions)
if not self.episodes or self._curr_episode in self.episodes:
summary: dict = self.env.summarize_state()
summary: dict = self.env.unwrapped.summarize_state()
# summary.update(done=done)
# summary.update({'episode': self._curr_episode})
# TODO Protobuff Adjustments ######

82
marl_factory_grid/utils/plotting/plot_single_runs.py
View File

@ -3,11 +3,15 @@ from os import PathLike
from pathlib import Path
from typing import Union
import numpy as np
import pandas as pd
from marl_factory_grid.utils.helpers import IGNORED_DF_COLUMNS
from marl_factory_grid.utils.plotting.plotting_utils import prepare_plot
from marl_factory_grid.utils.renderer import Renderer
from marl_factory_grid.utils.utility_classes import RenderEntity
def plot_single_run(run_path: Union[str, PathLike], use_tex: bool = False, column_keys=None,
file_key: str = 'monitor', file_ext: str = 'pkl'):
@ -60,3 +64,81 @@ def plot_single_run(run_path: Union[str, PathLike], use_tex: bool = False, colum
prepare_plot(run_path.parent / f'{run_path.parent.name}_monitor_lineplot.png', df_melted, use_tex=use_tex)
print('Plotting done.')
rotation_mapping = {
'north': ('cardinal', 0),
'east': ('cardinal', 270),
'south': ('cardinal', 180),
'west': ('cardinal', 90),
'northeast': ('diagonal', 0),
'southeast': ('diagonal', 270),
'southwest': ('diagonal', 180),
'northwest': ('diagonal', 90)
}
def plot_routes(factory, agents):
renderer = Renderer(factory.map.level_shape, custom_assets_path={
'cardinal': 'marl_factory_grid/utils/plotting/action_assets/cardinal.png',
'diagonal': 'marl_factory_grid/utils/plotting/action_assets/diagonal.png',
'door': 'marl_factory_grid/utils/plotting/action_assets/door.png',
'wall': 'marl_factory_grid/environment/assets/wall.png'})
wall_positions = factory.map.walls
for index, agent in enumerate(agents):
action_entities = []
# Add walls to the action_entities list
for pos in wall_positions:
wall_entity = RenderEntity(
name='wall',
probability=1.0,
pos=np.array(pos),
)
action_entities.append(wall_entity)
current_position = agent.spawn_position
if hasattr(agent, 'action_probabilities'):
# Handle RL agents with action probabilities
top_actions = sorted(agent.action_probabilities.items(), key=lambda x: -x[1])[:4]
else:
# Handle deterministic agents by iterating through all actions in the list
top_actions = [(action, 1.0) for action in agent.action_list]
for action, probability in top_actions:
base_icon, rotation = rotation_mapping.get(action.lower(), ('north', 0))
icon_name = base_icon
new_position = action_to_coords(current_position, action.lower())
print(f"current position type and value: {type(current_position)}, {new_position}")
action_entity = RenderEntity(
name=icon_name,
pos=np.array(current_position),
probability=probability,
rotation=rotation
)
action_entities.append(action_entity)
current_position = new_position
renderer.render_action_icons(action_entities)
def action_to_coords(current_position, action):
direction_mapping = {
'north': (0, -1),
'south': (0, 1),
'east': (1, 0),
'west': (-1, 0),
'northeast': (1, -1),
'northwest': (-1, -1),
'southeast': (1, 1),
'southwest': (-1, 1)
}
delta = direction_mapping.get(action)
if delta is not None:
new_position = [current_position[0] + delta[0], current_position[1] + delta[1]]
return new_position
print(f"No valid action found for {action}.")
return current_position

112
marl_factory_grid/utils/renderer.py
View File

@ -29,10 +29,9 @@ class Renderer:
AGENT_VIEW_COLOR = (9, 132, 227)
ASSETS = Path(__file__).parent.parent
def __init__(self, lvl_shape: Tuple[int, int] = (16, 16),
lvl_padded_shape: Union[Tuple[int, int], None] = None,
cell_size: int = 40, fps: int = 7, factor: float = 0.9,
grid_lines: bool = True, view_radius: int = 2):
def __init__(self, lvl_shape: Tuple[int, int] = (16, 16), lvl_padded_shape: Union[Tuple[int, int], None] = None,
cell_size: int = 40, fps: int = 7, factor: float = 0.9, grid_lines: bool = True, view_radius: int = 2,
custom_assets_path=None):
"""
The Renderer class initializes and manages the rendering environment for the simulation,
providing methods for preparing entities for display, loading assets, calculating visibility rectangles and
@ -53,7 +52,6 @@ class Renderer:
:param view_radius: Radius for agent's field of view.
:type view_radius: int
"""
# TODO: Custom_assets paths
self.grid_h, self.grid_w = lvl_shape
self.lvl_padded_shape = lvl_padded_shape if lvl_padded_shape is not None else lvl_shape
self.cell_size = cell_size
@ -64,8 +62,9 @@ class Renderer:
self.screen_size = (self.grid_w*cell_size, self.grid_h*cell_size)
self.screen = pygame.display.set_mode(self.screen_size)
self.clock = pygame.time.Clock()
assets = list(self.ASSETS.rglob('*.png'))
self.assets = {path.stem: self.load_asset(str(path), factor) for path in assets}
self.custom_assets_path = custom_assets_path
self.assets = self.load_assets(custom_assets_path)
self.save_counter = 1
self.fill_bg()
now = time.time()
@ -116,6 +115,28 @@ class Renderer:
rect.centerx, rect.centery = c_, r_
return dict(source=img, dest=rect)
def load_assets(self, custom_assets_path):
"""
Loads assets from the custom path if provided, otherwise from the default path.
"""
assets_directory = custom_assets_path if custom_assets_path else self.ASSETS
assets = {}
if isinstance(assets_directory, dict):
for key, path in assets_directory.items():
asset = self.load_asset(path)
if asset is not None:
assets[key] = asset
else:
print(f"Warning: Asset for key '{key}' is missing and was not loaded.")
else:
for path in Path(assets_directory).rglob('*.png'):
asset = self.load_asset(str(path))
if asset is not None:
assets[path.stem] = asset
else:
print(f"Warning: Asset '{path.stem}' is missing and was not loaded.")
return assets
def load_asset(self, path, factor=1.0):
"""
Loads and resizes an asset from the specified path.
@ -126,10 +147,28 @@ class Renderer:
:type factor: float
:return: Resized asset.
"""
s = int(factor*self.cell_size)
asset = pygame.image.load(path).convert_alpha()
asset = pygame.transform.smoothscale(asset, (s, s))
return asset
try:
s = int(factor * self.cell_size)
asset = pygame.image.load(path).convert_alpha()
asset = pygame.transform.smoothscale(asset, (s, s))
return asset
except pygame.error as e:
print(f"Failed to load asset {path}: {e}")
return self.load_default_asset()
def load_default_asset(self, factor=1.0):
"""
Loads a default asset to be used when specific assets fail to load.
"""
default_path = 'marl_factory_grid/utils/plotting/action_assets/default.png'
try:
s = int(factor * self.cell_size)
default_asset = pygame.image.load(default_path).convert_alpha()
default_asset = pygame.transform.smoothscale(default_asset, (s, s))
return default_asset
except pygame.error as e:
print(f"Failed to load default asset: {e}")
return None
def visibility_rects(self, bp, view):
"""
@ -201,9 +240,58 @@ class Renderer:
return np.transpose(rgb_obs, (2, 0, 1))
# return torch.from_numpy(rgb_obs).permute(2, 0, 1)
def render_action_icons(self, action_entities):
"""
Renders action icons based on the entities' specified actions, positions, and probabilities.
:param action_entities: List of entities representing actions.
:type action_entities: List[RenderEntity]
"""
self.fill_bg() # Clear the background
font = pygame.font.Font(None, 24) # Initialize the font once for all text rendering
for action_entity in action_entities:
if not isinstance(action_entity.pos, np.ndarray) or action_entity.pos.ndim != 1:
print(f"Invalid position format for entity: {action_entity.pos}")
continue
# Load and potentially rotate the icon based on action name
img = self.assets[action_entity.name.lower()]
if hasattr(action_entity, 'rotation'):
img = pygame.transform.rotate(img, action_entity.rotation)
if img is None:
print(f"Error: No asset available for '{action_entity.name}'. Skipping rendering this entity.")
continue
# Blit the icon image
img_rect = img.get_rect(center=(action_entity.pos[0] * self.cell_size + self.cell_size // 2,
action_entity.pos[1] * self.cell_size + self.cell_size // 2))
self.screen.blit(img, img_rect)
# Render the probability next to the icon if it exists
if hasattr(action_entity, 'probability'):
prob_text = font.render(f"{action_entity.probability:.2f}", True, (255, 0, 0))
prob_text_rect = prob_text.get_rect(top=img_rect.bottom, left=img_rect.left)
self.screen.blit(prob_text, prob_text_rect)
pygame.display.flip() # Update the display with all new blits
self.save_screen("route_graph")
def save_screen(self, filename):
"""
Saves the current screen to a PNG file, appending a counter to ensure uniqueness.
:param filename: The base filename where to save the image.
:param agent_id: Unique identifier for the agent.
"""
unique_filename = f"{filename}_agent_{self.save_counter}.png"
self.save_counter += 1
pygame.image.save(self.screen, unique_filename)
print(f"Image saved as {unique_filename}")
if __name__ == '__main__':
renderer = Renderer(fps=2, cell_size=40)
renderer = Renderer(cell_size=40, fps=2)
for pos_i in range(15):
entity_1 = RenderEntity('agent_collision', [5, pos_i], 1, 'idle', 'idle')
renderer.render([entity_1])

2
marl_factory_grid/utils/utility_classes.py
View File

@ -33,6 +33,8 @@ class RenderEntity:
id: int = 0
aux: Any = None
real_name: str = 'none'
probability: float = None # Default to None if not used
rotation: int = 0 # Default rotation if not specified
@dataclass

2
studies/marl_adapted.py
View File

@ -94,4 +94,4 @@ def two_rooms_one_door_modified_multi_agent_eval(emergent_phenomenon):
if __name__ == '__main__':
dirt_quadrant_single_agent_training()
dirt_quadrant_5_multi_agent_ctde_eval(True)

2
studies/tsp_runs.py
View File

@ -104,4 +104,4 @@ def two_rooms_one_door_modified_multi_agent_tsp(emergent_phenomenon):
if __name__ == '__main__':
dirt_quadrant_multi_agent_tsp(False)
two_rooms_one_door_modified_multi_agent_tsp(False)

12
test_run.py
View File

@ -1,4 +1,5 @@
from pathlib import Path
from pprint import pprint
from tqdm import trange
@ -7,12 +8,17 @@ from marl_factory_grid.algorithms.static.TSP_item_agent import TSPItemAgent
from marl_factory_grid.algorithms.static.TSP_target_agent import TSPTargetAgent
from marl_factory_grid.environment.factory import Factory
from marl_factory_grid.utils.plotting.plot_single_runs import plot_routes
if __name__ == '__main__':
# Render at each step?
run_path = Path('study_out')
render = True
monitor = True
record = True
# Path to config File
path = Path('marl_factory_grid/configs/simple_crossing.yaml')
path = Path('marl_factory_grid/configs/test_config.yaml')
# Env Init
factory = Factory(path)
@ -33,3 +39,5 @@ if __name__ == '__main__':
if done:
print(f'Episode {episode} done...')
break
plot_routes(factory, agents, )