steffen-illium ff9846eb54 No more Monitor,
env hparams pickeling,
pomdp,
now training and learning
2021-06-01 16:38:55 +02:00

79 lines
2.1 KiB
Python

import numpy as np
from pathlib import Path
# Constants
WALL = '#'
LEVELS_DIR = 'levels'
LEVEL_IDX = 0
AGENT_START_IDX = 1
IS_FREE_CELL = 0
IS_OCCUPIED_CELL = 1
TO_BE_AVERAGED = ['dirt_amount', 'dirty_tiles']
IGNORED_DF_COLUMNS = ['Episode', 'Run', 'train_step', 'step', 'index', 'dirt_amount', 'dirty_tile_count']
# Utility functions
def parse_level(path):
with path.open('r') as lvl:
level = list(map(lambda x: list(x.strip()), lvl.readlines()))
if len(set([len(line) for line in level])) > 1:
raise AssertionError('Every row of the level string must be of equal length.')
return level
def one_hot_level(level, wall_char=WALL):
grid = np.array(level)
binary_grid = np.zeros(grid.shape, dtype=np.int8)
binary_grid[grid == wall_char] = 1
return binary_grid
def check_agent_move(state, dim, action):
agent_slice = state[dim] # horizontal slice from state tensor
agent_pos = np.argwhere(agent_slice == 1)
if len(agent_pos) > 1:
raise AssertionError('Only one agent per slice is allowed.')
x, y = agent_pos[0]
x_new, y_new = x, y
# Actions
if action == 0: # North
x_new -= 1
elif action == 1: # East
y_new += 1
elif action == 2: # South
x_new += 1
elif action == 3: # West
y_new -= 1
elif action == 4: # NE
x_new -= 1
y_new += 1
elif action == 5: # SE
x_new += 1
y_new += 1
elif action == 6: # SW
x_new += 1
y_new -= 1
elif action == 7: # NW
x_new -= 1
y_new -= 1
else:
pass
# Check if agent colides with grid boundrys
valid = not (
x_new < 0 or y_new < 0
or x_new >= agent_slice.shape[0]
or y_new >= agent_slice.shape[0]
)
# Check for collision with level walls
valid = valid and not state[LEVEL_IDX][x_new, y_new]
return (x, y), (x_new, y_new), valid
if __name__ == '__main__':
parsed_level = parse_level(Path(__file__).parent / 'factory' / 'levels' / 'simple.txt')
y = one_hot_level(parsed_level)
print(np.argwhere(y == 0))