def mouse_test(maze, mouse, mode):
if (mode != 'complete') and (mode != 'incomplete'):
raise Exception('Argument Error!')
testmaze = maze
testmouse = mouse
starting = [0,0]
destination_final = testmaze.destinations
location_real = starting[:]
orientation_real = 'up'
location_reference = starting[:]
orientation_reference = orientation_real
location_last = starting[:]
num_actions_1 = 0
length_movement_1 = 0
num_actions_2 = 0
length_movement_2 = 0
num_actions_3 = 0
length_movement_3 = 0
exploration_time = 0
maze_visited_observed = np.zeros((testmaze.dim_x, testmaze.dim_y), dtype = np.int32)
maze_visited_observed[tuple(starting)] = 1
percentage_maze_visited_observed = float(np.sum(maze_visited_observed))/(maze_visited_observed.shape[0] * maze_visited_observed.shape[1])
exploration_start = time.time()
while ((testmouse.percentage_visited < 1.0) if (mode == 'complete') else (testmouse.found_destination == False)):
destination_best, direction_list, movement_list, path_list = testmouse.mouse_action(maze = testmaze, location_real = location_real, orientation_real = orientation_real)
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = direction))
movement_list_observed = movement_list[:]
location_real = coordinate_observed(reference_mouse = testmouse.location_reference, reference_observed = location_reference, coordinate_mouse = testmouse.location_defined)
orientation_real = orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = testmouse.orientation)
location_expected = destination_expectation(maze = testmaze, starting = location_last, direction_list = direction_list_observed, movement_list = movement_list_observed)
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
maze_visited_observed[tuple(location_real)] = 1
percentage_maze_visited_observed = float(np.sum(maze_visited_observed))/(maze_visited_observed.shape[0] * maze_visited_observed.shape[1])
if location_real in destination_final:
testmouse.found_destination = True
testmouse.destinations.append(testmouse.location_defined)
num_actions_1 += (len(path_list) - 1)
length_movement_1 += length_count(path_list = path_list)
location_last = location_real
exploration_end = time.time()
exploration_time = exploration_end - exploration_start
direction_list, movement_list, path_list = testmouse.return_origin()
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = direction))
movement_list_observed = movement_list[:]
location_real = coordinate_observed(reference_mouse = testmouse.location_reference, reference_observed = location_reference, coordinate_mouse = testmouse.location_defined)
orientation_real = orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = testmouse.orientation)
location_expected = destination_expectation(maze = testmaze, starting = location_last, direction_list = direction_list_observed, movement_list = movement_list_observed)
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
location_last = location_real
num_actions_2 += (len(path_list) - 1)
length_movement_2 += length_count(path_list = path_list)
direction_list, movement_list, path_list = testmouse.go_destinations()
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = direction))
movement_list_observed = movement_list[:]
location_real = coordinate_observed(reference_mouse = testmouse.location_reference, reference_observed = location_reference, coordinate_mouse = testmouse.location_defined)
orientation_real = orientation_observed(reference_mouse = testmouse.orientation_reference, reference_observed = orientation_reference, orientation_mouse = testmouse.orientation)
location_expected = destination_expectation(maze = testmaze, starting = location_last, direction_list = direction_list_observed, movement_list = movement_list_observed)
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
location_last = location_real
num_actions_3 += (len(path_list) - 1)
length_movement_3 += length_count(path_list = path_list)
score = num_actions_3 + 1./30 * (num_actions_1 + num_actions_2)
return (num_actions_1, length_movement_1, num_actions_2, length_movement_2, num_actions_3, length_movement_3, percentage_maze_visited_observed, score, exploration_time)
# Current mouse location observed
location_real = coordinate_observed(
reference_mouse=testmouse.location_reference,
reference_observed=location_reference,
coordinate_mouse=testmouse.location_defined)
# Current mouse orientation observed
orientation_real = orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=testmouse.orientation)
# Expected mouse location based on the directions and movements
location_expected = destination_expectation(
maze=testmaze,
starting=location_last,
direction_list=direction_list_observed,
movement_list=movement_list_observed)
# Check whether location_real and location_expected match
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
# Update observed maze_visited
maze_visited_observed[tuple(location_real)] = 1
percentage_maze_visited_observed = float(
np.sum(maze_visited_observed)) / (maze_visited_observed.shape[0] *
maze_visited_observed.shape[1])
# Check if the mouse reached final destination
if location_real in destination_final:
def mouse_test(maze, mouse, mode):
# Check arguments
if (mode != 'complete') and (mode != 'incomplete'):
raise Exception('Argument Error!')
testmaze = maze
testmouse = mouse
# Initialize the micromouse
starting = [0, 0]
destination_final = testmaze.destinations
location_real = starting[:]
orientation_real = 'up'
# Set references
location_reference = starting[:]
orientation_reference = orientation_real
# Set last location
location_last = starting[:]
# Stage 1: Mouse exploration
# Statistics
num_actions_1 = 0
length_movement_1 = 0
num_actions_2 = 0
length_movement_2 = 0
num_actions_3 = 0
length_movement_3 = 0
exploration_time = 0
maze_visited_observed = np.zeros((testmaze.dim_x, testmaze.dim_y),
dtype=np.int32)
maze_visited_observed[tuple(starting)] = 1
percentage_maze_visited_observed = float(np.sum(maze_visited_observed)) / (
maze_visited_observed.shape[0] * maze_visited_observed.shape[1])
# Explore the maze
# If argument 1 is 'incomplete', return when mouse found destination
# If argument 2 is 'complete', return when mouse visited all the grids reachable
exploration_start = time.time()
while ((testmouse.percentage_visited < 1.0) if (mode == 'complete') else
(testmouse.found_destination == False)):
# Action parameters of mouse
destination_best, direction_list, movement_list, path_list = testmouse.mouse_action(
maze=testmaze,
location_real=location_real,
orientation_real=orientation_real)
# Action parameters observed
# Directions
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(
orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=direction))
# Movements
movement_list_observed = movement_list[:]
# Current mouse location observed
location_real = coordinate_observed(
reference_mouse=testmouse.location_reference,
reference_observed=location_reference,
coordinate_mouse=testmouse.location_defined)
# Current mouse orientation observed
orientation_real = orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=testmouse.orientation)
# Expected mouse location based on the directions and movements
location_expected = destination_expectation(
maze=testmaze,
starting=location_last,
direction_list=direction_list_observed,
movement_list=movement_list_observed)
# Check whether location_real and location_expected match
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
# Update observed maze_visited
maze_visited_observed[tuple(location_real)] = 1
percentage_maze_visited_observed = float(
np.sum(maze_visited_observed)) / (maze_visited_observed.shape[0] *
maze_visited_observed.shape[1])
# Check if the mouse reached final destination
if location_real in destination_final:
testmouse.found_destination = True
testmouse.destinations.append(testmouse.location_defined)
# Count number of actions
num_actions_1 += (len(path_list) - 1)
# Count the length of movements
length_movement_1 += length_count(path_list=path_list)
# Update location_last
location_last = location_real
#print('location_real',location_real)
#print('total num_actions',num_actions_1)
#print('length_movement',length_movement_1)
#print('coverage',percentage_maze_visited_observed)
exploration_end = time.time()
exploration_time = exploration_end - exploration_start
# Stage 2: Mouse goes back to starting point
# The actions of mouse in this stage were not accounted in the total actions
direction_list, movement_list, path_list = testmouse.return_origin()
# Action parameters observed
# Directions
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(
orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=direction))
# Movements
movement_list_observed = movement_list[:]
# Current mouse location observed
location_real = coordinate_observed(
reference_mouse=testmouse.location_reference,
reference_observed=location_reference,
coordinate_mouse=testmouse.location_defined)
# Current mouse orientation observed
orientation_real = orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=testmouse.orientation)
# Expected mouse location based on the directions and movements
location_expected = destination_expectation(
maze=testmaze,
starting=location_last,
direction_list=direction_list_observed,
movement_list=movement_list_observed)
# Check whether location_real and location_expected match
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
# Update location_last
location_last = location_real
# Count number of actions
num_actions_2 += (len(path_list) - 1)
# Count the length of movements
length_movement_2 += length_count(path_list=path_list)
# Stage 3: Mouse goes to the destination again
direction_list, movement_list, path_list = testmouse.go_destinations()
# Action parameters observed
# Directions
direction_list_observed = list()
for direction in direction_list:
direction_list_observed.append(
orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=direction))
# Movements
movement_list_observed = movement_list[:]
# Current mouse location observed
location_real = coordinate_observed(
reference_mouse=testmouse.location_reference,
reference_observed=location_reference,
coordinate_mouse=testmouse.location_defined)
# Current mouse orientation observed
orientation_real = orientation_observed(
reference_mouse=testmouse.orientation_reference,
reference_observed=orientation_reference,
orientation_mouse=testmouse.orientation)
# Expected mouse location based on the directions and movements
location_expected = destination_expectation(
maze=testmaze,
starting=location_last,
direction_list=direction_list_observed,
movement_list=movement_list_observed)
# Check whether location_real and location_expected match
if location_real != location_expected:
print('Warning: location_expected did not match location_real.')
# Update location_last
location_last = location_real
# Count number of actions
num_actions_3 += (len(path_list) - 1)
# Count the length of movements
length_movement_3 += length_count(path_list=path_list)
#print('total num_actions',num_actions_2)
#print('length_movement',length_movement_2)
#print('Final score', num_actions_2 + 1./30 * num_actions_1)
score = num_actions_3 + 1. / 30 * (num_actions_1 + num_actions_2)
return (num_actions_1, length_movement_1, num_actions_2, length_movement_2,
num_actions_3, length_movement_3, percentage_maze_visited_observed,
score, exploration_time)