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more work on setting up the framework 

- changed querying of NN
- drawing of clusters
- drawing of test results
- save each test runs individual observations
- etc.
add_velocity_into_framework
sp 6 months ago
parent
e7b5f8344b
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5d5f6ea38c
1 changed files with 76 additions and 65 deletions
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  1. 139
      rom_evaluate.py

139
rom_evaluate.py
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@ -70,24 +70,9 @@ def exec(command,verbose=True):
system(f"echo {command} >> list_of_exec")
return system(command)
num_tests_per_cluster = 50
factor_tests_per_cluster = 0.2
num_ski_positions = 8
def model_to_actual(ski_position):
if ski_position == 1:
return 1
elif ski_position in [2,3]:
return 2
elif ski_position in [4,5]:
return 3
elif ski_position in [6,7]:
return 4
elif ski_position in [8,9]:
return 5
elif ski_position in [10,11]:
return 6
elif ski_position in [12,13]:
return 7
elif ski_position == 14:
return 8
def input_to_action(char):
if char == "0":
@ -117,9 +102,20 @@ def drawImportantStates(important_states):
command = f"convert images/1_full_scaled_down.png {' '.join(draw_commands[i])} first_try_{i:02}.png"
exec(command)
def saveObservations(observations, verdict, testDir):
testDir = f"images/testing_{experiment_id}/{verdict.name}_{testDir}_{len(observations)}"
if len(observations) < 20:
logger.warn(f"Potentially spurious test case for {testDir}")
testDir = f"{testDir}_pot_spurious"
exec(f"mkdir {testDir}", verbose=False)
for i, obs in enumerate(observations):
img = Image.fromarray(obs)
img.save(f"{testDir}/{i:003}.png")
ski_position_counter = {1: (Action.LEFT, 40), 2: (Action.LEFT, 35), 3: (Action.LEFT, 30), 4: (Action.LEFT, 10), 5: (Action.NOOP, 1), 6: (Action.RIGHT, 10), 7: (Action.RIGHT, 30), 8: (Action.RIGHT, 40) }
def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=200):
#print(f"Running Test from x: {x:04}, y: {y:04}, ski_position: {ski_position}", end="")
testDir = f"{x}_{y}_{ski_position}"
for i, r in enumerate(ramDICT[y]):
ale.setRAM(i,r)
ski_position_setting = ski_position_counter[ski_position]
@ -134,7 +130,8 @@ def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=200):
first_action_set = False
first_action = 0
for i in range(0,duration):
resized_obs = cv2.resize(ale.getScreenGrayscale() , (84,84), interpolation=cv2.INTER_AREA)
resized_obs = cv2.resize(ale.getScreenGrayscale(), (84,84), interpolation=cv2.INTER_AREA)
for i in range(0,4):
all_obs.append(resized_obs)
if len(all_obs) >= 4:
stack_tensor = TensorDict({"obs": np.array(all_obs[-4:])})
@ -147,9 +144,10 @@ def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=200):
ale.act(Action.NOOP)
speed_list.append(ale.getRAM()[14])
if len(speed_list) > 15 and sum(speed_list[-6:-1]) == 0:
return (Verdict.BAD, first_action)
#time.sleep(0.005)
return (Verdict.INCONCLUSIVE, first_action)
saveObservations(all_obs, Verdict.BAD, testDir)
return Verdict.BAD
saveObservations(all_obs, Verdict.GOOD, testDir)
return Verdict.GOOD
def optimalAction(choices):
return max(choices.items(), key=operator.itemgetter(1))[0]
@ -245,19 +243,16 @@ x = 70
nn_wrapper = SampleFactoryNNQueryWrapper()
iteration = 0
id = int(time.time())
init_mdp = "velocity"
exec(f"mkdir -p images/testing_{id}")
exec(f"cp 1_full_scaled_down.png images/testing_{id}/testing_0000.png")
experiment_id = int(time.time())
init_mdp = "velocity_safety"
exec(f"mkdir -p images/testing_{experiment_id}")
exec(f"cp 1_full_scaled_down.png images/testing_{experiment_id}/testing_0000.png")
exec(f"cp {init_mdp}.prism {init_mdp}_000.prism")
markerSize = 1
#markerList = {1: list(), 2:list(), 3:list(), 4:list(), 5:list(), 6:list(), 7:list(), 8:list()}
def f(n):
if n >= 1.0:
return True
return False
imagesDir = f"images/testing_{experiment_id}"
def drawOntoSkiPosImage(states, color, target_prefix="cluster_", alpha_factor=1.0):
markerList = {ski_position:list() for ski_position in range(1,num_ski_positions + 1)}
@ -266,12 +261,13 @@ def drawOntoSkiPosImage(states, color, target_prefix="cluster_", alpha_factor=1.
marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
markerList[s.ski_position].append(marker)
for pos, marker in markerList.items():
command = f"convert images/testing_{id}/{target_prefix}_{pos:02}.png {' '.join(marker)} images/testing_{id}/{target_prefix}_{pos:02}.png"
command = f"convert {imagesDir}/{target_prefix}_{pos:02}.png {' '.join(marker)} {imagesDir}/{target_prefix}_{pos:02}.png"
exec(command, verbose=False)
def concatImages(prefix):
exec(f"montage images/testing_{id}/{prefix}_*png -geometry +0+0 -tile x1 images/testing_{id}/{prefix}.png", verbose=False)
exec(f"montage {imagesDir}/{prefix}_*png -geometry +0+0 -tile x1 {imagesDir}/{prefix}.png", verbose=False)
exec(f"sxiv {imagesDir}/{prefix}.png&")
def drawStatesOntoTiledImage(states, color, target, source="images/1_full_scaled_down.png", alpha_factor=1.0):
"""
@ -285,20 +281,32 @@ def drawStatesOntoTiledImage(states, color, target, source="images/1_full_scaled
marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
markerList[s.ski_position].append(marker)
for pos, marker in markerList.items():
command = f"convert {source} {' '.join(marker)} images/testing_{id}/{target}_{pos:02}.png"
command = f"convert {source} {' '.join(marker)} {imagesDir}/{target}_{pos:02}.png"
exec(command, verbose=False)
exec(f"montage images/testing_{id}/{target}_*png -geometry +0+0 -tile x1 images/testing_{id}/{target}.png", verbose=False)
exec(f"montage {imagesDir}/{target}_*png -geometry +0+0 -tile x1 {imagesDir}/{target}.png", verbose=False)
logger.info(f"Drawing {len(states)} states onto {target} - Done: took {toc()} seconds")
def drawClusters(clusterDict, target, alpha_factor=1.0):
for ski_position in range(1, num_ski_positions + 1):
source = "images/1_full_scaled_down.png"
exec(f"cp {source} images/testing_{id}/{target}_{ski_position:02}.png")
exec(f"cp {source} {imagesDir}/{target}_{ski_position:02}.png")
for _, clusterStates in clusterDict.items():
color = f"{np.random.choice(range(256))}, {np.random.choice(range(256))}, {np.random.choice(range(256))}"
drawOntoSkiPosImage(clusterStates, color, f"clusters")
concatImages("clusters")
drawOntoSkiPosImage(clusterStates, color, target, alpha_factor=alpha_factor)
concatImages(target)
def drawResult(clusterDict, target):
for ski_position in range(1, num_ski_positions + 1):
source = "images/1_full_scaled_down.png"
exec(f"cp {source} {imagesDir}/{target}_{ski_position:02}.png")
for _, (clusterStates, result) in clusterDict.items():
color = "100,100,100"
if result == Verdict.GOOD:
color = "0,200,0"
elif result == Verdict.BAD:
color = "200,0,0"
drawOntoSkiPosImage(clusterStates, color, target, alpha_factor=0.7)
concatImages(target)
def _init_logger():
logger = logging.getLogger('main')
@ -308,7 +316,7 @@ def _init_logger():
handler.setFormatter(formatter)
logger.addHandler(handler)
def clusterImportantStates(ranking, n_clusters=10):
def clusterImportantStates(ranking, n_clusters=40):
logger.info(f"Starting to cluster {len(ranking)} states into {n_clusters} cluster")
tic()
states = [[s[0].x,s[0].y, s[0].ski_position * 10, s[1].ranking] for s in ranking]
@ -324,36 +332,39 @@ if __name__ == '__main__':
_init_logger()
logger = logging.getLogger('main')
logger.info("Starting")
n_clusters = 40
testAll = False
while True:
#computeStateRanking(f"{init_mdp}_{iteration:03}.prism")
ranking = fillStateRanking("action_ranking")
sorted_ranking = sorted( (x for x in ranking.items() if x[1].ranking > 0.1), key=lambda x: x[1].ranking)
print(type(sorted_ranking))
clusters = clusterImportantStates(sorted_ranking)
sys.exit(1)
#for i, state in enumerate(sorted_ranking):
# print(state)
# if i % 10 == 0:
# input("")
#print(len(sorted_ranking))
"""
for important_state in ranking[-100:-1]:
optimal_choice = optimalAction(important_state[1].choices)
#print(important_state[1].choices, f"\t\tOptimal: {optimal_choice}")
x = important_state[0].x
y = important_state[0].y
ski_pos = model_to_actual(important_state[0].ski_position)
clusters = clusterImportantStates(sorted_ranking, n_clusters)
if testAll: failingPerCluster = {i: list() for i in range(0, n_clusters)}
clusterResult = dict()
for id, cluster in clusters.items():
num_tests = int(factor_tests_per_cluster * len(cluster))
num_tests = 1
logger.info(f"Testing {num_tests} states (from {len(cluster)} states) from cluster {id}")
randomStates = np.random.choice(len(cluster), num_tests, replace=False)
randomStates = [cluster[i] for i in randomStates]
verdictGood = True
for state in randomStates:
x = state[0].x
y = state[0].y
ski_pos = state[0].ski_position
result = run_single_test(ale,nn_wrapper,x,y,ski_pos, duration=50)
#print(f".... {result}")
marker = f"-fill 'rgba({verdict_to_color_map[result[0]],0.7})' -draw 'rectangle {x-markerSize},{y-markerSize} {x+markerSize},{y+markerSize} '"
markerList[ski_pos].append(marker)
populate_fixed_actions(important_state[0], result[1])
for pos, marker in markerList.items():
command = f"convert images/testing_{id}/testing_0000.png {' '.join(marker)} images/testing_{id}/testing_{iteration+1:03}_{pos:02}.png"
exec(command, verbose=False)
exec(f"montage images/testing_{id}/testing_{iteration+1:03}_*png -geometry +0+0 -tile x1 images/testing_{id}/{iteration+1:03}.png", verbose=False)
iteration += 1
"""
if result == Verdict.BAD:
if testAll:
failingPerCluster[id].append(state)
else:
clusterResult[id] = (cluster, Verdict.BAD)
verdictGood = False
break
if verdictGood:
clusterResult[id] = (cluster, Verdict.GOOD)
if testAll: drawClusters(failingPerCluster, f"failing")
drawResult(clusterResult, "result")
update_prism_file(f"{init_mdp}_{iteration-1:03}.prism", f"{init_mdp}_{iteration:03}.prism")
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