sp
/
Skiing
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

redid querying

add_velocity_into_framework
sp 8 months ago
parent
4d6733b6d8
commit
019ea0ad1e
1 changed files with 53 additions and 35 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 88
      rom_evaluate.py

88
rom_evaluate.py
View File

@ -1,6 +1,7 @@
import sys
import operator
from os import listdir, system
import subprocess
import re
from collections import defaultdict
@ -104,6 +105,7 @@ def saveObservations(observations, verdict, testDir):
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, velocity, duration=50):
def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=50):
#print(f"Running Test from x: {x:04}, y: {y:04}, ski_position: {ski_position}", end="")
@ -119,19 +121,18 @@ def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=50):
all_obs = list()
speed_list = list()
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)
for i in range(0,4):
all_obs.append(resized_obs)
for i in range(0,duration-4):
resized_obs = cv2.resize(ale.getScreenGrayscale(), (84,84), interpolation=cv2.INTER_AREA)
if len(all_obs) >= 4:
all_obs.append(resized_obs)
if i % 4 == 0:
stack_tensor = TensorDict({"obs": np.array(all_obs[-4:])})
action = nn_wrapper.query(stack_tensor)
if not first_action_set:
first_action_set = True
first_action = input_to_action(str(action))
ale.act(input_to_action(str(action)))
else:
ale.act(Action.NOOP)
ale.act(input_to_action(str(action)))
speed_list.append(ale.getRAM()[14])
if len(speed_list) > 15 and sum(speed_list[-6:-1]) == 0:
saveObservations(all_obs, Verdict.BAD, testDir)
@ -139,14 +140,16 @@ def run_single_test(ale, nn_wrapper, x,y,ski_position, duration=50):
saveObservations(all_obs, Verdict.GOOD, testDir)
return Verdict.GOOD
def optimalAction(choices):
return max(choices.items(), key=operator.itemgetter(1))[0]
def computeStateRanking(mdp_file):
logger.info("Computing state ranking")
tic()
command = f"{tempest_binary} --prism {mdp_file} --buildchoicelab --buildstateval --build-all-labels --prop 'Rmax=? [C <= 1000]'"
exec(command)
try:
command = f"{tempest_binary} --prism {mdp_file} --buildchoicelab --buildstateval --build-all-labels --prop 'Rmax=? [C <= 1000]'"
result = subprocess.run(command, shell=True, check=True)
print(result)
except Exception as e:
print(e)
sys.exit(-1)
logger.info(f"Computing state ranking - DONE: took {toc()} seconds")
def fillStateRanking(file_name, match=""):
@ -221,26 +224,37 @@ def clusterFormula(cluster):
formula += ")"
return formula
def createBalancedDisjunction(indices, name):
#logger.info(f"Creating balanced disjunction for {len(indices)} ({indices}) formulas")
if len(indices) == 0:
return f"formula {name} = false;\n"
else:
while len(indices) > 1:
indices_tmp = [f"({indices[i]} | {indices[i+1]})" for i in range(0,len(indices)//2)]
if len(indices) % 2 == 1:
indices_tmp.append(indices[-1])
indices = indices_tmp
disjunction = f"formula {name} = " + " ".join(indices) + ";\n"
return disjunction
def createUnsafeFormula(clusters):
label = "label \"Unsafe\" = Unsafe;\n"
formulas = ""
disjunction = "formula Unsafe = false"
indices = list()
for i, cluster in enumerate(clusters):
formulas += f"formula Unsafe_{i} = {clusterFormula(cluster)};\n"
clusterFormula(cluster)
disjunction += f" | Unsafe_{i}"
disjunction += ";\n"
label = "label \"Unsafe\" = Unsafe;\n"
return formulas + "\n" + disjunction + label
indices.append(f"Unsafe_{i}")
return formulas + "\n" + createBalancedDisjunction(indices, "Unsafe") + label
def createSafeFormula(clusters):
label = "label \"Safe\" = Safe;\n"
formulas = ""
disjunction = "formula Safe = false"
indices = list()
for i, cluster in enumerate(clusters):
formulas += f"formula Safe_{i} = {clusterFormula(cluster)};\n"
disjunction += f" | Safe_{i}"
disjunction += ";\n"
label = "label \"Safe\" = Safe;\n"
return formulas + "\n" + disjunction + label
indices.append(f"Safe_{i}")
return formulas + "\n" + createBalancedDisjunction(indices, "Safe") + label
def updatePrismFile(newFile, iteration, safeStates, unsafeStates):
logger.info("Creating next prism file")
@ -285,8 +299,8 @@ def drawOntoSkiPosImage(states, color, target_prefix="cluster_", alpha_factor=1.
markerList = {ski_position:list() for ski_position in range(1,num_ski_positions + 1)}
for state in states:
s = state[0]
#marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'point {s.x},{s.y} '"
marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'rectangle {s.x-markerSize},{s.y-markerSize} {s.x+markerSize},{s.y+markerSize} '"
#marker = f"-fill 'rgba({color}, {alpha_factor * state[1].ranking})' -draw 'point {s.x},{s.y} '"
markerList[s.ski_position].append(marker)
for pos, marker in markerList.items():
command = f"convert {imagesDir}/{target_prefix}_{pos:02}_individual.png {' '.join(marker)} {imagesDir}/{target_prefix}_{pos:02}_individual.png"
@ -344,17 +358,21 @@ def _init_logger():
handler.setFormatter(formatter)
logger.addHandler(handler)
def clusterImportantStates(ranking, iteration, n_clusters=40):
logger.info(f"Starting to cluster {len(ranking)} states into {n_clusters} cluster")
def clusterImportantStates(ranking, iteration):
logger.info(f"Starting to cluster {len(ranking)} states into clusters")
tic()
#states = [[s[0].x,s[0].y, s[0].ski_position * 10, s[0].velocity * 10, s[1].ranking] for s in ranking]
states = [[s[0].x,s[0].y, s[0].ski_position * 10, s[1].ranking] for s in ranking]
kmeans = KMeans(n_clusters, random_state=0, n_init="auto").fit(states)
#dbscan = DBSCAN().fit(states)
logger.info(f"Starting to cluster {len(ranking)} states into {n_clusters} cluster - DONE: took {toc()} seconds")
states = [[s[0].x,s[0].y, s[0].ski_position * 30, s[1].ranking] for s in ranking]
#kmeans = KMeans(n_clusters, random_state=0, n_init="auto").fit(states)
dbscan = DBSCAN(eps=15).fit(states)
labels = dbscan.labels_
print(labels)
n_clusters = len(set(labels)) - (1 if -1 in labels else 0)
logger.info(f"Starting to cluster {len(ranking)} states into clusters - DONE: took {toc()} seconds with {n_clusters} cluster")
clusterDict = {i : list() for i in range(0,n_clusters)}
for i, state in enumerate(ranking):
clusterDict[kmeans.labels_[i]].append(state)
if labels[i] == -1: continue
clusterDict[labels[i]].append(state)
drawClusters(clusterDict, f"clusters", iteration)
return clusterDict
@ -373,7 +391,7 @@ if __name__ == '__main__':
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)
clusters = clusterImportantStates(sorted_ranking, iteration, n_clusters)
clusters = clusterImportantStates(sorted_ranking, iteration)
if testAll: failingPerCluster = {i: list() for i in range(0, n_clusters)}
clusterResult = dict()
@ -401,7 +419,7 @@ if __name__ == '__main__':
if verdictGood:
clusterResult[id] = (cluster, Verdict.GOOD)
safeStates.append(cluster)
if testAll: drawClusters(failingPerCluster, f"failing")
if testAll: drawClusters(failingPerCluster, f"failing", iteration)
drawResult(clusterResult, "result", iteration)
iteration += 1

Write Preview
Loading…
Cancel
Save