def compare_trial(trial_id, move_probability):
# get the trial
trial = db.get_trial(trial_id)
# list of the images initially currently grouped
initial_images = [x for x in trial['init_state'] if x['group'] != -1]
# a dict of the currently partitioned objects. The key is the image_id, and
# the value is the group
current_partition = {}
for image in initial_images:
image_id = str(image['_id'])
current_partition[image_id] = image['group']
moveNum = -1
totalMoveNum = len(trial['moves']);
# iterate over each move in the trial
for move in trial['moves']:
moveNum += 1
print "\tRunning move", moveNum, "of", totalMoveNum
# calculate the normalized log probability of each potential move according to the particle filter
if moveNum > 0:
probs = move_probability(current_partition, move)
# augment the move object
move['move_results'] = probs
move['partition'] = copy(current_partition)
move['likelihood'] = probs[move['new_group']];
else:
move['move_results'] = {0:0.0}
move['partition'] = copy(current_partition)
move['likelihood'] = 0.0;
print "\tFound likelihood:", move['likelihood'];
# update the current partition
current_partition[move['image_id']] = move['new_group']
return trial
def run_trial_for_params(trial_id):
trial = db.get_trial(trial_id);
print "Starting...";
trial = compare_trial(trial['_id'], find_params_for_move);
print "Done!"
