Exemple #1
0
clusterAlg = DivisiveKmeans().__fit__

penguin = PenguinAggregation()

gold_subjects = penguin.__get_gold_subjects__()
gold_sample = gold_subjects[:50]

penguin.__readin_users__()

for count,zooniverse_id in enumerate(gold_sample):
    if count == 50:
        break
    print count, zooniverse_id
    penguin.__readin_subject__(zooniverse_id,read_in_gold=True)

    blankImage = penguin.__cluster_subject__(zooniverse_id, clusterAlg,fix_distinct_clusters=True,correction_alg=correctionAlg)
    penguin.__soy_it__(zooniverse_id)


    penguin.__signal_ibcc__()
    penguin.__roc__()
# one_overlap = penguin.__off_by_one__(display=True)
# last_id = None
#
# for t in one_overlap:
#     if t[0] != last_id:
#         print "*****"
#         print "====="
#         last_id = t[0]
#     penguin.__relative_confusion__(t)