animal_votes[animal_index] = [1]
else:
animal_votes[animal_index].append(1)
else:
votes.append((user_index, animal_index, 0))
if not (animal_index in animal_votes):
animal_votes[animal_index] = [0]
else:
animal_votes[animal_index].append(0)
print "=====---"
#print votes
classify = IterativeEM()
classify.__classify__(votes)
most_likely = classify.__getMostLikely__()
estimates = classify.__getEstimates__()
X = []
Y = []
X2 = []
Y2 = []
#for subject_index,zooniverse_id in enumerate(big_subjectList):
for ii in range(animal_index):
x = np.mean(animal_votes[ii])
y = estimates[ii][1]
X.append(x)
Y.append(y)
subject_vote[zooniverse_id] = [0]
else:
subject_vote[zooniverse_id].append(0)
except ValueError:
votes.append((user_index, subject_index, 0))
if not (zooniverse_id in subject_vote):
subject_vote[zooniverse_id] = [0]
else:
subject_vote[zooniverse_id].append(0)
print "=====---"
classify = IterativeEM()
classify.__classify__(votes)
most_likely = classify.__getMostLikely__()
estimates = classify.__getEstimates__()
X = []
Y = []
X2 = []
Y2 = []
for subject_index, zooniverse_id in enumerate(big_subjectList):
subject = subject_collection.find_one({"zooniverse_id": zooniverse_id})
if zooniverse_id in subject_vote:
x = np.mean(subject_vote[zooniverse_id])
y = estimates[subject_index][1]
if subject["state"] == "complete":
X.append(x)
