def run_diagnose(self):
standards = serial.objFromFile('prob_groups.txt')
c = ClusterBridge()
name_net = c.getNameNet()
for thres in range(1, 10):
# Experimental
def lengthFilter(triplet):
names = triplet[1]
return len(names) == thres
filtered_net = filter(lengthFilter, name_net)
# Experimental-end
observed = gstat.convertNameNet2Observed(filtered_net)
prediction = matchstat.convertObserved2Prediction(standards, observed)
# Format becomes:
# [(true1, true2,...), (predict1, predict2, ...), (meta1, meta2, ...)]
pairs = matchstat.unzipGroupPrediction(prediction)
num_label = 4
tester = tests.tester(num_label)
assert(len(pairs) >= 2) # sanity check
tester.record(pairs[0], pairs[1])
tester.recordMeta(pairs[2])
#print thres
print "Accuracy:", tester.accuracy()
print "Conf matrix:"
print tester.confusionMatrix(friends.groupToNumeric)
def run(self):
standards = serial.objFromFile('prob_groups.txt')
c = ClusterBridge()
name_net = c.getNameNet()
observed = gstat.convertNameNet2Observed(name_net)
prediction = matchstat.convertObserved2Prediction(standards, observed)
# Format becomes:
# [(true1, true2,...), (predict1, predict2, ...), (meta1, meta2, ...)]
pairs = matchstat.unzipGroupPrediction(prediction)
num_label = 4
tester = tests.tester(num_label)
assert(len(pairs) >= 2) # sanity check
tester.record(pairs[0], pairs[1])
tester.recordMeta(pairs[2])
#print thres
print "Accuracy:", tester.accuracy()
print "Conf matrix:"
print tester.confusionMatrix(friends.groupToNumeric)
