In [1]:
from os import listdir
from os.path import isfile, join
from sklearn.metrics import normalized_mutual_info_score
In [11]:
test_file = "karate_metadata.txt"
with open(test_file) as f:
test_set = []
for line in f.readlines():
a, b = line.split()
b = int(b)
test_set.append(b)
print test_set
In [20]:
onlyfiles = [ f for f in listdir('./') if 'comm' in f]
train_set = [0] * len(test_set)
print(onlyfiles)
for file in onlyfiles:
with open(file) as f:
now_label = 0
for line in f.readlines():
now_label += 1
node_list = line.split()
for node in node_list:
node = int(node)
train_set[node - 1] = now_label
print(normalized_mutual_info_score(test_set, train_set))
print(train_set)
In [17]: