def read_words(filename):

words = []

for line in open(filename):

words.append(line.strip())

return words

def read_vectors(filename):

vectors = []

for line in open(filename):

vectors.append(map(float, line.strip().split()))

return vectors

def write_tree(words, hierarchy, filename):

f = open(filename, "w")

print >> f, len(words)

for word in words:

print >> f, word

print >> f, len(hierarchy)

for children in hierarchy:

print >> f, len(children), " ".join(map(str, children))

def convert_fastcluster(cluster_data):

hierarchy = []

for n1, n2, _, _ in cluster_data:

hierarchy.append((int(n1), int(n2)))

return hierarchy

def depth(words, hierarchy):

depths = [1] * len(words)

for children in hierarchy:

new_depth = 1

for child in children:

new_depth = max(new_depth, depths[child] + 1)

depths.append(new_depth)

return depths[-1]

def read_tree(filename):

f = open(filename, "r")

words = []

num_words = int(f.readline().strip())

for i in range(num_words):

words.append(f.readline().strip())

tree = []

num_merges = int(f.readline().strip())

for i in range(num_merges):

children = map(int, f.readline().strip().split())

tree.append(tuple(children[1:]))

return words, tree