def output(self):
if (levenshtein(self.old, self.new) / len(self.old)) > 0.9:
return '"<' + self.old + '>"'
for match in self.matches:
if match.size == 1 and match.a != match.b:
continue
for i in range(match.a, match.a + match.size):
self.highlighted[i] = True
result = []
for char, highlight in zip(list(self.old), self.highlighted):
if highlight is None:
result.append(start + char + end)
else:
result.append(char)
return '"' + ''.join(result).replace('><', '') + '"'
lines = f.readlines()
sys.stderr.write("Read finished\n")
lines = [re.split("\t", line) for line in lines]
lines = [[entry.strip() for entry in line] for line in lines]
lines = [(line[0], line[2:]) for line in lines if len(line)>3]
distance_list = []
count = 0
size = len(lines)
for line in lines:
if count % 100 == 0:
sys.stderr.write(str(count) + "/" + str(size) + "\n")
count += 1
# distance_list.append((line[0], sorted([(str1, str2, lib.levenshtein(str1, str2)) for str1, str2 in itertools.combinations(line[1], 2)], key=lambda entry: entry[2], reverse=True)))
list = []
for str1, str2 in itertools.combinations(line[1], 2):
dist = lib.levenshtein(str1, str2)
maxlen = max(len(str1), len(str2))
normed = float(dist)/float(maxlen)
list.append((str1, str2, dist, normed))
distance_list.append((line[0], sorted(list, key=lambda entry: entry[3], reverse=True)))
for entry in distance_list:
print entry[0] + "\t" + str(len(entry[1]))
for p_entry in entry[1]:
print p_entry[0] + "\t" + p_entry[1] + "\t" + str(p_entry[2]) + "\t" + str(p_entry[3])
