-
Notifications
You must be signed in to change notification settings - Fork 3
/
scorers.py
50 lines (42 loc) · 1.33 KB
/
scorers.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
import numpy as np
import nltk.translate.bleu_score as bleu
def WRR(text1,text2):
a = set(text1.lower().split())
b = set(text2.lower().split())
if (len(a) == 0) and (len(b) == 0):
return .5
c = a.intersection(b)
return float(len(c))/(len(a) + len(b) - len(c))
def levenshtein(seq1, seq2):
seq1 = seq1.lower()
seq2 = seq2.lower()
size_x = len(seq1) + 1
size_y = len(seq2) + 1
matrix = np.zeros ((size_x, size_y))
for x in range(size_x):
matrix [x, 0] = x
for y in range(size_y):
matrix [0, y] = y
for x in range(1, size_x):
for y in range(1, size_y):
if seq1[x-1] == seq2[y-1]:
matrix [x,y] = min(
matrix[x-1, y] + 1,
matrix[x-1, y-1],
matrix[x, y-1] + 1
)
else:
matrix [x,y] = min(
matrix[x-1,y] + 1,
matrix[x-1,y-1] + 1,
matrix[x,y-1] + 1
)
#print (matrix)
return (matrix[size_x - 1, size_y - 1])
def CRR(text1, text2):
try:
return 1 - float(levenshtein(text1,text2))/max(len(text1),len(text2))
except:
return 0
def bleu_score(text1,text2):
return bleu.sentence_bleu([text1.lower().split()],text2.lower().split())