-
Notifications
You must be signed in to change notification settings - Fork 1
/
test.py
55 lines (54 loc) · 1.8 KB
/
test.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
51
52
53
54
55
import gensim
import numpy as np
import xlwt
model_EN = gensim.models.Word2Vec.load("model/v6_EN_SG_800.model")
model_FR = gensim.models.Word2Vec.load("model/v6_ES_SG_200.model")
#workbook = xlwt.Workbook(encoding = 'utf-8')
#worksheet = workbook.add_sheet('Result')
Thta = np.load("Thta/ThtaEN-ES0.01_4000.npy")
test = np.load("test/test1000EN-ES.npy")
'''font1 = xlwt.Font()
font1.height=0x00E8
font1.name = '宋体'
style1 = xlwt.XFStyle()
style1.font = font1
worksheet.write(0, 0, label = '英文测试单词', style = style1)
worksheet.col(0).width = 3333
worksheet.write(0, 1, label = '预测的西班牙语译文', style = style1)
worksheet.col(1).width = 4000
worksheet.write(0, 2, label = '词典给出的西班牙语译文', style = style1)
worksheet.col(2).width = 4400
worksheet.write(0, 3, label = '对错', style = style1)
worksheet.col(3).width = 4400'''
num = 0
true_Word=0.0
while num < 1000:
word_EN = test[num][0]
word_FR = test[num][1]
vec_Test = model_EN.wv[word_EN]
vec_Test.shape = (1,800)
b = np.dot(vec_Test,Thta)
b.shape = (200,)
e = model_FR.wv.similar_by_vector(b, topn=5, restrict_vocab=None)
print(e[0][0])
#worksheet.write(num+1, 0, label = word_EN)
#worksheet.write(num+1, 1, label = [e[k][0]+' ' for k in range(1)])
#worksheet.write(num+1, 2, label = word_FR)
tmp=5
for i in range(tmp):
if e[i][0] == word_FR:
#worksheet.write(num+1, 3, label = '✔️')
true_Word+=1
break
#else:
#worksheet.write(num+1, 3, label = '×')
#continue
elif i == (tmp-1):
#worksheet.write(num+1, 3, label = '×')
break
print('测试完成%d个单词'%(num+1))
num += 1
#worksheet.write(num+1, 0, label = '正确率', style = style1)
#worksheet.write(num+1, 1, label = str(true_Word/num*100)+'%')
print(str(true_Word/num*100)+'%')
#workbook.save('result/Adam_ThtaEN-ES0.0009_4000.npy@1.xls')