def test_main(filename_s, filename_e, filename_a):
wordlist_s = TextPreprocess.Tokens(filename_s)
wordlist_e = TextPreprocess.Tokens(filename_e)
dict_s = Process.DictBiulder(wordlist_s)
dict_e = Process.DictBiulder(wordlist_e)
Fin_dict = Process.MergeDict(dict_s, dict_e)
V1 = Features.GetVector(dict_s, Fin_dict)
V2 = Features.GetVector(dict_e, Fin_dict)
ans = Similarity.CosineSimilarity(V1, V2)
with open(filename_a, 'w') as f_obj:
temp = str(ans)
contents = ''
for i in range(0, 4):
contents = contents + temp[i]
f_obj.write(contents)
print(contents)
import TextPreprocess
import Process
import Features
import Similarity
import sys
wordlist_s = TextPreprocess.Tokens(sys.argv[1])
wordlist_e = TextPreprocess.Tokens(sys.argv[2])
dict_s = Process.DictBiulder(wordlist_s)
dict_e = Process.DictBiulder(wordlist_e)
Fin_dict = Process.MergeDict(dict_s, dict_e)
V1 = Features.GetVector(dict_s, Fin_dict)
V2 = Features.GetVector(dict_e, Fin_dict)
ans = Similarity.CosineSimilarity(V1, V2)
with open(sys.argv[3], 'w') as f_obj:
if ans == 0:
f_obj.write("0.00")
else:
temp = str(ans)
contents = ''
for i in range(0, 4):
contents = contents + temp[i]
f_obj.write(contents)