def cos_test_info(self, train_time):
# get word vector
info_dict = self.get_corpus_result(train_time)
# get predict interval
reviewer = get_reviewer(self.project_name)
print(reviewer)
# test_number = get_test_number(self.project_name)
# for i in test_number:
# new_word = info_dict.get(i)
# past_dict = {k: v for k, v in info_dict.items() if (k < i)}
# score_list = self.cos_score(new_word, past_dict, reviewer, 5)
# print(score_list)
return info_dict, reviewer
from storage.utils import get_reviewer
from storage.utils import get_test_number
from itertools import product
import re
if not os.path.exists(tie_path):
os.mkdir(tie_path)
ir_list= [i for i in os.walk(ir_path)][0][2]
# fps_file = [i for i in os.walk(fps_path)][0][2]
print(ir_list)
for i in ir_list:
project = re.search(r'[a-z]+.[a-z]+', i)[0]
project_index = [i.split('/')[1] for i in PROJECT_NAME]
realproject = PROJECT_NAME[project_index.index(project)]
test_number = get_test_number(realproject)
print(test_number)
all_reviewer = get_reviewer(realproject)
print(realproject)
ir_file = os.path.join(ir_path, i)
fps_file = os.path.join(fps_path, i)
tie_file = os.path.join(tie_path, i)
with open(ir_file, 'r') as f:
ir_content = f.readlines()[:-1]
with open(fps_file, 'r') as f2:
fps_content = f2.readlines()[:-2]
with open(ir_file, 'r') as f3:
ir_spend_time = f3.readlines()[-1]
ir_spend_time = float(re.search(r"\d+(\.\d{2})?",ir_spend_time)[0])
with open(fps_file, 'r') as f4:
fps_spend_time = f4.readlines()[-1]
fps_spend_time = float(re.search(r"\d+(\.\d{2})?",fps_spend_time)[0])
def main(project, train_time):
cf = CountFps()
train_start_number = get_train_start_number(project, train_time)
# print(train_start_number)
all_reviewer = get_reviewer(project, train_start_number)
all_file = get_file_name(project, train_start_number)
start_time = time.time()
proc = Process(project)
file_name = project.split('/')[1] + train_time.replace('-', '_')
print('Start Prepare Corpus')
info_dict, reviewer = proc.cos_test_info(train_time)
cn = CommentNetwork(project, train_time)
test_info, comment_info_all = cn.corpus_test()
end_train_time = time.time()
train_spend_time = end_train_time - start_time
print('start test-----')
count_dict1 = {'right': 0, 'wrong': 0, 'all': 0}
count_dict3 = {'right': 0, 'wrong': 0, 'all': 0}
count_dict5 = {'right': 0, 'wrong': 0, 'all': 0}
not_valie_id = []
predict_time_list = []
for number, pull_request_user in test_info.items():
try:
start_predict_time = time.time()
Rpf = {k: v for k, v in all_file.items() if k < number}
Rp_viewers_all = {
k: v
for k, v in all_reviewer.items() if k < number
}
f = all_file.get(number)
# print(f)
comment_info = comment_info_all.get(number, None)
if not comment_info or not f:
# write_to_file(file_name, {number: 'this pull request no comment info'})
continue
comment_info_key = list(comment_info.keys())
# print(comment_info_key)
result, predict = cf.main(f, Rpf, Rp_viewers_all, 5)
# print(f'fps is {predict[0:10]}')
score_list = cos_func(info_dict, number, reviewer, proc)
print('----', number, pull_request_user)
predict = [(i[0], i[1] * 0.3) for i in predict]
score_list = [(i[0], i[1] * 0.7) for i in score_list]
x = Counter(dict(predict))
y = Counter(dict(score_list))
last_result = list(dict(x + y))
# print('compare result is',last_result)
end_time = time.time()
predict_spend_time = end_time - start_predict_time
predict_time_list.append(predict_spend_time)
# if not score_list:
# continue
# print('========== graph test ========')
# edge_info = graph_func(comment_info_all, number, pull_request_user, cn)
# if edge_info:
# network_user = [i[2] for i in edge_info]
# commented_user = sort_priority(score_list, network_user)
# else:
# commented_user = score_list
commented_user = last_result[0:10]
# write_to_file(file_name, {number: commented_user})
commented_user_1, commented_user_3, commented_user_5 = [
commented_user[0]
], commented_user[0:2], commented_user[0:5]
#
# print('predict user',commented_user_1)
# print('reviewer user',comment_info_key)
# print('',commented_user_1)
# count_dict1 = compare_result(commented_user_1, comment_info_key,count_dict1)
# count_dict3 = compare_result(commented_user_3, comment_info_key,count_dict3)
# count_dict5 = compare_result(commented_user_5, comment_info_key,count_dict5)
except Exception as e:
LOG.error('Error in {}:{}, Cause {}'.format(
number, pull_request_user, e),
exc_info=True)
# save_rate(project, file_name, count_dict1)
# save_rate(project, file_name, count_dict3)
# save_rate(project, file_name, count_dict5)
predict_all_time = numpy.sum(predict_time_list)
write_to_file(file_name, f'train spend time is {train_spend_time}')
write_to_file(file_name, f'predict all spend time is {predict_all_time}')
end_time = time.time()
spend_time = end_time - start_time
write_to_file(file_name, f'spend time is {spend_time}')
print('end test----')