def main(issue):
weights = [
0.63000000000000012, 0.28000000000000019, 0.10000000000000012, 1.0,
0.80000000000000004
]
APISimilarReportsScores_dict = getSimilarityScores2Reports.main_API(issue)
APIdscpScors_dict = getAPIdscpScors.main(issue)
APISrcfileScores_dict = getAPISrcfileScores.main(
weights[:2], issue) #weights：自然语言 与程序语言之间的权重关系，决定相似度分数
Final_Result = getFinal_Result(APIdscpScors_dict,
APISimilarReportsScores_dict,
APISrcfileScores_dict, weights[2:])
#write_NoResult(Final_Result)
return Final_Result[issue.Issuekey]
def getAimList():
workbook = xlrd.open_workbook(r'Input/Hadoop_issuekeys_UsedAPI.xls')
sheet = workbook.sheet_by_name('sheet1')
Aimresult={}
for j in range(1,sheet.nrows):
issuekey=sheet.cell(j,0).value
if sheet.cell(j,1).value=='':
Aimresult[issuekey] = []
else:
Aimresult[issuekey] = sheet.cell(j,1).value.split(';')
return Aimresult
weights = [1,1, 1,1,1]#前两个用于Src相似度计算时，后三个用于 API 推荐结果的汇总
APISimilarReportsScores_dict = getSimilarityScores2Reports.main_API()
print '5'
APIdscpScors_dict = getAPIdscpScors.main()
APISrcfileScores_dict = getAPISrcfileScores.main(weights[:2])#weights：自然语言 与程序语言之间的权重关系，决定相似度分数
solutionnow =weights
valuenow = getevaluate(solutionnow)#目标函数解
print valuenow
best = 0.0
for count in range(6):
#for index in [1] + range(3,9) + range(10,17):
#for index in range(len(solutionnow)):
for index in [2,3,4]:
i=1.0
best_i = solutionnow[index]
while i>0.05:
