数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -35,7 +35,7 @@ def get_somedate():
 	someday = someday.strftime("%Y-%m-%d")
 	return someday
 ten_days=get_somedate()
-print(ten_days)
+# print(ten_days)
 
 #获取最近10天的数据
 def DATA_recently(x,y,z,q,t):
@@ -116,6 +116,7 @@ def t_test(x,y): #进行t检验
         # print(t_p_value)
         if t_p_value>0.05:
             print("策略前后两组数据无显著性差异，即该指标没有显著提升，p_value:{}" .format(t_p_value))
+            print("\n")
         else:
             print("策略前后两组数据有显著性差异，即该指标获得显著提升，p_value:{}" .format(t_p_value))
     else: #认为数据方差不具有齐性，equal_var=false
@@ -388,7 +389,7 @@ def mail():
     ret = True
     try:
         text = "Hi!\nHow are you?\nHere is the link you wanted:\nhttp://www.baidu.com"
-        msg = MIMEText(mean_var_ctr_old_precise, 'plain', 'utf-8')
+        msg = MIMEText(text, 'plain', 'utf-8')
         msg['From'] = formataddr(["王志伟", my_sender])
         msg['To'] = my_user1
         msg['Subject'] = str(datetime.date.today()) + "-esmm多目标模型训练指标统计"