coreV0 0727

LIB/MIDDLE/InfoChrgDrive/Charge/V1_0_0/coreV0.py

@@ -73,9 +73,12 @@ def gpstemp_new(data_sta):
                 k=x_time.index(time)
                 if temp[k]!='':
                     temp0=float(temp[k])
-                    data_sta.loc[i,'气温']=temp0
-    data_sta['气温'].fillna(method='ffill') 
-    print(data_sta['气温'])
+                    data_sta.loc[i,'气温']=temp0    
+                else:
+                    if k>0:     
+                        data_sta.loc[i,'气温']=data_sta.loc[i-1,'气温']  
+                    else:   
+                        data_sta.loc[i,'气温']=data_sta.loc[i+1,'气温']
     return data_sta
 
 def defcelltype(sn):
@@ -237,7 +240,7 @@ def gpstemp2(data_sta3):
     data_sta['airtemp_end']=temp22
     return data_sta
 
-def newsplit(data_new):
+def newsplit(data_new):  #重新分段：根据时间差和经纬度
     data_split=pd.DataFrame()
     splice_num = np.unique(data_new['data_split_by_status_time']) 
     for item in splice_num: 
@@ -267,7 +270,7 @@ def newsplit(data_new):
     data_split3=data_split3.reset_index(drop = True)
     return data_split3
 
-def chrgst_time(data_split):
+def chrgst_time(data_split):   #重新计算前后闲置时长
     for k in range(1,len(data_split)):
         if (data_split.loc[k,'data_status']=='charge') & (data_split.loc[k-1,'data_status']=='stand'):
             delta_time_f=(data_split.loc[k-1,'时间戳']-data_split.loc[k-2,'时间戳']).total_seconds()/60
@@ -283,9 +286,8 @@ def chrgst_time(data_split):
             data_split.loc[k-1,'stand_time']=delta_time_b     
     return data_split
 
-def chrgdr(data_split):
+def chrgdr(data_split):   #根据充电信息结果合并相连同状态
     chrg=pd.DataFrame()
-    dr=pd.DataFrame()
     if len(data_split)>3:
         if (data_split.loc[0,'data_status']=='charge')  & (data_split.loc[2,'data_status']=='stand'):
             chrg=chrg.append(data_split.iloc[:4]) 
@@ -313,7 +315,7 @@ def chrgdr(data_split):
 
     return chrg
 
-def makedf_chrgdr(df_splice_chrg,data_new):
+def makedf_chrgdr(df_splice_chrg,data_new):   #每个status取所有时间戳的数据
     time1=df_splice_chrg.loc[0,'时间戳']
     time2=df_splice_chrg.loc[1,'时间戳']
     status=df_splice_chrg.loc[0,'data_status']
@@ -326,6 +328,7 @@ def makedf_chrgdr(df_splice_chrg,data_new):
     return df_chrg
 
 def change_new(df_sts_chrg,chrg_last):
+    df_sts_chrg.reset_index(drop=True,inplace=True)
     time_last=chrg_last['time_end']
     time_first=df_sts_chrg.loc[0,'time_st']
     time_last=datetime.datetime.strptime(time_last,'%Y-%m-%d %H:%M:%S')
@@ -375,7 +378,7 @@ def change_new(df_sts_chrg,chrg_last):
         chrg_last=pd.DataFrame()
     return df_sts_chrg,chrg_last
 
-def sep_chrg_dr(df_merge,sn):
+def sep_chrg_dr(df_merge,sn,gpscity):
     cellvolt_list = [s for s in list(df_merge) if '单体电压' in s] 
     celltemp_name = [s for s in list(df_merge) if '温度' in s] 
     df_data=process(df_merge,cellvolt_list,celltemp_name,sn)
@@ -386,22 +389,24 @@ def sep_chrg_dr(df_merge,sn):
     data_new=DataPreProcess.data_split_by_time(data_new,data_new) 
     data_new=DataPreProcess.cal_stand_time(data_new,data_new)
     data_new.reset_index(inplace = True, drop = True)
-    data_split=newsplit(data_new)
+    data_sta=city(data_new,gpscity)
+    data_sta=data_sta.reset_index(drop=True)
+    data_sta2=gpstemp_new(data_sta)
+    data_split=newsplit(data_sta2)
     data_split=chrgst_time(data_split)
     chrg=chrgdr(data_split)
-    return chrg,data_new,param
+    return chrg,data_sta2,param
 
-def mkdf_chrg(chrg,data_new,param,gpscity):
+def mkdf_chrg(chrg,data_new,param):
     splice_num= np.unique(chrg['data_split_by_status_time'])  
-    df_sts_chrg=pd.DataFrame()       
+    df_sts_chrg=pd.DataFrame()     
     for item in splice_num: 
         df_splice_chrg = chrg[chrg['data_split_by_status_time'] == item] 
         df_splice_chrg.reset_index(inplace = True, drop = True)
         df_chrg=makedf_chrgdr(df_splice_chrg,data_new)
-        data_sta=city(df_chrg,gpscity)
-        data_sta=data_sta.reset_index(drop=True)
-        data_sta2=gpstemp_new(data_sta)
-        df_sts_chrg_temp=stat_chrg_st(data_sta2,param)
+    
+        df_sts_chrg_temp=stat_chrg_st(df_chrg,param)
+        
         if df_splice_chrg.loc[0,'data_status'] =='charge':
             stand_dur_f=df_splice_chrg.loc[0,'stand_time']
             stand_dur_b=df_splice_chrg.loc[1,'stand_time']
@@ -417,9 +422,10 @@ def pro_output(df_merge,sn,gpscity,chrg_last):
     new=pd.DataFrame()
     change=pd.DataFrame()
     if len(df_merge)>0:
-        chrg,data_new,param=sep_chrg_dr(df_merge,sn)
+        chrg,data_new,param=sep_chrg_dr(df_merge,sn,gpscity)
         if len(chrg)>0:
-            data_sta=mkdf_chrg(chrg,data_new,param,gpscity)
+            data_sta=mkdf_chrg(chrg,data_new,param)
+            data_sta.to_csv('data_sta.csv')
             new=data_sta.copy() 
             if len(chrg_last)>0:
                 new,change=change_new(data_sta,chrg_last)