Merge remote-tracking branch 'origin/dev' into pro

LIB/MIDDLE/WinterCharging/V1_0_0/uniqueI3.py

@@ -1,27 +0,0 @@
-
-from LIB.BACKEND import DBManager
-from LIB.MIDDLE.CellStateEstimation.Common import log
-import datetime
-import pandas as pd
-import numpy as np
-import os   
-from DataPreProcess import DataPreProcess
-
-dbManager = DBManager.DBManager()
-#basePath = r'C:\Users\zhuxi\My_VSCode\B 电池低温充电失败次数概率排名\result'
-fileNames = os.listdir('result')  #获取文件夹中所有文件的名称
-data_GMGC=pd.DataFrame()
-for k in range(10):
-    data_merge = pd.read_csv('result'+'\\'+fileNames[0])
-    df_sheetCat=DataPreProcess.data_split_by_status(DataPreProcess,data_merge, drive_interval_threshold=120, charge_interval_threshold=300, drive_stand_threshold=120, charge_stand_threshold=300)
-    data_charge=df_sheetCat[df_sheetCat['data_status']=='charge']
-    unique_status_idx=np.unique(data_charge.data_split_by_status.values)
-    data_I3=pd.DataFrame()
-    for n in unique_status_idx:
-        df_charge_buff=data_charge[data_charge.data_split_by_status==n]
-        list_I=df_charge_buff.loc[2:6,'总电流[A]'].values.tolist()
-        if((3 in list_I) and (df_charge_buff['总电流[A]'].value_counts()['3']>3)): 
-            data_I3=data_I3.append(df_charge_buff)
-    data_GMGC=data_GMGC.append(data_I3)
-  
-data_GMGC.to_csv('test7.csv')

LIB/MIDDLE/WinterCharging/V1_0_0/unique_I3.py

@@ -0,0 +1,42 @@
+
+from LIB.BACKEND import DBManager
+from LIB.MIDDLE.CellStateEstimation.Common import log
+import datetime
+import pandas as pd
+import numpy as np
+import os   
+from DataPreProcessMGMC import DataPreProcess
+
+#log信息配置
+mylog=log.Mylog('log.txt','error')
+mylog.logcfg()
+
+dbManager = DBManager.DBManager()
+dataSOH = pd.read_excel('sn-20210903.xlsx',sheet_name='MGMC')
+fileNames = dataSOH['sn']
+fileNames = list(fileNames)
+
+data_GMGC=pd.DataFrame()
+for k in range(len(fileNames)):
+    try:    
+        sn = fileNames[k]
+        df_data = dbManager.get_data(sn=sn, start_time='2021-10-28 00:00:00', end_time='2021-11-04 00:00:00', data_groups=['bms','gps'])
+        data_bms = df_data['bms']
+        data_gps = df_data['gps']
+        df_merge=pd.merge(data_bms, data_gps,how='outer',sort=True)
+        df_merge['sn']=sn
+        df_sheetCat=DataPreProcess.data_split_by_status(DataPreProcess,df_merge, drive_interval_threshold=120, charge_interval_threshold=300, drive_stand_threshold=120, charge_stand_threshold=300)
+        data_charge=df_sheetCat[df_sheetCat['data_status']=='charge']
+        unique_status_idx=np.unique(data_charge.data_split_by_status.values)
+        data_I3=pd.DataFrame()
+        for n in unique_status_idx:
+            df_charge_buff=data_charge[data_charge.data_split_by_status==n]
+            list_I=df_charge_buff['总电流[A]'].values.tolist()[1:8]
+            if((3 in list_I) and (df_charge_buff['总电流[A]'].value_counts()[3]>5)): 
+                data_I3=data_I3.append(df_charge_buff)
+                data_GMGC=data_GMGC.append(data_I3)
+        
+    except Exception as e:
+        print(repr(e))
+        mylog.logopt(sn,e)
+        pass