JSON传输时间戳格式修改

dataAnalysisBusiness/algorithm/generatorSpeedTorqueAnalyst.py

@@ -143,10 +143,13 @@ class GeneratorSpeedTorqueAnalyst(AnalystWithGoodPoint):
         if isinstance(engineTypeName, pd.Series):
             engineTypeName = engineTypeName.iloc[0]
 
+        n_dataFrame = pd.DataFrame({
+            'DateTime': pd.to_datetime(dataFrame['monthIntTime'], unit='s').dt.strftime('%Y-%m-%d %H:%M:%S')
+        })
+
         # 使用 apply() 对每个元素调用 datetime.fromtimestamp
         dataFrame['monthIntTime']=dataFrame['monthIntTime'].apply(lambda x: datetime.fromtimestamp(x).strftime('%Y-%m'))
-        dataFrame[Field_UnixYearMonth] = pd.to_datetime(dataFrame[Field_UnixYearMonth], unit='s').dt.strftime(
-            '%Y-%m-%d %H:%M:%S')
+
 
         # 构建最终的JSON对象
         json_output = {
@@ -161,7 +164,7 @@ class GeneratorSpeedTorqueAnalyst(AnalystWithGoodPoint):
                 "title":f' 发电机转速和转矩分析{name[0]}',
                 "xData": dataFrame[Field_GeneratorSpeed].tolist(),
                 "yData":dataFrame[Field_GeneratorTorque].tolist(),
-                "timeData": dataFrame[Field_UnixYearMonth].tolist(),
+                "timeData": n_dataFrame['DateTime'].tolist(),
                 "color": dataFrame['monthIntTime'].tolist(),
                 "colorbartitle": "时间",
                 "mode":'markers'

dataAnalysisBusiness/algorithm/powerScatter2DAnalyst.py

@@ -63,11 +63,13 @@ class PowerScatter2DAnalyst(AnalystWithGoodBadPoint):
             currentMillTypePowerDataFrame = dataFrameGuaranteePowerCurve[dataFrameGuaranteePowerCurve[Field_MillTypeCode] == millTypeCode]
             # 获取机型的名字（machine_type_code）
             engineTypeName = self.common.getTurbineModelByCode(millTypeCode, self.turbineModelInfo)[Field_MachineTypeCode]
+            n_dataFrame = pd.DataFrame({
+                'DateTime': pd.to_datetime(group['monthIntTime'], unit='s').dt.strftime('%Y-%m-%d %H:%M:%S')
+            })
             # 使用 apply() 对每个元素调用 datetime.fromtimestamp
             group['monthIntTime'] = group['monthIntTime'].apply(lambda x: datetime.fromtimestamp(x).strftime('%Y-%m'))
 
-            group[Field_UnixYearMonth] = pd.to_datetime(group[Field_UnixYearMonth], unit='s').dt.strftime(
-                '%Y-%m-%d %H:%M:%S')
+
             # 定义要替换的空值类型
             na_values = {pd.NA, float('nan')}
             # 构建最终的JSON对象
@@ -86,7 +88,7 @@ class PowerScatter2DAnalyst(AnalystWithGoodBadPoint):
                     "xrange":[cut_in_ws, 25],
                     "yData": group[Field_ActiverPower].replace(na_values, None).tolist(),
                     "yrange":[self.axisLowerLimitActivePower,self.axisUpperLimitActivePower],
-                    "timeData": group[Field_UnixYearMonth].tolist(),
+                    "timeData": n_dataFrame['DateTime'].tolist(),
                     "colorbar": group['monthIntTime'].tolist(),
                     "colorbartitle": "年月",
                     "mode":"markers"