def publishMetrics()

in forecastMetrics/forecastMetrics.py [0:0]

• 19 lines of code
• 7 McCabe index (conditional complexity)

def publishMetrics(currentDay,currentDayRealData,config):
    total_dif=0
    metricDataList=[]
    metricTimeStamp=getTimestampByDate(currentDay)
    for p in vars.forecastPList:
      metricDataList=[]
      for item in vars.ItemList:
          if (item.upper() in currentDayRealData):
              realValue=float(currentDayRealData[item.upper()])
              forcastValue=float(vars.ForcastData[tranformDateToString(currentDay)][item.lower()][p])
              if (realValue is None or realValue==0):
                  state_abs=0
              else:
                  state_abs=(abs((forcastValue-realValue)/realValue))*100
              total_dif=total_dif+state_abs
              # currently not need by state data for model monitor
              #metricDataList.append(getMetricData(metricTimeStamp, item, state_abs, p))
      avarage_abs=total_dif/len(vars.ItemList)
      logger.info("averageABS is "+str(avarage_abs) +  "============for :"+tranformDateToString(currentDay) +"====for p=" +p)
      metricDataList.append(getMetricData(metricTimeStamp, config["modelName"], avarage_abs, p))
      putForecastMetricsData(metricDataList)