2026-04-24 FE Backup

Gateways/FE/projects/.resources/ae45fa6ac07fbbcd0e298804263ec048431725e2a28b684e44c7f23dccc12563

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+from datetime import datetime
+
+def getRawDataTotalLoad(startDate, endDate, location, customArgs= {}):
+	return reports.MBR.totalpower.getRawDataTotalLoad(startDate, endDate, location, customArgs)
+
+def getRawDataCriticalLoad(startDate, endDate, location, customArgs= {}):
+	return reports.MBR.totalpower.getRawDataCriticalLoad(startDate, endDate, location, customArgs= {})
+
+
+def stripHistColumns(histDS, colsToKeep=[]):
+	"""
+		Support function to remove standalone columns
+	"""
+	histHeaders = system.dataset.getColumnHeaders(histDS)
+	newHeader = [histHeaders[0]] + colsToKeep
+	
+	allRows = []
+	for row in histDS:
+		allRows.append([row[c] for c in newHeader])
+	
+	return system.dataset.toPyDataSet(system.dataset.toDataSet((newHeader, allRows)))
+
+def processCalcPeakAvg(histDS, keyCol, colNames, interval):
+	"""
+	Calculate peak and avg by interval
+	Args:
+		histDS: history dataset to process
+		keyCol: identify the key column to calculate from
+		colNames: new column names for peak and avg
+		interval: histDS should be in minute intervals, how many rows per grouping
+	Returns:
+		dataset of t_stamp, Peak<keyCol>, Avg<keyCol>
+		GroupDict of interval raw values
+	"""
+	timeUnitStr = ""
+	GroupDict= {} # represents {"datetime":{"col1":[], "col2":[]...}}
+	histDsCols = [keyCol]
+	resultData = []
+	for i,row in enumerate(histDS):
+		if i%interval == 0: 
+			timeUnitStr = system.date.format(row["t_stamp"],"yyyy-MM-dd HH:mm")
+			GroupDict.setdefault(timeUnitStr, {})
+			GroupDict[timeUnitStr]={"values":[]}
+#		GroupDict[quarterHrStr].append(row["SumRealPwr"])
+		for col in histDsCols:
+			GroupDict[timeUnitStr]["values"].append(row[col] if row[col] is not None else 0)
+	sortedDateKeys = sorted(GroupDict.keys(), key=lambda x: datetime.strptime(x, '%Y-%m-%d %H:%M'))
+	for dt_str in sortedDateKeys:		
+		intervalAvg = sum(GroupDict[dt_str]["values"])/len(GroupDict[dt_str]["values"])
+		intervalPeak = max(GroupDict[dt_str]["values"])
+		oneRow = [system.date.parse(dt_str, "yyyy-MM-dd HH:mm"), intervalPeak, intervalAvg]
+		resultData.append(oneRow)
+	
+	return system.dataset.toPyDataSet(system.dataset.toDataSet(["t_stamp"]+colNames, resultData)), GroupDict
+
+def calcPUE(totalLoadDict, critLoadDict):
+	resultData = []
+	sortedDateKeys = sorted(totalLoadDict.keys(), key=lambda x: datetime.strptime(x, '%Y-%m-%d %H:%M'))
+	
+	for dt_str in sortedDateKeys:
+		pue_intervalList= [a/b if b> 0 else -1 for a,b in zip(critLoadDict[dt_str]["values"], totalLoadDict[dt_str]["values"])]
+		resultData.append([system.date.parse(dt_str, "yyyy-MM-dd HH:mm"), max(pue_intervalList), sum(pue_intervalList)/len(pue_intervalList)])		
+
+	return system.dataset.toPyDataSet(system.dataset.toDataSet(["t_stamp","PeakPUE", "AvgPUE"], resultData))
+
+def beginReport(startDate, endDate, intervalMin=15, location=None):
+	"""
+		Single call point for Report data fetch
+	"""
+	totalLoadHist = getRawDataTotalLoad(startDate, endDate, location)
+	critLoadHist = getRawDataCriticalLoad(startDate, endDate, location)
+	
+#	rawData = reports.MBR.common.util.mergeHistorianData(totalLoadHist, critLoadHist)
+	
+	totalLoadHist = reports.MBR.common.util.generateSumCol(totalLoadHist, sumColName="TotalLoad")
+	totalLoadHist, totalLoadDict = processCalcPeakAvg(totalLoadHist, "TotalLoad", ["PeakTotalLoad","AvgTotalLoad"], intervalMin)
+	critLoadHist = reports.MBR.common.util.generateSumCol(critLoadHist, sumColName="CriticalLoad")
+	critLoadHist, critLoadDict = processCalcPeakAvg(critLoadHist, "CriticalLoad", ["PeakCriticalLoad","AvgCriticalLoad"], intervalMin)
+	
+	pueData = calcPUE(totalLoadDict, critLoadDict)
+	
+	summaryData = reports.MBR.common.util.mergeHistorianData(totalLoadHist, critLoadHist)
+	summaryData = reports.MBR.common.util.mergeHistorianData(summaryData, pueData)
+	
+	return {"summaryData": summaryData}
+