2026-04-24 FE Backup

Gateways/FE/projects/.resources/a9fde284188178e8d48e83afc3db9892c10288db980f06d5a99f45bf7c2469c9

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+from datetime import datetime
+import re
+def getTagPaths(location=None):
+	"""
+		Get all the relvant tagpaths needed for the historian query
+	"""
+	baseTagPaths = reports.MBR.common.util.getBaseTagPaths(reports.MBR.common.static.getUPSBase(), location)
+	return baseTagPaths
+	
+def getPowerPaths(location):
+	paths = []
+	for ups1path, ups2path in getTagPaths(location):
+		paths.extend(["%s/Total kW"%ups1path, "%s/Total kW"%ups2path])
+	return paths
+def getPowerHist(startDate,endDate, location=None):
+	tagpaths = getPowerPaths(location)
+		
+	hist = reports.MBR.common.util.getHistory(tagpaths, startDate, endDate, customArgs={})
+	return reports.MBR.common.util.generateSumCol(hist, sumColName="SumTotalkW"), tagpaths
+	
+
+def averageHistData(histData, inclColumns, interval=None):
+	"""
+		Calculate the Average, Min Average, Max Average
+		Args:
+			data: historian data, expected in minute intervals
+			inclColumns: list of strings reprsenting the tagpath/column name from queryTagHistory
+			interval: grouping by minutes, None if daily
+		Returns:
+			dictionary containing calculated data
+	"""
+	data = system.dataset.toPyDataSet(histData)
+	res = {"MinAvg":-1,"MaxAvg":-1,"ResultData":None}
+	dailyGroup= {}
+	resultData = []
+	allAvgs = []
+	def getUPSName(inclNames):
+		newNames = []
+		for name in inclNames:
+			newNames.append(name.split("_")[-1].split("/")[0])
+		return newNames
+	if interval is None:
+		for row in data:
+	#		dayStr = system.date.format(system.date.fromMillis(row["t_stamp"]),"yyyy-MM-dd")
+			dayStr = system.date.format(row["t_stamp"],"yyyy-MM-dd")
+			dailyGroup.setdefault(dayStr,{c:[] for c in inclColumns})
+			for c in inclColumns:
+				dailyGroup[dayStr][c].append(row[c])
+				
+			
+		
+		sortedDateKeys = sorted(dailyGroup.keys(), key=lambda x: datetime.strptime(x, '%Y-%m-%d'))
+		for date_str in sortedDateKeys:
+			oneRow= [system.date.parse(date_str, "yyyy-MM-dd")]
+			for c in inclColumns:
+				cleanValues = [v for v in dailyGroup[date_str][c] if v is not None] 
+				dailyAvg = sum(cleanValues)/len(cleanValues) if len(cleanValues) > 0 else 0
+				allAvgs.append(dailyAvg)
+				oneRow.append(dailyAvg)
+			resultData.append(oneRow)		
+
+	else:		
+		quarterHrStr = ""
+		for i,row in enumerate(data):
+			if i%interval == 0: 
+				quarterHrStr = system.date.format(row["t_stamp"],"yyyy-MM-dd HH:mm")
+				dailyGroup.setdefault(quarterHrStr,{c:[] for c in inclColumns})
+			for c in inclColumns:
+				dailyGroup[quarterHrStr][c].append(row[c])
+		sortedDateKeys = sorted(dailyGroup.keys(), key=lambda x: datetime.strptime(x, '%Y-%m-%d %H:%M'))
+		for dt_str in sortedDateKeys:
+			oneRow = [system.date.parse(dt_str, "yyyy-MM-dd HH:mm")]
+			for c in inclColumns:
+#				print dailyGroup[dt_str]
+				cleanValues = [v for v in dailyGroup[dt_str][c] if v is not None] 
+				dtAvg = sum(cleanValues)/len(cleanValues) if len(cleanValues) > 0 else 0
+				allAvgs.append(dtAvg)
+				oneRow.append(dtAvg)
+			resultData.append(oneRow)
+	
+	res["MinAvg"] = min(allAvgs) if len(allAvgs) > 0 and not all(x == 0 for x in allAvgs) else -1
+	res["MaxAvg"] = max(allAvgs) if len(allAvgs) > 0 and not all(x == 0 for x in allAvgs) else 1
+	res["SimpAvg"] = sum(allAvgs)/len(allAvgs) if len(allAvgs) > 0 else 0
+	res["Paths"] = inclColumns
+
+	# we're going to inject two new columns to resultData
+	for row in resultData:
+		row.extend([res["MinAvg"], res["MaxAvg"]])
+		
+	res["ResultDS"] = system.dataset.toDataSet(["Date"]+["Unit%s"%(i+1) for i in range(len(inclColumns))]+["Min", "Max"], resultData)
+#	res["RawDS"] = data
+	return res
+
+def getEqNamesByLoc(location):
+	mEqPaths = []
+	for ups1path, ups2path in getTagPaths(location):
+		mEqPaths.extend(["%s/Meta/EqName"%ups1path, "%s/Meta/EqName"%ups2path])
+	return [qv.value for qv in system.tag.readBlocking(mEqPaths)]
+
+def getEqNamesByPath(paths):
+	mEqPaths = ["/".join(p.split("/")[:-1]) +"/Meta/EqName" for p in paths]
+	return [qv.value for qv in system.tag.readBlocking(mEqPaths)]
+	
+def processAverage(startDate, endDate, location, interval=None):
+	finalRes= {}
+	def getUPSName(tagpath):		
+		return tagpath.split("_")[-1].split("/")[0][:-2] if "-"in tagpath else 	tagpath.split("_")[-1].split("/")[0][:-1]
+	def getRoomName(tagpath):
+#		return tagpath.split("/")[1].split("_")[1]
+		if "]" in tagpath:
+			return tagpath.split("/")[0].split("]")[1]
+		else:
+			return tagpath.split("/")[0]
+
+	
+	histData, rawTagPaths = getPowerHist(startDate,endDate, location)
+	header = system.dataset.getColumnHeaders(histData)
+	# clone the header for actual tagpaths
+	rawTagPaths = [""]+rawTagPaths
+#	print header
+	allRows = []
+	newHeader = ["ChartName","MinAvg","MaxAvg","ChartDS", "SimpAvg"]
+	
+	res = averageHistData(histData, ["SumTotalkW"], interval)
+	allRows.append(["Data Hall Total Loading", res["MinAvg"], res["MaxAvg"], res["ResultDS"], res["SimpAvg"]])
+	finalRes["TotalLoading"] = system.dataset.toDataSet(newHeader, allRows)
+	
+	allRows= []
+	
+	# Format the result
+	for i in range(1, len(header)-2, 2):  # Start at index 1, step by 2 to get pairs
+		tag1, tag2 = header[i], header[i+1]
+		res = averageHistData(histData, [tag1,tag2], interval)
+		eq1,eq2 = reports.MBR.criticalpower.getEqNamesByPath([rawTagPaths[i], rawTagPaths[i+1]])
+		allRows.append([getRoomName(tag1)+" Loading", res["MinAvg"], res["MaxAvg"], res["ResultDS"], res["SimpAvg"], getUPSName(tag1), eq1, eq2])	    
+	
+	finalRes["reportDS"] = system.dataset.toDataSet(newHeader+["ChartCategory", "Eq1", "Eq2"], allRows)
+	finalRes["rawDS"] = histData
+#	finalRes["NameLists"] = reports.MBR.criticalpower.getEqNames(location)
+	
+	return finalRes
+	
+def doDailyReport(startDate, endDate, location=None):
+	return processAverage(startDate, endDate, location, None)
+	
+def doReportInterval(startDate, endDate, location=None, interval=15):
+	return processAverage(startDate, endDate, location, interval)