def test_dateDataListToList(self):
metricName = "metric"
dateDataList = [{metricName: 30}, {metricName: 40}, {metricName: 50}]
resList = util.dateDataListToList(dateDataList, metricName)
self.assertEqual(resList[0], 30)
self.assertEqual(resList[1], 40)
self.assertEqual(resList[2], 50)
def getdayDifference(lobName, granularity=0):
fromDate = util.jsStringToDate("2016-12-15T00:00:00.000Z").replace(hour=0, minute=0, second=0)
toDate = util.jsStringToDate("2017-01-05T00:00:00.000Z").replace(hour=0, minute=0, second=0)
response = {}
mongoQuery = data_query.DateRangeGroupQuery(fromDate, toDate, [lobName], granularity)
data = mongoQuery.execute()
metrics = {}
metricsList = mongoQuery.metrics
metadata = mongoQuery.metadata
data = data_query.medianDateRange(fromDate, toDate, lobName, granularity, data)
return util.dateDataListToList(data, "dayDifference")
def getData(flows, fromDate, toDate):
flow = flows[0]
flowName = flow["name"]
mongoQuery = data_query.DateRangeGroupQuery(fromDate,
toDate,
flows,
granularity=granularity)
data = mongoQuery.execute()
metricsList = mongoQuery.metrics
metadata = mongoQuery.metadata
if len(flows) == 1:
metric = metricsList[0]
flowLevelQuery = data_query.FlowLevelDateRangeQuery(
fromDate, toDate, flows, metadata["granularity"], data)
flowLevelData = flowLevelQuery.execute()
data = util.merge2DateLists(flowLevelData, None, data, None)
metricsList.extend(flowLevelQuery.metrics)
outageQuery = data_query.OutageDateRangeQuery(fromDate, toDate,
flows[0],
metadata["granularity"])
outageQuery.setPrecomputedData(data, metric)
outageList = outageQuery.execute()
data = util.merge2DateLists(outageList, [outageQuery.metric], data,
None)
metricsList.append(outageQuery.metric)
dates = list(
map(lambda x: x.strftime("%d.%m %H:%M"),
util.dateDataListToList(data, "_id")))
data1 = util.dateDataListToList(data, flowName)
expected = util.dateDataListToList(data, "expected")
dataTicks = []
dataTickPos = []
for i in range(0, len(dates)):
if True:
dataTicks.append(dates[i])
dataTickPos.append(i)
return data1, expected, dataTicks, dataTickPos
for x, y in zip(windowData, weights):
s += x * y
average = s / sum(weights)
output.append(average)
return output
fromDate = util.stringToTime("02.03.2017 00:00:00")
toDate = util.stringToTime("03.03.2017 00:00:00")
granularity = 15
q = DateRangeGroupQuery(
fromDate, toDate,
[MediationConfig.getLobWithCountry("CZ", "GSM")["flows"]["MSSBRN1A"]],
granularity)
# q = DateRangeGroupQuery(fromDate, toDate, [MediationConfig.getLobWithCountry("CZ","ACI")["flows"]["GSM"]], granularity)
lob1Data = util.dateDataListToList(q.execute(), "MSSBRN1A")
lob1Data.append(0)
lob1Data.append(0)
lob1Data.append(0)
lob1Data.append(0)
dates = list(
map(
lambda x: util.dateToTimeString(x).split("+")[0].split("T")[1].split(
":")[0], util.dateDataListToList(q.execute(), "_id")))
dataTicks = []
dataTickPos = []
for i in range(0, len(dates)):
if i % 4 == 0:
dataTicks.append(dates[i])
dataTickPos.append(i)
s += x * y
average = s / sum(weights)
output.append(average)
return output
fromDate = util.stringToTime("02.03.2017 00:00:00")
toDate = util.stringToTime("03.03.2017 00:00:00")
granularity = 60
x = MediationConfig.getLobWithCountry("CZ", "GSM")
q = DateRangeGroupQuery(
fromDate, toDate,
[MediationConfig.getLobWithCountry("CZ", "DAR")["flows"]["DARE2FEE"]],
granularity)
# q = DateRangeGroupQuery(fromDate, toDate, [MediationConfig.getLobWithCountry("CZ","ACI")["flows"]["GSM"]], granularity)
lob1Data = util.dateDataListToList(q.execute(), "DARE2FEE")
dates = list(
map(
lambda x: util.dateToTimeString(x).split("+")[0].split("T")[1].split(
":")[0], util.dateDataListToList(q.execute(), "_id")))
dataTicks = []
dataTickPos = []
for i in range(0, len(dates)):
if i % 4 == 0:
dataTicks.append(dates[i])
dataTickPos.append(i)
# lob1Data=[100,0,0,100,0,0,100,0,0,100,0,0,100,0,0,100,0,0,100,0,0,100,0,0]
plt.figure(figsize=(12, 6))
plt.plot(lob1Data, color="#ff009f", label="actual data")
metric = metricsList[0]
flowLevelQuery = data_query.FlowLevelDateRangeQuery(
fromDate, toDate, flows, metadata["granularity"], data)
flowLevelData = flowLevelQuery.execute()
data = util.merge2DateLists(flowLevelData, None, data, None)
metricsList.extend(flowLevelQuery.metrics)
outageQuery = data_query.OutageDateRangeQuery(fromDate, toDate, flows[0],
metadata["granularity"])
outageQuery.setPrecomputedData(data, metric)
outageList = outageQuery.execute()
data = util.merge2DateLists(outageList, [outageQuery.metric], data, None)
metricsList.append(outageQuery.metric)
dates = list(
map(lambda x: x.strftime("%d.%m %H:%M"),
util.dateDataListToList(data, "_id")))
data1 = util.dateDataListToList(data, flowName)
expected = util.dateDataListToList(data, "expected")
dataTicks = []
dataTickPos = []
for i in range(0, len(dates)):
if i % 24 == 0:
dataTicks.append(dates[i])
dataTickPos.append(i)
plt.figure(figsize=(12, 5))
plt.plot(data1, color="red", label=lobName + "-" + flowName)
plt.plot(expected, color="blue", label="expected")
plt.plot(util.dateDataListToList(data, "dayAverage"),
color="orange",
label="day average")
metric = metricsList[0]
flowLevelQuery = data_query.FlowLevelDateRangeQuery(
fromDate, toDate, flows, metadata["granularity"], data)
flowLevelData = flowLevelQuery.execute()
data = util.merge2DateLists(flowLevelData, None, data, None)
metricsList.extend(flowLevelQuery.metrics)
outageQuery = data_query.OutageDateRangeQuery(fromDate, toDate, flows[0],
metadata["granularity"])
outageQuery.setPrecomputedData(data, metric)
outageList = outageQuery.execute()
data = util.merge2DateLists(outageList, [outageQuery.metric], data, None)
metricsList.append(outageQuery.metric)
dates = list(
map(lambda x: x.strftime("%d.%m %H:%M"),
util.dateDataListToList(data, "_id")))
data1 = util.dateDataListToList(data, flowName)
expected = util.dateDataListToList(data, "expected")
dayDifference = util.dateDataListToList(data, "dayDifference")
tickDifference = util.dateDataListToList(data, "tickDifference")
dataTicks = []
dataTickPos = []
for i in range(0, len(dates)):
if i % 12 == 0:
dataTicks.append(dates[i])
dataTickPos.append(i)
plt.figure(figsize=(12, 9))
plt.subplot(211)
plt.xticks(dataTickPos, dataTicks, rotation=25)