def test_getDailyVoltDataByLevel(self) -> None:
"""tests the function that gets hourly data of entity metric
"""
appDbConnStr = self.jsonConf['appDbConnStr']
mRepo = MetricsDataRepo(appDbConnStr)
startDt = dt.datetime(2020, 1, 1)
endDt = dt.datetime(2020, 1, 10)
samples = mRepo.getDailyVoltDataByLevel(
765, "%Time >420 or 800", startDt, endDt)
self.assertFalse(len(samples) == 0)
def fetchSection1_7_2Context(appDbConnStr: str, startDt: dt.datetime, endDt: dt.datetime) -> ISection_1_7_2:
mRepo = MetricsDataRepo(appDbConnStr)
# get voltage data for this month
maxVoltData = mRepo.getDailyVoltDataByLevel(400, "Max", startDt, endDt)
maxVoltDf = pd.DataFrame(maxVoltData)
maxVoltDf["data_val"] = pd.to_numeric(
maxVoltDf["data_val"], errors='coerce')
maxVoltSeries = maxVoltDf.groupby("entity_name").apply(getMax)
maxVoltSeries = maxVoltSeries.round()
maxVoltSeries = maxVoltSeries.rename("max_vol")
minVoltData = mRepo.getDailyVoltDataByLevel(400, "Min", startDt, endDt)
minVoltDf = pd.DataFrame(minVoltData)
minVoltDf["data_val"] = pd.to_numeric(
minVoltDf["data_val"], errors='coerce')
minVoltSeries = minVoltDf.groupby("entity_name").apply(getMin)
minVoltSeries = minVoltSeries.round()
minVoltSeries = minVoltSeries.rename("min_vol")
lessVoltPercData = mRepo.getDailyVoltDataByLevel(
400, "%Time <380 or 728", startDt, endDt)
lessVoltPercDf = pd.DataFrame(lessVoltPercData)
lessVoltPercDf["data_val"] = pd.to_numeric(
lessVoltPercDf["data_val"], errors='coerce')
lessVoltPercSeries = lessVoltPercDf.groupby("entity_name").apply(getMean)
lessVoltPercSeries = lessVoltPercSeries.round(2)
lessVoltPercSeries = lessVoltPercSeries.rename("less_perc")
bandVoltPercData = mRepo.getDailyVoltDataByLevel(
400, "%Time within IEGC Band", startDt, endDt)
bandVoltPercDf = pd.DataFrame(bandVoltPercData)
bandVoltPercDf["data_val"] = pd.to_numeric(
bandVoltPercDf["data_val"], errors='coerce')
bandVoltPercSeries = bandVoltPercDf.groupby("entity_name").apply(getMean)
bandVoltPercSeries = bandVoltPercSeries.round(2)
bandVoltPercSeries = bandVoltPercSeries.rename("band_perc")
moreVoltPercData = mRepo.getDailyVoltDataByLevel(
400, "%Time >420 or 800", startDt, endDt)
moreVoltPercDf = pd.DataFrame(moreVoltPercData)
moreVoltPercDf["data_val"] = pd.to_numeric(
moreVoltPercDf["data_val"], errors='coerce')
moreVoltPercSeries = moreVoltPercDf.groupby("entity_name").apply(getMean)
moreVoltPercSeries = moreVoltPercSeries.round(2)
moreVoltPercSeries = moreVoltPercSeries.rename("more_perc")
numMonthHrs = (endDt - startDt).total_seconds()/(60*60)
secDf = pd.concat([maxVoltSeries, minVoltSeries, lessVoltPercSeries,
bandVoltPercSeries, moreVoltPercSeries], axis=1)
secDf['less_hrs'] = secDf['less_perc']*(numMonthHrs*0.01)
secDf['more_hrs'] = secDf['more_perc']*(numMonthHrs*0.01)
secDf['out_hrs'] = secDf['less_hrs'] + secDf['more_hrs']
secDf['vdi'] = secDf['out_hrs']*(1/numMonthHrs)
secDf['less_hrs'] = secDf['less_hrs'].apply(hrsToDurationStr)
secDf['more_hrs'] = secDf['more_hrs'].apply(hrsToDurationStr)
secDf['out_hrs'] = secDf['out_hrs'].apply(hrsToDurationStr)
secDf['vdi'] = secDf['vdi'].apply(hrsToDurationStr)
secDf.reset_index(inplace=True)
secDf['entity_name'] = secDf['entity_name'].apply(strip400)
secDf.rename(columns={"entity_name": "station"}, inplace=True)
secDataRows = secDf.to_dict('records')
sectionData: ISection_1_7_2 = {
'voltVdiProfile400': secDataRows
}
return sectionData
def fetchSection1_1_voltContext(appDbConnStr: str, startDt: dt.datetime, endDt: dt.datetime) -> ISection_1_1_volt:
monthDtObj = dt.datetime(startDt.year, startDt.month, 1)
month_name = dt.datetime.strftime(startDt, "%b %y")
mRepo = MetricsDataRepo(appDbConnStr)
# get high voltage violation data for 765 kV
voltData765 = mRepo.getDailyVoltDataByLevel(
765, "%Time >420 or 800", startDt, endDt)
# convert to dataframe
voltData765Df = pd.DataFrame(voltData765)
# take only required columns
voltData765Df = voltData765Df[["entity_name", "data_val"]]
# convert column to numeric
voltData765Df['data_val'] = pd.to_numeric(
voltData765Df['data_val'], errors='coerce')
# get mean for each substation
voltData765Df = voltData765Df.groupby("entity_name").mean()
voltData765Df.reset_index(inplace=True)
# check if there is violation more than 0.1
is765MoreThan10Perc = voltData765Df[voltData765Df["data_val"]
> 10].shape[0] > 0
msg765 = ""
if not is765MoreThan10Perc:
msgStations = voltData765Df[voltData765Df["data_val"]
> 0]["entity_name"].values
msgStations = [x.replace(' - 765KV', '').capitalize()
for x in msgStations]
msg765 = "All 765 kV nodes of WR were within the IEGC limit."
if len(msgStations) > 0:
msg765 = "All 765 kV nodes of WR were within the IEGC limit except few instances at {0}.".format(
','.join(msgStations))
else:
msgStations = voltData765Df[voltData765Df["data_val"]
> 10]["entity_name"].values
msgStations = [x.replace(' - 765KV', '').capitalize()
for x in msgStations]
highViolSubstation = voltData765Df.loc[voltData765Df['data_val'].idxmax(
)]
msg765 = "High Voltage (greater than 800 kV) at 765 kV substations were observed at {0}. Highest of {1}{2} of time voltage remained above 780 kV at {3} in the month of {4}.".format(
', '.join(msgStations), round(highViolSubstation["data_val"], 2), "%", highViolSubstation["entity_name"].replace(' - 765KV', '').capitalize(), month_name)
# get high voltage violation data for 400 kV
voltData400 = mRepo.getDailyVoltDataByLevel(
400, "%Time >420 or 800", startDt, endDt)
# convert to dataframe
voltData400Df = pd.DataFrame(voltData400)
# take only required columns
voltData400Df = voltData400Df[["entity_name", "data_val"]]
# convert column to numeric
voltData400Df['data_val'] = pd.to_numeric(
voltData400Df['data_val'], errors='coerce')
# get mean for each substation
voltData400Df = voltData400Df.groupby("entity_name").mean()
voltData400Df.reset_index(inplace=True)
# check if there is violation more than 0.1
is400MoreThan10Perc = voltData400Df[voltData400Df["data_val"]
> 10].shape[0] > 0
msg400 = ""
if not is400MoreThan10Perc:
msgStations = voltData400Df[voltData400Df["data_val"]
> 0]["entity_name"].values
msgStations = [x.replace(' - 400KV', '').capitalize()
for x in msgStations]
msg400 = "All 400 kV nodes of WR were within the IEGC limit."
if len(msgStations) > 0:
msg400 = "All 400 kV nodes of WR were within the IEGC limit except few instances at {0}.".format(
','.join(msgStations))
else:
msgStations = voltData400Df[voltData400Df["data_val"]
> 10]["entity_name"].values
msgStations = [x.replace(' - 400KV', '').capitalize()
for x in msgStations]
highViolSubstation = voltData400Df.loc[voltData400Df['data_val'].idxmax(
)]
msg400 = "High Voltage (greater than 420 kV) at 400 kV substations were observed at {0}. Highest of {1}{2} of time voltage remained above 420 kV at {3} in the month of {4}.".format(
', '.join(msgStations), round(highViolSubstation["data_val"], 2), "%", highViolSubstation["entity_name"].replace(' - 400KV', '').capitalize(), month_name)
msg = " ".join([msg765, msg400])
secData: ISection_1_1_volt = {
"msg_1_1_volt": msg
}
return secData
def fetchSection1_7Context(appDbConnStr: str, startDt: dt.datetime,
endDt: dt.datetime) -> ISection_1_7:
metricsInfo = getVoltMetrics()
mRepo = MetricsDataRepo(appDbConnStr)
allMetris = {}
allMetris['400'] = {}
allMetris['765'] = {}
allStations = []
for metricIndex in range(len(metricsInfo)):
metricInfo = metricsInfo[metricIndex]
voltLevel = metricInfo['voltageLevel']
operation = metricInfo['operation']
metricName = metricInfo['metric_name']
if operation != 'compute ':
allEntityMetricData = mRepo.getDailyVoltDataByLevel(
voltLevel, metricName, startDt, endDt)
allEntityMetricDf = pd.DataFrame(allEntityMetricData)
allEntityMetricDf = allEntityMetricDf.groupby("entity_name")
allStations = allEntityMetricDf.groups.keys()
combinedObj = {}
for eachStation in allStations:
combinedObj[eachStation] = []
for eachRecord in allEntityMetricData:
if math.isnan(float(eachRecord['data_val'])):
eachRecord['data_val'] = 0
combinedObj[eachRecord['entity_name']].append(
float(eachRecord['data_val']))
stndWiseOperationData = {}
for eachStation in allStations:
stnData = combinedObj[eachStation]
val = 0
if operation == 'max':
val = max(stnData)
elif operation == 'sum':
val = sum(stnData) / ((endDt - startDt).days + 1)
# val = sum(stnData)
elif operation == 'min':
val = min(stnData)
stndWiseOperationData[eachStation] = val
allMetris[str(voltLevel)][metricName] = stndWiseOperationData
else:
refColumnName = metricInfo['evalColumn']
multiplyFactor = metricInfo['multiply']
allMetris[metricName] = {}
stndWiseOperationData = {}
for eachStation in allStations:
val = allMetris[str(voltLevel)][refColumnName][eachStation]
if multiplyFactor == 'monthHrs':
difference = endDt - startDt
days = difference.days + 1
factor = days * 24
stndWiseOperationData[eachStation] = int(val) * factor
elif multiplyFactor == 'weekHrs':
factor = 24 * 7
stndWiseOperationData[eachStation] = int(val) / factor
allMetris[str(voltLevel)][metricName] = stndWiseOperationData
print(allMetris)
df400 = pd.DataFrame(allMetris['400'])
df765 = pd.DataFrame(allMetris['765'])
df = df765.append(df400, ignore_index=True)
allMetricRecords400KV: List[IVoltageRecord] = []
allMetricRecords765V: List[IVoltageRecord] = []
allMetricRecords400KV = builtIRecord(df400)
allMetricRecords765V = builtIRecord(df765)
secData: ISection_1_7 = {
'voltageLevel400KV': allMetricRecords400KV,
'voltageLevel765KV': allMetricRecords765V
}
return secData
def fetchSection1_7_3Context(appDbConnStr: str, startDt: dt.datetime,
endDt: dt.datetime) -> ISection_1_7_3:
fullMonthName = dt.datetime.strftime(startDt, "%b' %Y")
mRepo = MetricsDataRepo(appDbConnStr)
metrics = ["Max", "Min"]
lvls = [400, 765]
numPltsPerPage = 6
numPages = 0
for m in metrics:
for l in lvls:
voltData = mRepo.getDailyVoltDataByLevel(l, m, startDt, endDt)
voltDf = pd.DataFrame(voltData)
voltDf["data_val"] = pd.to_numeric(voltDf["data_val"],
errors='coerce')
voltDf = voltDf.pivot(index="data_time",
columns="entity_name",
values="data_val")
if l == 400:
voltDf.columns = [strip400(x) for x in voltDf.columns]
elif l == 765:
voltDf.columns = [strip765(x) for x in voltDf.columns]
lowThresh = 300 if l == 400 else 650
voltDf[voltDf < lowThresh] = np.nan
numStations = voltDf.shape[1]
pageStartStnInd = 0
while pageStartStnInd < numStations:
pageEndStnInd = pageStartStnInd + numPltsPerPage
if pageEndStnInd >= numStations:
pageEndStnInd = numStations - 1
# create a plotting area and get the figure, axes handle in return
fig, ax = plt.subplots(figsize=(7.5, 4.5))
pltTitle = "{0}. Voltage Profile during the month of {1} - {2} kV S/S".format(
m, fullMonthName, l)
# set plot title
ax.set_title(pltTitle)
# set x and y labels
ax.set_xlabel('Date')
ax.set_ylabel('kV')
#c0c0c0
ax.set_facecolor("#c0c0c0")
# enable y axis grid lines
ax.yaxis.grid(True)
for stnIter in range(pageStartStnInd, pageEndStnInd + 1):
stnName = voltDf.columns[stnIter]
la, = ax.plot(voltDf.index.values,
voltDf[stnName].values,
linestyle='solid',
marker='.')
la.set_label(stnName)
# set x axis locator as day of month
ax.set_xlim((startDt, endDt), auto=True)
ax.xaxis.set_major_locator(mdates.DayLocator())
# set x axis formatter as month name
ax.xaxis.set_major_formatter(mdates.DateFormatter('%d'))
# enable legends
ax.legend(bbox_to_anchor=(0.0, -0.3, 1, 0),
loc='lower center',
ncol=numPltsPerPage,
mode="expand",
borderaxespad=0.)
fig.subplots_adjust(bottom=0.2, left=0.07, right=0.99)
fig.savefig('assets/section_1_7_3_{0}.png'.format(numPages))
numPages += 1
pageStartStnInd = pageEndStnInd + 1
sectionData: ISection_1_7_3 = {'num_plts_sec_1_7_3': numPages}
return sectionData
