wetOrDry,
month,
region,
randomSeed,
multiThreadApplyModels))
threads.append(t)
else:
# Run each pipeline in sequence
print('Running pipeline for %s, %s' % (region, month.capitalize()))
thesisFunctions.runKFoldPipeline(baseDirectoryPath,
myFeaturesIndex,
myLabelIndex,
selectedFeatureList,
kFolds,
wetOrDry,
month,
region,
randomSeed,
multiThreadApplyModels)
print()
if multiThreading:
# Start all threads
for t in threads:
t.start()
# Wait for all threads to finish before continuing
for t in threads:
t.join()
myFeaturesIndex = 6
myLabelIndex = 5
kFolds = 5
modelApproach = 'sacramento'
randomSeed = constants.randomSeed
selectedFeatureList = ['p0', 'p1', 'p2', 'p3', 'p4', 'p5', 'p6', 'p7', 'p8', 'p9', 'p10', 'p11', 'p12',
't0', 't1', 't2', 't3', 't4', 't5', 't6', 't7', 't8', 't9', 't10', 't11', 't12',
'p2sum', 'p3sum', 'p6sum', 'PERMAVE', 'RFACT', 'DRAIN_SQKM', 'ELEV_MEAN_M_BASIN_30M',
'WD_BASIN', 'IntMnt', 'jan', 'feb', 'mar', 'apr', 'may', 'jun', 'jul', 'aug',
'sep', 'oct', 'nov']
multiThreadApplyModels = True
# Run the flow model pipeline for five folds
thesisFunctions.runKFoldPipeline(baseDirectoryPath,
myFeaturesIndex,
myLabelIndex,
selectedFeatureList,
kFolds,
modelApproach,
randomSeed=randomSeed,
multiThreadApplyModels=multiThreadApplyModels)
endSecond = time.time()
endTime = time.strftime('%a, %d %b %Y %X')
totalSeconds = endSecond - startSecond
print()
print('Start time:', startTime)
print('End time:', endTime)
print('Total: {} minutes and {} seconds'.format(int(totalSeconds // 60), round(totalSeconds % 60)))
