traind = None
if class_name in class_options:
traind = class_options[class_name]
elif not recover and not testdatafor:
print('available classes:')
for key, val in class_options.iteritems():
print(key)
raise Exception('wrong class selection')
if testdatafor:
logging.info('converting test data, no weights applied')
dc.createTestDataForDataCollection(
testdatafor,
infile,
outPath,
outname=(args.batch if args.batch else 'dataCollection.dc'),
traind=(traind(class_args) if traind else None),
relpath=relpath)
elif recover:
dc.recoverCreateDataFromRootFromSnapshot(recover)
elif args.means:
dc.convertListOfRootFiles(infile,
traind(class_args) if class_args else traind(),
outPath,
means_only=True,
output_name='batch_template.dc',
relpath=relpath)
else:
logging.info('Start conversion')
dc.convertListOfRootFiles(
useRelativePaths=True if not args.noRelativePaths else False)
if len(nchilds):
dc.nprocs = int(nchilds)
if class_name in class_options:
traind = class_options[class_name]
elif not recover and not testdatafor:
print('available classes:')
for key, val in class_options.iteritems():
print(key)
raise Exception('wrong class selection')
if testdatafor:
logging.info('converting test data, no weights applied')
dc.createTestDataForDataCollection(
testdatafor,
infile,
outPath,
outname=args.batch if args.batch else 'dataCollection.dc',
batch_mode=bool(args.batch))
elif recover:
dc.recoverCreateDataFromRootFromSnapshot(recover)
elif args.means:
dc.convertListOfRootFiles(infile,
traind(),
outPath,
means_only=True,
output_name='batch_template.dc')
else:
dc.convertListOfRootFiles(
infile,
traind(),
outPath,
dc.nprocs = int(nchilds)
traind = None
if class_name in class_options:
traind = class_options[class_name]
elif not recover and not testdatafor:
print('available classes:')
for key, val in class_options.iteritems():
print(key)
raise Exception('wrong class selection')
if testdatafor:
logging.info('converting test data, no weights applied')
dc.createTestDataForDataCollection(
testdatafor,
infile,
outPath,
outname=args.batch if args.batch else 'dataCollection.dc',
batch_mode=bool(args.batch),
traind=traind(class_args) if traind else None)
elif recover:
dc.recoverCreateDataFromRootFromSnapshot(recover)
elif args.means:
dc.convertListOfRootFiles(infile,
traind(class_args) if class_args else traind(),
outPath,
means_only=True,
output_name='batch_template.dc')
else:
dc.convertListOfRootFiles(
infile,
traind(class_args) if class_args else traind(),