data.sample_project_column,
line))
# Empty names
empty_names = data.empty_names
if len(empty_names) > 0:
check_status = 1
for line in empty_names:
logging.warning("Empty %s and/or %s in line:\n%s" %
(data.sample_id_column,
data.sample_project_column,
line))
# Predict outputs
if check_status == 0 or args.ignore_warnings or args.view:
# Generate prediction
prediction = []
predictor = IlluminaData.SampleSheetPredictor(sample_sheet=data)
title = "Predicted projects:"
prediction.append("%s\n%s" % (title,('='*len(title))))
for project_name in predictor.project_names:
prediction.append("- %s" % project_name)
for project_name in predictor.project_names:
project = predictor.get_project(project_name)
title = "%s (%d samples)" % (project_name,
len(project.sample_ids))
prediction.append("\n%s\n%s" % (title,('-'*len(title))))
for sample_id in project.sample_ids:
sample = project.get_sample(sample_id)
for barcode in sample.barcode_seqs:
lanes = sample.lanes(barcode)
if lanes:
lanes = "L%s" % (','.join([str(l)
