def main():
args = docopt.docopt(__doc__)
print(args)
cluster.require_qsub()
workspace = pipeline.workspace_from_dir(args['<workspace>'])
# If not a fragment workspace, make a new one
if not hasattr(workspace, 'fasta_path'):
step = workspace.get_next_step()
workspace = pipeline.ValidationWorkspace(workspace.root_dir, step)
workspace.check_paths()
workspace.make_dirs()
workspace.clear_fragments()
inputs = pick_inputs(workspace)
if not inputs:
print('All inputs already have fragments')
# if not '--input_model' in args:
# model = workspace.input_pdb_path
# else:
# model = args['--input_model']
# Run the fragment generation script.
generate_fragments = [
'klab_generate_fragments',
'--outdir',
workspace.fragments_dir,
'--memfree',
args['--mem-free'],
] + inputs
if not args['--ignore-loop-file']:
generate_fragments += [
'--loops_file',
workspace.loops_path,
]
if args['--dry-run']:
print(' '.join(generate_fragments))
else:
subprocess.call(generate_fragments)
def get_workspace(root_dir, step):
return pipeline.ValidationWorkspace(root_dir, step)
def get_workspace(root_dir, step):
'''
Provides information to the submission script about the workspace
'''
return pipeline.ValidationWorkspace(root_dir, step)