Predicted=float(linetokens[1]),
ID=id))
id += 1
else:
raise Exception(
'At least two columns (experimental DDG, predicted DDG) are expected.'
)
return table
except Exception, e:
raise Exception('An exception occurred parsing the CSV/TSV file: %s' %
str(e))
if __name__ == '__main__':
try:
arguments = docopt.docopt(__doc__.format(**locals()))
except Exception, e:
print('Failed while parsing arguments: %s.' % str(e))
sys.exit(1)
# Read file input file
input_filename = arguments['<inputfile>'][0]
if not os.path.exists(input_filename):
print('Error: the input file %s does not exist.' % input_filename)
sys.exit(2)
analysis_table = read_json(input_filename)
if not analysis_table:
analysis_table = parse_csv(input_filename)
# Set up the output filename
output_filename = arguments['--output']
for linetokens in lines:
if len(linetokens) >= 3:
table.append(dict(Experimental = float(linetokens[0]), Predicted = float(linetokens[1]), ID = str(linetokens[2])))
elif len(linetokens) == 2:
table.append(dict(Experimental = float(linetokens[0]), Predicted = float(linetokens[1]), ID = id))
id += 1
else:
raise Exception('At least two columns (experimental DDG, predicted DDG) are expected.')
return table
except Exception, e:
raise Exception('An exception occurred parsing the CSV/TSV file: %s' % str(e))
if __name__ == '__main__':
try:
arguments = docopt.docopt(__doc__.format(**locals()))
except Exception, e:
print('Failed while parsing arguments: %s.' % str(e))
sys.exit(1)
# Read file input file
input_filename = arguments['<inputfile>'][0]
if not os.path.exists(input_filename):
print('Error: the input file %s does not exist.' % input_filename)
sys.exit(2)
analysis_table = read_json(input_filename)
if not analysis_table:
analysis_table = parse_csv(input_filename)
# Set up the output filename
output_filename = arguments['--output']
# Create the new PDB file with the loop residue backbone atoms added back in
write_file(os.path.join(output_directory, '{0}.pdb'.format(pdb_prefix)), new_pdb_content)
# Create a loop file in Rosetta numbering for protocols which require that format (the loopmodel code currently
# requires this at the time of writing)
write_file(os.path.join(output_directory, '{0}.loop'.format(pdb_prefix)), loop_file_content)
sys.stdout.write('.')
sys.stdout.flush()
print('')
if __name__ == '__main__':
from libraries import docopt
arguments = docopt.docopt(__doc__)
output_directory = arguments['<output_directory>']
e, trc = '', ''
if True:
# Disable this code by default
try:
os.mkdir(output_directory)
except Exception, e: trc = traceback.format_exc()
if not os.path.exists(output_directory):
colortext.error('Error: Could not create the output directory.')
if e: colortext.error(str(e))
colortext.warning(trc)
#create_pruned_structures(output_directory)
add_missing_residues(output_directory)
#!/usr/bin/env python2
"""\
Usage: hilbert_demo.py [--steps=STEPS] [--test-run]
"""
import subprocess, numpy as np
from libraries import docopt, utils
args = docopt.docopt(__doc__)
num_particles = 512 if args['--test-run'] else 512
num_steps = int(args['--steps'] or
(1 if args['--test-run'] else (20 if utils.running_on_cluster() else 3)))
num_xyz_restraints = np.linspace(10, 50, num=num_steps).astype(int)
num_pair_restraints = np.linspace(150, 500, num=num_steps).astype(int)
params = []
for n_xyz in num_xyz_restraints:
for n_pair in num_pair_restraints:
params.append({
'num_particles': num_particles,
'num_xyz_restraints': n_xyz,
'num_pair_restraints': n_pair,
})
utils.clear_directories('jsons', 'pdbs', 'movies')
utils.submit_job('run_hilbert_demo.py', params)