def main():
args = docopt.docopt(__doc__)
cluster.require_qsub()
workspace = pipeline.ValidatedDesigns(args['<workspace>'], args['<round>'])
workspace.check_paths()
workspace.check_rosetta()
workspace.make_dirs()
workspace.clear_fragments()
# Run the fragment generation script.
generate_fragments = [
'klab_generate_fragments',
'--loops_file',
workspace.loops_path,
'--outdir',
workspace.fragments_dir,
'--memfree',
args['--mem-free'],
workspace.input_dir,
]
if args['--dry-run']:
print ' '.join(generate_fragments)
else:
subprocess.call(generate_fragments)
def main():
args = docopt.docopt(__doc__)
cluster.require_qsub()
workspace = pipeline.workspace_from_path(args['<workspace>'])
workspace.check_paths()
workspace.make_dirs()
workspace.clear_fragments()
# Run the fragment generation script.
generate_fragments = [
'klab_generate_fragments',
workspace.input_pdb_path,
'--outdir',
workspace.fragments_dir,
'--memfree',
args['--mem_free'],
]
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 main():
args = docopt.docopt(__doc__)
cluster.require_qsub()
# Setup the workspace.
workspace = pipeline.FixbbDesigns(args['<workspace>'], args['<round>'])
workspace.check_paths()
workspace.check_rosetta()
workspace.make_dirs()
if args['--clear'] or args['--test-run']:
workspace.clear_outputs()
# Decide which inputs to use.
inputs = workspace.unclaimed_inputs
nstruct = len(inputs) * int(args['--nstruct'])
if not inputs:
print """\
All the input structures have already been (or are already being) designed. If
you want to rerun all the inputs from scratch, use the --clear flag."""
raise SystemExit
# Submit the design job.
big_jobs.submit('pip_design.py',
workspace,
inputs=inputs,
nstruct=nstruct,
max_runtime=args['--max-runtime'],
max_memory=args['--max-memory'],
test_run=args['--test-run'])
def main():
args = docopt.docopt(__doc__)
cluster.require_qsub()
# Setup the workspace.
workspace = pipeline.ValidatedDesigns(args['<workspace>'], args['<round>'])
workspace.check_paths()
workspace.make_dirs()
if args['--clear'] or args['--test-run']:
workspace.clear_outputs()
# Setup an output directory for each input.
inputs = workspace.unclaimed_inputs
nstruct = len(inputs) * int(args['--nstruct'])
if nstruct == 0:
scripting.print_error_and_die("""\
No unclaimed input files.
If you previously started a round of simulations and then stopped them for some
reason, the problem is probably that all the inputs are still claimed by those
simulations. Use the '--clear' flag to remove the claims and try again.""")
for input in inputs:
subdir = workspace.output_subdir(input)
scripting.clear_directory(subdir)
# Launch the validation job.
big_jobs.submit(
'pip_validate.py',
workspace,
inputs=inputs,
nstruct=nstruct,
max_runtime=args['--max-runtime'],
max_memory=args['--max-memory'],
test_run=args['--test-run'],
)
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 main():
arguments = docopt.docopt(__doc__)
cluster.require_qsub()
# Setup the workspace.
workspace = pipeline.RestrainedModels(arguments['<workspace>'])
workspace.check_paths()
workspace.check_rosetta()
workspace.make_dirs()
if arguments['--clear'] or arguments['--test-run']:
workspace.clear_outputs()
# Submit the model building job.
big_jobs.submit('pip_build.py',
workspace,
nstruct=arguments['--nstruct'],
max_runtime=arguments['--max-runtime'],
max_memory=arguments['--max-memory'],
test_run=arguments['--test-run'])
def main():
cluster.require_qsub()
start_time = time.time()
workspace, job_info = big_jobs.initiate()
pdbpath = workspace.input_path(job_info)
if not os.path.exists(workspace.output_prefix(job_info)):
os.mkdir(workspace.output_prefix(job_info))
outpath = workspace.output_path(job_info)
test_run = job_info.get('test_run', False)
# append location of Rosetta binaries to path
abinitio = '/wynton/home/kortemme/krivacic/rosetta/source/bin/AbinitioRelax.linuxgccrelease'
# find necessary files
print('fdir :', workspace.fragments_dir)
print('pdb :', pdbpath)
print(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*3mers.gz'))
tmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*3mers.gz'))[0]
nmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*9mers.gz'))[0]
ss2 = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*psipred_ss2'))[0]
fasta = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*fasta'))[0]
# Set up tempdir
if 'TMPDIR' in os.environ:
os_tmp = os.environ['TMPDIR']
elif args['--task']:
os_tmp = os.path.join(os.environ['HOME'], 'temp')
else:
os_tmp = os.path.join('/scratch', os.environ['USER'])
outdir_temp = os.path.join(os_tmp, str(task_num))
if not os.path.exists(outdir_temp):
os.makedirs(outdir_temp, exist_ok=True)
# Run the ab initio relax script.
outfile = os.path.join(
outdir_temp, 'silent{}.out'.format(workspace.output_suffix(job_info)))
relax_abinitio = [
abinitio,
'-abinitio:relax',
'-use_filters',
'true',
'-abinitio::increase_cycles',
'10',
'-abinitio::rg_reweight',
'0.5',
'-abinitio::rsd_wt_helix',
'0.5',
'-abinitio::rsd_wt_loop',
'0.5',
'-relax::fast',
'-in:file:fasta',
fasta,
'-in:file:frag3',
tmers,
'-in:file:frag9',
nmers,
'-in:file:psipred_ss2',
ss2,
'-nstruct',
'10',
# '-out:pdb_gz',
# '-out:sf', workspace.output_prefix(job_info) + 'score{}.sc'.format(workspace.output_suffix(job_info)),
# '-out:file:silent', workspace.output_prefix(job_info) + 'silent{}.out'.format(workspace.output_suffix(job_info)),
'-out:file:silent',
outfile,
# '-out:prefix', workspace.output_prefix(job_info),
# '-out:suffix', workspace.output_suffix(job_info),
'-out:no_nstruct_label'
# '--outdir', workspace.fragments_dir,
# '--memfree', args['--mem-free']
]
print('Running ROSETTA command:')
print(' '.join(relax_abinitio))
subprocess.call(relax_abinitio)
from shutil import copyfile
if not os.path.exists(workspace.output_prefix(job_info)):
os.makedirs(workspace.output_prefix(job_info), exist_ok=True)
final = os.path.join(
workspace.output_prefix(job_info),
'silent{}.out'.format(workspace.output_suffix(job_info)))
copyfile(outfile, final)
def main():
cluster.require_qsub()
start_time = time.time()
workspace, job_info = big_jobs.initiate()
pdbpath = workspace.input_path(job_info)
if not os.path.exists(workspace.output_prefix(job_info)):
os.mkdir(workspace.output_prefix(job_info))
outpath = workspace.output_path(job_info)
test_run = job_info.get('test_run', False)
# append location of Rosetta binaries to path
abinitio = '/wynton/home/kortemme/krivacic/rosetta/source/bin/AbinitioRelax.linuxgccrelease'
# find necessary files
print('fdir :', workspace.fragments_dir)
print('pdb :', pdbpath)
print(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*3mers.gz'))
tmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*3mers.gz'))[0]
nmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*9mers.gz'))[0]
ss2 = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*psipred_ss2'))[0]
fasta = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath.lower()) + '?',
'*fasta'))[0]
# Run the ab initio relax script.
relax_abinitio = [
abinitio,
'-abinitio:relax',
'-use_filters',
'true',
'-abinitio::increase_cycles',
'10',
'-abinitio::rg_reweight',
'0.5',
'-abinitio::rsd_wt_helix',
'0.5',
'-abinitio::rsd_wt_loop',
'0.5',
'-relax::fast',
'-in:file:fasta',
fasta,
'-in:file:frag3',
tmers,
'-in:file:frag9',
nmers,
'-in:file:psipred_ss2',
ss2,
'-nstruct',
'10',
# '-out:pdb_gz',
'-out:file:silent',
workspace.output_prefix(job_info) +
'silent_{}.out'.format(workspace.output_suffix(job_info)),
# '-out:prefix', workspace.output_prefix(job_info),
# '-out:suffix', workspace.output_suffix(job_info),
'-out:no_nstruct_label'
# '--outdir', workspace.fragments_dir,
# '--memfree', args['--mem-free']
]
print('Running ROSETTA command:')
print(' '.join(relax_abinitio))
subprocess.call(relax_abinitio)
def main():
args = docopt.docopt(__doc__)
if not args['--local'] and not args['--slurm'] and not args['--make-dirs']:
cluster.require_qsub()
workspace = pipeline.workspace_from_dir(args['<workspace>'])
if args['--step']:
step = args['--step']
elif hasattr(workspace, 'step'):
step = workspace.step
else:
step = workspace.get_next_step()
if not args['<script>']:
script = os.path.join(workspace.focus_dir, 'run.py')
else:
script = args['<script>']
if not os.path.exists(script):
raise pipeline.PathNotFound(script)
# Workspace type is defined in the run script, so we first need to
# import that.
script_path = os.path.dirname(script)
sys.path.insert(1, script_path)
script_name = os.path.basename(script)[:-3]
imp = importlib.import_module(script_name)
workspace = imp.get_workspace(workspace.root_dir, step)
workspace.check_paths()
# workspace.check_rosetta()
workspace.make_dirs()
if args['--make-dirs']:
sys.exit()
# Copying the script to the focus directory helps track exactly what
# we did at each step.
shutil.copyfile(script, workspace.script_path)
if args['--clear'] or args['--test-run']:
workspace.clear_outputs()
inputs = [
x for x in workspace.unclaimed_inputs
]
if len(inputs)==0:
num_inputs = 1
else:
num_inputs = len(inputs)
if args['--test-run']:
nstruct = num_inputs * 10
else:
nstruct = num_inputs * int(args['--nstruct'])
if workspace.subdirs:
for inp in inputs:
subdir = workspace.output_subdir(inp)
# scripting.clear_directory(subdir)
# Submit the job
if args['--local']:
print('Running locally.')
for n in range(1,nstruct + 1):
cmd = [workspace.python_path]
cmd.append(workspace.script_path)
cmd.append(workspace.focus_dir)
cmd.append(str(n))
execute(cmd)
# read_and_display(cmd)
elif args['--slurm']:
big_jobs.submit_slurm(
workspace,
nstruct=nstruct,
max_runtime=args['--max-runtime'],
max_memory=args['--max-memory'],
test_run=args['--test-run'],
job_name=script_name,
inputs=inputs
)
else:
big_jobs.submit(
workspace.script_path, workspace,
nstruct=nstruct,
max_runtime=args['--max-runtime'],
max_memory=args['--max-memory'],
test_run=args['--test-run'],
job_name=script_name,
inputs=inputs
)
def main():
args = docopt.docopt(__doc__)
print(args)
cluster.require_qsub()
start_time = time.time()
workspace, job_info = big_jobs.initiate()
pdbpath = workspace.input_path(job_info)
if not os.path.exists(workspace.output_prefix(job_info)):
os.mkdir(workspace.output_prefix(job_info))
outpath = workspace.output_path(job_info)
test_run = job_info.get('test_run', False)
# append location of Rosetta binaries to path
sys.path.append('/wynton/home/kortemme/krivacic/source/bin')
# find necessary files
tmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath) + '?', '*3mers.gz'))
nmers = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath) + '?', '*9mers.gz'))
ss2 = glob.glob(
os.path.join(workspace.fragments_dir,
workspace.fragments_tag(pdbpath) + '?', '*psipred_ss2'))
# Run the ab initio relaxation script.
relax_abinitio = [
'AbinitioRelax.linuxgccrelease',
'-abinitio:relax',
'-use_filters',
'true',
'-abinitio::increase_cycles',
'10',
'-abinitio::rg_reweight',
'0.5',
'-abinitio::rsd_wt_helix',
'0.5',
'-abinitio::rsd_wt_loop',
'0.5',
'-relax::fast',
'-in:file:fasta',
workspace.fasta_path,
'-in:file:frag3',
tmers,
'-in:file:frag9',
nmers,
'-in:file:psipred_ss2',
ss2,
'-nstruct',
args.nstruct,
'-out:pdb_gz',
'-out:prefix',
workspace.output_prefix(job_info),
'-out:suffix',
workspace.output_suffix(job_info),
# '--outdir', workspace.fragments_dir,
# '--memfree', args['--mem-free']
]
if args['--dry-run']:
print(' '.join(relax_abinitio))
else:
subprocess.call(relax_abinitio)
init()
pose = pose_from_file(outpath)
input_pose = pose_from_file(pdbpath)
ca_rmsd = CA_rmsd(pose, input_pose)
all_atom_rmsd = all_atom_rmsd(pose, input_pose)
setPoseExtraScore(pose, 'EXTRA_METRIC_CA_RMSD [[-]]', ca_rmsd)
setPoseExtraScore(pose, 'EXTRA_METRIC_AllAtom_RMSD [[-]]', all_atom_rmsd)
filters = workspace.get_filters(pose,
task_id=job_info['task_id'],
score_fragments=not test_run,
test_run=test_run)
filters.run_filters()
total_time = time.time() - start_time
setPoseExtraScore(pose, 'EXTRA_METRIC_Run time', total_time)
outname = os.path.basename(outpath)
outfolder = os.path.join(workspace.output_prefix(job_info), 'filtered')
pose.dump_pdb(os.path.join(outfolder, outpath))
def submit(workspace,
cmd,
distributor='local',
clear=False,
test_run=False,
make_dirs=False,
ntasks=None,
nstruct=1,
max_runtime='10:00:00',
max_memory='5G'):
# args = docopt.docopt(__doc__)
# if not args['--local'] and not args['--slurm'] and not args['--make-dirs']:
if distributor == 'sge':
cluster.require_qsub()
# if args['--step']:
# step = args['--step']
# elif hasattr(workspace, 'step'):
# step = workspace.step
# else:
# step = workspace.get_next_step()
# if not args['<script>']:
# script = os.path.join(workspace.focus_dir, 'run.py')
# else:
# script = args['<script>']
# if not os.path.exists(script):
# raise pipeline.PathNotFound(script)
# Workspace type is defined in the run script, so we first need to
# import that.
# script_path = os.path.dirname(script)
# sys.path.insert(1, script_path)
# script_name = os.path.basename(script)[:-3]
# imp = importlib.import_module(script_name)
script_name = os.path.basename(cmd[1]).split('.')[0]
# workspace.check_paths()
# workspace.check_rosetta()
workspace.make_dirs()
# if args['--make-dirs']:
if make_dirs:
sys.exit()
# Copying the script to the focus directory helps track exactly what
# we did at each step.
# shutil.copyfile(script, workspace.script_path)
# if args['--clear'] or args['--test-run']:
if clear or test_run:
workspace.clear_outputs()
inputs = [x for x in workspace.unclaimed_inputs]
if len(inputs) == 0:
num_inputs = 1
else:
num_inputs = len(inputs)
if ntasks:
nstruct = ntasks
else:
nstruct = num_inputs * nstruct
# if workspace.subdirs:
# for inp in inputs:
# subdir = workspace.output_subdir(inp)
# scripting.clear_directory(subdir)
# Submit the job
if distributor == 'local':
print('Running locally.')
for n in range(1, nstruct + 1):
# cmd = [workspace.python_path]
# cmd.append(workspace.script_path)
# cmd.append(workspace.focus_dir)
# cmd.append(str(n))
cmd += str(n),
execute(cmd)
# read_and_display(cmd)
elif distributor == 'slurm':
big_jobs.submit_slurm(workspace,
cmd,
nstruct=workspace.nstruct,
max_runtime=max_runtime,
max_memory=max_memory,
test_run=test_run,
job_name=script_name,
inputs=inputs)
else:
print('Submitting the following command to SGE:')
print(' '.join(cmd))
big_jobs.submit(workspace,
cmd,
nstruct=nstruct,
max_runtime=max_runtime,
max_memory=max_memory,
test_run=test_run,
job_name=script_name,
inputs=inputs)