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job.addChildJobFn(get_inferred_structural_interactome_by_table, dataset_name, table, memory="120000M")
def start_toil(job, dataset_name):
if not os.path.isdir(get_interfaces_path(dataset_name)):
os.makedirs(get_interfaces_path(dataset_name))
obsjob = job.addChildJobFn(start_toil_observed, dataset_name)
infjob = obsjob.addFollowOnJobFn(start_toil_inferred, dataset_name)
infmergejob = infjob.addFollowOnJobFn(start_toil_inferred_merge, dataset_name, cores=20, memory="240000M")
return
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
options = parser.parse_args()
options.logLevel = "DEBUG"
options.clean = "always"
dataset_name = options.jobStore.split(":")[-1]
print "Running"
job = Job.wrapJobFn(start_toil, dataset_name)
with Toil(options) as toil:
toil.start(job)
cjob.addFollowOnJobFn(inferred_bsa, dataset_name, sfam_id, memory=memory)
elif "/inferred" not in keys:
cjob = job.addChildJobFn(inferred_bsa, dataset_name, sfam_id, memory=memory)
job.addFollowOnJobFn(start_toil, dataset_name, iteration=1)
# cjob = job.addChildJobFn(observed_bsa, dataset_name, sfam_id)
# if not os.path.isfile(sfam_path+".inferred_interactome"):
# continue
# cjob.addFollowOnJobFn(inferred_bsa, dataset_name, sfam_id)
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
options = parser.parse_args()
options.logLevel = "DEBUG"
options.clean = "always"
dataset_name = options.jobStore.split(":")[-1]
job = Job.wrapJobFn(start_toil, dataset_name)
with Toil(options) as toil:
toil.start(job)
def get_toil_defaults(self):
"""
Extracts the default toil options as a dictionary, setting jobStore to None
:return: dict
"""
parser = Job.Runner.getDefaultArgumentParser()
namespace = parser.parse_args(['']) # empty jobStore attribute
namespace.jobStore = None # jobStore attribute will be updated per-batch
return namespace
def get_toil_defaults(self):
"""
Extracts the default toil options as a dictionary, setting jobStore to None
:return: dict
"""
parser = Job.Runner.getDefaultArgumentParser()
namespace = parser.parse_args(['']) # empty jobStore attribute
namespace.jobStore = None # jobStore attribute will be updated per-batch
return namespace
run_cath_hierarchy(job, cathcode, process_superfamily, cathFileStoreID,
update_features=update_features, force=force)
else:
superfamilies = domains_to_run["cathcode"].drop_duplicates().str.replace(".", "/")
RealtimeLogger.info("Superfamilies to run: {}".format(len(superfamilies)))
map_job(job, process_superfamily, superfamilies, cathFileStoreID,
update_features=update_features, force=force)
#Build Interactome
#job.addChildJobFn()
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
parser.add_argument(
"-c", "--cathcode",
nargs='+',
default=None)
parser.add_argument(
"--features",
nargs="+",
default=None
)
parser.add_argument(
"--force",
action="store_true",
default=False)
options = parser.parse_args()
options.logLevel = "DEBUG"
#options.clean = "always"
def get_toil_defaults(self):
"""
Extracts the default toil options as a dictionary, setting jobStore to None
:return: dict
"""
parser = Job.Runner.getDefaultArgumentParser()
namespace = parser.parse_args(['']) # empty jobStore attribute
namespace.jobStore = None # jobStore attribute will be updated per-batch
return namespace
# sfams = pd.read_hdf(pdb_file, "Superfamilies", columns=
# ["sfam_id"]).drop_duplicates().dropna()["sfam_id"].sort_values()
sfams = [299845.0]
map_job(job, calculate_features_for_sfam, sfams)
#os.remove(pdb_file)
#job.addChildJobFn(calculate_features, "301320/yc/1YCS_A_sdi225433_d0.pdb")
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
options = parser.parse_args()
options.logLevel = "DEBUG"
options.clean = "always"
options.targetTime = 1
job = Job.wrapJobFn(start_toil)
with Toil(options) as toil:
toil.start(job)
if split_groups:
pdb = pdb.assign(group=pdb["pdb"].str[:3])
pdb_groups = pdb.groupby("group")["pdb"].apply(list)
map_job(job, process_pdb_group, pdb_groups, cathFileStoreID, further_parallelize)
else:
map_job(job, process_pdb, pdb["pdb"], cathFileStoreID)
#map_job(job, process_pdb, ["4ht5"], cathFileStoreID)
#job.addFollowOnJobFn(run_cath_hierarchy, merge_cath, None, cathFileStoreID)
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
parser.add_argument("--force", default=False, action="store_true")
options = parser.parse_args()
options.logLevel = "DEBUG"
options.clean = "always"
options.targetTime = 1
if not os.path.isfile("cath.h5"):
eppic_interfaces.read_input_file("cath-domain-description-file-small.h5", "cath.h5")
with Toil(options) as workflow:
cathFileURL = 'file://' + os.path.abspath("cath.h5")
cathFileID = workflow.importFile(cathFileURL)
workflow.start(Job.wrapJobFn(start_toil, cathFileID, options.force))
# sfams = pd.read_hdf(pdb_file, "Superfamilies", columns=
# ["sfam_id"]).drop_duplicates().dropna()["sfam_id"].sort_values()
sfams = [299845.0]
map_job(job, calculate_features_for_sfam, sfams)
#os.remove(pdb_file)
#job.addChildJobFn(calculate_features, "301320/yc/1YCS_A_sdi225433_d0.pdb")
if __name__ == "__main__":
from toil.common import Toil
from toil.job import Job
parser = Job.Runner.getDefaultArgumentParser()
options = parser.parse_args()
options.logLevel = "DEBUG"
options.clean = "always"
options.targetTime = 1
job = Job.wrapJobFn(start_toil)
with Toil(options) as toil:
toil.start(job)