saveModelPath=saveModelNameTmp,
isLastStep=isLastStep)
if USE_2_STEPS:
outpathCodif = codifyStep(methodProtocol=conf.modelType + "_2",
feedbackPaths=predictOutPath_1)
saveModelNameTmp = None if saveModelName is None else saveModelName + "." + conf.modelType + "_2"
predictOutPath_2 = trainAndTest(outpathCodif,
resultsRoot,
methodProtocol=conf.modelType + "_2",
saveModelPath=saveModelNameTmp,
isLastStep=True)
if __name__ == "__main__":
parser = Configuration.getArgParser()
parser.modify_field("pdbsIndir",
help="Directory where training pdbs are located",
_type=Configuration.file_path)
parser.modify_field(
"wdir",
help="Directory where partial results and final results will be saved",
_type=Configuration.file_path)
parser.modify_field("tmp",
help="Temporary directory",
_type=Configuration.file_path)
parser.modify_field(
"ncpu",
help=
"Number of cpus for trainng. Each complex in a cross-validation fold is computed in an indepented worker. NCPU workers are computed in parallel"
})
f.close()
Parallel(n_jobs=ncpu,
backend="multiprocessing")(delayed(predictOneComplex)(**params)
for params in argsList)
if __name__ == "__main__":
from Config import Configuration
Configuration.update_config_dict(
project_config="./configFiles/cmdTool/configFile_pred.cfg",
other_dict=dict(force_protocol=None, wdir="./wdir"))
conf = Configuration()
parser = conf.getArgParser()
command_group = parser.add_mutually_exclusive_group()
command_group.add_argument(
"-i",
"--inputDir",
help=
"Directory where input files are located. They can be .pdb or .fasta, but they have to"
"follow Benchmark 5 naming convenctions PREFIX_[lr]_[bu].(pdb|fasta)",
type=Configuration.file_path,
default=None)
command_group.add_argument(
"-f",
"--inputFile",
help="A .csv file with PDB ids and chains to download",
type=argparse.FileType('r'),
