def molprobity_validation_multiple_targets(targetids=None, modeling_stage=None, loglevel=None): """ Calculate model quality using MolProbity ``oneline-analysis`` command. For each target, this function outputs a text file named ``models/[targetid]/validation_scores_sorted-[method]-[ensembler_stage]`` which contains a list of targetids sorted by validation score. This can be used by the subsequent ``package_models`` command to filter out models below a specified quality threshold. Typically, this should be run after models have been refined to the desired extent (e.g. after implicit or explicit MD refinement) More detailed validation results are written to the individual model directories. MPI-enabled. Parameters ---------- targetids: list of str or str modeling_stage: str {None|build_models|refine_implicit_md|refine_explicit_md} Default: None (automatically selects most advanced stage) """ set_loglevel(loglevel) if targetids is None: targetids = [target.id for target in get_targets()] elif type(targetids) is str: targetids = [targetids] for targetid in targetids: logger.info("Working on target {}".format(targetid)) molprobity_validation(targetid=targetid, ensembler_stage=modeling_stage, loglevel=loglevel)
def molprobity_validation_multiple_targets(targetids=None, modeling_stage=None, loglevel=None): """ Calculate model quality using MolProbity ``oneline-analysis`` command. For each target, this function outputs a text file named ``models/[targetid]/validation_scores_sorted-[method]-[ensembler_stage]`` which contains a list of targetids sorted by validation score. This can be used by the subsequent ``package_models`` command to filter out models below a specified quality threshold. Typically, this should be run after models have been refined to the desired extent (e.g. after implicit or explicit MD refinement) More detailed validation results are written to the individual model directories. MPI-enabled. Parameters ---------- targetids: list of str or str modeling_stage: str {None|build_models|refine_implicit_md|refine_explicit_md} Default: None (automatically selects most advanced stage) """ set_loglevel(loglevel) if targetids is None: targetids = [target.id for target in get_targets()] elif type(targetids) is str: targetids = [targetids] for targetid in targetids: logger.info('Working on target {}'.format(targetid)) molprobity_validation(targetid=targetid, ensembler_stage=modeling_stage, loglevel=loglevel)
def dispatch(args): if args['--targetsfile']: with open(args['--targetsfile'], 'r') as targetsfile: targets = [line.strip() for line in targetsfile.readlines() if line[0] != '#'] elif args['--targets']: targets = args['--targets'].split(',') else: targets = [target.id for target in get_targets()] if args['--modeling_stage'] == 'auto': modeling_stage = None elif args['--modeling_stage']: modeling_stage = args['--modeling_stage'] else: modeling_stage = None for target in targets: MkTraj(targetid=target, ensembler_stage=modeling_stage)