c957b240a42675d49f9c2d9a65f2f548b60ba99b,src/pyscenic/scenic.py,,find_motifs,#Any#,85

Before Change

        else GeneSignature.from_gmt(args.module_fname.name, args.nomenclature)
    nomenclature = modules[0].nomenclature

    print("{} - Loading databases.".format(datetime.datetime.now()))
    def name(fname):
        return os.path.basename(fname).split(".")[0]
    dbs = [open(fname=fname, name=name(fname), nomenclature=nomenclature) for fname in args.database_fname]

    print("{} - Calculating regulomes.".format(datetime.datetime.now()))
    motif_annotations_fname = args.annotations_fname.name
    with ProgressBar() if args.mode == "dask_multiprocessing" else NoProgressBar():
        df = motifs(dbs, modules, motif_annotations_fname,
                   rank_threshold=args.rank_threshold,
                   auc_threshold=args.auc_threshold,
                   nes_threshold=args.nes_threshold,
                   client_or_address=args.mode,
                   module_chunksize=args.chunk_size,
                   num_workers=args.num_workers)

    print("{} - Writing results to file.".format(datetime.datetime.now()))
    df.to_csv(args.output)


def prune_targets(args):

After Change

def find_motifs(args):
    LOGGER.info("{} - Loading modules.")
    // Loading from YAML is extremely slow. Therefore this is a potential performance improvement.
    // Potential improvements are switching to JSON or to use a CLoader:
    // https://stackoverflow.com/questions/27743711/can-i-speedup-yaml
    modules = load_from_yaml(args.module_fname.name) if args.module_fname.name.lower().endswith(".gmt") \
        else GeneSignature.from_gmt(args.module_fname.name, args.nomenclature)
    nomenclature = modules[0].nomenclature

    LOGGER.info("{} - Loading databases.")
    def name(fname):
        return os.path.basename(fname).split(".")[0]
    dbs = [open(fname=fname, name=name(fname), nomenclature=nomenclature) for fname in args.database_fname]

    LOGGER.info("{} - Calculating regulomes.")
    motif_annotations_fname = args.annotations_fname.name
    with ProgressBar() if args.mode == "dask_multiprocessing" else NoProgressBar():
        df = find_features(dbs, modules, motif_annotations_fname,
                   rank_threshold=args.rank_threshold,
                   auc_threshold=args.auc_threshold,
                   nes_threshold=args.nes_threshold,
                   client_or_address=args.mode,
                   module_chunksize=args.chunk_size,
                   num_workers=args.num_workers)

    LOGGER.info("{} - Writing results to file.")
    df.to_csv(args.output)


def prune_targets(args):

Instances