nanoraw_helper.py 文件源码

def get_base_means(raw_read_coverage, chrm_sizes):
    # ignore divide by zero errors that occur where there is no
    # coverage. Need to correct nan values after subtracting two sets of
    # coverage so leave as nan for now
    old_err_settings = np.seterr(all='ignore')
    # take the mean over all signal overlapping each base
    mean_base_signal = {}
    for chrm, strand in [(c, s) for c in chrm_sizes.keys()
                         for s in ('+', '-')]:
        if (chrm, strand) in raw_read_coverage:
            cs_base_means = get_reads_base_means(
                raw_read_coverage[(chrm, strand)], chrm_sizes[chrm],
                strand == '-')
        else:
            cs_base_means = np.empty(chrm_sizes[chrm])
            cs_base_means[:] = np.nan
        mean_base_signal[(chrm, strand)] = cs_base_means
    _ = np.seterr(**old_err_settings)

    return mean_base_signal