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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def sample_callable_bed(bam_file, ref_file, data):
 """Retrieve callable regions for a sample subset by defined analysis regions. """

    from bcbio.heterogeneity import chromhacks
    CovInfo = collections.namedtuple("CovInfo", "callable, raw_callable, depth_files")
    noalt_calling = "noalt_calling" in dd.get_tools_on(data) or "altcontigs" in dd.get_exclude_regions(data)
    def callable_chrom_filter(r):
        """Filter to callable region, potentially limiting by chromosomes.
        """
        return r.name == "CALLABLE" and (not noalt_calling or chromhacks.is_nonalt(r.chrom))
    out_file = "%s-callable_sample.bed" % os.path.splitext(bam_file)[0]
    with shared.bedtools_tmpdir(data):
        sv_bed = regions.get_sv_bed(data)
        callable_bed, depth_files = coverage.calculate(bam_file, data, sv_bed)
        input_regions_bed = dd.get_variant_regions(data)
        if not utils.file_uptodate(out_file, callable_bed):
            with file_transaction(data, out_file) as tx_out_file:
                callable_regions = pybedtools.BedTool(callable_bed)
                filter_regions = callable_regions.filter(callable_chrom_filter)
                if input_regions_bed:
                    if not utils.file_uptodate(out_file, input_regions_bed):
                        input_regions = pybedtools.BedTool(input_regions_bed)
                        filter_regions.intersect(input_regions, nonamecheck=True).saveas(tx_out_file)
                else:
                    filter_regions.saveas(tx_out_file)
    return CovInfo(out_file, callable_bed, depth_files)