def _titancna_summary(call, data):
    """Summarize purity, ploidy and LOH for TitanCNA.
    """
    out = {}
    for svtype, coords in get_coords(data):
        cur_calls = {k: collections.defaultdict(int) for k in coords.keys()}
        with open(call["subclones"]) as in_handle:
            header = in_handle.readline().strip().split()
            for line in in_handle:
                val = dict(zip(header, line.strip().split()))
                start = int(val["Start_Position.bp."])
                end = int(val["End_Position.bp."])
                for region, cur_coords in coords.items():
                    if val["Chromosome"] == cur_coords[0] and are_overlapping((start, end), cur_coords[1:]):
                        cur_calls[region][_check_copy_number_changes(svtype, _to_cn(val["Copy_Number"]),
                                                                     _to_cn(val["MinorCN"]), data)] += 1
        out[svtype] = {r: _merge_cn_calls(c, svtype) for r, c in cur_calls.items()}

    with open(call["hetsummary"]) as in_handle:
        vals = dict(zip(in_handle.readline().strip().split("\t"), in_handle.readline().strip().split("\t")))
    out["purity"] = vals["purity"]
    out["ploidy"] = vals["ploidy"]
    return out
Summarize purity, ploidy and LOH for TitanCNA.