code: def freq_summary(val_file, call_file, truth_file, target_name):
      
      out_file = "%s-freqs.csv" % utils.splitext_plus(val_file)[0]
      truth_freqs = _read_truth_freqs(truth_file)
      call_freqs = _read_call_freqs(call_file, target_name)
      with VariantFile(val_file) as val_in:
          with open(out_file, "w") as out_handle:
              writer = csv.writer(out_handle)
              writer.writerow(["vtype", "valclass", "freq"])
              for rec in val_in:
                  call_type = _classify_rec(rec)
                  val_type = _get_validation_status(rec)
                  key = _get_key(rec)
                  freq = truth_freqs.get(key, call_freqs.get(key, 0.0))
                  writer.writerow([call_type, val_type, freq])
      return out_file
docs: Summarize true and false positive calls by variant type and frequency.
  
      Resolve differences in true/false calls based on output from hap.py:
      https://github.com/sequencing/hap.py