code: def plot_model_segments(seg_files, work_dir, data):
      
      from bcbio.heterogeneity import chromhacks
      out_file = os.path.join(work_dir, "%s.modeled.png" % dd.get_sample_name(data))
      if not utils.file_exists(out_file):
          with file_transaction(data, out_file) as tx_out_file:
              dict_file = utils.splitext_plus(dd.get_ref_file(data))[0] + ".dict"
              plot_dict = os.path.join(os.path.dirname(tx_out_file), os.path.basename(dict_file))
              with open(dict_file) as in_handle:
                  with open(plot_dict, "w") as out_handle:
                      for line in in_handle:
                          if line.startswith("@SQ"):
                              cur_chrom = [x.split(":", 1)[1].strip()
                                           for x in line.split("\t") if x.startswith("SN:")][0]
                              if chromhacks.is_autosomal_or_sex(cur_chrom):
                                  out_handle.write(line)
                          else:
                              out_handle.write(line)
              params = ["-T", "PlotModeledSegments",
                        "--denoised-copy-ratios", tz.get_in(["depth", "bins", "normalized"], data),
                        "--segments", seg_files["final_seg"],
                        "--allelic-counts", seg_files["tumor_hets"],
                        "--sequence-dictionary", plot_dict,
                        "--minimum-contig-length", "10",
                        "--output-prefix", dd.get_sample_name(data),
                        "-O", os.path.dirname(tx_out_file)]
              _run_with_memory_scaling(params, tx_out_file, data)
      return {"seg": out_file}
docs: Diagnostic plots of segmentation and inputs.