示例#1
0
    std::unique_ptr<ImageIO::Base> MRtrix::create (Header& H) const
    {
      File::OFStream out (H.name(), std::ios::out | std::ios::binary);

      out << "mrtrix image\n";

      write_mrtrix_header (H, out);

      bool single_file = Path::has_suffix (H.name(), ".mif");

      int64_t offset = 0;
      out << "file: ";
      if (single_file) {
        offset = out.tellp() + int64_t(18);
        offset += ((4 - (offset % 4)) % 4);
        out << ". " << offset << "\nEND\n";
      }
      else out << Path::basename (H.name().substr (0, H.name().size()-4) + ".dat") << "\n";

      out.close();

      std::unique_ptr<ImageIO::Base> io_handler (new ImageIO::Default (H));
      if (single_file) {
        File::resize (H.name(), offset + footprint(H));
        io_handler->files.push_back (File::Entry (H.name(), offset));
      }
      else {
        std::string data_file (H.name().substr (0, H.name().size()-4) + ".dat");
        File::create (data_file, footprint(H));
        io_handler->files.push_back (File::Entry (data_file));
      }

      return io_handler;
    }
示例#2
0
void run ()
{

  const bool weights_provided = get_options ("tck_weights_in").size();

  float step_size = NAN;
  size_t count = 0, header_count = 0;
  float min_length = std::numeric_limits<float>::infinity();
  float max_length = 0.0f;
  double sum_lengths = 0.0, sum_weights = 0.0;
  std::vector<double> histogram;
  std::vector<LW> all_lengths;
  all_lengths.reserve (header_count);

  {
    Tractography::Properties properties;
    Tractography::Reader<float> reader (argument[0], properties);

    if (properties.find ("count") != properties.end())
      header_count = to<size_t> (properties["count"]);

    if (properties.find ("output_step_size") != properties.end())
      step_size = to<float> (properties["output_step_size"]);
    else
      step_size = to<float> (properties["step_size"]);
    if (!std::isfinite (step_size) || !step_size) {
      WARN ("Streamline step size undefined in header");
      if (get_options ("histogram").size())
        WARN ("Histogram will be henerated using a 1mm interval");
    }

    std::unique_ptr<File::OFStream> dump;
    Options opt = get_options ("dump");
    if (opt.size())
      dump.reset (new File::OFStream (std::string(opt[0][0]), std::ios_base::out | std::ios_base::trunc));

    ProgressBar progress ("Reading track file... ", header_count);
    Tractography::Streamline<> tck;
    while (reader (tck)) {
      ++count;
      const float length = std::isfinite (step_size) ? tck.calc_length (step_size) : tck.calc_length();
      min_length = std::min (min_length, length);
      max_length = std::max (max_length, length);
      sum_lengths += tck.weight * length;
      sum_weights += tck.weight;
      all_lengths.push_back (LW (length, tck.weight));
      const size_t index = std::isfinite (step_size) ? std::round (length / step_size) : std::round (length);
      while (histogram.size() <= index)
        histogram.push_back (0.0);
      histogram[index] += tck.weight;
      if (dump)
        (*dump) << length << "\n";
      ++progress;
    }
  }

  if (histogram.front())
    WARN ("read " + str(histogram.front()) + " zero-length tracks");
  if (count != header_count)
    WARN ("expected " + str(header_count) + " tracks according to header; read " + str(count));

  const float mean_length = sum_lengths / sum_weights;

  float median_length = 0.0f;
  if (weights_provided) {
    // Perform a weighted median calculation
    std::sort (all_lengths.begin(), all_lengths.end());
    size_t median_index = 0;
    double sum = sum_weights - all_lengths[0].get_weight();
    while (sum > 0.5 * sum_weights) { sum -= all_lengths[++median_index].get_weight(); }
    median_length = all_lengths[median_index].get_length();
  } else {
    median_length = Math::median (all_lengths).get_length();
  }

  double stdev = 0.0;
  for (std::vector<LW>::const_iterator i = all_lengths.begin(); i != all_lengths.end(); ++i)
    stdev += i->get_weight() * Math::pow2 (i->get_length() - mean_length);
  stdev = std::sqrt (stdev / (((count - 1) / float(count)) * sum_weights));

  const size_t width = 12;

  std::cout << " " << std::setw(width) << std::right << "mean"
            << " " << std::setw(width) << std::right << "median"
            << " " << std::setw(width) << std::right << "std. dev."
            << " " << std::setw(width) << std::right << "min"
            << " " << std::setw(width) << std::right << "max"
            << " " << std::setw(width) << std::right << "count\n";

  std::cout << " " << std::setw(width) << std::right << (mean_length)
            << " " << std::setw(width) << std::right << (median_length)
            << " " << std::setw(width) << std::right << (stdev)
            << " " << std::setw(width) << std::right << (min_length)
            << " " << std::setw(width) << std::right << (max_length)
            << " " << std::setw(width) << std::right << (count) << "\n";

  Options opt = get_options ("histogram");
  if (opt.size()) {
    File::OFStream out (opt[0][0], std::ios_base::out | std::ios_base::trunc);
    if (!std::isfinite (step_size))
      step_size = 1.0f;
    if (weights_provided) {
      out << "Length,Sum_weights\n";
      for (size_t i = 0; i != histogram.size(); ++i)
        out << str(i * step_size) << "," << str(histogram[i]) << "\n";
    } else {
      out << "Length,Count\n";
      for (size_t i = 0; i != histogram.size(); ++i)
        out << str(i * step_size) << "," << str<size_t>(histogram[i]) << "\n";
    }
    out << "\n";
    out.close();
  }

}