void tdigest_accuracy_profile::run()

in cpp/src/tdigest_accuracy_profile_impl.hpp [32:76]

• 35 lines of code
• 6 McCabe index (conditional complexity)

void tdigest_accuracy_profile<T>::run() {
  const unsigned lg_min = 0;
  const unsigned lg_max = 23;
  const unsigned ppo = 8;
  const unsigned num_trials = 1000;
  const unsigned error_pct = 99;

  const uint16_t compression = 200;
  const std::vector<double> ranks = {0.01, 0.05, 0.5, 0.95, 0.99};

  std::vector<std::vector<double>> rank_errors(ranks.size(), std::vector<double>());

  std::vector<T> values(1ULL << lg_max, 0);

  std::cout << "N";
  for (const double rank: ranks) std::cout << "\terr at " << rank;
  std::cout << "\n";

  std::random_device rd;
  std::mt19937 gen(rd());
//  std::uniform_real_distribution<T> dist(0, 1.0);
  std::exponential_distribution<T> dist(1.5);

  const unsigned num_steps = count_points(lg_min, lg_max, ppo);
  unsigned stream_length = 1 << lg_min;
  for (unsigned i = 0; i < num_steps; ++i) {
    for (unsigned t = 0; t < num_trials; t++) {
      for (size_t j = 0; j < stream_length; ++j) values[j] = dist(gen);
      run_trial(values, stream_length, compression, ranks, rank_errors);
    }

    std::cout << stream_length;

    for (auto& errors: rank_errors) {
      std::sort(errors.begin(), errors.end());
      const size_t error_pct_index = num_trials * error_pct / 100;
      const double rank_error = errors[error_pct_index];
      std::cout << "\t" << rank_error * 100;
      errors.clear();
    }
    std::cout << "\n";

    stream_length = pwr_2_law_next(ppo, stream_length);
  }
}