coring.cpp

/*
Copyright (c) 2015, Florian Sittel (www.lettis.net)
All rights reserved.

Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice,
   this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT
SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT
OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/

#include "coring.hpp"

#include "logger.hpp"
#include "tools.hpp"

#include <iostream>
#include <fstream>
#include <algorithm>
#include <vector>

#include <omp.h>

namespace Clustering {
namespace Coring {
  WTDMap
  compute_wtd(std::list<std::size_t> streaks) {
    WTDMap wtd;
    if (streaks.size() > 0) {
      streaks.sort(std::greater<std::size_t>());
      std::size_t max_streak = streaks.front();
      for (std::size_t i=0; i <= max_streak; ++i) {
        float n_steps = 0.0f;
        for (auto s: streaks) {
          if (i > s) {
            break;
          }
          n_steps += 1.0f;
        }
        wtd[i] = n_steps / ((float) streaks.size());
      }
    }
    return wtd;
  }

  void
  main(boost::program_options::variables_map args) {
    using namespace Clustering::Tools;
    namespace b_po = boost::program_options;
    // load states
    std::vector<std::size_t> states = Clustering::Tools::read_clustered_trajectory(args["states"].as<std::string>());
    std::set<std::size_t> state_names(states.begin(), states.end());
    std::size_t n_frames = states.size();
    if (args.count("output") || args.count("distribution") || args.count("cores")) {
      // load concatenation limits to treat concatenated trajectories correctly
      // when performing dynamical corrections
      std::vector<std::size_t> concat_limits;
      if (args.count("concat-limits")) {
        concat_limits = Clustering::Tools::read_single_column<std::size_t>(args["concat-limits"].as<std::string>());
      } else if (args.count("concat-nframes")) {
        std::size_t n_frames_per_subtraj = args["concat-nframes"].as<std::size_t>();
        for (std::size_t i=n_frames_per_subtraj; i <= n_frames; i += n_frames_per_subtraj) {
          concat_limits.push_back(i);
        }
      } else {
        concat_limits = {n_frames};
      }
      // load window size information
      std::map<std::size_t, std::size_t> coring_windows;
      {
        std::ifstream ifs(args["windows"].as<std::string>());
        std::string buf1, buf2;
        std::size_t size_for_all = 1;
        while (ifs.good()) {
          ifs >> buf1;
          ifs >> buf2;
          if (ifs.good()) {
            if (buf1 == "*") {
              size_for_all = string_to_num<std::size_t>(buf2);
            } else {
              coring_windows[string_to_num<std::size_t>(buf1)] = string_to_num<std::size_t>(buf2);
            }
          }
        }
        // fill remaining, not explicitly defined states with common window size
        for (std::size_t name: state_names) {
          if ( ! coring_windows.count(name)){
            coring_windows[name] = size_for_all;
          }
        }
      }
      // core trajectory
      std::vector<std::size_t> cored_traj(n_frames);
      std::size_t current_core = states[0];
      std::vector<long> cores(n_frames);
      // honour concatenation limits, i.e. treat every concatenated trajectory-part on its own
      std::size_t last_limit = 0;
      for (std::size_t next_limit: concat_limits) {
        for (std::size_t i=last_limit; i < next_limit; ++i) {
          // coring window
          std::size_t w = std::min(i+coring_windows[states[i]], next_limit);
          bool is_in_core = true;
          for (std::size_t j=i+1; j < w; ++j) {
            if (states[j] != states[i]) {
              is_in_core = false;
              break;
            }
          }
          if (is_in_core) {
            current_core = states[i];
            cores[i] = current_core;
          } else {
            cores[i] = -1;
          }
          cored_traj[i] = current_core;
        }
        last_limit = next_limit;
      }
      // write cored trajectory to file
      if (args.count("output")) {
        Clustering::Tools::write_clustered_trajectory(args["output"].as<std::string>(), cored_traj);
      }
      // write core information to file
      if (args.count("cores")) {
        Clustering::Tools::write_single_column<long>(args["cores"].as<std::string>(), cores, false);
      }
      // compute/save escape time distributions
      if (args.count("distribution")) {
        std::map<std::size_t, std::list<std::size_t>> streaks;
        std::size_t current_state = cored_traj[0];
        long n_counts = 0;
        for (std::size_t state: cored_traj) {
          if (state == current_state) {
            ++n_counts;
          } else {
            streaks[current_state].push_back(n_counts);
            current_state = state;
            n_counts = 1;
          }
        }
        streaks[current_state].push_back(n_counts);

        std::map<std::size_t, WTDMap> etds;
        for (std::size_t state: state_names) {
          etds[state] = compute_wtd(streaks[state]);
        }
        // write WTDs to file
        for (auto state_etd: etds) {
          std::string fname = Clustering::Tools::stringprintf(args["distribution"].as<std::string>() + "_%d", state_etd.first);
          Clustering::Tools::write_map<std::size_t, float>(fname, state_etd.second);
        }
      }
    } else {
      std::cerr << "\n" << "error (coring): nothing to do! please define '--output', '--distribution' or both!" << "\n\n";
      exit(EXIT_FAILURE);
    }
  }
} // end namespace Coring
} // end namespace Clustering