mpp.hpp

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/*
Copyright (c) 2015-2019, Florian Sittel (www.lettis.net) and Daniel Nagel
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
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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*/
#pragma once

#include <vector>
#include <map>
#include <set>
#include <stdexcept>
#include <string>

#include <boost/program_options.hpp>
#include <boost/numeric/ublas/matrix_sparse.hpp>
#include <boost/numeric/ublas/io.hpp>

#include "tools.hpp"
namespace Clustering {
  namespace MPP {
    using SparseMatrixF = boost::numeric::ublas::mapped_matrix<float>;
    using Neighborhood = Clustering::Tools::Neighborhood;
    SparseMatrixF
    read_transition_probabilities(std::string fname);
    SparseMatrixF
    transition_counts(std::vector<std::size_t> trajectory
                    , std::vector<std::size_t> concat_limits
                    , std::size_t n_lag_steps
                    , std::size_t i_max = 0);
    SparseMatrixF
    weighted_transition_counts(std::vector<std::size_t> trajectory
                             , std::vector<std::size_t> concat_limits
                             , std::size_t n_lag_steps);
    SparseMatrixF
    row_normalized_transition_probabilities(SparseMatrixF count_matrix
                                          , std::set<std::size_t> microstate_names);
    SparseMatrixF
    updated_transition_probabilities(SparseMatrixF transition_matrix
                                   , std::map<std::size_t, std::size_t> sinks
                                   , std::map<std::size_t, std::size_t> pops);
    std::map<std::size_t, std::size_t>
    single_step_future_state(SparseMatrixF transition_matrix,
                             std::set<std::size_t> cluster_names,
                             float q_min,
                             std::map<std::size_t, float> min_free_energy);
    std::map<std::size_t, std::vector<std::size_t>>
    most_probable_path(std::map<std::size_t, std::size_t> future_state, std::set<std::size_t> cluster_names);
    std::map<std::size_t, std::size_t>
    microstate_populations(std::vector<std::size_t> clusters, std::set<std::size_t> cluster_names);
    std::map<std::size_t, float>
    microstate_min_free_energy(const std::vector<std::size_t>& clustering,
                               const std::vector<float>& free_energy);
    std::map<std::size_t, std::size_t>
    path_sinks(std::vector<std::size_t> clusters,
               std::map<std::size_t, std::vector<std::size_t>> mpp,
               SparseMatrixF transition_matrix,
               std::set<std::size_t> cluster_names,
               float q_min,
               std::vector<float> free_energy);
    std::vector<std::size_t>
    lumped_trajectory(std::vector<std::size_t> trajectory,
                      std::map<std::size_t, std::size_t> sinks);
    std::tuple<std::vector<std::size_t>
             , std::map<std::size_t, std::size_t>
             , SparseMatrixF>
    fixed_metastability_clustering(std::vector<std::size_t> initial_trajectory,
                                   SparseMatrixF trans_prob,
                                   float q_min,
                                   std::vector<float> free_energy);
    void
    main(boost::program_options::variables_map args);
  } // end namespace Clustering::MPP
} // end namespace Clustering