MRMFeatureSelector.h

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// --------------------------------------------------------------------------
//                   OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2021.
//
// This software is released under a three-clause BSD license:
//  * Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
//  * 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.
//  * Neither the name of any author or any participating institution
//    may be used to endorse or promote products derived from this software
//    without specific prior written permission.
// For a full list of authors, refer to the file AUTHORS.
// --------------------------------------------------------------------------
// 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
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// --------------------------------------------------------------------------
// $Maintainer: Douglas McCloskey, Pasquale Domenico Colaianni, Svetlana Kutuzova $
// $Authors: Douglas McCloskey, Pasquale Domenico Colaianni, Svetlana Kutuzova $
// --------------------------------------------------------------------------
 
#pragma once
 
#include <OpenMS/config.h> // OPENMS_DLLAPI
#include <OpenMS/DATASTRUCTURES/LPWrapper.h>
#include <OpenMS/DATASTRUCTURES/String.h>
#include <OpenMS/KERNEL/FeatureMap.h>
 
namespace OpenMS
{
 
  class OPENMS_DLLAPI MRMFeatureSelector
  {
public:
    MRMFeatureSelector() = default;
    virtual ~MRMFeatureSelector() = default;
 
    enum class VariableType
    {
      INTEGER = 1,
      CONTINUOUS
    };
 
    enum class LambdaScore
    {
      LINEAR = 1,
      INVERSE,
      LOG,
      INVERSE_LOG,
      INVERSE_LOG10
    };
 
    friend class MRMFeatureSelector_test;
 
    struct SelectorParameters
    {
      SelectorParameters() = default;
 
      SelectorParameters(
        Int nn,
        bool lw,
        bool stg,
        Int swl,
        Int ssl,
        MRMFeatureSelector::VariableType vt,
        double ot,
        std::map<String, MRMFeatureSelector::LambdaScore>& sw
      ) :
        nn_threshold(nn),
        locality_weight(lw),
        select_transition_group(stg),
        segment_window_length(swl),
        segment_step_length(ssl),
        variable_type(vt),
        optimal_threshold(ot),
        score_weights(sw) {}
 
      Int    nn_threshold            = 4; 
      bool   locality_weight         = false; 
      bool   select_transition_group = true; 
      Int    segment_window_length   = 8; 
      Int    segment_step_length     = 4; 
      MRMFeatureSelector::VariableType variable_type = MRMFeatureSelector::VariableType::CONTINUOUS; 
      double optimal_threshold       = 0.5; 
      std::map<String, MRMFeatureSelector::LambdaScore> score_weights; 
    };
 
    virtual void optimize(
      const std::vector<std::pair<double, String>>& time_to_name,
      const std::map<String, std::vector<Feature>>& feature_name_map,
      std::vector<String>& result,
      const SelectorParameters& parameters
    ) const = 0;
 
    void selectMRMFeature(
      const FeatureMap& features,
      FeatureMap& selected_filtered,
      const SelectorParameters& parameters
    ) const;
 
protected:
    Int addVariable_(
      LPWrapper& problem,
      const String& name,
      const bool bounded,
      const double obj,
      const VariableType variableType
    ) const;
 
    double computeScore_(const Feature& feature, const std::map<String, LambdaScore>& score_weights) const;
 
    void addConstraint_(
      LPWrapper& problem,
      std::vector<Int> indices,
      std::vector<double> values,
      const String& name,
      const double lb,
      const double ub,
      const LPWrapper::Type param
    ) const;
 
private:
    void constructTargTransList_(
      const FeatureMap& features,
      std::vector<std::pair<double, String>>& time_to_name,
      std::map<String, std::vector<Feature>>& feature_name_map,
      const bool select_transition_group
    ) const;
 
    double weightScore_(const double score, const LambdaScore lambda_score) const;
 
    String removeSpaces_(String str) const;
  };
 
  class OPENMS_DLLAPI MRMFeatureSelectorQMIP : public MRMFeatureSelector
  {
public:
    void optimize(
      const std::vector<std::pair<double, String>>& time_to_name,
      const std::map<String, std::vector<Feature>>& feature_name_map,
      std::vector<String>& result,
      const SelectorParameters& parameters
    ) const override;
  };
 
  class OPENMS_DLLAPI MRMFeatureSelectorScore : public MRMFeatureSelector
  {
public:
    void optimize(
      const std::vector<std::pair<double, String>>& time_to_name,
      const std::map<String, std::vector<Feature>>& feature_name_map,
      std::vector<String>& result,
      const SelectorParameters& parameters
    ) const override;
  };
 
  class MRMFeatureSelector_test : public MRMFeatureSelectorQMIP
  {
public:
    MRMFeatureSelector_test() = default;
    ~MRMFeatureSelector_test() override = default;
 
    void constructTargTransList_(
      const FeatureMap& features,
      std::vector<std::pair<double, String>>& time_to_name,
      std::map<String, std::vector<Feature>>& feature_name_map,
      const bool select_transition_group
    ) const
    {
      selector_.constructTargTransList_(features, time_to_name, feature_name_map, select_transition_group);
    }
 
    double weightScore_(const double score, const LambdaScore lambda_score) const
    {
      return selector_.weightScore_(score, lambda_score);
    }
 
    double computeScore_(const Feature& feature, const std::map<String, LambdaScore>& score_weights) const
    {
      return selector_.computeScore_(feature, score_weights);
    }
 
    String removeSpaces_(String str) const
    {
      return selector_.removeSpaces_(str);
    }
 
    MRMFeatureSelectorQMIP selector_;
  };
}