Scoring.h

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// Copyright (c) 2002-2023, The OpenMS Team -- EKU Tuebingen, ETH Zurich, and FU Berlin
// SPDX-License-Identifier: BSD-3-Clause
//
// --------------------------------------------------------------------------
// $Maintainer: Hannes Roest$
// $Authors: Hannes Roest$
// --------------------------------------------------------------------------
 
#pragma once
 
#include <numeric>
#include <map>
#include <vector>
 
#include <OpenMS/OPENSWATHALGO/OpenSwathAlgoConfig.h>
 
namespace OpenSwath
{
 
  namespace Scoring
  {
    typedef std::pair<unsigned int, unsigned int> pos2D;
    struct pair_hash 
    {
      template <class T1, class T2>
      std::size_t operator () (const std::pair<T1,T2> &p) const {
        auto h1 = std::hash<T1>{}(p.first);
        auto h2 = std::hash<T2>{}(p.second);
        return h1 ^ h2;  
      }
    };
    
    typedef std::pair<int, double> XCorrEntry;
    struct XCorrArrayType 
    {
public:
    std::vector<XCorrEntry> data;
 
    // Access functions
    typedef std::vector<XCorrEntry>::iterator iterator;
    typedef std::vector<XCorrEntry>::const_iterator const_iterator;
 
    iterator begin() {return data.begin();}
    const_iterator begin() const {return data.begin();}
    iterator end() {return data.end();}
    const_iterator end() const {return data.end();}
    };
 
    OPENSWATHALGO_DLLAPI double NormalizedManhattanDist(double x[], double y[], int n);
 
    OPENSWATHALGO_DLLAPI double RootMeanSquareDeviation(double x[], double y[], int n);
 
    OPENSWATHALGO_DLLAPI double SpectralAngle(double x[], double y[], int n);
 
    OPENSWATHALGO_DLLAPI XCorrArrayType calcxcorr_legacy_mquest_(std::vector<double>& data1,
                                                  std::vector<double>& data2, bool normalize);
 
    OPENSWATHALGO_DLLAPI XCorrArrayType normalizedCrossCorrelation(std::vector<double>& data1,
                                                                   std::vector<double>& data2, const int maxdelay, const int lag);
 
    OPENSWATHALGO_DLLAPI XCorrArrayType normalizedCrossCorrelationPost(std::vector<double>& normalized_data1,
                                                                       std::vector<double>& normalized_data2, const int maxdelay, const int lag);                                                                   
 
    OPENSWATHALGO_DLLAPI XCorrArrayType calculateCrossCorrelation(const std::vector<double>& data1,
                                                                  const std::vector<double>& data2, const int maxdelay, const int lag);
 
    OPENSWATHALGO_DLLAPI XCorrArrayType::const_iterator xcorrArrayGetMaxPeak(const XCorrArrayType & array);
 
    OPENSWATHALGO_DLLAPI void standardize_data(std::vector<double>& data);
 
    OPENSWATHALGO_DLLAPI void normalize_sum(double x[], unsigned int n);
 
    // Compute rank of vector elements, append it to @p ranks and return the highest rank
    OPENSWATHALGO_DLLAPI unsigned int computeAndAppendRank(const std::vector<double>& v, std::vector<unsigned int>& ranks);
 
    // Compute rank of vector elements and its highest rank for each row in a 2D array
    OPENSWATHALGO_DLLAPI std::vector<unsigned int> computeRankVector(const std::vector<std::vector<double>>& intensity, std::vector<std::vector<unsigned int>>& ranks);
 
    // Estimate mutual information between two vectors of ranks
    OPENSWATHALGO_DLLAPI double rankedMutualInformation(std::vector<unsigned int>& ranked_data1, std::vector<unsigned int>& ranked_data2, const unsigned int max_rank1, const unsigned int max_rank2);
 
 
  }
}