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Scoring.h
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31 // $Maintainer: Hannes Roest$
32 // $Authors: Hannes Roest$
33 // --------------------------------------------------------------------------
34
35 #pragma once
36
37 #include <numeric>
38 #include <map>
39 #include <vector>
40
41 #include <OpenMS/OPENSWATHALGO/OpenSwathAlgoConfig.h>
42 #include <boost/lambda/casts.hpp>
43 #include <boost/lambda/lambda.hpp>
44
45 namespace OpenSwath
46 {
47
53 namespace Scoring
54 {
59 typedef std::pair<int, double> XCorrEntry;
61 struct XCorrArrayType
62 {
63 public:
64 std::vector<XCorrEntry> data;
65
66 // Access functions
67 typedef std::vector<XCorrEntry>::iterator iterator;
68 typedef std::vector<XCorrEntry>::const_iterator const_iterator;
69
70 iterator begin() {return data.begin();}
71 const_iterator begin() const {return data.begin();}
72 iterator end() {return data.end();}
73 const_iterator end() const {return data.end();}
74 };
76
90 OPENSWATHALGO_DLLAPI double NormalizedManhattanDist(double x[], double y[], int n);
91
100 OPENSWATHALGO_DLLAPI double RootMeanSquareDeviation(double x[], double y[], int n);
101
110 OPENSWATHALGO_DLLAPI double SpectralAngle(double x[], double y[], int n);
111
114 OPENSWATHALGO_DLLAPI XCorrArrayType calcxcorr_legacy_mquest_(std::vector<double>& data1,
115 std::vector<double>& data2, bool normalize);
116
119 OPENSWATHALGO_DLLAPI XCorrArrayType normalizedCrossCorrelation(std::vector<double>& data1,
120 std::vector<double>& data2, const int& maxdelay, const int& lag);
121
123 OPENSWATHALGO_DLLAPI XCorrArrayType calculateCrossCorrelation(const std::vector<double>& data1,
124 const std::vector<double>& data2, const int& maxdelay, const int& lag);
125
127 OPENSWATHALGO_DLLAPI XCorrArrayType::const_iterator xcorrArrayGetMaxPeak(const XCorrArrayType & array);
128
130 OPENSWATHALGO_DLLAPI void standardize_data(std::vector<double>& data);
131
133 OPENSWATHALGO_DLLAPI void normalize_sum(double x[], unsigned int n);
134
135 // Compute rank of vector elements
136 OPENSWATHALGO_DLLAPI std::vector<unsigned int> computeRank(const std::vector<double>& w);
137
138 // Estimate rank-transformed mutual information between two vectors of data points
139 OPENSWATHALGO_DLLAPI double rankedMutualInformation(std::vector<double>& data1, std::vector<double>& data2);
140
142
143 }
144 }
145
OpenSwath::Scoring::calculateCrossCorrelation
OPENSWATHALGO_DLLAPI XCorrArrayType calculateCrossCorrelation(const std::vector< double > &data1, const std::vector< double > &data2, const int &maxdelay, const int &lag)
Calculate crosscorrelation on std::vector data without normalization.
OpenSwath::Scoring::rankedMutualInformation
OPENSWATHALGO_DLLAPI double rankedMutualInformation(std::vector< double > &data1, std::vector< double > &data2)
OpenSwath::Scoring::xcorrArrayGetMaxPeak
OPENSWATHALGO_DLLAPI XCorrArrayType::const_iterator xcorrArrayGetMaxPeak(const XCorrArrayType &array)
Find best peak in an cross-correlation (highest apex)
OpenSwath
Definition: MRMScoring.h:49
OpenSwath::Scoring::XCorrArrayType::begin
const_iterator begin() const
Definition: Scoring.h:71
OpenSwath::Scoring::XCorrArrayType::iterator
std::vector< XCorrEntry >::iterator iterator
Definition: Scoring.h:67
OpenSwath::Scoring::XCorrArrayType::end
const_iterator end() const
Definition: Scoring.h:73
OpenSwath::Scoring::SpectralAngle
OPENSWATHALGO_DLLAPI double SpectralAngle(double x[], double y[], int n)
Calculate the Spectral angle (acosine of the normalized dotproduct)
OpenSwath::Scoring::calcxcorr_legacy_mquest_
OPENSWATHALGO_DLLAPI XCorrArrayType calcxcorr_legacy_mquest_(std::vector< double > &data1, std::vector< double > &data2, bool normalize)
OpenSwath::Scoring::NormalizedManhattanDist
OPENSWATHALGO_DLLAPI double NormalizedManhattanDist(double x[], double y[], int n)
Calculate the normalized Manhattan distance between two arrays.
OpenSwath::Scoring::XCorrEntry
std::pair< int, double > XCorrEntry
Cross Correlation array contains (lag,correlation) pairs.
Definition: Scoring.h:60
OpenSwath::Scoring::standardize_data
OPENSWATHALGO_DLLAPI void standardize_data(std::vector< double > &data)
Standardize a vector (subtract mean, divide by standard deviation)
OpenSwath::normalize
OPENSWATHALGO_DLLAPI void normalize(const std::vector< double > &intensities, double normalization_factor, std::vector< double > &normalized_intensities)
Normalize intensities in vector by normalization_factor.
OpenSwath::Scoring::XCorrArrayType::const_iterator
std::vector< XCorrEntry >::const_iterator const_iterator
Definition: Scoring.h:68
OpenSwath::Scoring::XCorrArrayType::end
iterator end()
Definition: Scoring.h:72
OpenSwath::Scoring::XCorrArrayType::data
std::vector< XCorrEntry > data
Definition: Scoring.h:64
OpenSwath::Scoring::XCorrArrayType::begin
iterator begin()
Definition: Scoring.h:70
OpenSwath::Scoring::XCorrArrayType
Definition: Scoring.h:61
OpenSwath::Scoring::normalizedCrossCorrelation
OPENSWATHALGO_DLLAPI XCorrArrayType normalizedCrossCorrelation(std::vector< double > &data1, std::vector< double > &data2, const int &maxdelay, const int &lag)
OpenSwath::Scoring::RootMeanSquareDeviation
OPENSWATHALGO_DLLAPI double RootMeanSquareDeviation(double x[], double y[], int n)
Calculate the RMSD (root means square deviation)
OpenSwath::Scoring::normalize_sum
OPENSWATHALGO_DLLAPI void normalize_sum(double x[], unsigned int n)
divide each element of x by the sum of the vector
OpenSwath::Scoring::computeRank
OPENSWATHALGO_DLLAPI std::vector< unsigned int > computeRank(const std::vector< double > &w)