/usr/include/OpenMS/ANALYSIS/PIP/LocalLinearMap.h is in libopenms-dev 1.11.1-5.
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// OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2013.
//
// This software is released under a three-clause BSD license:
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// notice, this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
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// For a full list of authors, refer to the file AUTHORS.
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// $Maintainer: Alexandra Scherbart $
// $Authors: $
// --------------------------------------------------------------------------
#ifndef OPENMS_ANALYSIS_PIP_LOCALLINEARMAP_H
#define OPENMS_ANALYSIS_PIP_LOCALLINEARMAP_H
#include <OpenMS/DATASTRUCTURES/Matrix.h>
namespace OpenMS
{
/**
@brief Trained Local Linear %Map (LLM) model for peak intensity prediction
This class offers a model for predictions of peptide peak heights
(referred to as intensities) by a Local Linear %Map (LLM) model and
is the basis of PeakIntensityPredictor.
A general introduction to the Peak Intensity Predictor (PIP)
can be found in the <A HREF="tutorial_pip.html">PIP Tutorial</A>.
The model trained needs two files for storing the position of the
codebook vectors and the linear mappings (codebooks.data, linearMapping.data)
This is the default model used by PeakIntensityPredictor.
*/
class OPENMS_DLLAPI LocalLinearMap
{
public:
/**
@brief Define parameters needed by the Local Linear %Map (LLM) model
Parameters xdim and ydim define the size of the two dimensional
grid structure. Parameter radius gives the width of the Gaussian
neighborhood function.
*/
struct OPENMS_DLLAPI LLMParam
{
UInt xdim; /**< size of first coordinate */
UInt ydim; /**< size of second coordinate */
DoubleReal radius; /**< width of Gaussian neighborhood function */
};
/// default constructor
LocalLinearMap();
/// destructor
virtual ~LocalLinearMap();
///return parameters of the LocalLinearMap model
const LLMParam & getLLMParam() const;
///return position of the codebook vectors (18-dim)
const Matrix<DoubleReal> & getCodebooks() const;
///return linear mappings of the codebooks
const Matrix<DoubleReal> & getMatrixA() const;
///return linear bias
const std::vector<DoubleReal> & getVectorWout() const;
///return coordinates of codebook vectors on the 2-d grid
const Matrix<UInt> & getCord() const;
///calculate and return normalized amino acid index variables from string representation of peptide
void normalizeVector(std::vector<DoubleReal> & aaIndexVariables);
///calculate neighborhood function based on distance of prototypes to winner prototype on two-dimensional grid structure and neighborhood width.
std::vector<DoubleReal> neigh(const Matrix<UInt> & cord, Size win, DoubleReal radius);
private:
LLMParam param_; ///<parameters of the model
Matrix<DoubleReal> code_; ///<codebook vectors
Matrix<DoubleReal> A_; ///<linear mappings
std::vector<DoubleReal> wout_; ///<linear bias
Matrix<UInt> cord_; ///<coordinates of codebooks on grid
/// needed to store prototype coordinates
Matrix<UInt> genCord_(Size xdim, Size ydim);
///calculate distance between two prototypes
DoubleReal dist_(const Matrix<UInt> & u, const Matrix<UInt> & v, Size a, Size b);
///Copy constructor not implemented => private
LocalLinearMap(LocalLinearMap & rhs);
///Assignment operator not implemented => private
LocalLinearMap & operator=(const LocalLinearMap & llm);
};
}
#endif
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