ProcMatrix.cc

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// -*- C++ -*-
//
// Package:     MVAComputer
// Class  :     ProcMatrix
// 

// Implementation:
//     Variable processor to apply a matrix transformation to the input
//     variables. An n x m matrix applied to n input variables results in
//     m output variables.
//
// Author:      Christophe Saout
// Created:     Sat Apr 24 15:18 CEST 2007
//

#include <stdlib.h>

#include "PhysicsTools/MVAComputer/interface/VarProcessor.h"
#include "PhysicsTools/MVAComputer/interface/Calibration.h"

using namespace PhysicsTools;

namespace { // anonymous

class ProcMatrix : public VarProcessor {
    public:
    typedef VarProcessor::Registry::Registry<ProcMatrix,
                    Calibration::ProcMatrix> Registry;

    ProcMatrix(const char *name,
               const Calibration::ProcMatrix *calib,
               const MVAComputer *computer);
    virtual ~ProcMatrix() {}      

    virtual void configure(ConfIterator iter, unsigned int n) override;
    virtual void eval(ValueIterator iter, unsigned int n) const override;
    virtual std::vector<double> deriv(ValueIterator iter,
                                      unsigned int n) const override;

    private:
    class Matrix {
        public:
        inline Matrix(const Calibration::Matrix *calib) :
            rows(calib->rows), cols(calib->columns),
            coeffs(calib->elements) {}

        inline unsigned int getRows() const { return rows; }
        inline unsigned int getCols() const { return cols; }

        inline double operator () (unsigned int row,
                                   unsigned int col) const
        { return coeffs[row * cols + col]; }

        private:
        unsigned int        rows;
        unsigned int        cols;
        std::vector<double> coeffs;
    };

    Matrix  matrix;
};

static ProcMatrix::Registry registry("ProcMatrix");

ProcMatrix::ProcMatrix(const char *name,
                       const Calibration::ProcMatrix *calib,
                       const MVAComputer *computer) :
    VarProcessor(name, calib, computer),
    matrix(&calib->matrix)
{
}

void ProcMatrix::configure(ConfIterator iter, unsigned int n)
{
    if (n != matrix.getCols())
        return;

    for(unsigned int col = 0; col < matrix.getCols(); col++)
        iter++(Variable::FLAG_NONE);

    for(unsigned int row = 0; row < matrix.getRows(); row++)
        iter << Variable::FLAG_NONE;
}

void ProcMatrix::eval(ValueIterator iter, unsigned int n) const
{
    double *sums = (double*)alloca(matrix.getRows() * sizeof(double));
    for(unsigned int row = 0; row < matrix.getRows(); row++)
        sums[row] = 0.0;

    for(unsigned int col = 0; col < matrix.getCols(); col++) {
        double val = *iter++;
        for(unsigned int row = 0; row < matrix.getRows(); row++)
            sums[row] += matrix(row, col) * val;
    }

    for(unsigned int row = 0; row < matrix.getRows(); row++)
        iter(sums[row]);
}

std::vector<double> ProcMatrix::deriv(ValueIterator iter,
                                      unsigned int n) const
{
    std::vector<double> result;
    result.reserve(matrix.getRows() * matrix.getCols());

    for(unsigned int row = 0; row < matrix.getRows(); row++)
        for(unsigned int col = 0; col < matrix.getCols(); col++)
            result.push_back(matrix(row, col));

    return result;
}

} // anonymous namespace