LinAlg.cpp

/**
 * \copyright
 * Copyright (c) 2012-2016, OpenGeoSys Community (http://www.opengeosys.org)
 *            Distributed under a Modified BSD License.
 *              See accompanying file LICENSE.txt or
 *              http://www.opengeosys.org/project/license
 *
 */

#include "LinAlg.h"

// TODO reorder LinAlg function signatures?

// Global PETScMatrix/PETScVector //////////////////////////////////////////
#ifdef USE_PETSC

#include "MathLib/LinAlg/PETSc/PETScVector.h"
#include "MathLib/LinAlg/PETSc/PETScMatrix.h"

namespace MathLib { namespace LinAlg
{

// Vector

void set(PETScVector& x, double const a)
{
    VecSet(x.getRawVector(), a);
}

void copy(PETScVector const& x, PETScVector& y)
{
    if (!y.getRawVector()) y.shallowCopy(x);
    VecCopy(x.getRawVector(), y.getRawVector());
}

void scale(PETScVector& x, double const a)
{
    VecScale(x.getRawVector(), a);
}

// y = a*y + X
void aypx(PETScVector& y, double const a, PETScVector const& x)
{
    // TODO check sizes
    VecAYPX(y.getRawVector(), a, x.getRawVector());
}

// y = a*x + y
void axpy(PETScVector& y, double const a, PETScVector const& x)
{
    // TODO check sizes
    VecAXPY(y.getRawVector(), a, x.getRawVector());
}

// y = a*x + b*y
void axpby(PETScVector& y, double const a, double const b, PETScVector const& x)
{
    // TODO check sizes
    VecAXPBY(y.getRawVector(), a, b, x.getRawVector());
}

// Explicit specialization
// Computes w = x/y componentwise.
template<>
void componentwiseDivide(PETScVector& w,
                         PETScVector const& x, PETScVector const& y)
{
    VecPointwiseDivide(w.getRawVector(), x.getRawVector(), y.getRawVector());
}

// Explicit specialization
// Computes the Manhattan norm of x
template<>
double norm1(PETScVector const& x)
{
    PetscScalar norm = 0.;
    VecNorm(x.getRawVector(), NORM_1, &norm);
    return norm;
}

// Explicit specialization
// Computes the Euclidean norm of x
template<>
double norm2(PETScVector const& x)
{
    PetscScalar norm = 0.;
    VecNorm(x.getRawVector(), NORM_2, &norm);
    return norm;
}

// Explicit specialization
// Computes the Maximum norm of x
template<>
double normMax(PETScVector const& x)
{
    PetscScalar norm = 0.;
    VecNorm(x.getRawVector(), NORM_INFINITY, &norm);
    return norm;
}


// Matrix

void copy(PETScMatrix const& A, PETScMatrix& B)
{
    B = A;
}

// A = a*A
void scale(PETScMatrix& A, double const a)
{
    MatScale(A.getRawMatrix(), a);
}

// Y = a*Y + X
void aypx(PETScMatrix& Y, double const a, PETScMatrix const& X)
{
    // TODO check sizes
    // TODO sparsity pattern, currently they are assumed to be different (slow)
    MatAYPX(Y.getRawMatrix(), a, X.getRawMatrix(),
            DIFFERENT_NONZERO_PATTERN);
}

// Y = a*X + Y
void axpy(PETScMatrix& Y, double const a, PETScMatrix const& X)
{
    // TODO check sizes
    // TODO sparsity pattern, currently they are assumed to be different (slow)
    MatAXPY(Y.getRawMatrix(), a, X.getRawMatrix(),
            DIFFERENT_NONZERO_PATTERN);
}


// Matrix and Vector

// v3 = A*v1 + v2
void matMult(PETScMatrix const& A, PETScVector const& x, PETScVector& y)
{
    // TODO check sizes
    assert(&x != &y);
    if (!y.getRawVector()) y.shallowCopy(x);
    MatMult(A.getRawMatrix(), x.getRawVector(), y.getRawVector());
}

// v3 = A*v1 + v2
void matMultAdd(PETScMatrix const& A, PETScVector const& v1,
                       PETScVector const& v2, PETScVector& v3)
{
    // TODO check sizes
    assert(&v1 != &v3);
    if (!v3.getRawVector()) v3.shallowCopy(v1);
    MatMultAdd(A.getRawMatrix(), v1.getRawVector(), v2.getRawVector(), v3.getRawVector());
}

void finalizeAssembly(PETScMatrix& A)
{
    A.finalizeAssembly(MAT_FINAL_ASSEMBLY);
}

void finalizeAssembly(PETScVector& x)
{
    x.finalizeAssembly();
}

}} // namespaces



// Sparse global EigenMatrix/EigenVector //////////////////////////////////////////
#elif defined(OGS_USE_EIGEN)

#include "MathLib/LinAlg/Eigen/EigenVector.h"
#include "MathLib/LinAlg/Eigen/EigenMatrix.h"

namespace MathLib { namespace LinAlg
{

// Vector

void set(EigenVector& x, double const a)
{
    x.getRawVector().setConstant(a);
}

void copy(EigenVector const& x, EigenVector& y)
{
    y = x;
}

void scale(EigenVector& x, double const a)
{
    x.getRawVector() *= a;
}

// y = a*y + X
void aypx(EigenVector& y, double const a, EigenVector const& x)
{
    // TODO: does that break anything?
    y.getRawVector() = a * y.getRawVector() + x.getRawVector();
}

// y = a*x + y
void axpy(EigenVector& y, double const a, EigenVector const& x)
{
    // TODO: does that break anything?
    y.getRawVector() += a * x.getRawVector();
}

// y = a*x + y
void axpby(EigenVector& y, double const a, double const b, EigenVector const& x)
{
    // TODO: does that break anything?
    y.getRawVector() = a * x.getRawVector() + b * y.getRawVector();
}

// Explicit specialization
// Computes w = x/y componentwise.
template<>
void componentwiseDivide(EigenVector& w,
                         EigenVector const& x, EigenVector const& y)
{
    w.getRawVector().noalias() =
            x.getRawVector().cwiseQuotient(y.getRawVector());
}

// Explicit specialization
// Computes the Manhattan norm of x
template<>
double norm1(EigenVector const& x)
{
    return x.getRawVector().lpNorm<1>();
}

// Explicit specialization
// Euclidean norm
template<>
double norm2(EigenVector const& x)
{
    return x.getRawVector().norm();
}

// Explicit specialization
// Computes the Maximum norm of x
template<>
double normMax(EigenVector const& x)
{
    return x.getRawVector().lpNorm<Eigen::Infinity>();
}


// Matrix

void copy(EigenMatrix const& A, EigenMatrix& B)
{
    B = A;
}

// A = a*A
void scale(EigenMatrix& A, double const a)
{
    // TODO: does that break anything?
    A.getRawMatrix() *= a;
}

// Y = a*Y + X
void aypx(EigenMatrix& Y, double const a, EigenMatrix const& X)
{
    // TODO: does that break anything?
    Y.getRawMatrix() = a*Y.getRawMatrix() + X.getRawMatrix();
}

// Y = a*X + Y
void axpy(EigenMatrix& Y, double const a, EigenMatrix const& X)
{
    // TODO: does that break anything?
    Y.getRawMatrix() = a*X.getRawMatrix() + Y.getRawMatrix();
}


// Matrix and Vector

// v3 = A*v1 + v2
void matMult(EigenMatrix const& A, EigenVector const& x, EigenVector& y)
{
    assert(&x != &y);
    y.getRawVector() = A.getRawMatrix() * x.getRawVector();
}

// v3 = A*v1 + v2
void matMultAdd(EigenMatrix const& A, EigenVector const& v1, EigenVector const& v2, EigenVector& v3)
{
    assert(&v1 != &v3);
    // TODO: does that break anything?
    v3.getRawVector() = v2.getRawVector() + A.getRawMatrix()*v1.getRawVector();
}

void finalizeAssembly(EigenMatrix& x)
{
    x.getRawMatrix().makeCompressed();
}

} // namespace LinAlg

} // namespace MathLib

#endif