Select Git revision
OnelabServer.cpp
Forked from
gmsh / gmsh
Source project has a limited visibility.
fullMatrix.cpp 17.75 KiB
// Gmsh - Copyright (C) 1997-2016 C. Geuzaine, J.-F. Remacle
//
// See the LICENSE.txt file for license information. Please report all
// bugs and problems to the public mailing list <gmsh@geuz.org>.
#include <complex>
#include <string.h>
#include <algorithm>
#include "GmshConfig.h"
#include "fullMatrix.h"
#include "GmshMessage.h"
//#if defined(_MSC_VER)
//#define F77NAME(x) (x)
//#endif
#if !defined(F77NAME)
#define F77NAME(x) (x##_)
#endif
// Specialisation of fullVector/Matrix operations using BLAS and LAPACK
#if defined(HAVE_BLAS)
extern "C" {
void F77NAME(daxpy)(int *n, double *alpha, double *x, int *incx, double *y, int *incy);
void F77NAME(dcopy)(int *n, double *a, int *inca, double *b, int *incb);
void F77NAME(zcopy)(int *n, std::complex<double> *a, int *inca, std::complex<double> *b, int *incb);
void F77NAME(dgemm)(const char *transa, const char *transb, int *m, int *n, int *k,
double *alpha, double *a, int *lda,
double *b, int *ldb, double *beta,
double *c, int *ldc);
void F77NAME(zgemm)(const char *transa, const char *transb, int *m, int *n, int *k,
std::complex<double> *alpha, std::complex<double> *a, int *lda,
std::complex<double> *b, int *ldb, std::complex<double> *beta,
std::complex<double> *c, int *ldc);
void F77NAME(dgemv)(const char *trans, int *m, int *n,
double *alpha, double *a, int *lda,
double *x, int *incx, double *beta,
double *y, int *incy);
void F77NAME(zgemv)(const char *trans, int *m, int *n,
std::complex<double> *alpha, std::complex<double> *a, int *lda,
std::complex<double> *x, int *incx, std::complex<double> *beta,
std::complex<double> *y, int *incy);
void F77NAME(dscal)(int *n, double *alpha,double *x, int *incx);
void F77NAME(zscal)(int *n, std::complex<double> *alpha,std::complex<double> *x, int *incx);
}
template<>
void fullVector<double>::axpy(const fullVector<double> &x,double alpha)
{
int M = _r, INCX = 1, INCY = 1;
F77NAME(daxpy)(&M, &alpha, x._data,&INCX, _data, &INCY);
}
template<>
void fullVector<double>::setAll(const fullVector<double> &m)
{
int stride = 1;
F77NAME(dcopy)(&_r, m._data, &stride, _data, &stride);
}
template<>
void fullVector<std::complex<double> >::setAll(const fullVector<std::complex<double> > &m)
{
int stride = 1;
F77NAME(zcopy)(&_r, m._data, &stride, _data, &stride);
}
template<>
void fullMatrix<double>::setAll(const fullMatrix<double> &m)
{
if (_r != m._r || _c != m._c )
Msg::Fatal("fullMatrix size does not match");
int N = _r * _c;
int stride = 1;
F77NAME(dcopy)(&N, m._data, &stride, _data, &stride);
}
template<>
void fullMatrix<std::complex<double> >::setAll(const fullMatrix<std::complex<double > > &m)
{
if (_r != m._r || _c != m._c )
Msg::Fatal("fullMatrix size does not match");
int N = _r * _c;
int stride = 1;
F77NAME(zcopy)(&N, m._data, &stride, _data, &stride);
}
template<>
void fullMatrix<double>::scale(const double s)
{
int N = _r * _c;
int stride = 1;
double ss = s;
F77NAME(dscal)(&N, &ss,_data, &stride);
}
template<>
void fullMatrix<std::complex<double> >::scale(const double s)
{
int N = _r * _c;
int stride = 1;
std::complex<double> ss(s, 0.);
F77NAME(zscal)(&N, &ss,_data, &stride);
}
template<>
void fullMatrix<double>::mult(const fullMatrix<double> &b, fullMatrix<double> &c) const
{
int M = c.size1(), N = c.size2(), K = _c;
int LDA = _r, LDB = b.size1(), LDC = c.size1();
double alpha = 1., beta = 0.;
F77NAME(dgemm)("N", "N", &M, &N, &K, &alpha, _data, &LDA, b._data, &LDB,
&beta, c._data, &LDC);
}
template<>
void fullMatrix<std::complex<double> >::mult(const fullMatrix<std::complex<double> > &b,
fullMatrix<std::complex<double> > &c) const
{
int M = c.size1(), N = c.size2(), K = _c;
int LDA = _r, LDB = b.size1(), LDC = c.size1();
std::complex<double> alpha = 1., beta = 0.;
F77NAME(zgemm)("N", "N", &M, &N, &K, &alpha, _data, &LDA, b._data, &LDB,
&beta, c._data, &LDC);
}
template<>
void fullMatrix<double>::gemm(const fullMatrix<double> &a, const fullMatrix<double> &b,
double alpha, double beta, bool transposeA, bool transposeB)
{
int M = size1(), N = size2(), K = transposeA ? a.size1() : a.size2();
int LDA = a.size1(), LDB = b.size1(), LDC = size1();
F77NAME(dgemm)(transposeA ? "T" : "N", transposeB ? "T" :"N", &M, &N, &K, &alpha, a._data, &LDA, b._data, &LDB,
&beta, _data, &LDC);
}
template<>
void fullMatrix<std::complex<double> >::gemm(const fullMatrix<std::complex<double> > &a,
const fullMatrix<std::complex<double> > &b,
std::complex<double> alpha,
std::complex<double> beta,
bool transposeA,
bool transposeB)
{
int M = size1(), N = size2(), K = transposeA ? a.size1() : a.size2();
int LDA = a.size1(), LDB = b.size1(), LDC = size1();
F77NAME(zgemm)(transposeA ? "T" : "N", transposeB ? "T" :"N", &M, &N, &K, &alpha, a._data, &LDA, b._data, &LDB,
&beta, _data, &LDC);
}
template<>
void fullMatrix<double>::axpy(const fullMatrix<double> &x,double alpha)
{
int M = _r * _c, INCX = 1, INCY = 1;
F77NAME(daxpy)(&M, &alpha, x._data,&INCX, _data, &INCY);
}
template<>
void fullMatrix<double>::mult(const fullVector<double> &x, fullVector<double> &y) const
{
int M = _r, N = _c, LDA = _r, INCX = 1, INCY = 1;
double alpha = 1., beta = 0.;
F77NAME(dgemv)("N", &M, &N, &alpha, _data, &LDA, x._data, &INCX,
&beta, y._data, &INCY);
}
template<>
void fullMatrix<double>::multAddy(const fullVector<double> &x, fullVector<double> &y) const
{
int M = _r, N = _c, LDA = _r, INCX = 1, INCY = 1;
double alpha = 1., beta = 1.;
F77NAME(dgemv)("N", &M, &N, &alpha, _data, &LDA, x._data, &INCX,
&beta, y._data, &INCY);
}
template<>
void fullMatrix<std::complex<double> >::mult(const fullVector<std::complex<double> > &x,
fullVector<std::complex<double> > &y) const
{
int M = _r, N = _c, LDA = _r, INCX = 1, INCY = 1;
std::complex<double> alpha = 1., beta = 0.;
F77NAME(zgemv)("N", &M, &N, &alpha, _data, &LDA, x._data, &INCX,
&beta, y._data, &INCY);
}
template<>
void fullMatrix<std::complex<double> >::multAddy(const fullVector<std::complex<double> > &x,
fullVector<std::complex<double> > &y) const
{
int M = _r, N = _c, LDA = _r, INCX = 1, INCY = 1;
std::complex<double> alpha = 1., beta = 1.;
F77NAME(zgemv)("N", &M, &N, &alpha, _data, &LDA, x._data, &INCX,
&beta, y._data, &INCY);
}
template<>
void fullMatrix<double>::multOnBlock(const fullMatrix<double> &b, const int ncol, const int fcol, const int alpha_, const int beta_, fullVector<double> &c) const
{
int M = 1, N = ncol, K = b.size1() ;
int LDA = _r, LDB = b.size1(), LDC = 1;
double alpha = alpha_, beta = beta_;
F77NAME(dgemm)("N", "N", &M, &N, &K, &alpha, _data, &LDA, &(b._data[fcol*K]), &LDB,
&beta, &(c._data[fcol]), &LDC);
}
template<>
void fullMatrix<double>::multWithATranspose(const fullVector<double> &x, double alpha, double beta,fullVector<double> &y) const
{
int M = _r, N = _c, LDA = _r, INCX = 1, INCY = 1;
F77NAME(dgemv)("T", &M, &N, &alpha, _data, &LDA, x._data, &INCX,
&beta, y._data, &INCY);
}
#endif
#if defined(HAVE_LAPACK)
extern "C" {
void F77NAME(dgesv)(int *N, int *nrhs, double *A, int *lda, int *ipiv,
double *b, int *ldb, int *info);
void F77NAME(dgetrf)(int *M, int *N, double *A, int *lda, int *ipiv, int *info);
void F77NAME(dgetrs)(char *trans, int *N, int *nrhs, double *A, int *lda, int *ipiv,
double *b, int *ldb, int *info);
void F77NAME(dgetri)(int *M, double *A, int *lda, int *ipiv, double *work,
int *lwork, int *info);
void F77NAME(dgesvd)(const char* jobu, const char *jobvt, int *M, int *N,
double *A, int *lda, double *S, double* U, int *ldu,
double *VT, int *ldvt, double *work, int *lwork, int *info);
void F77NAME(dgeev)(const char *jobvl, const char *jobvr, int *n, double *a,
int *lda, double *wr, double *wi, double *vl, int *ldvl,
double *vr, int *ldvr, double *work, int *lwork, int *info);
}
static void swap(double *a, int inca, double *b, int incb, int n)
{
double tmp;
for (int i = 0; i < n; i++, a += inca, b += incb) {
tmp = (*a);
(*a) = (*b);
(*b) = tmp;
}
}
static void eigSort(int n, double *wr, double *wi, double *VL, double *VR)
{
// Sort the eigenvalues/vectors in ascending order according to
// their real part. Warning: this will screw up the ordering if we
// have complex eigenvalues.
for (int i = 0; i < n - 1; i++){
int k = i;
double ek = wr[i];
// search for something to swap
for (int j = i + 1; j < n; j++){
const double ej = wr[j];
if(ej < ek){
k = j;
ek = ej;
}
}
if (k != i){
swap(&wr[i], 1, &wr[k], 1, 1);
swap(&wi[i], 1, &wi[k], 1, 1);
swap(&VL[n * i], 1, &VL[n * k], 1, n);
swap(&VR[n * i], 1, &VR[n * k], 1, n);
}
}
}
template<>
bool fullMatrix<double>::eig(fullVector<double> &DR, fullVector<double> &DI,
fullMatrix<double> &VL, fullMatrix<double> &VR,
bool sortRealPart)
{
int N = size1(), info;
int lwork = 10 * N;
double *work = new double[lwork];
F77NAME(dgeev)("V", "V", &N, _data, &N, DR._data, DI._data,
VL._data, &N, VR._data, &N, work, &lwork, &info);
delete [] work;
if(info > 0)
Msg::Error("QR Algorithm failed to compute all the eigenvalues", info, info);
else if(info < 0)
Msg::Error("Wrong %d-th argument in eig", -info);
else if(sortRealPart)
eigSort(N, DR._data, DI._data, VL._data, VR._data);
return true;
}
template<>
bool fullMatrix<double>::luSolve(const fullVector<double> &rhs, fullVector<double> &result)
{
int N = size1(), nrhs = 1, lda = N, ldb = N, info;
int *ipiv = new int[N];
for(int i = 0; i < N; i++) result(i) = rhs(i);
F77NAME(dgesv)(&N, &nrhs, _data, &lda, ipiv, result._data, &ldb, &info);
delete [] ipiv;
if(info == 0) return true;
return false;
}
template<>
bool fullMatrix<double>::luFactor(fullVector<int> &ipiv)
{
int M = size1(), N = size2(), lda = size1(), info;
ipiv.resize(std::min(M, N));
F77NAME(dgetrf)(&M, &N, _data, &lda, &ipiv(0), &info);
if(info == 0) return true;
return false;
}
template<>
bool fullMatrix<double>::luSubstitute(const fullVector<double> &rhs, fullVector<int> &ipiv, fullVector<double> &result)
{
int N = size1(), nrhs=1, lda = N, ldb = N, info;
char trans = 'N';
for(int i = 0; i < N; i++) result(i) = rhs(i);
F77NAME(dgetrs)(&trans, &N, &nrhs, _data, &lda, &ipiv(0), result._data, &ldb, &info);
if(info == 0) return true;
return false;
}
template<>
bool fullMatrix<double>::invert(fullMatrix<double> &result) const
{
int M = size1(), N = size2(), lda = size1(), info;
int *ipiv = new int[std::min(M, N)];
if (result.size2() != M || result.size1() != N) {
if (result._own_data || !result._data)
result.resize(M,N,false);
else
Msg::Fatal("FullMatrix: Bad dimension, I cannot write in proxy");
}
result.setAll(*this);
F77NAME(dgetrf)(&M, &N, result._data, &lda, ipiv, &info);
if(info == 0){
int lwork = M * 4;
double *work = new double[lwork];
F77NAME(dgetri)(&M, result._data, &lda, ipiv, work, &lwork, &info);
delete [] work;
}
delete [] ipiv;
if(info == 0) return true;
else if(info > 0)
Msg::Error("U(%d,%d)=0 in matrix inversion", info, info);
else
Msg::Error("Wrong %d-th argument in matrix inversion", -info);
return false;
}
template<>
bool fullMatrix<double>::invertInPlace()
{
int N = size1(), nrhs = N, lda = N, ldb = N, info;
int *ipiv = new int[N];
double * invA = new double[N*N];
for (int i = 0; i < N * N; i++) invA[i] = 0.;
for (int i = 0; i < N; i++) invA[i * N + i] = 1.;
F77NAME(dgesv)(&N, &nrhs, _data, &lda, ipiv, invA, &ldb, &info);
memcpy(_data, invA, N * N * sizeof(double));
delete [] invA;
delete [] ipiv;
if(info == 0) return true;
if(info > 0)
Msg::Error("U(%d,%d)=0 in matrix in place inversion", info, info);
else
Msg::Error("Wrong %d-th argument in matrix inversion", -info);
return false;
}
template<>
double fullMatrix<double>::determinant() const
{
fullMatrix<double> tmp(*this);
int M = size1(), N = size2(), lda = size1(), info;
int *ipiv = new int[std::min(M, N)];
F77NAME(dgetrf)(&M, &N, tmp._data, &lda, ipiv, &info);
double det = 1.;
if(info == 0){
for(int i = 0; i < size1(); i++){
det *= tmp(i, i);
if(ipiv[i] != i + 1) det = -det;
}
}
else if(info > 0)
det = 0.;
else
Msg::Error("Wrong %d-th argument in matrix factorization", -info);
delete [] ipiv;
return det;
}
template<>
bool fullMatrix<double>::svd(fullMatrix<double> &V, fullVector<double> &S)
{
fullMatrix<double> VT(V.size2(), V.size1());
int M = size1(), N = size2(), LDA = size1(), LDVT = VT.size1(), info;
int lwork = std::max(3 * std::min(M, N) + std::max(M, N), 5 * std::min(M, N));
fullVector<double> WORK(lwork);
F77NAME(dgesvd)("O", "A", &M, &N, _data, &LDA, S._data, _data, &LDA,
VT._data, &LDVT, WORK._data, &lwork, &info);
V = VT.transpose();
if(info == 0) return true;
if(info > 0)
Msg::Error("SVD did not converge");
else
Msg::Error("Wrong %d-th argument in SVD decomposition", -info);
return false;
}
#else
// Provide a default implementation of the matrix inversion
// Bad algorithms but it allows to use
// the polynomial basis without having lapack
template<>
double fullMatrix<double>::determinant() const{
if(_r == 2)
return (*this)(0,0) * (*this)(1,1) - (*this)(0,1) * (*this)(1,0);
else if (_r == 3)
{
double det = ((*this)(0,0)*(*this)(1,1)*(*this)(2,2)
+ (*this)(0,1)*(*this)(1,2)*(*this)(2,0)
+ (*this)(0,2)*(*this)(1,0)*(*this)(2,1));
det -= (*this)(0,0)*(*this)(1,2)*(*this)(2,1);
det -= (*this)(0,1)*(*this)(1,0)*(*this)(2,2);
det -= (*this)(0,2)*(*this)(1,1)*(*this)(2,0);
return det;
}
else if (_r == 4)
{
std::vector<fullMatrix<double> > temp(4,fullMatrix<double>(3,3));
for(int k = 0; k < 4; k++)
{
for(int i = 1; i < 4; i++)
{
int j1 = 0;
for(int j = 0; j < 4; j++)
{
if(k != j)
temp[k](i-1,j1++) = (*this)(i,j);
}
}
}
return ((*this)(0,0) * temp[0].determinant() -
(*this)(0,1) * temp[1].determinant() +
(*this)(0,2) * temp[2].determinant() -
(*this)(0,3) * temp[3].determinant());
}
else if (_r == 5)
{
std::vector<fullMatrix<double> > temp(5,fullMatrix<double>(4,4));
for(int k = 0; k < 5; k++)
{
for(int i = 1; i < 5; i++)
{
int j1 = 0;
for(int j = 0; j < 5; j++)
{
if(k != j)
temp[k](i-1,j1++) = (*this)(i,j);
}
}
}
return ((*this)(0,0) * temp[0].determinant() -
(*this)(0,1) * temp[1].determinant() +
(*this)(0,2) * temp[2].determinant() -
(*this)(0,3) * temp[3].determinant() +
(*this)(0,4) * temp[4].determinant());
}
else
{
std::vector<fullMatrix<double> > temp(_r,fullMatrix<double>(_r-1,_r-1));
for(int k = 0; k < _r; k++)
{
for(int i = 1; i < _r; i++)
{
int j1 = 0;
for(int j = 0; j < _r; j++)
{
if(k != j)
temp[k](i-1,j1++) = (*this)(i,j);
}
}
}
double det = 0;
for(int k = 0; k < _r; k+=2)
{
det += (*this)(0,k) * temp[k].determinant();
}
for(int k = 1; k < _r; k+=2)
{
det -= (*this)(0,k) * temp[k].determinant();
}
return det;
}
return (*this)(0,0); // 1x1 matrix
}
template<>
bool fullMatrix<double>::invert(fullMatrix<double> &result) const
{
if(_r != _c) return false;
// Copy the matrix
result.resize(_r,_c);
// to find out Determinant
double det = this->determinant();
if(det == 0)
return false;
// Matrix of cofactor put this in a function?
fullMatrix<double> cofactor(_r,_c);
if(_r == 2)
{
cofactor(0,0) = (*this)(1,1);
cofactor(0,1) = -(*this)(1,0);
cofactor(1,0) = -(*this)(0,1);
cofactor(1,1) = (*this)(0,0);
}
else if(_r >= 3)
{
std::vector<std::vector<fullMatrix<double> > > temp(_r,std::vector<fullMatrix<double> >(_r,fullMatrix<double>(_r-1,_r-1)));
for(int k1 = 0; k1 < _r; k1++)
{
for(int k2 = 0; k2 < _r; k2++)
{
int i1 = 0;
for(int i = 0; i < _r; i++)
{
int j1 = 0;
for(int j = 0; j < _r; j++)
{
if(k1 != i && k2 != j)
temp[k1][k2](i1,j1++) = (*this)(i,j);
}
if(k1 != i)
i1++;
}
}
}
bool flagPositive;
for(int k1 = 0; k1 < _r; k1++)
{
flagPositive = (k1 % 2) == 0 ? true : false;
for(int k2 = 0; k2 < _r; k2++)
{
if(flagPositive)
{
cofactor(k1,k2) = temp[k1][k2].determinant();
flagPositive = false;
}
else
{
cofactor(k1,k2) = -temp[k1][k2].determinant();
flagPositive = true;
}
}
}
}
// end cofactor
// inv = transpose of cofactor / Determinant
for(int i = 0; i < _r; i++)
{
for(int j = 0; j < _c; j++)
{
result(j,i) = cofactor(i,j) / det;
}
}
return true;
}
#endif