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#include <cxxstd/iostream.h>
#include <flens/flens.cxx>
#ifndef SEED
#define SEED 0
#endif
#ifndef MAX_M
#define MAX_M 1500
#endif
#ifndef MAX_N
#define MAX_N 1500
#endif
#ifndef MAX_NNZ
#define MAX_NNZ 3*MAX_M
#endif
using namespace flens;
using namespace std;
//
// Create sparse matrix A and control matrix A_
//
template <typename CRS, typename FS>
void
setup(int m, int n, int max_nnz, int indexBase,
GeCRSMatrix<CRS> &A, GeMatrix<FS> &A_)
{
typedef typename GeCRSMatrix<CRS>::ElementType ElementType;
typedef CoordStorage<double, CoordRowColCmp> Coord;
const ElementType Zero(0);
A_.resize(m, n, indexBase, indexBase);
A_ = Zero;
//
// We first setup the sparse matrix B in coordinate storage. Later we
// convert it to compressed row storage.
//
GeCoordMatrix<Coord> B(m, n, 1, indexBase);
for (int k=1; k<=max_nnz; ++k) {
const int i = indexBase + rand() % m;
const int j = indexBase + rand() % n;
const int v1 = rand() % 10;
const int v2 = rand() % 10;
B(i,j) += v1;
A_(i,j) += v1;
B(i,j) -= v2;
A_(i,j) -= v2;
}
//
// Convert coordinate storage matrix B to compressed row storage matrix A
//
A = B;
//
// Convert compressed row storage matrix A to full storage matrix A__
//
typename GeMatrix<FS>::NoView A__ = A;
if (! lapack::isIdentical(A_, A__, "A_", "A__")) {
cerr << "m = " << m << endl;
cerr << "n = " << n << endl;
cerr << "max_nnz = " << max_nnz << endl;
ASSERT(0);
}
}
template <typename CRS, typename FS>
void
mv(int m, int n, int max_nnz, const GeCRSMatrix<CRS> &A, const GeMatrix<FS> &A_)
{
typedef typename GeCRSMatrix<CRS>::ElementType ElementType;
DenseVector<Array<ElementType> > x(n), y, y_;
for (int j=1; j<=n; ++j) {
x(j) = rand() % 10;
}
y = A * x;
y_ = A_ * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y = A*x" << endl;
ASSERT(0);
}
y += A * x;
y_ += A_ * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y += A*x" << endl;
ASSERT(0);
}
y -= A * x;
y_ -= A_ * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y -= A*x" << endl;
ASSERT(0);
}
ElementType alpha, beta;
for (int test=1; test<=20; ++test) {
alpha = std::pow(2, 5 - std::max(1, rand() % 10));
beta = std::pow(2, 5 - std::max(1, rand() % 10));
//
// Reset y (and y_) to some random vector
//
for (int i=1; i<=m; ++i) {
y(i) = rand() % 1000;
}
y_ = y;
y = beta*y + alpha*A * x;
y_ = beta*y_ + alpha*A_ * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y = beta*y + alpha*A*x" << endl;
cout << "alpha = " << alpha << endl;
cout << "beta = " << beta << endl;
cout << "A_ = " << A_ << endl;
cout << "x = " << x << endl;
cout << "y_ = " << y_ << endl;
ASSERT(0);
}
}
}
template <typename CRS, typename FS>
void
mtv(int m, int n, int max_nnz,
const GeCRSMatrix<CRS> &A, const GeMatrix<FS> &A_)
{
typedef typename GeCRSMatrix<CRS>::ElementType ElementType;
DenseVector<Array<ElementType> > x(m), y, y_;
for (int i=1; i<=m; ++i) {
x(i) = rand() % 10;
}
y = transpose(A) * x;
y_ = transpose(A_) * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y = A*x" << endl;
ASSERT(0);
}
y += transpose(A) * x;
y_ += transpose(A_) * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y += A*x" << endl;
ASSERT(0);
}
y -= transpose(A) * x;
y_ -= transpose(A_) * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y -= A*x" << endl;
ASSERT(0);
}
ElementType alpha, beta;
for (int test=1; test<=20; ++test) {
alpha = std::pow(2, 5 - std::max(1, rand() % 10));
beta = std::pow(2, 5 - std::max(1, rand() % 10));
//
// Reset y (and y_) to some random vector
//
for (int j=1; j<=n; ++j) {
y(j) = rand() % 1000;
}
y_ = y;
y = beta*y + alpha * transpose(A) * x;
y_ = beta*y_ + alpha * transpose(A_) * x;
if (! lapack::isIdentical(y, y_, "y", "y_")) {
cerr << endl << "failed: y = beta*y + alpha*A*x" << endl;
cout << "alpha = " << alpha << endl;
cout << "beta = " << beta << endl;
cout << "A_ = " << A_ << endl;
cout << "x = " << x << endl;
cout << "y_ = " << y_ << endl;
ASSERT(0);
}
}
}
int
main()
{
srand(SEED);
for (int run=1; run<=30; ++run) {
int m = std::max(1, rand() % (MAX_M));
int n = std::max(1, rand() % (MAX_N));
// check case 'nnz==0' at least onece
int max_nnz = (run==1) ? 0 : (rand() % (MAX_NNZ));
cerr << "run " << run << ":" << endl;
for (int indexBase=-3; indexBase<=3; ++indexBase) {
//
// Test non-square matrices
//
{
cerr << "indexBase = " << indexBase << endl;
cerr << "m = " << m << endl;
cerr << "n = " << n << endl;
cerr << "max_nnz = " << max_nnz << endl << endl;
GeCRSMatrix<CRS<double> > A;
GeMatrix<FullStorage<double> > A_;
setup(m, n, max_nnz, indexBase, A, A_);
mv(m, n, max_nnz, A, A_);
mtv(m, n, max_nnz, A, A_);
}
//
// Test square matrices
//
{
cerr << "indexBase = " << indexBase << endl;
cerr << "m x m = " << m << " x " << m << endl;
cerr << "max_nnz = " << max_nnz << endl << endl;
GeCRSMatrix<CRS<double> > A;
GeMatrix<FullStorage<double> > A_;
setup(m, m, max_nnz, indexBase, A, A_);
mv(m, m, max_nnz, A, A_);
mtv(m, m, max_nnz, A, A_);
}
}
}
}
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