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#include <iostream>
#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_); } } } } |