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* introduced method createRandomMatrixOfRank (R = U*D*V where U,V unitary, D r-by-c diag. with rank non-zero values)

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* switched lu/qr tests to be using createRandomMatrixOfRank
* removed unused methods doSomeRankPreservingOperations
* removed NOTE about doSomeRankPreservingOperations
This commit is contained in:
Hauke Heibel 2009-05-17 16:07:12 +02:00
parent 934d6b4749
commit 6358c12998
3 changed files with 23 additions and 58 deletions
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30
test/lu.cpp
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@ -25,44 +25,16 @@
#include "main.h"
#include <Eigen/LU>
template<typename Derived>
void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
{
typedef typename Derived::RealScalar RealScalar;
for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
{
RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
int i = Eigen::ei_random<int>(0,m.rows()-1); // i is a random row number
int j;
do {
j = Eigen::ei_random<int>(0,m.rows()-1);
} while (i==j); // j is another one (must be different)
m.row(i) += d * m.row(j);
i = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
do {
j = Eigen::ei_random<int>(0,m.cols()-1);
} while (i==j); // j is another one (must be different)
m.col(i) += d * m.col(j);
}
}
template<typename MatrixType> void lu_non_invertible()
{
/* this test covers the following files:
LU.h
*/
// NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
int rows = ei_random<int>(20,200), cols = ei_random<int>(20,200), cols2 = ei_random<int>(20,200);
int rank = ei_random<int>(1, std::min(rows, cols)-1);
MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
m1 = MatrixType::Random(rows,cols);
if(rows <= cols)
for(int i = rank; i < rows; i++) m1.row(i).setZero();
else
for(int i = rank; i < cols; i++) m1.col(i).setZero();
doSomeRankPreservingOperations(m1);
createRandomMatrixOfRank(rank, rows, cols, m1);
LU<MatrixType> lu(m1);
typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();

21
test/main.h
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@ -136,6 +136,7 @@ namespace Eigen
#define EIGEN_INTERNAL_DEBUGGING
#define EIGEN_NICE_RANDOM
#include <Eigen/Array>
#include <Eigen/QR> // required for createRandomMatrixOfRank
#define VERIFY(a) do { if (!(a)) { \
@ -225,6 +226,26 @@ inline bool test_ei_isMuchSmallerThan(const MatrixBase<Derived>& m,
return m.isMuchSmallerThan(s, test_precision<typename ei_traits<Derived>::Scalar>());
}
template<typename Derived>
void createRandomMatrixOfRank(int desired_rank, int rows, int cols, Eigen::MatrixBase<Derived>& m)
{
typedef Derived MatrixType;
typedef MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
MatrixType a = MatrixType::Random(rows,rows);
MatrixType d = MatrixType::Identity(rows,cols);
MatrixType b = MatrixType::Random(cols,cols);
// set the diagonal such that only desired_rank non-zero entries reamain
const int diag_size = std::min(d.rows(),d.cols());
d.diagonal().segment(desired_rank, diag_size-desired_rank) = VectorType::Zero(diag_size-desired_rank);
QR<MatrixType> qra(a);
QR<MatrixType> qrb(b);
m = (qra.matrixQ() * d * qrb.matrixQ()).lazy();
}
} // end namespace Eigen
template<typename T> struct GetDifferentType;

30
test/qr.cpp
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@ -55,42 +55,14 @@ template<typename MatrixType> void qr(const MatrixType& m)
VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
}
template<typename Derived>
void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
{
typedef typename Derived::RealScalar RealScalar;
for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
{
RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
int i = Eigen::ei_random<int>(0,m.rows()-1); // i is a random row number
int j;
do {
j = Eigen::ei_random<int>(0,m.rows()-1);
} while (i==j); // j is another one (must be different)
m.row(i) += d * m.row(j);
i = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
do {
j = Eigen::ei_random<int>(0,m.cols()-1);
} while (i==j); // j is another one (must be different)
m.col(i) += d * m.col(j);
}
}
template<typename MatrixType> void qr_non_invertible()
{
/* this test covers the following files: QR.h */
// NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
int rows = ei_random<int>(20,200), cols = ei_random<int>(20,rows), cols2 = ei_random<int>(20,rows);
int rank = ei_random<int>(1, std::min(rows, cols)-1);
MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
m1 = MatrixType::Random(rows,cols);
if(rows <= cols)
for(int i = rank; i < rows; i++) m1.row(i).setZero();
else
for(int i = rank; i < cols; i++) m1.col(i).setZero();
doSomeRankPreservingOperations(m1);
createRandomMatrixOfRank(rank, rows, cols, m1);
QR<MatrixType> lu(m1);
// typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();