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* add cmake files to find (optional) supported libraries

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* add unit tests for sparse cholesky
This commit is contained in:
Gael Guennebaud
2008-10-20 10:43:11 +00:00
parent f44316e5f8
commit fa27cd1ed0
10 changed files with 331 additions and 97 deletions
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41
test/sparse.cpp
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@@ -23,6 +23,8 @@
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "main.h"
#include <Eigen/Cholesky>
#include <Eigen/LU>
#include <Eigen/Sparse>
enum {
@@ -46,8 +48,7 @@ initSparse(double density,
{
Scalar v = (ei_random<Scalar>(0,1) < density) ? ei_random<Scalar>() : 0;
if ((flags&ForceNonZeroDiag) && (i==j))
while (ei_abs(v)<1e-2)
v = ei_random<Scalar>();
v = ei_random<Scalar>(Scalar(5.),Scalar(20.));
if ((flags & MakeLowerTriangular) && j>i)
v = 0;
else if ((flags & MakeUpperTriangular) && j<i)
@@ -98,7 +99,7 @@ template<typename Scalar> void sparse(int rows, int cols)
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
VERIFY_IS_APPROX(m, refMat);
#if 0
// test InnerIterators and Block expressions
for(int j=0; j<cols; j++)
{
@@ -216,9 +217,43 @@ template<typename Scalar> void sparse(int rows, int cols)
// TODO test row major
}
#endif
// test LLT
{
SparseMatrix<Scalar> m2(rows, cols);
DenseMatrix refMat2(rows, cols);
DenseVector b = DenseVector::Random(cols);
DenseVector refX(cols), x(cols);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
refMat2 += refMat2.adjoint();
refMat2.diagonal() *= 0.5;
refMat2.llt().solve(b, &refX);
// std::cerr << refMat2 << "\n\n" << refMat2.llt().matrixL() << "\n\n";
// std::cerr << m2 << "\n\n";
typedef SparseMatrix<Scalar,Lower|SelfAdjoint> SparseSelfAdjointMatrix;
x = b;
SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
#ifdef EIGEN_CHOLMOD_SUPPORT
x = b;
SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
#endif
#ifdef EIGEN_TAUCS_SUPPORT
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
x = b;
SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
#endif
}
}