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fix MaxCols in ComplexEigenSolver which was causing memory allocation instead of static allocation in the nomalloc test. Uncomment commenetd parts of the nomalloc test since now matrix-matrix products are safe.

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This commit is contained in:
Gael Guennebaud 2011-01-27 18:02:49 +01:00
parent 32124bc64a
commit 3d8e179aa2
2 changed files with 3 additions and 8 deletions
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2
Eigen/src/Eigenvalues/ComplexEigenSolver.h
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@ -96,7 +96,7 @@ template<typename _MatrixType> class ComplexEigenSolver
* This is a square matrix with entries of type #ComplexScalar.
* The size is the same as the size of #MatrixType.
*/
typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, ColsAtCompileTime> EigenvectorType;
typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime> EigenvectorType;
/** \brief Default constructor.
*

9
test/nomalloc.cpp
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@ -70,12 +70,7 @@ template<typename MatrixType> void nomalloc(const MatrixType& m)
VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), (m1.array()*m1.array()).matrix());
if (MatrixType::RowsAtCompileTime<EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD) {
// If the matrices are too large, we have better to use the optimized GEMM
// routines which allocates temporaries. However, on some platforms
// these temporaries are allocated on the stack using alloca.
VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2));
}
VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2));
}
template<typename Scalar>
@ -110,7 +105,7 @@ void ctms_decompositions()
// Eigenvalues module
Eigen::HessenbergDecomposition<ComplexMatrix> hessDecomp; hessDecomp.compute(complexA);
Eigen::ComplexSchur<ComplexMatrix> cSchur(size); cSchur.compute(complexA);
Eigen::ComplexEigenSolver<ComplexMatrix> cEigSolver; //cEigSolver.compute(complexA); // NOTE: Commented-out because makes test fail (L135 of ComplexEigenSolver.h has a product that allocates on the stack)
Eigen::ComplexEigenSolver<ComplexMatrix> cEigSolver; cEigSolver.compute(complexA);
Eigen::EigenSolver<Matrix> eigSolver; eigSolver.compute(A);
Eigen::SelfAdjointEigenSolver<Matrix> saEigSolver(size); saEigSolver.compute(saA);
Eigen::Tridiagonalization<Matrix> tridiag; tridiag.compute(saA);