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* added innerSize / outerSize functions to MatrixBase

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* added complete implementation of sparse matrix product
  (with a little glue in Eigen/Core)
* added an exhaustive bench of sparse products including GMM++ and MTL4
  => Eigen outperforms in all transposed/density configurations !
This commit is contained in:
Gael Guennebaud
2008-06-28 23:07:14 +00:00
parent 6917be9113
commit 027818d739
16 changed files with 622 additions and 380 deletions
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11
test/cholesky.cpp
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@@ -24,6 +24,7 @@
#include "main.h"
#include <Eigen/Cholesky>
#include <Eigen/LU>
template<typename MatrixType> void cholesky(const MatrixType& m)
{
@@ -34,12 +35,12 @@ template<typename MatrixType> void cholesky(const MatrixType& m)
int cols = m.cols();
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
MatrixType a = MatrixType::random(rows,cols).transpose();
VectorType b = VectorType::random(cols);
SquareMatrixType covMat = a.adjoint() * a;
MatrixType a = MatrixType::random(rows,cols);
VectorType b = VectorType::random(rows);
SquareMatrixType covMat = a * a.adjoint();
CholeskyWithoutSquareRoot<SquareMatrixType> cholnosqrt(covMat);
VERIFY_IS_APPROX(covMat, cholnosqrt.matrixL() * cholnosqrt.vectorD().asDiagonal() * cholnosqrt.matrixL().adjoint());