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/Eigen3

SparseCore module

This module provides a sparse matrix representation, and basic associated matrix manipulations and operations.

#include <Eigen/SparseCore>

This module depends on: Core.


class	Eigen::Map< SparseMatrixType >
	Specialization of class Map for SparseMatrix-like storage. More...

class	Eigen::Ref< SparseMatrixType, Options >
	A sparse matrix expression referencing an existing sparse expression. More...

class	Eigen::Ref< SparseVectorType >
	A sparse vector expression referencing an existing sparse vector expression. More...

class	Eigen::SparseCompressedBase< Derived >
	Common base class for sparse [compressed]-{row\|column}-storage format. More...

class	Eigen::SparseMapBase< Derived, ReadOnlyAccessors >
	Common base class for Map and Ref instance of sparse matrix and vector. More...

class	Eigen::SparseMapBase< Derived, WriteAccessors >
	Common base class for writable Map and Ref instance of sparse matrix and vector. More...

class	Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >
	A versatible sparse matrix representation. More...

class	Eigen::SparseMatrixBase< Derived >
	Base class of any sparse matrices or sparse expressions. More...

class	Eigen::SparseSelfAdjointView< MatrixType, _Mode >
	Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. More...

class	Eigen::SparseSolverBase< Derived >
	A base class for sparse solvers. More...

class	Eigen::SparseVector< _Scalar, _Options, _StorageIndex >
	a sparse vector class More...

class	Eigen::SparseView< MatrixType >
	Expression of a dense or sparse matrix with zero or too small values removed. More...

class	Eigen::TriangularViewImpl< MatrixType, Mode, Sparse >
	Base class for a triangular part in a sparse matrix. More...

class	Eigen::Triplet< Scalar, StorageIndex >
	A small structure to hold a non zero as a triplet (i,j,value). More...


const SparseView< Derived >	Eigen::MatrixBase< Derived >::sparseView (const Scalar &m_reference=Scalar(0), const typename NumTraits< Scalar >::Real &m_epsilon=NumTraits< Scalar >::dummy_precision()) const

sparseView()

template<typename Derived >

const SparseView< Derived > Eigen::MatrixBase< Derived >::sparseView	(	const Scalar &	reference = `Scalar(0)`,
		const typename NumTraits< Scalar >::Real &	epsilon = `NumTraits<Scalar>::dummy_precision()`
	)		const

Returns: a sparse expression of the dense expression *this with values smaller than reference * epsilon removed.

This method is typically used when prototyping to convert a quickly assembled dense Matrix D to a SparseMatrix S:

MatrixXd D(n,m);
SparseMatrix<double> S;
S = D.sparseView();             // suppress numerical zeros (exact)
S = D.sparseView(reference);
S = D.sparseView(reference,epsilon);

where reference is a meaningful non zero reference value, and epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision().

See also: SparseMatrixBase::pruned(), class SparseView