Note: this is documentation for an old release. View the latest documentation at docs.fenicsproject.org/basix/v0.8.0/cpp/namespacebasix_1_1math.html

# Basix 0.5.0

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basix::math Namespace Reference

## Functions

template<typename U , typename V >
std::pair< std::vector< typename U::value_type >, std::array< std::size_t, 2 > > outer (const U &u, const V &v)
Compute the outer product of vectors u and v. More...

template<typename U , typename V >
std::array< typename U::value_type, 3 > cross (const U &u, const V &v)

std::pair< std::vector< double >, std::vector< double > > eigh (const std::span< const double > &A, std::size_t n)

std::vector< double > solve (const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> &A, const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> &B)

bool is_singular (const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> &A)

std::vector< std::size_t > transpose_lu (std::pair< std::vector< double >, std::array< std::size_t, 2 >> &A)

template<typename U , typename V , typename W >
void dot (const U &A, const V &B, W &&C)

std::vector< double > eye (std::size_t n)

## Detailed Description

Mathematical functions

Note
The functions in this namespace are designed to be called multiple times at runtime, so their performance is critical.

## ◆ cross()

template<typename U , typename V >
 std::array basix::math::cross ( const U & u, const V & v )

Compute the cross product u x v

Parameters
 u The first vector. It must has size 3. v The second vector. It must has size 3.
Returns
The cross product u x v. The type will be the same as u.

## ◆ dot()

template<typename U , typename V , typename W >
 void basix::math::dot ( const U & A, const V & B, W && C )

Compute C = A * B

Parameters
 [in] A Input matrix [in] B Input matrix [out] C Output matrix. Must be sized correctly before calling this function.

## ◆ eigh()

 std::pair< std::vector< double >, std::vector< double > > basix::math::eigh ( const std::span< const double > & A, std::size_t n )

Compute the eigenvalues and eigenvectors of a square Hermitian matrix A

Parameters
 [in] A Input matrix, row-major storage [in] n Number of rows
Returns
Eigenvalues (0) and eigenvectors (1). The eigenvector array uses column-major storage, which each column being an eigenvector.
Precondition
The matrix A must be symmetric

## ◆ eye()

 std::vector< double > basix::math::eye ( std::size_t n )

Build an identity matrix

Parameters
 [in] n The number of rows/columns
Returns
Identity matrix using row-major storage

## ◆ is_singular()

 bool basix::math::is_singular ( const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> & A )

Check if A is a singular matrix

Parameters
 [in] A The matrix
Returns
A bool indicating if the matrix is singular

## ◆ outer()

template<typename U , typename V >
 std::pair, std::array > basix::math::outer ( const U & u, const V & v )

Compute the outer product of vectors u and v.

Parameters
 u The first vector v The second vector
Returns
The outer product. The type will be the same as u.

## ◆ solve()

 std::vector< double > basix::math::solve ( const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> & A, const std::experimental::mdspan< const double, std::experimental::dextents< std::size_t, 2 >> & B )

Solve A X = B

Parameters
 [in] A The matrix [in] B Right-hand side matrix/vector
Returns
A^{-1} B

## ◆ transpose_lu()

 std::vector< std::size_t > basix::math::transpose_lu ( std::pair< std::vector< double >, std::array< std::size_t, 2 >> & A )

Compute the LU decomposition of the transpose of a square matrix A

Parameters
 [in,out] A The matrix
Returns
The LU permutation, in prepared format (see basix::precompute::prepare_permutation)