la_svd::svd Interface Reference

Singular value decomposition. More...

Public Member Functions
subroutine	la_svd_s (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.
subroutine	la_svd_d (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.
subroutine	la_svd_q (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.
subroutine	la_svd_c (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.
subroutine	la_svd_z (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.
subroutine	la_svd_w (a, s, u, vt, overwrite_a, full_matrices, err)
	SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Detailed Description

Singular value decomposition.

Singular values

Member Function/Subroutine Documentation

la_svd_c()

subroutine la_svd::svd::la_svd_c	(	complex(sp), dimension(:,:), intent(inout), target	a,
		real(sp), dimension(:), intent(out)	s,
		complex(sp), dimension(:,:), intent(out), optional, target	u,
		complex(sp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

la_svd_d()

subroutine la_svd::svd::la_svd_d	(	real(dp), dimension(:,:), intent(inout), target	a,
		real(dp), dimension(:), intent(out)	s,
		real(dp), dimension(:,:), intent(out), optional, target	u,
		real(dp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

la_svd_q()

subroutine la_svd::svd::la_svd_q	(	real(qp), dimension(:,:), intent(inout), target	a,
		real(qp), dimension(:), intent(out)	s,
		real(qp), dimension(:,:), intent(out), optional, target	u,
		real(qp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

la_svd_s()

subroutine la_svd::svd::la_svd_s	(	real(sp), dimension(:,:), intent(inout), target	a,
		real(sp), dimension(:), intent(out)	s,
		real(sp), dimension(:,:), intent(out), optional, target	u,
		real(sp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

la_svd_w()

subroutine la_svd::svd::la_svd_w	(	complex(qp), dimension(:,:), intent(inout), target	a,
		real(qp), dimension(:), intent(out)	s,
		complex(qp), dimension(:,:), intent(out), optional, target	u,
		complex(qp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

la_svd_z()

subroutine la_svd::svd::la_svd_z	(	complex(dp), dimension(:,:), intent(inout), target	a,
		real(dp), dimension(:), intent(out)	s,
		complex(dp), dimension(:,:), intent(out), optional, target	u,
		complex(dp), dimension(:,:), intent(out), optional, target	vt,
		logical(lk), intent(in), optional	overwrite_a,
		logical(lk), intent(in), optional	full_matrices,
		type(la_state), intent(out), optional	err
	)

SVD of matrix A = U S V^T, returning S and optionally U and V^T.

Parameters

[in,out]	a	Input matrix A[m,n]
[out]	s	Array of singular values
[out]	u	The columns of U contain the eigenvectors of A A^T
[out]	vt	The rows of V^T contain the eigenvectors of A^T A
[in]	overwrite_a	[optional] Can A data be overwritten and destroyed?
[in]	full_matrices	[optional] full matrices have shape(u)==[m,m], shape(vh)==[n,n] (default); otherwise they are shape(u)==[m,k] and shape(vh)==[k,n] with k=min(m,n)
[out]	err	[optional] state return flag. On error if not requested, the code will stop

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The documentation for this interface was generated from the following file:

• la_svd.f90