MADNESS: madness::ConvolutionData1D< Q > Struct Template Reference

MADNESS 0.10.1

!!! Note that if Rnormf is zero then ALL of the tensors are empty More...

#include <convolution1d.h>

Collaboration diagram for madness::ConvolutionData1D< Q >:

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Public Member Functions
	ConvolutionData1D (const Tensor< Q > &R, const Tensor< Q > &T)
	ConvolutionData1D (const Tensor< Q > &R, const Tensor< Q > &T, const bool modified)
void	make_approx (const Tensor< Q > &R, Tensor< Q > &RU, Tensor< typename Tensor< Q >::scalar_type > &Rs, Tensor< Q > &RVT, double &norm)

Public Attributes
double	N_diff
double	N_F
	the norms according to Beylkin 2008, Eq. (21) ff
double	N_up
double	NSnormf
Tensor< Q >	R
double	Rnorm
double	Rnormf
Tensor< typename Tensor< Q >::scalar_type >	Rs
Tensor< Q >	RU
Tensor< Q >	RVT
Tensor< Q >	T
	if NS: R=ns, T=T part of ns; if modified NS: T=\uparrow r^(n-1)
double	Tnorm
double	Tnormf
Tensor< typename Tensor< Q >::scalar_type >	Ts
	hold relative errors, NOT the singular values..
Tensor< Q >	TU
Tensor< Q >	TVT
	SVD approximations to R and T.

Detailed Description

template<typename Q>
struct madness::ConvolutionData1D< Q >

!!! Note that if Rnormf is zero then ALL of the tensors are empty

actual data for 1 dimension and for 1 term and for 1 displacement for a convolution operator here we keep the transformation matrices

Constructor & Destructor Documentation

◆ ConvolutionData1D() [1/2]

template<typename Q>

madness::ConvolutionData1D< Q >::ConvolutionData1D	(	const Tensor< Q > &	R,
		const Tensor< Q > &	T )

inline

ctor for NS form make the operator matrices r^n and \uparrow r^(n-1)

Parameters

[in]	R	operator matrix of the requested level; NS: unfilter(r^(n+1)); modified NS: r^n
[in]	T	upsampled operator matrix from level n-1; NS: r^n; modified NS: filter( r^(n-1) )

References madness::copy(), e(), madness::FunctionDefaults< NDIM >::k, make_approx(), N_diff, N_F, N_up, madness::Tensor< T >::normf(), NSnormf, R, Rnorm, Rnormf, Rs, RU, RVT, T, Tnorm, Tnormf, Ts, TU, and TVT.

◆ ConvolutionData1D() [2/2]

template<typename Q>

madness::ConvolutionData1D< Q >::ConvolutionData1D	(	const Tensor< Q > &	R,
		const Tensor< Q > &	T,
		const bool	modified )

inline

ctor for modified NS form make the operator matrices r^n and \uparrow r^(n-1)

Parameters

[in]	R	operator matrix of the requested level; NS: unfilter(r^(n+1)); modified NS: r^n
[in]	T	upsampled operator matrix from level n-1; NS: r^n; modified NS: filter( r^(n-1) )
[in]	modified	use (un) modified NS form

References e(), make_approx(), N_diff, N_F, N_up, R, Rnorm, Rnormf, Rs, RU, RVT, T, Tnorm, Tnormf, Ts, TU, and TVT.

Member Function Documentation

◆ make_approx()

template<typename Q>

void madness::ConvolutionData1D< Q >::make_approx	(	const Tensor< Q > &	R,
		Tensor< Q > &	RU,
		Tensor< typename Tensor< Q >::scalar_type > &	Rs,
		Tensor< Q > &	RVT,
		double &	norm )

inline

approximate the operator matrices using SVD, and abuse Rs to hold the error instead of the singular values (seriously, who named this??)

References norm(), R, Rs, RU, RVT, and madness::svd().

Referenced by ConvolutionData1D(), and ConvolutionData1D().

Member Data Documentation

◆ N_diff

template<typename Q>

double madness::ConvolutionData1D< Q >::N_diff

Referenced by ConvolutionData1D(), ConvolutionData1D(), and madness::SeparatedConvolution< double, 3 >::munorm2_modified().

◆ N_F

template<typename Q>

double madness::ConvolutionData1D< Q >::N_F

the norms according to Beylkin 2008, Eq. (21) ff

Referenced by ConvolutionData1D(), ConvolutionData1D(), and madness::SeparatedConvolution< double, 3 >::munorm2_modified().

◆ N_up

template<typename Q>

double madness::ConvolutionData1D< Q >::N_up

Referenced by ConvolutionData1D(), ConvolutionData1D(), and madness::SeparatedConvolution< double, 3 >::munorm2_modified().

◆ NSnormf

template<typename Q>

double madness::ConvolutionData1D< Q >::NSnormf

Referenced by ConvolutionData1D().

◆ R

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::R

Referenced by ConvolutionData1D(), ConvolutionData1D(), and make_approx().

◆ Rnorm

template<typename Q>

double madness::ConvolutionData1D< Q >::Rnorm

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ Rnormf

template<typename Q>

double madness::ConvolutionData1D< Q >::Rnormf

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ Rs

template<typename Q>

Tensor<typename Tensor<Q>::scalar_type> madness::ConvolutionData1D< Q >::Rs

Referenced by ConvolutionData1D(), ConvolutionData1D(), and make_approx().

◆ RU

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::RU

Referenced by ConvolutionData1D(), ConvolutionData1D(), and make_approx().

◆ RVT

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::RVT

Referenced by ConvolutionData1D(), ConvolutionData1D(), and make_approx().

◆ T

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::T

if NS: R=ns, T=T part of ns; if modified NS: T=\uparrow r^(n-1)

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ Tnorm

template<typename Q>

double madness::ConvolutionData1D< Q >::Tnorm

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ Tnormf

template<typename Q>

double madness::ConvolutionData1D< Q >::Tnormf

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ Ts

template<typename Q>

Tensor<typename Tensor<Q>::scalar_type> madness::ConvolutionData1D< Q >::Ts

hold relative errors, NOT the singular values..

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ TU

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::TU

Referenced by ConvolutionData1D(), and ConvolutionData1D().

◆ TVT

template<typename Q>

Tensor<Q> madness::ConvolutionData1D< Q >::TVT

SVD approximations to R and T.

Referenced by ConvolutionData1D(), and ConvolutionData1D().

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

convolution1d.h