Struct MatsubaraSamplingPositiveOnly 

pub struct MatsubaraSamplingPositiveOnly<S: StatisticsType> { /* private fields */ }

Matsubara sampling for positive frequencies only

Exploits symmetry to reconstruct real coefficients from positive frequencies only. Supports: {0, 1, 2, 3, …} (no negative frequencies)

Implementations

impl<S: StatisticsType> MatsubaraSamplingPositiveOnly<S>

pub fn new(basis: &impl Basis<S>) -> Self

where S: 'static,

Create Matsubara sampling with default positive-only sampling points

Uses extrema-based sampling point selection (positive frequencies only). Exploits symmetry to reconstruct real coefficients.

pub fn with_sampling_points( basis: &impl Basis<S>, sampling_points: Vec<MatsubaraFreq<S>>, ) -> Self

where S: 'static,

Create Matsubara sampling with custom positive-only sampling points

pub fn from_matrix( sampling_points: Vec<MatsubaraFreq<S>>, matrix: DTensor<Complex<f64>, 2>, ) -> Self

Create Matsubara sampling (positive-only) with custom sampling points and pre-computed matrix

This constructor is useful when the sampling matrix is already computed. Uses symmetry to fit real coefficients from complex values at positive frequencies.

Arguments

• sampling_points - Matsubara frequency sampling points (should be positive)
• matrix - Pre-computed sampling matrix (n_points × basis_size)

Returns

A new MatsubaraSamplingPositiveOnly object

Panics

Panics if sampling_points is empty or if matrix dimensions don’t match

pub fn sampling_points(&self) -> &[MatsubaraFreq<S>]

Get sampling points

pub fn n_sampling_points(&self) -> usize

Number of sampling points

pub fn basis_size(&self) -> usize

Basis size

pub fn evaluate(&self, coeffs: &[f64]) -> Vec<Complex<f64>>

Evaluate basis coefficients at sampling points

pub fn fit(&self, values: &[Complex<f64>]) -> Vec<f64>

Fit basis coefficients from values at sampling points

pub fn evaluate_nd( &self, backend: Option<&GemmBackendHandle>, coeffs: &Tensor<f64, DynRank>, dim: usize, ) -> Tensor<Complex<f64>, DynRank>

Evaluate N-dimensional array of real basis coefficients at sampling points

Arguments

• coeffs - N-dimensional tensor of real basis coefficients
• dim - Dimension along which to evaluate (must have size = basis_size)

Returns

N-dimensional tensor of complex values at Matsubara frequencies

pub fn fit_nd( &self, backend: Option<&GemmBackendHandle>, values: &Tensor<Complex<f64>, DynRank>, dim: usize, ) -> Tensor<f64, DynRank>

Fit N-dimensional array of complex values to real basis coefficients

Arguments

• backend - Optional GEMM backend handle (None uses default)
• values - N-dimensional tensor of complex values at Matsubara frequencies
• dim - Dimension along which to fit (must have size = n_sampling_points)

Returns

N-dimensional tensor of real basis coefficients