Struct NonCentrosymmSVE 

pub struct NonCentrosymmSVE<T, K>
where
    T: CustomNumeric + Send + Sync + 'static,
    K: AbstractKernel + KernelProperties,
{ /* private fields */ }

Non-centrosymmetric SVE computation

This strategy computes the kernel matrix directly over the full domain [-xmax, xmax] × [-ymax, ymax]. No symmetry exploitation is performed, so it works for any kernel.

Centrosymmetric kernels are also expanded correctly: their SVEHints segments cover only the half-domain [0, xmax] and are mirrored onto the full domain before discretization. The singular values then agree with CentrosymmSVE up to rounding, but the SVD is taken of a single matrix with twice as many rows and columns as each even/odd block, and the singular functions carry no parity tag.

The SVD sign gauge is fixed by demanding u_l(xmax) >= 0, as CentrosymmSVE does and as libsparseir’s SamplingSVE::postprocess does via canonicalize (convention-matched with backend/cxx/include/sparseir/impl/sve_impl.ipp, libsparseir commit 4bc58ea).

Implementations

impl<T, K> NonCentrosymmSVE<T, K>

where T: CustomNumeric + Send + Sync + Clone + 'static, K: AbstractKernel + KernelProperties + Clone, <K as KernelProperties>::SVEHintsType<T>: SVEHints<T> + Clone,

pub fn new(kernel: K, epsilon: f64) -> Result<NonCentrosymmSVE<T, K>, Error>

Create a new NonCentrosymmSVE

Errors

Error::InvalidParameter if the SVE hints of the kernel give segments that are not finite and strictly increasing

Trait Implementations

impl<T, K> SVEStrategy<T> for NonCentrosymmSVE<T, K>

where T: CustomNumeric + Send + Sync + Clone + 'static, K: AbstractKernel + KernelProperties + Clone, <K as KernelProperties>::SVEHintsType<T>: SVEHints<T> + Clone,

fn matrices(&self) -> Vec<Mat<T>>

Compute the discretized matrices for SVD

fn postprocess( &self, u_list: Vec<Mat<T>>, s_list: Vec<Vec<T>>, v_list: Vec<Mat<T>>, ) -> Result<SVEResult, Error>

Post-process SVD results to create SVEResult