pp_wavelet_svd — Wavelet S V D

Group: Augmentation · Binding: n4m.sklearn.WaveletSVD · C ABI: n4m_pp_wavelet_svd_*

Description

DWT coefficient projection through SVD scores.

Parameters

Name

Type

Default

family

str

'haar'

mode

str

'periodization'

max_level

int

2

n_components

float

5.0

Explanations

Bibliographic source

Standard spectroscopic operator — see the nirs4all preprocessing / augmentation handbook and the cited literature within the binding docstring.

Mathematical principle

DWT coefficient projection through SVD scores.

Implementation

C ABI n4m_pp_wavelet_svd_* in libn4m (create / apply / destroy lifecycle), wrapped by n4m.sklearn.WaveletSVD. The same numerical kernel backs every language binding.

Usage

from n4m.sklearn import WaveletSVD
op = WaveletSVD()
X_transformed = op.fit_transform(X)

Benchmarks

Adaptive wall-clock per cell measured against full_matrix.csv. Only backends that implement this method are listed; libraries without the method are omitted.

Verdict  ·  ✓ ref / ≈ ref / ~ shape mark a reference-gate pass at strict / relaxed / qualitative tolerance  ·  ✓ bind = pls4all binding agrees with the C++ baseline  ·  ⇄ cross-check = documented by-design selector/RNG/model, noncanonical API/facade convention, or secondary oracle  ·  ✗ divergent  ·  ⚠ error  ·  — not run. The fastest backend per column is marked 🏆.

Reference gate: strict — numeric equivalence (rmse_rel_tol 1e-12).

BackendParity50×250 (ms)250×50 (ms)
C++ native · libn4m
pls4all.cpp.blas✓ ref
pls4all.cpp.blas+omp✓ ref5.15 ms4.86 ms
pls4all.cpp.omp✓ ref
pls4all.cpp.ref✓ ref5.41 ms5.98 ms
Python · pls4all
pls4all.python✓ bind3.00 ms🏆3.08 ms
pls4all.sklearn✓ bind3.03 ms3.02 ms🏆
Python · external
ref.python_numpysource

See also: methods index · interactive dashboard