pp_wavelet_features — Wavelet Features¶
Group: Augmentation · Binding: n4m.sklearn.WaveletFeatures · C ABI: n4m_pp_wavelet_features_*
Description¶
Multi-level DWT summary features.
Parameters¶
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Explanations¶
Bibliographic source¶
Standard spectroscopic operator — see the nirs4all preprocessing / augmentation handbook and the cited literature within the binding docstring.
Mathematical principle¶
Multi-level DWT summary features.
Implementation¶
C ABI n4m_pp_wavelet_features_* in libn4m (create / apply / destroy lifecycle), wrapped by n4m.sklearn.WaveletFeatures. The same numerical kernel backs every language binding.
Usage¶
from n4m.sklearn import WaveletFeatures
op = WaveletFeatures()
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).
| Backend | Parity | 50×250 (ms) | 250×50 (ms) |
|---|---|---|---|
| C++ native · libn4m | |||
pls4all.cpp.blas | ✓ ref | — | 0.13 ms |
pls4all.cpp.blas+omp | ✓ ref | 0.12 ms | 0.10 ms |
pls4all.cpp.omp | ✓ ref | — | 0.10 ms |
pls4all.cpp.ref | ✓ ref | 0.12 ms | 0.13 ms |
| Python · pls4all | |||
pls4all.python | ✓ bind | 0.06 ms🏆 | 0.07 ms🏆 |
pls4all.sklearn | ✓ bind | 0.06 ms | 0.07 ms |
| Python · external | |||
ref.python_numpy | source | — | — |
See also: methods index · interactive dashboard