filter_composite — Composite Filter¶
Group: Sample / feature filters · Binding: n4m.sklearn.CompositeFilter · C ABI: n4m_filter_composite_*
Description¶
Boolean composition of leverage and quality filters.
Parameters¶
Name |
Type |
Default |
|---|---|---|
|
`str |
int` |
|
|
|
Explanations¶
Bibliographic source¶
Standard spectroscopic operator — see the nirs4all preprocessing / augmentation handbook and the cited literature within the binding docstring.
Mathematical principle¶
Boolean composition of leverage and quality filters.
Implementation¶
C ABI n4m_filter_composite_* in libn4m (create / apply / destroy lifecycle), wrapped by n4m.sklearn.CompositeFilter. The same numerical kernel backs every language binding.
Usage¶
from n4m.sklearn import CompositeFilter
op = CompositeFilter()
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+omp | ✓ ref | — | — |
| Python · external | |||
nirs4all | source | — | — |
See also: methods index · interactive dashboard