# `split_spxy_fold` — S P X Y Fold Splitter _Group_: **Splitters** · _Binding_: `n4m.sklearn.SPXYFoldSplitter` · _C ABI_: `n4m_split_spxy_fold_*` ## Description SPXY k-fold splitter over paired ``X`` and ``y`` matrices. ### Parameters | Name | Type | Default | |------|------|---------| | `n_splits` | `int` | `5` | | `y_metric` | `str | int` | `'mahalanobis'` | ## Explanations ### Bibliographic source _Standard spectroscopic operator — see the nirs4all preprocessing / augmentation handbook and the cited literature within the binding docstring._ ### Mathematical principle SPXY k-fold splitter over paired ``X`` and ``y`` matrices. ### Implementation C ABI `n4m_split_spxy_fold_*` in libn4m (create / apply / destroy lifecycle), wrapped by `n4m.sklearn.SPXYFoldSplitter`. The same numerical kernel backs every language binding. ### Usage ```python from n4m.sklearn import SPXYFoldSplitter op = SPXYFoldSplitter() X_transformed = op.fit_transform(X) ``` ### Benchmarks Adaptive wall-clock per cell measured against [`full_matrix.csv`](../benchmarks/overview.md). 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 · ✗ divergent · ⚠ error · — not run. The fastest backend per column is marked 🏆. **Reference gate**: strict — numeric equivalence (`rmse_rel_tol ≤ 1e-12`). ::::{tab-set} :class: parity-tabs :::{tab-item} 1 thread :sync: threads-1
| Backend | Parity | 50×250 (ms) | 250×50 (ms) |
|---|---|---|---|
| C++ native · libn4m | |||
pls4all.cpp.blas+omp | ✓ ref | — | — |
| Python · external | |||
nirs4all | source | — | — |