pp_log — Log Transform

Group: Preprocessing · Binding: n4m.sklearn.LogTransform · C ABI: n4m_pp_log_*

Description

Element-wise logarithm with optional fit-time auto-offset.

Parameters

Name	Type	Default
base	float	0.0
offset	float	0.0
auto_offset	bool	True
min_value	float	1e-08

Explanations

Bibliographic source

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

Mathematical principle

Element-wise logarithm with optional fit-time auto-offset.

Implementation

C ABI n4m_pp_log_* in libn4m (create / apply / destroy lifecycle), wrapped by n4m.sklearn.LogTransform. The same numerical kernel backs every language binding.

Usage

from n4m.sklearn import LogTransform
op = LogTransform()
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).

1 thread

Backend	Parity	50×250 (ms)	250×50 (ms)
C++ native · libn4m
pls4all.cpp.blas	✓ ref	—	0.10 ms
pls4all.cpp.blas+omp	✓ ref	0.10 ms	0.07 ms
pls4all.cpp.omp	✓ ref	—	0.09 ms
pls4all.cpp.ref	✓ ref	0.10 ms	0.10 ms
Python · pls4all
pls4all.python	✓ bind	0.06 ms🏆	0.06 ms🏆
pls4all.sklearn	✓ bind	0.06 ms	0.06 ms
Python · external
nirs4all	source	0.07 ms	0.07 ms
ref.python_numpy	source	—	—

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See also: methods index · interactive dashboard