nirs4all-methods

nirs4all-methods is the full numerical/method engine distribution. The Python distribution name is nirs4all-methods; the import package is n4m, matching the stable libn4m C ABI and n4m_* exported symbols.

The wheel bundles the libn4m shared library, so pip install nirs4all-methods is self-contained — no separate native build is required. The slim pls4all distribution remains available for PLS-focused users; both distributions load the same ABI family.

import n4m
from n4m.estimators.regression.latent import PLS

print(n4m.version())      # project version + ABI, e.g. "1.0.19+abi.2.5.0"
print(n4m.abi_version())  # ABI triple, e.g. (2, 5, 0)

model = PLS(n_components=2).fit(X, y)
pred = model.predict(X)

n4m loads libn4m via ctypes.CDLL and exposes version/ABI helpers, Context, and role-based packages such as n4m.estimators, n4m.transform, n4m.feature_selection, n4m.model_selection, and n4m.augmentation. Estimator-style wrappers live under those role packages; there is no flat n4m.sklearn package in the ABI 2 surface.

Native hyperparameter studies can be checkpointed without Python pickles: checkpoint = optimizer.save() returns portable N4MOPT bytes and Optimizer.load(checkpoint) resumes the exact sequential ask/tell trajectory.

Set N4M_LIB_PATH to point at a development libn4m build when overriding the bundled wheel library.

See https://github.com/GBeurier/nirs4all-methods for documentation.

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