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. "1.0.12+abi.2.3.0"
print(n4m.abi_version())  # ABI triple, e.g. (2, 3, 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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Data verified by PyPI on Aug 25, 2026
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  • Released:
Newer release available (1.0.19)

1 maintainer

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Avatar for gbeurier from gravatar.com gbeurier

Credits

Author: Grégory Beurier and contributors

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Data verified by PyPI on Aug 25, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

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CECILL-2.1
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Requires

Python >=3.10

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