Skip to main content

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. "1.2.1+abi.2.14.0"
print(n4m.abi_version())  # ABI triple, e.g. (2, 14, 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.

Metadata

Release files for nirs4all-methods 1.2.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for nirs4all-methods 1.2.1
File
nirs4all_methods-1.2.1-py3-none-win_amd64.whl Python 3 none Windows x86-64 Details
nirs4all_methods-1.2.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl Python 3 none Linux glibc 2.24+ x86-64, Linux glibc 2.28+ x86-64 Details
nirs4all_methods-1.2.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl Python 3 none Linux glibc 2.28+ ARM64, Linux glibc 2.24+ ARM64 Details
nirs4all_methods-1.2.1-py3-none-macosx_11_0_universal2.whl Python 3 none macOS 11.0+ universal2 (ARM64, x86-64) Details

Total release size: 23.9 MB

Release files / nirs4all_methods-1.2.1-py3-none-win_amd64.whl

Download URL nirs4all_methods-1.2.1-py3-none-win_amd64.whl
Size 2.0 MB
Tags Python 3 Windows x86-64
SHA-256 checksum
How to use checksums
4cd94c5047dc3a5d9519ddb9d01cfbcc6fb99bdec03d0af81edea40db7d7f158
BLAKE2b-256 checksum
How to use checksums
6f757661e72292c1dea497fa4c9a398e18541e5496acca39ca395677a132edf6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log

Release files / nirs4all_methods-1.2.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Download URL nirs4all_methods-1.2.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Size 5.8 MB
Tags Linux glibc 2.24+ x86-64 Linux glibc 2.28+ x86-64 Python 3
SHA-256 checksum
How to use checksums
52afbb38f5911f626be8d32061c39441713b23343eb5e8ea87e16253a0e70e13
BLAKE2b-256 checksum
How to use checksums
999390e8ae4091940c8715a25d2b628c7ead34d612b813bbda4cd46d2426a3ee
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log

Release files / nirs4all_methods-1.2.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl

Download URL nirs4all_methods-1.2.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
Size 5.1 MB
Tags Linux glibc 2.24+ ARM64 Linux glibc 2.28+ ARM64 Python 3
SHA-256 checksum
How to use checksums
03a232fec5c30a04ea1eb4cb42b472dc7fc55ca3658a15f95846dc625193347b
BLAKE2b-256 checksum
How to use checksums
5be4be15bf5afc230bd0e962c777fe4e4ff8b5cb9701bc74d7631a8f54b7fb08
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log

Release files / nirs4all_methods-1.2.1-py3-none-macosx_11_0_universal2.whl

Download URL nirs4all_methods-1.2.1-py3-none-macosx_11_0_universal2.whl
Size 11.0 MB
Tags Python 3 macOS 11.0+ universal2 (ARM64, x86-64)
SHA-256 checksum
How to use checksums
83d2523ab29b6e4426400ad7defc8562c39c1b98d3cc0abb297f92f922155f4e
BLAKE2b-256 checksum
How to use checksums
839059e733c3f7b9a4fcc5778b53ce74f3c38b83c116f8570daeb8ec7b636199
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page