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. "1.1.1+abi.2.13.0"
print(n4m.abi_version())  # ABI triple, e.g. (2, 13, 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 1.1.1

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 1.1.1
File
nirs4all_methods-1.1.1-py3-none-win_amd64.whl Python 3 none Windows x86-64 Details
nirs4all_methods-1.1.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl Python 3 none Linux glibc 2.28+ x86-64, Linux glibc 2.24+ x86-64 Details
nirs4all_methods-1.1.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl Python 3 none Linux glibc 2.24+ ARM64, Linux glibc 2.28+ ARM64 Details
nirs4all_methods-1.1.1-py3-none-macosx_11_0_universal2.whl Python 3 none macOS 11.0+ universal2 (ARM64, x86-64) Details

Total release size: 23.4 MB

Release files / nirs4all_methods-1.1.1-py3-none-win_amd64.whl

Download URL nirs4all_methods-1.1.1-py3-none-win_amd64.whl
Size 1.9 MB
Tags Python 3 Windows x86-64
SHA-256 checksum
How to use checksums
ea8fc6e9f3c3a6b0a9136dbdc2c3a1e4e027e8166e0c057d14cee2cf8d8ad6a5
BLAKE2b-256 checksum
How to use checksums
faa9cbcccc029cb756a2927abbf4347103cacc5f2b116f563b51cef3e3b76dd9
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-1.1.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Download URL nirs4all_methods-1.1.1-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Size 5.7 MB
Tags Linux glibc 2.24+ x86-64 Linux glibc 2.28+ x86-64 Python 3
SHA-256 checksum
How to use checksums
6443e18d9357a3f261de92014c967ef074df12ae1a1d39505f2beff794d6119c
BLAKE2b-256 checksum
How to use checksums
2db8e5592f26b8ffc960c6f2935c9d875bf75a1662ec1dd4a4d9f07132d06fc2
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-1.1.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl

Download URL nirs4all_methods-1.1.1-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
Size 5.0 MB
Tags Linux glibc 2.24+ ARM64 Linux glibc 2.28+ ARM64 Python 3
SHA-256 checksum
How to use checksums
5a79940732915866ae111bbc49e4c7b90ae75a39ceffd7ceb19f35199b0836c9
BLAKE2b-256 checksum
How to use checksums
4e29cede7135e62c269d566154a5a4dd8dcef4aa05b3bb0cbee4304411911ec8
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-1.1.1-py3-none-macosx_11_0_universal2.whl

Download URL nirs4all_methods-1.1.1-py3-none-macosx_11_0_universal2.whl
Size 10.8 MB
Tags Python 3 macOS 11.0+ universal2 (ARM64, x86-64)
SHA-256 checksum
How to use checksums
17de886fab4c97c9888c8292f66d0893547793e23ed5f763765b1ae9f5bd1f25
BLAKE2b-256 checksum
How to use checksums
685dcc578793c119e857561f61cc38d875f686e0b6707067f99945ed17d913b4
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