Metadata-Version: 2.4
Name: nirs4all-methods
Version: 0.99.0
Summary: nirs4all-methods — portable PLS / NIRS engine (full surface) over the libn4m C ABI.
Author: Grégory Beurier and contributors
License-Expression: CECILL-2.1
Project-URL: Homepage, https://github.com/GBeurier/pls4all
Project-URL: Repository, https://github.com/GBeurier/pls4all
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21
Dynamic: license-file

# nirs4all-methods

nirs4all-methods — portable PLS / NIRS engine (full surface) over the libn4m C ABI.

The wheel bundles the `libn4m` shared library, so `pip install nirs4all-methods` is
self-contained — no separate native build is required.

```python
import n4m

print(n4m.version())      # project version + ABI, e.g. "0.99.0+abi.1.22.0"
print(n4m.abi_version())  # ABI triple, e.g. (1, 22, 0)
```

`n4m` loads `libn4m` via `ctypes.CDLL` and exposes a Pythonic `Context` /
`Config`, the method fit/predict surface, and a scikit-learn-compatible estimator
layer (`n4m.sklearn`). `scikit-learn` is an optional dependency; the core
`import n4m` works with NumPy alone.

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