McrNmf Documentation
====================

Welcome to the documentation for **McrNmf**, a Python package for Multivariate Curve
Resolution (MCR) using different Nonnegative Matrix Factorization (NMF) algorithms. The
source code is hosted on GitHub: `https://github.com/siddarthVasudevan/mcrnmf <https://github.com/siddarthVasudevan/mcrnmf>`__

MCR is widely used in chemometrics to decompose mixture spectra into their pure
component spectra and associated concentration profiles.

Key Features
------------

- **Multiple solvers** -- unified interface for three NMF variants:
  classic Alternating Least Squares (:class:`~mcrnmf.models.FroALS`),
  Fast Projected Gradient (:class:`~mcrnmf.models.FroFPGM`), and
  Minimum-Volume formulation (:class:`~mcrnmf.models.MinVol`)
- **Built-in constraints** -- supports closure, normalization, equality, and per-component
  unimodality constraints
- **Robust initialisation** -- includes :class:`~mcrnmf.models.SNPA` algorithm for generating
  reliable starting estimates of spectra and concentrations
- **Lightweight implementation** -- written almost entirely in `NumPy <https://numpy.org/doc/stable/>`__,
  with `Numba <https://numba.readthedocs.io/en/stable/>`__ used only to speed up unimodal regression


Installation
------------

.. code-block:: bash

   conda install -c conda-forge mcrnmf

Basic Usage
-----------

.. code-block:: python

   from mcrnmf import MinVol, SNPA
   from mcrnmf.datasets import load_rxn_spectra

   # Load example data
   X, wv, time = load_rxn_spectra()

   # Get initial guess using SNPA
   snpa = SNPA(rank=4)
   snpa.fit(X)
   Wi = snpa.W.copy()
   Hi = snpa.H.copy()

   # Initialize MinVol with SNPA results and apply constraints
   model = MinVol(rank=4, constraint_kind=1)
   model.fit(X=X, Wi=Wi, Hi=Hi)

   # Access results
   W = model.W  # Pure component spectra
   H = model.H  # Concentration profiles

Next Steps
----------

- See the :doc:`usage/index` page for worked examples
- Browse the :doc:`api` for full API documentation
- Check the :doc:`installation` page for detailed setup info

Contents
--------

.. toctree::
   :maxdepth: 2

   installation
   usage/index
   api
   changelog

Indices and Tables
------------------

* :ref:`genindex`
* :ref:`search`