Installing

Install the latest release from PyPI:

pip install gmcluster

To install from source (for development), clone the repository and do an editable install:

git clone https://github.com/cabouman/gmcluster.git
cd gmcluster
pip install -e .

Quick Start

The package provides one class, GaussianMixture. Fit it to your data, read the estimated parameters, then classify points or draw new samples.

import numpy as np
from gmcluster import GaussianMixture

X = np.random.default_rng(0).standard_normal((500, 2))

# Fit the mixture; "auto" selects the number of clusters by MDL.
gm = GaussianMixture(num_clusters="auto").fit(X)

print(gm.estimated_num_clusters)   # number of clusters found
print(gm.estimated_weights)        # shape (K,)
print(gm.estimated_means)          # shape (K, M)
print(gm.estimated_covariances)    # shape (K, M, M)

labels = gm.classify(X)            # most-likely cluster per point, shape (N,)
new_points = gm.sample(100)        # draw 100 samples from the fitted mixture

Running the demos

Validate the installation by running a demo:

cd demo
python demo_1.py

Citation

Please cite this software when you use it. The BibTeX entry is in docs/source/credits.rst and in the online documentation at https://gmcluster.readthedocs.io/ .