Metadata-Version: 2.4
Name: conditional_kde
Version: 0.1.2
Summary: Conditional Kernel Density Estimation.
Author-email: David Prelogović <david.prelogovic@gmail.com>
Maintainer-email: David Prelogović <david.prelogovic@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/dprelogo/conditional_kde
Project-URL: Repository, https://github.com/dprelogo/conditional_kde
Project-URL: Documentation, https://conditional-kde.readthedocs.io
Keywords: conditional_kde,kernel density estimation,machine learning
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9
Description-Content-Type: text/x-rst
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Provides-Extra: test
Requires-Dist: pytest>=3; extra == "test"
Provides-Extra: dev
Requires-Dist: pytest>=3; extra == "dev"
Requires-Dist: bump2version; extra == "dev"
Requires-Dist: wheel; extra == "dev"
Requires-Dist: watchdog; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: tox; extra == "dev"
Requires-Dist: coverage; extra == "dev"
Requires-Dist: Sphinx; extra == "dev"
Requires-Dist: twine; extra == "dev"
Requires-Dist: black; extra == "dev"
Requires-Dist: matplotlib; extra == "dev"
Dynamic: license-file

===============
Conditional KDE
===============

.. image:: https://img.shields.io/pypi/v/conditional_kde.svg
        :target: https://pypi.python.org/pypi/conditional_kde
        :alt: PyPI Version

.. image:: https://img.shields.io/pypi/pyversions/conditional_kde.svg
        :target: https://pypi.python.org/pypi/conditional_kde
        :alt: Python Versions

.. image:: https://github.com/dprelogo/conditional_kde/workflows/CI/badge.svg
        :target: https://github.com/dprelogo/conditional_kde/actions?query=workflow%3ACI
        :alt: CI Status

.. image:: https://codecov.io/gh/dprelogo/conditional_kde/branch/main/graph/badge.svg
        :target: https://codecov.io/gh/dprelogo/conditional_kde
        :alt: Code Coverage

.. image:: https://readthedocs.org/projects/conditional-kde/badge/?version=latest
        :target: https://conditional-kde.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status

.. image:: https://img.shields.io/github/license/dprelogo/conditional_kde.svg
        :target: https://github.com/dprelogo/conditional_kde/blob/main/LICENSE
        :alt: License

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
        :target: https://github.com/psf/black
        :alt: Code Style: Black




Conditional Kernel Density Estimation
-------------------------------------

A Python package for conditional kernel density estimation. This library provides efficient implementations for estimating conditional probability densities using kernel methods.

* **Free software:** MIT license
* **Documentation:** https://conditional-kde.readthedocs.io
* **PyPI:** https://pypi.org/project/conditional_kde/
* **Source Code:** https://github.com/dprelogo/conditional_kde


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

Install from PyPI::

    pip install conditional_kde

For development installation::

    git clone https://github.com/dprelogo/conditional_kde.git
    cd conditional_kde
    pip install -e .[dev]


Quick Start
-----------

.. code-block:: python

    from conditional_kde import ConditionalKDE

    # Example usage
    ckde = ConditionalKDE()
    # Add your code example here


Features
--------

* Gaussian and interpolated kernel density estimation
* Support for conditional density estimation
* Efficient implementation using NumPy and SciPy
* Comprehensive test coverage
* Type hints for better IDE support

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
