elliptical-distribution-toolkit


Nameelliptical-distribution-toolkit JSON
Version 0.0.1 PyPI version JSON
download
home_pagehttps://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit
SummaryToolkit related to multivariate elliptical distributions.
upload_time2025-08-02 23:04:07
maintainerNone
docs_urlNone
authorJay Damask
requires_python>=3.7
licenseApache License 2.0
keywords multivariate statistics
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls. 
            <img src="https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/raw/main/images/elliptical-tile-logo.1500px.png" alt="elliptical-logo" height="150"> 


# Elliptical-Distribution Toolkit

[![pipeline status](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/badges/main/pipeline.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/pipelines)
[![coverage report](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/badges/main/coverage.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/commits/main)
[![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/blob/main/LICENSE)
[![Code style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![python versions](https://img.shields.io/badge/py-%3E%3D3.7-blue)](https://pypi.python.org/pypi/elliptical-distribution-toolkit)
[![numpy versions](https://img.shields.io/badge/numpy-%3E%3D1.23-blue)](https://www.numpy.org/)
[![pypi version](https://img.shields.io/pypi/v/elliptical-distribution-toolkit.svg)](https://pypi.python.org/pypi/elliptical-distribution-toolkit)
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/elliptical-distribution-toolkit.svg)](https://anaconda.org/conda-forge/elliptical-distribution-toolkit)


## Overview

This package, `elliptical-distribution-toolkit`, provides a variety of functions that deal with multivariate elliptical distributions. Two key distributions are the multivariate (mv) Gaussian and mv Student-t. 

Among the provided functions, `mahal_explicit` and `mahal_estimate` resolve longstanding issues with other implementations of the Mahalanobis distance calculation wherein the latter do not properly handle vectorized input whereas the implementations in this package do. 


## Package Installation

The two package hosts for `elliptical-distribution-toolkit` are [PyPi]() and [Conda-Forge](). The packages are identical and the only difference is the means of delivery. From PyPi, use `pip`,

```bash
$ pip install elliptical-distribution-toolkit
```

and from Conda-Forge use `conda`:

```bash
$ conda install -c conda-forge elliptical-distribution-toolkit
```

Once installed, the package is importable to Python:

```python
>>> import elliptical_distribution_toolkit as ell_tk
```

## Package Dependency

The only dependencies `elliptical-distribution-toolkit` has at this time is on [python >= 3.7](https://www.python.org/) and [numpy >= 1.23](https://www.numpy.org/). 


## Buell Lane Press

[Buell Lane Press](https://buell-lane-press.co) is the package sponsor.

Raw data

            {
    "_id": null,
    "home_page": "https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit",
    "name": "elliptical-distribution-toolkit",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.7",
    "maintainer_email": null,
    "keywords": "multivariate statistics",
    "author": "Jay Damask",
    "author_email": "jaydamask@buell-lane-press.co",
    "download_url": "https://files.pythonhosted.org/packages/07/96/9e8de13a692a72fbdeb61640ae538d4d8676071115cb516a50a99b3c7f6e/elliptical_distribution_toolkit-0.0.1.tar.gz",
    "platform": null,
    "description": "<img src=\"https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/raw/main/images/elliptical-tile-logo.1500px.png\" alt=\"elliptical-logo\" height=\"150\"> \n\n\n# Elliptical-Distribution Toolkit\n\n[![pipeline status](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/badges/main/pipeline.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/pipelines)\n[![coverage report](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/badges/main/coverage.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/commits/main)\n[![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/blob/main/LICENSE)\n[![Code style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![python versions](https://img.shields.io/badge/py-%3E%3D3.7-blue)](https://pypi.python.org/pypi/elliptical-distribution-toolkit)\n[![numpy versions](https://img.shields.io/badge/numpy-%3E%3D1.23-blue)](https://www.numpy.org/)\n[![pypi version](https://img.shields.io/pypi/v/elliptical-distribution-toolkit.svg)](https://pypi.python.org/pypi/elliptical-distribution-toolkit)\n[![Conda Version](https://img.shields.io/conda/vn/conda-forge/elliptical-distribution-toolkit.svg)](https://anaconda.org/conda-forge/elliptical-distribution-toolkit)\n\n\n## Overview\n\nThis package, `elliptical-distribution-toolkit`, provides a variety of functions that deal with multivariate elliptical distributions. Two key distributions are the multivariate (mv) Gaussian and mv Student-t. \n\nAmong the provided functions, `mahal_explicit` and `mahal_estimate` resolve longstanding issues with other implementations of the Mahalanobis distance calculation wherein the latter do not properly handle vectorized input whereas the implementations in this package do. \n\n\n## Package Installation\n\nThe two package hosts for `elliptical-distribution-toolkit` are [PyPi]() and [Conda-Forge](). The packages are identical and the only difference is the means of delivery. From PyPi, use `pip`,\n\n```bash\n$ pip install elliptical-distribution-toolkit\n```\n\nand from Conda-Forge use `conda`:\n\n```bash\n$ conda install -c conda-forge elliptical-distribution-toolkit\n```\n\nOnce installed, the package is importable to Python:\n\n```python\n>>> import elliptical_distribution_toolkit as ell_tk\n```\n\n## Package Dependency\n\nThe only dependencies `elliptical-distribution-toolkit` has at this time is on [python >= 3.7](https://www.python.org/) and [numpy >= 1.23](https://www.numpy.org/). \n\n\n## Buell Lane Press\n\n[Buell Lane Press](https://buell-lane-press.co) is the package sponsor. \n\n",
    "bugtrack_url": null,
    "license": "Apache License 2.0",
    "summary": "Toolkit related to multivariate elliptical distributions.",
    "version": "0.0.1",
    "project_urls": {
        "Changelog": "https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/",
        "Documentation": "https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/",
        "Homepage": "https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit",
        "Issue Tracker": "https://gitlab.com/elliptical-distribution-toolkit-dev/elliptical-distribution-toolkit/issues"
    },
    "split_keywords": [
        "multivariate",
        "statistics"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "fb3aa077be4c947064a2b1cffb0055bbe6b060eb19cb716dbd4dc97d2ea91d78",
                "md5": "1b57d16ac552e80a9bceeba85dfd590a",
                "sha256": "145ac81edb9b6e47566da32c6cf4e12e398d93132e37b71fe4f6267ab033d845"
            },
            "downloads": -1,
            "filename": "elliptical_distribution_toolkit-0.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "1b57d16ac552e80a9bceeba85dfd590a",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.7",
            "size": 7507,
            "upload_time": "2025-08-02T23:04:06",
            "upload_time_iso_8601": "2025-08-02T23:04:06.445791Z",
            "url": "https://files.pythonhosted.org/packages/fb/3a/a077be4c947064a2b1cffb0055bbe6b060eb19cb716dbd4dc97d2ea91d78/elliptical_distribution_toolkit-0.0.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "07969e8de13a692a72fbdeb61640ae538d4d8676071115cb516a50a99b3c7f6e",
                "md5": "32b2c2b949b3ced9d7a4cf5bb443f748",
                "sha256": "d3da0b8a5a72beb19d6e3e03196cb78c667cadf9c967b3e7ea9721677cd68b2e"
            },
            "downloads": -1,
            "filename": "elliptical_distribution_toolkit-0.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "32b2c2b949b3ced9d7a4cf5bb443f748",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.7",
            "size": 8409,
            "upload_time": "2025-08-02T23:04:07",
            "upload_time_iso_8601": "2025-08-02T23:04:07.711703Z",
            "url": "https://files.pythonhosted.org/packages/07/96/9e8de13a692a72fbdeb61640ae538d4d8676071115cb516a50a99b3c7f6e/elliptical_distribution_toolkit-0.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-08-02 23:04:07",
    "github": false,
    "gitlab": true,
    "bitbucket": false,
    "codeberg": false,
    "gitlab_user": "elliptical-distribution-toolkit-dev",
    "gitlab_project": "elliptical-distribution-toolkit",
    "lcname": "elliptical-distribution-toolkit"
}
Jay Damask
Elapsed time: 1.38985s