e3md


Namee3md JSON
Version 0.2.0 PyPI version JSON
download
home_pageNone
SummaryLibrary for machine learning on physical tensors
upload_time2025-07-20 21:42:22
maintainerNone
docs_urlNone
authorNone
requires_python>=3.9
licenseNone
keywords machine learning e3nn-jax physics
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            E3MD
====

.. image:: https://codecov.io/gh/muhrin/e3md/branch/develop/graph/badge.svg
    :target: https://codecov.io/gh/muhrin/e3md
    :alt: Coverage

.. image:: https://github.com/muhrin/e3md/actions/workflows/ci.yml/badge.svg
    :target: https://github.com/muhrin/e3md/actions/workflows/ci.yml
    :alt: Tests

.. image:: https://img.shields.io/pypi/v/e3md.svg
    :target: https://pypi.python.org/pypi/e3md/
    :alt: Latest Version

.. image:: https://img.shields.io/pypi/wheel/e3md.svg
    :target: https://pypi.python.org/pypi/e3md/

.. image:: https://img.shields.io/pypi/pyversions/e3md.svg
    :target: https://pypi.python.org/pypi/e3md/

.. image:: https://img.shields.io/pypi/l/e3md.svg
    :target: https://pypi.python.org/pypi/e3md/

E3MD is an open-source code for building E(3)-equivariant interatomic potentials written in JAX,
based on the ``tensorial`` and ``reax`` libraries.


Quick start
-----------

.. code-block:: shell

    pip install e3md

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "e3md",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.9",
    "maintainer_email": null,
    "keywords": "machine learning, e3nn-jax, physics",
    "author": null,
    "author_email": "Martin Uhrin <martin.uhrin.10@ucl.ac.uk>",
    "download_url": "https://files.pythonhosted.org/packages/ca/c4/7bbaa7fd3ea04056799c6a02a40570d6456d79536465bd89e358998f72db/e3md-0.2.0.tar.gz",
    "platform": null,
    "description": "E3MD\n====\n\n.. image:: https://codecov.io/gh/muhrin/e3md/branch/develop/graph/badge.svg\n    :target: https://codecov.io/gh/muhrin/e3md\n    :alt: Coverage\n\n.. image:: https://github.com/muhrin/e3md/actions/workflows/ci.yml/badge.svg\n    :target: https://github.com/muhrin/e3md/actions/workflows/ci.yml\n    :alt: Tests\n\n.. image:: https://img.shields.io/pypi/v/e3md.svg\n    :target: https://pypi.python.org/pypi/e3md/\n    :alt: Latest Version\n\n.. image:: https://img.shields.io/pypi/wheel/e3md.svg\n    :target: https://pypi.python.org/pypi/e3md/\n\n.. image:: https://img.shields.io/pypi/pyversions/e3md.svg\n    :target: https://pypi.python.org/pypi/e3md/\n\n.. image:: https://img.shields.io/pypi/l/e3md.svg\n    :target: https://pypi.python.org/pypi/e3md/\n\nE3MD is an open-source code for building E(3)-equivariant interatomic potentials written in JAX,\nbased on the ``tensorial`` and ``reax`` libraries.\n\n\nQuick start\n-----------\n\n.. code-block:: shell\n\n    pip install e3md\n",
    "bugtrack_url": null,
    "license": null,
    "summary": "Library for machine learning on physical tensors",
    "version": "0.2.0",
    "project_urls": {
        "Home": "https://github.com/muhrin/e3md",
        "Source": "https://github.com/muhrin/e3md"
    },
    "split_keywords": [
        "machine learning",
        " e3nn-jax",
        " physics"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "01fbe28d8cd40a34355be18cc0698e24af3e66a99dd743bd6152770b56d304e1",
                "md5": "51d31e7e4f016a2fc46f25c017741a3e",
                "sha256": "07a10fa61c5407866f000f72913c3eb73ba6eea3db6e986d9c2c4f52ad0f294f"
            },
            "downloads": -1,
            "filename": "e3md-0.2.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "51d31e7e4f016a2fc46f25c017741a3e",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.9",
            "size": 36420,
            "upload_time": "2025-07-20T21:42:21",
            "upload_time_iso_8601": "2025-07-20T21:42:21.069890Z",
            "url": "https://files.pythonhosted.org/packages/01/fb/e28d8cd40a34355be18cc0698e24af3e66a99dd743bd6152770b56d304e1/e3md-0.2.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "cac47bbaa7fd3ea04056799c6a02a40570d6456d79536465bd89e358998f72db",
                "md5": "a8ba819e1d993a66fcfbd45ee85f0e9d",
                "sha256": "0e62f6656507994bb2132ead634005ba0f7c796ba3d91aa87e2e32523e42fca9"
            },
            "downloads": -1,
            "filename": "e3md-0.2.0.tar.gz",
            "has_sig": false,
            "md5_digest": "a8ba819e1d993a66fcfbd45ee85f0e9d",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.9",
            "size": 30116,
            "upload_time": "2025-07-20T21:42:22",
            "upload_time_iso_8601": "2025-07-20T21:42:22.753425Z",
            "url": "https://files.pythonhosted.org/packages/ca/c4/7bbaa7fd3ea04056799c6a02a40570d6456d79536465bd89e358998f72db/e3md-0.2.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-07-20 21:42:22",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "muhrin",
    "github_project": "e3md",
    "github_not_found": true,
    "lcname": "e3md"
}
        
Elapsed time: 1.62157s