# <span style="color:#555"><span style="color:#A62B17">**Mo**</span>vement A<span style="color:#A62B17">**nalys**</span>is Libr<span style="color:#A62B17">**a**</span>ry (Monalysa)</span>
Monalysa, _aka_ <u>**Mo**</u>vement a<u>**nalys**</u>is libr<u>**a**</u>ry, is a unified python library for the quantitative analysis of sensorimotor behavior. Monalysa provides a set of data structures, functions, and classes for representing, analyzing, and visualizing movement-related data from different technologies (motion capture, inertial measurement units, robots, force/torque sensors, force plates, etc.).
## Purpose of the library
In the spirit of open science, the monalysa library provides open-source code for a set of commonly used methods, measures, and tools for analyzing movement data. Such a library can be a step towards the standardization of procedures used for movement analysis.
## Who is this library for?
This library is aimed at students, researchers, clinicians and industry professionals working with movement data.
## Installing Monalysa
Monalysa is available through PyPI and can be easily installed using the following pip command.
```console
(.venv) $ pip install monalysa
````
## Read the Documentation
You can find the documentation for the Monalysa library at [https://monalysa.readthedocs.io/en/latest/](https://monalysa.readthedocs.io/en/latest/).
## Contributors
Sivakumar Balasubramanian, Tanya Subash, Alejandro Melendez-Calderon, Camila Shirota.
Raw data
{
"_id": null,
"home_page": "https://github.com/siva82kb/monalysa",
"name": "monalysa",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.9,<4.0",
"maintainer_email": "",
"keywords": "movement analysis,biomechanics,neurorehabilitation,sport science",
"author": "Sivakumar Balasubramanian (Siva)",
"author_email": "siva82kb@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/fc/96/83a1881280378a4ad02119b7f3722f71563f191f4b7d0c8c671eecbec18e/monalysa-0.2.0.tar.gz",
"platform": null,
"description": "# <span style=\"color:#555\"><span style=\"color:#A62B17\">**Mo**</span>vement A<span style=\"color:#A62B17\">**nalys**</span>is Libr<span style=\"color:#A62B17\">**a**</span>ry (Monalysa)</span>\n\nMonalysa, _aka_ <u>**Mo**</u>vement a<u>**nalys**</u>is libr<u>**a**</u>ry, is a unified python library for the quantitative analysis of sensorimotor behavior. Monalysa provides a set of data structures, functions, and classes for representing, analyzing, and visualizing movement-related data from different technologies (motion capture, inertial measurement units, robots, force/torque sensors, force plates, etc.).\n\n## Purpose of the library\nIn the spirit of open science, the monalysa library provides open-source code for a set of commonly used methods, measures, and tools for analyzing movement data. Such a library can be a step towards the standardization of procedures used for movement analysis.\n\n## Who is this library for?\nThis library is aimed at students, researchers, clinicians and industry professionals working with movement data.\n\n## Installing Monalysa \nMonalysa is available through PyPI and can be easily installed using the following pip command.\n```console\n(.venv) $ pip install monalysa \n````\n\n## Read the Documentation\nYou can find the documentation for the Monalysa library at [https://monalysa.readthedocs.io/en/latest/](https://monalysa.readthedocs.io/en/latest/).\n\n## Contributors\nSivakumar Balasubramanian, Tanya Subash, Alejandro Melendez-Calderon, Camila Shirota.",
"bugtrack_url": null,
"license": "MIT",
"summary": "A unified library for quantitative movement analysis.",
"version": "0.2.0",
"project_urls": {
"Homepage": "https://github.com/siva82kb/monalysa",
"Repository": "https://github.com/siva82kb/monalysa"
},
"split_keywords": [
"movement analysis",
"biomechanics",
"neurorehabilitation",
"sport science"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "7a5947ca6a5a1bfa19a4e1f986027b458463f912528e0a9d16b8336324d2ada7",
"md5": "f8a6d18b716193188f49824c67728f31",
"sha256": "dce81c8890aa6e62cf6a3af4195a1b358560e1dffc98e46dba7ac21611aa0aa4"
},
"downloads": -1,
"filename": "monalysa-0.2.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "f8a6d18b716193188f49824c67728f31",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9,<4.0",
"size": 25267,
"upload_time": "2024-01-15T09:31:38",
"upload_time_iso_8601": "2024-01-15T09:31:38.054368Z",
"url": "https://files.pythonhosted.org/packages/7a/59/47ca6a5a1bfa19a4e1f986027b458463f912528e0a9d16b8336324d2ada7/monalysa-0.2.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "fc9683a1881280378a4ad02119b7f3722f71563f191f4b7d0c8c671eecbec18e",
"md5": "f2e3618b8f971f1a2bfec5987ba6f711",
"sha256": "94af395fd0c564e31d23fcc82837c4a45b1fc31b33ef0cfc5d84d823220f7f4b"
},
"downloads": -1,
"filename": "monalysa-0.2.0.tar.gz",
"has_sig": false,
"md5_digest": "f2e3618b8f971f1a2bfec5987ba6f711",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9,<4.0",
"size": 19034,
"upload_time": "2024-01-15T09:31:39",
"upload_time_iso_8601": "2024-01-15T09:31:39.910170Z",
"url": "https://files.pythonhosted.org/packages/fc/96/83a1881280378a4ad02119b7f3722f71563f191f4b7d0c8c671eecbec18e/monalysa-0.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-15 09:31:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "siva82kb",
"github_project": "monalysa",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [],
"lcname": "monalysa"
}