monalysa


Namemonalysa JSON
Version 0.2.1 PyPI version JSON
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home_pagehttps://github.com/siva82kb/monalysa
SummaryA unified library for quantitative movement analysis.
upload_time2024-07-09 06:37:57
maintainerNone
docs_urlNone
authorSivakumar Balasubramanian (Siva)
requires_python<4.0,>=3.9
licenseMIT
keywords movement analysis biomechanics neurorehabilitation sport science
VCS
bugtrack_url
requirements pip numpy pandas matplotlib scipy
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # <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.
            

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