Skip to main content

A unified library for quantitative movement analysis.

Project description

Movement Analysis Library (Monalysa)

Monalysa, aka Movement analysis library, 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.

(.venv) $ pip install monalysa  

Read the Documentation

You can find the documentation for the Monalysa library at https://monalysa.readthedocs.io/en/latest/.

Contributors

Sivakumar Balasubramanian, Tanya Subash, Alejandro Melendez-Calderon, Camila Shirota.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

monalysa-0.2.1.tar.gz (19.3 kB view details)

Uploaded Source

Built Distribution

monalysa-0.2.1-py3-none-any.whl (25.5 kB view details)

Uploaded Python 3

File details

Details for the file monalysa-0.2.1.tar.gz.

File metadata

  • Download URL: monalysa-0.2.1.tar.gz
  • Upload date:
  • Size: 19.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.9.12 Darwin/23.5.0

File hashes

Hashes for monalysa-0.2.1.tar.gz
Algorithm Hash digest
SHA256 3d20ce419d5a5de35ab2ae8a499ae5e39a2a3e3c70d0a33dbc62ef73e417428d
MD5 a161aa1425c99a700c94819f20eb6e8e
BLAKE2b-256 34cc04763c68032b40552022e93e765cd52e5a6a384797814afc6f3e13253719

See more details on using hashes here.

File details

Details for the file monalysa-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: monalysa-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 25.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.9.12 Darwin/23.5.0

File hashes

Hashes for monalysa-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2bb4909ebb1d962ba0d88e49ffc8b2f7898dcb3b87b3b9aee5ecfb8678dd3967
MD5 7dafdbde278a3690ad9bfa8c7d482e61
BLAKE2b-256 3263207bdf087be2771871640e82ef5cc86717c98742aaf4941da65faacf94ba

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page