Skip to main content

Python toolkit for analysing passive acoustic data

Project description

docssource_staticecosound_logo_small.png

Welcome to ecosound!

https://img.shields.io/pypi/v/ecosound.svg Documentation Status https://travis-ci.com/xaviermouy/ecosound.svg?branch=master https://coveralls.io/repos/github/xaviermouy/ecosound/badge.svg?branch=master

Ecosound is an open source python package to facilitate the analysis of passive acoustic data. It includes modules for manual annotation processing and visualization, automatic detection, signal classification, and localization. It heavily relies on libraries such as xarray, pandas, numpy and scikit-learn. Under the hood it also uses dask which supports the processing of large data sets that don’t fit into memory, and makes processing scalable through distributed computing (on either local clusters or on the cloud). Outputs from ecosound are compatible with popular bioacoustics software such as Raven and PAMlab.

Status

Ecosound is very much a work in progress and is still under heavy development. At this stage, it is recommended to contact the main contributor before using ecosound for your projects.

Documentation

No documentation yet, but we’re working on it… https://ecosound.readthedocs.io

Contributors

Xavier Mouy (@XavierMouy) leads this project as part of his PhD in the Juanes Lab at the University of Victoria (British Columbia, Canada).

Credits

License

Ecosound is licensed under the open source BSD-3-Clause License.

History

0.0.0 (2020-11-20)

  • First release on PyPI.

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

ecosound-0.0.24.tar.gz (1.4 MB view details)

Uploaded Source

Built Distribution

ecosound-0.0.24-py3-none-any.whl (199.8 kB view details)

Uploaded Python 3

File details

Details for the file ecosound-0.0.24.tar.gz.

File metadata

  • Download URL: ecosound-0.0.24.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for ecosound-0.0.24.tar.gz
Algorithm Hash digest
SHA256 cbfb77d54b860ecb8e42080218f99b9d2976f146a08d3521b15239dbd4828014
MD5 6bd7ee8941ba1667e5955c52a5c375bb
BLAKE2b-256 1efa920ccb73d34ce8a72b15b5174711459c737e86ebff8558df2119ae12883e

See more details on using hashes here.

File details

Details for the file ecosound-0.0.24-py3-none-any.whl.

File metadata

  • Download URL: ecosound-0.0.24-py3-none-any.whl
  • Upload date:
  • Size: 199.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for ecosound-0.0.24-py3-none-any.whl
Algorithm Hash digest
SHA256 473635aa3b4f39eefc09bcc9ef97a53da45add70c5f423c17b5222bb856a0afa
MD5 d90de6df2a9fd786473149289632ff5b
BLAKE2b-256 2a579a59ac6dbe388d53c8966afbee7efa80c6f92ac37c0dcd6d2a29b4a22874

See more details on using hashes here.

Supported by

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