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-0.0.13.tar.gz (1.2 MB view details)

Uploaded Source

Built Distribution

ecosound-0.0.13-py3-none-any.whl (183.4 kB view details)

Uploaded Python 3

File details

Details for the file ecosound-0.0.13.tar.gz.

File metadata

  • Download URL: ecosound-0.0.13.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.11.3 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.63.0 CPython/3.9.11

File hashes

Hashes for ecosound-0.0.13.tar.gz
Algorithm Hash digest
SHA256 19a2db25e38e6eb87e96d324c4b8ca52bb0367c0ace86445931e5e535838ec7a
MD5 94587130a3088a8a610c4e62a4ef8dc4
BLAKE2b-256 573d7fee0627dbabf2e47114eefad6018b76113064f5897c8160b578b5ff0327

See more details on using hashes here.

File details

Details for the file ecosound-0.0.13-py3-none-any.whl.

File metadata

  • Download URL: ecosound-0.0.13-py3-none-any.whl
  • Upload date:
  • Size: 183.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.11.3 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.63.0 CPython/3.9.11

File hashes

Hashes for ecosound-0.0.13-py3-none-any.whl
Algorithm Hash digest
SHA256 dd24f200e73a54b808893dcf71086d1a0ed9985417a6d56eddcc06af9c2b5ded
MD5 92cc3a87380bcb02e912d6f65d1799cf
BLAKE2b-256 03196092dbbc584b1325e4f969d6be6e8de1af674514cd337e9db9f8f0c015ff

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