Skip to main content

Python package to handle data gathered from biologgers (GPS, TDR, AXY) attached to central-place foraging seabirds. The idea is to make movement ecology data a bit easier to process.

Project description

cpforager text logo with colors


github stars github forks github issues github pull request github last commit
license python 3.11+
pypi version pypi downloads


Are you a scientist involved in movement ecology working with biologging data collected from central-place foraging seabirds? cpforager is a Python package designed to help you manipulate, process, analyse and visualise the biologging datasets with ease.


The main objectives of cpforager are :

  1. Efficiently handle large-scale biologging datasets, including high-resolution sensor data (e.g. accelerometers).
  2. Provide a modular and extensible architecture, allowing users to tailor the code to their specific research needs.
  3. Facilitate a smooth transition to Python for movement ecology researchers familiar with other languages (e.g. R).

cpforager package supports various biologging sensor types commonly used in movement ecology and provides the following core classes:

  • GPS : for handling position recordings.
  • TDR : for handling pressure recordings.
  • AXY : for handling tri-axial acceleration recordings at high resolution combined with lower resolution position and pressure recordings.
  • GPS_TDR : for handling position and pressure recordings.

cpforager also allows to deal with a list of sensors using the following classes:

  • GPS_Collection : for working with datasets composed of multiple GPS loggers.
  • TDR_Collection : for working with datasets composed of multiple TDR loggers.
  • AXY_Collection : for working with datasets composed of multiple AXY loggers.
  • GPS_TDR_Collection : for working with datasets composed of multiple GPS_TDR loggers.

Each class automatically enhances raw data but also computes key features specific to each biologger (e.g. trip segmentation for GPS, dive segmentation for TDR, ODBA calculation for AXY). They are also accompanied with methods for data processing and visualisation.


cpforager logo with colors

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

cpforager-1.3.0.tar.gz (62.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cpforager-1.3.0-py3-none-any.whl (78.0 kB view details)

Uploaded Python 3

File details

Details for the file cpforager-1.3.0.tar.gz.

File metadata

  • Download URL: cpforager-1.3.0.tar.gz
  • Upload date:
  • Size: 62.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.3

File hashes

Hashes for cpforager-1.3.0.tar.gz
Algorithm Hash digest
SHA256 f8c2f43f6015cf3163fcf78773e98ef37048aca8ec2d10c958f5d8a786872415
MD5 a9d5a8ae8965a813bf838d50ee88c8b0
BLAKE2b-256 135e8d17035423e83e783ff12dcb8f6b57d54c42ff2721cb9b1d860c35d18c9a

See more details on using hashes here.

File details

Details for the file cpforager-1.3.0-py3-none-any.whl.

File metadata

  • Download URL: cpforager-1.3.0-py3-none-any.whl
  • Upload date:
  • Size: 78.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.3

File hashes

Hashes for cpforager-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a3d4a81f7d20b0a1ee0168d1e70ce763f3f9c9419066ede7b384edc326121ad3
MD5 46589cb0192ad03199f2836184ff9578
BLAKE2b-256 4d043521d8fe307e83d9ada6eab9b7c63577edf83798646c4dcc586b3a1f1a3a

See more details on using hashes here.

Supported by

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