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-1.1.1.tar.gz (64.1 MB view details)

Uploaded Source

Built Distribution

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

cpforager-1.1.1-py3-none-any.whl (76.6 kB view details)

Uploaded Python 3

File details

Details for the file cpforager-1.1.1.tar.gz.

File metadata

  • Download URL: cpforager-1.1.1.tar.gz
  • Upload date:
  • Size: 64.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.3

File hashes

Hashes for cpforager-1.1.1.tar.gz
Algorithm Hash digest
SHA256 ab543907c4b25ac31c09c670d22e348791224b076dcc990da1b5884d8a6c4185
MD5 40eec10edb96a74abd7787f39516c553
BLAKE2b-256 b40ee3dda2490845bac884b200425fd3a0bd15f51978789ad4fd39860e58c364

See more details on using hashes here.

File details

Details for the file cpforager-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: cpforager-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 76.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.3

File hashes

Hashes for cpforager-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1a8e7c02278df59f2ac82744e1afd14fdf45172e6212c3574c3cc2966509c1a8
MD5 ff78236bdd579147702b456a20f3fc96
BLAKE2b-256 d2c66d7c1f0fc409d0524e7e84887e0d6d21d799d9810627dc25335b488ea47b

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