Skip to main content

LapTrack

Project description

PyPI Status Python Version License

Read the documentation at https://laptrack.readthedocs.io/ Tests Codecov

pre-commit Black Zenodo

Features

Provides a robust particle tracking algorithm using the Linear Assignment Problem, with various cost functions for linking.

Installation

You can install LapTrack via pip from PyPI:

$ pip install laptrack

Usage

Please see the Usage for details.

Contributing

Contributions are very welcome. To learn more, see the Contributor Guide.

License

Distributed under the terms of the The 3-Clause BSD License, LapTrack is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

Credits

Citation

If you use this program for your research, please cite it and help us build more.

@misc{laptrack,
   author = {Yohsuke T. Fukai},
   title = {laptrack},
   year  = {2021},
   url   = {https://doi.org/10.5281/zenodo.5519537},
}

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

laptrack-0.1.6.tar.gz (12.6 kB view details)

Uploaded Source

Built Distribution

laptrack-0.1.6-py3-none-any.whl (12.5 kB view details)

Uploaded Python 3

File details

Details for the file laptrack-0.1.6.tar.gz.

File metadata

  • Download URL: laptrack-0.1.6.tar.gz
  • Upload date:
  • Size: 12.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for laptrack-0.1.6.tar.gz
Algorithm Hash digest
SHA256 6215f7aabe7816941fe665d2fbd7f6437713a987021621bccf9e2da82358d19e
MD5 04777654d20d5da8e1aad658fa1a36be
BLAKE2b-256 f4cdf89bcc08d5a44a8141bc2f1c1bfa65986ea8db525a09c7f2af2277b7afaa

See more details on using hashes here.

File details

Details for the file laptrack-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: laptrack-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 12.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for laptrack-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 4274fcb9693b0133f059681b9d1fb846f4762d891be20e0bc17fd123c3b78ad0
MD5 a9d74088853980714a9fe182a97d8b3f
BLAKE2b-256 af718871c841e2a9429994a015e55e7d488c5264d454400ec6a04c8737b649fc

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