A Python package for generating tropical cyclone tracks.
Project description
TCTrack
TCTrack is a Python library providing bindings to tracking algorithms for tropical cyclones in an accessible manner to generate high-quality and FAIR output data.
It can be used for tracking cyclones in simulations and observations, and to compare the output of different algorithms for a variety of data sources.
Installation
Dependencies
The package requires Python 3 (>=3.10).
Package Installation
We recommend using a Conda virtual environment for TCTrack in order to simplify the installation of dependencies (cf-python, esmpy/ESMF, UDUNITS).
conda create -n tctrack-env -c conda-forge cf-python cf-plot udunits2 esmpy
conda activate tctrack-env
When finished using TCTrack this can be turned off with conda deactivate.
TCTrack can then be installed using pip:
pip install tctrack
See the documentation. for futher details about installation and dependencies, including how to install the individual tracking algorithms.
Using TCTrack
Details of how to use TCTrack can be found in the getting-started documentation online.
New users may wish to follow the TCTrack tutorial
using the scripts in the tutorial/
directory.
For a complete description of the library API see API documentation.
Contributing
Contributions and collaborations are welcome.
For bugs, feature requests, and clear suggestions for improvement please open an issue.
If you have added something to TCTrack that would be useful to others, or can address an open issue, please fork the repository and open a pull request.
Additional dependencies for deleopment can be installed as follows:
pip install --editable .[dev]
Full details for contribution and developers can be found in the online documentation.
Code of Conduct
Everyone participating in the TCTrack project, and in particular in the issue tracker, pull requests, and social media activity, is expected to treat other people with respect and, more generally, to follow the guidelines articulated in the Python Community Code of Conduct.
License
Copyright © ICCS
TCTrack is distributed under the GPL 3.
Acknowledgments
This work was funded by a philantropic donation to the University of Cambridge from INIGO Insurance as part of the InSPIRe project.
The TCTrack logo was designed by Jack Atkinson - @jatkinson1000.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file tctrack-0.2.tar.gz.
File metadata
- Download URL: tctrack-0.2.tar.gz
- Upload date:
- Size: 514.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2d3e6c4d87bd92967121f5443387d3bfd90c889cc2867f3bda426cff66ec30e5
|
|
| MD5 |
d2af4a79041601921f60b28cc82b1e26
|
|
| BLAKE2b-256 |
c0ce57031801a1d8fc04644a4b9b1d3a282a9ad05c03e8ba76878c1bbc20db70
|
File details
Details for the file tctrack-0.2-py3-none-any.whl.
File metadata
- Download URL: tctrack-0.2-py3-none-any.whl
- Upload date:
- Size: 52.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2255d869a77aeb43c97bd44014b7e9b412c8eef2eaf4dea2004e8120b71ee175
|
|
| MD5 |
41d85d3c8a2382e0c1ecceb82a306e05
|
|
| BLAKE2b-256 |
b2e8af714f5402a5a1954d8fba7f3c19b262fb299597c72aead92b6dabfa8bf8
|