tintx 2024.8.1

Description:

tintx 2024.8.1

TintX (Tint is not TITAN) tracking algorithm for any kind of input data








TintX is an adaptation of the tint tracking algorithm.
Tint and tintX are easy-to-use storm cell tracking packages. While Tint is meant
to be applied to radar data using the
py-ART toolkit tintX can
be applied with any data - for example output from numerical weather prediction
models. The original tracking algorithm has been developed by a team of
researchers at Monash University Raut et al. 2020.
Installation
The tintX package can be installed using the conda-froge conda channel:
conda install -c conda-forge tintx

Alternatively the package can be installed with pip:
python -m pip install tintx

Usage
Documentation can be found on the
official documentation page of this
library.
If you just want to try the usage and play with tracking data you can follow
this link
to launch and familiarise yourself with the tracking by executing one of the
example notebooks.
Contributing
Any contributions to improve this software in any way are welcome. Below is a
check list that makes sure your contributions can be added as fast as
possible to tintX:

Create a fork of this repository
and clone this fork (not the original code)
Install the code in development mode: python3 -m pip install -e .[dev]
Create a new branch in the forked repository git checkout -b my-new-branch
Add your changes
Make sure all tests are sill running. To do so run the following commands

tox


Create a new pull request to the main branch of the
original repository.

Adding new Jupyter examples
You can add more examples to the
docs/source documentation folder.
Because notebooks are executed automatically by the unit tests GitHub workflow,
you should make sure that any additional dependencies imported in the notebook
are added to the docs section in the
setup.py.
All notebooks should be run with a kernel called tintx to install a new
kernel named tintx run the following command in the root directory
of the cloned repository:
python -m ipykernel install --name tintx --display-name "tintX kernel"\
--env DATA_FIELS $PWD/docs/source/_static/data --user

Make also sure to add additional link(s) to the
notebook readme file.
Acknowledgements
This work is the adaptation of tracking code in R created by Bhupendra Raut
who was working at Monash University, Australia in the Australian Research
Council's Centre of Excellence for Climate System Science led by
Christian Jakob. This work was supported by the Department of
Energy, Atmospheric Systems Research (ASR) under Grant DE-SC0014063,
“The vertical structure of convective mass-flux derived from modern radar
systems - Data analysis in support of cumulus parametrization”
The development of this software was funded by the Australian Research
Council's Centre of Excellence for Climate Extremes under the funding
number CE170100023.