Tracking facility to track rainfall and other non-continous data.
Project description
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 package based on the
TITAN methodology by Dixon and Wiener. 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 that has been developed by a team of
researchers at Monash University Raut et al. 2020.
Installation
The tintX
package can be installed using pip:
python -m pip install tintx
if you don't have root access add the --user
flag for a local installation.
Usage
Documentation can be found on the official document page of this library. If you want to just test 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 you contributions can bee added as fast as possible to the tintX:
- Create a fork of this repository and clone this fork (not the original code)
- 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
- make lint
- make test
- make docs
- 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 have 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 fundering number CE170100023.
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