A Python-based application that helps you view, analyze and interact with LMA (Lightning Mapping Array) data. This application replicates XLMA's essential features while operating significantly faster. It is not meant as an alternative and does not offer full functionality. We suggest checking out the PyXLMA project for that purpose. Our mission is to perform the most used tasks of viewing, selection, and extracting flash information quickly and reliably with a modern UI.
- Instructions for installing the git lfs by operating systems here
- Clone the repository using:
git clone https://github.com/krishnacalindi/hlma.gitand move into it:cd hlma. - Install poetry using
pip install poetry. - Ensure poetry is configured to create virtual environments inside project folder using
poetry config virtualenvs.in-project true. - Install dependencies using
poetry install. - Run the app using
poetry run python hlma.py.
- GUI based: we offer a GUI heavily influenced by feedback from LMA scientists.
- Filtering: We offer the ability to filter the data using specified filter fields, or selecting with a polygon.
- Plotting: We provide a suite of map features, map options and colorcet's entire collection of named linear colormaps.
- Exporting: You can export LMA data as .dat files that are compatible with XLMA and lmatools and parquet files for further processing.
- States: You can save the state of the application at any point, and use the saved file to get back to where you were!
- Flash algorithms: We offer simple dot-to-dot and McCaul flash algorithm via a custom implementation. This feature is still in beta, please be cautious of errors.
If you would like to contribute please reach out to Dr.Timothy Logan.
McCaul , E. W., S. J. Goodman, K. M. LaCasse, and D. J. Cecil, 2009: Forecasting Lightning Threat Using Cloud-Resolving Model Simulations. Wea. Forecasting, 24, 709–729, https://doi.org/10.1175/2008WAF2222152.1.