AntADatabase#
This Python module provides an efficient SQLite database for browsing, visualizing and processing Internal Reflecting Horizons (isochrones) across Antarctica, curated by the AntArchitecture action group. It is specifically designed for ice dynamic modelers who need a fast, memory-efficient data structure to constrain their models.
SQLite Database#
The database uses SQLite for efficient indexing. Data is sourced from the associated DOIs and stored as binary DataFrame files for each layer (IRH) and trace ID. This structure enables:
Browsing by author (region), layer age, or trace ID.
Memory efficiency: Only relevant data is read when needed.
Fast read performance: Lightweight and optimized for speed.
Datasets currently included:#
Winter et al. 2018, (https://doi.org/10.1594/PANGAEA.895528)
Cavitte et al. 2020, (https://doi.org/10.15784/601411)
Beem et al. 2021, (https://doi.org/10.15784/601437)
Wang et al. 2023, (https://doi.org/10.1594/PANGAEA.958462)
Mulvaney et al. 2023, (https://doi.pangaea.de/10.1594/PANGAEA.963470)
Chung et al. 2023 (https://doi.pangaea.de/10.1594/PANGAEA.957176)
Sanderson et al. 2024, (https://doi.org/10.5285/cfafb639-991a-422f-9caa-7793c195d316)
Franke et al. 2025, (https://doi.org/10.1594/PANGAEA.973266)
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Figures created using plotting functions from this module
Key Features#
Efficient SQLite indexing
Quick visualization on Antarctica map
Generate lazy data for later use
Acknowledgments#
I am developing this tool as part of my PhD project, which is funded by the Swiss National Science Foundation (grant no. 211542, Project CHARIBDIS) Any data used through this database should be cited at source. For this, use the DOI provided in the metadata. If you used this tool for your work and this was useful, please cite this module, so other people get to know that it exists.
Tutorial#
To get started with this module and get an overview of the features and capabilities, visit: