LESIA Observatoire de Paris-PSL CNRS vopdc cdpp Sorbonne Université cnes Université de Paris

TFCat (Time-Frequency Catalogue): JSON Implementation and Python library. Tutorials.

Tuesday 27 September 2022, by Baptiste Cecconi

This series of tutorials supplements: Cecconi et al. (2022), TFCat (Time-Frequency Catalogue): JSON Implementation and Python library. submitted to Frontiers in Astronomy and Space Sciences.

Link to data repository

Description

TFCat MultiPoint feature and feature processing

This jupyter notebook is showing how to use TFCat together with shapely to process a MultiPoint geometry into a Polygon.

TFCat MultiPolygon feature and data filtering example

This jupyter notebook is showing how to use TFCat together with shapely and das2 to use a MultiPolygon geometry to select data and so statistical analysis.

TFCat Multiple Catalogue Example

This jupyter notebook is showing how to use several TFCat collections together with shapely and das2 to compare the coverage of the catalogues and display them on data.

Acknowledgments

The Europlanet 2024 Research Infrastructure project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871149.
This work used the EGI Infrastructure with the dedicated support of IN2P3-IRES and CESNET-MCC.
Additional funding was provided in France by the Centre National d’\’Etudes Spatiales (CNES),
and Action Spécifique Observatoire Virtuel (ASOV).

References


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