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Observatoire Astronomique de Strasbourg, Université de Strasbourg, CNRS, Strasbourg
Address:
France
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Abstract Reference: 30897
Identifier: P6.2
Presentation: Poster presentation
Key Theme: 6 Python in Astronomy

MOCPy, a Python library to manipulate spatial coverage maps

Authors:
Boch Thomas

We will present MOCPy, a Python library to handle and manipulate MOC (Multi Order Coverage maps). MOC is a Virtual Observatory standard - based on the HEALPix tessellation - that has proven to be quite useful to describe and compare spatial coverage of datasets. Our library allows for easy creation of MOC objects from a list of sources or for a given VizieR table with positions. Intersections of coverages can be computed and VizieR tables data can be efficiently queried to retrieve only rows inside a given MOC coverage. Eventually, we will also discuss how we use Jupyter notebooks running on mybinder.org service to provide with interactive examples of MOCPy usage.