MOCPy is a Python library allowing easy creation and manipulation of MOCs (Multi-Order Coverage maps).
MOC is an IVOA standard enabling description of arbitrary sky regions. Based on the HEALPix sky tessellation, it maps regions on the sky into hierarchically grouped predefined cells.
An experimental support for TMOC (temporal MOC) has been added since version 0.4.0. It allows creation, parsing and comparison of TMOCs.
Space & Time coverages (STMOC) are an extension of MOC to add time information. It is possible to get a TMOC by querying a STMOC with a MOC and/or get a MOC by querying a STMOC with a TMOC.
Please check the mocpy's documentation for more details about installing MOCPy and using it.
For a command line tool, see the moc-cli.
For more information about the MOCPy Rust core, see the moc crate.
MOC.MAX_ORDER` and `TimeMOC.MAX_ORDER
replace the formerIntervalSet.HPX_MAX_ORDER
andIntervalSet.TIME_MAX_ORDER
MOC.to_depth29_ranges
is now a public method replacing the former privateIntervalSet.nested
and addition ofTimeMOC.to_depth61_ranges
for a time counterpart
MOC.contains_skycoords
andMOC.contains_lonlat
replaceMOC.contains
(contains
will be removed in v1.0.0)TimeMOC.contains_with_timeresolution
has been added with the previous behaviour ofTimeMOC.contains
from_uniq` removed from `IntervalSet
and added toMOC
MOC.from_healpix_cells
now requires themax_depth
argument, the depth of the MOC we want to createWorld2ScreenMPL
has been renamedWCS
We strongly recommend to work in an environnement
- from pip
pip install mocpy
- from conda
conda install -c conda-forge mocpy
- from this repository
git clone https://github.com/cds-astro/mocpy.git cd mocpy pip install .
Note that the point is important.
The example notebooks require additional dependencies. They can be installed with
pip install mocpy[notebooks]
Wheels that run in pyodide can be downloaded from this repository assets. This is not fully tested.