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MOCPy is a python package that allows the manipulation of Time-Space Multi-Order Coverage maps. These maps are defined by an International Virtual Observatory standard (https://ivoa.net/documents/MOC/20220727/index.html).
Concretely, time and space (on the sky sphere) are described by cells of different coarseness, and a MOC is an ensemble of these cells.
Here are three MOCs (plotted with MOCPy) describing regions of the sky :
This format is particularly useful to perform operations (union, difference, ...) on time and space regions.
Here is the union of the previous MOCs:
Typical uses of the library are:
estimation of telescopes field of view (uses space information)
knowing if a satellite has observed a short-lived event in the sky (uses time and space information)
Scope
Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):
We were an astropy-affiliated package with the former system (pre-2024).
For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):
Who is the target audience and what are scientific applications of this package?
The audience is astronomers. From a quick scanning of the libraries that use MOCPy on github, we identify three major poles:
big astronomical databases. They either cross-match astronomical catalogs between each other, or they are building and interrogating databases indexed with the HEALPix tesselation (the one used for MOC space cells).
telescope crew that use MOCPy to calculate field of view and plan observations
Are there other Python packages that accomplish the same thing? If so, how does yours differ?
There is pymoc (https://github.com/grahambell/pymoc), a pure python implementation. It works, but the API is more minimal (no creation of MOCs from shapes, no check to see if a sky-coordinate falls within a MOC, only Space-MOCs no Time-MOCs, no plotting utilities, no multi-threading, ...)
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The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
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Submitting Author: (@ManonMarchand)
All current maintainers: (@fxpineau, @tboch, @bmatthieu3, @ManonMarchand)
Package Name: MOCPy
One-Line Description of Package: MOCPy allows to read/write, and create Multi-Order Coverage Maps
Repository Link: https://github.com/cds-astro/mocpy
Version submitted: 0.17.1
EiC: @coatless
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD
Code of Conduct & Commitment to Maintain Package
Description
MOCPy is a python package that allows the manipulation of Time-Space Multi-Order Coverage maps. These maps are defined by an International Virtual Observatory standard (https://ivoa.net/documents/MOC/20220727/index.html).
Concretely, time and space (on the sky sphere) are described by cells of different coarseness, and a MOC is an ensemble of these cells.
Here are three MOCs (plotted with MOCPy) describing regions of the sky :
This format is particularly useful to perform operations (union, difference, ...) on time and space regions.
Here is the union of the previous MOCs:
Typical uses of the library are:
Scope
Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):
Domain Specific
Community Partnerships
If your package is associated with an
existing community please check below:
We were an astropy-affiliated package with the former system (pre-2024).
For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):
The audience is astronomers. From a quick scanning of the libraries that use MOCPy on github, we identify three major poles:
There is pymoc (https://github.com/grahambell/pymoc), a pure python implementation. It works, but the API is more minimal (no creation of MOCs from shapes, no check to see if a sky-coordinate falls within a MOC, only Space-MOCs no Time-MOCs, no plotting utilities, no multi-threading, ...)
Technical checks
For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:
Publication Options
JOSS Checks
paper.md
matching JOSS's requirements with a high-level description in the package root or ininst/
.Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.
Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
Confirm each of the following by checking the box.
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Footnotes
Please fill out a pre-submission inquiry before submitting a data visualization package. ↩
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