How to Install and Uninstall python3-pymoc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 16,2024

1. Install "python3-pymoc" package

Please follow the step by step instructions below to install python3-pymoc on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                python3-pymoc
            
                    
    
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2. Uninstall "python3-pymoc" package

Please follow the guidance below to uninstall python3-pymoc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python3-pymoc
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-pymoc package on Ubuntu 21.10 (Impish Indri)

Package: python3-pymoc
Architecture: all
Version: 0.5.0-5
Priority: optional
Section: universe/python
Source: pymoc
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Astro Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 84
Depends: python3-astropy, python3:any
Suggests: python3-healpy
Filename: pool/universe/p/pymoc/python3-pymoc_0.5.0-5_all.deb
Size: 18112
MD5sum: 91575c7f5567574611c527b1e69594d8
SHA1: 62cb16aea30b61f3f55ae9e61f21255ace21fd5a
SHA256: abc89f50e2fe35fdc4c5640b3681d9b5a595b8a141e9961c43f579fa9c322932
SHA512: 179ba3be742c273079a8df0bc6f2800abddb6dc81303949d2f43685192107c2b091cdf71d78e6c78ceb3799403ed09f10f2bfe04db5f1ad692910a7210091ac0
Homepage: https://github.com/grahambell/pymoc
Description-en: Python Multi-Order Coverage maps for Virtual Observatory
PyMOC provides a Python compatible library for handling MOCs.
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Frequently astronomical survey catalogues or images are sparse and
cover only a small part of the sky. In a Multi-Order Coverage map
the extent of data in a particular dataset is cached as a
pre-calculated mask image. The hierarchical nature enables fast
boolean operations in image space, without needing to perform complex
geometrical calculations. Services such as VizieR generally offer the
MOC masks, allowing a faster experience in graphical applications
such as Aladin, or for researchers quickly needing to locate which
datasets may contain overlapping coverage.
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The MOC mask image itself is tessellated and stored in NASA HealPix
format, encoded inside a FITS image container. Using the HealPix
(Hierarchical Equal Area isoLatitude Pixelization) tessellation
method ensures that more precision (pixels) in the mask are available
when describing complex shapes such as approximating survey or
polygon edges, while only needing to store a single big cell/pixel
when an coverage is either completely inside, or outside of the mask.
Catalogues can be rendered on the mask as circles.
Description-md5: dd08809f5fe35817a256e4e1bd2a51ca