pymoctool

Pymoctool Installation On A Debian, Ubuntu, Kali, Fedora And Raspbian

Pymoctool Installation On A Debian, Ubuntu, Kali, Fedora And Raspbian

pymoctool

Python Multi-Order Coverage maps tool for Virtual Observatory

Maintainer: Debian Astro Team



Section: science

Install pymoctool

  • Debian apt-get install pymoctool Click to copy
  • Ubuntu apt-get install pymoctool Click to copy
  • Kali Linux apt-get install pymoctool Click to copy
  • Fedora dnf install pymoctool Click to copy
  • Raspbian apt-get install pymoctool Click to copy

pymoctool

Python Multi-Order Coverage maps tool for Virtual Observatory

'pymoctool' is a command-line Python-based library for manipulating Multi-Order Coverage maps (MOCs). 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. 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. It is written in Python 2/3 and uses the PyMOC library.

python3-pymoc

Python 3 Multi-Order Coverage maps for Virtual Observatory

PyMOC provides a Python 3-compatible library for handling MOCs. 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. 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.

Install the latest version of pymoctool in Debian, Ubuntu, Kali, Fedora and Raspbian from terminal. To install the pymoctool just copy the above command for your OS and run into terminal. After you run the command it will grab the latest version of pymoctool from the respository and install it in your computer/server.