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Install

Install this package:

emerge -a dev-python/pymoc

If the package is masked, you can unmask it using the autounmask tool or standard emerge options:

autounmask dev-python/pymoc

Or alternatively:

emerge --autounmask-write -a dev-python/pymoc

Package Information

Description:

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.

Homepage:

http://pymoc.readthedocs.io

License:

GPL-3

Versions

Metadata

Description

• 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.

Maintainers

• Gentoo Astronomy Project (sci-astronomy@gentoo.org) - Type: project
• Astro Benzene (universebenzene@sina.com) - Type: person

Upstream

• Remote IDs:
  • pypi: pymoc
  • github: grahambell/pymoc

<pkgmetadata>
	<maintainer type="project">
		<email>sci-astronomy@gentoo.org</email>
		<name>Gentoo Astronomy Project</name>
	</maintainer>
	<maintainer type="person">
		<email>universebenzene@sina.com</email>
		<name>Astro Benzene</name>
	</maintainer>
	<longdescription lang="en">
		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.
	</longdescription>
	<upstream>
		<remote-id type="pypi">pymoc</remote-id>
		<remote-id type="github">grahambell/pymoc</remote-id>
	</upstream>
</pkgmetadata>

Lint Warnings

• [Error] Missing md5-cache for ebuild pymoc-0.5.2

Manifest