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authorV3n3RiX <venerix@redcorelinux.org>2017-10-09 18:53:29 +0100
committerV3n3RiX <venerix@redcorelinux.org>2017-10-09 18:53:29 +0100
commit4f2d7949f03e1c198bc888f2d05f421d35c57e21 (patch)
treeba5f07bf3f9d22d82e54a462313f5d244036c768 /dev-python/pymoc/metadata.xml
reinit the tree, so we can have metadata
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+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
+<pkgmetadata>
+ <maintainer type="project">
+ <email>sci-astronomy@gentoo.org</email>
+ <name>Gentoo Astronomy Project</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>