32 lines
1.6 KiB
XML
32 lines
1.6 KiB
XML
<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
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<pkgmetadata>
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<maintainer type="project">
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<email>sci-astronomy@gentoo.org</email>
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<name>Gentoo Astronomy Project</name>
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</maintainer>
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<longdescription lang="en">
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Frequently astronomical survey catalogues or images are sparse and
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cover only a small part of the sky. In a Multi-Order Coverage map
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the extent of data in a particular dataset is cached as a
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pre-calculated mask image. The hierarchical nature enables fast
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boolean operations in image space, without needing to perform complex
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geometrical calculations. Services such as VizieR generally offer the
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MOC masks, allowing a faster experience in graphical applications
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such as Aladin, or for researchers quickly needing to locate which
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datasets may contain overlapping coverage.
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The MOC mask image itself is tessellated and stored in NASA HealPix
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format, encoded inside a FITS image container. Using the HealPix
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(Hierarchical Equal Area isoLatitude Pixelization) tessellation
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method ensures that more precision (pixels) in the mask are available
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when describing complex shapes such as approximating survey or
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polygon edges, while only needing to store a single big cell/pixel
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when an coverage is either completely inside, or outside of the mask.
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Catalogues can be rendered on the mask as circles.
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</longdescription>
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<upstream>
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<remote-id type="pypi">pymoc</remote-id>
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<remote-id type="github">grahambell/pymoc</remote-id>
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</upstream>
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</pkgmetadata>
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