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Cuboid Cartesian Matching
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<h4><a name="CuboidCartesianMatchEngine">7.1.8 <code>2d_cuboid</code>, ...:
Cuboid Cartesian Matching</a></h4>
<p><pre>matcher=2d_cuboid values*='<x> <y>'
params='<error-in-x> <error-in-y>'
tuning='<bin-factor>'</pre>
<blockquote>
<dl>
<dt><strong><code>values*</code>:</strong></dt>
<dd>
<ul>
<li><code>x</code>: Cartesian co-ordinate #1
</li>
<li><code>y</code>: Cartesian co-ordinate #2
</li>
</ul>
</dd>
<dt><strong><code>params</code>:</strong></dt>
<dd>
<ul>
<li><code>error-in-x</code>: Half length of cuboid in Cartesian co-ordinate #1 direction
</li>
<li><code>error-in-y</code>: Half length of cuboid in Cartesian co-ordinate #2 direction
</li>
</ul>
</dd>
<dt><strong><code>tuning</code>:</strong></dt>
<dd>
<ul>
<li><code>bin-factor</code>: Scaling factor to adjust bin size; larger values mean larger bins
</li>
</ul>
</dd>
</dl>
</blockquote>
</p>
<p>The <code>2d_cuboid</code> matcher compares positions
in 2-dimensional Cartesian space in cuboidal cells.
Rows are considered to match if their (<code>x</code>,<code>y</code>)
positions fall within an error cuboid with half-axis lengths
<code>error-in-x</code>, <code>error-in-y</code> of each other.
This kind of match is suitable for grouping items into pixels,
though it's not a very efficient way of doing that.
</p>
<p>Matching in any number of dimensions using N-dimensional hyper-cuboids
can be done by extending this syntax in the obvious way.
</p>
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Anisotropic Cartesian Matching</a><br>
<hr><i>STILTS - Starlink Tables Infrastructure Library Tool Set<br>Starlink User Note256<br>STILTS web page:
<a href="http://www.starlink.ac.uk/stilts/">http://www.starlink.ac.uk/stilts/</a><br>Author email:
<a href="mailto:m.b.taylor@bristol.ac.uk">m.b.taylor@bristol.ac.uk</a><br>Mailing list:
<a href="mailto:topcat-user@jiscmail.ac.uk">topcat-user@jiscmail.ac.uk</a><br></i></body>
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