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    <title>MATLAB Central Newsreader - Delaunay</title>
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    <item>
      <pubDate>Thu, 14 May 2009 13:08:01 -0400</pubDate>
      <title>Delaunay</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/251355#649818</link>
      <author>Luigi Giaccari</author>
      <description>Hi I was testing the new delaunay triangulator from the CGAL library available from R2009a.&lt;br&gt;
&lt;br&gt;
These are my results: &lt;br&gt;
The new one is faster than delaunayn of 3-4 factors on uniform dataset.&lt;br&gt;
Instead, for sparse dataset is terribly slower, for a medium number of points I had to stop the test before it finished.&lt;br&gt;
&lt;br&gt;
Test were run on 2-D 3-D models with increasing number of points up to 1e5.&lt;br&gt;
&lt;br&gt;
Have you some explanation on that? and what is your opinon?&lt;br&gt;
&lt;br&gt;
Thanks in advance</description>
    </item>
    <item>
      <pubDate>Thu, 14 May 2009 16:45:48 -0400</pubDate>
      <title>Re: Delaunay</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/251355#649922</link>
      <author>Damian Sheehy</author>
      <description>Hi Luigi,&lt;br&gt;
&lt;br&gt;
For randomly distributed datapoints the new triangulation functions are 3-4 &lt;br&gt;
times faster.&lt;br&gt;
For highly-degenerate datasets, such as datapoints arranged in a regular &lt;br&gt;
grid, the performance is worse, but the code is robust in tringulating this &lt;br&gt;
data.&lt;br&gt;
We are aware of this issue and we actively working on addressing it.&lt;br&gt;
Thank you for your feedback.&lt;br&gt;
&lt;br&gt;
Regards,&lt;br&gt;
&lt;br&gt;
Damian&lt;br&gt;
&lt;br&gt;
&quot;Luigi Giaccari&quot; &amp;lt;giaccariluigi@msn.com&amp;gt; wrote in message &lt;br&gt;
news:guh53h$22b$1@fred.mathworks.com...&lt;br&gt;
&amp;gt; Hi I was testing the new delaunay triangulator from the CGAL library &lt;br&gt;
&amp;gt; available from R2009a.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; These are my results:&lt;br&gt;
&amp;gt; The new one is faster than delaunayn of 3-4 factors on uniform dataset.&lt;br&gt;
&amp;gt; Instead, for sparse dataset is terribly slower, for a medium number of &lt;br&gt;
&amp;gt; points I had to stop the test before it finished.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Test were run on 2-D 3-D models with increasing number of points up to &lt;br&gt;
&amp;gt; 1e5.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Have you some explanation on that? and what is your opinon?&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Thanks in advance </description>
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