excellent :)<br><br>I won't have time to test it until at end March-April, so if others could start testing it, that would be great.<br><br>An idea may be to follow up with those people who asked about weird distance functions (eg distance on the planet surface). See if they can help us test it, even if they just help to provide use with use-cases, data, etc.<br>
<br>Can I leave that in your (the list, or Sylvain's) hands?<br><br>cheers<br>Paul<br><br><div class="gmail_quote">2009/2/19 Sylvain Bougerel <span dir="ltr"><<a href="mailto:sylvain.bougerel.devel@gmail.com">sylvain.bougerel.devel@gmail.com</a>></span><br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">Hi,<br>
<br>
In the branch sb/bugfixes (no mistakes this time) I've merged the<br>
changes for the distance functor with the changes from master.<br>
<br>
test_kdtree.cpp and test_hayne.cpp are the version from the master,<br>
they both compiled and passed without any modification.<br>
<br>
So far the only distance functor tested is euclidean_distance. I<br>
haven't tested manhattan_distance or fast_euclidean_distance yet.<br>
<br>
I have added fast_euclidean_distance that is unsafe because it can<br>
overflow, but will compute faster than the safer euclidean_distance.<br>
However it is not the default distance functor for the tree, so you<br>
need to declare your templates accordingly if you intend to use it.<br>
<br>
Cheers,<br>
<br>
Sylvain<br>
<br>
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