Uses of Class
visad.VisADException

Packages that use VisADException
visad   
 

Uses of VisADException in visad
 

Subclasses of VisADException in visad
 class SetException
          SetException is an exception for an error with a VisAD sampling.
 class UnimplementedException
          UnimplementedException is an exception for a VisAD method not yet implemented.
 

Methods in visad that throw VisADException
static Delaunay Delaunay.factory(float[][] samples, boolean exact)
          The factory class method heuristically decides which extension to the Delaunay abstract class to use in order to construct the fastest triangulation, and calls that extension, returning the finished triangulation.
 void Delaunay.finish_triang(float[][] samples)
          calculate a triangulation's helper arrays, Walk and Edges, if the triangulation algorithm hasn't calculated them already.
 void Delaunay.improve(float[][] samples, int pass)
          use edge-flipping to bring the current triangulation closer to the true Delaunay triangulation.
static void DelaunayFast.main(java.lang.String[] argv)
          Illustrates the speed increase over other Delaunay algorithms
static void DelaunayOverlap.main(java.lang.String[] argv)
          run 'java visad.DelaunayOverlap' to test the DelaunayOverlap class
 

Constructors in visad that throw VisADException
Delaunay()
          The abstract constructor initializes the class's data arrays.
DelaunayClarkson(float[][] samples)
          construct a Delaunay triangulation of the points in the samples array using Clarkson's algorithm
DelaunayFast(float[][] samples)
          construct an approximate Delaunay triangulation of the points in the samples array using Curtis Rueden's algorithm
DelaunayOverlap(float[][] samples, int lenx, int leny)
          Construct a Delaunay triangulation of the points in the samples array, which are a sequence of 2-D grids of size lenx * leny, and which may overlap with each other.
DelaunayWatson(float[][] samples)
          construct a Delaunay triangulation of the points in the samples array using Watson's algorithm
 



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