This is a page showing some of VTK techniques/results for visualizing scattered data. We begin with just 2D data.
del2d.py (Python script):
100 random 2D points between [-0.5,0.5] (+ 4 corner points), each assigned a
scalar = simple distance function from the origin.
Using vtkDelaunay2D (wireframe and shaded):
It is apparently possible to force the output to conform to a particular polygonal mesh (e.g., square; rf. class doc), but I didn't attempt this here.
shep.py (Python script):
Using vtkShepardMethod (interpolates the scattered data onto a StructGrid).
Note that results will vary considerably depending on values of various
params (e.g., MaximumDistance, SampleDimensions) for this class, as well as
the scalar range used for the mapper.
It goes without saying that one needs
to interpret the results of any interpolant with care.
(The name of the image reflects the parameters that were used for the script).
500 points:
Delaunay2D:
