[SciPy-User] Interpolate based on three closest points
Wed Apr 21 09:04:56 CDT 2010
I have an irregular mesh of ~1e5 data points, with unreliable connection
data. I am trying to interpolate based on these points. My current method,
in pseudocode, is roughly the following:
> Matrix of data is a numpy array with X,Y,Z as columns
point of interest is x,y,z
Find distance from point of interest to all points by ~ numpy.sqrt((X-x)**2
> + (Y-y)**2 + (Z-z)**2)
for each triangle that can be made by N closest points:
if triangle contains point of interest:
area.append(area of triangle)
tri.append(three triangle vertices)
if tri: break
Do a linear interpolation based on triangle with smallest area
This method works great, but is super slow. I do this for ~1e6 points. I
was thinking there might be a faster way to find the closest points, perhaps
by doing some sort of binary tree structure? Or perhaps I can build a
better mesh, and trace mesh connections to the closest points?
Any ideas would be appreciated.
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