Dnia 2009-10-08, czw o godzinie 10:02 +0200, Roberto Vidmar pisze:
Let me explain better my problem:
I have n (many millions) laser points data in a numpy array:
laser_points.shape = (1000, 3)
the columns are the x, y, z coordinates of these points in 3D space.
These points are
Let me explain better my problem:
I have n (many millions) laser points data in a numpy array:
laser_points.shape = (1000, 3)
the columns are the x, y, z coordinates of these points in 3D space.
These points are irregularly spaced and are the result of a survey on a
real world object
Hello Andreas,
I have (many) millions of point coordinated (X, y, z) in 3D space
(easting, westing, height) like these:
import numpy as np
x = np.random.random(1)
y = np.random.random(1)
z = x * np.exp(-x**2-y**2)
So the points are:
p = (x, y, z)
I need to interpolate them to a
Dnia 2009-10-07, śro o godzinie 10:41 +0200, Roberto Vidmar pisze:
Hello Andreas,
I have (many) millions of point coordinated (X, y, z) in 3D space
(easting, westing, height) like these:
import numpy as np
x = np.random.random(1)
y = np.random.random(1)
z = x *
Hi Roberto,
On Freitag 02 Oktober 2009, Roberto Vidmar wrote:
I wonder if it is possible to use PyCUDA to grid on a two dimensional
regular grid xyz scattered data. Our datasets are usually quite large
(some millions of points) .
Many thanks for any help in this topic.
As usual, if
Hello,
I wonder if it is possible to use PyCUDA to grid on a two dimensional
regular grid xyz scattered data. Our datasets are usually quite large
(some millions of points) .
Many thanks for any help in this topic.
Roberto Vidmar
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