Yes,
Thanks, Friedrich. :-)
This is exactly what I want. By now I know we have to plot over a
uniformly sampled plane any way at the end of the day, no matter
whether our original data is uniformly sampled or not.
Zhe Yao
On Thu, Apr 8, 2010 at 6:07 PM, Friedrich Romstedt
I think it should be possible to do unsorted scatter plot, so you can
avoid the second loop. Maybe the current source doesn't allow for,
but it's certainly possible (hu, I'm not that aquainted with current
z-sorting code, so maybe I'm wrong?) It may be that current z-sorting
uses the mesh grid.
Year, I think we could do unsorted scatter plot as well, however I'm
still not satisfied with the book tracking routines I have to check
when doing the surface plotting.
Anyway, thanks, man. You saved a lot.
Hope this time, it CC to the mailing list as well. :-)
2010/4/1 ericyosho ericyo...@gmail.com:
And we know that for points with coordination, scatter must be the
simplest way to visualize them.
Is there any trick to convert a scatter graph into a surface picture directly?
I'm afraid not, because one needs an algorithm to infer the connectivity :-(
Hi, All,
I have a bunch of 3D points with coordinations in a dict
pointset = {
(x1,y1):z1,
(x2,y2):z2,
...
}
It seems I have to
1. fire a loop to change each item and convert the whole dictionary into arrays;
x = []
y = []
for i in pointset.items():
x.append(i[0][0])
y.append(i[0][1])
On 3/31/2010 10:40 PM, ericyosho wrote:
send x and y ranges to meshgrid
Does this mean you have the entire grid of points?
In any case, you can get an array of your points
as np.array([(x,y,z) for (x,y),z in d.iteritems()])
fwiw,
Alan Isaac
