The mplot3d tutorial page, which is the first result when you google
'mplot3d', includes a section on 'Tri-surface plots' and is precisely what
you are looking for.
You certainly do not need to use scipy. Matplotlib includes its own
Delaunay triangulator, as specified in the 'triangular grids'
documentation, which is the first result when you google 'matplotlib
triangulation'.
Ian
On 25 June 2015 at 12:22, Philipp A. <flying-sh...@web.de> wrote:
> hi!
>
> do a delaunay triangulation
> <http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.Delaunay.html>
> on them.
>
> also try to do the triangulation only on the xy coordinates and see which
> of both gives the results you like more.
>
> best, p
>
> justonium <justinorth...@gmail.com> schrieb am Do., 25. Juni 2015 um
> 05:21 Uhr:
>
>> I have a set of three dimensional coordinates, each of which is on a
>> landscape. I would like to visualize the entire landscape.
>>
>> I've already tried plotting the points in 3D space using Axes3D.scatter,
>> but
>> I just see a bunch of points, and it's hard to visually understand what's
>> going on.
>>
>> Ideally, I would like to view a wireframe plot. In order for this to be
>> drawn, height values will need to be interpolated from the samples that I
>> have, which don't line up with a grid.
>>
>> Another solution might be:
>>
>> For each point, draw a vertical line from it, straight down, to a point
>> below it which has the same x and y coordinates, with 0 as the z
>> coordinate.
>> This might still be difficult to visually understand.
>>
>>
>>
>> --
>> View this message in context:
>> http://matplotlib.1069221.n5.nabble.com/How-can-I-visualize-a-landscape-which-I-have-sample-heights-of-tp45834.html
>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>
>>
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