[Matplotlib-users] Creating a smooth surface in 3D

[Bala subramanian]

Thanks for the inputs. After some efforts, I managed to create the surface
by generating vertex and faces using an external program and mpl tools.

ax1.plot_trisurf(x, y, z, triangles=faces,color='w', lw=10)

ax1.scatter3D(x, y, z, c= cols,s=10)

However, i am now trying to figure out the simple way to color the
triangles using the vertex colors.

For each vertex, I have assigned a color (ranges from blue to red) which in
my case represents a calculated property. So basically I have a color array
(cols in the above snippet) that I passed to the scatter function. I would
like to know how I can color the triangle by interpolating to the colors of
the vertex it belongs to. The available examples in net show the usage of
colormaps. In my case, the triangles should adopt vertex colors.

Any tricks to achieve this could be of much help. I have attached a sample
figure, which i believe, could better elucidate the problem.






On Mon, May 28, 2018 at 3:19 PM, Benjamin Root <ben.v.root at gmail.com> wrote:

> mplot3d is good for real simple 3d scenes, but it falls apart when you
> start composing things like this. You might want to consider using
> something like glumpy or mayavi for better results. There are some
> discussions in the past on the problems inherent in creating spheres in
> mplot3d. There are some interesting solutions, but they get fairly complex
> pretty quickly.
>
> Cheers!
> Ben Root
>
> On Mon, May 28, 2018 at 8:16 AM, Bala subramanian <
> bala.biophysics at gmail.com> wrote:
>
>> Dear mpl friends,
>>
>> My objective is to create a molecular surface using matplotlib. I used
>> the snippet pasted below to create a series of spheres (attached png),
>> drawn using the atom attributes (their positions and radius). From here, I
>> would like to create a smooth surface which can depict the shape of the
>> molecule surface (curves,cavities etc). Based on examples in net, I get a
>> mixed feeling that either triangulation or making 3D grids are some
>> directions to proceed. If anyone has some suggestions or better protocols
>> for such task with some example data, it would be of great help to me.
>>
>> fig = plt.figure(figsize=(6,6),dpi=140)
>>
>> ax1 = fig.add_subplot(111, projection='3d')
>>
>> # Define spherical coordinates
>>
>> u, v = np.mgrid[0:2*np.pi:20j, 0:np.pi:10j]
>>
>> S = np.cos(u)*np.sin(v)
>>
>> C = np.sin(u)*np.sin(v)
>>
>> T = np.cos(v)
>>
>> for P,R in zip(positions,radii):
>>
>>          ax1.plot_wireframe(R*S+P[0],R*C+P[1],R*T+P[2],color='r',alph
>> a=0.4)
>>
>> Thanks in advance,
>>
>> Bala
>>
>>
>> --
>> C. Balasubramanian
>>
>> _______________________________________________
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>> Matplotlib-users at python.org
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>>
>>
>


-- 
C. Balasubramanian
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