Python：Matplotlib Surface_plot

Question

I'm trying to Plot a high resolution surface_plot, but I would also really like some nice grid lines on top of it. If i use the gridlines in the same argument

ax.plot_surface(x_itp, y_itp, z_itp, rstride=1, cstride=1, facecolors=facecolors, linewidth=0.1)

I get a LOT of grid lines. If I, on the other hand, set "rstride" and "cstride" to higher values, my sphere will become ugly.

I then tried to smash a

ax.plot_wireframe(x_itp, y_itp, z_itp, rstride=3, cstride=3)

in afterwards, but it just lies on top of the colored sphere.. meaning that I can see the backside of the wireframe and then the surface_plot behind it all.

Have anyone tried this?

Another option was to use "Basemap" which can create a nice grid, but then I will have to adapt my colored surface to that.?!

My plot looks like this:

If I add edges to the map with a higher "rstride" and "cstride" then it looks like this:

code :

norm = plt.Normalize()
facecolors = plt.cm.jet(norm(d_itp))

# surface plot 
fig, ax = plt.subplots(1, 1, subplot_kw={'projection':'3d', 'aspect':'equal'})
ax.hold(True)
surf = ax.plot_surface(x_itp, y_itp, z_itp, rstride=4, cstride=4, facecolors=facecolors)
surf.set_edgecolors("black")

I want to show the \\theta and \\phi angles around the sphere.. maybe with 30 degrees apart.

Cheers! Morten

Answer 1

It looks like you may need to use basemap. With plot_surface() you can either have high resolution plot or low resolution with good grid on top. But not both. I just made a simple basemap with contour plot. I think you can do easily apply pcolor on it. Just do not draw continent and country boundary. Then, you have a nice sphere which gives more control. After making your plot, you can easily add grid on it.

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np

map = Basemap(projection='ortho',lat_0=45,lon_0=-150) 
map.drawmapboundary(fill_color='aquamarine')
map.drawmeridians(np.arange(0,360,30)) # grid every 30 deg
map.drawparallels(np.arange(-90,90,30))

nlats = 73; nlons = 145; delta = 2.*np.pi/(nlons-1)
lats = (0.5*np.pi-delta*np.indices((nlats,nlons))[0,:,:])
lons = (delta*np.indices((nlats,nlons))[1,:,:])
wave = 0.6*(np.sin(2.*lats)**6*np.cos(4.*lons))
mean = 0.5*np.cos(2.*lats)*((np.sin(2.*lats))**2 + 2.)

x, y = map(lons*180./np.pi, lats*180./np.pi) # projection from lat, lon to sphere
cs = map.contour(x,y,wave+mean,15,linewidths=1.5) # contour data. You can use pcolor() for your project
plt.title('test1')
plt.show()