pcolormesh plot is blank; pcolor plot works

[Timothy-W-Hilton]

I am experiencing strange behavior using mpl_toolkits.basemap.Basemap. My understanding is that pcolormesh is faster than pcolor, and thus preferable. Here is a minimal example (below) where I get a different plot from pcolormesh than from pcolor.

On two systems (mac os x 10.9.5; Ubuntu 11.04 (GNU/Linux 2.6.32.28 x86_64); basemap 1.0.7 on the mac and 1.0.8 on the Ubuntu machine; both using matplotlib 1.4.2) I get the expected grid of random colors from pcolor, but a monochrome plot from pcolormesh.

Is this expected? Are there circumstances in which I should be using pcolor instead of pcolormesh? Is this a bug in matplotlib or in basemap?

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

def setup_map(ax):

    m = Basemap(width=8.0e6,
                height=6.5e6,
                projection='aeqd',
                lat_0=54,
                lon_0=-105,
                resolution='l',
                area_thresh=1000, 
                rsphere=6371007.181000,
                fix_aspect=True,
                ax=ax)
    m.drawcoastlines()
    m.drawcountries()
    m.drawstates()
    return(m)

# create pseudo-data with longitudes and latitudes
lon, lat = np.meshgrid(np.arange(-180, 180), 
                       np.arange(90, -90, -1))
data = np.random.rand(*lon.shape) * 100

# two-panel figure
fig, ax = plt.subplots(nrows=1, ncols=2)

# plot pseudodata in left panel using pcolormesh
m0 = setup_map(ax[0])
cm = m0.pcolormesh(lon, lat, data, latlon=True, 
              vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
plt.colorbar(cm, ax=ax[0])
ax[0].set_title('pcolormesh')

# plot pseudodata in left panel using pcolor
m1 = setup_map(ax[1])
cm = m1.pcolor(lon, lat, data, latlon=True, 
          vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
plt.colorbar(cm, ax=ax[1])
ax[1].set_title('pcolor')

plt.show()

[davidmanheim]

Your having this problem because of your indexes; if you use

lon, lat = np.meshgrid(np.arange(-180, 180), np.arange(-90, 90, 1))

, reversing the second index, then the problem goes away. I suspect this is due to the way the mesh is constructed.

It might be useful to have the note about the index in the documentation.