Listers,
I'm using basemap to plot randomly sampled values (x,y,z) through hexbin. This
produces a very nice result. Some sample code is:
----------
import numpy as np
from numpy.random import seed
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib.mlab import griddata
ll_lat = -38.39477 # extent of area of interest
ll_lon = 144.54767
ur_lat = -37.51642
ur_lon = 145.67144
num_points = 100 # sample points
# create random sampling over the area of interest
seed(0)
data = np.ones((3, num_points))
data[0,:] *= ll_lon + np.random.random((num_points))*(ur_lon-ll_lon)
data[1,:] *= ll_lat + np.random.random((num_points))*(ur_lat-ll_lat)
data[2,:] *= np.random.random((num_points))*10000
# plot the data
fig = plt.figure()
ax = fig.add_subplot(111)
m = Basemap(projection='cyl', llcrnrlat=ll_lat, urcrnrlat=ur_lat,
llcrnrlon=ll_lon, urcrnrlon=ur_lon, resolution='f',
suppress_ticks=False, area_thresh=0.5)
plt.hexbin(data[0,:], data[1,:], data[2,:], zorder=3)
m.fillcontinents(color=(0.8,0.8,0.8,0), zorder=1)
m.drawcoastlines(linewidth=0.25, color='k', zorder=2)
plt.show()
----------
This contrived example shows a sparse set of hexagons on both land and ocean.
I would like the hexagons over the ocean to be hidden. I can make the ones on
land disappear by changing the 'zorder' parameter of .hexbin() to 0. However I
have found no way of doing the inverse and hiding hexagons over the ocean.
Using drawlsmask() is too crude at a 5-minute resolution.
Any ideas?
Thanks,
Ross
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