Ross,
one way is to mask (or remove) ocean points using the _geoslib module
provided with basemap.
When you create a Basemap instance, you can retrieve all its polygons land
(continents and islands) with "mymap.coastpolygons".
Thay are stored as numpy arrays, and you can convert them to
_geoslib.Polygon objects :
poly = _geoslib.Polygon(N.asarray(coastalpoly).T)
Then you loop over all Polygons and all (x,y) points and test :
good_point = _geoslib.Point((x,y)).within(poly)
Thanks to this method, you can choose you optimal resolution.
You can even compute the intersection of you hexagons with coastal polygons
using .intersection() and .area (instead of simply checking if the center is
inside) and then reject points depending the fraction of the cell covered by
land (or ocean).
On Mon, Nov 2, 2009 at 8:07 AM, <ross.wil...@ga.gov.au> wrote:
> 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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