Re: [Matplotlib-users] basemap: Mask the ocean [SEC=UNCLASSIFIED]

Stephane Raynaud wrote:
> 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).

Following Stephane's excellent suggestion, here's a prototype Basemap 
method that checks to see if a point is on land or over water.  Ross - 
if you find it useful I'll include it in the next release.  Note that it 
will be slow for lots of points or large map regions.

-Jeff
>
> On Mon, Nov 2, 2009 at 8:07 AM, <Ros...@ga... 
> <mailto:Ros...@ga...>> 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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> -- 
> Stephane Raynaud
> ------------------------------------------------------------------------
>
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