old_contents: from mpl_toolkits.basemap import Basemap
  import matplotlib.pyplot as plt
  import numpy as np
  import gzip, os
  from netCDF4 import Dataset
  
  # create a land/sea mask using GMT grdlandmask utility.
  # this script reads the file generated by grdlandmask, plots it, 
  # and saves it in the format that Basemap._readlsmask expects.
  
  
  # run grdlandmask
  #resolution = 'i' # gshhs resolution
  #grid = '5' # grid size in minutes
  athresh={}
  athresh['c']=10000
  athresh['l']=1000
  athresh['i']=100
  athresh['h']=10
  athresh['f']=1
  
  for resolution in ['c','l','i']:
      for grid in [2.5,5]:
  
          filename = 'grdlandmask%smin_%s.nc' % (grid,resolution)
          cmd = \
          'grdlandmask -F -G%s -I%sm -R-180/180/-90/90 -D%s -N0/1/2/1/2 -A%s+l' % \
          (filename, grid, resolution, athresh[resolution])
          print cmd
          os.system(cmd)
          
          # read in data.
          nc = Dataset(filename)
          lons = nc.variables['x'][:]
          nlons = len(lons)
          lats = nc.variables['y'][:]
          nlats = len(lats)
          lsmask = nc.variables['z'][:].astype(np.uint8)
          
          # plot
          fig = plt.figure()
          m =\
          Basemap(llcrnrlon=-180,llcrnrlat=-90,urcrnrlon=180,urcrnrlat=90,resolution=resolution,projection='mill')
          m.drawcoastlines() # coastlines should line up with land/sea mask.
          m.drawlsmask(land_color='coral',ocean_color='aqua',lsmask=lsmask,lsmask_lons=lons,lsmask_lats=lats,lakes=True)
          plt.title('%s by %s land-sea mask (resolution = %s) from grdlandmask' %\
                  (nlons,nlats,resolution))
          
          # write out.
          f = gzip.open('lsmask_%smin_%s.bin' % (grid,resolution),'wb')
          print lsmask.dtype, lsmask.shape
          f.write(lsmask.tostring())
          f.close()
  
  plt.show()
  
new_contents: from mpl_toolkits.basemap import Basemap
  import matplotlib.pyplot as plt
  import numpy as np
  import gzip, os
  from netCDF4 import Dataset
  
  # create land/sea masks using GMT grdlandmask utility.
  # this script reads the file generated by grdlandmask, plots it, 
  # and saves it in the format that Basemap._readlsmask expects.
  
  
  # run grdlandmask
  athresh={}
  athresh['c']=10000
  athresh['l']=1000
  athresh['i']=100
  athresh['h']=10
  athresh['f']=1
  
  for resolution in ['c','l','i']:
      for grid in [1.25,2.5,5,10]:
  
          filename = 'grdlandmask%smin_%s.nc' % (grid,resolution)
          cmd = \
          'grdlandmask -F -G%s -I%sm -R-180/180/-90/90 -D%s -N0/1/2/1/2 -A%s+l' % \
          (filename, grid, resolution, athresh[resolution])
          print cmd
          os.system(cmd)
          
          # read in data.
          nc = Dataset(filename)
          lons = nc.variables['x'][:]
          nlons = len(lons)
          lats = nc.variables['y'][:]
          nlats = len(lats)
          lsmask = nc.variables['z'][:].astype(np.uint8)
          
          # plot
          fig = plt.figure()
          m =\
          Basemap(llcrnrlon=-180,llcrnrlat=-90,urcrnrlon=180,urcrnrlat=90,resolution=resolution,projection='mill')
          m.drawcoastlines() # coastlines should line up with land/sea mask.
          m.drawlsmask(land_color='coral',ocean_color='aqua',lsmask=lsmask,lsmask_lons=lons,lsmask_lats=lats,lakes=True)
          plt.title('%s by %s land-sea mask (resolution = %s) from grdlandmask' %\
                  (nlons,nlats,resolution))
          
          # write out.
          f = gzip.open('lsmask_%smin_%s.bin' % (grid,resolution),'wb')
          print lsmask.dtype, lsmask.shape
          f.write(lsmask.tostring())
          f.close()
  
  plt.show()
  
subject: create 1.25 and 10 min resolution masks.