pcolor subplots using matplotlib.basemap

cmap_discretize.py

import numpy as np
import matplotlib as mpl
from matplotlib import cm

def cmap_discretize(cmap, N=10):

     cmap = cm.get_cmap(eval(cmap))
     colors_i = np.concatenate((np.linspace(0, 1., N), (0.,0.,0.,0.)))
     colors_rgba = cmap(colors_i)
     indices = np.linspace(0, 1., N+1)
     cdict = {}
     for ki,key in enumerate(('red','green','blue')):
        cdict[key] = [(indices[i], colors_rgba[i-1,ki], colors_rgba[i,ki]) for i in xrange(N+1)]

     return mpl.colors.LinearSegmentedColormap(cmap.name + "_%d"%N, cdict, 1024)

sub_plot_pcolor.py

import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.basemap import Basemap
import mpl_toolkits.basemap.cm as GMT
# import xray
import numpy as np

def sub_plot_pcolor(lons, lats, data, title=None, cmap=cm.jet,
                    vmin=None, vmax=None, cbar=True, cbar_location='bottom',
                    units=None):
    

    if vmin is None:
        vmin=data.min()
    if vmax is None:
        vmax=data.max()

    projection = {'urcrnrlat': 27.511827255753555, 
                  'urcrnrlon': 16.90845094934209, 
                  'llcrnrlat': 16.534986367884521, 
                  'llcrnrlon': 189.2229322311162, 
                  'projection': 'lcc', 
                  'rsphere': 6371200.0, 
                  'lon_0': -114, 
                  'lat_0': 90}
        
    m = Basemap(**projection)
    xi,yi = m(np.squeeze(lons),np.squeeze(lats))
    sp = m.pcolormesh(xi, yi, np.squeeze(data), vmin=vmin,vmax=vmax, cmap=cmap)
    m.drawparallels(np.arange(-80.,81.,20.))
    m.drawmeridians(np.arange(-180.,181.,20.))
    m.drawcoastlines(color='k',linewidth=0.25);
    
    if title:
        plt.title(title,size=13)
    if cbar:
        cbar = m.colorbar(location=cbar_location)
    cbar.set_label(units)
    
    return sp