#--- read data ---
D = Data('./example_data/air.mon.mean.nc', 'air',read=True)
P = Data('./example_data/pr_wtr.eatm.mon.mean.nc','pr_wtr',read=True)
#--- some analysis ---
print 'Temporal stdv. ...'
t = D.timstd(return_object=True)
map_plot(t,use_basemap=True,title='Temporal stdv.',show_stat=True)
print 'Temporal trend ...'
f=plt.figure()
ax1=f.add_subplot(221)
ax2=f.add_subplot(222)
ax3=f.add_subplot(223)
ax4=f.add_subplot(224)
R,S,I,P = D.temporal_trend(return_object=True)
map_plot(R, use_basemap=True, ax=ax1)
map_plot(S, use_basemap=True, ax=ax2)
map_plot(I, use_basemap=True, ax=ax3)
map_plot(P, use_basemap=True, ax=ax4)
f.suptitle('Example of temporal correlation analysis results', size=20)
print 'Calculate climatology and plot ...'
# get_climatology() returns 12 values which are then used for plotting
map_season(D.get_climatology(return_object=True), use_basemap=True, vmin=-20., vmax=30.)
print 'Map difference between datasets ...'
map_difference(D,P)
print 'ZonalPlot ...'
