def hexbin(self,x,y,**kwargs):
"""
Make a hexagonal binning plot of x versus y, where x, y are 1-D
sequences of the same length, N. If C is None (the default), this is a
histogram of the number of occurences of the observations at
(x[i],y[i]).
If C is specified, it specifies values at the coordinate (x[i],y[i]).
These values are accumulated for each hexagonal bin and then reduced
according to reduce_C_function, which defaults to the numpy mean function
(np.mean). (If C is specified, it must also be a 1-D sequence of the
same length as x and y.)
x, y and/or C may be masked arrays, in which case only unmasked points
will be plotted.
(see matplotlib.pyplot.hexbin documentation).
Extra keyword ``ax`` can be used to override the default axis instance.
Other \**kwargs passed on to matplotlib.pyplot.hexbin
"""
ax, plt = self._ax_plt_from_kw(kwargs)
# allow callers to override the hold state by passing hold=True|False
b = ax.ishold()
h = kwargs.pop('hold',None)
if h is not None:
ax.hold(h)
try:
# make x,y masked arrays
# (masked where data is outside of projection limb)
x = ma.masked_values(np.where(x > 1.e20,1.e20,x), 1.e20)
y = ma.masked_values(np.where(y > 1.e20,1.e20,y), 1.e20)
ret = ax.hexbin(x,y,**kwargs)
except:
ax.hold(b)
raise
ax.hold(b)
# reset current active image (only if pyplot is imported).
if plt:
plt.sci(ret)
# clip for round polar plots.
if self.round: ret,c = self._clipcircle(ax,ret)
# set axes limits to fit map region.
self.set_axes_limits(ax=ax)
return ret
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