<html><head><meta name="color-scheme" content="light dark"></head><body><pre style="word-wrap: break-word; white-space: pre-wrap;">"""
hexbin is an axes method or pyplot function that is essentially a
pcolor of a 2-D histogram with hexagonal cells.
"""

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab

delta = 0.025
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = Z2 - Z1  # difference of Gaussians

x = X.ravel()
y = Y.ravel()
z = Z.ravel()

if 1:
    # make some points 20 times more common than others, but same mean
    xcond = (-1 &lt; x) &amp; (x &lt; 1)
    ycond = (-2 &lt; y) &amp; (y &lt; 0)
    cond = xcond &amp; ycond
    xnew = x[cond]
    ynew = y[cond]
    znew = z[cond]
    for i in range(20):
        x = np.hstack((x, xnew))
        y = np.hstack((y, ynew))
        z = np.hstack((z, znew))

xmin = x.min()
xmax = x.max()
ymin = y.min()
ymax = y.max()

gridsize = 30

plt.subplot(211)
plt.hexbin(x, y, C=z, gridsize=gridsize, marginals=True, cmap=plt.cm.RdBu,
           vmax=abs(z).max(), vmin=-abs(z).max())
plt.axis([xmin, xmax, ymin, ymax])
cb = plt.colorbar()
cb.set_label('mean value')


plt.subplot(212)
plt.hexbin(x, y, gridsize=gridsize, cmap=plt.cm.Blues_r)
plt.axis([xmin, xmax, ymin, ymax])
cb = plt.colorbar()
cb.set_label('N observations')

plt.show()
</pre></body></html>