norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
cmap = cm.PRGn
fig, _axs = plt.subplots(nrows=2, ncols=2)
fig.subplots_adjust(hspace=0.3)
axs = _axs.flatten()
cset1 = axs[0].contourf(X, Y, Z, levels, norm=norm,
cmap=cm.get_cmap(cmap, len(levels) - 1))
// It is not necessary, but for the colormap, we need only the
// number of levels minus 1. To avoid discretization error, use
// either this number or a large number such as the default (256).
// If we want lines as well as filled regions, we need to call
// contour separately; don"t try to change the edgecolor or edgewidth
// of the polygons in the collections returned by contourf.
// Use levels output from previous call to guarantee they are the same.
cset2 = axs[0].contour(X, Y, Z, cset1.levels, colors="k")
// We don"t really need dashed contour lines to indicate negative
// regions, so let"s turn them off.
for c in cset2.collections:
c.set_linestyle("solid")
// It is easier here to make a separate call to contour than
// to set up an array of colors and linewidths.
// We are making a thick green line as a zero contour.
// Specify the zero level as a tuple with only 0 in it.
cset3 = axs[0].contour(X, Y, Z, (0,), colors="g", linewidths=2)
axs[0].set_title("Filled contours")
fig.colorbar(cset1, ax=axs[0])
axs[1].imshow(Z, extent=extent, cmap=cmap, norm=norm)
axs[1].contour(Z, levels, colors="k", origin="upper", extent=extent)
