## Note: example as seen on matplotlib webpage (2013-08-26): ## - http://matplotlib.org/examples/pylab_examples/griddata_demo.html ## Only adapted color handling ## Loading necessary python modules for this example from numpy.random import uniform, seed from matplotlib.mlab import griddata import matplotlib.pyplot as plt import numpy as np ## make up data. seed(0) npts = 200 x = uniform(-2,2,npts) y = uniform(-2,2,npts) z = x*np.exp(-x**2-y**2) ## define grid. xi = np.linspace(-2.1,2.1,100) yi = np.linspace(-2.1,2.1,200) ## grid the data. zi = griddata(x,y,z,xi,yi,interp='linear') ## contour the gridded data, plotting dots at the nonuniform data points. CS = plt.contour(xi,yi,zi,len(colors)-1,linewidths=0.5,colors='k') CS = plt.contourf(xi,yi,zi,len(colors)-1,colors=colors, vmax=abs(zi).max(), vmin=-abs(zi).max()) plt.colorbar() # draw colorbar ## plot data points. plt.scatter(x,y,marker='o',c='b',s=5,zorder=10) plt.xlim(-2,2) plt.ylim(-2,2) plt.title('griddata test (%d points)' % npts) plt.show()