ta(points, values, (grid_x, grid_y), method='linear')
    >>> grid_z2 = griddata(points, values, (grid_x, grid_y), method='cubic')

    One can see that the exact result is reproduced by all of the
    methods to some degree, but for this smooth function the piecewise
    cubic interpolant gives the best results:

    >>> import matplotlib.pyplot as plt
    >>> plt.subplot(221)
    >>> plt.imshow(func(grid_x, grid_y).T, extent=(0,1,0,1), origin='lower')
    >>> plt.plot(points[:,0], points[:,1], 'k.', ms=1)
    >>> plt.title('Original')
    >>> plt.subplot(222)
    >>> plt.imshow(grid_z0.T, extent=(0,1,0,1), origin='lower')
    >>> plt.title('Nearest')
    >>> plt.subplot(223)
    >>> plt.imshow(grid_z1.T, extent=(0,1,0,1), origin='lower')
    >>> plt.title('Linear')
    >>> plt.subplot(224)
    >>> plt.imshow(grid_z2.T, extent=(0,1,0,1), origin='lower')
    >>> plt.title('Cubic')
    >>> plt.gcf().set_size_inches(6, 6)
    >>> plt.show()

    