title: Interpolation of a 3D regular griddata using scipy.interpolate.Rbf
body: <p>This h5 file contains the information of an analytical function on a regular 3D gird. For interpolation purpose, I have got very poor result using the Regulargridinterpolator here. Now, I want to test <code>scipy.interpolate.Rbf</code> interpolator for my data set. Can anyone help me to do that? I had a look at the documentation of this interpolator but didn't understand properly. </p>
  
  <p>I have created a h5 file like this:</p>
  
  <pre><code>import numpy as np
  from numpy import gradient
  import h5py
  from scipy.interpolate import Rbf
  
  def f(x,y,z):
      return ( -1 / np.sqrt(x**2 + y**2 + z**2))
  
  #grid
  x = np.linspace(0, 100, 32)  # since the boxsize is 320 Mpc/h
  y = np.linspace(0, 100, 32)
  z = np.linspace(0, 100, 32)
  
  
  mesh_data = phi_an(*np.meshgrid(x, y, z, indexing='ij', sparse=True))
  
  
  #create h5 file
  h5file = h5py.File('analytic.h5', 'w')
  h5file.create_dataset('/x', data=x)
  h5file.create_dataset('/y', data=y)
  h5file.create_dataset('/z', data=z)
  h5file.create_dataset('/mesh_data', data=mesh_data)
  
  h5file.close()
  </code></pre>