title: Correct usage of scipy.interpolate.RegularGridInterpolator
body: <p>I am a little confused by the <a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.RegularGridInterpolator.html" rel="noreferrer">documentation for scipy.interpolate.RegularGridInterpolator</a>.</p>
  
  <p>Say for instance I have a function f: R^3 => R which is sampled on the vertices of the unit cube. I would like to interpolate so as to find values inside the cube.</p>
  
  <pre><code>import numpy as np
  
  # Grid points / sample locations
  X = np.array([[0,0,0], [0,0,1], [0,1,0], [0,1,1], [1,0,0], [1,0,1], [1,1,0], [1,1,1.]])
  
  # Function values at the grid points
  F = np.random.rand(8)
  </code></pre>
  
  <p>Now, <code>RegularGridInterpolator</code> takes a <code>points</code> argument, and a <code>values</code> argument.</p>
  
  <blockquote>
    <p><strong>points</strong> : tuple of ndarray of float, with shapes (m1, ), ..., (mn, )
    The points defining the regular grid in n dimensions.</p>
    
    <p><strong>values</strong> : array_like, shape (m1, ..., mn, ...)
    The data on the regular grid in n dimensions.</p>
  </blockquote>
  
  <p>I interpret this as being able to call as such:</p>
  
  <pre><code>import scipy.interpolate as irp
  
  rgi = irp.RegularGridInterpolator(X, F)
  </code></pre>
  
  <p>However, when I do so, I get the following error:</p>
  
  <blockquote>
    <p>ValueError: There are 8 point arrays, but values has 1 dimensions</p>
  </blockquote>
  
  <p>What am I misinterpreting in the docs?</p>