title: finding indexes of common subarrays
body: <p>I have 2 large, unsorted arrays (structured set of xyz coordinates) and I'm trying to find the positions of all identical subarrays (common points consisting of 3 coordinates). Example:</p>
  
  <pre><code>a = array([[0, 1, 2], [3, 4, 5]])
  b = array([[3, 4, 5], [6, 7, 8]])
  </code></pre>
  
  <p>Here the correct subarray would be <code>[3, 4, 5]</code>, but more than one identical subarrays are possible. The correct indexes would be <code>[0,1]</code> for <code>a</code> and <code>[1,0]</code> for <code>b</code>. </p>
  
  <p>I already implemented a pure python method by iterating over all points of one array and comparing them to every point of the other array, but this is extremely slow.</p>
  
  <p>My question is, is there an efficient way to find the indexes for both arrays (preferably in numpy, because I need the arrays for further calculations)? Perhaps a rolling_window approach?</p>