title: Numpy interp not interpolating/extrapolating the values, only finding if the data point is above or below the max empirical value
body: <p>I have the following empirical data:</p>
  
  <pre><code>emp_data = np.array([[0.5, -24.111869188789498],
  [1.0, -30.166986253668671],
  [1.5, -33.310250723584765],
  [2.0, -35.629672538473848],
  [2.5, -39.416821042883605],
  [3.0, -41.05367278405226],
  [3.5, -42.702793174115918],
  [3.653, -41.173808136289971],
  [4.0, -45.327195234249011],
  [4.5, -47.170664776211105],
  [5.0, -45.838914309065679],
  [5.5, -47.83778613822286],
  [6.0, -49.55982614930786],
  [6.5, -48.899619370977753]])
  </code></pre>
  
  <p>And I want to interpolate or extrapolate a value from this data based on a new data point similar to the second column. eg -38. If I try interpolate this value interp returns 6.5. </p>
  
  <pre><code>numpy.interp(-38, emp_data[:,1], emp_data[:,0])
  Out[65]: 6.5
  </code></pre>
  
  <p>numpy interp returns 6.5 for any value below -48.89 (the max value in the emprical data) and 0.5 for any value above. Anyone know why?</p>
  
  <p>thanks</p>