title: SciPy interp1d results are different than MatLab interp1
body: <p>I'm converting a MatLab program to Python, and I'm having problems understanding why scipy.interpolate.interp1d is giving different results than MatLab interp1.</p>
  
  <p>In MatLab the usage is slightly different:</p>
  
  <pre><code>yi = interp1(x,Y,xi,'cubic')
  </code></pre>
  
  <p>SciPy:</p>
  
  <pre><code>f = interp1d(x,Y,kind='cubic')
  yi = f(xi)
  </code></pre>
  
  <p>For a trivial example the results are the same:
  MatLab:</p>
  
  <pre><code>interp1([0 1 2 3 4], [0 1 2 3 4],[1.5 2.5 3.5],'cubic')
    1.5000 2.5000 3.5000
  </code></pre>
  
  <p>Python:</p>
  
  <pre><code>interp1d([1,2,3,4],[1,2,3,4],kind='cubic')([1.5,2.5,3.5])
    array([ 1.5,  2.5,  3.5])
  </code></pre>
  
  <p>But for a real-world example they are not the same:</p>
  
  <pre><code>x =   0.0000e+000  2.1333e+001  3.2000e+001  1.6000e+004  2.1333e+004  2.3994e+004
  Y =   -6   -6   20   20   -6   -6
  xi =  0.00000 11.72161 23.44322 35.16484...  (2048 data points)
  </code></pre>
  
  <p>Matlab:</p>
  
  <pre><code>-6.0000e+000
  -1.2330e+001
  -3.7384e+000
    ...
   7.0235e+000
   7.0028e+000
   6.9821e+000
  </code></pre>
  
  <p>SciPy:    </p>
  
  <pre><code>array([[ -6.00000000e+00],
         [ -1.56304101e+01],
         [ -2.04908267e+00],
         ..., 
         [  1.64475576e+05],
         [  8.28360759e+04],
         [ -5.99999999e+00]])
  </code></pre>
  
  <p>Any thoughts as to how I can get results that are consistent with MatLab?</p>
  
  <p>Edit: I understand that there is some latitude in implementation for cubic interpolation algorithms which probably accounts for the differences I'm seeing.  It also seems that the original MatLab program that I am converting should have used linear interpolation, so the question is probably moot.</p>