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POSciPy interp1d results are different than MatLab interp1
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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. In MatLab the usage is slightly different: <pre><code>yi = interp1(x,Y,xi,'cubic') </code></pre> SciPy: <pre><code>f = interp1d(x,Y,kind='cubic') yi = f(xi) </code></pre> For a trivial example the results are the same: MatLab: <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> Python: <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> But for a real-world example they are not the same: <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> Matlab: <pre><code>-6.0000e+000 -1.2330e+001 -3.7384e+000 ... 7.0235e+000 7.0028e+000 6.9821e+000 </code></pre> SciPy: <pre><code>array([[ -6.00000000e+00], [ -1.56304101e+01], [ -2.04908267e+00], ..., [ 1.64475576e+05], [ 8.28360759e+04], [ -5.99999999e+00]]) </code></pre> Any thoughts as to how I can get results that are consistent with MatLab? 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.
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<python><matlab><scipy><interpolation>
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SciPy interp1d results are different than MatLab interp1
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