python polynomial fitting and derivatives

1
votes

I am trying to re-implemet a method I have read in a paper but am not sure how to do some aspects of it. It is based upon least squares polynomial fitting and its derivative.

I have my input data such that:

x = [ 421.25571634  426.25279224  431.24986815  436.24694405  441.24401995
      446.24109586  451.23817176 .............. 621.13875245  626.13582836  
      631.13290426  636.12998016  641.12705606 646.12413197]

y = [ 0.02931459  0.03093554  0.03563261  0.03440331  0.03535223  0.03594375
      0.03639583  ..........  0.0525954   0.05118096  0.05143359  0.05036936    
      0.04952418  0.04774826]

I can fit a 5th order least squares polynomial to this using:

coeffs = numpy.polyfit(x, y, 5)
ffit = numpy.poly1d(coeffs)

and can plot this using matplotlib.

ffit returns me:

           5             4             3            2
6.267e-12 x - 1.642e-08 x + 1.709e-05 x - 0.008833 x + 2.266 x - 231.1

However, I would like to find the first derivative of this and plot this line also. Is there a pythonic way of doing this? I have a lot of data so it would need to be as automated as possible. I understand differentiation but am unsure how I could do it in python.

1
pythonpolynomial-mathdifferentiation

1 Answers

2
votes

You can use fderiv = ffit.deriv(). This will return the derivative of type poly1d.