Using a list of coordinates of the turning points of a polynomial, I am trying to find a list of coefficients of the polynomial. The diagram above graphically shows what I'm trying to work out.
I have tried to use numpy.polyfit
to generate a polynomial, however the polynomial given goes through these points wherever, rather than specifically at the turning points.
Does there exist a function which could do this?
If there is no such function an approach I am considdering is to integrate (x-turningX[0])(x-turningX[1])(x-turningX[n])
to find the polynomial but I am unsure how I would go about this in python.
You can create such a curve with scipy.interpolate.CubicHermiteSpline
by giving it an array of zeros for the dydx
parameter. For example, this code
In [60]: import numpy as np
In [61]: from scipy.interpolate import CubicHermiteSpline
In [62]: x = np.array([1, 2.5, 4.5, 6, 7]) # x coordinates of turning points
In [63]: y = np.array([1, 3, 2, 3.5, 2.5]) # y coordinates of turning points
In [64]: p = CubicHermiteSpline(x=x, y=y, dydx=np.zeros_like(y)) # interpolator
In [65]: plot(x, y, 'o')
Out[65]: [<matplotlib.lines.Line2D at 0xa2f1aef90>]
In [66]: xx = np.linspace(0.9, 7.1, 1000)
In [67]: plot(xx, p(xx))
Out[67]: [<matplotlib.lines.Line2D at 0xa287fb9d0>]