Smoothing out curve in Python

Question

I have two lists of data points:

list_x = [-10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,         


        

Answer 1

One easy option that echoes the suggestion from Davis Herring would be to use a polynomial approximation for the data

import numpy as np
import matplotlib.pyplot as plt

plt.figure()
poly = np.polyfit(list_x,list_y,5)
poly_y = np.poly1d(poly)(list_x)
plt.plot(list_x,poly_y)
plt.plot(list_x,list_y)
plt.show()

You would notice the oscillation at the right end of the plot that is not present in the original data which is an artifact of polynomial approximation.

Spline interpolation as suggested above by Davis is another good option. Varying the smoothness parameter s you can achieve different balance between smoothness and distance to the original data.

from scipy.interpolate import splrep, splev

plt.figure()
bspl = splrep(list_x,list_y,s=5)
bspl_y = splev(list_x,bspl)
plt.plot(list_x,list_y)
plt.plot(list_x,bspl_y)
plt.show()

Answer 2

Because your data is approximate (i.e., it has been quantized), you want an approximating spline, not an interpolating spline.