interpolate curve between three values

Question

I have the following script that plots a graph:

x = np.array([0,1,2])
y = np.array([5, 4.31, 4.01])
plt.plot(x, y)
plt.show()

The problem is, that the line goes straight from point to point, but I want to smooth the line between the points.

If I use scipy.interpolate.spline to smooth my data I got following result:

 order = np.array([0,1,2])
 y = np.array([5, 4.31, 4.01])
 xnew = np.linspace(order.min(), order.max(), 300)
 smooth = spline(order, y, xnew)
 plt.plot(xnew, smooth)
 plt.show()

But I want to have the same result like in that given example

if you know the underlying correlation (e.g. exponential decay or whatsoever), you could fit the function to the data using `scipy.optimize.curvefit`. — Moritz, Jul 21 '18 at 15:45

score 1 · Accepted Answer · answered Jul 21 '18 at 15:32

If you use more points than 3 you will get the same result as in the linked question. There are many ways a spline of order 3 can go through 3 points.

But you may of course reduce the order to 2.

import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import spline

x = np.array([0,1,2])
y = np.array([5, 4.31, 4.01])
plt.plot(x, y)

xnew = np.linspace(x.min(), x.max(), 300)
smooth = spline(x, y, xnew, order=2)
plt.plot(xnew, smooth)


plt.show()

interpolate curve between three values

1 Answers1

Linked