CODEWITHSUNDEEP
pythonnumpymatplotlibscipy
jm18457
jm18457

Reputation: 463

How to do curve_fit in python

I need to curve fit a set of data using y = x / (a + x), where a is the parameter that I am required to get from this excercise.

import numpy as np 
import matplotlib.pyplot as plt 
from scipy.optimize import curve_fit

x = [1, 2, 7, 10, 20, 70, 200, 1000]
y = [0, 0, 15.3, 34.6, 49.3, 82.6, 100]
def fit(x, a):
    return x/(a+x)
par, con = curve_fit(fit, x, y)
plt.plot(x, fit(x, par[0]))
plt.show()

Using this I get some abomination of a fit. Doesn't even remotely fit.

If I try it like this:

def fit(x, a, b):
    return b*x/(a+x)

I get a fit but it's without round cornerns. It's just straight lines. What am I doing wrong?

Upvotes: 1

Views: 586

Answers (1)

CT Zhu
CT Zhu

Reputation: 54330

Notice that your x is a list of int, in Python division are by default integer division, which is not what you want here.

Therefore, a few changes will make it work, use the 2nd function as an example, your first function is not going to fit well as it will have a limit of 1 when x->inf:

def fit(x, a, b):
    return b*x*1./(a+x)
A, B=curve_fit(fit, x, y)[0]
plt.plot(x, fit(x, A, B))
plt.plot(x, y, 'r+')
plt.savefig('temp.png')

enter image description here

It is a set of straight lines because you only calculate y at those x values, to get a curve: change the plotting call to plt.plot(np.linspace(0,200,100), fit(np.linspace(0,200,100), A, B)) enter image description here

Upvotes: 3

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