Exponential Curve Fitting With Python

I am trying to convert some Matlab code I have for curve fitting my data into python code but am having trouble getting similar answers. The data is: x = array([ 0. , 12.5 ,

Solution 1:

curve_fit(fitFunc, y, x], p0=init_vals) should be curve_fit(fitFunc, x,y, p0=init_vals) ie, x goes before y . fitFunc(A, B, k, t) should be fitFunc(t,A, B, k). The independent variable goes first. See the code below:

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

x = np.array([   0.  ,   12.5 ,   24.5 ,   37.75,   54.  ,   70.25,   87.5 ,
    108.5 ,  129.5 ,  150.5 ,  171.5 ,  193.75,  233.75,  273.75])
y = np.array([-8.79182857, -5.56347794, -5.45683824, -4.30737662, -1.4394612 ,
   -1.58047016, -0.93225927, -0.6719836 , -0.45977157, -0.37622436,
   -0.56115757, -0.3038559 , -0.26594558, -0.26496367])

def fitFunc(t, A, B, k):
    return A - B*np.exp(-k*t)
init_vals = np.random.rand(1,3)

fitParams, fitCovariances = curve_fit(fitFunc, x, y, p0=init_vals)
print fitParams
plt.plot(x,y)
plt.plot(x,fitFunc(x,*fitParams))
plt.show()