python-scipyHow do I use Python and SciPy to fit an exponential curve?

To fit an exponential curve with Python and SciPy, the curve_fit function from scipy.optimize can be used.

The curve_fit function takes a function with the desired curve shape as an argument, as well as the data points to fit the curve to.

For example, to fit an exponential curve to data points xdata and ydata:

from scipy.optimize import curve_fit
import numpy as np

def func(x, a, b, c):
    return a * np.exp(-b * x) + c

popt, pcov = curve_fit(func, xdata, ydata)

The popt variable contains the best-fit parameters for the curve, and pcov contains the covariance of the parameters.

Parts of the code:

• from scipy.optimize import curve_fit: imports the curve_fit function from SciPy
• import numpy as np: imports the NumPy library
• def func(x, a, b, c):: defines the function for the exponential curve, with parameters a, b, and c
• popt, pcov = curve_fit(func, xdata, ydata): uses curve_fit to fit the data points to the defined exponential curve

Helpful links

• https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html
• https://docs.scipy.org/doc/numpy/reference/

Edit this code on GitHub