python-scipyHow can I use Python SciPy to fit a model?

Using the Python SciPy package, you can fit a model to data by using the curve_fit function. This function takes a function that describes the model, an array of x-values, and an array of y-values, and returns an array of parameters that best fit the data. For example,

from scipy.optimize import curve_fit

def func(x, a, b):
    return a * x + b

xdata = [0, 1, 2]
ydata = [0, 1, 2]

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

print(popt)

The above code would output [1.0, 0.0] as the parameters that best fit the data.

Code explanation

• from scipy.optimize import curve_fit: imports the curve_fit function from the SciPy package
• def func(x, a, b):: defines the model function with two parameters, a and b
• xdata = [0, 1, 2] and ydata = [0, 1, 2]: defines the x- and y-values to fit the model to
• popt, pcov = curve_fit(func, xdata, ydata): calls curve_fit to fit the model to the data
• print(popt): prints the best-fit parameters

Helpful links

• SciPy Optimize Curve Fitting

Edit this code on GitHub