CURVE FITTING IN PYTHON USING POLYFIT AND IPYWIDGETS

In this article you will learn how to make a interactive curve fitting in python. the advantage of this it is interactive one so instead of running your code again and again you can ipywidgets to make a interactive curve fitting graph in jupyter

note : this program is specially designed for jupyter 

make sure to install ipywidgets 

pip install ipywidgets (run this anacond command manager)

# MAIN PROGRAM

import numpy

import matplotlib.pyplot as plt

from ipywidgets import interactive

def f(n):

    x = [1,2,3,4,5,6,7,8,9,10,11,12,15,17,22,23,25,30]

    y = [100,90,80,60,60,55,60,65,70,70,75,76,78,79,90,99,99,100]

    curve_model = numpy.poly1d(numpy.polyfit(x, y, n))

    curve_fitting_line = numpy.linspace(1, 30, 1000)

    plt.scatter(x, y)

    plt.plot(curve_fitting_line, curve_model(curve_fitting_line))

    plt.show()

interactive_plot= interactive(f,n=(1,10))

interactive_plot

curve_model = this line of code basically hold all the data and specify what kind of

polyfit/ curve fitting equation we want to use in our graph. the variable n defined

basically the type of equation we are going to use if it's 1 it means we are using

linear regression equation to do that

curve_fitting_line = this line represent that basically show much our curve fitting

happens (if you have any doubt here just comment i will modify the blog and clear your

doubt)

we are using ipywidgets to basically to make this interactive graph there are other

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