Algorithm_Implementations/Linear_Curve_Fitting.py at main · daijingz/Algorithm_Implementations · GitHub

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# Author: Jingze Dai
# Email Address: [email protected] or [email protected]
# Github: https://github.com/daijingz
# Linkedin: https://www.linkedin.com/in/jingze-dai/
# Description: Linear curve fitting (drawing linear curves for 2-dimensional data points)
# fit a straight line to the economic data
from numpy import arange
from pandas import read_csv
from scipy.optimize import curve_fit
from matplotlib import pyplot


# define the true objective function
def objective(x, a, b):
    return a * x + b


# load the dataset
url = 'https://raw.githubusercontent.com/jbrownlee/Datasets/master/longley.csv'
dataframe = read_csv(url, header=None)
data = dataframe.values
# choose the input and output variables
x, y = data[:, 4], data[:, -1]
# curve fit
popt, _ = curve_fit(objective, x, y)
# summarize the parameter values
a, b = popt
print('y = %.5f * x + %.5f' % (a, b))
# plot input vs output
pyplot.scatter(x, y)
# define a sequence of inputs between the smallest and largest known inputs
x_line = arange(min(x), max(x), 1)
# calculate the output for the range
y_line = objective(x_line, a, b)
# create a line plot for the mapping function
pyplot.plot(x_line, y_line, '--', color='red')
pyplot.show()