import numpy as np 

import matplotlib.pyplot as plt 

from scipy.optimize import curve_fit

​

#Curve fit functions

def linear_func(t,a,b):

    return a*t+b

def quadratic_func(t,a,b,c):

    return a*pow(t,2)+b*t+c

def cubic_func(t,a,b,c,d):

    return a*pow(t,3)+b*pow(t,2)+c*t+d

def quartic_func(t,a,b,c,d,e):

    return a*pow(t,4)+b*pow(t,3)+c*pow(t,2)+d*t+e

​

​

#Function to read data file

def read_file():

    temp = []

    cp = []

    for line in open('data','r'):

        value = line.split(',')

        temp.append(float(value[0]))

        cp.append(float(value[1]))

    return[temp,cp]

​

​

#Curve fit for linear equation

temp,cp = read_file()

popt,pcov = curve_fit(linear_func,temp,cp)

fit_cp = linear_func(np.array(temp),*popt)

plt.figure(1)

plt.plot(temp,cp,color='blue')

plt.plot(temp,fit_cp,color='red')

plt.legend(['Actual data','Curve fit'])

plt.title('Linear curve fit')

plt.xlabel('Temprature in [k]')

plt.ylabel('Cp')

​

​

#Curve fit for quadratic equation

popt,pcov = curve_fit(quadratic_func,temp,cp)

fit_cp = quadratic_func(np.array(temp),*popt)

plt.figure(2)

plt.plot(temp,cp,color='blue')

plt.plot(temp,fit_cp,color='red')

plt.legend(['Actual data','Curve fit'])

plt.title('Quadratic curve fit')

plt.xlabel('Temprature in [k]')

plt.ylabel('Cp')

​

​

#Curve fit for cubic equation

popt,pcov = curve_fit(cubic_func,temp,cp)

fit_cp = cubic_func(np.array(temp),*popt)

plt.figure(3)

plt.plot(temp,cp,color='blue')

plt.plot(temp,fit_cp,color='red')

plt.legend(['Actual data','Curve fit'])

plt.title('Cubic curve fit')

plt.xlabel('Temprature in [k]')

plt.ylabel('Cp')

​

​

#Curve fit for quartic equation

popt,pcov = curve_fit(quartic_func,temp,cp)

fit_cp = quartic_func(np.array(temp),*popt)

plt.figure(4)

plt.plot(temp,cp,color='blue')

plt.plot(temp,fit_cp,color='red')

plt.legend(['Actual data','Curve fit'])

plt.title('Quartic curve fit')

plt.xlabel('Temprature in [k]')

plt.ylabel('Cp')

plt.show()