import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
def func(t, a, b, c, d):
return a*pow(t,3) + b*pow(t,2) + c*t + d
def read_file():
temperature = []
cp = []
for line in open('data','r'):
values = line.split(',')
temperature.append(float(values[0]))
cp.append(float(values[1]))
return [temperature, cp]
temperature, cp = read_file()
a = 0
b = 399
fit_cp = []
for i in range(0,8):
c = temperature[a:b+1]
d = cp[a:b+1]
popt, pcov = curve_fit(func, c, d)
z = func(np.array(c), *popt)
for j in z:
fit_cp.append(j)
a = b + 1
b = b + 400
plt.figure()
plt.plot(temperature, cp, color = 'green')
plt.plot(temperature, fit_cp, color = 'red')
plt.legend(['Actual data','curve fit'])
plt.xlabel('temperature [k]')
plt.ylabel('cp')
plt.show()
