import numpy as np
from scipy.optimize import curve_fit
# NXFT18XH103F05RL
data = np.array([
[-40,195652],
[-35,148171],
[-30,113347],
[-25,87559],
[-20,68237],
[-15,53650],
[-10,42506],
[-5,33892],
[0,27219],
[5,22021],
[10,17926],
[15,14674],
[20,12081],
[25,10000],
[30,8315],
[35,6948],
[40,5834],
[45,4917],
[50,4161],
[55,3535],
[60,3014],
[65,2586],
[70,2228],
[75,1925],
[80,1669],
[85,1452],
[90,1268],
[95,1110],
[100,974],
[105,858],
[110,758],
[115,672],
[120,596],
[125,531],
])

T_K = data[:, 0] + 273.15
R = data[:, 1]

def steinhart_hart(R, A, B, C):
    return 1 / (A + B * np.log(R) + C * (np.log(R))*(np.log(R))*(np.log(R)))



params, _ = curve_fit(steinhart_hart, R, 1/T_K)

A, B, C = params
print(f"A: {A}, B: {B}, C: {C}")