import numpy as np
from scipy.optimize import curve_fit
# NXFT15XH103
data = np.array([
[-40,197338],
[-35,149395],
[-30,114345],
[-25,88381],
[-20,68915],
[-15,54166],
[-10,42889],
[-5,34196],
[0,27445],
[5,22165],
[10,18010],
[15,14720],
[20,12099],
[25,10000],
[30,8309],
[35,6939],
[40,5824],
[45,4911],
[50,4160],
[55,3539],
[60,3024],
[65,2593],
[70,2233],
[75,1929],
[80,1673],
[85,1455],
[90,1270],
[95,1112],
[100,976],
[105,860],
[110,759],
[115,673],
[120,598],
[125,532],
])

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}")