実験データを $[[t_1, \alpha_1], [t_2, \alpha_2], \cdots]$という形の2次元配列に代入。

rawData = np.array([
[3.55, 21.1],
[4.78, 20.8],
[5.83, 20.8],
[7.0, 20.0],
[8.03, 19.5],
[9.4, 20.0],
[9.58, 19.5],
[10.95, 19.1],
[11.63, 19.8],
[12.5, 18.7],
[13.62, 19.5],
[14.12, 18.4],
[14.45, 18.1],
[14.98, 17.8],
[15.37, 17.8],
[16.07, 17.6],
[16.33, 17.7],
[17.17, 17.5],
[17.85, 17.3],
[18.58, 17.2],
[19.5, 17.1],
[20.55, 16.9],
[26.33, 15.5],
[31.6, 14.7],
[33.75, 14.2],
[33.97, 14.4],
[34.75, 14.3],
[35.25, 14.3],
[35.88, 14.3],
[36.5, 14.2],
[38.25, 14.1],
[38.8, 13.9],
[38.83, 13.8],
[39.18, 13.85],
[39.83, 13.7],
[40.12, 13.8],
[40.8, 13.8],
[52.55, 12.8],
[59.83, 12.3],
[75.67, 11.65],
[90.0, 11.3],
[123, 10.95],
[150.5, 10.8],
[175, 10.65],
[197, 10.6],
])

式 (7), (11), (12) を用いて$K, k_f, k_b$ の誤差を計算、表示。

errKe = np.sqrt(covMat[0][0])/xainf**2
errkf = np.sqrt(k**2*covMat[0][0] + (1-xainf)**2*covMat[1][1] + 2*covMat[0][1])
errkb = np.sqrt(k**2*covMat[0][0] +    xainf**2*covMat[1][1] + 2*covMat[0][1])