python - 来自实验数据的正态拟合

Question

大家好，我想从实验结果中获得的一组数据中获得正常拟合。由于我从 python 开始，我不知道从哪里开始。这是我的实验数据。它的粒度分布。我想获得平均值和标准。x 是大小，y 是频率。

预先感谢您的任何帮助！

import matplotlib.pyplot as plt
import numpy as np



x=([0.251839516,0.490440575,0.744647994,0.990643452,1.244142316,1.488611658,1.741274792,1.986416351,2.232538986,2.495993944,2.736393641,2.985059803,3.241792581,3.497435276,3.744829674,3.991788039,4.23860106])
y=([0.271164269,0.492366389,1.256781226,2.468772142,4.479769871,8.376708554,11.85803482,14.57231794,15.56056321,14.05547313,11.11227252,7.625604845,3.947070401,2.186355791,0.937144587,0.455061317,0.228687358])
plt.scatter(x,y,color='red',label='Experiment')

标签： pythonnormal-distribution

Answer 1

如果你想使用 SciPy，你有scipy.stats.norm：

from scipy.stats import norm
mu, std = norm.fit(data)