使用python拟合“多模态”对数正态分布到数据

import numpy as np
from scipy.stats import lognorm
from scipy.optimize import curve_fit

def multimodal_lognorm(x, *params):
    result = np.zeros_like(x)
    for i in range(0, len(params), 3):
        mean = params[i]
        sigma = params[i+1]
        weight = params[i+2]
        result += weight * lognorm.pdf(x, sigma, scale=np.exp(mean))
    return result

data = np.array([1.2, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0])

# 初始化参数猜测值
initial_guess = [1, 1, 0.5, 2, 1, 0.5]

# 拟合数据
params, _ = curve_fit(multimodal_lognorm, data, np.zeros_like(data), p0=initial_guess)

x = np.linspace(0, 6, 100)
y = multimodal_lognorm(x, *params)