如何在scipy.stats中制作混合随机变量

import numpy as np
from scipy.stats import rv_continuous

class MixtureRandomVariable(rv_continuous):
    def __init__(self, components, weights):
        self.components = components
        self.weights = weights
        super().__init__(a=min(components), b=max(components))

    def _pdf(self, x):
        pdf = np.zeros_like(x)
        for component, weight in zip(self.components, self.weights):
            pdf += weight * component.pdf(x)
        return pdf

    def _cdf(self, x):
        cdf = np.zeros_like(x)
        for component, weight in zip(self.components, self.weights):
            cdf += weight * component.cdf(x)
        return cdf

# 定义两个组成部分的概率密度函数和权重
component1 = scipy.stats.norm(loc=0, scale=1)
component2 = scipy.stats.norm(loc=2, scale=0.5)
components = [component1, component2]
weights = [0.7, 0.3]

# 创建混合随机变量
mixture_rv = MixtureRandomVariable(components, weights)

# 生成随机样本
samples = mixture_rv.rvs(size=1000)

# 打印混合随机变量的统计信息
print("Mean:", mixture_rv.mean())
print("Variance:", mixture_rv.var())
print("Median:", mixture_rv.median())

import numpy as np
from scipy.stats import rv_discrete

class MixtureRandomVariable(rv_discrete):
    def __init__(self, components, weights):
        self.components = components
        self.weights = weights
        super().__init__(values=np.arange(len(components)))

    def _pmf(self, x):
        pmf = np.zeros_like(x, dtype=float)
        for i, component in enumerate(self.components):
            pmf[x == i] = self.weights[i] * component.pmf(x[x == i])
        return pmf

    def _cdf(self, x):
        cdf = np.zeros_like(x, dtype=float)
        for i, component in enumerate(self.components):
            cdf[x >= i] += self.weights[i] * component.pmf(x[x >= i])
        return cdf

# 定义两个组成部分的概率质量函数和权重
component1 = scipy.stats.poisson(mu=2)
component2 = scipy.stats.poisson(mu=5)
components = [component1, component2]
weights = [0.6, 0.4]

# 创建混合随机变量
mixture_rv = MixtureRandomVariable(components, weights)

# 生成随机样本
samples = mixture_rv.rvs(size=1000)

# 打印混合随机变量的统计信息
print("Mean:", mixture_rv.mean())
print("Variance:", mixture_rv.var())
print("Median:", mixture_rv.median())