Numpy採樣函數

Question

numpy或scipy中是否有任何函數對於給定的pdf，從該分佈採樣的點將返回？

例如，我有高斯分佈的混合物：

means = 0., 8. 
stdevs = 1.0,1.0 
weights = 0.75,0.25 

pdfs = [p * norm.pdf(x, mu, sd) for mu, sd, p in zip(means, stdevs, weights)] 

爲PDF的曲線圖和用於從該分佈採樣應該像點直方圖：

感謝

Answer 1

你可以用numpy解決這個問題

import numpy as np 
x_vals = np.random.normal(0., 1.0, 100) 
y_vals = np.random.normal(8., 1.0, 100) 
x_norm = [*x_vals, *y_vals] 

Answer 2

如果要合併多個pdf，以便仍然可以通過x，則需要創建一個新函數。做到這一點的一種方法是創建一個函數返回一個函數與高斯的加權和。

from scipy.stats import norm 
import numpy as np 

def create_mixed_pdf(means, stdevs, weights): 
    # this uses a lambda function to return the weighted sum of the pdfs at x 
    return lambda x: sum([p*norm(mu, sd).pdf(x) for mu, sd, p in zip(means, stdevs, weights)]) 

# this sets `my_pdf` to be the combined pdf distributions 
my_pdf = create_mixed_pdf(means, stdevs, weights) 

# testing: 
import matplotlib.pyplot as plt 
x = np.arange(-4, 12, .05) 

plt.plot(x, my_pdf(x)) 
plt.show()