Python Scipy stats.foldnorm()用法及代碼示例

scipy.stats.foldnorm()是折疊的普通連續隨機變量，它使用標準格式和一些形狀參數定義以完成其規格。

參數：
q :上下尾概率
a :形狀參數
x :分位數
loc :[可選]位置參數。默認值= 0
scale:[可選]比例參數。默認值= 1
size :[int型元組，可選]形狀或隨機變量。
moments:[可選]由字母['mvsk']組成； “ m” =均值，“ v” =方差，“ s” = Fisher的偏度，“ k” = Fisher的峰度。 (默認=“ MV”)。

Results:折疊正態連續隨機變量

代碼1：創建折疊後的普通連續隨機變量

from scipy.stats import foldnorm 
  
numargs = foldnorm.numargs 
[a] = [0.7, ] * numargs 
rv = foldnorm(a) 
  
print ("RV:\n", rv) 

輸出：

RV:
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D56531160>

代碼2：折疊正態隨機變量和概率分布。

import numpy as np 
quantile = np.arange (0.01, 1, 0.1) 
   
# Random Variates 
R = foldnorm.rvs(a, scale = 2,  size = 10) 
print ("Random Variates:\n", R) 
  
# PDF 
R = foldnorm.pdf(a, quantile, loc = 0, scale = 1) 
print ("\nProbability Distribution:\n", R)

輸出：

Random Variates:
 [1.91938545 1.98147825 2.45557747 6.33452251 1.94893049 1.67444448
 1.33462558 2.94928303 0.87723162 1.16012323]

Probability Distribution:
 [0.62449194 0.6225821  0.61750041 0.60927878 0.59797273 0.58366613
 0.56647659 0.54656084 0.52411892 0.49939664]
 

代碼3：圖形表示。

import numpy as np 
import matplotlib.pyplot as plt 
  
distribution = np.linspace(0, np.minimum(rv.dist.b, 3)) 
print("Distribution:\n", distribution) 
  
plot = plt.plot(distribution, rv.pdf(distribution))

輸出：

Distribution:
 [0.         0.06122449 0.12244898 0.18367347 0.24489796 0.30612245
 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449  0.67346939
 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633
 1.10204082 1.16326531 1.2244898  1.28571429 1.34693878 1.40816327
 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102
 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714
 2.20408163 2.26530612 2.32653061 2.3877551  2.44897959 2.51020408
 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102
 2.93877551 3.        ]

代碼4：更改位置參數

import matplotlib.pyplot as plt 
import numpy as np 
  
x = np.linspace(0, 5, 100) 
  
# Varying positional arguments 
y1 = foldnorm.pdf(x, 1, 3) 
y2 = foldnorm.pdf(x, 1, 4) 
plt.plot(x, y1, "*", x, y2, "r--")

輸出：