scipy stats.arcsine() | Python

scipy.stats.arcsine()是一个反正弦连续随机变量，使用标准格式和一些形状参数定义以完成其规范。

Parameters :
q : lower and upper tail probability
x : quantiles
loc : [optional]location parameter. Default = 0
scale : [optional]scale parameter. Default = 1
size : [tuple of ints, optional] shape or random variates.
moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : arcsine continuous random variable

编程需要懂一点英语

代码 #1：创建反正弦连续随机变量

# importing scipy
from scipy.stats import arcsine
  
numargs = arcsine.numargs
[ ] = [0.6, ] * numargs
rv = arcsine()
  
print ("RV : \n", rv)

输出：

RV :

代码#2：反正弦随机变量和概率分布函数。

quantile = np.arange (0.01, 1, 0.1)
   
# Random Variates
R = arcsine.rvs(scale = 2,  size = 10)
print ("Random Variates : \n", R)
  
# PDF
R = arcsine.pdf(x = quantile, scale = 2)
print ("\nProbability Distribution : \n", R)

输出：

Random Variates : 
 [1.17353658 1.96350916 1.73419819 0.71255312 0.28760466 1.54410451
 1.9644408  0.35014597 0.26798525 0.24599504]

Probability Distribution : 
 [2.25643896 0.69810843 0.51917523 0.43977033 0.39423905 0.3651505
 0.34568283 0.33260295 0.32421577 0.31960693]

代码#3：图形表示。

# libraries
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))

输出：

Distribution : 
 [0.         0.02040816 0.04081633 0.06122449 0.08163265 0.10204082
 0.12244898 0.14285714 0.16326531 0.18367347 0.20408163 0.2244898
 0.24489796 0.26530612 0.28571429 0.30612245 0.32653061 0.34693878
 0.36734694 0.3877551  0.40816327 0.42857143 0.44897959 0.46938776
 0.48979592 0.51020408 0.53061224 0.55102041 0.57142857 0.59183673
 0.6122449  0.63265306 0.65306122 0.67346939 0.69387755 0.71428571
 0.73469388 0.75510204 0.7755102  0.79591837 0.81632653 0.83673469
 0.85714286 0.87755102 0.89795918 0.91836735 0.93877551 0.95918367
 0.97959184 1.        ]

代码#4：改变位置和规模

from scipy.stats import arcsine
import matplotlib.pyplot as plt
import numpy as np
a = 2
b = 2
x = np.linspace(0, np.minimum(rv.dist.b, 3))
  
# Varying location and scale
y1 = arcsine.pdf(x, -0.1, .8)
y2 = arcsine.pdf(x, -3.25, 3.25)
plt.plot(x, y1, "*", x, y2, "r--")