Uniform Distribution in Python

scipy.stats.uniform() is a Uniform continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution.

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 : Uniform continuous random variable

Code #1 : Creating Uniform continuous random variable

# importing library  

from scipy.stats import uniform     
numargs = uniform .numargs 
a, b = 0.2, 0.8
rv = uniform (a, b)    
 print ("RV : \n", rv)  

Output :

RV : 
 scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D9F1E708

Code #2 : Uniform continuous variates and probability distribution

import numpy as np 
quantile = np.arange (0.01, 1, 0.1)  
# Random Variates 
R = uniform .rvs(a, b, size = 10) 
print ("Random Variates : \n", R)  

 # PDF 
x = np.linspace(uniform.ppf(0.01, a, b),             
   uniform.ppf(0.99, a, b), 10)

R = uniform.pdf(x, 1, 3)
print ("\nProbability Distribution : \n", R) 

Output :

Random Variates : 
 [0.30819979 0.95991962 0.70622125 0.60895239 0.72550267 0.73555393
 0.3757751  0.88295358 0.50726709 0.57936421]

Probability Distribution : 
 [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]

Code #3 : Graphical Representation.

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)) 

Output :

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.        ]
  

Code #4 : Varying Positional Arguments

import matplotlib.pyplot as plt 
import numpy as np   

x = np.linspace(0, 5, 100)      

# Varying positional arguments 
y1 = uniform.pdf(x, a, b) 
y2 = uniform.pdf(x, a, b) 
plt.plot(x, y1, "*", x, y2, "r--") 
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