scipy stats.cosine() | Python
Last Updated :
20 Mar, 2019
scipy.stats.cosine() is an cosine continuous random variable that is defined with a standard format and some shape parameters to complete its specification.
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 : cosine continuous random variable
Code #1 : Creating cosine continuous random variable
from scipy.stats import cosine
numargs = cosine.numargs
[] = [ 0.6 , ] * numargs
rv = cosine()
print ( "RV : \n" , rv)
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Output :
RV :
<scipy.stats._distn_infrastructure.rv_frozen object at 0x000001FDC89DEE10>
Code #2 : cosine random variates and probability distribution function.
import numpy as np
quantile = np.arange ( 0.01 , 1 , 0.1 )
R = cosine.rvs(scale = 2 , size = 10 )
print ( "Random Variates : \n" , R)
R = cosine.pdf(quantile, loc = 0 , scale = 1 )
print ( "\nProbability Distribution : \n" , R)
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Output:
Random Variates :
[ 1.2323289 2.49938238 0.29072394 -1.10925673 0.55881836 1.70470811
1.29090489 2.64865261 4.32789346 0.14597439]
Probability Distribution :
[0.31830193 0.31734797 0.3148134 0.31072354 0.30511926 0.29805655
0.28960598 0.27985198 0.26889203 0.25683561]
Code #3 : Graphical Representation.
import numpy as np
import matplotlib.pyplot as plt
distribution = np.linspace( 0 , np.minimum(rv.dist.b, 5 ))
print ( "Distribution : \n" , distribution)
plot = plt.plot(distribution, rv.pdf(distribution))
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Output :
Distribution :
[0. 0.06411414 0.12822827 0.19234241 0.25645654 0.32057068
0.38468481 0.44879895 0.51291309 0.57702722 0.64114136 0.70525549
0.76936963 0.83348377 0.8975979 0.96171204 1.02582617 1.08994031
1.15405444 1.21816858 1.28228272 1.34639685 1.41051099 1.47462512
1.53873926 1.60285339 1.66696753 1.73108167 1.7951958 1.85930994
1.92342407 1.98753821 2.05165235 2.11576648 2.17988062 2.24399475
2.30810889 2.37222302 2.43633716 2.5004513 2.56456543 2.62867957
2.6927937 2.75690784 2.82102197 2.88513611 2.94925025 3.01336438
3.07747852 3.14159265]
Code #4: Varying Location and Scale
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace( 0 , 5 , 100 )
y1 = cosine.pdf(x, 1 , 6 )
y2 = cosine.pdf(x, 1 , 4 )
plt.plot(x, y1, "*" , x, y2, "r--" )
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