Sympy stats.VonMises() in Python
Last Updated :
08 Jun, 2020
With the help of sympy.stats.VonMises()
method, we can get the continuous random variable which represents the Von Mises distribution.
Syntax : sympy.stats.VonMises(name, mu, k)
Where, mu and k are real number.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.VonMises()
method, we are able to get the continuous random variable representing Von Mises distribution by using this method.
from sympy.stats import VonMises, density
from sympy import Symbol, pprint
z = Symbol( "z" )
mu = Symbol( "mu" , positive = True )
k = Symbol( "k" , positive = True )
X = VonMises( "x" , mu, k)
gfg = density(X)(z)
pprint(gfg)
|
Output :
k*cos(mu – z)
e
——————
2*pi*besseli(0, k)
Example #2 :
from sympy.stats import VonMises, density
from sympy import Symbol, pprint
z = 0.78
mu = 1.23
k = 4
X = VonMises( "x" , mu, k)
gfg = density(X)(z)
pprint(gfg)
|
Output :
18.3318728167628
—————-
pi*besseli(0, 4)
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