With the help of sympy.stats.JointRV()
method, we can get the continuous joint random variable which represents the Von Mises distribution.
Syntax :
sympy.stats.JointRV(name, pdf)
Return : Return the continuous joint random variable.
Example #1 :
In this example we can see that by using sympy.stats.JointRV()
method, we are able to get the continuous joint random variable representing JointRV distribution by using this method.
# Import sympy and JointRV from sympy.stats import JointRV, density
from sympy import Symbol, pprint
z = Symbol( "z" )
pdf = 2 * pi * z
# Using sympy.stats.JointRV() method X = JointRV( "x" , pdf)
gfg = density(X)
pprint(gfg) |
Output :
JointDistributionHandmade(Lambda((), 2*pi*z), FiniteSet(()))
Example #2 :
# Import sympy and JointRV from sympy.stats import JointRV, density
from sympy import Symbol, pprint
z = 3
pdf = 2 * pi * z
# Using sympy.stats.JointRV() method X = JointRV( "x" , pdf)
gfg = density(X)
pprint(gfg) |
Output :
6*pi