With the help of sympy.stats.Nakagami()
method, we can get the continuous random variable which represents the nakagami distribution.
Syntax :
sympy.stats.Nakagami(name, mu, omega)
Where, mu and omega are real number and mu > 1/2, omega > 0.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.Nakagami()
method, we are able to get the continuous random variable representing nakagami distribution by using this method.
# Import sympy and Nakagami from sympy.stats import Nakagami, density from sympy import Symbol, pprint z = Symbol( "z" ) mu = Symbol( "mu" , positive = True ) omega = Symbol( "omega" , positive = True ) # Using sympy.stats.Nakagami() method X = Nakagami( "x" , mu, omega) gfg = density(X)(z) pprint(gfg) |
Output :
2
-mu*z
——-
mu -mu 2*mu – 1 omega
2*mu *omega *z *e
———————————-
Gamma(mu)
Example #2 :
# Import sympy and Nakagami from sympy.stats import Nakagami, density from sympy import Symbol, pprint z = 1.1 mu = 0.5 omega = 4 # Using sympy.stats.Nakagami() method X = Nakagami( "x" , mu, omega) gfg = density(X)(z) pprint(gfg) |
Output :
0.342943855019384