NormalDistribution

class pharmpy.model.NormalDistribution(name, level, mean, variance)

Bases: Distribution

Normal distribution for one random variable

Parameters:

• name (str) – Name of the random variable

• level (str) – Name of the variability level

• mean (expression or number) – Mean of the random variable

• variance (expression or number) – Variance of the random variable

Example

>>> from pharmpy.model import NormalDistribution, Parameter
>>> omega = Parameter.create('OMEGA_CL', 0.1)
>>> dist = NormalDistribution.create("IIV_CL", "IIV", 0, omega.symbol)
>>> dist
IIV_CL ~ N(0, OMEGA_CL)

Attributes Summary

free_symbols	Free symbols including random variable itself
level	Name of VariabilityLevel of the random variables
mean
names	Names of random variables of distribution
variance

Methods Summary

create(name, level, mean, variance)
evalf(parameters)
from_dict(d)
get_covariance(name1, name2)
get_variance(name)
latex_string([aligned])
replace(**kwargs)	Replace properties and create a new NormalDistribution
subs(d)	Substitute expressions
to_dict()

Attributes Documentation

free_symbols

Free symbols including random variable itself

level

mean

names

variance

Methods Documentation

classmethod create(name, level, mean, variance)

evalf(parameters)

classmethod from_dict(d)

get_covariance(name1, name2)

get_variance(name)

latex_string(aligned=False)

replace(**kwargs)

Replace properties and create a new NormalDistribution

subs(d)

Substitute expressions

Parameters:

d (dict) – Dictionary of from: to pairs for substitution

Examples

>>> import sympy
>>> from pharmpy.model import NormalDistribution, Parameter
>>> omega = Parameter.create("OMEGA_CL", 0.1)
>>> dist = NormalDistribution.create("IIV_CL", "IIV", 0, omega.symbol)
>>> dist = dist.subs({omega.symbol: sympy.Symbol("OMEGA_NEW")})
>>> dist
IIV_CL ~ N(0, OMEGA_NEW)

to_dict()