metasyn.distribution.normal.LogNormalDistribution

class metasyn.distribution.normal.LogNormalDistribution(mean, sd)

Log-normal distribution for floating point type.

This class implements the log-normal mu and sigma as initialization input.

Parameters:

• mean (float) – Controls the mean of the distribution.

• sd (float) – Controls the width of the distribution.

Examples

>>> LogNormalDistribution(mean=-2.0, sd=4.5)

name

core.lognormal

unique

False

version

1.0

var_type

continuous

__init__(mean, sd)

Parameters:

• mean (float)

• sd (float)

Methods

__init__(mean, sd)
default_distribution([var_type])	Get a distribution with default parameters.
draw()	Draw a random element from the fitted distribution.
draw_list(n)	Draw a list of values from the distribution.
draw_reset()	Reset the drawing of elements to start again.
from_dict(dist_dict)	Create a distribution from a dictionary.
information_criterion(values)	Get the BIC value for a particular set of values.
matches_name(name)	Check whether the name matches the distribution.
provides_var_type(var_type)
schema()	Create sub-schema to validate GMF file.
to_dict()	Convert the distribution to a dictionary.

Attributes

n_par	Number of parameters for distribution.
name	The identifier for the implemented distribution
scipy_class
unique	Whether the distribution creates only unique values
var_type	The variable type of the distribution
version	Version of the implemented distribution