metasyn.distribution.normal.ContinuousTruncatedNormalDistribution

class metasyn.distribution.normal.ContinuousTruncatedNormalDistribution(lower, upper, mean, sd)

Truncated normal distribution for floating point type.

Parameters:

• lower (float) – Lower bound of the truncated normal distribution.

• upper (float) – Upper bound of the truncated normal distribution.

• mean (float) – Mean of the non-truncated normal distribution.

• sd (float) – Standard deviation of the non-truncated normal distribution.

Examples

>>> TruncatedNormalDistribution(lower=1.0, upper=3.5, mean=2.3, sd=5)

name

core.truncated_normal

unique

False

version

1.0

var_type

continuous

__init__(lower, upper, mean, sd)

Parameters:

• lower (float)

• upper (float)

• mean (float)

• sd (float)

Methods

__init__(lower, upper, 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