src.pydasa.elements.specs.statistical

Statistical perspective for variable representation.

This module defines the StatisticalSpecs class representing the probabilistic distribution and sampling properties of a variable.

Classes:

StatisticalSpecs: Statistical variable specifications

IMPORTANT: Based on the theory from:

# H.Gorter, Dimensionalanalyse: Eine Theoririe der physikalischen Dimensionen mit Anwendungen

Classes

StatisticalSpecs

Statistical perspective: probabilistic distributions. Answers the question: "How do we MODEL uncertainty?"

Module Contents

class src.pydasa.elements.specs.statistical.StatisticalSpecs

Statistical perspective: probabilistic distributions. Answers the question: “How do we MODEL uncertainty?”

This perspective focuses on:

• Probability distribution types (uniform, normal, beta, custom)

• Distribution parameters

• Random sampling mechanisms

• Monte Carlo simulation support

• Uncertainty quantification

_sym: str

_dist_type: str = 'uniform'

Type of distribution (e.g., ‘uniform’, ‘normal’). By default is ‘uniform’.

_dist_params: Dict[str, Any] | None

1} for uniform).

Type:

Parameters for the distribution (e.g., {‘min’

Type:

0, ‘max’

_depends: List[str] = []

List of variable names that this variable depends on. (e.g., for calculated variables like F = m*a).

_dist_func: Callable[Ellipsis, float] | None = None

Callable representing the distribution function defined externally by the user.

sample(*args)

sample() Generate a random sample.

Parameters:

*args – Additional arguments for the distribution function.

Returns:

Random sample from distribution.

Return type:

float

Raises:

ValueError – If no distribution has been set.

has_function()

has_function() Check if distribution is set.

Returns:

True if distribution is configured.

Return type:

bool

property dist_type: str

dist_type Get the distribution type.

Returns:

Distribution type (e.g., ‘uniform’, ‘normal’).

Return type:

str

property dist_params: Dict[str, Any] | None

dist_params Get the distribution parameters.

Returns:

Distribution parameters.

Return type:

Optional[Dict[str, Any]

property dist_func: Callable[Ellipsis, float] | None

dist_func Get the distribution function.

Returns:

Distribution function.

Return type:

Optional[Callable]

property depends: List[str]

depends Get the list of variable dependencies.

Returns:

List of variable names that this variable depends on.

Return type:

List[str]

clear()

clear() Reset statistical attributes to default values.

Resets distribution type, parameters, and function.

Return type:

None