NumericalDiscreteParameter¶

class baybe.parameters.numerical.NumericalDiscreteParameter[source]¶

Parameter class for discrete numerical parameters (a.k.a. setpoints).

Public methods

`__init__`(name, values[, tolerance])	Method generated by attrs for class NumericalDiscreteParameter.
`from_dict`(dictionary)	Create an object from its dictionary representation.
`from_json`(string)	Create an object from its JSON representation.
`is_in_range`(item)	Return whether an item is within the parameter range.
`summary`()	Return a custom summarization of the parameter.
`to_dict`()	Create an object's dictionary representation.
`to_json`()	Create an object's JSON representation.
`to_searchspace`()	Create a one-dimensional search space from the parameter.
`to_subspace`()	Create a one-dimensional search space from the parameter.
`transform`(series, /)	Transform parameter values from experimental to computational representation.

Public attributes and properties

`comp_df`	Return the computational representation of the parameter.
`is_continuous`	Boolean indicating if this is a continuous parameter.
`is_discrete`	Boolean indicating if this is a discrete parameter.
`is_numerical`	Class variable encoding whether this parameter is numeric.
`values`	The values the parameter can take.
`tolerance`	The absolute tolerance used for deciding whether a value is in range.
`encoding`	An optional encoding for the parameter.
`name`	The name of the parameter

__init__(name: str, values, tolerance: float = 0.0)¶

Method generated by attrs for class NumericalDiscreteParameter.

For details on the parameters, see Public attributes and properties.

classmethod from_dict(dictionary: dict)¶

Create an object from its dictionary representation.

classmethod from_json(string: str)¶

Create an object from its JSON representation.

is_in_range(item: float)[source]¶

Return whether an item is within the parameter range.

Parameters:: item (float) – The item to be checked.
Return type:: bool
Returns:: True if the item is within the parameter range, False otherwise.

summary()¶

Return a custom summarization of the parameter.

to_dict()¶

Create an object’s dictionary representation.

to_json()¶

Create an object’s JSON representation.

to_searchspace()¶

Create a one-dimensional search space from the parameter.

to_subspace()¶

Create a one-dimensional search space from the parameter.

transform(series: Series, /)¶

Transform parameter values from experimental to computational representation.

Parameters:: series (Series) – The parameter values to be transformed.
Return type:: DataFrame
Returns:: The transformed parameter values.

property comp_df: DataFrame¶: Return the computational representation of the parameter.

encoding: ParameterEncoding | None¶: An optional encoding for the parameter.

property is_continuous: bool¶: Boolean indicating if this is a continuous parameter.

property is_discrete: bool¶: Boolean indicating if this is a discrete parameter.

is_numerical: ClassVar[bool] = True¶: Class variable encoding whether this parameter is numeric.

tolerance: float¶: The absolute tolerance used for deciding whether a value is in range. A tolerance larger than half the minimum distance between parameter values is not allowed because that could cause ambiguity when inputting data points later.