parameterspace.parameters.categorical

CategoricalParameter (BaseParameter)

Categorical parameter that can take discrete values of any type.

Source code in parameterspace/parameters/categorical.py

class CategoricalParameter(BaseParameter):
    """Categorical parameter that can take discrete values of any type."""

    @store_init_arguments
    def __init__(
        self,
        name: str,
        values: Tuple[Any, ...],
        prior: Union[list, np.ndarray, None] = None,
        transformation: Optional[BaseTransformation] = None,
        inactive_numerical_value: Optional[float] = np.nan,
    ):
        """
        Initialize with options for categorical parameter.

        Args:
            name: Name of the parameter.
            values: Allowed values for this parameter.
            prior: Probabilities for each value (does not need to be normalized).
            transformation: A transformation that can translate the arbitrary type of
                the values to a numerical value. The only supported one right now
                is [parameterspace.transformations.categorical.Cat2Num][], which is
                also used as default.
            inactive_numerical_value: [description]
        """
        self.values = values
        transformation = Cat2Num(values) if transformation is None else transformation

        if prior is None:
            prior = Categorical([1.0] * len(values))
        elif not isinstance(prior, Categorical):
            prior = Categorical(prior)

        super().__init__(
            name,
            prior,
            transformation,
            is_continuous=False,
            is_ordered=False,
            num_values=len(values),
            inactive_numerical_value=inactive_numerical_value,
        )

    def check_value(self, value):
        """Check if value is valid."""
        return value in self.values

check_value(self, value)

Check if value is valid.

Source code in parameterspace/parameters/categorical.py

def check_value(self, value):
    """Check if value is valid."""
    return value in self.values