(
    study: Study, ordered_dict: bool = False, include_pruned: bool = False
)
return IntersectionSearchSpace(include_pruned=include_pruned).calculate(
        study, ordered_dict=ordered_dict
    )
Return the intersection search space of the :class:`~optuna.study.Study`.

    Intersection search space contains the intersection of parameter distributions that have been
    suggested in the completed trials of the study so far.
    If there are multiple parameters that have the same name but different distributions,
    neither is included in the resulting search space
    (i.e., the parameters with dynamic value ranges are excluded).

    .. note::
        :class:`~optuna.samplers.IntersectionSearchSpace` provides the same functionality with
        a much faster way. Please consider using it if you want to reduce execution time
        as much as possible.

    Args:
        study:
            A study with completed trials.
        ordered_dict:
            A boolean flag determining the return type.
            If :obj:`False`, the returned object will be a :obj:`dict`.
            If :obj:`True`, the returned object will be an :obj:`collections.OrderedDict` sorted by
            keys, i.e. parameter names.
        include_pruned:
            Whether pruned trials should be included in the search space.

    Returns:
        A dictionary containing the parameter names and parameter's distributions.
Return the intersection search space of the :class:`~optuna.study.Study`.
Return the intersection search space of the : class : ~optuna . study . Study .
def intersection_search_space(
    study: Study, ordered_dict: bool = False, include_pruned: bool = False
) -> Dict[str, BaseDistribution]:
    """Return the intersection search space of the :class:`~optuna.study.Study`.

    Intersection search space contains the intersection of parameter distributions that have been
    suggested in the completed trials of the study so far.
    If there are multiple parameters that have the same name but different distributions,
    neither is included in the resulting search space
    (i.e., the parameters with dynamic value ranges are excluded).

    .. note::
        :class:`~optuna.samplers.IntersectionSearchSpace` provides the same functionality with
        a much faster way. Please consider using it if you want to reduce execution time
        as much as possible.

    Args:
        study:
            A study with completed trials.
        ordered_dict:
            A boolean flag determining the return type.
            If :obj:`False`, the returned object will be a :obj:`dict`.
            If :obj:`True`, the returned object will be an :obj:`collections.OrderedDict` sorted by
            keys, i.e. parameter names.
        include_pruned:
            Whether pruned trials should be included in the search space.

    Returns:
        A dictionary containing the parameter names and parameter's distributions.
    """

    return IntersectionSearchSpace(include_pruned=include_pruned).calculate(
        study, ordered_dict=ordered_dict
    )
def intersection_search_space ( study : Study , ordered_dict : bool = False , include_pruned : bool = False ) -> Dict [ str , BaseDistribution ] : return IntersectionSearchSpace ( include_pruned = include_pruned ) . calculate ( study , ordered_dict = ordered_dict )