atoti_ai.AutoExplain - Atoti Hub

final class atoti_ai.AutoExplain

Manage the Auto-Explain feature of a Cube.

Example

Read and set the Auto-Explain constants as attributes of the cube’s auto_explain.

See also: atoti.Cube.auto_explain.

`excluded_hierarchies`	The hierarchies that are never explored.
`excluded_hierarchies_per_measure`	The per-measure overrides of `excluded_hierarchies`, keyed by measure name.
`included_hierarchies`	The hierarchies exploration is restricted to.
`included_hierarchies_per_measure`	The per-measure overrides of `included_hierarchies`, keyed by measure name.
`max_depth`	The maximum number of hierarchies the algorithm drills down through.
`max_distinct_hierarchies`	The maximum number of distinct hierarchies reported across the explanation.
`max_entropy`	The maximum entropy above which a level is considered too uniform to explain.
`max_members_per_level`	The maximum number of members reported per level.
`min_percentage_absolute_contribution`	The minimum absolute contribution (as a percentage) a member must reach to be reported.
`min_percentage_relative_contribution`	The minimum relative contribution (as a percentage) a member must reach to be reported.
`min_variation_threshold`	The minimum variation a contributor must reach to be reported.
`opposite_contributors_included`	Whether contributors moving in the opposite direction of the overall variation are also reported.

atoti_ai.AiConfig

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