pdstools.decision_analyzer.plots._sensitivity

Sensitivity / threshold / prioritization-factor boxplot methods.

Functions

threshold_deciles(self, thresholding_on, thresholding_name)

sensitivity(self[, win_rank, hide_priority, ...])

Sensitivity of the prioritization factors.

prio_factor_boxplots(...)

Module Contents

threshold_deciles(self, thresholding_on, thresholding_name, return_df=False)
sensitivity(self, win_rank: int = 1, hide_priority=True, return_df=False, reference_group=None, additional_filters=None, total_decisions: int | None = None)

Sensitivity of the prioritization factors.

If reference_group is None, this works as global sensitivity, otherwise it is local sensitivity where the focus is on the reference_group.

When total_decisions is provided the x-axis shows percentages relative to that number and the hover includes both the absolute influence count and the total decisions.

Parameters:

  • win_rank (int)

  • total_decisions (int | None)

prio_factor_boxplots(self, reference: polars.Expr | list[polars.Expr] | None = None, return_df=False, additional_filters=None, others_filter: polars.Expr | list[polars.Expr] | None = None) → tuple[plotly.graph_objects.Figure, str | None]
Parameters:

  • reference (polars.Expr | list[polars.Expr] | None)

  • others_filter (polars.Expr | list[polars.Expr] | None)

Return type:

tuple[plotly.graph_objects.Figure, str | None]