pdstools.decision_analyzer.plots._sensitivity
=============================================

.. py:module:: pdstools.decision_analyzer.plots._sensitivity

.. autoapi-nested-parse::

   Sensitivity / threshold / prioritization-factor boxplot methods.



Functions
---------

.. autoapisummary::

   pdstools.decision_analyzer.plots._sensitivity.threshold_deciles
   pdstools.decision_analyzer.plots._sensitivity.sensitivity
   pdstools.decision_analyzer.plots._sensitivity.prio_factor_boxplots


Module Contents
---------------

.. py:function:: threshold_deciles(self, thresholding_on, thresholding_name, return_df=False)

.. py:function:: 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.


.. py:function:: 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]