responsibility
==============

.. py:module:: responsibility

.. autoapi-nested-parse::

   calculate causal responsibility



Functions
---------

.. autoapisummary::

   responsibility.subbox
   responsibility.update_depth_reached
   responsibility.prune
   responsibility.causal_explanation


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

.. py:function:: subbox(tree, name, max_depth, min_size, mode, r_map=None)

   Split a box into 4 contiguous children or None if no possible.

   @param tree: a search tree
   @param name: a node name to search for in <tree>
   @param max_depth: tree depth limit for new children
   @param min_size: minimum new child size
   @param mode: spectral, tabular, RGB, L or voxel
   @param r_map=None: responsibility map

   @return None or new children


.. py:function:: update_depth_reached(depth_reached, passing)

   Update the max tree depth reached.

   @param depth_reached: current max_depth
   @param passing: a list of passing Mutant

   @return int


.. py:function:: prune(mutants, technique=Queue.Intersection, keep=None)

   Reduce the search queue to improve both efficiency and (possibly) result quality.

   @param mutants: a list of passing Mutant objects
   @param technique: a Queue enum
   @param keep=None: how many items to keep in the queue, all if keep is None

   @return a list of mutants of length <= keep


.. py:function:: causal_explanation(process, data, args, prediction_func, current_map=None)

   Calculate causal responsiblity.

   @param process: an integer value
   @param data: a Data object
   @param args: a CausalArgs object
   @param prediction_func: a higher order
       function that calls a model and return a Prediction object