backtracking.minimax
====================

.. py:module:: backtracking.minimax

.. autoapi-nested-parse::

   Minimax helps to achieve maximum score in a game by checking all possible moves
   depth is current depth in game tree.

   nodeIndex is index of current node in scores[].
   if move is of maximizer return true else false
   leaves of game tree is stored in scores[]
   height is maximum height of Game tree



Functions
---------

.. autoapisummary::

   backtracking.minimax.main
   backtracking.minimax.minimax


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

.. py:function:: main() -> None

.. py:function:: minimax(depth: int, node_index: int, is_max: bool, scores: list[int], height: float) -> int

   This function implements the minimax algorithm, which helps achieve the optimal
   score for a player in a two-player game by checking all possible moves.
   If the player is the maximizer, then the score is maximized.
   If the player is the minimizer, then the score is minimized.

   Parameters:
   - depth: Current depth in the game tree.
   - node_index: Index of the current node in the scores list.
   - is_max: A boolean indicating whether the current move
             is for the maximizer (True) or minimizer (False).
   - scores: A list containing the scores of the leaves of the game tree.
   - height: The maximum height of the game tree.

   Returns:
   - An integer representing the optimal score for the current player.

   >>> import math
   >>> scores = [90, 23, 6, 33, 21, 65, 123, 34423]
   >>> height = math.log(len(scores), 2)
   >>> minimax(0, 0, True, scores, height)
   65
   >>> minimax(-1, 0, True, scores, height)
   Traceback (most recent call last):
       ...
   ValueError: Depth cannot be less than 0
   >>> minimax(0, 0, True, [], 2)
   Traceback (most recent call last):
       ...
   ValueError: Scores cannot be empty
   >>> scores = [3, 5, 2, 9, 12, 5, 23, 23]
   >>> height = math.log(len(scores), 2)
   >>> minimax(0, 0, True, scores, height)
   12