Deleted minmax.py (#9482)

backtracking/minmax.py

@@ -1,69 +0,0 @@
-"""
-Minimax helps to achieve maximum score in a game by checking all possible moves.
-
-"""
-from __future__ import annotations
-
-import math
-
-
-def minimax(
-    depth: int, node_index: int, is_max: bool, scores: list[int], height: float
-) -> int:
-    """
-    depth is current depth in game tree.
-    node_index is index of current node in scores[].
-    scores[] contains the leaves of game tree.
-    height is maximum height of game tree.
-
-    >>> 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
-    """
-
-    if depth < 0:
-        raise ValueError("Depth cannot be less than 0")
-
-    if not scores:
-        raise ValueError("Scores cannot be empty")
-
-    if depth == height:
-        return scores[node_index]
-
-    return (
-        max(
-            minimax(depth + 1, node_index * 2, False, scores, height),
-            minimax(depth + 1, node_index * 2 + 1, False, scores, height),
-        )
-        if is_max
-        else min(
-            minimax(depth + 1, node_index * 2, True, scores, height),
-            minimax(depth + 1, node_index * 2 + 1, True, scores, height),
-        )
-    )
-
-
-def main() -> None:
-    scores = [90, 23, 6, 33, 21, 65, 123, 34423]
-    height = math.log(len(scores), 2)
-    print(f"Optimal value : {minimax(0, 0, True, scores, height)}")
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()
-    main()