Fix min() error for small time limits (t=0.1)

chesspp/baysian_mcts.py

@@ -9,10 +9,10 @@ from chesspp.util_gaussian import gaussian_ucb1, max_gaussian, min_gaussian
 class BayesianMctsNode(IMctsNode):
     def __init__(self, board: chess.Board, strategy: IStrategy, color: chess.Color, parent: Self | None,
                  move: chess.Move | None,
-                 random_state: random.Random, inherit_result: int | None = None, depth: int = 0):
+                 random_state: random.Random, inherit_result: int | None = None, depth: int = 0, visits: int = 0):
         super().__init__(board, strategy, parent, move, random_state)
         self.color = color  # Color of the player whose turn it is
-        self.visits = 0
+        self.visits = visits
         self.result = inherit_result if inherit_result is not None else 0
         self._set_mu_sigma()
         self.depth = depth
@@ -140,8 +140,7 @@ class BayesianMcts(IMcts):
 
     def __init__(self, board: chess.Board, strategy: IStrategy, color: chess.Color, seed: int | None = None):
         super().__init__(board, strategy, seed)
-        self.root = BayesianMctsNode(board, strategy, color, None, None, self.random_state)
-        self.root.visits += 1
+        self.root = BayesianMctsNode(board, strategy, color, None, None, self.random_state, visits=1)
         self.color = color
 
     def sample(self, runs: int = 1000) -> None:
@@ -164,10 +163,11 @@ class BayesianMcts(IMcts):
                 child.depth = 0
                 self.root.parent = None
                 self.root.update_depth(0)
+                self.root.visits = 1
                 return
 
         # if no child node contains the move, initialize a new tree.
-        self.root = BayesianMctsNode(self.board, self.root.strategy, self.color, None, None, self.random_state)
+        self.root = BayesianMctsNode(self.board, self.root.strategy, self.color, None, None, self.random_state, visits=1)
 
     def get_children(self) -> list[IMctsNode]:
         return self.root.children