Added cli parameters for simulation test

main.py

@@ -1,4 +1,6 @@
 import random
+import time
+
 import chess
 import chess.engine
 import chess.pgn
@@ -9,6 +11,8 @@ from chesspp.stockfish_strategy import StockFishStrategy
 from chesspp import engine
 from chesspp import util
 from chesspp import simulation, eval
+import argparse
+import os
 
 
 def test_simulate():
@@ -37,7 +41,10 @@ def test_bayes_mcts():
     seed = None
     strategy = RandomStrategy(random.Random(seed))
     mcts = BayesianMcts(board, strategy, chess.BLACK, seed)
-    mcts.sample()
+    t1 = time.time_ns()
+    mcts.sample(1)
+    t2 = time.time_ns()
+    print ((t2 - t1)/1e6)
     mcts.print()
     for move, score in mcts.get_moves().items():
         print("move (mcts):", move, " with score:", score)
@@ -80,11 +87,20 @@ def analyze_results(moves: dict):
 
 
 def test_evaluation():
-    a = engine.BayesMctsEngine
-    b = engine.ClassicMctsEngine
-    limit = engine.Limit(time=0.5)
-    evaluator = simulation.Evaluation(a, StockFishStrategy(), b, StockFishStrategy(), limit)
-    results = evaluator.run(24)
+    a, b, s1, s2, n, limit, stockfish_path, proc = read_arguments()
+    limit = engine.Limit(time=limit)
+    if s1 == StockFishStrategy:
+        strat1 = StockFishStrategy(stockfish_path)
+    else:
+        strat1 = s1()
+
+    if s2 == StockFishStrategy:
+        strat2 = StockFishStrategy(stockfish_path)
+    else:
+        strat2 = s1()
+
+    evaluator = simulation.Evaluation(a, strat1, b, strat2, limit)
+    results = evaluator.run(n, proc)
     a_results = len(list(filter(lambda x: x.winner == simulation.Winner.Engine_A, results))) / len(results) * 100
     b_results = len(list(filter(lambda x: x.winner == simulation.Winner.Engine_B, results))) / len(results) * 100
     draws = len(list(filter(lambda x: x.winner == simulation.Winner.Draw, results))) / len(results) * 100
@@ -94,6 +110,43 @@ def test_evaluation():
     print(f"{draws}% of games resulted in a draw")
 
 
+def read_arguments():
+    parser = argparse.ArgumentParser(
+        prog='EvaluateEngine',
+        description='Compare two engines by playing multiple games against each other'
+    )
+
+    engines = {"Classic": engine.ClassicMctsEngine, "Baysian": engine.BayesMctsEngine, "Random": engine.RandomEngine}
+    strategies = {"Random": RandomStrategy, "Stockfish": StockFishStrategy}
+
+    if os.name == 'nt':
+        stockfish_default = "../stockfish/stockfish-windows-x86-64-avx2"
+    else:
+        stockfish_default = "../stockfish/stockfish-ubuntu-x86-64-avx2"
+
+    parser.add_argument("--proc", default=2, help="Number of processors to use for simulation, default=1")
+    parser.add_argument("--time", default=0.5, help="Time limit for each simulation step, default=0.5")
+    parser.add_argument("-n", default=100, help="Number of games to simulate, default=100")
+    parser.add_argument("--stockfish", default=stockfish_default,
+                        help=f"Path for stockfish executable, default='{stockfish_default}'")
+    parser.add_argument("--engine1", "--e1", help="Engine A for the simulation", choices=engines.keys(), required=True)
+    parser.add_argument("--engine2", "--e2", help="Engine B for the simulation", choices=engines.keys(), required=True)
+    parser.add_argument("--strategy1", "--s1", default=list(strategies.keys())[0],
+                        help="Strategy for engine A for the rollout",
+                        choices=strategies.keys())
+    parser.add_argument("--strategy2", "--s2", default=list(strategies.keys())[0],
+                        help="Strategy for engine B for the rollout",
+                        choices=strategies)
+    args = parser.parse_args()
+
+    engine1 = engines[args.engine1]
+    engine2 = engines[args.engine2]
+    strategy1 = strategies[args.strategy1]
+    strategy2 = strategies[args.strategy2]
+
+    return engine1, engine2, strategy1, strategy2, int(args.n), float(args.time), args.stockfish, int(args.proc)
+
+
 def main():
     test_evaluation()
     # test_simulate()