Add hypothesis test

This commit is contained in:
2024-01-31 18:07:02 +01:00
parent 13403b74f3
commit 26784956a3
2 changed files with 58 additions and 11 deletions

View File

@@ -1,9 +1,13 @@
from typing import TypedDict
import chess
import chess.engine
from stockfish import Stockfish
import numpy as np
import random
from scipy.stats import binomtest
def pick_move(board: chess.Board) -> chess.Move | None:
"""
@@ -77,3 +81,38 @@ def simulate_stockfish_prob(board: chess.Board, move: chess.Move, games: int = 1
print(scores)
# TODO: return distribution here?
return np.array(scores).mean(), np.array(scores).std()
HypothesisTestResult = TypedDict('HypothesisTestResult', {"trials": int, "pvalue": float, "statistic": float})
def hypothesis_test(wins: int, draws: int, losses: int) -> HypothesisTestResult:
"""
Hypothesis test using Binomial distributions.
Null Hypothesis: Both engines have the same strength, aka they win on average half of the games.
Alternative Hypothesis: Both engines have different strength.
:returns: tuple of trials, pvalue, test-statistic
"""
# wins give 1 point, and draws give 1/2 points
score = wins + draws // 2
# number of games
trials = wins + draws + losses
# due to rounding down the variable score, if draws are even, we have to reduce trials by one.
if draws % 2 != 0:
trials -= 1
# we expect that if both engines have the same strength, that they "win" on 50% on average
expected_success_rate = 0.5
result = binomtest(score, trials, expected_success_rate, alternative='two-sided')
return {
"trials": trials,
"pvalue": result.pvalue,
"statistic": result.statistic
}

30
main.py
View File

@@ -1,18 +1,20 @@
import argparse
import os
import random
import time
import chess
import chess.engine
import chess.pgn
from chesspp.mcts.classic_mcts import ClassicMcts
from chesspp import engine
from chesspp import simulation, eval
from chesspp import util
from chesspp.mcts.baysian_mcts import BayesianMcts
from chesspp.mcts.classic_mcts import ClassicMcts
from chesspp.random_strategy import RandomStrategy
from chesspp.stockfish_strategy import StockFishStrategy
from chesspp import engine
from chesspp import util
from chesspp import simulation, eval
import argparse
import os
from chesspp.util import hypothesis_test
def test_simulate():
@@ -44,7 +46,7 @@ def test_bayes_mcts():
t1 = time.time_ns()
mcts.sample(1)
t2 = time.time_ns()
print ((t2 - t1)/1e6)
print((t2 - t1) / 1e6)
mcts.print()
for move, score in mcts.get_moves().items():
print("move (mcts):", move, " with score:", score)
@@ -106,10 +108,15 @@ def test_evaluation():
b_wins = len(list(filter(lambda x: x.winner == simulation.Winner.Engine_B, results)))
draws = len(list(filter(lambda x: x.winner == simulation.Winner.Draw, results)))
alpha = 0.001
test_result = hypothesis_test(a_wins, draws, b_wins)
reject_h0 = test_result['pvalue'] < alpha
print(f"{games_played} games played")
print(f"Engine {a.get_name()} won {a_wins} games ({a_wins/games_played:.2%})")
print(f"Engine {b.get_name()} won {b_wins} games ({b_wins/games_played:.2%})")
print(f"{draws} games ({draws/games_played:.2%}) resulted in a draw")
print(f"Engine {a.get_name()} won {a_wins} games ({a_wins / games_played:.2%})")
print(f"Engine {b.get_name()} won {b_wins} games ({b_wins / games_played:.2%})")
print(f"{draws} games ({draws / games_played:.2%}) resulted in a draw")
print(f"Hypothesis test: trials={test_result['trials']}, pvalue={test_result['pvalue']:2.10f}, statistic={test_result['statistic']:2.4f}, reject_h0={reject_h0}")
def read_arguments():
@@ -118,7 +125,8 @@ def read_arguments():
description='Compare two engines by playing multiple games against each other'
)
engines = {"ClassicMCTS": engine.ClassicMctsEngine, "BayesianMCTS": engine.BayesMctsEngine, "Random": engine.RandomEngine}
engines = {"ClassicMCTS": engine.ClassicMctsEngine, "BayesianMCTS": engine.BayesMctsEngine,
"Random": engine.RandomEngine}
strategies = {"Random": RandomStrategy, "Stockfish": StockFishStrategy}
if os.name == 'nt':