def test_foxwq():
for sgf in ["data/fox sgf error.sgf", "data/fox sgf works.sgf"]:
file = os.path.join(os.path.dirname(__file__), sgf)
move_tree = KaTrainSGF.parse_file(file)
katrain = KaTrainBase(force_package_config=True, debug_level=0)
game = Game(katrain, MagicMock(), move_tree)
assert [] == move_tree.placements
assert [] == game.root.placements
while game.current_node.children:
assert 1 == len(game.current_node.children)
game.redo(1)
def test_ai_strategies(self):
katrain = KaTrainBase(force_package_config=True, debug_level=0)
engine = KataGoEngine(katrain, katrain.config("engine"))
game = Game(katrain, engine)
n_rounds = 3
for _ in range(n_rounds):
for strategy in AI_STRATEGIES:
settings = katrain.config(f"ai/{strategy}")
move, played_node = generate_ai_move(game, strategy, settings)
katrain.log(f"Testing strategy {strategy} -> {move}", OUTPUT_INFO)
assert move.coords is not None
assert played_node == game.current_node
assert game.current_node.depth == len(AI_STRATEGIES) * n_rounds
for strategy in AI_STRATEGIES:
game = Game(katrain, engine)
settings = katrain.config(f"ai/{strategy}")
move, played_node = generate_ai_move(game, strategy, settings)
katrain.log(f"Testing strategy on first move {strategy} -> {move}", OUTPUT_INFO)
assert game.current_node.depth == 1
from katrain.core.base_katrain import KaTrainBase
from katrain.core.game import Game, KaTrainSGF
from katrain.core.engine import KataGoEngine
from rank_utils import rank_game
def format_rank(rank):
if rank <= 0:
return f"{1-rank:5.1f}d"
else:
return f"{rank:5.1f}k"
if __name__ == "__main__":
kt = KaTrainBase(force_package_config=True)
e_config = kt.config("engine")
e_config["max_visits"] = e_config[
"fast_visits"] = 1 # since it's just policy anyway
engine = KataGoEngine(kt, e_config)
for filename in glob.glob("sgf_ogs/*.sgf"):
game = Game(kt, engine, move_tree=KaTrainSGF.parse_file(filename))
size = game.board_size
len_segment = 80
ranks = rank_game(game, len_segment)
if not ranks:
continue
print("* File name: {0:s}".format(filename))
for start, end, rank in ranks:
assert rank[-1] == "k", f"unexpected rank {rank}"
return 1 - int(rank[:-1])
def polyfit(x, y, degree=1):
coeffs = np.polyfit(x, y, degree)
correlation = np.corrcoef(x, y)[0, 1]
results = {
"coef": coeffs.tolist(),
"r": correlation,
"rsq": correlation**2
}
return results
katrain = KaTrainBase(force_package_config=True, debug_level=0)
combined_settings = {**katrain.config("engine"), **settings}
engine = KataGoEngine(katrain, {**katrain.config("engine"), **settings})
thresholds = katrain.config("trainer/eval_thresholds")
games = []
n = 0
for sgf in os.listdir("sgftest/"):
if sgf.lower().endswith("sgf"):
print(sgf)
with open(os.path.join("sgftest", sgf)) as f:
move_tree = KaTrainSGF.parse_sgf(f.read())
games.append(
Game(katrain, engine, move_tree=move_tree, analyze_fast=False))
n += 1
if n >= 30000: # small test=3
def test_ai_rank_estimation(self):
katrain = KaTrainBase(force_package_config=True, debug_level=0)
for strategy in AI_STRATEGIES:
settings = katrain.config(f"ai/{strategy}")
rank = ai_rank_estimation(strategy, settings)
assert -20 <= rank <= 9