def record(node):
if not node["is_root"]:
annotations.annotate_sgf(
C,
annotations.format_winrate(node["stats"], node["move_list"],
board_size, None), [], [])
move_list_to_display = []
# Only display info for the principal variation or for lines that have been explored.
for i in range(len(node["children"])):
child = node["children"][i]
if child is not None and (i == 0 or child["explored"]):
move_list_to_display.append(node["move_list"][i])
(analysis_comment, lb_values,
tr_values) = annotations.format_analysis(node["stats"],
move_list_to_display,
None)
annotations.annotate_sgf(C, analysis_comment, lb_values, tr_values)
for i in range(len(node["children"])):
child = node["children"][i]
if child is not None:
if child["explored"]:
advance(C, node["color"], child["history"][-1])
record(child)
C.previous()
# Only show variations for the principal line, to prevent info overload
elif i == 0:
pv = node["move_list"][i]["pv"]
c = node["color"]
num_to_show = min(len(pv), max(1, len(pv) * 2 / 3 - 1))
for k in range(num_to_show):
advance(C, c, pv[k])
c = 'black' if c == 'white' else 'white'
for k in range(num_to_show):
C.previous()
next_game_move = None
if not cursor.atEnd:
cursor.next()
if 'W' in cursor.node.keys():
next_game_move = cursor.node['W'].data[0]
if 'B' in cursor.node.keys():
next_game_move = cursor.node['B'].data[0]
cursor.previous()
annotations.annotate_sgf(
cursor,
annotations.format_winrate(stats, move_list, board_size,
next_game_move), [], [])
if has_prev and ((move_num - 1) in comment_requests_analyze or
(move_num - 1) in comment_requests_variations
or transdelta <= -analyze_threshold):
if not (args.skip_white and prev_player
== "white") and not (args.skip_black
and prev_player == "black"):
(analysis_comment, lb_values,
tr_values) = annotations.format_analysis(
prev_stats, prev_move_list, this_move)
cursor.previous()
# adding comment to sgf with suggested alternative variations
annotations.annotate_sgf(cursor, analysis_comment,
lb_values, tr_values)
cursor.next()
annotations.annotate_sgf(C, delta_comment,
delta_lb_values, [])
if has_prev and (transdelta <= -variations_threshold or
(move_num - 1)
in comment_requests_variations):
if not (args.skip_white and prev_player
== "white") and not (args.skip_black
and prev_player == "black"):
needs_variations[move_num - 1] = (prev_stats,
prev_move_list)
if (move_num - 1) not in comment_requests_variations:
variations_tasks += 1
annotations.annotate_sgf(
C, annotations.format_winrate(stats, move_list,
board_size), [], [])
if has_prev and ((move_num - 1) in comment_requests_analyze or
(move_num - 1) in comment_requests_variations
or transdelta <= -analyze_threshold):
if not (args.skip_white and prev_player
== "white") and not (args.skip_black
and prev_player == "black"):
(analysis_comment, lb_values,
tr_values) = annotations.format_analysis(
prev_stats, prev_move_list, this_move)
C.previous()
annotations.annotate_sgf(C, analysis_comment,
lb_values, tr_values)
C.next()
if 'B' in C.node.keys():
next_game_move = C.node['B'].data[0]
C.previous()
# add triangle marker for next move and "A" label for bot move
LB_values = []
TR_values = []
if args.mark_next and next_game_move != None and not annotations.pos_is_pass(next_game_move):
TR_values.append(next_game_move)
if len(move_list) > 0:
leela_move = move_list[0]['pos']
if args.mark_leela and leela_move != next_game_move and not annotations.pos_is_pass(leela_move):
LB_values.append("%s:%s" % (leela_move, "A"))
annotations.annotate_sgf(C, annotations.format_winrate(stats,move_list,board_size,next_game_move), LB_values, TR_values)
# add analysis when a bad move was made
if has_prev and ((move_num-1) in comment_requests_analyze or (move_num-1) in comment_requests_variations or transdelta <= -analyze_threshold):
if not (args.skip_white and prev_player == "white") and not (args.skip_black and prev_player == "black"):
(analysis_comment, lb_values, tr_values) = annotations.format_analysis(prev_stats, prev_move_list, this_move)
C.previous()
annotations.annotate_sgf(C, analysis_comment, lb_values, tr_values)
C.next()
prev_stats = stats
prev_move_list = move_list
has_prev = True
analyze_tasks_initial_done += 1
refresh_pb()
def analyze_sgf(args, sgf_to_analyze):
time_start = datetime.datetime.now()
analyzer_logger.info(f"Game analysis started to file: {sgf_to_analyze}")
analyzer_logger.info(
f"Time settings: main line {args.analyze_time:d} seconds/move, "
f"variations {args.variations_time:d} seconds/move")
sgf = parse_sgf(sgf_to_analyze)
base_dir = prepare_checkpoint_dir(sgf)
analyzer_logger.debug(f"Using checkpoint dir: {base_dir}")
# Set up SGF cursor and get values from first node
cursor = sgf.cursor()
game_settings = get_initial_values(cursor)
board_size = game_settings['board_size']
handicap_stones = game_settings['handicap_stones']
komi = game_settings['komi']
if board_size != 19:
analyzer_logger.warning(
"Board size is not 19 so Leela could be much weaker and less accurate."
)
# First loop for comments parsing
moves_to_analyze, moves_to_variations = collect_requested_moves(
cursor, args)
analyze_tasks = len(moves_to_analyze)
variations_tasks = len(moves_to_variations)
analyze_tasks_done = 0
variations_tasks_done = 0
leela = Leela(board_size=board_size,
path_to_exec=args.path_to_leela,
handicap_stones=handicap_stones,
komi=komi,
seconds_per_search=args.analyze_time)
collected_stats = {}
collected_move_lists = {}
best_moves = {}
try:
progress_bar = ProgressBar(max_value=analyze_tasks)
leela.start()
progress_bar.start()
cursor = sgf.cursor()
add_moves_to_leela(cursor, leela)
move_num = -1
prev_stats = {}
prev_move_list = []
has_prev = False
previous_player = None
analyzer_logger.info(f"Executing analysis for {analyze_tasks} moves")
# analyze main line, without variations
while not cursor.atEnd:
cursor.next()
move_num += 1
this_move = add_moves_to_leela(cursor, leela)
current_player = 'black' if 'W' in cursor.node else 'white'
if previous_player == current_player:
raise PlayedTwiceError
if move_num in moves_to_analyze:
stats, move_list, skipped = do_analyze(leela, base_dir,
args.analyze_time)
# Here we store ALL statistics
collected_stats[move_num] = stats
collected_move_lists[move_num] = move_list
if move_list and 'winrate' in move_list[0]:
best_moves[move_num] = move_list[0]
delta = 0.0
if 'winrate' in stats and (move_num - 1) in best_moves:
if this_move != best_moves[move_num - 1]['pos']:
delta = stats['winrate'] - best_moves[move_num -
1]['winrate']
delta = min(0.0, (-delta if leela.whose_turn()
== "black" else delta))
if -delta > args.analyze_threshold:
(delta_comment,
delta_lb_values) = annotations.format_delta_info(
delta, this_move, board_size)
annotations.annotate_sgf(cursor, delta_comment,
delta_lb_values, [])
if has_prev and delta <= -args.variations_threshold and not is_skipped(
args, previous_player):
if (move_num - 1) not in moves_to_variations:
variations_tasks += 1
moves_to_variations[move_num - 1] = True
if args.show_winrate and -delta > args.analyze_threshold:
progress_bar.set_message(
f'winrate {(stats["winrate"]*100):.2f}% | '
f'{current_player} '
f'{convert_position(board_size, this_move):<3} | '
f'delta {(delta*100):.2f}%')
next_game_move = next_move_pos(cursor)
annotations.annotate_sgf(
cursor,
annotations.format_winrate(stats, move_list, board_size,
next_game_move), [], [])
if has_prev and ((move_num - 1) in moves_to_analyze
and -delta > args.analyze_threshold or
(move_num - 1) in moves_to_variations):
if not (args.skip_white and previous_player
== "white") and not (args.skip_black and
previous_player == "black"):
def filter_move_list(move_list):
visit_sums = sum(
[move['visits'] for move in move_list])
return [
move for move in move_list if move['visits'] /
visit_sums > config.move_list_threshold
]
(analysis_comment, lb_values,
tr_values) = annotations.format_analysis(
prev_stats, filter_move_list(prev_move_list),
this_move, board_size)
cursor.previous()
# adding comment to sgf with suggested alternative variations
annotations.annotate_sgf(cursor, analysis_comment,
lb_values, tr_values)
cursor.next()
prev_stats = stats
prev_move_list = move_list
has_prev = True
analyze_tasks_done += 1
# save to file results with analyzing main line
save_to_file(sgf_to_analyze, sgf)
if not skipped:
if args.win_graph and len(collected_stats) > 1:
graph_winrates(collected_stats, sgf_to_analyze)
progress_bar.update(analyze_tasks_done, analyze_tasks)
progress_bar.set_message(None)
else:
prev_stats = {}
prev_move_list = []
has_prev = False
previous_player = current_player
progress_bar.finish()
leela.stop()
leela.clear_history()
if args.win_graph:
graph_winrates(collected_stats, sgf_to_analyze)
# Now fill in variations for everything we need (suggested variations)
progress_bar = ProgressBar(max_value=variations_tasks)
progress_bar.start()
leela = Leela(board_size=board_size,
path_to_exec=args.path_to_leela,
handicap_stones=handicap_stones,
komi=komi,
seconds_per_search=args.variations_time)
move_num = -1
cursor = sgf.cursor()
leela.start()
add_moves_to_leela(cursor, leela)
analyzer_logger.info(
f"Exploring variations for {variations_tasks:d} moves with {args.variations_depth:d} steps"
)
while not cursor.atEnd:
cursor.next()
move_num += 1
add_moves_to_leela(cursor, leela)
if move_num not in moves_to_variations:
continue
stats, move_list = collected_stats[move_num], collected_move_lists[
move_num]
if 'bookmoves' in stats or len(move_list) <= 0:
continue
next_game_move = next_move_pos(cursor)
do_variations(cursor, leela, stats, move_list, board_size,
next_game_move, base_dir, args)
variations_tasks_done += 1
save_to_file(sgf_to_analyze, sgf)
progress_bar.update(variations_tasks_done, variations_tasks)
progress_bar.finish()
except:
analyzer_logger.critical(f"{traceback.format_exc()}")
traceback.print_exc()
finally:
leela.stop()
time_stop = datetime.datetime.now()
analyzer_logger.info(
f"Leela analysis stopped at {time_stop.strftime('%H:%M:%S')}")
# delay in case of sequential running of several analysis
time.sleep(1)