Files
katrain-qt/game_node.py
T
2020-04-15 23:21:40 +02:00

98 lines
3.6 KiB
Python

import copy
import random
from typing import Dict, List, Optional
from sgf_parser import SGFNode
class GameNode(SGFNode):
"""Represents a single game node, with one or more moves and placements."""
def __init__(self, parent=None, properties=None, move=None):
super().__init__(parent=parent, properties=properties, move=move)
self.analysis = None
self.ownership = None
self.auto_undid = False
self.move_number = 0
self.undo_threshold = random.random() # for fractional undos, store the random threshold in the move itself for consistency
@property
def sgf_properties(self):
best_sq = []
properties = copy.copy(super().sgf_properties)
if best_sq and "SQ" not in properties:
properties["SQ"] = best_sq
comment = self.comment(sgf=True)
if comment:
properties["C"] = properties.get("C", "") + comment
return properties
# various analysis functions
def analyze(self, engine):
engine.request_analysis(self, lambda result: self.set_analysis(result))
def set_analysis(self, analysis_blob):
self.analysis = analysis_blob["moveInfos"] # TODO: fix when rootInfos comes in
self.ownership = analysis_blob["ownership"]
@property
def analysis_ready(self):
return self.analysis is not None
def format_score(self, score=None):
score = score or self.score
return f"{'B' if score >= 0 else 'W'}+{abs(score):.1f}"
def format_win_rate(self, win_rate=None):
win_rate = win_rate or self.analysis[0]['winrate']
b_adv = win_rate-0.5
return f"{'B' if b_adv > 0 else 'W'}+{abs(b_adv):.1%}"
def comment(self, sgf=False, eval=False, hints=False):
single_move = self.single_move
if not self.parent or not single_move: # root
return ""
text = f"Move {self.depth}: {single_move.player} {single_move.gtp()}\n"
if self.analysis_ready:
score = self.score
if sgf:
text += f"Score: {self.format_score(score)}\n"
if self.parent and self.parent.analysis_ready:
if sgf or hints:
text += f"Top move was {self.parent.analysis[0]['move']} ({self.format_score(self.parent.analysis[0]['scoreLead'])})\n"
elif self.parent.analysis[0]["move"] != single_move.gtp():
points_lost = self.points_lost
if points_lost > 0.5:
text += f"Estimated point loss: {points_lost:.1f}\n"
else:
text = "No analysis available" if sgf else "Analyzing move..."
return text
@property
def points_lost(self) -> Optional[float]:
single_move = self.single_move
if single_move and self.parent and self.analysis_ready and self.parent.analysis_ready:
parent_score = self.parent.score
score = self.score
return self.player_sign(single_move.player) * (parent_score - score)
@property
def score(self):
return self.analysis[0]["scoreLead"] # TODO: update for rootInfo
@staticmethod
def player_sign(player):
return {"B": 1, "W": -1, None: 0}[player]
@property
def ai_moves(self) -> List[Dict]:
if not self.analysis_ready:
return []
analysis = copy.copy(self.analysis) # not deep, so eval is saved, but avoids race conditions
for d in analysis:
d["pointsLost"] = self.player_sign(self.next_player) * (analysis[0]["scoreLead"] - d["scoreLead"]) # TODO: update for rootInfo
return analysis