def priority(self, position):
score = 0
if self.last_conclusion is not None:
dist = mdist(position, self.last_conclusion)
score += max(5 - dist, 0)
for adj in self.adjacencies[position]:
if not self.is_unknown(adj):
score += 1
return score
def priority(self, position):
score = 0
if self.last_conclusion is not None:
if self.last_conclusion in self.adjacencies[position]:
score += self.conclusion_adjacent_value
elif self.last_conclusion in self.corner_adjacencies[position]:
score += self.conclusion_corner_adjacent_value
else:
dist = mdist(self.last_conclusion, position)
if dist in self.conclusion_distance_values:
score += self.conclusion_distance_values[dist]
for adj in self.adjacencies[position]:
if not self.is_unknown(adj):
score += self.known_adjacent_value
return score
def valid_white_reachable(self, position=None, color=None):
if color == BLACK:
return True
if color == WHITE:
candidates = [position]
else:
candidates = self.white_positions.difference(self.given_positions)
for pos_white in candidates:
for pos_given in self.given_positions:
number = self[pos_given]
if mdist(pos_given, pos_white) < number:
break # this candidate has a given close enough
else:
return False # no numbers close enough
return True
def priority(self, position):
score = 0
if self.last_conclusion is not None:
if self.last_conclusion in self.adjacencies[position]:
score += self.conclusion_adjacent_value
else:
dist = mdist(self.last_conclusion, position)
if dist in self.conclusion_distance_values.keys():
score += self.conclusion_distance_values[dist]
# known lines nearby
adjs = self.adjacencies[position]
known_score = self.known_adjacent_value * len(adjs)
for adj in adjs:
if self.is_unknown(adj):
known_score -= self.known_adjacent_value
score += known_score
# givens nearby
for gpos in self.adjacent_givens(position):
number = self.givens[gpos]
if number in self.given_adjacent_values.keys():
score += self.given_adjacent_values[number]
return score
