def placeFigures(self, board: GameBoard, state: GameState) -> None:
"""
Random choose the initial position of the figures.
:param board: board of the game
:param state: the current state
"""
# select area
x, y = np.where(state.placement_zone[self.team] > 0)
figures = state.getFigures(self.team)
# choose random positions
indices = np.random.choice(len(x), size=len(figures), replace=False)
for i in range(len(figures)):
# move each unit to its position
figure = figures[i]
dst = Hex(x[indices[i]], y[indices[i]]).cube()
state.moveFigure(figure, figure.position, dst)
def placeFigures(self, board: GameBoard, state: GameState) -> None:
"""
Find the initial position for the figure where the state has the best value. The generation of the position is
done randomly 100 times.
:param board: board of the game
:param state: the current state
"""
# select area
x, y = np.where(state.placement_zone[self.team] > 0)
figures = state.getFigures(self.team)
# choose groups of random positions
indices = [
np.random.choice(len(x), size=len(figures), replace=False)
for _ in range(100)
]
scores = []
s = deepcopy(state)
for i in range(len(indices)):
# select a group of positions
group = indices[i]
for j in range(len(group)):
# move each unit to its position
figure = figures[j]
dst = Hex(x[group[j]], y[group[j]]).cube()
s.moveFigure(figure, figure.position, dst)
score = stateScore(self.team, self.goal_params, board, s)
scores.append((score, group))
# choose the better group
score, group = self.opt(scores)
for j in range(len(group)):
figure = figures[j]
dst = Hex(x[group[j]], y[group[j]]).cube()
state.moveFigure(figure, dst=dst)
logger.info(f'{self.team:5}: placed his troops in {group} ({score})')
def placeFigures(self, board: GameBoard, state: GameState) -> None:
for figure in state.getFigures(self.team):
if figure.index in self.place:
dst = self.place[figure.index]
state.moveFigure(figure, figure.position, dst)