def to_commands(self):
"""Translate the assignments of ships to commands."""
self.save_destinations(self.assignments)
commands = []
# Dropoff collisions.
if self.allow_dropoff_collisions():
self.resolve_dropoff_collisions(commands)
# Assignment of next move.
cost_matrix = self.create_cost_matrix()
ships = [assignment.ship for assignment in self.assignments]
row_ind, col_ind = LinearSum.assignment(cost_matrix,
ships,
cluster_mode=True)
for k, i in zip(row_ind, col_ind):
assignment = self.assignments[k]
target = to_cell(i)
commands.append(assignment.to_command(target))
# Create dropoff assignments.
for ship in self.dropoff_assignments:
commands.append(ship.make_dropoff())
return commands
def new_want_to_spawn():
"""New implementation of want_to_spawn()."""
turnremain = constants.MAX_TURNS - game.turn_number
m = game_map.height * game_map.width
halite = np.array([to_cell(i).halite_amount for i in range(m)])
haliteremain = halite.sum()
return (param['spawn_intercept'] +
param['spawn_turnremain'] * turnremain +
param['spawn_haliteremain'] * haliteremain) > 2000
def dropoff_ship(self):
"""Determine ship that creates the ghost dropoff."""
for ship in self.ships:
if ship.position == self.ghost.position:
if (self.me.halite_amount < self.dropoff_cost(ship)
or to_cell(to_index(ship)).has_structure):
return None
return ship
return None
def best_position(self, indices):
"""Determine the best position.
Note:
Returns None if a good position was not found. If that is the case,
the GhostDropoff should not be considered any further.
"""
if not indices:
return None
best_index = min(indices, key=self.cost)
if self.cost(best_index) == 0.0:
return None
return to_cell(best_index).position
def assignment(self, ships):
"""Assign destinations to ships using an assignment algorithm."""
cost_matrix = self.create_cost_matrix(ships)
row_ind, col_ind = LinearSum.assignment(cost_matrix, ships)
for i, j in zip(row_ind, col_ind):
ship = ships[i]
best_average_halite = -1.0 * cost_matrix[i, j]
if not self.valuable(ship, best_average_halite):
self.assign_kamikaze(ship)
elif (ship.halite_amount > 550
and self._return_average_halite(ship) > best_average_halite):
self.assign_return(ship)
else:
destination = to_cell(j).position
self.schedule.assign(ship, destination)
def cost(self, index):
"""Cost representing the quality of the index as a dropoff location."""
if to_cell(index).has_structure:
return 0.0
modifier = self._disputed_factor(index) * self._expansion_factor(index)
return -1.0 * modifier * self.map_data.halite_density[index]