def score_planet(pw: planet_wars.PlanetWars, p: planet_wars.Planet):
"""
Function to give a planet a score based on many factors.
:param pw: `PlanetWars` object
:param p: `Planet` object
:return: `float` score of planet
"""
raw_score = get_raw_score(p)
structural_score = 1 - (pythag(MY_PLANETS_CENTER,
(p.x(), p.y())) / pw.map_size)
surrounding_score = 0
for planet in filter(lambda _p: _p != p, pw.planets()):
temp = (
1 -
(pw.distance(p.planet_id(), planet.planet_id()) / pw.map_size))**5
surrounding_score += get_raw_score(planet) * temp
surrounding_score /= pw.total_growth
latency_score = p.latency / pw.map_size
center_score = 1 - (pw.distance(p.planet_id(), 0) / pw.map_size)
score = 0
score += raw_score
score += STRUCTURAL_FACTOR * structural_score
score += SURROUNDING_FACTOR * surrounding_score
score += LATENCY_FACTOR * latency_score
score += CENTER_FACTOR * center_score
return score
def furthest_meaningful_planet(pw: planet_wars.PlanetWars,
planet: planet_wars.Planet, owner: int):
planets = tuple(filter(lambda p: p.owner() == owner, pw.planets()))
fleets = tuple(filter(lambda f: f.owner() == owner, pw.fleets()))
furthest_distance = 0
for other_planet in planets:
furthest_distance = max(
furthest_distance,
pw.distance(other_planet.planet_id(), planet.planet_id()))
for fleet in fleets:
furthest_distance = max(
furthest_distance,
fleet.turns_remaining() +
pw.distance(fleet.destination_planet(), planet.planet_id()))
return furthest_distance
def expand(pw: planet_wars.PlanetWars,
expand_limit: int = 99,
possible_planets=None,
reckless: bool = False):
"""
Expand to neutral planets with all ships. Designed to come after `defend_possible()` because this doesn't account
for possible attacks from the opponent.
:param pw: `PlanetWars` object
:param expand_limit: `int` the maximum number of planets to expand to.
:param possible_planets: `list` of `Planet` objects, the planets to consider expanding to. None -> all
:param reckless: `bool` whether to care about the defensibility of the planet
:return: None
"""
expand_limit = min(expand_limit, len(pw.neutral_planets()))
if possible_planets is None:
possible_planets = filter(lambda p: p not in pw.my_future_neutrals,
pw.neutral_planets())
possible_planets = filter(lambda p: p not in pw.enemy_future_neutrals,
possible_planets)
sorted_planets = sorted(
possible_planets,
key=lambda p:
(score_planet(pw, p) - get_raw_score(p) + return_ships(pw, p) /
(pw.map_size / 2)) / (p.num_ships() + 1),
reverse=True)
for _ in range(expand_limit):
for attack_planet in sorted_planets[:expand_limit]:
if not (attack_planet.latency > 0 and attack_planet.num_ships() < attack_planet.growth_rate()) and \
not reckless and not defensible(pw, attack_planet):
continue
# if not reckless and not defensible(pw, attack_planet):
# continue
quickest_planet = min(
pw.my_planets(),
key=lambda p: turn_to_take(pw, p, attack_planet))
closest_distance = pw.map_size
for enemy_planet in pw.enemy_planets():
closest_distance = min(
closest_distance,
pw.distance(enemy_planet.planet_id(),
attack_planet.planet_id()))
for enemy_planet in pw.enemy_future_neutrals:
closest_distance = min(
closest_distance,
pw.distance(enemy_planet.planet_id(),
attack_planet.planet_id()) +
pw.enemy_future_neutrals[enemy_planet][0])
if turn_to_take(pw, quickest_planet,
attack_planet) > closest_distance:
continue
if quickest_planet.num_ships() > attack_planet.num_ships():
pw.issue_order(quickest_planet.planet_id(),
attack_planet.planet_id(),
attack_planet.num_ships() + 1)
quickest_planet.remove_ships(attack_planet.num_ships() + 1)
pw.my_future_neutrals[attack_planet] = (pw.distance(
quickest_planet.planet_id(), attack_planet.planet_id()), 1)
for planet in pw.planets():
planet.my_maximum_ships[pw.distance(quickest_planet.planet_id(), planet.planet_id()) - 1] -= \
attack_planet.num_ships()
planet.my_maximum_ships[
pw.distance(quickest_planet.planet_id(),
attack_planet.planet_id()) +
pw.distance(attack_planet.planet_id(),
planet.planet_id())] += 1
for t in range(
pw.distance(quickest_planet.planet_id(),
attack_planet.planet_id()) +
pw.distance(attack_planet.planet_id(),
planet.planet_id()), 2 * pw.map_size):
planet.my_maximum_ships[
t] += attack_planet.growth_rate()
expand_limit -= 1
sorted_planets.remove(attack_planet)
break
else:
quickest_planet.num_ships(0)
return
else:
break
