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check building diversity and take account for build delay in score

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This commit is contained in:
Thefeli73 2020-10-07 19:16:42 +02:00
parent fd424496bb
commit 5637da5a34
1 changed files with 34 additions and 9 deletions
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43
main.py
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@ -262,30 +262,31 @@ def calculate_best_upgrade(current_building):
def calculate_best_utility(): def calculate_best_utility():
global state, money_reserve_multiplier global state, money_reserve_multiplier
rounds_left = 700 - state.turn
best_utility = [] best_utility = []
for utility_blueprint in state.available_utility_buildings: for utility_blueprint in state.available_utility_buildings:
if state.turn >= utility_blueprint.release_tick and (money_reserve_multiplier*utility_blueprint.cost < state.funds): if state.turn >= utility_blueprint.release_tick and (money_reserve_multiplier*utility_blueprint.cost < state.funds):
rounds_left = 700 - state.turn - (100 / utility_blueprint.build_speed)
for i in range(len(available_tiles)): for i in range(len(available_tiles)):
if isinstance(available_tiles[i], tuple): if isinstance(available_tiles[i], tuple):
score = 0 score = 0
cost = utility_blueprint.cost cost = utility_blueprint.cost
for effect_name in utility_blueprint.effects: for effect_name in utility_blueprint.effects:
effect = game_layer.get_effect(effect_name) effect = game_layer.get_effect(effect_name)
affected_people = tile_score(available_tiles[i], effect.radius)[0] affected_people = tile_score(available_tiles[i], effect.radius, effect_name)[0]
affected_buildings = tile_score(available_tiles[i], effect.radius)[1] affected_buildings = tile_score(available_tiles[i], effect.radius, effect_name)[1]
cost -= effect.building_income_increase * rounds_left cost -= effect.building_income_increase * rounds_left
happiness_increase = affected_people * effect.max_happiness_increase * rounds_left happiness_increase = affected_people * effect.max_happiness_increase * rounds_left
co2 = affected_people * effect.co2_per_pop_increase * rounds_left - effect.mwh_production * affected_buildings co2 = affected_people * effect.co2_per_pop_increase * rounds_left - effect.mwh_production * affected_buildings * rounds_left
score = happiness_increase / 10 - co2 score += happiness_increase / 10 - co2
# print(effect_name + " gave score " + str(score))
# score = score / cost # score = score / cost
best_utility.append((score, utility_blueprint.building_name, i)) best_utility.append((score, utility_blueprint.building_name, i))
def sort_key(e): def sort_key(e):
return e[0] return e[0]
best_utility.sort(reverse=True, key=sort_key) best_utility.sort(reverse=True, key=sort_key)
# print(best_utility)
if not best_utility: if not best_utility:
return False return False
return best_utility[0] return best_utility[0]
@ -294,18 +295,30 @@ def calculate_best_utility():
def calculate_best_residence(): def calculate_best_residence():
global state, money_reserve_multiplier global state, money_reserve_multiplier
rounds_left = 700 - state.turn
best_residence = [] best_residence = []
for residence_blueprint in state.available_residence_buildings: for residence_blueprint in state.available_residence_buildings:
if state.turn >= residence_blueprint.release_tick and (money_reserve_multiplier*residence_blueprint.cost < state.funds): if state.turn >= residence_blueprint.release_tick and (money_reserve_multiplier*residence_blueprint.cost < state.funds):
rounds_left = 700 - state.turn - (100 / residence_blueprint.build_speed)
average_outdoor_temp = (state.max_temp - state.min_temp)/2 average_outdoor_temp = (state.max_temp - state.min_temp)/2
average_heating_energy = ((0 - 0.04 * residence_blueprint.max_pop + (21 - average_outdoor_temp) * residence_blueprint.emissivity) / 0.75) average_heating_energy = ((0 - 0.04 * residence_blueprint.max_pop + (21 - average_outdoor_temp) * residence_blueprint.emissivity) / 0.75)
lifetime_energy = (residence_blueprint.base_energy_need + average_heating_energy) * rounds_left lifetime_energy = (residence_blueprint.base_energy_need + average_heating_energy) * rounds_left
distinct_residences = number_of_distinct_residences(residence_blueprint.building_name)
diversity = 1 + distinct_residences[0]/10
co2 = 0.03 * residence_blueprint.max_pop * rounds_left + residence_blueprint.co2_cost + (0.1 * lifetime_energy / 1000) co2 = 0.03 * residence_blueprint.max_pop * rounds_left + residence_blueprint.co2_cost + (0.1 * lifetime_energy / 1000)
max_happiness = residence_blueprint.max_happiness * residence_blueprint.max_pop * rounds_left max_happiness = residence_blueprint.max_happiness * residence_blueprint.max_pop * rounds_left
max_happiness *= diversity
score = residence_blueprint.max_pop*15 + max_happiness/10 - co2 diversity_bonus = 0
if distinct_residences[1]:
happy = 0
for residence in state.residences:
happy += residence.happiness_per_tick_per_pop * residence.current_pop
diversity_bonus = (happy * rounds_left / 10) / 10
score = residence_blueprint.max_pop*15 + max_happiness / 10 - co2 + diversity_bonus
# score = score / residence_blueprint.cost # score = score / residence_blueprint.cost
best_residence.append((score, residence_blueprint.building_name)) best_residence.append((score, residence_blueprint.building_name))
@ -317,6 +330,18 @@ def calculate_best_residence():
return best_residence[0] return best_residence[0]
def number_of_distinct_residences(new_building):
global state
unique_names = []
for residence in state.residences:
if not residence.building_name in unique_names:
unique_names.append(residence.building_name)
if not new_building in unique_names:
unique_names.append(new_building)
return len(unique_names), True
return len(unique_names), False
def chart_map(): def chart_map():
global state global state
for x in range(len(state.map) - 1): for x in range(len(state.map) - 1):