shummiev26-3-2.py 文件源码

def update_recover_maps(self):
        max_distance = self.width // 2
        self.recover_map = np.zeros((max_distance + 1, self.width, self.height))
        self.recover_map[0] = np.divide(self.strength_map, self.production_map_01) * (self.is_neutral_map - self.combat_zone_map)

        self.prod_over_str_map = np.zeros((max_distance + 1, self.width, self.height))
        #self.prod_over_str_map[0] = np.divide(self.production_map, self.strength_map_01) * (self.is_neutral_map - self.combat_zone_map)
        new_str_map = np.copy(self.strength_map)
        new_str_map[new_str_map == 0] = 2
        #self.prod_over_str_map[0] = np.divide(self.production_map, self.strength_map_01) * (self.is_neutral_map - self.combat_zone_map)
        self.prod_over_str_map[0] = np.divide(self.production_map, new_str_map) * (self.is_neutral_map - self.combat_zone_map)
        self.recover_map[0] = 1 / np.maximum(self.prod_over_str_map[0], 0.01)

        for distance in range(1, max_distance + 1):
            self.prod_over_str_map[distance] = spread_n(self.prod_over_str_map[distance - 1], 1)
            self.prod_over_str_map[distance][self.prod_over_str_map[distance-1] == 0] = 0
            self.prod_over_str_map[distance] = self.prod_over_str_map[distance] / 5
            self.recover_map[distance] = 1 / np.maximum(self.prod_over_str_map[distance], 0.01)

        self.prod_over_str_max_map = np.apply_along_axis(np.max, 0, self.prod_over_str_map)
        self.recover_max_map = 1 / np.maximum(self.prod_over_str_max_map, 0.01)
        self.prod_over_str_avg_map = np.apply_along_axis(np.mean, 0, self.prod_over_str_map)
        self.recover_avg_map = 1 / np.maximum(self.prod_over_str_avg_map, 0.01)
        self.prod_over_str_wtd_map = (self.prod_over_str_max_map + self.prod_over_str_avg_map) / 2
        self.recover_wtd_map = 1 / np.maximum(self.prod_over_str_wtd_map, 0.01)