def test_csv_roundtrip(self):
aesthetic_settings = AestheticSettings()
paths = AestheticSettings.get_csv_data_paths()
for i, path in enumerate(paths):
aesthetic, setting = path
aesthetic_settings.__dict__[aesthetic].__dict__[setting] = i
aesthetic_settings.mission_aesthetic.hazard_spread_probability = {
Tiles.water: 1,
Tiles.fire: 2
}
aesthetic_settings.mission_graph_aesthetic.branch_probability = [
0, 1, 2, 3
]
csv_data = aesthetic_settings.to_csv_data()
expected_csv_data = [
"0", "1", "2", "3", "4", "5", "6", "[1, 2]", "8", "9", "10",
"[0, 1, 2, 3]", "12", "13", "14", "15", "16", "17", "18", "19"
]
self.assertEqual(expected_csv_data, csv_data)
aesthetic_settings2 = AestheticSettings()
aesthetic_settings2.from_csv_data(csv_data)
expected_values = [
0.0, 1.0, 2, 3, 4, 5.0, 6.0, {
Tiles.water: 1.0,
Tiles.fire: 2.0
}, 8, 9, 10.0, [0.0, 1.0, 2.0, 3.0], 12.0, 13.0, 14.0, 15, 16, 17,
18, 19.0
]
for path, expected_value in zip(paths, expected_values):
aesthetic, setting = path
value = aesthetic_settings2.__dict__[aesthetic].__dict__[setting]
self.assertEqual(value, expected_value)
def level_aesthetic(self, i):
data = self.file_data.splitlines()[i].split(
Ratings.CSV_SEPARATOR)[Ratings.
SETTINGS_INDEX:Ratings.SETTINGS_INDEX +
len(AestheticSettings.get_csv_data_paths())]
aesthetic = AestheticSettings()
aesthetic.from_csv_data(data)
return aesthetic
def test_get_csv_data_paths(self):
l = "level_space_aesthetic"
m = "mission_aesthetic"
g = "mission_graph_aesthetic"
t = "tweaker_aesthetic"
data_paths = AestheticSettings.get_csv_data_paths()
expected_data_paths = [(l, "noise_empty_percentage"),
(l, "noise_percentage"), (l, "rectangle_count"),
(l, "rectangle_max"), (l, "rectangle_min"),
(l, "x_mirror_probability"),
(l, "y_mirror_probability"),
(m, "hazard_spread_probability"),
(m, "max_seconds_per_move"),
(m, "min_seconds_per_move"),
(m, "single_lock_is_hazard_probability"),
(g, "branch_probability"),
(g, "collectable_in_room_probability"),
(g, "insert_room_probability"),
(g, "key_is_sokoban_probability"),
(g, "max_depth"),
(g, "max_locks_per_multi_lock"),
(g, "max_multi_lock_count"), (g, "min_depth"),
(t, "should_fill_unused_space")]
self.assertEqual(expected_data_paths, data_paths)
def add_level(self, id, seed):
settings = ["0"] * len(AestheticSettings.get_csv_data_paths())
line = [str(id), str(int(seed))] + settings + ["0", "0"]
self.file_data += Ratings.CSV_SEPARATOR.join(line) + "\n"