def _get_lock_water_fire_lock_graph():
start = Start()
key_red = Key("red")
lock_red = Lock("red")
flippers = Key("flippers")
water1 = Lock("water1")
water2 = Lock("water2")
key_green = Key("green")
lock_green = Lock("green")
fire_boots = Key("fireboots")
fire1 = Lock("fire1")
fire2 = Lock("fire2")
end = End()
start.add_child_s([fire2, key_red, lock_red])
key_red.add_lock_s(lock_red)
lock_red.add_child_s([flippers, water1])
flippers.add_lock_s([water1, water2])
water1.add_child_s(water2)
water2.add_child_s([fire_boots, fire1])
fire_boots.add_lock_s([fire1, fire2])
fire1.add_child_s(key_green)
key_green.add_lock_s(lock_green)
fire2.add_child_s(lock_green)
lock_green.add_child_s(end)
return Node.find_all_nodes(start, method="topological-sort")
def get_node_layout(start_node):
def only_visit_children_of_non_keys(node, child, visited_nodes):
return not isinstance(node, Key)
def sort_keys_last(node):
if isinstance(node, Collectable):
return 2
elif isinstance(node, Key):
return 1
else:
return 0
nodes = Node.find_all_nodes(
node=start_node,
method="depth-first",
will_traverse_method=only_visit_children_of_non_keys,
child_sort_method=sort_keys_last)
node_positions = dict()
rows = defaultdict(lambda: -1)
for node in nodes:
node_depth = GraphVisualizer.get_node_depth(node)
if not isinstance(node, Key):
row_width = GraphVisualizer.get_max_width_below_row(
rows, node_depth)
else:
row_width = rows[node_depth]
node_width = np.maximum(row_width + 1, rows[node_depth - 1])
rows[node_depth] = node_width
node_positions[node] = np.array([node_width, node_depth])
return node_positions
def get_random_descendant(self, node):
def is_valid_descendant(child):
return not isinstance(child, Key) and not isinstance(child, End)
possible_descendants = [
node for node in Node.find_all_nodes(node)
if is_valid_descendant(node)
]
descendant = np.random.choice(possible_descendants)
return descendant
def _get_simple_graph():
start = Start()
key = Key()
lock = Lock()
end = End()
start.add_child_s([key, lock])
key.add_lock_s(lock)
lock.add_child_s(end)
return Node.find_all_nodes(start, method="topological-sort")
def insert_rooms(self, aesthetic):
nodes = Node.find_all_nodes(self.start, method="topological-sort")
for node in nodes:
keys = [n for n in node.child_s if isinstance(n, Key)]
if len(keys) > 0 and np.random.random(
) < aesthetic.insert_room_probability:
room = Room(str(self.get_room_id()), parent_s=node)
for key in keys:
key.remove_parent_s(node)
key.add_parent_s(room)
def test_topological_sort_bug(self):
start = Start()
key = Key("key")
lock = Lock("lock")
end = End()
start.add_child_s(key)
key.add_lock_s(lock)
lock.add_child_s(end)
nodes = Node.find_all_nodes(start, method="topological-sort")
self.assertEqual(nodes, [start, key, lock, end])
def test_find_all_nodes(self):
a, all_nodes = TestGraphs.get_man_graph()
nodes = Node.find_all_nodes(a)
self.assertEqual(set(nodes), all_nodes)
a, all_nodes = TestGraphs.get_house_graph()
nodes = Node.find_all_nodes(a)
self.assertEqual(set(nodes), all_nodes)
a, all_nodes = TestGraphs.get_graph_b()
nodes = Node.find_all_nodes(a)
self.assertEqual(set(nodes), all_nodes)
a, all_nodes = TestGraphs.get_graph_a()
nodes = Node.find_all_nodes(a)
self.assertEqual(set(nodes), all_nodes)
a, all_nodes = TestGraphs.get_triangle_graph()
nodes = Node.find_all_nodes(a)
self.assertEqual(set(nodes), all_nodes)
def init_spatial_graph(mission_graph_start_node, random_initial_positions=True):
nodes = Node.find_all_nodes(mission_graph_start_node)
nodes = sorted(nodes, key=lambda x: x.name)
if random_initial_positions:
node_positions = np.random.random([len(nodes), 2]) * 10
else:
node_positions = np.transpose(np.stack([np.arange(len(nodes)), np.zeros(len(nodes))]))
adjacency_matrix = np.zeros([len(nodes), len(nodes)])
for i, node_start in enumerate(nodes):
for j, node_end in enumerate(nodes):
if node_end in node_start.child_s:
adjacency_matrix[(i, j)] = 1
adjacency_matrix[(j, i)] = 1
return nodes, node_positions, adjacency_matrix
def test_find_all_nodes_topological_sort(self):
top_sort = "topological-sort"
n0 = GNode("0")
n1 = GNode("1")
n2 = GNode("2")
n3 = GNode("3")
n4 = GNode("4")
n5 = GNode("5")
n5.add_child_s([n0, n2, n4])
n2.add_child_s(n3)
n3.add_child_s(n1)
n4.add_child_s([n0, n1])
nodes = Node.find_all_nodes(n5, method=top_sort)
self.assertTrue(
self.assert_ordered(nodes, [(n5, [n4, n3, n2, n1, n0]),
(n4, [n0, n1]), (n2, [n3, n1]),
(n3, [n1]), (n0, []), (n1, [])]))
n0 = GNode("0")
n1 = GNode("1")
n2 = GNode("2")
n3 = GNode("3")
n4 = GNode("4")
n5 = GNode("5")
n0.add_child_s([n1, n2, n3])
n1.add_child_s(n4)
n2.add_child_s(n5)
n3.add_child_s(n1)
n4.add_child_s(n2)
nodes = Node.find_all_nodes(n0, method=top_sort)
self.assertTrue(
self.assert_ordered(nodes, [(n0, [n1, n2, n3, n4, n5]),
(n1, [n4, n2, n5]), (n2, [n5]),
(n3, [n1, n4, n2, n5]), (n4, [n2, n5]),
(n5, [])]))
def _get_water_lock_graph():
start = Start()
key_red = Key("red")
lock_red = Lock("red")
flippers = Key("flippers")
water = Lock("water")
end = End()
start.add_child_s([flippers, water, lock_red])
flippers.add_lock_s(water)
water.add_child_s(key_red)
key_red.add_lock_s(lock_red)
lock_red.add_child_s(end)
return Node.find_all_nodes(start, method="topological-sort")
def test_works_with_branched_graphs(self):
# return
# S
# |-----------
# | | |
# L1 K2 L2
# | |
# E K1
start = Start()
key1 = Key("1")
key2 = Key("2")
lock1 = Lock("1")
lock2 = Lock("2")
end = End()
start.add_child_s([lock1, key2, lock2])
lock1.add_child_s(end)
lock2.add_child_s(key1)
key1.add_child_s(lock1)
key2.add_child_s(lock2)
key1.add_lock_s(lock1)
key2.add_lock_s(lock2)
np.random.seed(4)
level = Level()
w = Tiles.wall
e = Tiles.empty
layer = np.array([[w, w, w, w, w, w, w, w], [w, e, e, e, e, e, e, w],
[w, e, e, e, e, e, e, w], [w, w, w, w, w, w, w, w],
[w, e, e, w, e, e, e, w], [w, e, e, w, e, e, e, w],
[w, e, e, w, e, e, e, w], [w, w, w, w, w, w, w, w]],
dtype=object)
solution_node_order = Node.find_all_nodes(start,
method="topological-sort")
aesthetic_settings = AestheticSettings()
was_successful = Generator.generate(
level=level,
size=layer.shape,
aesthetic_settings=aesthetic_settings,
max_retry_count=10,
pregenerated_level_layer=layer,
pregenerated_solution_node_order=solution_node_order)
self.assertTrue(was_successful)
Log.print(level)
def generate_mission(level, mission_aesthetic):
node_to_tile = dict()
solution_node_order = Node.find_all_nodes(level.mission,
method="topological-sort")
spatial_graph = SpatialGraph(level.upper_layer)
mission_spatial_nodes, mission_to_mission_spatial = MissionGenerator.convert_mission_graph_to_spatial_subgraph_form(
solution_node_order)
mission_to_spaces_mapping = SubgraphFinder.get_subgraph_mapping(
spatial_graph.nodes, mission_spatial_nodes)
if mission_to_spaces_mapping is not None:
MissionGenerator.apply_mission_mapping_to_level(
level, solution_node_order, mission_to_mission_spatial,
mission_to_spaces_mapping, node_to_tile, mission_aesthetic)
level.required_collectable_count = np.count_nonzero(
level.upper_layer == Tiles.collectable)
return Solver.does_level_follow_mission(level)
return False, None
def add_multi_lock(self, lock_count=2):
def is_node_multilock_candidate(node):
is_candidate = (isinstance(node, Key) and len(node.lock_s) == 1
and len(next(iter(node.lock_s)).key_s) == 1)
return is_candidate
multilock_key_candidates = [
node for node in Node.find_all_nodes(self.start)
if is_node_multilock_candidate(node)
]
multilock_key = np.random.choice(multilock_key_candidates)
lock = next(iter(multilock_key.lock_s))
for _ in range(lock_count):
current_node = self.get_random_descendant(lock)
child = None
if len(current_node.child_s) > 0:
child = np.random.choice(list(current_node.child_s))
lock = self.add_lock(current_node, multilock_key, child)
def show_graph(start_node,
draw_straight_lines=True,
draw_key_connections=True):
sorted_nodes = Node.find_all_nodes(start_node,
method="topological-sort")
node_positions = GraphVisualizer.get_node_layout(start_node)
im = Image.new('RGB', GraphVisualizer.get_image_size(node_positions),
GraphVisualizer.background_color)
draw = ImageDraw.Draw(im)
# Draw Connections
for node in sorted_nodes:
parent_node = GraphVisualizer.get_not_key_parent(node)
if parent_node is not None:
GraphVisualizer.draw_connection(draw,
node_positions[parent_node],
node_positions[node],
straight=draw_straight_lines,
is_key_connection=False)
if isinstance(node, Key) and draw_key_connections:
for lock in node.lock_s:
GraphVisualizer.draw_connection(draw,
node_positions[node],
node_positions[lock],
straight=True,
is_key_connection=True)
# Draw Nodes
for node in sorted_nodes:
if isinstance(node, Key):
node_type = "key"
else:
node_type = "lock"
GraphVisualizer.draw_node(draw,
node_positions[node],
node.name,
n_type=node_type)
im.show()
def get_efficient_node_order(mission_start_node):
def sort_keys_last(node):
if isinstance(node, Collectable):
return 5
elif isinstance(node, SokobanKey):
return 3
elif isinstance(node, Key):
return 4
elif isinstance(node, SokobanLock):
return 2
elif isinstance(node, Lock):
return 1
else:
return 0
solution_node_order = Node.find_all_nodes(
mission_start_node,
method="topological-sort",
child_sort_method=sort_keys_last)
solution_node_order = [
n for n in solution_node_order if not isinstance(n, Room)
]
return solution_node_order
def fill_rooms_with_collectables(self, aesthetic):
def can_node_contain_collectable(node):
return isinstance(node, Start) or isinstance(
node, Lock) or isinstance(node, Room)
collectables = []
possible_collectable_room_nodes = [
node for node in Node.find_all_nodes(self.start)
if can_node_contain_collectable(node)
]
collectable_rooms = [
room for room in possible_collectable_room_nodes
if np.random.random() < aesthetic.collectable_in_room_probability
]
for collectable_room in collectable_rooms:
collectable = self.add_collectable(collectable_room)
collectables.append(collectable)
collectables.extend(self.fill_dead_ends())
end_parent = next(iter(self.end.parent_s))
self.end.remove_parent_s(end_parent)
collectable_barrier = CollectableBarrier("B", end_parent, self.end,
collectables)
def test_works_with_difficult_graph(self):
return
start = Start()
key_red = Key("red")
lock_red = Lock("red")
flippers = Key("flippers")
water1 = Lock("water1")
water2 = Lock("water2")
key_green = Key("green")
lock_green = Lock("green")
fire_boots = Key("fireboots")
fire1 = Lock("fire1")
fire2 = Lock("fire2")
end = End()
start.add_child_s([fire2, key_red, lock_red])
key_red.add_lock_s(lock_red)
lock_red.add_child_s([flippers, water1])
flippers.add_lock_s([water1, water2])
water1.add_child_s(water2)
water2.add_child_s([fire_boots, fire1])
fire_boots.add_lock_s([fire1, fire2])
fire1.add_child_s(key_green)
key_green.add_lock_s(lock_green)
fire2.add_child_s(lock_green)
lock_green.add_child_s(end)
np.random.seed(12)
level = Level()
w = Tiles.wall
e = Tiles.empty
layer = np.array(
[[w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w, e, e, w],
[w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w, w]],
dtype=object)
solution_node_order = Node.find_all_nodes(start,
method="topological-sort")
start_time = time.time()
aesthetic_settings = AestheticSettings()
aesthetic_settings.mission_aesthetic.single_lock_is_hazard_probability = 0
aesthetic_settings.mission_aesthetic.hazard_spread_probability[
Tiles.water] = 0
aesthetic_settings.mission_aesthetic.hazard_spread_probability[
Tiles.fire] = 0
was_successful = Generator.generate(
level=level,
size=layer.shape,
aesthetic_settings=aesthetic_settings,
max_retry_count=10,
pregenerated_level_layer=layer,
pregenerated_solution_node_order=solution_node_order)
end_time = time.time()
self.assertTrue(was_successful)
Log.print(level)
Log.print("Generated in {} seconds".format(end_time - start_time))