def test_blob_math_contain():
# These rectangles look like this:
# xxxxx
# x###x
# x###x
# x###x
# xxxxx
rect1 = Rectangle(origin=Point(0, 0), size=Size(5, 5))
rect2 = Rectangle(origin=Point(1, 1), size=Size(3, 3))
blob1 = Blob.from_rectangle(rect1)
blob2 = Blob.from_rectangle(rect2)
union_blob = blob1 + blob2
assert union_blob.area == blob1.area
assert union_blob.height == blob1.height
left_blob = blob1 - blob2
assert left_blob.area == 16
assert left_blob.height == 5
assert left_blob.spans == {
0: (Span(0, 4), ),
1: (Span(0, 0), Span(4, 4)),
2: (Span(0, 0), Span(4, 4)),
3: (Span(0, 0), Span(4, 4)),
4: (Span(0, 4), ),
}
right_blob = blob2 - blob1
assert right_blob.area == 0
assert right_blob.height == 0
assert right_blob.spans == {}
def test_blob_math_overlap():
# These rectangles look like this:
# xxx
# x##x
# x##x
# xxx
rect1 = Rectangle(origin=Point(0, 0), size=Size(3, 3))
rect2 = Rectangle(origin=Point(1, 1), size=Size(3, 3))
blob1 = Blob.from_rectangle(rect1)
blob2 = Blob.from_rectangle(rect2)
union_blob = blob1 + blob2
assert union_blob.area == 14
left_blob = blob1 - blob2
assert left_blob.area == 5
assert left_blob.height == 3
assert left_blob.spans == {
0: (Span(0, 2), ),
1: (Span(0, 0), ),
2: (Span(0, 0), ),
}
right_blob = blob2 - blob1
assert right_blob.area == 5
assert right_blob.height == 3
assert right_blob.spans == {
1: (Span(3, 3), ),
2: (Span(3, 3), ),
3: (Span(1, 3), ),
}
def test_blob_math_disjoint():
# These rectangles look like this:
# xxx
# xxx
# xxx xxx
# xxx
# xxx
rect1 = Rectangle(origin=Point(0, 0), size=Size(3, 3))
rect2 = Rectangle(origin=Point(6, 2), size=Size(3, 3))
blob1 = Blob.from_rectangle(rect1)
blob2 = Blob.from_rectangle(rect2)
union_blob = blob1 + blob2
assert union_blob.area == blob1.area + blob2.area
assert union_blob.area == rect1.area + rect2.area
assert union_blob.height == 5
left_blob = blob1 - blob2
from pprint import pprint
pprint(blob1.spans)
pprint(blob2.spans)
pprint(left_blob.spans)
assert left_blob.area == blob1.area
assert left_blob == blob1
right_blob = blob2 - blob1
from pprint import pprint
pprint(blob1.spans)
pprint(blob2.spans)
pprint(right_blob.spans)
assert right_blob.area == blob2.area
assert right_blob == blob2
def __init__(self, size):
self.rect = size.to_rect(Point.origin())
self.entity_positions = WeakKeyDictionary()
self.tiles = {
point: Tile(self, point)
for point in self.rect.iter_points()
}
def __init__(self, size):
self.rect = size.to_rect(Point.origin())
# TODO i think using types instead of entities /most of the time/ is
# more trouble than it's worth
self._arch_grid = {point: CaveWall for point in self.rect.iter_points()}
self._item_grid = {point: [] for point in self.rect.iter_points()}
self._creature_grid = {point: None for point in self.rect.iter_points()}
self.floor_spaces = set()
def __init__(self, size):
self.rect = size.to_rect(Point.origin())
self.entity_positions = WeakKeyDictionary()
self.portal_index = {}
self.tiles = {
point: Tile(self, point)
for point in self.rect.iter_points()
}
def __init__(self, size):
self.rect = size.to_rect(Point.origin())
# TODO i think using types instead of entities /most of the time/ is
# more trouble than it's worth
self._arch_grid = {
point: CaveWall for point in self.rect.iter_points()}
self._item_grid = {point: [] for point in self.rect.iter_points()}
self._creature_grid = {
point: None for point in self.rect.iter_points()}
self.floor_spaces = set()
def randomize(cls, region, *, minimum_size=Size(5, 5)):
"""Place a room randomly in a region, randomizing its size and position.
"""
# TODO need to guarantee the region is big enough
size = Size(
random_normal_range(minimum_size.width, region.width),
random_normal_range(minimum_size.height, region.height),
)
left = region.left + random.randint(0, region.width - size.width)
top = region.top + random.randint(0, region.height - size.height)
rect = Rectangle(Point(left, top), size)
return cls(rect)
def _generate_river(self, noise):
# TODO seriously starting to feel like i need a Feature type for these
# things? like, passing `noise` around is a really weird way to go
# about this. what would the state even look like though?
'''
# TODO i think this needs another flooding algorithm, which probably
# means it needs to be a lot simpler and faster...
noise_factory = discrete_perlin_noise_factory(
*self.region.size, resolution=2, octaves=1)
noise = {
point: abs(noise_factory(*point) - 0.5) * 2
for point in self.region.iter_points()
}
for point, n in noise.items():
if n < 0.2:
self.map_canvas.set_architecture(point, e.Water)
return
'''
# Build some Blob internals representing the two halves of the river.
left_side = {}
right_side = {}
river = {}
center_factory = discrete_perlin_noise_factory(
self.region.height, resolution=3)
width_factory = discrete_perlin_noise_factory(
self.region.height, resolution=6, octaves=2)
center = random_normal_int(
self.region.center().x, self.region.width / 4 / 3)
for y in self.region.range_height():
center += (center_factory(y) - 0.5) * 3
width = width_factory(y) * 2 + 5
x0 = int(center - width / 2)
x1 = int(x0 + width + 0.5)
for x in range(x0, x1 + 1):
self.map_canvas.set_architecture(Point(x, y), e.Water)
left_side[y] = (Span(self.region.left, x0 - 1),)
right_side[y] = (Span(x1 + 1, self.region.right),)
river[y] = (Span(x0, x1),)
return Blob(left_side), Blob(river), Blob(right_side)
def __init__(self, size):
self.rect = size.to_rect(Point.origin())
self.arch_grid = {point: CaveWall for point in self.rect.iter_points()}
self.item_grid = {point: [] for point in self.rect.iter_points()}
self.creature_grid = {point: None for point in self.rect.iter_points()}
def generate(self):
self.map_canvas.clear(CaveWall)
# First create a bunch of hallways and rooms.
# For now, just carve a big area, run a hallway through the middle, and
# divide either side into rooms.
area = Room.randomize(self.region, minimum_size=self.region.size // 2)
area.draw_to_canvas(self.map_canvas)
center = area.rect.center()
y0 = center.y - 2
y1 = center.y + 2
hallway = Rectangle(origin=Point(area.rect.left, center.y - 2), size=Size(area.rect.width, 5))
Room(hallway).draw_to_canvas(self.map_canvas)
top_space = area.rect.replace(bottom=hallway.top)
bottom_space = area.rect.replace(top=hallway.bottom)
rooms = []
for orig_space in (top_space, bottom_space):
space = orig_space
# This includes walls!
minimum_width = 7
# Note that the rooms overlap where they touch, so we subtract one
# from both the total width and the minimum width, in effect
# ignoring all the walls on one side
maximum_rooms = (space.width - 1) // (minimum_width - 1)
# The maximum number of rooms that will fit also affects how much
# wiggle room we're willing to have. For example, if at most 3 rooms
# will fit, then generating 2 rooms is also reasonable. But if 10
# rooms will fit, generating 2 rooms is a bit silly. We'll arbitrarily
# use 1/3 the maximum as the minimum. (Plus 1, to avoid rounding down
# to zero.)
minimum_rooms = maximum_rooms // 6 + 1
num_rooms = random_normal_range(minimum_rooms, maximum_rooms)
# TODO normal distribution doesn't have good results here. think
# more about how people use rooms -- often many of similar size,
# with some exceptions. also different shapes, bathrooms or
# closets nestled together, etc.
while num_rooms > 1:
# Now we want to divide a given amount of space into n chunks, where
# the size of each chunk is normally-distributed. I have no idea how
# to do this in any strict mathematical sense, so instead we'll just
# carve out one room at a time and hope for the best.
min_width = minimum_width
avg_width = (space.width - 1) // num_rooms + 1
max_width = space.width - (minimum_width - 1) * (num_rooms - 1)
room_width = random_normal_int(avg_width, min(max_width - avg_width, avg_width - min_width) // 3)
room = space.replace(right=space.left + room_width - 1)
rooms.append(room)
space = space.replace(left=room.right)
num_rooms -= 1
rooms.append(space)
for rect in rooms:
Room(rect).draw_to_canvas(self.map_canvas)
from flax.component import Lockable
# Add some doors for funsies.
locked_room = random.choice(rooms)
for rect in rooms:
x = random.randrange(rect.left + 1, rect.right - 1)
if rect.top > hallway.top:
side = Direction.down
else:
side = Direction.up
point = rect.edge_point(side.opposite, x, 0)
door = e.Door(Lockable(locked=rect is locked_room))
self.map_canvas.set_architecture(point, door)
self.hallway_area = Blob.from_rectangle(hallway)
self.locked_area = Blob.from_rectangle(locked_room)
self.rooms_area = reduce(operator.add, (Blob.from_rectangle(rect) for rect in rooms if rect is not locked_room))
def generate(self):
self.map_canvas.clear(Floor)
# So what I want here is to have a cave system with a room in the
# middle, then decay the room.
# Some constraints:
# - the room must have a wall where the entrance could go, which faces
# empty space
# - a wall near the entrance must be destroyed
# - the player must start in a part of the cave connected to the
# destroyed entrance
# - none of the decay applied to the room may block off any of its
# interesting features
# TODO it would be nice if i could really write all this without ever
# having to hardcode a specific direction, so the logic could always be
# rotated freely
side = random.choice([Direction.left, Direction.right])
# TODO assert region is big enough
room_size = Size(
random_normal_range(9, int(self.region.width * 0.4)),
random_normal_range(9, int(self.region.height * 0.4)),
)
room_position = self.region.center() - room_size // 2
room_position += Point(
random_normal_int(0, self.region.width * 0.1),
random_normal_int(0, self.region.height * 0.1),
)
room_rect = Rectangle(room_position, room_size)
self.room_region = room_rect
room = Room(room_rect)
cave_area = (
Blob.from_rectangle(self.region)
- Blob.from_rectangle(room_rect)
)
self.cave_region = cave_area
walls = [point for (point, _) in self.region.iter_border()]
floors = []
for point, edge in room_rect.iter_border():
if edge is side or edge.adjacent_to(side):
floors.append(point)
floors.append(point + side)
generate_caves(
self.map_canvas, cave_area, CaveWall,
force_walls=walls, force_floors=floors,
)
room.draw_to_canvas(self.map_canvas)
# OK, now draw a gate in the middle of the side wall
if side is Direction.left:
x = room_rect.left
else:
x = room_rect.right
mid_y = room_rect.top + room_rect.height // 2
if room_rect.height % 2 == 1:
min_y = mid_y - 1
max_y = mid_y + 1
else:
min_y = mid_y - 2
max_y = mid_y + 1
for y in range(min_y, max_y + 1):
self.map_canvas.set_architecture(Point(x, y), KadathGate)
# Beat up the border of the room near the gate
y = random.choice(
tuple(range(room_rect.top, min_y))
+ tuple(range(max_y + 1, room_rect.bottom))
)
for dx in range(-2, 3):
for dy in range(-2, 3):
point = Point(x + dx, y + dy)
# TODO i think what i may want is to have the cave be a
# "Feature", where i can check whether it has already claimed a
# tile, or draw it later, or whatever.
if self.map_canvas._arch_grid[point] is not CaveWall:
distance = abs(dx) + abs(dy)
ruination = random_normal_range(0, 0.2) + distance * 0.2
self.map_canvas.set_architecture(
point, e.Rubble(Breakable(ruination)))
# And apply some light ruination to the inside of the room
border = list(room_rect.iter_border())
# TODO don't do this infinitely; give up after x tries
while True:
point, edge = random.choice(border)
if self.map_canvas._arch_grid[point + edge] is CaveWall:
break
self.map_canvas.set_architecture(point, CaveWall)
self.map_canvas.set_architecture(point - edge, CaveWall)
# TODO this would be neater if it were a slightly more random pattern
for direction in (
Direction.up, Direction.down, Direction.left, Direction.right):
self.map_canvas.set_architecture(
point - edge + direction, CaveWall)
def generate(self):
# This noise is interpreted roughly as the inverse of "frequently
# travelled" -- low values are walked often (and are thus short grass),
# high values are left alone (and thus are trees).
noise_factory = discrete_perlin_noise_factory(
*self.region.size, resolution=6)
noise = {
point: noise_factory(*point)
for point in self.region.iter_points()
}
local_minima = set()
for point, n in noise.items():
# We want to ensure that each "walkable region" is connected.
# First step is to collect all local minima -- any walkable tile is
# guaranteed to be conneted to one.
if all(noise[npt] >= n for npt in point.neighbors if npt in noise):
local_minima.add(point)
if n < 0.3:
arch = CutGrass
elif n < 0.6:
arch = Grass
else:
arch = Tree
self.map_canvas.set_architecture(point, arch)
left_bank, river_blob, right_bank = self._generate_river(noise)
# Decide where bridges should go. They can only cross where there's
# walkable space on both sides, so find all such areas.
# TODO maybe a nicer api for testing walkability here
# TODO this doesn't detect a walkable area on one side that has no
# walkable area on the other side, and tbh i'm not sure what to do in
# such a case anyway. could forcibly punch a path through the trees, i
# suppose? that's what i'll have to do anyway, right?
# TODO this will break if i ever add a loop in the river, but tbh i
# have no idea how to draw bridges in that case
new_block = True
start = None
end = None
blocks = []
for y, (span,) in river_blob.spans.items():
if self.map_canvas._arch_grid[Point(span.start - 1, y)] is not Tree and \
self.map_canvas._arch_grid[Point(span.end + 1, y)] is not Tree:
if new_block:
start = y
end = y
new_block = False
else:
end = y
else:
if not new_block:
blocks.append((start, end))
new_block = True
if not new_block:
blocks.append((start, end))
for start, end in blocks:
y = random_normal_range(start, end)
span = river_blob.spans[y][0]
local_minima.add(Point(span.start - 1, y))
local_minima.add(Point(span.end + 1, y))
for x in span:
self.map_canvas.set_architecture(Point(x, y), e.Bridge)
# Consider all local minima along the edges, as well.
for x in self.region.range_width():
for y in (self.region.top, self.region.bottom):
point = Point(x, y)
n = noise[point]
if (n < noise.get(Point(x - 1, y), 1) and
n < noise.get(Point(x + 1, y), 1)):
local_minima.add(point)
for y in self.region.range_height():
for x in (self.region.left, self.region.right):
point = Point(x, y)
n = noise[point]
if (n < noise.get(Point(x, y - 1), 1) and
n < noise.get(Point(x, y + 1), 1)):
local_minima.add(point)
for point in local_minima:
if point not in river_blob:
self.map_canvas.set_architecture(point, e.Dirt)
for blob in (left_bank, right_bank):
paths = self.flood_valleys(blob, local_minima, noise)
for path_point in paths:
self.map_canvas.set_architecture(path_point, e.Dirt)
# Whoops time for another step: generating a surrounding cave wall.
for edge in Direction.orthogonal:
width = self.region.edge_length(edge)
wall_noise = discrete_perlin_noise_factory(width, resolution=6)
for n in self.region.edge_span(edge):
offset = int(wall_noise(n) * 4 + 1)
for m in range(offset):
point = self.region.edge_point(edge, n, m)
self.map_canvas.set_architecture(point, e.CaveWall)
def test_blob_create():
rect = Rectangle(origin=Point(0, 0), size=Size(5, 5))
blob = Blob.from_rectangle(rect)
assert blob.area == rect.area
assert blob.height == rect.height
