def make_level(image):
level_array = np.zeros(image.size, dtype="int")
player_before_pos = None
player_after_pos = None
lowest_air = -float("inf")
highest_liquid = float("inf")
liquid_type = LiquidType.NONE
item_locations = []
for xy in Rect(Coord(0,0), Coord(image.size[0], image.size[1])):
p = image.getpixel((xy.x, xy.y))
m = color_to_abstract[p]
if p in player_before_colors and player_before_pos is None:
player_before_pos = xy
if p in player_after_colors and player_after_pos is None:
player_after_pos = xy
if p in air_colors and xy.y > lowest_air:
lowest_air = xy.y
if p in water_colors and xy.y < highest_liquid:
liquid_type = LiquidType.WATER
highest_liquid = xy.y
if p == item_color:
item_locations.append(xy)
level_array[(xy.x, xy.y)] = m
#TODO: other liquids
# Water level has to be /strictly/ below the lowest air,
# and at least as high as the highest liquid
liquid_interval = Interval(lowest_air + 1, highest_liquid)
# Put the liquid as low as possible
level = LevelState(Coord(0,0), level_array, LiquidType.WATER, highest_liquid, {}, {})
if player_after_pos is None:
player_after_pos = player_before_pos.copy()
return player_before_pos, player_after_pos, level, liquid_interval, liquid_type, item_locations
def collide(self, ds, debug=False):
s = self.copy()
v = self.velocity
for d in ds:
# Landing on the ground
if d == Coord(0, 1):
vh = HVelocity(VType.RUN, 0)
vv = 0
v = Velocity(vv, vh)
s.velocity = v
# Any non-morph pose leaves you standing
#TODO: what if you're in spin in a 2-high gap -- this will clip you into the floor!!
if s.pose == SamusPose.SPIN:
s.pose = SamusPose.STAND
s.position += Coord(0, -1)
elif s.pose != SamusPose.MORPH:
s.pose = SamusPose.STAND
# Colliding with the ceiling
elif d == Coord(0, -1):
vv = 0
v = Velocity(vv, s.velocity.vh.copy())
s.velocity = v
# Colliding with a wall (kill horizontal velocity)
else:
vh = HVelocity(VType.RUN, 0)
v = Velocity(s.velocity.vv, vh)
s.velocity = v
if debug:
print("Collided")
print(s)
return s
def horizontal_flip(self):
vnew = self.vfunction.horizontal_flip()
# Flip the after position horizontally too
pnew = Coord(-self.after_position.x, self.after_position.y)
# Flip the set of items obtained
new_items = [Coord(-g.x, g.y) for g in self.gain_items]
return SamusFunction(vnew, self.required_items, new_items,
self.before_pose, self.after_pose, pnew)
def extent(coords):
"""Returns the smallest rectangle that contains each of the coords"""
if len(coords) == 0:
return None
minx = min(coords, key=lambda item: item.x).x
miny = min(coords, key=lambda item: item.y).y
maxx = max(coords, key=lambda item: item.x).x
maxy = max(coords, key=lambda item: item.y).y
return Rect(Coord(minx, miny), Coord(maxx, maxy) + Coord(1, 1))
def find_all_rects(space):
all_rects = set()
for p in space:
p_rects = find_all_rects_at(space,
p,
directions=[Coord(1, 0),
Coord(0, 1)])
all_rects |= p_rects
return all_rects
def horizontal_flip(self):
pos = Coord(-self.pos.x, self.pos.y)
walls = [Coord(-w.x, w.y) for w in self.walls]
airs = [(Coord(-d.x, d.y), [Coord(-t.x, t.y) for t in tiles])
for d, tiles in self.airs]
if self.samusfunction is None:
sf = None
else:
sf = self.samusfunction.horizontal_flip()
return IntermediateState(pos, walls, airs, sf)
def get_cross(p):
""" Cross-shaped group of coords centered on p """
directions = [
Coord(0, 0),
Coord(1, 0),
Coord(-1, 0),
Coord(0, 1),
Coord(0, -1)
]
return [p + d for d in directions]
def pretty_print(self, samus_states, image_folder):
tile_size = 16
scale_factor = Coord(tile_size, tile_size)
center = Coord(tile_size // 2, tile_size // 2)
image_dict = parse_image_folder(image_folder)
i = Image.new("RGB",
(self.shape[0] * tile_size, self.shape[1] * tile_size))
pixels = i.load()
# Draw the level
for xy in self.rect:
pos = (xy - self.origin) * scale_factor
# Have to convert pos from coord to tuple for some reason
i.paste(image_dict[abstract_to_image[self[xy]]], (pos[0], pos[1]))
# Draw the samusstates
# Draw s0 arbitrarily first
if len(samus_states) > 0:
s0_i = image_dict[samus_state_to_image(samus_states[0], None)]
pos = (samus_states[0].position - self.origin) * scale_factor
i.paste(s0_i, (pos[0], pos[1]))
# Samus facing direction depends on context of previous state
for s1, s2 in pairwise(samus_states):
s_i = image_dict[samus_state_to_image(s2, s1)]
pos = (s2.position - self.origin) * scale_factor
i.paste(s_i, (pos[0], pos[1]))
# Draw the items (over the samuses, to make them visible, under the arrows)
for pos, item in self.items.items():
if item in item_to_image:
item_image = image_dict[item_to_image[item]]
else:
# Handles bosses, etc.
item_image = image_dict["item_unknown.png"]
real_pos = pos * scale_factor
i.paste(item_image, (real_pos[0], real_pos[1]))
# Convert to numpy to draw arrows using CV2
numpy_i = np.array(i)
# Draw the arrows connecting the samusstates
for index, (s1, s2) in enumerate(pairwise(samus_states)):
p1 = s1.position * scale_factor + center
p2 = s2.position * scale_factor + center
# cv2 does not have fixed size tiplengths
length = p2.euclidean(p1)
if length == 0:
tiplength = 0
else:
tiplength = 10 / length
percent = index / len(samus_states)
c_index = int(255 * percent)
color = (c_index, 0, 255 - c_index)
cv2.arrowedLine(numpy_i, p1, p2, color, 2, tipLength=tiplength)
# Convert back to PIL
i = Image.fromarray(numpy_i)
return i
def get_extra_fixed_tiles(rect, fixed_tiles, extra_similarity):
assert extra_similarity >= 0
assert extra_similarity <= 1
border_tiles = set()
for x in range(rect.start.x, rect.end.x):
border_tiles.add(Coord(x, rect.start.y))
border_tiles.add(Coord(x, rect.end.y - 1))
for y in range(rect.start.y, rect.end.y):
border_tiles.add(Coord(rect.start.x, y))
border_tiles.add(Coord(rect.end.x - 1, y))
free_tiles = rect.as_set() - (fixed_tiles | border_tiles)
n_fixed = int(len(free_tiles) * extra_similarity)
extra_fixed_tiles = set(random.sample(free_tiles, n_fixed))
return extra_fixed_tiles | border_tiles
def wfc_level_data(room_header,
auto_rect=False,
rects=None,
extra_similarity=0,
seed=None):
if seed is not None:
random.seed(seed)
# Get fns before messing with the level data
fns = get_state_functions(room_header)
fixed_tiles, screen_map = get_fixed_tiles(room_header)
default_level_data = room_header.state_chooser.default.level_data
level_shape = Coord(*default_level_data.level_array.layer1.shape)
level_bits = bit_array_from_bytes(default_level_data.level_bytes,
level_shape)
# Get the rectangularization either automatically, by input, or just the whole level at once
if auto_rect:
assert rects is None
# Scale them back up to size 16x16 (rects found are rects of screens)
#TODO: choose tiles based on ratio of tiles / pattern (higher is better)
rects = [
rect.scale(16)
for rect in wfc_rectangularize(screen_map, max_area=9)
]
print("Found rectangles: {}".format(rects))
# Use one big rect if none is satisfied
elif rects is None:
offset = Coord(0, 0)
size = Coord(*level_shape)
rects = [Rect(offset, size)]
# Use WFC to reconstruct each rect using tiles from within that rect
#TODO: how to use tiles from the entire room?
for rect in rects:
print("For rectangle {}:".format(rect))
# Add borders etc.
extra_fixed_tiles = get_extra_fixed_tiles(rect, fixed_tiles,
extra_similarity)
all_fixed_tiles = fixed_tiles | extra_fixed_tiles
rect_bits = level_bits[rect.start[0]:rect.end[0],
rect.start[1]:rect.end[1]]
rect_fixed_tiles = rel_fixed_tiles(rect, all_fixed_tiles)
#print(rect_fixed_tiles)
print("Fixed tile ratio: {}".format(len(rect_fixed_tiles) / rect.area))
wfc_bits = bit_wfc(rect_bits, rect_fixed_tiles)
# Overwrite level_bits with the new data
level_bits[rect.start[0]:rect.end[0],
rect.start[1]:rect.end[1]] = wfc_bits
level = level_from_bits(level_bits)
return level, fns
def random_node_place(graph, dimensions, up_es, down_es):
"""
Returns a dictionary of node -> location by choosing locations for the nodes
at random.
"""
r = Rect(Coord(0, 0), dimensions)
# Use as_list since set() is forbidden for ordering
xys = r.as_list()
locs = random.sample(xys, graph.nnodes)
node_list = graph.nodes.keys()
node_locs = {}
# choose elevator locations: down elevators are the lowest locs, and up are the highest locs
#TODO: seems like it doesn't always return the lowest n or highest n points
sorted_locs = sorted(locs, key=lambda n: n.y)
for node in node_list:
if node in up_es:
node_locs[node] = sorted_locs.pop(
0) # highest y coordinate is further down
elif node in down_es:
node_locs[node] = sorted_locs.pop()
node_list = [
node for node in node_list if node not in up_es and node not in down_es
]
random.shuffle(node_list)
#TODO: this is where we can make sure there is an item behind Draygon or some such??
# -> pick an item node later in the order than Draygon and put it past Draygon?
# -> default to supers
for i in range(len(node_list)):
if node_list[i] not in node_locs:
node_locs[node_list[i]] = sorted_locs[i]
return node_locs
def compose(self, other, offset=Coord(0,0), collision_policy="error"):
"""Returns a new cmap which is a composition of self and other.
If self and other share a maptile, then the collision policy decides."""
new_tiles = {}
for c, t in self.items():
# Use a copy to avoid duplicates
new_tiles[c] = t.copy()
for c, t in other.items():
c_o = c + offset
if not self.in_bounds(c_o) or c_o in new_tiles:
# 'defer' means tiles from self are preferred over tiles from other
if collision_policy == "defer":
continue
# 'error' means bomb out when there's a conflict
elif collision_policy == "error":
assert False, "Collision in compose: " + str(c)
# 'none' means to not produce a composed cmap if there is a conflict
elif collision_policy == "none":
return None
else:
assert False, "Bad collision policy: " + collision_policy
else:
new_tiles[c_o] = t.copy()
#TODO: which dimensions does it get?
return ConcreteMap(self.dimensions, _tiles=new_tiles)
def parse_statefunction(name, level_image, d):
#print("Parsing rule: {}".format(name))
b_pos, a_pos, level, liquid_interval, liquid_type, item_locations = make_level(level_image)
rel_pos = a_pos - b_pos
scan_direction = (a_pos - b_pos).sign()
r = Rect(Coord(0,0), Coord(level.shape[0], level.shape[1]))
vf = parse_vfunction(d)
p_initial = Coord(0,0)
v_final = vf.domain
pose_initial = pose_str[d["b_pose"]]
pose_final = pose_str[d["a_pose"]]
items_initial = parse_items(d["items"])
sfunction = SamusFunction(vf, items_initial, item_locations, pose_initial, pose_final, rel_pos)
#TODO: certain (i.e. the first of each rule) IntermediateStates hold the sfunction so that samus' state
# can be inferred within the rule
#TODO: verify by checking that the inferred end state is the same as the end state achieved through function
# composition
i_states = []
for xy in r.iter_direction(scan_direction):
s_t = samus_tiles(xy, pose_final)
level_t = [index_level(level, t) for t in s_t]
#If samus is here through the rule
if all([t == AbstractTile.AIR for t in level_t]):
# Note the position, nearby airs, and nearby walls
all_adj = get_all_adj(xy, pose_final)
walls = get_all(level, all_adj, AbstractTile.SOLID)
# Normalized
walls = normalize_list(walls, xy)
airs = []
# Collect the necessary airs for each direction
for direction in [Coord(scan_direction.x, 0), Coord(0, scan_direction.y)]:
airs_in_d = get_all(level, get_adj(xy, pose_final, direction), AbstractTile.AIR)
airs_in_d = normalize_list(airs_in_d, xy)
airs.append((direction, airs_in_d))
# The position of this intermediate state relative to the origin
rel_pos = xy - b_pos
i_states.append(IntermediateState(rel_pos, walls, airs, None))
if len(i_states) > 0:
# Applies the function at the beginning of the rule
i_states[0].samusfunction = sfunction
lfunction = LevelFunction(liquid_type, liquid_interval, i_states)
cost = int(d["cost"])
s = StateFunction(name, sfunction, lfunction, cost)
if "Symmetric" not in d:
return [s, s.horizontal_flip()]
else:
return [s]
def get_tile(level, origin, tile):
index = tile - origin
try:
# Do not allow negative indexing
if Coord(0, 0) > index:
return None
return level[index]
# Do not allow oob indexing
except IndexError:
return None
def get_item_locations(plms):
item_locations = {}
plm_to_item = mk_plm_to_item(item_definitions.make_item_definitions())
for plm in plms.l:
print(hex(plm.plm_id))
if plm.plm_id in plm_to_item:
iset = plm_to_item[plm.plm_id]
c = Coord(plm.xpos, plm.ypos)
item_locations[c] = iset
return item_locations
def sub(self, rect, relative=False):
"""Returns a subcmap which is the cmap defined by the [start, end) rectangle."""
new_tiles = {}
if relative:
offset = rect.start
else:
offset = Coord(0, 0)
for c in rect.as_list():
if c in self:
new_tiles[c - offset] = self[c]
# new cmap's dimensions are end-start
return ConcreteMap(rect.size_coord(), _tiles=new_tiles), rect.start
def find_all_rects_at(positions, pos, directions=coord_directions):
assert pos in positions
i_rect = Rect(pos, pos + Coord(1, 1))
finished = set([i_rect])
q = [i_rect]
while len(q) > 0:
r = q.pop()
expands = expand_rect(positions, r, directions)
for e in expands:
if e not in finished:
finished.add(e)
q.append(e)
return finished
def parse_pattern(pattern_filename):
f = open(pattern_filename, "r")
tiles = {}
max_tile = Coord(0, 0)
max_area = 0
for y, line in enumerate(f.readlines()):
for x, entry in enumerate(line.split()):
assert entry[0] == "["
assert entry[-1] == "]"
entry = entry[1:-1]
es = entry.split(",")
# Assume BTS
if len(es) == 2:
bts = 0
elif len(es) == 3:
bts = int(es[2], 16)
else:
assert False, "Bad entry: " + entry
# Find the texture
if es[0] == "_":
texture = Texture(0, 0, is_any=True)
else:
tex_index, flips = find_flips(es[0])
texture = Texture(tex_index, flips)
# Find the type
if es[1] == "_":
tile_type = Type(0, 0, is_any=True)
else:
ty_index = int(es[1], 16)
ty = Type(ty_index, bts)
c = Coord(x, y)
a = c.area()
tiles[c] = Tile(texture, ty)
if a >= max_area:
max_tile = c
max_area = a
f.close()
level = Level(max_tile + Coord(1, 1), tiles=tiles)
return level
def spring_model(node_locs, graph, n_iterations, spring_constant,
spring_equilibrium, dt, damping):
"""Changes node placement based on a simple spring model.
Node locs is the dictionary of initial node placements and is edited by the function.
graph is the graph of how the nodes are connected to each other
(i.e. where to place springs).
n_iterations is how many time steps to run the model for.
A few should suffice for my purposes.
spring_constant is the k in -kx.
spring_equilibrium is the distance where the spring is at rest.
dt is the time step.
Returns a lower potential-energy node_locs."""
# node locs is node_name -> node_position
# node_name -> node_velocity
# using mcoords as a vector
node_v = {n: Coord(0, 0) for n in node_locs}
# node_name -> node_acceleration
node_a = {n: Coord(0, 0) for n in node_locs}
iteration = 0
while iteration < n_iterations:
for n in node_locs:
# Update node_v
for e in graph.nodes[n].edges:
t = e.terminal
# The amount of stretching, possibly negative
x = euclidean(node_locs[n], node_locs[t]) - spring_equilibrium
# Direction
n_to_t = (node_locs[t] - node_locs[n]).to_unit()
#-kx
node_v[n] = node_v[n] + n_to_t.scale(spring_constant * x * dt)
node_v[t] = node_v[t] + n_to_t.scale(-spring_constant * x * dt)
# update node_locs
node_locs[n] = node_locs[n] + node_v[n].scale(dt)
iteration = iteration + 1
# resolve to an int
# TODO: is there a dict map function?
node_locs = {n: node_locs[n].resolve_int() for n in node_locs}
return node_locs
def load_patterns(path):
# Get all the filenames in path
fnames = [
f for f in os.listdir(path) if os.path.isfile(os.path.join(path, f))
]
patterns = {}
for f in fnames:
name, ext = f.split(".")
if ext == "txt":
p = parse_pattern(os.path.join(path, f))
#TODO: create a flag that can be written in the file for whether to include a flip
patterns[name + "_l"] = p
patterns[name + "_r"] = p.reflect(Coord(1, 0))
return patterns
def expand_rect(positions, rect, directions=coord_directions):
"""
Helper for find_rect
"""
#TODO: randomize order?
rects = []
for d in directions:
if d < Coord(0, 0):
r = Rect(rect.start + d, rect.end)
else:
r = Rect(rect.start, rect.end + d)
# Need the resulting expanded rect to be a subset of the space
if r.as_set() <= positions:
rects.append(r)
return rects
def node_place(graph, dimensions, up_es, down_es, settings):
"""
Find a placement for nodes where their respective areas do not violate
each other.
Random initially, with elevators guaranteed to be at the top and bottom (initially)
Subjected to a spring model which reduces the total potential energy (moves far nodes closer)
Subject to a search so that nodes can be placed without violating each other's areas.
"""
initial = random_node_place(graph, dimensions, up_es, down_es)
spring = spring_model(initial, graph, settings["n_iterations"],
settings["spring_constant"], settings["equilibrium"],
settings["spring_dt"], settings["spring_damping"])
trunc_spring = {
n: xy.truncate(Coord(0, 0), dimensions)
for (n, xy) in spring.items()
}
# Now do a search for a good placement for each nod.
cmap = ConcreteMap(dimensions)
return find_placement(trunc_spring, cmap, up_es, down_es)
def level_from_bytes(levelbytes, dimensions):
# First two bytes are the amount of level1 data
levelsize = int.from_bytes(levelbytes[0:2], byteorder='little')
# Cut off the size
levelbytes = levelbytes[2:]
# Make sure everything matches
assert levelsize % 2 == 0, "Purported level size {} is not even!".format(
levelsize)
assert levelsize == dimensions.x * dimensions.y * 2, "Level data length {} does not match specified room dimensions {}".format(
levelsize, dimensions.x * dimensions.y * 2)
# The level might not include level2 data
if len(levelbytes) == int(2.5 * levelsize):
has_level2 = True
elif len(levelbytes) == int(1.5 * levelsize):
has_level2 = False
else:
assert False, "Purported level size does not match actual level size"
level = Level(dimensions)
for y in range(dimensions.y):
for x in range(dimensions.x):
index = y * dimensions.x + x
level1index = index * 2
level1 = int.from_bytes(levelbytes[level1index:level1index + 2],
byteorder='little')
btsindex = index + levelsize
bts = int.from_bytes(levelbytes[btsindex:btsindex + 1],
byteorder='little')
if has_level2:
level2index = index + (3 * levelsize // 2)
level2 = int.from_bytes(levelbytes[level2index:level2index +
2],
byteorder='little')
else:
level2 = 0
#TODO: level2 info dropped on the floor
ttype = level1 >> 12
hflip = (level1 >> 11) & 1
vflip = (level1 >> 10) & 1
tindex = level1 & 0b1111111111
texture = Texture(tindex, (hflip, vflip))
tiletype = Type(ttype, bts)
level[Coord(x, y)] = Tile(texture, tiletype)
return level
def make_level_from_room(room_header):
#TODO: is there a way to know which state is currently in use?
state = room_header.state_chooser.default
# Get layer1:
larray = state.level_data.level_array
layer1 = larray.layer1
bts = larray.bts
level_array = np.zeros(layer1.shape, dtype="int")
it = np.nditer(layer1, flags=["multi_index", "refs_ok"])
# Abstractify level data
for tile in it:
tile = tile.item()
i = it.multi_index
# Get the up and left tiles for v and h copy
x = i[0]
y = i[1]
up = None
left = None
if y > 0:
up = level_array[x, y-1]
if x > 0:
left = level_array[x-1, y]
tile_bts = bts[i]
level_array[i] = tile_to_abstract(tile, tile_bts, up, left, i)
#TODO: May not use default FX depending on door
#TODO: Door cap PLMs change level data!
fx = state.fx.default_fx
if fx is not None and fx.layer3_type in layer3_to_liquid:
liquid_type = layer3_to_liquid[fx.layer3_type]
#TODO - tile or pixel?
liquid_level = fx.liquid_target_y // 16
else:
liquid_type = LiquidType.NONE
liquid_level = None
#TODO
item_locations = get_item_locations(state.plms)
level = LevelState(Coord(0,0), level_array, liquid_type, liquid_level, item_locations, {})
return level
def rectangularize(subroom_state, cmap):
"""
Finds a set of initial rectangular subrooms for the given concrete map
"""
position_order = list(cmap.keys())
random.shuffle(position_order)
positions = set(cmap.keys())
# Gross way of getting the main set of tiles
assert len(subroom_state.g.nodes.keys()) == 1
# Main subroom is always initially subroom 0
main_subroom = subroom_state[0]
# Find rectangles until the entire cmap is covered
rects = []
print("RECT: Finding rectangles")
while len(positions) > 0:
pos = position_order[0]
rect = find_rect_at(positions, pos)
# Only need to create a subroom if the remaining cmap component that
# contains it also contains other cells
cmap_components = find_components(positions)
r_set = rect.as_set()
r_components = [c for c in cmap_components if r_set <= c]
assert len(r_components) == 1
r_component = r_components[0]
#TODO: rects are not relative to the room position, but they should be...
print(rect)
rects.append(rect)
if r_set < r_component:
# Find the subroom id for the component in question
t = next(iter(r_component)).scale(16) + Coord(8, 8)
component_parent_sid = subroom_state.tile_to_subroom(t)
rect_room = rect.scale(
16).as_set() & subroom_state[component_parent_sid].tiles
subroom_state.place_subroom(rect_room)
# Update positions
for c in rect:
positions.remove(c)
position_order.remove(c)
def paste(self, level_origin, level):
assert self.origin + self.shape <= Coord(level.shape[0],
level.shape[1])
o = self.origin - level_origin
assert o >= Coord(0, 0), o
level[o.x:o.x + self.shape.x, o.y:o.y + self.shape.y] = self.level
def get_fixed_tiles(room_header):
"""Compute the set of tiles that should be fixed for WFC for a given room header"""
fixed_tiles = set()
screen_map = set()
all_states = room_header.all_states()
#all_states = [s.state for s in room_header.state_chooser.conditions] + [room_header.state_chooser.default]
shapes = [
state.level_data.level_array.layer1.shape for state in all_states
]
# Hopefully all level datas have the same shape...
assert len(set(shapes)) == 1
for state in all_states:
# Add doors
layer1 = state.level_data.level_array.layer1
def inbounds(c):
if c[0] < 0 or c[1] < 0:
return False
if c[0] >= layer1.shape[0] or c[1] >= layer1.shape[1]:
return False
return True
it = np.nditer(layer1, flags=["multi_index", "refs_ok"])
for tile in it:
tile = tile.item()
if tile.tile_type == 9:
fixed_tiles.add(Coord(*it.multi_index))
# Add all enemy positions
#TODO: Some enemies may take up more than one tile...
#TODO: PLMs may want to have more than one tile allocated too
for enemy in state.enemy_list.enemies:
e_pos = Coord(enemy.x_pos // 16, enemy.y_pos // 16)
enemy_locale = get_cross(e_pos)
for p in enemy_locale:
if inbounds(p):
fixed_tiles.add(p)
# Add PLM positions
for plm in state.plms.l:
plm_pos = Coord(plm.x_pos, plm.y_pos)
plm_locale = get_cross(plm_pos)
for p in plm_locale:
if inbounds(p):
fixed_tiles.add(p)
# Add screens that are either fully solid or fully air
for x in range(layer1.shape[0] // 16):
for y in range(layer1.shape[1] // 16):
screen_x = x * 16
screen_y = y * 16
screen = layer1[screen_x:screen_x + 16, screen_y:screen_y + 16]
test_solid = np.vectorize(lambda x: x.tile_type == 8)
test_air = np.vectorize(lambda x: x.tile_type == 0)
if np.all(test_solid(screen)) or np.all(test_air(screen)):
# Add this screen and its borders
for x_sub in range(-1, 17):
for y_sub in range(-1, 17):
c = (screen_x + x_sub, screen_y + y_sub)
if inbounds(c):
fixed_tiles.add(Coord(*c))
# Add all "valid" screens to the screen map
else:
screen_map.add(Coord(x, y))
# Add level borders
for x in range(layer1.shape[0]):
fixed_tiles.add(Coord(x, 0))
fixed_tiles.add(Coord(x, layer1.shape[1] - 1))
for y in range(layer1.shape[1]):
fixed_tiles.add(Coord(0, y))
fixed_tiles.add(Coord(layer1.shape[0] - 1, y))
#TODO: constrain scroll boundaries?
return fixed_tiles, screen_map
def level_from_bits(bits):
new_bytes = bytes_from_bit_array(bits)
new_arrays = level_array_from_bytes(new_bytes, Coord(*bits.shape[:-1]))
return new_bytes, new_arrays
def __getitem__(self, index):
internal_index = index - self.origin
# Do not allow negative indexing
if Coord(0, 0) > internal_index:
raise IndexError(internal_index)
return self.level[internal_index]
def horizontal_flip(self, level):
position = self.position.flip_in_rect(level.rect, Coord(1, 0))
v = self.velocity.horizontal_flip()
i = self.items.copy()
p = self.pose
return SamusState(position, v, i, p)