def add_containment_axioms(self, solver: z3.Optimize, confIdx: int,
parent: IView[NT], x_dim: bool) -> None:
pl, pr = anchor_id_to_z3_var(parent.left_anchor.id,
confIdx), anchor_id_to_z3_var(
parent.right_anchor.id, confIdx)
pt, pb = anchor_id_to_z3_var(parent.top_anchor.id,
confIdx), anchor_id_to_z3_var(
parent.bottom_anchor.id, confIdx)
for child in parent.children:
cl, cr = anchor_id_to_z3_var(child.left_anchor.id,
confIdx), anchor_id_to_z3_var(
child.right_anchor.id, confIdx)
ct, cb = anchor_id_to_z3_var(child.top_anchor.id,
confIdx), anchor_id_to_z3_var(
child.bottom_anchor.id, confIdx)
# if child.left_anchor.value >= parent.left_anchor.value:
if x_dim:
solver.add(cl >= pl)
# if child.right_anchor.value <= parent.right_anchor.value:
solver.add(cr <= pr)
# if child.top_anchor.value >= parent.top_anchor.value:
else:
solver.add(ct >= pt)
# if child.bottom_anchor.value <= parent.bottom_anchor.value:
solver.add(cb <= pb)
self.add_containment_axioms(solver, confIdx, child, x_dim)
def evalOthers(toRun, name, makeSpec, checkFunc):
print(name)
lineLengths = toRun.copy()
gamutSizes = toRun.copy()
tasks = list(itertools.product(lineLengths, gamutSizes))
results = []
print(tasks)
res = []
for (length, gamut) in tasks:
try:
print((length, gamut))
s = cantusSpec(length, gamut, '')
opt = Optimize()
for c in s.constraints:
opt.add(c.formula)
checked, _ = timeWithTimeout(lambda: opt.check(), 10)
if (checked == sat):
cf = [extractPitch(opt.model(), p) for p in s.line]
res += doCheck(
makeSpec([ConstPitch(x) for x in cf], gamut, ''),
lambda x: checkFunc(cf, x), length, gamut, name)
except Exception:
pass
dt = str(datetime.datetime.now())
out = pd.DataFrame(columns=['length', 'gamut', 'mutations', 'time'],
data=res)
out.to_csv('output/checker/' + name + '/time_' + dt + '.csv')
def add_conf_dims(solver: z3.Optimize, conf: Conformance, confIdx: int, targets: Tuple[IAnchor[NT],IAnchor[NT],IAnchor[NT],IAnchor[NT]]) -> None:
top_x, top_y, top_width, top_height = targets
top_x_v = anchor_id_to_z3_var(top_x.id, confIdx)
top_y_v = anchor_id_to_z3_var(top_y.id, confIdx)
top_w_v = anchor_id_to_z3_var(top_width.id, confIdx)
top_h_v = anchor_id_to_z3_var(top_height.id, confIdx)
solver.add(top_w_v == conf.width)
solver.add(top_h_v == conf.height)
solver.add(top_x_v == conf.x)
solver.add(top_y_v == conf.y)
def doRepair(spec: Spec, check, length, gamut, name):
specs = getAllBadSpecs(
spec=spec, maxCount=5, doShuffle=True,
filterOutUnsatisfiable=False) + [spec]
ret = []
for s in specs:
numMutations = sum(
[1 if 'inverse' in str(x) else 0 for x in s.constraints])
# Using this rather than generator because generator is increadibly slow in this
# context for some reason
opt = Optimize()
for c in s.constraints:
opt.add(c.formula)
checked, _ = timeWithTimeout(lambda: opt.check(), 10)
if (checked == sat):
line = [extractPitch(opt.model(), p) for p in s.line]
res, runtime = timeWithTimeout(lambda: check(line), 10)
if res is not None:
ret.append((length, gamut, numMutations, runtime))
return ret
def add_layout_axioms(self,
solver: z3.Optimize,
confIdx: int,
boxes: Iterable[IView[NT]],
x_dim: bool,
tracking: bool = False) -> None:
for box in boxes:
w, h = anchor_id_to_z3_var(box.width_anchor.id, confIdx), \
anchor_id_to_z3_var(box.height_anchor.id, confIdx)
l, r = anchor_id_to_z3_var(box.left_anchor.id, confIdx), \
anchor_id_to_z3_var(box.right_anchor.id, confIdx)
t, b = anchor_id_to_z3_var(box.top_anchor.id, confIdx), \
anchor_id_to_z3_var(box.bottom_anchor.id, confIdx)
c_x = anchor_id_to_z3_var(box.center_x_anchor.id, confIdx)
c_y = anchor_id_to_z3_var(box.center_y_anchor.id, confIdx)
widthAx = w == (r - l)
heightAx = h == (b - t)
# print('adding axioms:', widthAx, heightAx, w>=0, h >= 0)
if tracking:
if x_dim:
raise Exception('unimplemented')
solver.assert_and_track(widthAx,
f'{box.name}-wax-{str(confIdx)}')
solver.assert_and_track(heightAx,
f'{box.name}-hax-{str(confIdx)}')
solver.assert_and_track(c_x == (l + r) / 2,
f'{box.name}-cx-{str(confIdx)}')
solver.assert_and_track(c_y == (t + b) / 2,
f'{box.name}-cy-{str(confIdx)}')
for idx, anchor in enumerate(box.anchors):
solver.assert_and_track(
anchor_id_to_z3_var(anchor.id, confIdx) >= 0,
f'{box.name}-pos-{str(confIdx)}-{str(idx)}')
else:
if x_dim:
solver.add(widthAx)
solver.add(c_x == (l + r) / 2)
for anchor in box.x_anchors:
solver.add(
anchor_id_to_z3_var(anchor.id, confIdx) >= 0)
else:
solver.add(heightAx)
solver.add(c_y == (t + b) / 2)
for anchor in box.y_anchors:
solver.add(
anchor_id_to_z3_var(anchor.id, confIdx) >= 0)
def solve(grid_size_x, grid_size_y, max_height, robots, depots, i_grid, g_grid, timeout=100000):
i_grid = deepcopy(i_grid)
#print ("Solving: ", grid_size_x, grid_size_y, max_height, robots, depots, i_grid, g_grid)
assert(grid_size_y == len(i_grid))
adjacent = defaultdict(list)
# A cell X is supporter of another Y if we will use X in order to access Y
for x in range(grid_size_x):
for y in range (grid_size_y):
if x > 0:
adjacent [(x, y)].append((x-1, y))
if y > 0:
adjacent [(x, y)].append((x, y-1))
if x < grid_size_x - 1:
adjacent [(x, y)].append((x+1, y))
if y < grid_size_y - 1:
adjacent [(x, y)].append((x, y+1))
intermediate_board=[[Int('intermediate%d-%d' % (c, r)) for c in range(grid_size_x)] for r in range(grid_size_y)]
target_board=[[Int('target%d-%d' % (c, r)) for c in range(grid_size_x)] for r in range(grid_size_y)]
order=[[Int('order%d-%d' % (c, r)) for c in range(grid_size_x)] for r in range(grid_size_y)]
is_supporter=[[Bool('supporter%d-%d' % (c, r)) for c in range(grid_size_x)] for r in range(grid_size_y)]
is_supported=[[Bool('supported%d-%d' % (c, r)) for c in range(grid_size_x)] for r in range(grid_size_y)]
supporter_variables = {}
for x in range(grid_size_x):
for y in range (grid_size_y):
for (xp, yp) in adjacent[(x,y)]:
supporter_variables[(x, y, xp, yp)] = Bool('supporter%d-%d-%d-%d' % (x, y, xp, yp))
all_intermediate_board = [cell for column in intermediate_board for cell in column ]
s = Optimize()
#s.set("timeout", timeout)
for (y, row) in enumerate(g_grid):
for (x, tile) in enumerate (row):
if (x, y) in depots:
s.add (intermediate_board[y][x] == 0) # The depot location must always have height 0
s.add (order[y][x] == 0) # The depot location must always have order 0
else:
s.add (order[y][x] > 0)
s.add (target_board[y][x] == tile)
s.add(intermediate_board[y][x] <= max_height) # Intermediate_Board cannot have more height than max_height
s.add(intermediate_board[y][x] >= max(tile, i_grid[y][x])) # Intermediate_Board cannot have negative height
# All intermediate_board supporter or greater than 0 must have a supporter
s.add(Implies(intermediate_board[y][x] > 0, is_supported[y][x] == True))
s.add (is_supported[y][x] == Or (*[supporter_variables[(x, y, xp, yp)] == True for (xp, yp) in adjacent[(x, y)]]))
s.add (is_supporter[y][x] == Or (*[supporter_variables[(xp, yp, x, y)] == True for (xp, yp) in adjacent[(x, y)]]))
s.add (Implies(is_supporter[y][x], is_supported[y][x]))
for (xp, yp) in adjacent[(x, y)]:
# A cell cannot support its supporter (there is a total order of supporters)
s.add(Implies(supporter_variables[(x, y, xp, yp)], order[yp][xp] < order[y][x]))
# The supporter must give access to the cell
s.add(Or(supporter_variables[(x, y, xp, yp)] == False, intermediate_board[y][x] == intermediate_board[yp][xp], intermediate_board[y][x] == intermediate_board[yp][xp] + 1))
# The supporter must give access to remove the cell
s.add(Implies(supporter_variables[(x, y, xp, yp)], target_board[y][x] >= target_board[yp][xp]))
#s.add(Or(is_supporter[y][x] == False, is_supported[y][x] == False, is_supporter[yp][xp] == False, is_supported[yp][xp] == False, order[y][x] == order[yp][xp], order[y][x] == order[yp][xp] + 1, order[y][x] == order[yp][xp] - 1))
#s.add (intermediate_board[0][0] == 0)
h=s.minimize(Sum(*all_intermediate_board)*1000 + Sum([cell for column in order for cell in column ]))
s_result = s.check()
# print(s)
# print(s_result)
if str(s_result).strip() == "unsat":
#print(s)
exit()
return None
m = s.model()
# for r in range(grid_size_y):
# sys.stdout.write ("; ")
# for c in range(grid_size_x):
# sys.stdout.write (str(m[cells[r][c]])+" ")
# print ("")
target_grid = [[int(m[intermediate_board[r][c]].as_long()) for c in range(grid_size_x)] for r in range(grid_size_y)]
order_grid = [[int(m[order[r][c]].as_long()) for c in range(grid_size_x)] for r in range(grid_size_y)]
# print ("Init:")
# print_grid(i_grid)
# print ("Target:")
# print_grid(target_grid)
# print ("Goal:")
# print_grid(g_grid)
# print ("Order:")
# print_grid(order_grid)
# for x in range(grid_size_x):
# for y in range (grid_size_y):
# for (xp, yp) in adjacent[(x, y)]:
# if m[supporter_variables[(x, y, xp, yp)]]:
# print ((x, y), " is supported by ", (xp, yp))
# exit()
depot_loc = get_location(*depots[0])
plan = []
while i_grid != target_grid:
# Pick lowest position that is different. In case of tie, pick the one highest in order
different_positions = [(x, y) for x in range(grid_size_x) for y in range (grid_size_y) if i_grid[y][x] < target_grid[y][x] if accessible(i_grid, x, y, True)]
if not different_positions:
print ("Error: I cannot place the next position")
print_grid(i_grid)
print ()
print_grid(target_grid)
exit()
(x, y) = min(different_positions, key=lambda p : (i_grid[p[1]][p[0]], -order_grid[p[1]][p[0]]))
plan.append("(create-block {})".format(depot_loc))
path = get_shortest_path(i_grid, depots[0], (x, y), True, order_grid)
if not path:
return None
prev_loc = path[0]
for loc in path[1:-1]:
plan.append(move(i_grid, prev_loc, loc))
prev_loc = loc
plan.append(place_block(i_grid, path[-2], path[-1]))
for loc in path[::-1][2:]:
plan.append(move(i_grid, prev_loc, loc))
prev_loc = loc
i_grid[y][x] += 1
while i_grid != g_grid:
# Pick highest position that is different
different_positions = [(x, y) for x in range(grid_size_x) for y in range (grid_size_y) if i_grid[y][x] != g_grid[y][x] if accessible(i_grid, x, y, False)]
if not different_positions:
print ("Error: I cannot remove a block from the next position")
print_grid(i_grid)
print ()
print_grid(g_grid)
exit()
(x, y) = max(different_positions, key=lambda p : (i_grid[p[1]][p[0]], -order_grid[p[1]][p[0]]))
# print("Current grid")
# print_grid(i_grid)
# print("Goal grid")
# print_grid(g_grid)
# print("Candidates: ", different_positions)
# print ("Remove", (x, y))
path = get_shortest_path(i_grid, depots[0], (x, y), False, order_grid)
if not path:
return None
prev_loc = path[0]
for loc in path[1:-1]:
plan.append(move(i_grid, prev_loc, loc))
prev_loc = loc
plan.append(remove_block(i_grid, path[-2], path[-1]))
for loc in path[::-1][2:]:
plan.append(move(i_grid, prev_loc, loc))
prev_loc = loc
i_grid[y][x] -= 1
plan.append("(destroy-block {})".format(depot_loc))
while plan[-1].startswith("(move"):
plan.pop()
return (plan)