def decomposition_function(self, tiling: Tiling) -> Tuple[Tiling]:
if any(assumption in tiling.assumptions
for assumption in self.assumptions):
raise StrategyDoesNotApply(
"The assumption is already on the tiling.")
return (tiling.add_assumptions(self.assumptions), )
def reverse_fusion_rules():
t = Tiling(
obstructions=(
GriddedPerm((0, 1, 2), ((1, 0), (1, 0), (1, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (1, 0), (2, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (1, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (1, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (2, 0), (2, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (2, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (2, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (3, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (3, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((1, 0), (4, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (2, 0), (2, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (2, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (2, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (3, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (3, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((2, 0), (4, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((3, 0), (3, 0), (3, 0))),
GriddedPerm((0, 1, 2), ((3, 0), (3, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((3, 0), (4, 0), (4, 0))),
GriddedPerm((0, 1, 2), ((4, 0), (4, 0), (4, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (0, 0), (0, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (0, 0), (1, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (0, 0), (2, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (0, 0), (3, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (0, 0), (4, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (1, 0), (1, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (1, 0), (2, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (1, 0), (3, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (1, 0), (4, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (2, 0), (2, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (2, 0), (3, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (2, 0), (4, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (3, 0), (3, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (3, 0), (4, 0))),
GriddedPerm((0, 1, 2, 3), ((0, 0), (0, 0), (4, 0), (4, 0))),
),
requirements=(),
assumptions=(),
)
left_overlap = TrackingAssumption.from_cells([(0, 0), (1, 0)])
left = TrackingAssumption.from_cells([(1, 0)])
right = TrackingAssumption.from_cells([(2, 0)])
right_overlap = TrackingAssumption.from_cells([(2, 0), (3, 0)])
# Only track left of the fuse region
t1 = t.add_assumptions([left_overlap, right_overlap, left])
yield FusionStrategy(col_idx=1, tracked=True)(t1).to_reverse_rule(0)
# Only track right of the fuse region
t2 = t.add_assumptions([left_overlap, right_overlap, right])
yield FusionStrategy(col_idx=1, tracked=True)(t2).to_reverse_rule(0)
# Only track the bottom of the fuse region
yield FusionStrategy(row_idx=1,
tracked=True)(t1.rotate270()).to_reverse_rule(0)
# Only track the top of the fuse region
yield FusionStrategy(row_idx=1,
tracked=True)(t2.rotate270()).to_reverse_rule(0)
# Track both side of the fuse region
t3 = t.add_assumptions([left_overlap, right_overlap, left, right])
yield FusionStrategy(col_idx=1, tracked=True)(t3).to_reverse_rule(0)
yield FusionStrategy(row_idx=1,
tracked=True)(t3.rotate270()).to_reverse_rule(0)
