def on(self, grid: Grid) -> None:
if self.starting_cell is None:
self.starting_cell = grid.random_cell()
if not is_cell(self.starting_cell) or self.starting_cell not in grid:
ValueError(
"Starting point of the algorithm must be a valid cell in the grid"
)
# We'll use the list as a stack to do very easily any backtracking
walked_path = []
walked_path.append(self.starting_cell)
while len(walked_path) > 0:
current_cell = walked_path[-1]
unvisited_neighbors = [
neighbor for neighbor in current_cell.neighbors
if len(neighbor.links) == 0
]
if len(unvisited_neighbors) == 0:
walked_path.pop()
else:
neighbor = choice(unvisited_neighbors)
current_cell += neighbor
walked_path.append(neighbor)
def test_random_cell() -> None:
grid = Grid(2, 2)
for _ in range(100):
assert grid.random_cell() in [
Cell(0, 0), Cell(0, 1),
Cell(1, 0), Cell(1, 1)
]
def on(self, grid: Grid) -> None:
current_cell = grid.random_cell()
unvisited_count = grid.size - 1
while unvisited_count > 0:
neighbor = current_cell.random_neighbour()
if neighbor is None:
raise ValueError("Aldous-Broder algorithm needs all cells to have at least one neighbor")
if len(neighbor.links) == 0:
current_cell += neighbor
unvisited_count -= 1
current_cell = neighbor
def on(grid: Grid) -> Grid:
current_cell = grid.random_cell()
unvisited_count = grid.size - 1
while unvisited_count > 0:
neighbor = choice(current_cell.neighbors)
if neighbor is None:
raise ValueError(
"Aldous-Broder algorithm needs all cells to have at least one neighbor"
)
if len(neighbor.links) == 0:
current_cell.link(neighbor)
unvisited_count -= 1
current_cell = neighbor
return grid
def on(self, grid: Grid) -> None:
current_cell: Optional[Cell] = grid.random_cell()
while current_cell is not None:
unvisited_neighbors = [neighbor for neighbor in current_cell.neighbors if len(neighbor.links) == 0]
if len(unvisited_neighbors) > 0:
# as int as there are unvisited paths, walk them
neighbor = choice(unvisited_neighbors)
current_cell += neighbor
current_cell = neighbor
else:
# enter hunt mode, find first unvisited cell near any visited cell
current_cell = None
for cell in grid.each_cell():
visited_neighbors = [neighbor for neighbor in cell.neighbors if len(neighbor.links) > 0]
if len(cell.links) == 0 and len(visited_neighbors) > 0:
current_cell = cast(Cell, cell) # outside of Mypy it's a mere assignment
neighbor = choice(visited_neighbors)
current_cell += neighbor
break
def on(grid: Grid, starting_cell: Optional[Cell] = None) -> Grid:
if starting_cell is None:
starting_cell = grid.random_cell()
# We'll use the list as a stack to do very easily any backtracking
walked_path = []
walked_path.append(starting_cell)
while len(walked_path) > 0:
current_cell = walked_path[-1]
unvisited_neighbors = [
neighbor for neighbor in current_cell.neighbors
if len(neighbor.links) == 0
]
if len(unvisited_neighbors) == 0:
walked_path.pop()
else:
neighbor = choice(unvisited_neighbors)
current_cell.link(neighbor)
walked_path.append(neighbor)
return grid
def on(grid: Grid) -> Grid:
current_cell = grid.random_cell() # type: Optional[Cell]
while current_cell is not None:
unvisited_neighbors = \
[neighbor for neighbor in current_cell.neighbors if len(neighbor.links) == 0]
if len(unvisited_neighbors) > 0:
# as long as there are unvisited paths, walk them
neighbor = choice(unvisited_neighbors)
current_cell.link(neighbor)
current_cell = neighbor
else:
# enter hunt mode, find first unvisited cell near any visited cell
current_cell = None
for cell in grid.each_cell():
visited_neighbors = [neighbor for neighbor in cell.neighbors if len(neighbor.links) > 0]
if len(cell.links) == 0 and len(visited_neighbors) > 0:
current_cell = cast(Cell, cell)
neighbor = choice(visited_neighbors)
current_cell.link(neighbor)
break
return grid
