def backtrack(r, c):
global solved, board, rows, cols, boxes
N = 9
if board[r][c] == ".":
for d in range(1, 10):
if could_place(d, r, c):
fill_number(d, r, c)
if r == N - 1 and c == N - 1:
solved = True
elif c == N - 1:
if r == 6 and board[0][6] == '6' and board[0][7] == '5':
boards.print_board(board)
backtrack(r + 1, 0)
else:
if r == 8 and board[5][3] == '1' and board[0][7] == '5':
boards.print_board(board)
backtrack(r, c + 1)
if not solved:
erase_number(r, c)
else:
if r == N - 1 and c == N - 1:
solved = True
return
elif c == N - 1:
backtrack(r + 1, 0)
else:
backtrack(r, c + 1)
def run(self, max_eps=None, printstep=500):
"""Runs the simulator.
Generates possible moves and chooses one.
Loops until game_over or max_eps is exceeded.
"""
ep = 0
while ep != max_eps and self.get_options():
# generate options and features
scores = {x: self.control(*x) for x in self.options}
best_moves = tuple(k for k, v in scores.items()
if v == max(scores.values()))
orient, pos = self.sequence.choice(best_moves)
self.space.imprint_zoid(self.curr_z, orient=orient, pos=pos)
self.update_score()
self.new_zoids()
# the True parameter means full rows are counted *and* cleared
self.space.check_full(True)
if self.show_scores and ep % printstep == 0 and not printstep == -1:
print("\nEpisode: " + str(ep))
self.printscores()
ep += 1
if self.show_choice:
print_board(self.space, entire=True, show_full=True)
time.sleep(self.choice_step)
if self.show_result:
print("\n\nGame Over\nFinal scores:")
print("Episodes: " + str(ep))
self.printscores()
self.printcontroller()
print("\n")
return ({
"lines": self.lines,
"l1": self.l[1],
"l2": self.l[2],
"l3": self.l[3],
"l4": self.l[4],
"score": self.score,
"level": self.level,
"eps": ep
})
def solve_one():
global board, rows, cols, boxes, solved
n, N = 3, 9
rows = [[0] * N for _ in range(N)]
cols = [[0] * N for _ in range(N)]
boxes = [[0] * N for _ in range(N)]
for i in range(N):
for j in range(N):
if board[i][j] != '.':
fill_number(int(board[i][j]), i, j)
boards.print_board(board)
solved = False
backtrack(0, 0)
if solved:
print "Solved !!!"
boards.print_board(board)
else:
print "Unsatisfiable !!!"
def run(self, max_eps=None, printstep=500):
"""Runs the simulator.
Generates possible moves and chooses one.
Loops until game_over or max_eps is exceeded.
"""
ep = 0
while ep != max_eps and self.get_options():
# generate options and features
scores = {x: self.control(*x) for x in self.options}
best_moves = tuple(k for k, v in scores.items() if v == max(scores.values()))
orient, pos = self.sequence.choice(best_moves)
self.space.imprint_zoid(self.curr_z, orient=orient, pos=pos)
self.update_score()
self.new_zoids()
# the True parameter means full rows are counted *and* cleared
self.space.check_full(True)
if self.show_scores and ep % printstep == 0 and not printstep == -1:
print ("\nEpisode: " + str(ep))
self.printscores()
ep += 1
if self.show_choice:
print_board(self.space, entire=True, show_full=True)
time.sleep(self.choice_step)
if self.show_result:
print ("\n\nGame Over\nFinal scores:")
print ("Episodes: " + str(ep))
self.printscores()
self.printcontroller()
print ("\n")
return {
"lines": self.lines,
"l1": self.l[1],
"l2": self.l[2],
"l3": self.l[3],
"l4": self.l[4],
"score": self.score,
"level": self.level,
"eps": ep,
}
def solve_one():
global board
boards.print_board(board)
# 9x9 matrix of integer variables
X = [[Int("x_%s_%s" % (i + 1, j + 1)) for j in range(9)] for i in range(9)]
# each cell contains a value in {1, ..., 9}
cells_c = [
And(1 <= X[i][j], X[i][j] <= 9) for i in range(9) for j in range(9)
]
# each row contains a digit at most once
rows_c = [Distinct(X[i]) for i in range(9)]
# each column contains a digit at most once
cols_c = [Distinct([X[i][j] for i in range(9)]) for j in range(9)]
# each 3x3 square contains a digit at most once
sq_c = [
Distinct(
[X[3 * i0 + i][3 * j0 + j] for i in range(3) for j in range(3)])
for i0 in range(3) for j0 in range(3)
]
sudoku_c = cells_c + rows_c + cols_c + sq_c
board_c = [
If(board[i][j] == '.', True, X[i][j] == (ord(board[i][j]) - 0x30))
for i in range(9) for j in range(9)
]
s = Solver()
s.add(sudoku_c + board_c)
if s.check() == sat:
m = s.model()
# r = [ [m.evaluate(X[i][j]) for j in range(9)] for i in range(9) ]
#print_matrix(r)
for i in range(9):
for j in range(9):
board[i][j] = m.evaluate(X[i][j])
boards.print_board(board)
else:
print "failed to solve"