def feature_7(self, sudoku):
self.arc_consistency(sudoku, 10)
counts = dict()
for i in range(10):
counts[i] = 0
for i in range(9):
for j in range(9):
domain = sudoku.getLegalMoves(i, j)
for d in domain:
counts[d] += 1
maxvalue = 0
for key in counts.keys():
if key == 0:
continue
maxvalue = max(counts[key], maxvalue)
return maxvalue
def arc_consistency(self, sudoku, numRounds):
domains = dict()
for i in range(0, 9):
domains[i] = dict()
size_of_domain = 0
total_domains = list()
for round in range(numRounds):
for i in range(9):
for j in range(9):
domains[i][j] = sudoku.getLegalMoves(i, j)
size_of_domain += len(domains[i][j])
if len(domains[i][j]) == 1:
sudoku.setSquare(i, j, domains[i][j][0])
total_domains.append(size_of_domain)
size_of_domain = 0
return total_domains
def arc_consistency(self, sudoku, numRounds):
domains = dict()
for i in range(0, 9):
domains[i] = dict()
size_of_domain = 0
total_domains = list()
for round in range(numRounds):
for i in range(9):
for j in range(9):
domains[i][j] = sudoku.getLegalMoves(i, j)
size_of_domain += len(domains[i][j])
if len(domains[i][j]) == 1:
sudoku.setSquare(i, j, domains[i][j][0])
total_domains.append(size_of_domain)
size_of_domain = 0
return total_domains
def feature_7(self, sudoku):
self.arc_consistency(sudoku, 10)
counts = dict()
for i in range(10):
counts[i] = 0
for i in range(9):
for j in range(9):
domain = sudoku.getLegalMoves(i, j)
for d in domain:
counts[d] += 1
maxvalue = 0
for key in counts.keys():
if key == 0:
continue
maxvalue = max(counts[key], maxvalue)
return maxvalue
def isSolvableByAC(self, sudoku):
domains = dict()
for i in range(0, 9):
domains[i] = dict()
prev_domain = None
size_of_domain = 0
while True:
self.arcConsistencyCounter += 1
for i in range(9):
for j in range(9):
domains[i][j] = sudoku.getLegalMoves(i, j)
size_of_domain += len(domains[i][j])
if len(domains[i][j]) == 1:
sudoku.setSquare(i, j, domains[i][j][0])
if (prev_domain == domains):
return False
if (sudoku.isComplete()):
return True
prev_domain = domains
def isSolvableByAC(self, sudoku):
domains = dict()
for i in range(0, 9):
domains[i] = dict()
prev_domain = None
size_of_domain = 0
while True:
self.arcConsistencyCounter += 1
for i in range(9):
for j in range(9):
domains[i][j] = sudoku.getLegalMoves(i, j)
size_of_domain += len(domains[i][j])
if len(domains[i][j]) == 1:
sudoku.setSquare(i, j, domains[i][j][0])
if prev_domain == domains:
return False
if sudoku.isComplete():
return True
prev_domain = domains
def doBacktracking(self, sudoku, moveStack):
empties = sudoku.getEmptySquares()
if (len(empties) == 0):
self.backTrackingResult = sudoku
return True
else:
(i, j) = empties[0]
domain = sudoku.getLegalMoves(i, j)
moveStack.append(((i, j), sudoku.copy()))
for value in domain:
sudoku.setSquare(i, j, value)
self.backTrackingCounter += 1
if self.isSolvableByAC(sudoku):
self.backTrackingResult = sudoku
return True
if not sudoku.hasEmptyDomain():
if self.doBacktracking(sudoku, moveStack):
return True
sudoku = moveStack[-1][1].copy()
moveStack.pop()
return False
def doBacktracking(self, sudoku, moveStack):
empties = sudoku.getEmptySquares()
if len(empties) == 0:
self.backTrackingResult = sudoku
return True
else:
(i, j) = empties[0]
domain = sudoku.getLegalMoves(i, j)
moveStack.append(((i, j), sudoku.copy()))
for value in domain:
sudoku.setSquare(i, j, value)
self.backTrackingCounter += 1
if self.isSolvableByAC(sudoku):
self.backTrackingResult = sudoku
return True
if not sudoku.hasEmptyDomain():
if self.doBacktracking(sudoku, moveStack):
return True
sudoku = moveStack[-1][1].copy()
moveStack.pop()
return False
