def mainLoopmC():
while True:
state = None
state = read()['puzzle']
assignment = mostConstrainingSearch(state)
temp = assignAll(assignment, state) # the final solution as a 2d list
print('the answer is:')
printPuzzle(temp)
def mainLoop():
while True:
state = None
state = read()['puzzle']
assignment = backtracking(state)
temp = assignAll(assignment, state) # the final solution as a 2d list
print('the answer is:')
printPuzzle(temp)
def solve_puzzle():
while True:
puzzle=read()['puzzle']
result,num_nodes=arc_consistent(puzzle)
print()
if result == None:
print('no solution found')
else:
print('the answer is:')
printPuzzle(result)
print('Number of Nodes Visited: ' + str(num_nodes))
def investigate():
puzzle = read()['puzzle']
list1 = initialize()
for i in range(len(list1)):
t_initial = timeit.default_timer()
solution, list1[i]['numVisited'] = list1[i]['function'](puzzle)
list1[i]['time'] = timeit.default_timer() - t_initial
print('{} solves the puzzle'.format(list1[i]['name']))
print('{} nodes visited'.format(list1[i]['numVisited']))
print('the answer is:')
printPuzzle(solution)
for dict1 in list1:
time = dict1['time']
name = dict1['name']
num = dict1['numVisited']
print('{} solved the puzzle in {} s. {} nodes were visited'.format(
name, time, num))
def backtrackingHelper(A,U,state):
current = assignAll(A, state)
printPuzzle(current)
if rule.solutionCheck(current): # all unassigned cell have been assigned
return A # and the number constraint is satisfied
elif len(U) > 0:
(i, j) = U.pop(0)
for option in ['b', '_']: # one coordinate has 2 possible assignment
B = A.copy()
B[(i, j)] = option
if ((i, j) not in rule.goodCells(current)) and option == 'b':
continue
temp = assignAll(B, state)
if not rule.numberConstrain(temp):
continue
# recursive call with new assignments B
result = backtrackingHelper(B, U.copy(), state)
if result is not None: # WE HAVE no solution in this case
return result
return None
def mostConstrainingSearchHelper(A, U, state):
current = assignDict(A, state) # the current state
printPuzzle(current)
if rule.solutionCheck(current): # all unassigned cell have been assigned
return A # and the number constraint is satisfied
elif len(U) > 0:
# get the most constraining coordinate
(i, j) = mostConstrainingCell(current, U)
U.remove((i, j))
for option in ['b', '_']: # one coordinate has 2 possible assignment
B = A.copy()
B[(i, j)] = option
if ((i, j) not in rule.goodCells(current)) and option == 'b':
continue
temp = assignDict(B, state)
if not rule.numberConstrain(temp):
continue
# recursive call with new assignments B
result = mostConstrainingSearchHelper(B, U.copy(), state)
if result is not None: # WE HAVE no solution in this case
return result
return None
