def solution(self):
result = backtracking_search(self.int_csp)
sol = ""
for i in range(0, len(result)):
sol += self.variables[i] + ": " + self.domain[result[i]] + "\n"
print(sol)
def test_5():
print(
'Test 5: Map Coloring CSP with all heuristics and inferencing.----------------------------'
)
mapColoringProblem = MapColoringProblem()
print(mapColoringProblem)
solution = backtracking_search(mapColoringProblem, mrv=True, lcv=True)
print(solution)
def test_1():
print(
'Test 1: Map Coloring CSP with no heuristic or inferencing.----------------------------'
)
mapColoringProblem = MapColoringProblem()
print(mapColoringProblem)
solution = backtracking_search(mapColoringProblem)
print(solution)
def test_2():
print(
'Test 2: Map Coloring CSP with inferencing.----------------------------'
)
mapColoringProblem = MapColoringProblem()
print(mapColoringProblem)
solution = backtracking_search(mapColoringProblem, mac=True)
print(solution)
def test_1():
print(
'Test 1: Temporal CSP with no heuristic or inferencing.----------------------------'
)
tcsp = TemporalCSP()
#print(tcsp)
solution = backtracking_search(tcsp)
print(solution)
def test_6():
print(
'Test 6: Circuit Board CSP with all heuristics and inferencing togther. ----------------'
)
csp = CircuitBoardProblem(cb, [circuit_a, circuit_b, circuit_c, circuit_e])
#-- If you want to print the problem just uncomment below. There are lots of constraints tho so beware of the output.
#print(csp)
solution = backtracking_search(csp, mrv=True, lcv=True, mac=True)
print(solution)
def test_3():
print(
'Test 3: Circuit Board CSP with MAC-3 Inferencing.--------------------------------------'
)
csp = CircuitBoardProblem(cb, [circuit_a, circuit_b, circuit_c, circuit_e])
#-- If you want to print the problem just uncomment below. There are lots of constraints tho so beware of the output.
#print(csp)
solution = backtracking_search(csp, mrv=False, lcv=False, mac=True)
print(solution)
def test_10():
big_board = CircuitBoard(10, 6)
print(
'Test 10: Big Circuit Board CSP with all heuristics and inferencing.----------------------------'
)
csp = CircuitBoardProblem(big_board, [
circuit_a, circuit_b, circuit_c, circuit_e, circuit_f, circuit_g,
circuit_h, circuit_i
])
#-- If you want to print the problem just uncomment below. There are lots of constraints tho so beware of the output.
#print(csp)
solution = backtracking_search(csp, mrv=True, lcv=True, mac=True)
print(solution)
def solution(self):
result = backtracking_search(self.int_csp)
board = [["."] * self.board_n for _ in range(self.board_m)]
for piece in self.variables:
cover = self.piece_coverage(piece,
result[self.variables.index(piece)])
for pos in cover:
coordinates = self.convert_to_coordinates(pos)
board[int(coordinates[0])][int(
coordinates[1])] = piece.getChar()
str = "Solution Board: \n"
for r in range(len(board) - 1, -1, -1):
for c in range(len(board[0])):
str += board[r][c]
str += "\n"
print(str)
def test_4():
print('Test 4: Map Coloring CSP with LCV.----------------------------')
mapColoringProblem = MapColoringProblem()
print(mapColoringProblem)
solution = backtracking_search(mapColoringProblem, lcv=True)
print(solution)
def test_3():
print('Test 3: Map Coloring CSP with MRV.----------------------------')
mapColoringProblem = MapColoringProblem()
print(mapColoringProblem)
solution = backtracking_search(mapColoringProblem, mrv=True)
print(solution)
def test_4():
print('Test 4: Temporal CSP with LCV.----------------------------')
tcsp = TemporalCSP()
#print(tcsp)
solution = backtracking_search(tcsp, mac=False, mrv=False, lcv=True)
print(solution)
def test_2():
print('Test 2: Temporal CSP with inferencing.----------------------------')
tcsp = TemporalCSP()
#print(tcsp)
solution = backtracking_search(tcsp, mac=True, mrv=False, lcv=False)
print(solution)