def solve_problem_2_4(puzzles):
print('\n\nSolving puzzles for problem 2.4 with AC-3 only...\n')
for p in puzzles:
puzzle = SudokuIO(p)
sudoku = CSP(puzzle.variables, puzzle.domains, puzzle.neighbors,
equal_constraint)
result = backtracking_search(puzzle.assignment, sudoku, mrv, mac,
False)
print('Puzzle {} result: {}'.format(p, result))
puzzle.output_puzzle(result)
print(
'\n\nSolving puzzles for problem 2.4 with all inference methods...\n')
for p in puzzles:
puzzle = SudokuIO(p)
sudoku = CSP(puzzle.variables, puzzle.domains, puzzle.neighbors,
equal_constraint)
result = backtracking_search(puzzle.assignment, sudoku, mrv, mac, True)
print('Puzzle {} result: {}'.format(p, result))
puzzle.output_puzzle(result)
def solve(variables, domains, neighbors, assignment, heuristic,
with_inferences, instrumented):
sudoku = CSP(variables, domains, neighbors, equal_constraint)
if with_inferences:
# problem 2.4
return backtracking_search(assignment, sudoku, heuristic, mac)
elif instrumented:
# problem 2.3
return instrumented_recursive_backtracking(assignment, sudoku,
heuristic)
else:
# problem 2.2
return recursive_backtracking_search(assignment, sudoku, heuristic)
def search(sudoku, useAc3=False):
if useAc3 is False:
return backtracking_search(sudoku, var_selector_no_ac3)
else:
variables = set()
for i in range(len(sudoku)):
for j in range(len(sudoku[i])):
if sudoku[i][j] == 0:
variables.add((i, j))
domainSetMat = calculateDomainSetMat(sudoku)
check = ac3(sudoku, variables, domainSetMat)
if check is False:
return None
return backtracking_search_memory(sudoku, var_selector_ac3, domainSetMat, variables)
def search(sudoku):
return backtracking_search(sudoku, var_selector, True)
tests_dir = 'data/'
tests_patterns = r'level_32_test_03_[0-9]+.*\.txt', r'level_32_test_04_[0-9]+.*\.txt'
files = [
f for f in os.listdir(tests_dir)
if any([re.match(pat, f) for pat in tests_patterns])
]
print(files)
times = 1
for filename in files:
for implementation in (
'csp_tuple', ): # 'csp_list', 'csp_bitstring', 'csp_number'):
csp_data = load_csp(tests_dir + filename)
zero = time.process_time()
for _ in range(times):
solution = backtracking.backtracking_search(
csp_data, implementation)
elapsed = time.process_time() - zero
print('{} backtracking_search({}): {}'.format(filename, implementation,
elapsed / times))
if solution:
for line in solution:
# print(('{:0' + str(w) + 'b}').format(line).replace('1', '8').replace('0', ' '))
# print(line.replace('1', '8').replace('0', ' '))
print(line)
pass
else:
print('NOT FOUND')
# zero = time.process_time()
# for _ in range(times):
# solution = iterimprov.iterative_improvement(csp_data, implementation)
# elapsed = time.process_time() - zero