def test_swap(self):
p0 = np.array([[4, 2, 7, 1, 0, 0, 0, 0,
8], [6, 8, 9, 2, 0, 7, 1, 3, 5],
[3, 5, 1, 0, 8, 9, 2, 4,
7], [0, 0, 0, 4, 6, 8, 5, 0, 9],
[5, 0, 0, 7, 9, 2, 0, 8,
1], [7, 0, 8, 5, 1, 0, 4, 2, 6],
[0, 1, 6, 8, 7, 4, 9, 5,
3], [0, 4, 0, 9, 0, 1, 7, 6, 2],
[9, 0, 5, 3, 2, 6, 8, 1, 4]])
desired_state = np.array([[2, 4, 7, 1, 0, 0, 0, 0, 8],
[6, 8, 9, 2, 0, 7, 1, 3, 5],
[3, 5, 1, 0, 8, 9, 2, 4, 7],
[0, 0, 0, 4, 6, 8, 5, 0, 9],
[5, 0, 0, 7, 9, 2, 0, 8, 1],
[7, 0, 8, 5, 1, 0, 4, 2, 6],
[0, 1, 6, 8, 7, 4, 9, 5, 3],
[0, 4, 0, 9, 0, 1, 7, 6, 2],
[9, 0, 5, 3, 2, 6, 8, 1, 4]])
s = Sudoku(p0)
sq1 = (0, 0)
sq2 = (0, 1)
new_state = s.swap(sq1, sq2)
np.testing.assert_array_equal(new_state, desired_state)
print("test_swap: passed")
def test_cost_function_optimal(self):
p0 = np.array([[1, 9, 8, 5, 2, 6, 3, 4,
7], [7, 2, 5, 3, 4, 1, 6, 9, 8],
[3, 4, 6, 9, 7, 8, 2, 1,
5], [9, 8, 1, 2, 5, 7, 4, 6, 3],
[5, 6, 4, 1, 3, 9, 8, 7,
2], [2, 3, 7, 6, 8, 4, 1, 5, 9],
[4, 7, 3, 8, 1, 5, 9, 2,
6], [8, 1, 9, 7, 6, 2, 5, 3, 4],
[6, 5, 2, 4, 9, 3, 7, 8, 1]])
s = Sudoku(p0)
cost = s.cost_function(s.state)
self.assertEqual(cost, 0)
print("test_cost_function_optimal: passed")
def test_no_global_conflicts(self):
p0 = np.array([[1, 9, 8, 5, 2, 6, 3, 4,
7], [7, 2, 5, 3, 4, 1, 6, 9, 8],
[3, 4, 6, 9, 7, 8, 2, 1,
5], [9, 8, 1, 2, 5, 7, 4, 6, 3],
[5, 6, 4, 1, 3, 9, 8, 7,
2], [2, 3, 7, 6, 8, 4, 1, 5, 9],
[4, 7, 3, 8, 1, 5, 9, 2,
6], [8, 1, 9, 7, 6, 2, 5, 3, 4],
[6, 5, 2, 4, 9, 3, 7, 8, 1]])
s = Sudoku(p0)
gc = s.global_conflicts(s.state)
self.assertEqual(gc, 0)
print("test_no_global_conflicts: passed")
def test_cost_function(self):
p0 = np.array([
[4, 2, 7, 1, 3, 4, 6, 9, 8], #1
[6, 8, 9, 2, 6, 7, 1, 3, 5], #1
[3, 5, 1, 5, 8, 9, 2, 4, 7], #1
[6, 1, 5, 4, 6, 8, 5, 3, 9], #2
[3, 4, 2, 7, 9, 2, 7, 8, 1], #2
[7, 9, 8, 5, 1, 3, 4, 2, 6], #0
[7, 1, 6, 8, 7, 4, 9, 5, 3], #1
[3, 4, 2, 9, 5, 1, 7, 6, 2], #1
[9, 8, 5, 3, 2, 6, 8, 1, 4]
]) #1
#4 3 2 1 1 1 1 1 0 24
s = Sudoku(p0)
cost = s.cost_function(s.state)
self.assertEqual(cost, 24)
print("test_cost_function: passed")
def test_global_conflicts(self):
p0 = np.array([
[4, 2, 7, 1, 3, 4, 6, 9, 8], #1
[6, 8, 9, 2, 6, 7, 1, 3, 5], #1
[3, 5, 1, 5, 8, 9, 2, 4, 7], #1
[6, 1, 5, 4, 6, 8, 5, 3, 9], #2
[3, 4, 2, 7, 9, 2, 7, 8, 1], #2
[7, 9, 8, 5, 1, 3, 4, 2, 6], #0
[7, 1, 6, 8, 7, 4, 9, 5, 3], #1
[3, 4, 2, 9, 5, 1, 7, 6, 2], #1
[9, 8, 5, 3, 2, 6, 8, 1, 4]
]) #1
#5 3 2 1 1 1 1 1 0 25
s = Sudoku(p0)
gc = s.global_conflicts(s.state)
self.assertEqual(gc, 25)
print("test_global_conflicts: passed")
def test_squares_combinations(self):
# possible combinations
# unit1 = 28, unit2 = 21, unit3 = 15
# unit4 = 10, unit5 = 6, unit6 = 3
# unit7 = 1, unit8 = 0, unit9 = 0
p0 = np.array([[4, 0, 0, 1, 0, 0, 0, 0,
8], [0, 0, 0, 2, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0,
7], [0, 0, 2, 4, 6, 8, 5, 0, 9],
[5, 0, 0, 0, 0, 2, 0, 8,
1], [7, 0, 8, 5, 0, 0, 4, 0, 6],
[6, 1, 0, 0, 7, 6, 6, 5,
3], [3, 4, 0, 9, 5, 1, 9, 7, 2],
[9, 2, 5, 3, 2, 4, 8, 1, 4]])
s = Sudoku(p0)
self.assertEqual(len(list(s.squares_combinations())), 84)
print("test_squares_combinations: passed")
def test_squares_combinations_reduced_conflicts(self):
# possible combinations
# [((0, 0), (2, 1)), ((0, 1), (2, 0)),
# ((0, 2), (2, 1)), ((1, 0), (2, 1)),
# ((1, 1), (2, 2)), ((1, 2), (2, 1)),
# ((0, 5), (1, 3))]
p0 = np.array([[1, 3, 4, 4, 6, 3, 2, 9,
8], [2, 6, 8, 5, 0, 0, 0, 0, 0],
[5, 7, 9, 0, 0, 0, 0, 0,
0], [6, 0, 0, 0, 0, 0, 0, 0, 0],
[9, 0, 0, 0, 0, 0, 0, 0,
0], [8, 0, 0, 0, 0, 0, 0, 0, 0],
[4, 0, 0, 0, 0, 0, 0, 0,
0], [2, 0, 0, 0, 0, 0, 0, 0, 0],
[9, 0, 0, 0, 0, 0, 0, 0, 0]])
s = Sudoku(p0)
s.fixed_cells = []
self.assertEqual(len(list(s.squares_combinations_reduced_conflicts())),
7)
print("test_squares_combinations_reduced_conflicts: passed")
def test_random_fill(self):
'''
Verifies if each unit contains the set from 1 to 9
after randomly filling the blank squares.
'''
p0 = np.array([[4, 0, 7, 1, 0, 0, 0, 0,
8], [0, 8, 9, 2, 0, 7, 1, 0, 5],
[3, 5, 1, 0, 8, 9, 0, 4,
7], [0, 0, 0, 4, 6, 8, 5, 0, 9],
[5, 0, 0, 7, 9, 2, 0, 8,
1], [7, 0, 8, 5, 1, 0, 4, 0, 6],
[0, 1, 0, 0, 7, 0, 0, 5,
3], [0, 4, 0, 9, 0, 1, 0, 0, 2],
[9, 0, 5, 3, 2, 0, 8, 1, 4]])
s = Sudoku(p0)
s.random_fill()
for i, j in ((x, y) for x in range(0, 9, 3) for y in range(0, 9, 3)):
current_unit = s.state[i // 3 * 3:i // 3 * 3 + 3,
j // 3 * 3:j // 3 * 3 + 3].ravel()
self.assertEqual(len(set(current_unit)), len(current_unit))
print("test_random_fill: passed")
x = []
y = []
data = []
heuristics_options = {
"hc": run_hill_climbing,
"hcr": run_hill_climbing_reduced,
"sa": run_simulated_annealing
}
for p in problems:
start = time.clock()
initial_state = shape(p)
s = Sudoku(initial_state)
s.random_fill()
final_state, steps, score = heuristics_options[args.heuristic](args, s)
x.append(steps)
y.append(score)
tclock = time.clock() - start
if args.verbose:
print("execution time:", tclock)
if args.heuristic == "sa":
data.append((p, args.heuristic, array2str(final_state.flatten()),
s.cost_function(final_state), len(steps), tclock))
else:
data.append((p, args.heuristic, array2str(final_state.flatten()),
score, steps, tclock))
def test_nb_worse_scenario_squares_combinations(self):
p0 = np.zeros((9, 9))
s = Sudoku(p0)
combinations = len(list(s.squares_combinations()))
self.assertEqual(combinations, 324)
print("test_nb_worse_scenario_squares_combinations: passed")