def test_small_sudoku_problem():
matrix = load_problem("tests/files/small_sudoku.csv")
assert matrix.shape == (64, 64)
col_sums = np.sum(matrix, axis=0)
assert all(col_sums <= 4)
row_sums = np.sum(matrix, axis=1)
assert np.isin(row_sums, [0, 4]).all()
def test_solve_impossible_sudoku_problem():
matrix = load_problem("tests/files/impossible_sudoku.csv")
with pytest.raises(NoSolution):
get_exact_cover(matrix)
def test_solve_very_hard_sudoku_problem_2():
matrix = load_problem("tests/files/very_hard_sudoku_2.csv")
solution = get_exact_cover(matrix)
assert is_solution(solution, matrix)
def test_solve_medium_sudoku_problem():
matrix = load_problem("tests/files/medium_sudoku.csv")
solution = get_exact_cover(matrix)
assert is_solution(solution, matrix)
def test_basic_roundtrip():
_, filename = mkstemp()
array = create_numpy_array([[0, 1, 0], [1, 0, 1]])
save_problem(filename, array)
problem = load_problem(filename)
assert_array_equal(array, problem)
data = cover_data + dummy_data
shuffled_data = draw(permutations(data))
return np.array(shuffled_data, dtype=np.int32)
@composite
def array_with_trivial_solution(draw):
array = draw(exact_cover_problem())
height, width = array.shape
row = draw(integers(min_value=0, max_value=height - 1))
array[row] = 1
return array
large_problems_with_solution = one_of(
just(load_problem("tests/files/pentominos_chessboard.csv")), )
array_with_solution = one_of(
array_with_trivial_solution(),
array_with_exact_cover(),
large_problems_with_solution,
)
@example(np.array([[1, 1, 1]], dtype=np.int32))
@example(np.array([[1, 0, 0], [0, 1, 1]], dtype=np.int32))
@given(array_with_solution)
@pytest.mark.skipif(GLOBAL_CONFIG["SKIP_SLOW"], reason="Skipping slow tests")
def test_exact_cover_with_solution(array_data):
rowcount = len(array_data)
actual = get_exact_cover(array_data)
