def _test_common_sort(sort, *args, **kwargs):
random.seed(1000)
n = random.randint(10, 20)
arr = DynamicOneDimensionalArray(int, 0)
for _ in range(n):
arr.append(random.randint(1, 1000))
for _ in range(n // 3):
arr.delete(random.randint(0, n // 2))
expected_arr = [
686, 779, 102, 134, 362, 448, 480, 548, None, None, None, 228, 688,
247, 373, 696, None, None, None, None, None, None, None, None, None,
None, None, None, None, None, None
]
sort(arr, *args, **kwargs, start=2, end=10)
assert arr._data == expected_arr
sort(arr, *args, **kwargs)
expected_arr = [
102, 134, 228, 247, 362, 373, 448, 480, 548, 686, 688, 696, 779, None,
None, None, None, None, None, None, None, None, None, None, None, None,
None, None, None, None, None
]
assert arr._data == expected_arr
assert (arr._last_pos_filled, arr._num, arr._size) == (12, 13, 31)
n = random.randint(10, 20)
arr = OneDimensionalArray(int, n)
for i in range(n):
arr[i] = random.randint(1, 1000)
expected_arr = [42, 695, 147, 500, 768, 998, 473, 732, 728, 426, 709, 910]
sort(arr, *args, **kwargs, start=2, end=5)
assert arr._data == expected_arr
def test_merge_sort_parallel():
random.seed(1000)
n = random.randint(10, 20)
arr = DynamicOneDimensionalArray(int, 0)
for _ in range(n):
arr.append(random.randint(1, 1000))
for _ in range(n // 3):
arr.delete(random.randint(0, n // 2))
expected_arr = [
686, 779, 102, 134, 362, 448, 480, 548, 228, 688, 247, 373, 696, None,
None, None, None, None, None, None, None, None, None, None, None, None,
None
]
merge_sort_parallel(arr, 5, start=2, end=10)
assert arr._data == expected_arr
n = random.randint(10, 20)
arr = OneDimensionalArray(int, n)
for i in range(n):
arr[i] = random.randint(1, 1000)
expected_arr = [42, 695, 147, 500, 768, 998, 473, 732, 728, 426, 709, 910]
merge_sort_parallel(arr, 5, start=2, end=5)
assert arr._data == expected_arr
def _test_append(size):
data = [random.randint(-size, size) for _ in range(size)]
doda_cpp = DynamicOneDimensionalArray(int, 0, backend=Backend.CPP)
doda_python = DynamicOneDimensionalArray(int, 0)
python_list = []
cpp_backend, python_backend, list_time = (0, 0, 0)
for datum in data:
timer_cpp = timeit.Timer(functools.partial(doda_cpp.append, datum))
cpp_backend += min(timer_cpp.repeat(repeat, number))
timer_python = timeit.Timer(functools.partial(doda_python.append, datum))
python_backend += min(timer_python.repeat(repeat, number))
timer_list = timeit.Timer(functools.partial(python_list.append, datum))
list_time += min(timer_list.repeat(repeat, number))
assert cpp_backend < python_backend
assert cpp_backend/list_time < 1.5
def _test_delete(size):
data = [random.random() * 2 * size for _ in range(size)]
doda_cpp = DynamicOneDimensionalArray(float, data, backend=Backend.CPP)
doda_python = DynamicOneDimensionalArray(float, data)
python_list = [datum for datum in data]
list_indices = [i for i in range(size)]
random.seed(0)
random.shuffle(list_indices)
def _list_remove(obj, index):
del obj[index]
list_time = 0
for i in range(size):
idx = list_indices[i]
timer_list = timeit.Timer(functools.partial(_list_remove, python_list, idx))
list_time += min(timer_list.repeat(1, 1))
for j in range(i + 1, size):
if list_indices[j] > idx:
list_indices[j] -= 1
cpp_backend, python_backend = (0, 0)
while doda_cpp._num > 0:
indices = [i for i in range(doda_cpp._last_pos_filled + 1)]
random.shuffle(indices)
for idx in indices:
timer_cpp = timeit.Timer(functools.partial(doda_cpp.delete, idx))
cpp_backend += min(timer_cpp.repeat(1, 1))
timer_python = timeit.Timer(functools.partial(doda_python.delete, idx))
python_backend += min(timer_python.repeat(1, 1))
if doda_cpp._num == 0:
break
assert cpp_backend < python_backend
assert cpp_backend < list_time
def test_counting_sort():
random.seed(1000)
n = random.randint(10, 20)
arr = DynamicOneDimensionalArray(int, 0)
for _ in range(n):
arr.append(random.randint(1, 1000))
for _ in range(n//3):
arr.delete(random.randint(0, n//2))
expected_arr = [102, 134, 228, 247, 362, 373, 448,
480, 548, 686, 688, 696, 779]
assert counting_sort(arr)._data == expected_arr
