def test_quantiles(self):
case_class = namedtuple('case_class', 'array subset_count key expected_res')
cases = (
case_class(array=[100], subset_count=1, key=None, expected_res=[100]),
case_class(array=[1, 3, 5, 4, 2, 7, 6], subset_count=3, key=None, expected_res=[2, 5, 7]),
case_class(array=[1, 3, 5, 4, 2, 7, 6], subset_count=4, key=None, expected_res=[2, 4, 5, 7]),
case_class(array=[1, 3, 5, 4, 2, 7, 6], subset_count=7, key=None, expected_res=[1, 2, 3, 4, 5, 6, 7]),
case_class(array=[8, 2, 1, 3, 7, 5, 4, 6], subset_count=1, key=None, expected_res=[8]),
case_class(array=[8, 2, 1, 3, 7, 5, 4, 6], subset_count=2, key=None, expected_res=[4, 8]),
case_class(array=[8, 2, 1, 3, 7, 5, 4, 6], subset_count=3, key=None, expected_res=[3, 5, 8]),
case_class(array=[8, 2, 1, 3, 7, 5, 4, 6], subset_count=3, key=lambda x: -x, expected_res=[6, 4, 1]),
case_class(array=[8, 2, 1, 3, 7, 5, 4, 6], subset_count=4, key=None, expected_res=[2, 4, 6, 8]),
)
for case in cases:
# print(case.array, case.subset_count)
res = calc_quantiles(case.array, case.subset_count, case.key)
self.assertEqual(case.expected_res, res)
for length in range(1, 100):
subset_count = randint(1, length)
array = [x * 2 for x in range(0, length)]
rand_permutate(array)
# print(array, subset_count)
res = calc_quantiles(array, subset_count)
# print(res)
self.assertEqual(subset_count, len(res))
if subset_count > 1:
diffs = []
for i in range(0, subset_count - 1):
self.assertEqual(0, res[i] % 2)
diffs.append(res[i + 1] - res[i])
min_diff, max_diff = min_max(diffs)
self.assertTrue(max_diff - min_diff <= 2)
self.assertEqual(array[length - 1], res[subset_count - 1])
def test_rand_insert_delete(self):
rbt = RBTree()
insertion_seq = list(range(1000))
rand_permutate(insertion_seq)
values = []
i = 0
while i < len(insertion_seq):
if len(values) > 0:
rand = uniform(0, 1)
else:
rand = 0
if rand > 0.5:
rand_index = randint(0, len(values) - 1)
value = values[rand_index]
# print("delete %d" % value)
values.pop(rand_index)
node = rb_search(rbt, value)
rb_pop(rbt, node)
else:
value = insertion_seq[i]
i += 1
# print("insert %d" % value)
values.append(value)
values.sort()
rb_insert(rbt, value)
rb_assert_properties(rbt)
node_count = rb_node_count(rbt, rbt.root)
self.assertEqual(len(values), node_count)
self.assertSequenceEqual(values, list(rb_iter(rbt)))
def test_rand_insert_delete(self):
avl = AVLTree()
insertion_seq = list(range(1000))
rand_permutate(insertion_seq)
values = []
i = 0
while i < len(insertion_seq):
if len(values) > 0:
rand = uniform(0, 1)
else:
rand = 0
if rand > 0.5:
rand_index = randint(0, len(values) - 1)
value = values[rand_index]
# print("delete %d" % value)
values.pop(rand_index)
avl_pop(avl, value)
else:
value = insertion_seq[i]
i += 1
# print("insert %d" % value)
values.append(value)
values.sort()
avl_insert(avl, value)
self._assert_avl_properties(avl)
# print(len(values))
self.assertSequenceEqual(values, list(bst_iter(avl)))
def test_selection(self):
case_class = namedtuple('case_class', 'array i key expected_res')
for select_method in (
rand_select,
select,
select_variant,
):
cases = (
case_class(array=[1], i=0, key=None, expected_res=1),
case_class(array=[3, 2, 1], i=0, key=None, expected_res=1),
case_class(array=[1, 3, 5, 4, 2, 7, 6],
i=4,
key=None,
expected_res=5),
case_class(array=[1, 3, 5, 4, 2, 7, 6],
i=2,
key=None,
expected_res=3),
case_class(array=[1, 3, 5, 4, 2, 7, 6],
i=6,
key=lambda x: -x,
expected_res=1),
case_class(array=[8, 3, 2, 4, 6, 9, 7, 5, 1],
i=0,
key=None,
expected_res=1),
case_class(array=[
16, 196, 64, 121, 144, 9, 36, 0, 49, 100, 4, 81, 169, 1, 25
],
i=4,
key=None,
expected_res=16),
case_class(array=[1, 16, 4, 9, 49, 100, 25, 36, 81, 64, 0],
i=0,
key=None,
expected_res=0),
)
for case in cases:
# print(case.array, case.i)
self.assertEqual(case.expected_res,
select_method(case.array, case.i, case.key))
for length in range(1, 100):
i = randint(0, length - 1)
array = [x * x for x in range(0, length)]
rand_permutate(array)
case = case_class(array=array,
i=i,
key=None,
expected_res=i * i)
# print(case.array, case.i)
self.assertEqual(case.expected_res,
select_method(case.array, case.i, case.key))
def test_rand_insertions(self):
avl = AVLTree()
insertion_seq = list(range(1, 129))
rand_permutate(insertion_seq)
cnt = 0
for i in insertion_seq:
avl_insert(avl, i)
self._assert_avl_properties(avl)
self.assertSequenceEqual(sorted(insertion_seq[:cnt + 1]), list(bst_iter(avl)))
cnt += 1
self.assertSequenceEqual(sorted(insertion_seq), list(bst_iter(avl)))
def test_heap_delete_rand(self):
from Common.common import rand_permutate
from random import randint
for i in range(100):
len = randint(10, 100)
array = list(range(1, len + 1))
rand_permutate(array)
build_max_heap(array, 0)
self.assertTrue(check_max_heap(array, 0, 0))
for j in range(len):
array_copy = list(array)
heap_delete(array_copy, j)
self.assertTrue(
check_max_heap(array_copy, 0, 0),
msg='Heap is not max %r. from %r deleting element at %d' %
(array_copy, array, j))
def test_two_smallest(self):
case_class = namedtuple('case_class',
'array offset length key min second_min')
cases = (
case_class(array=(1, 1),
offset=0,
length=None,
key=None,
min=1,
second_min=1),
case_class(array=(1, 2),
offset=0,
length=None,
key=lambda x: -x,
min=2,
second_min=1),
case_class(array=(2, 1),
offset=0,
length=None,
key=lambda x: -x,
min=2,
second_min=1),
case_class(array=(1, 3, 2),
offset=0,
length=None,
key=None,
min=1,
second_min=2),
case_class(array=(2, 3, 4, 5, 1),
offset=0,
length=None,
key=None,
min=1,
second_min=2),
case_class(array=(3, 8, 2, 5, 1, 7, 6, 4),
offset=0,
length=6,
key=None,
min=1,
second_min=2),
case_class(array=(3, 8, 2, 5, 1, 7, 6, 4),
offset=0,
length=None,
key=None,
min=1,
second_min=2),
case_class(array=(3, 8, 2, 5, 1, 7, 6, 4),
offset=0,
length=7,
key=None,
min=1,
second_min=2),
case_class(array=(2, 1, 3, 3, 2, 3, 1),
offset=0,
length=None,
key=None,
min=1,
second_min=1),
case_class(array=(1, 2, 3, 4, 5, 6, 7, 8, 9),
offset=0,
length=None,
key=None,
min=1,
second_min=2),
)
for case in cases:
self.assertEqual((case.min, case.second_min),
two_smallest(case.array, case.offset, case.length,
case.key))
for length in range(2, 129):
array = [x for x in range(1, length + 1)]
rand_permutate(array)
# print(array)
case = case_class(array=array,
offset=0,
length=None,
key=None,
min=1,
second_min=2)
self.assertEqual((case.min, case.second_min),
two_smallest(case.array, case.offset, case.length,
case.key))