def test_extract_min(self):
""" Makes sure that the heap produces min values and that
the heap property is preserved.
Given the following heap:
(4)
/ \
(4) (8)
/ \ / \
(9) (4) (12) (9)
/ \
(11) (13)
"""
data = [4, 4, 8, 9, 4, 12, 9, 11, 13]
h = Heap(data)
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data),
'should still hold the heap property')
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data),
'should still hold the heap property')
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data),
'should still hold the heap property')
def test_extract_min(self):
""" Makes sure that the heap produces min values and that
the heap property is preserved.
Given the following heap:
(4)
/ \
(4) (8)
/ \ / \
(9) (4) (12) (9)
/ \
(11) (13)
"""
data = [4, 4, 8, 9, 4, 12, 9, 11, 13]
h = Heap(data)
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data), 'should still hold the heap property')
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data), 'should still hold the heap property')
min_key = h.extract_min()
self.assertEqual(min_key, 4, 'should extract the min value')
self.assertTrue(Heap.is_heap(data), 'should still hold the heap property')
def test_problem_1(self):
""" You are given as input an unsorted array of n distinct numbers,
where n is a power of 2. Give an algorithm that identifies the
second-largest number in the array, and that uses at most
n+log2n−2 comparisons.
Solution: use a hash data structure.
"""
numbers = [5,1,2,5,1,2,3,54,6,7,1,3,3,5,6,2,3,4,56,6]
h = Heap()
for number in numbers:
h.insert(-number)
h.extract_min()
actual = -h.extract_min()
self.assertEqual(actual, 54, 'found the second largest number')
def test_problem_1(self):
""" You are given as input an unsorted array of n distinct numbers,
where n is a power of 2. Give an algorithm that identifies the
second-largest number in the array, and that uses at most
n+log2n−2 comparisons.
Solution: use a hash data structure.
"""
numbers = [
5, 1, 2, 5, 1, 2, 3, 54, 6, 7, 1, 3, 3, 5, 6, 2, 3, 4, 56, 6
]
h = Heap()
for number in numbers:
h.insert(-number)
h.extract_min()
actual = -h.extract_min()
self.assertEqual(actual, 54, 'found the second largest number')
