def TestSizeReducedAfterExtractMin(self):
input = [6, 1, 4, 5, 3, 2]
h = Heap()
for num in input:
h.insert(num)
initial_size = h.size
self.assertEqual(initial_size, len(h.a))
h.extract_min()
self.assertEqual(initial_size - 1, h.size)
def TestBuildMinHeap(self):
input = [random.randrange(100) for _ in range(100)]
h = Heap(input)
sorted_input = sorted(input)
for i in range(len(input)):
self.assertEqual(h.peek_min(), sorted_input[i])
self.assertEqual(h.extract_min(), sorted_input[i])
def TestMinHeapWithTuples(self):
input = [(random.randrange(100), "Hullo!") for _ in range(100)]
h = Heap(key=lambda x: x[0])
for num in input:
h.insert(num)
sorted_input = sorted(input)
for i in range(len(input)):
self.assertEqual(h.extract_min(), sorted_input[i])
def TestMinHeapWithRandomInput(self):
input = [random.randrange(100) for _ in range(100)]
h = Heap()
for num in input:
h.insert(num)
sorted_input = sorted(input)
for i in range(len(input)):
self.assertEqual(h.extract_min(), sorted_input[i])
def calculate_medians_with_heaps(numbers):
"""Calculate the sum of all 10,000 medians, modulo 10000"""
max_heap = MaxHeap() # For storing the smaller half of numbers
min_heap = MinHeap() # For storing the larger half of numbers
medians = []
for number in numbers:
if max_heap.peek_max() is None or max_heap.peek_max() > number:
max_heap.insert(number)
if max_heap.size > min_heap.size + 1:
min_heap.insert(max_heap.extract_max())
else:
min_heap.insert(number)
if min_heap.size > max_heap.size + 1:
max_heap.insert(min_heap.extract_min())
if max_heap.size >= min_heap.size:
medians.append(max_heap.peek_max())
else:
medians.append(min_heap.peek_min())
return medians
def TestMinHeapProperty(self):
input = [6, 1, 4, 5, 3, 2]
h = Heap()
for num in input:
h.insert(num)
self.assertEqual(h.extract_min(), 1)