def test_min(self):
mh = MinHeap()
with self.assertRaises(IndexError):
mh.min()
mh.append(1)
self.assertEqual(1, mh.min())
self.assertEqual(1, mh.min())
mh.append(1)
self.assertEqual(1, mh.min())
mh.pop()
self.assertEqual(1, mh.min())
mh.pop()
with self.assertRaises(IndexError):
mh.min()
mh.append(3)
self.assertEqual(3, mh.min())
mh.append(1)
self.assertEqual(1, mh.min())
mh.pop()
self.assertEqual(3, mh.min())
class Median:
def __init__(self):
self.h_low = MaxHeap()
self.h_high = MinHeap()
def add_element(self, value):
if self.h_low.heap_size == 0 or value < self.h_low.max():
self.h_low.insert(value)
if self.h_low.heap_size - self.h_high.heap_size > 1:
self.h_high.insert(self.h_low.extract_max())
else:
self.h_high.insert(value)
if self.h_high.heap_size - self.h_low.heap_size > 1:
self.h_low.insert(self.h_high.extract_min())
def get_median(self):
if (self.h_low.heap_size + self.h_high.heap_size) % 2 == 0:
return self.h_low.max(), self.h_high.min()
else:
if self.h_low.heap_size > self.h_high.heap_size:
return self.h_low.max()
else:
return self.h_high.min()
def get_maxheap_elements(self):
return self.h_low.heap
def get_minheap_elements(self):
return self.h_high.heap
def dijkstra(graph, root):
vertices = graph.keys()
n = len(vertices)
# Initialize the priority queue
inf = float("inf")
pq = MinHeap([(v, inf) for v in graph.keys()])
pq.change_priority(root, 0)
# Other initializations
parent = collections.defaultdict(lambda: None)
selected = set()
cost = collections.defaultdict(lambda: inf)
cost[root] = 0
while len(selected) < n:
u = pq.min()
du = cost[u] = pq.get_priority(u)
selected.add(u)
pq.take_min()
for (v, w) in graph[u].items():
if v not in selected and pq.get_priority(v) > du + w:
pq.change_priority(v, du + w)
parent[v] = u
return cost, parent
def dijkstra(graph, root):
vertices = graph.keys()
n = len(vertices)
# Initialize the priority queue
inf = float("inf")
pq = MinHeap([(v, inf) for v in graph.keys()])
pq.change_priority(root, 0)
# Other initializations
parent = collections.defaultdict(lambda: None)
selected = set()
cost = collections.defaultdict(lambda: inf)
cost[root] = 0
while len(selected) < n:
u = pq.min()
du = cost[u] = pq.get_priority(u)
selected.add(u)
pq.take_min()
for (v, w) in graph[u].items():
if v not in selected and pq.get_priority(v) > du + w:
pq.change_priority(v, du + w)
parent[v] = u
return cost, parent
