class RunningMedian:
def __init__(self):
self.left_max_heap = MaxHeap()
self.right_min_heap = MinHeap()
def stream_element(self, a):
left_len, right_len = self.left_max_heap.get_length(
), self.right_min_heap.get_length()
if left_len == right_len:
self.left_max_heap.push(a)
return
if left_len > right_len:
peek = self.left_max_heap.peek()
if a >= peek:
self.right_min_heap.push(a)
else:
popped = self.left_max_heap.pop()
self.left_max_heap.push(a)
self.right_min_heap.push(popped)
return
if left_len < right_len:
peek = self.right_min_heap.peek()
if a <= peek:
self.left_max_heap.push(a)
else:
popped = self.right_min_heap.pop()
self.right_min_heap.push(a)
self.left_max_heap.push(popped)
return
def get_current_median(self):
left_len, right_len = self.left_max_heap.get_length(
), self.right_min_heap.get_length()
if left_len == 0 and right_len == 0:
raise ("No element is streamed")
if left_len > right_len:
median = self.left_max_heap.peek()
return median
if right_len > left_len:
median = self.right_min_heap.peek()
return median
if left_len == right_len:
median = (self.left_max_heap.peek() +
self.right_min_heap.peek()) / 2.0
return median
def findMaxK(vals, k):
minHeap = MinHeap(k)
for n in vals:
if minHeap.get_size() < k:
minHeap.push(n)
elif minHeap.peek() < n:
minHeap.pop()
minHeap.push(n)
while minHeap.get_size() > 0:
print(minHeap.pop())
class PriorityQueue(object):
def __init__(self):
self._heap = MinHeap()
self._num_inserted = 0
def _gen_order(self):
self._num_inserted += 1
return self._num_inserted
def insert(self, prioritized_item):
prioritized_item._order = self. _gen_order()
self._heap.push(prioritized_item)
def pop(self):
return self._heap.pop()
def peek(self):
return self._heap.peek()
def __str__(self):
s = []
[s.append(str(item)) for item in self._heap._list]
return "".join(s)