def _balance(self):
while len(self.heap_high) - len(self.heap_low) > 1:
self.heap_low.append(heapq.heappop(self.heap_high))
heapq._siftdown_max(self.heap_low, 0, len(self.heap_low) - 1)
while len(self.heap_low) - len(self.heap_high) > 1:
heapq.heappush(self.heap_high, heapq.heappop(self.heap_low))
heapq._siftup_max(self.heap_low, 0)
def _kth_smallest(nums, k):
heap = []
for num in itertools.islice(nums, 0, k):
heap.append(num)
heapq._siftdown_max(heap, 0, len(heap) - 1)
for num in itertools.islice(nums, k, len(nums)):
if num <= heap[0]:
heapq._heappushpop_max(heap, num)
return heap[0]
def HeapDelete(A, i):
if (len(A) <= i):
raise Exception("Heap does not have ith element.")
# Exchange i with last element and trim the list
last = A[len(A) - 1]
A[i] = A[last]
A = A[:(len(A) - 1)]
if A[i] < last:
# Bubble up the ith element
heapq._siftdown_max(A, 0, i)
else:
# Bubble down the ith element
heapq._siftup_max_(A, i)
def rebalance_heaps(self):
'''
@pre: two heaps that differ by more than 1 in size
@post: two heaps that differ by only one in size, obtained by shuffling elements
'''
if self.minL - self.maxL > 1:
self.maxH.append(heapq.heappop(self.minH))
self.maxL += 1
self.minL += -1
heapq._siftdown_max(self.maxH, 0, self.maxL - 1)
elif self.maxL - self.minL > 1:
heapq.heappush(self.minH, heapq._heappop_max(self.maxH))
self.maxL += -1
self.minL += 1
assert abs(self.maxL - self.minL) <= 1, "Not balanced!"
def insert(h_low, h_high, m):
"""Insert the item m to the heap.
"""
# Push the m in the heap
if m < h_low[0]:
h_low.append(m)
heapq._siftdown_max(h_low, 0, len(h_low) - 1)
else:
heapq.heappush(h_high, m)
# Balance the two heaps
size_diff = len(h_low) - len(h_high)
if size_diff > 1:
item = heapq._heappop_max(h_low)
heapq.heappush(h_high, item)
elif size_diff < -1:
item = heapq.heappop(h_high)
h_low.append(item)
heapq._siftdown_max(h_low, 0, len(h_low) - 1)
def heap_push(self, val):
'''
@pre: two balanced heaps
@post: two heaps with val added in the right spot, balanced
:param val: the value to be added to the median heap
adds the value to the proper heap
'''
# If we're adding to the max heap
if self.maxL == 0 or val < self.maxH[0]:
self.maxH.append(val)
self.maxL += 1
heapq._siftdown_max(self.maxH, 0, self.maxL - 1)
# Min heap is simpler
else:
heapq.heappush(self.minH, val)
self.minL += 1
self.rebalance_heaps()
print(self.get_median())
def median(arr):
max_heap = []
min_heap = []
results = []
heapq.heappush(min_heap, arr[0])
results.append(arr[0])
for i in arr[1:]:
max_l = len(max_heap)
min_l = len(min_heap)
if max_l > min_l:
if i < max_heap[0]:
temp = max_heap[0]
heapq._heapreplace_max(max_heap, i)
min_heap.heappush(temp)
else:
heapq.heappush(min_heap, i)
results.append((max_heap[0] + min_heap[0]) / 2)
continue
elif max_l < min_l:
if i > min_heap[0]:
temp = min_heap[0]
heapq.heapreplace(min_heap, i)
max_heap.append(temp)
heapq._siftdown_max(max_heap, 0, max_l)
else:
max_heap.append(i)
heapq._siftdown_max(max_heap, 0, max_l)
results.append((max_heap[0] + min_heap[0]) / 2)
continue
else:
if i > min_heap[0]:
heapq.heappush(min_heap, i)
results.append(min_heap[0])
else:
max_heap.append(i)
heapq._siftdown_max(max_heap, 0, max_l)
results.append(max_heap[0])
return results
def heappush_max(heap, item):
heap.append(item)
heapq._siftdown_max(
heap, 0,
len(heap) -
1) #use the heapq sifting function to push the item to the heap
def maxheappush(heap, item):
"""Push item onto heap, maintaining the heap invariant."""
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap) - 1)
def heappush(heap, item):
heap.append(item)
minq._siftdown_max(heap, 0, len(heap) - 1)
def update_event(self, inp=-1):
self.set_output_val(0, heapq._siftdown_max(self.input(0), self.input(1), self.input(2)))
def _push_to_heap_low(self, num):
self.heap_low.append(num)
heapq._siftdown_max(self.heap_low, 0, len(self.heap_low) - 1)
def maxheappush(heap, item):
"""Push item onto heap, maintaining the heap invariant."""
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap)-1)
def _heappush_max(self, heap, item):
"""Maxheap version of a heappush."""
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap) - 1)
import heapq
lst = [3, 8, 5, 4, 6, 9, 7]
heapq._heapify_max(lst) # heapify for max heap
print(*lst)
heapq._heappop_max(lst) # max element popped and lst is re-heapified
print(*lst)
heapq._heapreplace_max(lst, 0) # replace the max element of the heap
print(*lst)
# to push into a max heap- is different
lst.append(1)
heapq._siftdown_max(
lst, 0,
len(lst) -
1) # heapq._siftdown_max(heap,startpos of heap,pos of inserted element)
print(*lst)
# also we can use heapq._siftup_max(heap,pos)
def median(_add=None, _remove=None):
result = None
max_l = len(max_heap)
min_l = len(min_heap)
if _add:
if not min_l:
heapq.heappush(min_heap, _add)
elif max_l > min_l:
if _add < max_heap[0]:
temp = max_heap[0]
heapq._heapreplace_max(max_heap, _add)
heapq.heappush(min_heap, temp)
else:
heapq.heappush(min_heap, _add)
elif max_l < min_l:
if _add > min_heap[0]:
temp = min_heap[0]
heapq.heapreplace(min_heap, _add)
max_heap.append(temp)
heapq._siftdown_max(max_heap, 0, max_l)
else:
max_heap.append(_add)
heapq._siftdown_max(max_heap, 0, max_l)
else:
if _add > min_heap[0]:
heapq.heappush(min_heap, _add)
else:
max_heap.append(_add)
heapq._siftdown_max(max_heap, 0, max_l)
max_l = len(max_heap)
min_l = len(min_heap)
if _remove:
if min_heap and _remove >= min_heap[0]:
indx = min_heap.index(_remove)
min_heap[indx] = min_heap[-1]
min_heap.pop()
if indx < len(min_heap):
heapq._siftup(min_heap, indx)
heapq._siftdown(min_heap, 0, indx)
elif max_heap and _remove <= max_heap[0]:
indx = max_heap.index(_remove)
max_heap[indx] = max_heap[-1]
max_heap.pop()
if indx < len(max_heap):
heapq._siftup_max(max_heap, indx)
heapq._siftdown_max(max_heap, 0, indx)
max_l = len(max_heap)
min_l = len(min_heap)
if max_l - min_l >= 2:
temp = max_heap[0]
heapq._heappop_max(max_heap)
heapq.heappush(min_heap, temp)
elif min_l - max_l >= 2:
temp = min_heap[0]
heapq.heappop(min_heap)
max_heap.append(temp)
heapq._siftdown_max(max_heap, 0, max_l)
min_l = len(min_heap)
max_l = len(max_heap)
if min_l == max_l:
result = (max_heap[0] + min_heap[0]) / 2
# print(f'debug: max_heap[0]: {max_heap[0]} min_heap[0]:{min_heap[0]}')
elif min_l > max_l:
result = min_heap[0]
else:
result = max_heap[0]
return result
def add(self, element):
self.heap.append(element)
heapq._siftdown_max(self.heap, 0, len(self.heap) - 1)
# TLE
from heapq import heappush, heappop, _heappop_max, _siftdown_max
s = 0
l = []
r = []
n, k = map(int, input().split())
k = 100 - k
for _ in range(n):
x = int(input())
if x == 0:
if len(l) == 0:
print(r[0])
else:
print(l[0])
else:
s += 1
if len(l) == 0 or x <= l[0]:
l.append(x)
_siftdown_max(l, 0, len(l) - 1)
if len(r) < s * k // 100:
heappush(r, _heappop_max(l))
else:
heappush(r, x)
if len(r) > s * k // 100:
l.append(heappop(r))
_siftdown_max(l, 0, len(l) - 1)
def maxpush(self, item):
self._data.append(item)
heapq._siftdown_max(self._data, 0, len(self._data) - 1)
import heapq # Define minHeap = [9, 3, 5, 1, 2] heapq.heapify(minHeap) maxHeap = [9, 3, 5, 1, 2] heapq._heapify_max(maxHeap) # Insertion heapq.heappush(minHeap, 10) # heapq doesn't have built in maxHeap .insert maxHeap.append(10) heapq._siftdown_max(maxHeap, 0, len(maxHeap) - 1) # Access smallest = minHeap[0] largest = maxHeap[0] # Deletion print(heapq.heappop(minHeap)) print(heapq._heappop_max(maxHeap))
def _heappush_max(h, item):
h.append(item)
_siftdown_max(h, 0,
len(h) - 1)
def push(self, item):
self._heap.append(item)
_siftdown_max(self._heap, 0, len(self._heap) - 1)
def max_heappush(heap, item):
heap.append(item)
hq._siftdown_max(heap, 0, len(heap)-1)
# TLE
from heapq import _heappop_max, _siftdown_max, _heapify_max
n = int(input())
h = list(map(int, input().split()))
h.append(0)
_heapify_max(h)
c = 0
while len(h) > 1:
a = h[0]
_heappop_max(h)
a -= h[0]
_heappop_max(h)
if a != 0:
c += a
h.append(a)
_siftdown_max(h, 0, len(h) - 1)
print(c)
import heapq li = [1, 5, 4, 7, 8, 9, 2, 3] heapq._heapify_max(li) print(li) print(heapq._heappop_max(li)) print(li) heapq._heapreplace_max(li, 0) print(li) #No Inbuilt Push Function. Implement via own as shown below li.append(6) heapq._siftdown_max(li, 0, len(li) - 1) print(li)
# -*- coding: utf-8 -*- """ Created on Sat Jun 6 19:28:44 2020 @author: cheerag.verma """ #max heap inbuilts function import heapq li = [10,5,4,3,22,9,31] heapq._heapify_max(li) # builds the max heap heapq._heappop_max(li) # pops the max element from the list heapq._heapreplace_max(li,0) # pops out the top element and replace it with 0 (element) and perform downheapify # insert element in the max heap li.append(20) heapq._siftdown_max(li,0,len(li)-1) #li,startposition,endposition heapq._heapreplace_max(li)
def push(self, item):
self.heap.append((self.key(item), item))
heapq._siftdown_max(self.heap, 0, len(self.heap) - 1)
def mheappush(heap, item):
heap.append(item)
_siftdown_max(heap, 0, len(heap) - 1)
def _heappush_max(heap, item):
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap)-1)
def _heappush_max(heap, item):
""" why is this not in heapq """
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap) - 1)
def _heappush_max(heap, item):
heap.append(item)
heapq._siftdown_max(heap, 0, len(heap) - 1)
def heappush_max(self,hql,item): hql.append(item) heapq._siftdown_max(hql,0,len(hql)-1) return
