Python包含了用于min-堆的heapq模块,但我需要一个max堆。在Python中我应该使用什么来实现最大堆?
当前回答
我创建了一个名为heap_class的包,它实现了最大堆,还将各种堆函数包装到一个与列表兼容的环境中。
>>> from heap_class import Heap
>>> h = Heap([3, 1, 9, 20], max=True)
>>> h.pop()
20
>>> h.peek() # same as h[0]
9
>>> h.push(17) # or h.append(17)
>>> h[0] # same as h.peek()
17
>>> h[1] # inefficient, but works
9
从最大堆中获得最小堆。
>>> y = reversed(h)
>>> y.peek()
1
>>> y # repr is inefficient, but correct
Heap([1, 3, 9, 17], max=False)
>>> 9 in y
True
>>> y.raw() # underlying heap structure
[1, 3, 17, 9]
正如其他人所提到的,在max堆中处理字符串和复杂对象在heapq中是相当困难的,因为它们不同 否定的形式。heap_class实现简单:
>>> h = Heap(('aa', 4), ('aa', 5), ('zz', 2), ('zz', 1), max=True)
>>> h.pop()
('zz', 2)
支持自定义键,并与后续的推/追加和弹出一起工作:
>>> vals = [('Adam', 'Smith'), ('Zeta', 'Jones')]
>>> h = Heap(vals, key=lambda name: name[1])
>>> h.peek() # Jones comes before Smith
('Zeta', 'Jones')
>>> h.push(('Aaron', 'Allen'))
>>> h.peek()
('Aaron', 'Allen')
(实现是建立在heapq函数上的,所以它都是用C语言或C语言包装的,除了Python中max heap上的heappush和heapreplace)
其他回答
最简单的方法是反转键的值并使用heapq。例如,将1000.0转换为-1000.0,将5.0转换为-5.0。
我实现了一个最大堆版本的heapq,并将它提交给PyPI。(对heapq模块CPython代码的改动很小。)
https://pypi.python.org/pypi/heapq_max/
https://github.com/he-zhe/heapq_max
安装
pip install heapq_max
使用
dr:与heapq模块相同,只是所有函数都增加了' _max '。
heap_max = [] # creates an empty heap
heappush_max(heap_max, item) # pushes a new item on the heap
item = heappop_max(heap_max) # pops the largest item from the heap
item = heap_max[0] # largest item on the heap without popping it
heapify_max(x) # transforms list into a heap, in-place, in linear time
item = heapreplace_max(heap_max, item) # pops and returns largest item, and
# adds new item; the heap size is unchanged
解决方案是当你在堆中存储你的值时对其求反,或者像这样反转你的对象比较:
import heapq
class MaxHeapObj(object):
def __init__(self, val): self.val = val
def __lt__(self, other): return self.val > other.val
def __eq__(self, other): return self.val == other.val
def __str__(self): return str(self.val)
max-heap的例子:
maxh = []
heapq.heappush(maxh, MaxHeapObj(x))
x = maxh[0].val # fetch max value
x = heapq.heappop(maxh).val # pop max value
但是您必须记住包装和打开您的值,这需要知道您正在处理的是最小堆还是最大堆。
MinHeap, MaxHeap类
为MinHeap和MaxHeap对象添加类可以简化代码:
class MinHeap(object):
def __init__(self): self.h = []
def heappush(self, x): heapq.heappush(self.h, x)
def heappop(self): return heapq.heappop(self.h)
def __getitem__(self, i): return self.h[i]
def __len__(self): return len(self.h)
class MaxHeap(MinHeap):
def heappush(self, x): heapq.heappush(self.h, MaxHeapObj(x))
def heappop(self): return heapq.heappop(self.h).val
def __getitem__(self, i): return self.h[i].val
使用示例:
minh = MinHeap()
maxh = MaxHeap()
# add some values
minh.heappush(12)
maxh.heappush(12)
minh.heappush(4)
maxh.heappush(4)
# fetch "top" values
print(minh[0], maxh[0]) # "4 12"
# fetch and remove "top" values
print(minh.heappop(), maxh.heappop()) # "4 12"
如果你想用max heap得到最大的K元素,你可以做下面的技巧:
nums= [3,2,1,5,6,4]
k = 2 #k being the kth largest element you want to get
heapq.heapify(nums)
temp = heapq.nlargest(k, nums)
return temp[-1]
最好的方法:
from heapq import *
h = [5, 7, 9, 1, 3]
h_neg = [-i for i in h]
heapify(h_neg) # heapify
heappush(h_neg, -2) # push
print(-heappop(h_neg)) # pop
# 9
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