Python实现二叉堆的方法

二叉堆是一种特殊的堆，二叉堆是完全二元树（二叉树）或者是近似完全二元树（二叉树）。二叉堆有两种：最大堆和最小堆。最大堆：父结点的键值总是大于或等于任何一个子节点的键值；最小堆：父结点的键值总是小于或等于任何一个子节点的键值。

from pythonds.trees.binheap import BinHeap

bh = BinHeap()
bh.insert(5)
bh.insert(7)
bh.insert(3)
bh.insert(11)

print(bh.delMin())

print(bh.delMin())

print(bh.delMin())

print(bh.delMin()) 

class BinHeap:
  def init(self):
    self.heapList = [0]
    self.currentSize = 0 

def percUp(self,i):
  while i // 2 > 0:
   if self.heapList[i] < self.heapList[i // 2]:
     tmp = self.heapList[i // 2]
     self.heapList[i // 2] = self.heapList[i]
     self.heapList[i] = tmp
   i = i // 2 

def insert(self,k):
  self.heapList.append(k)
  self.currentSize = self.currentSize + 1
  self.percUp(self.currentSize) 

def percDown(self,i):
  while (i * 2) <= self.currentSize:
    mc = self.minChild(i)
    if self.heapList[i] > self.heapList[mc]:
      tmp = self.heapList[i]
      self.heapList[i] = self.heapList[mc]
      self.heapList[mc] = tmp
    i = mc

def minChild(self,i):
  if i * 2 + 1 > self.currentSize:
    return i * 2
  else:
    if self.heapList[i*2] < self.heapList[i*2+1]:
      return i * 2
    else:
      return i * 2 + 1 

def delMin(self):
  retval = self.heapList[1]
  self.heapList[1] = self.heapList[self.currentSize]
  self.currentSize = self.currentSize - 1
  self.heapList.pop()
  self.percDown(1)
  return retval 

def buildHeap(self,alist):
  i = len(alist) // 2
  self.currentSize = len(alist)
  self.heapList = [0] + alist[:]
  while (i > 0):
    self.percDown(i)
    i = i - 1 

i = 2 [0, 9, 5, 6, 2, 3]
i = 1 [0, 9, 2, 6, 5, 3]
i = 0 [0, 2, 3, 6, 5, 9] 

def insert(self,k):
   self.heapList.append(k)
   self.currentSize = self.currentSize + 1
   self.percUp(self.currentSize)

  def percDown(self,i):
   while (i * 2) <= self.currentSize:
     mc = self.minChild(i)
     if self.heapList[i] > self.heapList[mc]:
       tmp = self.heapList[i]
       self.heapList[i] = self.heapList[mc]
       self.heapList[mc] = tmp
     i = mc

  def minChild(self,i):
   if i * 2 + 1 > self.currentSize:
     return i * 2
   else:
     if self.heapList[i*2] < self.heapList[i*2+1]:
       return i * 2
     else:
       return i * 2 + 1

  def delMin(self):
   retval = self.heapList[1]
   self.heapList[1] = self.heapList[self.currentSize]
   self.currentSize = self.currentSize - 1 

能在 O(n) 的开销下能生成二叉堆看起来有点不可思议，其证明超出了本书的范围。但是，要理解用 O(n) 的开销能生成堆的关键是因为 logn 因子基于树的高度。而对于 buildHeap 里的许多操作，树的高度比 logn 要小。

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