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python计算最小优先级队列代码分享
摘要:复制代码代码如下:#-*-coding:utf-8-*-classHeap(object):@classmethoddefparent(cl...

复制代码 代码如下:

# -*- coding: utf-8 -*-

class Heap(object):

@classmethod

def parent(cls, i):

"""父结点下标"""

return int((i - 1) >> 1);

@classmethod

def left(cls, i):

"""左儿子下标"""

return (i << 1) + 1;

@classmethod

def right(cls, i):

"""右儿子下标"""

return (i << 1) + 2;

class MinPriorityQueue(list, Heap):

@classmethod

def min_heapify(cls, A, i, heap_size):

"""最小堆化A[i]为根的子树"""

l, r = cls.left(i), cls.right(i)

if l < heap_size and A[l] < A[i]:

least = l

else:

least = i

if r < heap_size and A[r] < A[least]:

least = r

if least != i:

A[i], A[least] = A[least], A[i]

cls.min_heapify(A, least, heap_size)

def minimum(self):

"""返回最小元素,伪码如下:

HEAP-MINIMUM(A)

1 return A[1]

T(n) = O(1)

"""

return self[0]

def extract_min(self):

"""去除并返回最小元素,伪码如下:

HEAP-EXTRACT-MIN(A)

1 if heap-size[A] < 1

2 then error "heap underflow"

3 min ← A[1]

4 A[1] ← A[heap-size[A]] // 尾元素放到第一位

5 heap-size[A] ← heap-size[A] - 1 // 减小heap-size[A]

6 MIN-HEAPIFY(A, 1) // 保持最小堆性质

7 return min

T(n) = θ(lgn)

"""

heap_size = len(self)

assert heap_size > 0, "heap underflow"

val = self[0]

tail = heap_size - 1

self[0] = self[tail]

self.min_heapify(self, 0, tail)

self.pop(tail)

return val

def decrease_key(self, i, key):

"""将i处的值减少到key,伪码如下:

HEAP-DECREASE-KEY(A, i, key)

1 if key > A[i]

2 then error "new key is larger than current key"

3 A[i] ← key

4 while i > 1 and A[PARENT(i)] > A[i] // 不是根结点且父结点更大时

5 do exchange A[i] ↔ A[PARENT(i)] // 交换两元素

6 i ← PARENT(i) // 指向父结点位置

T(n) = θ(lgn)

"""

val = self[i]

assert key <= val, "new key is larger than current key"

self[i] = key

parent = self.parent

while i > 0 and self[parent(i)] > self[i]:

self[i], self[parent(i)] = self[parent(i)], self[i]

i = parent(i)

def insert(self, key):

"""将key插入A,伪码如下:

MIN-HEAP-INSERT(A, key)

1 heap-size[A] ← heap-size[A] + 1 // 对元素个数增加

2 A[heap-size[A]] ← +∞ // 初始新增加元素为+∞

3 HEAP-DECREASE-KEY(A, heap-size[A], key) // 将新增元素减少到key

T(n) = θ(lgn)

"""

self.append(float('inf'))

self.decrease_key(len(self) - 1, key)

if __name__ == '__main__':

import random

keys = range(10)

random.shuffle(keys)

print(keys)

queue = MinPriorityQueue() # 插入方式建最小堆

for i in keys:

queue.insert(i)

print(queue)

print('*' * 30)

for i in range(len(queue)):

val = i % 3

if val == 0:

val = queue.extract_min() # 去除并返回最小元素

elif val == 1:

val = queue.minimum() # 返回最小元素

else:

val = queue[1] - 10

queue.decrease_key(1, val) # queue[1]减少10

print(queue, val)

print([queue.extract_min() for i in range(len(queue))])

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