基础算法概念:
时间复杂度
时间复杂度是从其增速的角度度量的,
时间复杂度一般用大O法表示。
递归
递归指的是调用自己的函数。
如果使用循环,程序性能可能更高;
如果使用递归,程序可能更容易理解。
基线条件:函数不再调用自己的条件,
递归条件:函数调用自己的条件。
二分法查找(递归)(时间复杂度O(logn)):
def binary_search(arr, key):
left = 0
right = len(arr) - 1
while right >= left:
mid = (left + right)/2
if key > arr[mid]:
left = mid + 1
elif key < arr[mid]:
right = mid - 1
else:
return mid
return -1
a = [1, 2, 3, 4, 5, 6, 7, 8, 9]
print binary_search(a, 11)
选择排序(时间复杂度O(n2)):
def findSmallest(arr): smallest = arr[0] # 储存最小的直 smallest_index = 0 # 储存最小元素的索引 for i in range(1, len(arr)): if arr[i] < smallest: smallest = arr[i] smallest_index = i return smallest_index def selectionSort(arr): # 对数组进行排序 newArr = [] for i in range(len(arr)): smallest = findSmallest(arr) # 找出数组中最小的数加入新数组 newArr.append(arr.pop(smallest)) return newArr print selectionSort([5, 3, 6, 2, 10])
快速排序(递归)(时间复杂度O(nlogn)):
def quicksort(array): if len(array) < 2: return array # 基线条件:为空或只包含一个元素的数组有序 else: pivot = array[0] # 递归条件 lesser = [i for i in array[1:] if i <= pivot] # 所有小于等于基准值的元素组成数组 greater = [i for i in array[1:] if i > pivot] # 所有大于基准值的元素组成数组 return quicksort(lesser) + [pivot] + quicksort(greater) print(quicksort([10, 5, 2, 3]))
快速排序(非递归):
# -*- coding:utf-8 -*- from collections import deque def quick_sort(arr): deq = deque([0, len(arr) - 1]) while deq: low = deq.popleft() l = low high = deq.popleft() h = high pivot = arr[low] while high > low: while high > low and arr[high] > pivot: high = high - 1 arr[high], arr[low] = arr[low], arr[high] while high > low and arr[low] < pivot: low = low + 1 arr[high], arr[low] = arr[low], arr[high] arr[high] = pivot m = high if m != l: deq.append(l) deq.append(m - 1) if m != h: deq.append(m + 1) deq.append(h) return arr print quick_sort([24, 2, 3, 23, 4, 7, 5])
冒泡排序:
def bubblesort(array): for i in range(len(array)): for j in range(len(array)-1-i): if array[j] < array[j+1]: array[j], array[j+1] = array[j+1], array[j] p = [1, 7, 9, 2, 3, 4, 5, 5] bubblesort(p) print p
归并排序:
def merge(arr1, arr2): arr = [] while len(arr1) != 0 and len(arr2) != 0: if arr1[0] > arr2[0]: arr.append(arr1.pop(0)) else: arr.append(arr2.pop(0)) return arr + arr1 + arr2 def mergeSort(array): if len(array) < 2: return array mid = len(array) / 2 left = mergeSort(array[:mid]) right = mergeSort(array[mid:]) return merge(left, right) c = [2, 6, 4, 0, 8, 5, 3] print mergeSort(c)