时间复杂度、枚举、模拟、递归、进制转换、前缀和、差分、离散化
1 时间复杂度
重要是看循环,一共运行了几次
1.1 简单代码看循环
#时间复杂度1
n = int(input())
for i in range(1,n+1):
for j in range(0,i):
pass
###时间复杂度:1+2+3+....+n=n(1+n)/2 所以时间复杂度是o(n^2)
#时间复杂度2
for i in range(1,n+1):
for j in range(0,n,i):
pass
###时间复杂度:n+ n/2+ n/3+ .....+n/n = nlog(n)
1.2 复杂代码
1.2.1 归并排序
通过不断地往回带入得出的:一共带入了多少次呢?
看n可以被多少个2整除就可以 个数为: ,则有个o(n)叠加在一起,所以复杂度为o(nlogn)
2 枚举
2.1 定义
通过逐个尝试,遍历所有的解
2.2 流程
2.3 例子
注意字符串再 in上的伟大应用!!!!
2.3.1 简单计算
a = input()
sum1,sum2=0,0
for s in a:
if s in "aeiou":
sum1 +=1
else:
sum2+=1
print(sum1)
print(sum2)
2.3.2 洁净数
问题描述:小明不喜欢数字2,包括数位上包含数字2 的数,如果没有2则称为洁净数
n = int(input())
ans = 0
for i in range(1,n+1):
if "2" not in str(i):
ans+=1
print(ans)
2.3.3 扫雷【初用矩阵哦】
问题描述:
#枚举
def input_list():
return list(map(int,input().split()))
n_m = input_list()
n = n_m[0]
m = n_m[1]
a = []
for i in range(n):
a.append(input_list())
b = [[0]*m for i in range(n)] #生成n行m列的矩阵!
# print(b)
#表示方向
dir = [(1,0),(0,1),(-1,0),(0,-1),(-1,-1),(-1,1),(-1,1),(1,1)] #一共8个方向
for i in range(0,n):
for j in range(0,m):
if a[i][j] == 1:
b[i][j]=9
else:
b[i][j]=0
for k in range(8):
x,y = i+dir[k][0],j+dir[k][1]
if 0<=x<n and 0<=y<m:
if a[x][y]==1:
b[i][j] +=1
print(b[i][j],end = ' ')
print()
2.3.4 容斥定理
容斥定理:
1到n中a的倍数有 n//a 个
1到n中b的倍数有 n//b 个
1到n中ab的倍数有 n//ab 个
那么1到n中是a或者b的倍数有n//a+n//b-n//ab 个
3 模拟
3.1 定义
3.2 例题
3.2.1 喝饮料
n = int(input())
ans = n
while True:
if n >=3:
ans += n//3
n = n//3+n%3
else:
break
print(ans)
3.2.2 像素模糊
问题描述:
像素在中间就是除以9,在别上就是除的数不定
def input_list():
return list(map(int,input().split()))
n,m = input_list()
b = [[0]*m for i in range(n)]
a = []
dir = [(0,-1),(0,1),(-1,0),(1,0),(-1,-1),(1,-1),(1,1),(-1,1)]
for i in range(n):
a.append(input_list())
for i in range(n):
for j in range(m):
count = 1
sum_= a[i][j]
for k in range(8):
x,y = i+dir[k][0],j+dir[k][1]
if 0<=x<n and 0<=y<m:
count += 1
sum_ += a[x][y]
b[i][j] = int(sum_/count)
print(b[i][j],end=' ')
print()
#或者这样输出!!!
# for i in b:
# print(' '.join(map(str,i)))
3.2.3 螺旋矩阵
用螺旋的方式填充矩阵!就是思考的那种形状
1 2 3 4
12 13 14 5
11 16 15 6
10 9 8 7
def input_list():
return list(map(int,input().split()))
n,m = input_list()
x,y = 0,0
value = 1
a=[[0]*m for i in range(n)]
a[x][y]=value
print(a)
while value < n*m:
while y+1 < m and a[x][y+1]==0:
y = y + 1
value += 1
a[x][y]=value
while x+1<n and a[x+1][y]==0:
x=x+1
value +=1
a[x][y]=value
while y-1>=0 and a[x][y-1] ==0:
y = y-1
value += 1
a[x][y]=value
while x-1>0 and a[x-1][y] == 0:
x = x-1
value += 1
a[x][y]= value
for i in a:
print(' '.join(map(str,i)))
3.2.4 对折矩阵
1 2 6 7
3 5 8 11
4 9 10 12
def input_list():
return list(map(int,input().split()))
n,m = input_list()
a = [[0]*m for i in range(n)]
value = 1
a[0][0]=1
y,x = 0,0 # n,m
while value < n*m:
if x+1 < m and a[y][x+1]==0:
value += 1
x=x+1
a[y][x]=value
while y+1<n and x-1>=0 and a[y+1][x-1]==0:
value+=1
y = y+1
x = x-1
a[y][x]=value
if y+1<n and a[y+1][x] ==0:
value +=1
y = y+1
a[y][x]=value
while y-1>=0 and x+1<m and a[y-1][x+1] == 0:
value +=1
y = y-1
x = x+1
a[y][x] = value
for i in a:
print(" ".join(map(str,i)))
4 递归
4.1 定义
4.2 汉诺塔问题
4.2.1 可以跳步的
(即可以从A直接到C)
def move(n,A,B,C):
#n个盘子从A移动到C,借助B
if n==0:
return
move(n-1,A,C,B)
print(A,"-->",C)
move(n-1,B,A,C)
move(3,"A","B","C")
4.2.2 不可以跳步
即只能相邻的移动,不能A直接到C
def move1(n,A,B,C):
if n==0:
return
move1(n-1,A,B,C)
print(A,"-->",B)
move1(n-1,C,B,A)
print(B,"-->",C)
move1(n-1,A,B,C)
move1(2,"A","B","C")
4.3 找自然数
只需要找到n前面可以加几个数 ,是相同的子问题!!
代码:
def f(n):
if n == 1:
return 1
ans = 1
for i in range(1,n//2 +1):
ans += f(i)
return ans
print(f(6))
# 6
# 16
# 26
# 126
# 36
# 136
4.4 快速排序和归并排序
见第一节中有哦
快速排序:找基准 时间复杂度0(nlogn)
def partition(a,left,right):
stand = a[left]
idx = left+1
for i in range(left+1,right+1):
if a[i]<stand:
a[idx],a[i]=a[i],a[idx]
idx +=1
a[idx-1],a[left]=a[left],a[idx-1]
#返回基准所在的位置
return idx-1
def quicksort(a,left,right):
if left == right:
return a
if left<right:
mix = partition(a,left,right)
quicksort(a,left,mix-1)
quicksort(a,mix+1,right)
return a
a = [3,4,5,6,2,1]
left = 0
right = 5
print(quicksort(a,left,right))
归并排序:
def merge(A,B):
C=[]
while len(A)!=0 and len(B)!=0:
if A[0]<=B[0]:
C.append(A.pop(0))
else:
C.append(B.pop(0))
C +=A
C+=B
return C
# A=[1,3,5]
# B=[2,4]
# print(merge(A,B))
def merge_sort(a):
if len(a)<2:
return a
mix = len(a)//2
left = merge_sort(a[0:mix])
right = merge_sort(a[mix:len(a)])
a = merge(left,right)
return a
a = [4,3 ,2,5,1]
print(merge_sort(a))
5 进制转换
5.1 基数和权
按权展开:
5.2 代码实现
5.2.1 K进制转换成10进制
int_to_char="0123456789ABCDEF"
char_to_int ={}
for idx,chr in enumerate(int_to_char):
char_to_int[chr] =idx
print(char_to_int)
# print(char_to_int["1"])
# x = "1234"
# x = x[::-1]
# print(x)
def K_to_Ten(k,x):
ans = 0
x = x[::-1] #把顺序颠倒了
for i in range(len(x)):
ans = ans + char_to_int[str(x[i])] * k**i
return ans
k = 8
x = "3506"
print(K_to_Ten(k,x))
5.2.2 十进制转任何进制
代码:
int_to_char="0123456789ABCDEF"
char_to_int ={}
for idx,chr in enumerate(int_to_char):
char_to_int[chr] =idx
def Ten_to_k(k,x):
ans = ""
while x !=0:
ans = ans + int_to_char[x%k]
x = x//k
return ans[::-1]
k=2
x=19
print(Ten_to_k(k,x))
5.2.3 任意进制之间的转换
以十进制作为桥梁
def k_k(m,n,x):
#m进制转n进制,数字是x现在
#第一步:m进制转10进制
int_to_char = '0123456789ABCDEF'
char_to_int = {}
for idx,char in enumerate(int_to_char):
char_to_int[char] = idx
x = str(x)[::-1]
y = 0
for i in range(len(x)):
y = y+char_to_int[str(x[i])]*m**i
#第二步:十进制转n进制
z = ""
while y!=0:
z = z+int_to_char[int(y)%n]
y = y//n
z = z[::-1]
return z
m = 2
n = 16
x = 10010
print(k_k(m,n,x))
6 一维前缀和(区间)
6.1 定义
前缀和的目的是:快速求出去区间之和!
6.2 代码实现前缀和
def get_presum(a):
n = len(a)
sum = [0]*n
sum[0] = a[0]
for i in range(1,n):
sum[i] = sum[i-1]+a[i]
return sum
print(get_presum([1,2,3,4,5]))
6.3 前缀和实现区间差
def get_sum(sum,l,r):
if l==0:
return sum[r]
else:
return sum[r] - sum[l-1]
a = [1,2,3,4,5]
sum = get_presum(a)
print(sum)
b = get_sum(sum,1,4)
print(b)
6.4 具体例题
6.4.1 例题1求k次方的和
注意题目中说的:"请对每一个查询输出一个答案,答案对10的9次方+7取模"的意思是:答案对10的9次方+7 取余数!!【NO!!!不是的】请看下面的文章!!!
编程语言中,取余和取模的区别到底是什么? - 知乎 (zhihu.com)
取余和取模在 都是正数的时候结果相同,但是到符号不同的时候会出现不同:
取余,遵循尽可能让商向0靠近的原则
取模,遵循尽可能让商向负无穷靠近的原则
原则的解释可见:负数取余mod_负数mod运算规则-CSDN博客
综上所述:蓝桥杯里出现取模的话:!!!你就这么写:
((sum[r]-sum[l-1])+mod)%mod
def input_list():
return list(map(int,input().split()))
mod =1000000007
def ger_presum(a):
n = len(a)
sum = [0]*n
sum[0]=a[0]
for i in range(1,n):
sum[i] = (sum[i-1]+ a[i])%mod
return sum
def get_sum(a,l,r):
if l==0:
return a[r]
else:
return ((a[r]-a[l-1])+mod)%mod
n,m = input_list()
a = input_list()
sum_list = []
for i in range(1,6):
tmp_a = [x**i for x in a]
sum_list.append(ger_presum(tmp_a))
for j in range(m):
l,r,k = input_list()
print(get_sum(sum_list[k-1],l-1,r-1))
6.4.2 平衡串
区间的统计都可以看作是前缀和!!!!当一个问题套三层循环的时候时间复杂度就太高了,容易不通过!
输出的最长平衡串的意思是:找到最长子串,所以基本的思想就是:遍历左端点再遍历右端点
def get_presum(a):
n = len(a)
sum = [0]*n
sum[0] = a[0]
for i in range(1,n):
sum[i] = sum[i-1]+a[i]
return sum
def get_sum(a,l,r):
if l==0:
return a[r]
else:
return a[r]-a[l-1]
s = input()
n = len(s)
a = []
for i in s:
if i=="L":
a.append(1)
else:
a.append(-1)
sum = get_presum(a)
ans = 0
for i in range(0,n):
for j in range(i,n):
if get_sum(sum,i,j) == 0:
ans = max(ans,j-i+1)
print(ans)
7 二维前缀和(矩阵)
7.1 定义
7.1.1 sum[i][j]之和
找递推式不能每一个都用两重迭代去求
7.1.2 (x1,y1)-(x2,y2)之和
7.2 代码实现
7.2.1 左上角全部
推荐使用方法2:在外围加上一行一列!
#方法1:使用原矩阵!
#输出一个二维矩阵
def output(a):
n = len(a)
for i in range(0,n):
print(" ".join(map(str,a[i][0:])))
def input_list():
return list(map(int,input().split()))
n,m = input_list()
a = [[0]*(m) for i in range(n)]
sum_ = [[0]*(m) for i in range(n)]
#输入一个二维数组
for i in range(0,n):
a[i] = input_list()
output(a,n)
for i in range(0,n):
for j in range(0,m):
sum_[0][0] = a[0][0]
if i==0 and j!=0:
sum_[i][j] = a[i][j]+sum_[i][j-1]
continue
if i!=0 and j==0:
sum_[i][j] = a[i][j]+sum_[i-1][j]
continue
sum_[i][j] = sum_[i][j-1]+sum_[i-1][j]+a[i][j]-sum_[i-1][j-1]
output(sum_,n)
#方法2 在外围扩充一行一列0
def output(a):
n = len(a)
for i in range(1,n):
print(" ".join(map(str,a[i][1:])))
def input_list():
return list(map(int,input().split()))
n,m = input_list()
a=[[0]*(m+1) for i in range(n+1)]
sum_ = [[0]*(m+1) for i in range(n+1)]
for i in range(1,n+1):
a[i] = [0]+input_list()
for i in range(1,n+1):
for j in range(1,m+1):
sum_[i][j] = sum_[i][j-1]+sum_[i-1][j] +a[i][j] -sum_[i-1][j-1]
output(a)
output(sum_)
#例题
7.2.2 任意子矩阵
#方法2 在外围扩充一行一列0
def output(a):
n = len(a)
for i in range(1,n):
print(" ".join(map(str,a[i][1:])))
def input_list():
return list(map(int,input().split()))
n,m = input_list()
a=[[0]*(m+1) for i in range(n+1)]
sum_ = [[0]*(m+1) for i in range(n+1)]
for i in range(1,n+1):
a[i] = [0]+input_list()
for i in range(1,n+1):
for j in range(1,m+1):
sum_[i][j] = sum_[i][j-1]+sum_[i-1][j] +a[i][j] -sum_[i-1][j-1]
output(a)
output(sum_)
print(sum_)
#
#任意子矩阵
x1,y1 =input_list()
x2,y2 =input_list()
sum1 = sum_[x2][y2] - sum_[x1-1][y2] - sum_[x2][y1-1] +sum_[x1-1][y1-1]
print(sum1)
7.3 例题
7.3.1 统计子矩阵
def output(a):
n = len(a)
for i in range(1,n):
print(" ".join(map(str,a[i][1:])))
def input_list():
return list(map(int,input().split()))
def get_a(n,m):
a = [[0] * (m + 1) for i in range(n + 1)]
for i in range(1,n+1):
a[i] = [0]+input_list()
return a
def get_presum(a,n,m):
sum_ = [[0]*(m+1) for i in range(n+1)]
for i in range(1,n+1):
for j in range(1,m+1):
sum_[i][j] = sum_[i][j-1]+sum_[i-1][j] +a[i][j] -sum_[i-1][j-1]
return sum_
#任意子矩阵
def get_sum(sum_,x1,y1,x2,y2):
sum1 = sum_[x2][y2] - sum_[x1-1][y2] - sum_[x2][y1-1] +sum_[x1-1][y1-1]
return sum1
#例题1
N,M,K= input_list()
a = get_a(N,M)
sum_ = get_presum(a,N,M)
ans = 0
for x1 in range(1,N+1):
for y1 in range(1,M+1):
for x2 in range(x1,N+1):
for y2 in range(y1,M+1):
sum1 = get_sum(sum_,x1,y1,x2,y2)
if sum1<=K:
ans +=1
print(ans)
8 差分
8.1 定义
差分数组是任意两个数字求差
很重要的一点是:!!!差分数组的前缀和等于原数组!!!
得到差分数组后,将原数组加上差分数组就是最后的结果!
8.2 例子
8.2.1 区间更新
def input_list():
return list(map(int,input().split()))
#注意这个数组是从1开始的!!!!意味着给定的下标和实际的下标相差1
while True:
try:
n,m = input_list()
# print(n,type(n))
# print(m)
a = input_list()
diff = [0]*(n+1)
diff[0] = a[0]
for i in range(1,n):
diff[i] = a[i] -a[i-1]
#给定的m个操作
for j in range(m):
# print("121312")
x,y,z = input_list()
x = x-1
y = y-1
diff[x] += z
diff[y+1] -=z
a[0] = diff[0]
for i in range(1,n):
a[i] = diff[i]+a[i-1]
print(' '.join(map(str,a)))
except:
break
9 二维差分数组
9.1 定义
在(x1,y1)到(x2,y2)这个矩阵里的元素都加上固定的值!哦
用上差分数组降低时间复杂度!
过程:
加上的3会把那一行:3那一个格后面的所有都加上3,所以用-3平衡掉影响!
找到差分数组后将原数组和它进行运算即可!
9.2 代码实现
##二维的
def input_list():
return list(map(int,input().split()))
def output(a):
n = len(a)
for i in range(1,n-1):
print(" ".join(map(str,a[i][1:m+1])))
n,m = input_list()
a = [[0]*(m+2) for i in range(n+2)]
# output(a)
for i in range(1,n+1):
a[i] = [0] +input_list() +[0]
diff =[[0]*(m+2) for i in range(n+2)]
# output(a)
for i in range(1,n+1):
for j in range(1,m+1):
diff[i][j] = a[i][j] - a[i-1][j] - a[i][j-1] +a[i-1][j-1]
# output(diff)
print("请输入x1,y1:")
x1,y1 = input_list()
print('请输入x2,y2:')
x2,y2 = input_list()
print("请输入需要增加的元素:")
k = int(input())
diff[x1][y1] +=k
diff[x1][y2+1] -=k
diff[x2+1][y1] -=k
diff[x2+1][y2+1] +=k
# output(diff)
for i in range(1,n+1):
for j in range(1,m+1):
a[i][j] =diff[i][j]+ a[i - 1][j]+a[i][j - 1]-a[i-1][j-1]
output(a)
10 离散化
10.1 定义(去重排序,返回下标)
10.2 算法步骤
10.3 代码
def Discrete(a):
#a是输入的列表#return是返回的结果
b = list(set(a))
b = sorted(b)
print(b)
value = list(range(0,len(b)))
dic = dict(zip(b,value))
ans = []
#对a中的每一个x返回b的下标
for x in a:
ans.append(dic[x])
return ans
a = list(map(int,input().split()))
print(Discrete(a))