第一章 引论
观念:写出一个可以工作的程序并不够。如果这个程序在巨大的数据集上运行,那么运行时间就变成了重要的问题。
第二章 算法分析
2.4.3 最大子序列和问题的解
算法1 O(N^3)
le062@Ubuntu20120606102912:~/algorithm$ cat source2-4-3_1.c
#include <stdio.h>
#include <stdlib.h>
int MaxNum(int* number,int n);
int main(void)
{
int i,N,A[100000];
printf("Please input the Number!\n");
scanf("%d",&N);
srand((unsigned)time(NULL));
for(i=0;i<=N;i++)
{
A[i]=rand()%20001-10000;
//printf("\n%d",A[i]);
}
printf("%d\n",MaxNum(A,N));
return 0;
}
int MaxNum(int* number,int n)
{
int thissum,maxsum,i,j,k;
maxsum=0;
for(i=0;i<n;i++)
for(j=i;j<n;j++)
{
thissum=0;
for(k=i;k<=j;k++)
thissum+=*(number+k);
if(thissum>maxsum)
maxsum=thissum;
}
return maxsum;
}
le062@Ubuntu20120606102912:~/algorithm$ gcc -W source2-4-3_1.c -o source2-4-3_1
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
10
21250
real 0m0.880s
user 0m0.000s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
100
66205
real 0m1.281s
user 0m0.000s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
500
87528
real 0m1.738s
user 0m0.150s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
1000
119906
real 0m3.137s
user 0m0.870s
sys 0m0.060s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
2000
304389
real 0m9.127s
user 0m5.740s
sys 0m0.090s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_1
Please input the Number!
4000
722457
real 1m3.492s
user 0m44.890s
sys 0m0.800s
算法2 O(N^2)
le062@Ubuntu20120606102912:~/algorithm$ vi source2-4-3_2.c
#include <stdio.h>
#include <stdlib.h>
int MaxNum(int* number,int n);
int main(void)
{
int i,N,A[100000];
printf("Please input the Number!\n");
scanf("%d",&N);
srand((unsigned)time(NULL));
for(i=0;i<=N;i++)
{
A[i]=rand()%20001-10000;
//printf("\n%d",A[i]);
}
printf("%d\n",MaxNum(A,N));
return 0;
}
int MaxNum(int* number,int n)
{
int thissum,maxsum,i,j;
maxsum=0;
for(i=0;i<n;i++)
{
thissum=0;
for(j=i;j<n;j++)
{
thissum+=*(number+j);
if(thissum>maxsum)
maxsum=thissum;
}
}
return maxsum;
}
"source2-4-3_2.c" 36L, 533C written
le062@Ubuntu20120606102912:~/algorithm$ gcc -W source2-4-3_2.c -o source2-4-3_2
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_2
Please input the Number!
10
13510
real 0m0.960s
user 0m0.000s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_2
Please input the Number!
100
115320
real 0m1.340s
user 0m0.000s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_2
Please input the Number!
1000
197663
real 0m1.473s
user 0m0.000s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_2
Please input the Number!
10000
433957
real 0m2.423s
user 0m0.280s
sys 0m0.000s
le062@Ubuntu20120606102912:~/algorithm$ time ./source2-4-3_2
Please input the Number!
100000
1587627
real 0m42.028s
user 0m28.030s
sys 0m0.640s
算法3 O(N log N)
int max_sub_sum( int a[], int left, int right )
{
int max_left_sum, max_right_sum;
int max_left_border_sum, max_right_border_sum;
int left_border_sum, right_border_sum;
int center, i;
/*1*/ if ( left == right ) /* Base Case */
/*2*/ if( a[left] > 0 )
/*3*/ return a[left];
else
/*4*/ return 0;
/*5*/ center = (left + right )/2;
/*6*/ max_left_sum = max_sub_sum( a, left, center );
/*7*/ max_right_sum = max_sub_sum( a, center+1, right );
/*8*/ max_left_border_sum = 0; left_border_sum = 0;
/*9*/ for( i=center; i>=left; i-- )
{
/*10*/ left_border_sum += a[i];
/*11*/ if( left_border_sum > max_left_border_sum )
/*12*/ max_left_border_sum = left_border_sum;
}
/*13*/ max_right_border_sum = 0; right_border_sum = 0;
/*14*/ for( i=center+1; i<=right; i++ )
{
/*15*/ right_border_sum += a[i];
/*16*/ if( right_border_sum > max_right_border_sum )
/*17*/ max_right_border_sum = right_border_sum;
}
/*18*/ return max3( max_left_sum, max_right_sum,max_left_border_sum + max_right_border_sum );
}
int max_sub_sequence_sum( int a[], unsigned int n )
{
return max_sub_sum( a, 0, n-1 );
}
算法4 O(N)
int max_subsequence_sum( int a[], unsigned int n )
{
int this_sum, max_sum, best_i, best_j, i, j;
/*1*/ i = this_sum = max_sum = 0; best_i = best_j = -1;
/*2*/ for( j=0; j<n; j++ )
{
/*3*/ this_sum += a[j];
/*4*/ if( this_sum > max_sum )
{ /* update max_sum, best_i, best_j */
/*5*/ max_sum = this_sum;
/*6*/ best_i = i;
/*7*/ best_j = j;
}
else
/*8*/ if( this_sum < 0 )
{
/*9*/ i = j + 1;
/*10*/ this_sum = 0;
}
}
/*11*/ return( max_sum );
}
2.4.4 运行时间中的对数
对分查找
int
binary_search( input_type a[ ], input_type x, unsigned int n )
{
int low, mid, high; /* Can't be unsigned; why? */
/*1*/ low = 0; high = n - 1;
/*2*/ while( low <= high )
{
/*3*/ mid = (low + high)/2;
/*4*/ if( a[mid] < x )
/*5*/ low = mid + 1;
else
/*6*/ if ( a[mid] < x )
/*7*/ high = mid - 1;
else
/*8*/ return( mid ); /* found */
}
/*9*/ return( NOT_FOUND );
}
欧几里德算法
unsigned int gcd( unsigned int m, unsigned int n )
{
unsigned int rem;
/*1*/ while( n > 0 )
{
/*2*/ rem = m % n;
/*3*/ m = n;
/*4*/ n = rem;
}
/*5*/ return( m );
}
第三章
习题3.1 编写打印出一个链表所有元素的程序
/*前些日子编译环境都是利用SSH在远端linux下,现在安装了个CODEBLOCKS,效果很好*/
#include <stdio.h>
#include <stdlib.h>
struct list
{
struct list* listp;
int gogogo;
};
int main()
{
struct list *header,*temp;
header = malloc(sizeof(struct list));
temp=header;
for(int i=0;i<100;i++)
{
temp->gogogo=i;
temp->listp=malloc(sizeof(struct list));
temp=temp->listp;
}
temp->listp=NULL;
temp=header;
while(temp->listp!=NULL)
{
printf("%d\n",temp->gogogo);
temp=temp->listp;
}
printf("Hello world!\n");
return 0;
}
3.10 约瑟夫环
对于 Josephus Problem 的一些算法
Josephus Problem 大家应该耳熟能详了吧,这里不再赘述
下文提到的 n 均指初始时人数,报数报到 m 退出
Ο(n * m)
用线性表实现的朴素方法多属于此类
Ο(n * log(m))
使用 BST,可以求出完整的退出序列
利用 BST 能在 Ο(log(n)) 求 n 个数中第 k 个数的性质,
每次求出要删除那个编号
Ο(n)
动态规划,s_n = (s_{n-1} + m) % n,这里编号从0开始
如果求出了 n-1 的人的情况下谁最后退出
那么对于 n 个人的情况,m-1 最早退出,
剩下 k k+1 ... n-1 0 1 ... k-2
每一项减去 k 并对 n 取模,得到 0 1 2 ... n-2,编号为 s_{n-1} 的人最后退出
还原为原来的编号,得到 (s_{n-1} + m) % n
Ο(log _ {m/(m-1)} ^ {k*m-n})
可以求出第 k 个退出的人的编号,
复杂度的含义是以 m/(m-1) 为底,k*m-n 的对数
如果忽略常数 m,求最后一个退出的人的编号可以在 Ο(log(n)) 时间内求出
把跳过的人编号添加到后面,1 -> n+1,2 -> n+2,...,m-1 -> n+m-1,m+1 -> n+m
对于编号 m*a+b,会变成 n+(m-1)*a+b
只要求出编号 m*k 原来的编号即可
这是后两种方法的实现,kth 就是那个复杂度描述很复杂的算法
last 是 Ο(n) 的动态规划算法
#include <assert.h>
#include <stdio.h>
int kth(int n, int m, int k)
{
for (k *= m; k > n; k = k-n+(k-n-1)/(m-1));
return k;
}
int last(int n, int m)
{
int s = 0;
for (int i = 2; i <= n; i++)
s = (s+m)%i;
return s+1;
}
int main(void)
{
int n, m;
while (scanf("%d%d", &n, &m) == 2) {
assert(n >= 2 && m > 1);
printf("%d %d\n", kth(n, m, n-1), kth(n, m, n));
//printf("%d\n", last(n, m));
}
return 0;
}
-------------------------------------------
#include <stdio.h>
#include <stdlib.h>
#include <sys/timeb.h>
/*
int algorithm(int Num,int M)
{
return Num;
}
*/
int kth(int n, int m, int k)
{
for (k *= m; k > n; k = k-n+(k-n-1)/(m-1));
return k;
}
int main()
{
int N,M;
struct timeb time1,time2;
printf("How many children? ");
scanf("%d",&N);
printf("How much the M? ");
scanf("%d",&M);
ftime (&time1);
//N=algorithm(N,M);
N=kth(N,M,N);
ftime (&time2);
printf("\nThe last one is %d\n",N);
printf("Running time is %.3fms\n",((float)(time2.time-time1.time)+((float)(time2.millitm-time1.millitm))/1000));
return 0;
}