数据结构病毒感染测试-(C语言版+BF匹配算法)

cs 复制代码
#define MAXSIZE 255
typedef struct
{
	char ch[MAXSIZE + 1];
	int length;
}SString;
typedef struct
{
	char result[MAXSIZE + 1];
}Detection;
int Index_BF(SString Person, SString temp)
{
	int i = 0, j = 0;
	while (i<Person.length && j<temp.length)
	{
		if (Person.ch[i] == temp.ch[j])
		{
			i++;
			j++;
		}
		else
		{
			i = i - j + 1;
			j = 0;
		}
	}
	if (j >= temp.length)
	{
		return 1;
	}
	else {
		return 0;
	}
}
void Virus_detection(SString S[], SString T[], int num, Detection detection[])
{
	SString Person, Virus, temp;
	int k = 0, i, j, flag, m;
	while (num--)
	{
		Person = S[k];
		Virus = T[k];
		flag = 0;
		m = Virus.length;
		//把病毒DNA扩大两倍
		for (i = m,j = 0; j < m; j++)
		{
			Virus.ch[i++] = Virus.ch[j];
		}
		//处理病毒与人体dna
		Virus.ch[2 * m] = '\0';
		for (i = 0; i < m; i++)
		{
			for (j = 0; j < m; j++)
			{
				temp.ch[j] = Virus.ch[i + j];
			}
			temp.ch[m] = '\0';
			temp.length = m;
			flag = Index_BF(Person, temp);
			if (flag == 1)
			{
				break;
			}
		}
		if (flag == 1)
		{
			strcpy(detection[k].result, "YES");
		}
		else {
			strcpy(detection[k].result, "NO");
		}
		k++;
	}
}
int main()
{
	Detection detection[10];
	SString S[10] =
	{
		{"bbaabbba",8},
		{"aaabbbba",8},
		{"abceaabb",8},
		{"abaabcea",8},
		{"cdabbbab",8},
		{"cabbbbab",8},
		{"bcdedbda",8},
		{"bdedbcda",8},
		{"cdcdcdec",8},
		{"cdccdcce",8}
	};
	SString T[10] =
	{
		{"baa"  ,3},
		{"baa"  ,3},
		{"aabb" ,4},
		{"aabb" ,4},
		{"abcd" ,4},
		{"abcd" ,4},
		{"abcde",5},
		{"acc"  ,3},
		{"cde"  ,3},
		{"cced" ,4}
	};
	int num = 10, i;
	Virus_detection(S, T, num, detection);
	printf("病毒\t人体DNA\t   结果\n");	
	for (i = 0; i < num; i++)
	{
		printf("%s  \t%s    %s\n", T[i].ch, S[i].ch, detection[i].result);	
	}
	return 0;
} 

2.下面是可以访问文本文件读取文件内容,然后判断完YES 或 NO后再生成的一个新的结果文本文件代码

cs 复制代码
#include <stdio.h>
#include <stdlib.h>

typedef struct {
    char ch[600];
    int len;
} HString;

int Index_BF(HString S, HString T, int pos) {
    int i = pos, j = 1;
    while (i <= S.len && j <= T.len) {
        if (S.ch[i] == T.ch[j]) {
            i++;
            j++;
        } else {
            i = i - j + 2;
            j = 1;
        }
    }
    if (j > T.len) {
        return i - T.len;
    } else {
        return 0;
    }
}

void Virus_detection() {
    int num, m, flag, i, j;
    char Vir[600];
    HString Virus, Person, temp;
    FILE *inFile = fopen("病毒感染检测输入数据.txt", "r");
    FILE *outFile = fopen("病毒感染检测输出结果.txt", "w");
    if (inFile == NULL || outFile == NULL) {
        printf("Error opening files\n");
        return;
    }
    fscanf(inFile, "%d", &num);
    while (num--) {
        fscanf(inFile, "%s", Virus.ch + 1);
        fscanf(inFile, "%s", Person.ch + 1);
        strcpy(Vir, Virus.ch);
        Virus.len = strlen(Virus.ch) - 1;
        Person.len = strlen(Person.ch) - 1;
        flag = 0;
        m = Virus.len;
        for (i = m + 1, j = 1; j <= m; j++) {
            Virus.ch[i++] = Virus.ch[j];
        }
        Virus.ch[2 * m + 1] = '\0';
        for (i = 0; i < m; i++) {
            for (j = 1; j <= m; j++) {
                temp.ch[j] = Virus.ch[i + j];
            }
            temp.ch[m + 1] = '\0';
            temp.len = strlen(temp.ch) - 1;
            flag = Index_BF(Person, temp, 1);
            if (flag) {
                break;
            }
        }
        if (flag) {
            fprintf(outFile, "%s\t%s\tYES\n", Vir + 1, Person.ch + 1);
        } else {
            fprintf(outFile, "%s\t%s\tNO\n", Vir + 1, Person.ch + 1);
        }
    }
    fclose(inFile);
    fclose(outFile);
}

int main() {
    Virus_detection();
    return 0;
}

其中病毒感染检测输入数据的内容如下:

cs 复制代码
11
baa	bbaabbba 
baa	aaabbbba
aabb	abceaabb
aabb	abaabcea
abcd	cdabbbab
abcd	cabbbbab
abcde	bcdedbda
acc	bdedbcda
cde	cdcdcdec
cced	cdccdcce
bcd     aabccdxdxbxa

读者可以自行创建笔记本,将该笔记本放在自己目标代码的目录下,即可

相关推荐
CoovallyAIHub18 小时前
中科大DSAI Lab团队多篇论文入选ICCV 2025,推动三维视觉与泛化感知技术突破
深度学习·算法·计算机视觉
NAGNIP19 小时前
Serverless 架构下的大模型框架落地实践
算法·架构
moonlifesudo19 小时前
半开区间和开区间的两个二分模版
算法
moonlifesudo19 小时前
300:最长递增子序列
算法
CoovallyAIHub1 天前
港大&字节重磅发布DanceGRPO:突破视觉生成RLHF瓶颈,多项任务性能提升超180%!
深度学习·算法·计算机视觉
CoovallyAIHub1 天前
英伟达ViPE重磅发布!解决3D感知难题,SLAM+深度学习完美融合(附带数据集下载地址)
深度学习·算法·计算机视觉
聚客AI2 天前
🙋‍♀️Transformer训练与推理全流程:从输入处理到输出生成
人工智能·算法·llm
大怪v2 天前
前端:人工智能?我也会啊!来个花活,😎😎😎“自动驾驶”整起!
前端·javascript·算法
惯导马工2 天前
【论文导读】ORB-SLAM3:An Accurate Open-Source Library for Visual, Visual-Inertial and
深度学习·算法
骑自行车的码农2 天前
【React用到的一些算法】游标和栈
算法·react.js