在 C 中实现 8-Connectivity Hoshen-Kopelman 算法

问题描述

我发现 here 是 Hoshen-Kopelman 算法的实现,但它只检查向上和向左的邻居,这意味着对角连接不被视为连接。

如何改进此代码,以便即使是对角线连接也将被视为连接?

在下面的例子中,我期望 1 个对象而不是 7 个对象:

4 5
1 0 1 0 1
0 1 0 1 0
1 0 1 0 0
0 0 1 0 0
 --input--
  1   0   1   0   1
  0   1   0   1   0
  1   0   1   0   0
  0   0   1   0   0
 --output--
  1   0   2   0   3
  0   4   0   5   0
  6   0   7   0   0
  0   0   7   0   0
HK reports 7 clusters found

这是实现(完整代码可以在here找到):

#include <stdio.h>
#include <stdlib.h>
#include <assert.h>

/* Implementation of Union-Find Algorithm */


/* The 'labels' array has the meaning that labels[x] is an alias for the label x; by
   following this chain until x == labels[x],you can find the canonical name of an
   equivalence class.  The labels start at one; labels[0] is a special value indicating
   the highest label already used. */

int* labels;
int  n_labels = 0;     /* length of the labels array */

/*  uf_find returns the canonical label for the equivalence class containing x */

int uf_find(int x)
{
    int y = x;
    while (labels[y] != y)
        y = labels[y];

    while (labels[x] != x)
    {
        int z = labels[x];
        labels[x] = y;
        x = z;
    }
    return y;
}

/*  uf_union joins two equivalence classes and returns the canonical label of the resulting class. */

int uf_union(int x,int y)
{
    return labels[uf_find(x)] = uf_find(y);
}

/*  uf_make_set creates a new equivalence class and returns its label */

int uf_make_set(void)
{
    labels[0] ++;
    assert(labels[0] < n_labels);
    labels[labels[0]] = labels[0];
    return labels[0];
}

/*  uf_intitialize sets up the data structures needed by the union-find implementation. */

void uf_initialize(int max_labels)
{
    n_labels = max_labels;
    labels = calloc(sizeof(int),n_labels);
    labels[0] = 0;
}

/*  uf_done frees the memory used by the union-find data structures */

void uf_done(void)
{
    n_labels = 0;
    free(labels);
    labels = 0;
}

/* End Union-Find implementation */

#define max(a,b) (a>b?a:b)
#define min(a,b) (a>b?b:a)

/* print_matrix prints out a matrix that is set up in the "pointer to pointers" scheme
   (aka,an array of arrays); this is incompatible with C's usual representation of 2D
   arrays,but allows for 2D arrays with dimensions determined at run-time */

void print_matrix(int** matrix,int m,int n)
{
    for (int i = 0; i < m; i++)
    {
        for (int j = 0; j < n; j++)
            printf("%3d ",matrix[i][j]);
        printf("\n");
    }
}


/* Label the clusters in "matrix".  Return the total number of clusters found. */

int hoshen_kopelman(int** matrix,int n)
{

    uf_initialize(m * n / 2);

    /* scan the matrix */

    for (int y = 0; y < m; y++)
    {
        for (int x = 0; x < n; x++)
        {
            if (matrix[y][x])
            {                        // if occupied ...

                int up = (y == 0 ? 0 : matrix[y - 1][x]);    //  look up  
                int left = (x == 0 ? 0 : matrix[y][x - 1]);  //  look left

                switch (!!up + !!left)
                {

                case 0:
                    matrix[y][x] = uf_make_set();      // a new cluster
                    break;

                case 1:                              // part of an existing cluster
                    matrix[y][x] = max(up,left);    // whichever is nonzero is labelled
                    break;

                case 2:                              // this site binds two clusters
                    matrix[y][x] = uf_union(up,left);
                    break;
                }

            }
        }
    }


    /* apply the relabeling to the matrix */

    /* This is a little bit sneaky.. we create a mapping from the canonical labels
       determined by union/find into a new set of canonical labels,which are
       guaranteed to be sequential. */

    int* new_labels = calloc(sizeof(int),n_labels); // allocate array,initialized to zero

    for (int i = 0; i < m; i++)
        for (int j = 0; j < n; j++)
            if (matrix[i][j])
            {
                int x = uf_find(matrix[i][j]);
                if (new_labels[x] == 0)
                {
                    new_labels[0]++;
                    new_labels[x] = new_labels[0];
                }
                matrix[i][j] = new_labels[x];
            }

    int total_clusters = new_labels[0];

    free(new_labels);
    uf_done();

    return total_clusters;
}

/* This procedure checks to see that any occupied neighbors of an occupied site
   have the same label. */

void check_labelling(int** matrix,int n)
{
    int N,S,E,W;
    for (int i = 0; i < m; i++)
        for (int j = 0; j < n; j++)
            if (matrix[i][j])
            {
                N = (i == 0 ? 0 : matrix[i - 1][j]);
                S = (i == m - 1 ? 0 : matrix[i + 1][j]);
                E = (j == n - 1 ? 0 : matrix[i][j + 1]);
                W = (j == 0 ? 0 : matrix[i][j - 1]);

                assert(N == 0 || matrix[i][j] == N);
                assert(S == 0 || matrix[i][j] == S);
                assert(E == 0 || matrix[i][j] == E);
                assert(W == 0 || matrix[i][j] == W);
            }
}

/* The sample program reads in a matrix from standard input,runs the HK algorithm on
   it,and prints out the results.  The form of the input is two integers giving the
   dimensions of the matrix,followed by the matrix elements (with data separated by
   whitespace).

a sample input file is the following:

8 8
1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 1
1 0 0 0 0 1 0 1
1 0 0 1 0 1 0 1
1 0 0 1 0 1 0 1
1 0 0 1 1 1 0 1
1 1 1 1 0 0 0 1
0 0 0 1 1 1 0 1

this sample input gives the following output:

 --input--
  1   1   1   1   1   1   1   1
  0   0   0   0   0   0   0   1
  1   0   0   0   0   1   0   1
  1   0   0   1   0   1   0   1
  1   0   0   1   0   1   0   1
  1   0   0   1   1   1   0   1
  1   1   1   1   0   0   0   1
  0   0   0   1   1   1   0   1
 --output--
  1   1   1   1   1   1   1   1
  0   0   0   0   0   0   0   1
  2   0   0   0   0   2   0   1
  2   0   0   2   0   2   0   1
  2   0   0   2   0   2   0   1
  2   0   0   2   2   2   0   1
  2   2   2   2   0   0   0   1
  0   0   0   2   2   2   0   1
HK reports 2 clusters found

*/

int main(int argc,char** argv)
{

    int m,n;
    int** matrix;

    /* Read in the matrix from standard input

       The whitespace-deliminated matrix input is preceeded
       by the number of rows and number of columns */

    while (2 == scanf_s("%d %d",&m,&n))
    {  // m = rows,n = columns

        matrix = (int**)calloc(m,sizeof(int*));

        for (int i = 0; i < m; i++)
        {
            matrix[i] = (int*)calloc(n,sizeof(int));
            for (int j = 0; j < n; j++)
                scanf_s("%d",&(matrix[i][j]));
        }

        printf_s(" --input-- \n");

        print_matrix(matrix,m,n);

        printf(" --output-- \n");

        /* Process the matrix */

        int clusters = hoshen_kopelman(matrix,n);

        /* Output the result */

        print_matrix(matrix,n);

        check_labelling(matrix,n);

        printf("HK reports %d clusters found\n",clusters);

        for (int i = 0; i < m; i++)
            free(matrix[i]);
        free(matrix);
    }

    return 0;
}

我尝试更改函数 hoshen_kopelman 如下所述,但我仍然得到 2 个对象而不是 1 个:

int hoshen_kopelman(int** matrix,int n)
{

    uf_initialize(m * n / 2);

    /* scan the matrix */

    for (int y = 0; y < m; y++)
    {
        for (int x = 0; x < n; x++)
        {
            if (matrix[y][x])
            {                        // if occupied ...

                int up = (y == 0 ? 0 : matrix[y - 1][x]);    //  look up  
                int left = (x == 0 ? 0 : matrix[y][x - 1]);  //  look left
                
                // ----------- THE NEW CODE -------------
                if (x > 0) 
                {
                    if (up == 0 && y > 0) // left+up
                        up = matrix[y - 1][x - 1];

                    if (left == 0 && y < m - 1) // left+down
                        left = matrix[y + 1][x - 1];
                }
                // ---------- END NEW CODE --------------

                switch (!!up + !!left)
                {

                case 0:
                    matrix[y][x] = uf_make_set();      // a new cluster
                    break;

                case 1:                              // part of an existing cluster
                    matrix[y][x] = max(up,initialized to zero

    for (int i = 0; i < m; i++)
        for (int j = 0; j < n; j++)
            if (matrix[i][j])
            {
                int x = uf_find(matrix[i][j]);
                if (new_labels[x] == 0)
                {
                    new_labels[0]++;
                    new_labels[x] = new_labels[0];
                }
                matrix[i][j] = new_labels[x];
            }

    int total_clusters = new_labels[0];

    free(new_labels);
    uf_done();

    return total_clusters;
}

现在获得以下输出(我期待 1 并得到 2):

4 5
1 0 1 0 1
0 1 0 1 0
1 0 1 0 0
0 0 1 0 0
 --input--
  1   0   1   0   1
  0   1   0   1   0
  1   0   1   0   0
  0   0   1   0   0
 --output--
  1   0   1   0   1
  0   1   0   1   0
  2   0   1   0   0
  0   0   1   0   0
HK reports 2 clusters found

纠正代码以检查所有 8 个邻居的正确方法是什么?

解决方法

我让你误入歧途,说要检查左下角。该算法依赖于它正在检查的当前节点是在它检查的所有邻居之后。所以你需要检查左上、上、左上和右上。您可以使用它代替新代码:

                if (y > 0) 
                {
                    if (left == 0 && x > 0) // left+up
                        left = matrix[y - 1][x - 1];

                    if (up == 0 && x < n-1) // right+up
                        up = matrix[y - 1][x + 1];
                }