int main(void)
{ int i;
const int nrows = 13;
const int ncols = 4;
double** data = malloc(nrows*sizeof(double*) );
int** mask = malloc(nrows*sizeof(int*));
double** distmatrix;
for (i = 0; i < nrows; i++)
{ data[i] = malloc(ncols*sizeof(double));
mask[i] = malloc(ncols*sizeof(int));
}
/* Test data, roughly distributed in 0-5, 6-8, 9-12 */
data[ 0][ 0]=0.1; data[ 0][ 1]=0.0; data[ 0][ 2]=9.6; data[ 0][ 3] = 5.6;
data[ 1][ 0]=1.4; data[ 1][ 1]=1.3; data[ 1][ 2]=0.0; data[ 1][ 3] = 3.8;
data[ 2][ 0]=1.2; data[ 2][ 1]=2.5; data[ 2][ 2]=0.0; data[ 2][ 3] = 4.8;
data[ 3][ 0]=2.3; data[ 3][ 1]=1.5; data[ 3][ 2]=9.2; data[ 3][ 3] = 4.3;
data[ 4][ 0]=1.7; data[ 4][ 1]=0.7; data[ 4][ 2]=9.6; data[ 4][ 3] = 3.4;
data[ 5][ 0]=0.0; data[ 5][ 1]=3.9; data[ 5][ 2]=9.8; data[ 5][ 3] = 5.1;
data[ 6][ 0]=6.7; data[ 6][ 1]=3.9; data[ 6][ 2]=5.5; data[ 6][ 3] = 4.8;
data[ 7][ 0]=0.0; data[ 7][ 1]=6.3; data[ 7][ 2]=5.7; data[ 7][ 3] = 4.3;
data[ 8][ 0]=5.7; data[ 8][ 1]=6.9; data[ 8][ 2]=5.6; data[ 8][ 3] = 4.3;
data[ 9][ 0]=0.0; data[ 9][ 1]=2.2; data[ 9][ 2]=5.4; data[ 9][ 3] = 0.0;
data[10][ 0]=3.8; data[10][ 1]=3.5; data[10][ 2]=5.5; data[10][ 3] = 9.6;
data[11][ 0]=0.0; data[11][ 1]=2.3; data[11][ 2]=3.6; data[11][ 3] = 8.5;
data[12][ 0]=4.1; data[12][ 1]=4.5; data[12][ 2]=5.8; data[12][ 3] = 7.6;
/* Some data are actually missing */
mask[ 0][ 0]=1; mask[ 0][ 1]=1; mask[ 0][ 2]=1; mask[ 0][ 3] = 1;
mask[ 1][ 0]=1; mask[ 1][ 1]=1; mask[ 1][ 2]=0; mask[ 1][ 3] = 1;
mask[ 2][ 0]=1; mask[ 2][ 1]=1; mask[ 2][ 2]=0; mask[ 2][ 3] = 1;
mask[ 3][ 0]=1; mask[ 3][ 1]=1; mask[ 3][ 2]=1; mask[ 3][ 3] = 1;
mask[ 4][ 0]=1; mask[ 4][ 1]=1; mask[ 4][ 2]=1; mask[ 4][ 3] = 1;
mask[ 5][ 0]=0; mask[ 5][ 1]=1; mask[ 5][ 2]=1; mask[ 5][ 3] = 1;
mask[ 6][ 0]=1; mask[ 6][ 1]=1; mask[ 6][ 2]=1; mask[ 6][ 3] = 1;
mask[ 7][ 0]=0; mask[ 7][ 1]=1; mask[ 7][ 2]=1; mask[ 7][ 3] = 1;
mask[ 8][ 0]=1; mask[ 8][ 1]=1; mask[ 8][ 2]=1; mask[ 8][ 3] = 1;
mask[ 9][ 0]=1; mask[ 9][ 1]=1; mask[ 9][ 2]=1; mask[ 9][ 3] = 0;
mask[10][ 0]=1; mask[10][ 1]=1; mask[10][ 2]=1; mask[10][ 3] = 1;
mask[11][ 0]=0; mask[11][ 1]=1; mask[11][ 2]=1; mask[11][ 3] = 1;
mask[12][ 0]=1; mask[12][ 1]=1; mask[12][ 2]=1; mask[12][ 3] = 1;
show_data(nrows, ncols, data, mask);
example_mean_median(nrows, ncols, data, mask);
distmatrix = example_distance_gene(nrows, ncols, data, mask);
if (distmatrix) example_hierarchical(nrows, ncols, data, mask, distmatrix);
example_distance_array(nrows, ncols, data, mask);
example_kmeans(nrows, ncols, data, mask);
example_som(nrows, ncols, data, mask);
return 0;
}
/*!
Put some help like for function thd_polyfit
*/
int thd_Acluster ( THD_3dim_dataset *in_set,
byte *mask, int nmask,
THD_3dim_dataset **clust_set,
THD_3dim_dataset **dist_set,
OPT_KMEANS oc )
{
int ii, nl, nc;
double **D=NULL, **distmatrix=NULL; /* this double business is a waste of
memory, at least for D..*/
int ncol = -1;
float *dvec=NULL;
int* clusterid = NULL;
short *sc = NULL;
ENTRY("thd_Acluster");
if (!clust_set || *clust_set) {
fprintf(stderr,
"ERROR: output volume pointer pointers must point to NULL\n");
RETURN(0);
}
if (!mask) nmask = DSET_NVOX(in_set);
ncol = DSET_NVALS(in_set);
if (ncol < DSET_NUM_TIMES(in_set)) ncol = DSET_NUM_TIMES(in_set);
if (oc.verb) {
ININFO_message("Have %d/%d voxels to process "
"with %d dimensions per voxel.\n",
nmask, DSET_NVOX(in_set), ncol);
}
/* Create data matrix */
D = (double **)calloc(sizeof(double*), nmask);
for (ii=0;ii<(nmask);++ii) {
if (!(D[ii] = (double *)calloc(sizeof(double), ncol))) {
fprintf(stderr,"ERROR: Failed while allocating %dx%d double matrix\n",
nmask, ncol);
RETURN(0);
}
}
dvec = (float * )malloc(sizeof(float)*ncol) ; /* array to hold series */
if (oc.verb) {
ININFO_message("Filling D(%dx%d) (mask=%p).\n", nmask, ncol, mask);
}
ii = 0;
for (nl=0; nl<DSET_NVOX(in_set); ++nl) {
if (!mask || mask[nl]) {
THD_extract_array( nl , in_set , 0 , dvec ) ;
for (nc=0; nc<ncol; ++nc) D[ii][nc] = dvec[nc];
++ii;
}
}
/* allocate for answer arrays */
if (!(clusterid = (int *)calloc(sizeof(int), nmask))) {
fprintf(stderr,"ERROR: Failed to allocate for clusterid\n");
RETURN(0);
}
/* now do the clustering
(ANDREJ: I do not know why the counting skipped 1st row and 1st col....) */
if (oc.k > 0) {
if (oc.verb) {
ININFO_message("Going to cluster: k=%d, r=%d\n"
"distmetric %c, jobname %s\n",
oc.k, oc.r, oc.distmetric, oc.jobname);
}
example_kmeans( nmask, ncol, D,
oc.k, oc.r, oc.distmetric,
oc.jobname, clusterid);
} else if (oc.kh > 0) {
if (oc.verb) {
ININFO_message("Going to h cluster: kh=%d\n"
"jobname %s\n",
oc.kh, oc.jobname);
}
if ((distmatrix = example_distance_gene(nmask, ncol, D))) {
example_hierarchical( nmask, ncol, D,
oc.jobname, oc.kh,
distmatrix,
clusterid);
/* YOU SHOULD FREE distmatrix here ...*/
} else {
ERROR_message("Failed to create distmatrix");
RETURN(0);
}
} else {
ERROR_message("Bad option selection");
RETURN(0);
}
/* create output datasets, if required*/
*clust_set = EDIT_empty_copy(in_set) ;
EDIT_dset_items( *clust_set ,
ADN_nvals , 1 ,
ADN_ntt , 1 ,
ADN_datum_all , MRI_short ,
ADN_brick_fac , NULL ,
ADN_prefix , "OML!" ,
ADN_none ) ;
/* MRI_float */
if (oc.verb) {
ININFO_message("loading results into %s\n",
DSET_PREFIX(*clust_set));
}
/* transfer ints in clusterid to shorts array */
sc = (short *)calloc(sizeof(short),DSET_NVOX(in_set));
ii = 0;
for (nl=0; nl<DSET_NVOX(in_set); ++nl) {
if (!mask || mask[nl]) {
sc[nl] = (short)clusterid[ii]+1;
++ii;
}
}
free(clusterid); clusterid = NULL;
EDIT_substitute_brick( *clust_set , 0 , MRI_short , sc ) ;
sc = NULL; /* array now in brick */
if (oc.verb) {
ININFO_message("Freedom");
}
if (dvec) free(dvec); dvec=NULL;
// To free D
for (ii=0;ii<nmask;++ii) {
if (D[ii]) free(D[ii]);
}
free(D); D = NULL;
RETURN(1);
}
int main(int argc, char **argv)
{
int ii=0, ncol=0, nrow=0, nl=0, nc=0, posi=0, posj=0, posk=0;
//int nclust=atoi(argv[2]);
MRI_IMAGE *im = NULL;
double *dar = NULL;
double **D = NULL;
//int **mask = NULL;
double** distmatrix = NULL;
//from command.c
int i = 1;
char* filename = 0;
char* jobname = 0;
int l = 0;
int k = 0;
int kh = 3;
int r = 1;
int s = 0;
int x = 2;
int y = 1;
int Rows, Columns;
char distmetric = 'u';
char arraymetric = '\0';
char method = 'm';
char cg = '\0';
char ca = '\0';
int ng = 0;
int na = 0;
while (i < argc)
{ const char* const argument = argv[i];
i++;
if (strlen(argument)<2)
{ printf("ERROR: missing argument\n");
return 0;
}
if (argument[0]!='-')
{ printf("ERROR: unknown argument\n");
return 0;
}
if(!strcmp(argument,"--version") || !strcmp(argument,"-v"))
{ display_version();
return 0;
}
if(!strcmp(argument,"--help") || !strcmp(argument,"-h"))
{ display_help();
return 0;
}
if(!strcmp(argument,"-cg"))
{ if (i==argc || strlen(argv[i])>1 || !strchr("am",argv[i][0]))
{ printf ("Error reading command line argument cg\n");
return 0;
}
cg = argv[i][0];
i++;
continue;
}
if(!strcmp(argument,"-ca"))
{ if (i==argc || strlen(argv[i])>1 || !strchr("am",argv[i][0]))
{ printf ("Error reading command line argument ca\n");
return 0;
}
ca = argv[i][0];
i++;
continue;
}
if(!strcmp(argument,"-ng"))
{ ng = 1;
continue;
}
if(!strcmp(argument,"-na"))
{ na = 1;
continue;
}
switch (argument[1])
{ case 'l': l=1; break;
case 'u':
{ if (i==argc)
{ printf ("Error reading command line argument u: "
"no job name specified\n");
return 0;
}
jobname = setjobname(argv[i],0);
i++;
break;
}
case 'f':
{ if (i==argc)
{ printf ("Error reading command line argument f: "
"no file name specified\n");
return 0;
}
filename = argv[i];
i++;
break;
}
case 'g':
{ int g;
if (i==argc)
{ printf ("Error reading command line argument g: parameter missing\n");
return 0;
}
g = readnumber(argv[i]);
if (g < 0 || g > 9)
{ printf ("Error reading command line argument g: "
"should be between 0 and 9 inclusive\n");
return 0;
}
i++;
distmetric = getmetric(g);
break;
}
case 'k':
{ if (i==argc)
{ printf ("Error reading command line argument k: "
"parameter missing\n");
return 0;
}
k = readnumber(argv[i]);
if (k < 1)
{ printf ("Error reading command line argument k: "
"a positive integer is required\n");
return 0;
}
i++;
break;
}
case 'c':
{ if (i==argc)
{ printf ("Error reading command line argument h: parameter missing\n");
return 0;
}
kh = readnumber(argv[i]);
if (kh < 1)
{ printf ("Error reading command line argument h: a positive integer is required\n");
return 0;
}
i++;
break;
}
case 'r':
{ if (i==argc)
{ printf ("Error reading command line argument r: parameter missing\n");
return 0;
}
r = readnumber(argv[i]);
if (r < 1)
{ printf ("Error reading command line argument r: "
"a positive integer is required\n");
return 0;
}
i++;
break;
}
case 'm':
{ if (i==argc || strlen(argv[i])>1 || !strchr("msca",argv[i][0]))
{ printf ("Error reading command line argument m: should be 'm', 's', 'c', or 'a'\n");
return 0;
}
method = argv[i][0];
i++;
break;
}
default: printf ("Unknown option\n");
}
}
if(jobname==0) jobname = setjobname(filename,1);
/* else
{ display_help();
return 0;
}
*/
if (argc < 2) {
display_help();
return 0;
}
//printf("num of clusters %d \n",nclust);
fprintf(stderr,"Patience, reading %s...\n ", filename);
im = mri_read_double_1D (filename);
/* ZIAD I get this warning
Aclustering.c:408: warning: passing argument 1 of mri_read_double_1D
discards qualifiers from pointer target type
Andrej: filename was declared as (const char *),
but the function expects (char *) */
if (!im) {
fprintf(stderr,"Error: Failed to read matrix data from %s\n",
argv[2]);
return(-1);
}
ncol = im->ny;
nrow = im->nx;
fprintf (stderr,"Have %d cols, %d rows\nNow...\n", ncol, nrow);
/* now just get the array and kill the rest */
dar = MRI_DOUBLE_PTR(im);
/* make sure that pointer is set to NULL in im, or risk hell */
mri_clear_data_pointer(im);
if (im) mri_free(im); im = NULL; /* now kill im */
/* for double loop*/
D = (double **)calloc(sizeof(double*), nrow-1);
for (ii=0;ii<(nrow-1);++ii) {
D[ii] = (double *)calloc(sizeof(double), ncol-1);
}
for (nl=1; nl<nrow; ++nl) {
for (nc=1; nc<ncol; ++nc) {
D[nl-1][nc-1] = dar[nl+nc*nrow];
}
//fprintf(stdout,"\n");
}
//show_data(nrows, ncols, data, mask);
//example_mean_median(nrows, ncols, data, mask);
//distmatrix = example_distance_gene(nrows, ncols, data, mask);
//if (distmatrix) example_hierarchical(nrows, ncols, data, mask, distmatrix);
//example_distance_array(nrows, ncols, data, mask);
if(k>0) example_kmeans(nrow-1, ncol-1, D, k, r, distmetric, jobname);
else
{
distmatrix = example_distance_gene(nrow-1, ncol-1, D); // ZIAD: goes2 SIGKILL error
if (distmatrix)
example_hierarchical(nrow-1, ncol-1, D, jobname, kh, distmatrix);
}
free(dar); dar = NULL; /* done with input array */
// To free D
for (ii=0;ii<(nrow-1);++ii) {
if (D[ii]) free(D[ii]);
}
free(D);
free(jobname);
//free();
fprintf (stderr,"\n");
return 0;
}
