MRI *
MRIScomputeDistanceMap(MRI_SURFACE *mris, MRI *mri_distance, int ref_vertex_no)
{
int vno ;
VERTEX *v ;
double circumference, angle, distance ;
VECTOR *v1, *v2 ;
if (mri_distance == NULL)
mri_distance = MRIalloc(mris->nvertices, 1, 1, MRI_FLOAT) ;
v1 = VectorAlloc(3, MATRIX_REAL) ; v2 = VectorAlloc(3, MATRIX_REAL) ;
v = &mris->vertices[ref_vertex_no] ;
VECTOR_LOAD(v1, v->x, v->y, v->z) ; /* radius vector */
circumference = M_PI * 2.0 * V3_LEN(v1) ;
for (vno = 0 ; vno < mris->nvertices ; vno++)
{
v = &mris->vertices[vno] ;
if (vno == Gdiag_no)
DiagBreak() ;
VECTOR_LOAD(v2, v->x, v->y, v->z) ; /* radius vector */
angle = fabs(Vector3Angle(v1, v2)) ;
distance = circumference * angle / (2.0 * M_PI) ;
MRIsetVoxVal(mri_distance, vno, 0, 0, 0, distance) ;
}
VectorFree(&v1) ; VectorFree(&v2) ;
return(mri_distance) ;
}
void ServerFreeSafe(struct server* st_server) {
struct client* st_client;
struct file* st_file;
assert(!st_server->listening);
/* Free memory related to the clients. */
if(st_server->st_clients != NULL) {
for(int i = 0; i < st_server->st_clients->current; i++) {
st_client = (struct client*)VectorGetPointer(st_server->st_clients, i);
if(ClientClose(st_client) == FAILED)
printf("Could not gracefully terminate client %s:%d\n", st_client->ip, st_client->port);
ClientDelete(st_client);
}
VectorFree(st_server->st_clients);
}
/* Free memory related to the clients. */
if(st_server->st_files != NULL) {
for(int i = 0; i < st_server->st_files->current; i++) {
st_file = (struct file*)VectorGetPointer(st_server->st_files, i);
ServerDeleteFile(st_server, st_file->descriptor);
}
VectorFree(st_server->st_files);
}
}
void GaussSeidel(const int n, double **a, double *b, double *x, double eps,
int max_iter) {
int iter, i, j; /* counter */
double sum; /* temporary real */
double *x_old; /* old solution */
double norm; /* L1-norm */
x_old=VectorAlloc(n);
iter=0;
do { /* repeat until safisfying sol. */
iter++;
for(i=0; i<n; i++) /* copy old solution */
x_old[i]=x[i];
norm=0.0; /* do an iteration */
for(i=0; i<n; i++) {
sum=-a[i][i]*x[i]; /* don't include term i=j */
for(j=0; j<n; j++)
sum+=a[i][j]*x[j];
x[i]=(b[i]-sum)/a[i][i];
norm+=fabs(x_old[i]-x[i]);
} /* for i */
} while ((iter<=max_iter) && (norm>=eps));
VectorFree(n, x_old);
} /* GaussSeidel */
void InversMatrix(const int n, double **b, double **ib) {
double **a;
double *e;
int i,j;
int *p;
a=MatrixAlloc(n);
e=VectorAlloc(n);
p=IntVectorAlloc(n);
MatrixCopy(n, a, b);
LUfact(n, a, p);
for(i=0; i<n; i++) {
for(j=0; j<n; j++)
e[j]=0.0;
e[i]=1.0;
LUsubst(n, a, p, e);
for(j=0; j<n; j++)
ib[j][i]=e[j];
} /* for i=1..n */
MatrixFree(n, a);
VectorFree(n, e);
IntVectorFree(n, p);
} /* InversMatrix */
// test vector's functions
int main(int argc, char **argv) {
size_t i;
vector_t v = VectorCreate(INITIAL_SIZE);
if (v == NULL)
return EXIT_FAILURE;
for (i = 0; i < FINAL_SIZE; ++i) {
int *x = (int*)malloc(sizeof(int));
if (x == NULL)
return EXIT_FAILURE;
*x = FINAL_SIZE - i;
element_t old;
// set the value to the position i in the vector
// terminate the program if VectorSet failed
if (!(VectorSet(v, i, x, &old)))
return EXIT_FAILURE;
}
PrintIntVector(v);
// free the values stored in the vector
for (i = 0; i < VectorLength(v); ++i)
free(VectorGet(v, i));
// free the vector
VectorFree(v);
return EXIT_SUCCESS;
}
static int
compute_cluster_statistics(MRI_SURFACE *mris, MRI *mri_profiles, CLUSTER *ct, int k) {
int i, vno, cluster, nsamples, num[MAX_CLUSTERS];
VECTOR *v1 ;
memset(num, 0, sizeof(num)) ;
nsamples = mri_profiles->nframes ;
v1 = VectorAlloc(nsamples, MATRIX_REAL) ;
for (cluster = 0 ; cluster < k ; cluster++)
VectorClear(ct[cluster].v_mean) ;
// compute means
for (vno = 0 ; vno < mris->nvertices ; vno++) {
cluster = mris->vertices[vno].curv ;
for (i = 0 ; i < nsamples ; i++) {
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
}
num[cluster]++ ;
VectorAdd(ct[cluster].v_mean, v1, ct[cluster].v_mean) ;
}
for (cluster = 0 ; cluster < k ; cluster++)
if (num[cluster] > 0)
VectorScalarMul(ct[cluster].v_mean, 1.0/(double)num[cluster], ct[cluster].v_mean) ;
VectorFree(&v1) ;
return(NO_ERROR) ;
}
static MRI *
apply_bias(MRI *mri_orig, MRI *mri_norm, MRI *mri_bias) {
MATRIX *m_vox2vox;
VECTOR *v1, *v2;
int x, y, z ;
double xd, yd, zd, bias, val_orig, val_norm ;
if (mri_norm == NULL)
mri_norm = MRIclone(mri_orig, NULL) ;
m_vox2vox = MRIgetVoxelToVoxelXform(mri_orig, mri_bias) ;
v1 = VectorAlloc(4, MATRIX_REAL);
v2 = VectorAlloc(4, MATRIX_REAL);
VECTOR_ELT(v1, 4) = 1.0 ;
VECTOR_ELT(v2, 4) = 1.0 ;
for (x = 0 ; x < mri_orig->width ; x++) {
V3_X(v1) = x ;
for (y = 0 ; y < mri_orig->height ; y++) {
V3_Y(v1) = y ;
for (z = 0 ; z < mri_orig->depth ; z++) {
V3_Z(v1) = z ;
if (x == Gx && y == Gy && z == Gz)
DiagBreak() ;
val_orig = MRIgetVoxVal(mri_orig, x, y, z, 0) ;
MatrixMultiply(m_vox2vox, v1, v2) ;
xd = V3_X(v2) ;
yd = V3_Y(v2) ;
zd = V3_Z(v2);
MRIsampleVolume(mri_bias, xd, yd, zd, &bias) ;
val_norm = val_orig * bias ;
if (mri_norm->type == MRI_UCHAR) {
if (val_norm > 255)
val_norm = 255 ;
else if (val_norm < 0)
val_norm = 0 ;
}
MRIsetVoxVal(mri_norm, x, y, z, 0, val_norm) ;
}
}
}
MatrixFree(&m_vox2vox) ;
VectorFree(&v1) ;
VectorFree(&v2) ;
return(mri_norm) ;
}
static int
find_most_likely_unmarked_vertex(MRI_SURFACE *mris, MRI *mri_profiles, CLUSTER *ct, int k, int *pcluster_no) {
double dist, min_dist ;
int vno, c, min_cluster, min_vno, n, okay ;
VECTOR *v_vals ;
VERTEX *v, *vn ;
v_vals = VectorAlloc(mri_profiles->nframes, MATRIX_REAL) ;
min_dist = -1 ;
min_vno = -1 ;
min_cluster = -1 ;
for (vno = 0 ; vno < mris->nvertices ; vno++) {
v = &mris->vertices[vno] ;
if (v->ripflag)
continue ;
if (v->curv < 0) // not in a cluster yet
continue ;
c = v->curv ;
for (n = 0 ; n < v->vnum ; n++) {
vn = &mris->vertices[v->v[n]] ;
if (vn->curv >= 0)
continue ;
if (vn->ripflag)
continue ;
load_vals(mri_profiles, v_vals, v->v[n]) ;
dist = MatrixMahalanobisDistance(ct[c].v_mean, ct[c].m_cov, v_vals);
if (min_vno < 0 || dist < min_dist) {
if (ct[c].npoints == 1)
okay = 1 ;
else // check to make sure it has at least 2 nbrs of the right class
{
int n2, nc ;
for (n2 = nc = 0 ; n2 < vn->vnum ; n2++)
if (mris->vertices[vn->v[n2]].curv == c)
nc++ ;
okay = nc > 1 ;
}
if (okay) {
min_cluster = c ;
min_dist = dist ;
min_vno = v->v[n] ;
}
}
}
}
v = &mris->vertices[min_vno] ;
*pcluster_no = min_cluster ;
VectorFree(&v_vals) ;
return(min_vno) ;
}
void Jacobi(const int n, double **a, double *b, double *x, double eps,
int max_iter) {
double d; /* temporary real */
int i, j, iter; /* counters */
double **a_new; /* a is altered */
double *b_new; /* b is altered */
double *u; /* new solution */
double norm; /* L1-norm */
a_new=MatrixAlloc(3);
b_new=VectorAlloc(3);
u=VectorAlloc(3);
for(i=0; i<n; i++) { /* the trick */
d=1.0/a[i][i];
b_new[i]=d*b[i];
for(j=0; j<n; j++)
a_new[i][j]=d*a[i][j];
} /* for i */
iter=0;
do {
iter++;
norm=0.0;
for(i=0; i<n; i++) { /* update process */
d=-a_new[i][i]*x[i]; /* don't include term i=j */
for(j=0; j<n; j++)
d+=a_new[i][j]*x[j];
u[i]=b_new[i]-d;
norm=fabs(u[i]-x[i]);
} /* for i */
for(i=0; i<n; i++) /* copy solution */
x[i]=u[i];
} while ((iter<=max_iter) && (norm>=eps));
MatrixFree(3, a_new);
VectorFree(3, b_new);
VectorFree(3, u);
} /* Jacobi */
void LUfact(const int n, double **a, int *p) {
int i, j, k; /* counters */
double z; /* temporary real */
double *s; /* pivot elements */
int not_finished; /* loop control var. */
int i_swap; /* swap var. */
double temp; /* another temp. real */
s=VectorAlloc(n);
for(i=0; i<n; i++) {
p[i]=i;
s[i]=0.0;
for(j=0; j<n; j++) {
z=fabs(a[i][j]);
if (s[i]<z)
s[i]=z;
} /* for j */
} /* for i */
for(k=0; k<(n-1); k++) {
j=k-1; /* select j>=k so ... */
not_finished=1;
while (not_finished) {
j++;
temp=fabs(a[p[j]][k]/s[p[j]]);
for(i=k; i<n; i++)
if (temp>=(fabs(a[p[i]][k])/s[p[i]]))
not_finished=0; /* end loop */
} /* while */
i_swap=p[k];
p[k]=p[j];
p[j]=i_swap;
temp=1.0/a[p[k]][k];
for(i=(k+1); i<n; i++) {
z=a[p[i]][k]*temp;
a[p[i]][k]=z;
for(j=(k+1); j<n; j++)
a[p[i]][j]-=z*a[p[k]][j];
} /* for i */
} /* for k */
VectorFree(n, s);
} /* LUfact */
static int
mark_clusters(MRI_SURFACE *mris, MRI *mri_profiles, CLUSTER *ct, int k) {
int i, vno, min_i, nsamples, num[MAX_CLUSTERS], nchanged ;
double min_dist, dist ;
VECTOR *v1 ;
VERTEX *v ;
memset(num, 0, sizeof(num)) ;
nsamples = mri_profiles->nframes ;
v1 = VectorAlloc(nsamples, MATRIX_REAL) ;
for (nchanged = vno = 0 ; vno < mris->nvertices ; vno++) {
v = &mris->vertices[vno] ;
if (v->ripflag)
continue ;
if (vno == Gdiag_no)
DiagBreak() ;
for (i = 0 ; i < nsamples ; i++)
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
min_dist = MatrixMahalanobisDistance(ct[0].v_mean, ct[0].m_cov, v1) ;
min_i = 0 ;
for (i = 1 ; i < k ; i++) {
if (i == Gdiag_no)
DiagBreak() ;
dist = MatrixMahalanobisDistance(ct[i].v_mean, ct[i].m_cov, v1) ;
if (dist < min_dist) {
min_dist = dist ;
min_i = i ;
}
}
CTABannotationAtIndex(mris->ct, min_i, &v->annotation) ;
if (v->curv != min_i)
nchanged++ ;
v->curv = min_i ;
num[min_i]++ ;
}
for (i = 0 ; i < k ; i++)
if (num[i] == 0)
DiagBreak() ;
VectorFree(&v1) ;
printf("%d vertices changed clusters...\n", nchanged) ;
return(nchanged) ;
}
void Tridiag(const int n, double *a, double *d, double *c, double *b) {
int i; /* counter */
double *x; /* solution */
x=VectorAlloc(n);
for(i=1; i<n; i++) {
d[i]-=(a[i-1]/d[i-1])*c[i-1];
b[i]-=(a[i-1]/d[i-1])*b[i-1];
} /* for i */
x[n-1]=b[n-1]/d[n-1];
for(i=(n-2); i>=0; i--)
x[i]=(b[i]-c[i]*b[i+1])/d[i];
for(i=0; i<n; i++)
b[i]=x[i];
VectorFree(n, x);
} /* Tridiag */
void LUsubst(const int n, double **a, int *p, double *b) {
int i, j, k; /* counters */
double sum; /* temporary sum variable */
double *x; /* solution */
x=VectorAlloc(n);
for(k=0; k<(n-1); k++) /* forward subst */
for(i=(k+1); i<n; i++)
b[p[i]]-=a[p[i]][k]*b[p[k]];
for(i=(n-1); i>=0; i--) { /* back subst */
sum=b[p[i]];
for(j=(i+1); j<n; j++)
sum-=a[p[i]][j]*x[j];
x[i]=sum/a[p[i]][i];
} /* for i */
for(i=0; i<n; i++) /* copy solution */
b[i]=x[i];
VectorFree(n, x);
} /* LUsubst */
int
MRIcomputePartialVolumeFractions(MRI *mri_src, MATRIX *m_vox2vox,
MRI *mri_seg, MRI *mri_wm, MRI *mri_subcort_gm, MRI *mri_cortex,
MRI *mri_csf,
int wm_val, int subcort_gm_val, int cortex_val, int csf_val)
{
int x, y, z, xs, ys, zs, label ;
VECTOR *v1, *v2 ;
MRI *mri_counts ;
float val, count ;
MATRIX *m_inv ;
m_inv = MatrixInverse(m_vox2vox, NULL) ;
if (m_inv == NULL)
{
MatrixPrint(stdout, m_vox2vox) ;
ErrorExit(ERROR_BADPARM, "MRIcomputePartialVolumeFractions: non-invertible vox2vox matrix");
}
mri_counts = MRIcloneDifferentType(mri_src, MRI_INT) ;
v1 = VectorAlloc(4, MATRIX_REAL) ;
v2 = VectorAlloc(4, MATRIX_REAL) ;
VECTOR_ELT(v1, 4) = 1.0 ; VECTOR_ELT(v2, 4) = 1.0 ;
for (x = 0 ; x < mri_seg->width ; x++)
{
V3_X(v1) = x ;
for (y = 0 ; y < mri_seg->height ; y++)
{
V3_Y(v1) = y ;
for (z = 0 ; z < mri_seg->depth ; z++)
{
if (x == Gx && y == Gy && z == Gz)
DiagBreak() ;
V3_Z(v1) = z ;
MatrixMultiply(m_vox2vox, v1, v2) ;
xs = nint(V3_X(v2)) ; ys = nint(V3_Y(v2)) ; zs = nint(V3_Z(v2)) ;
if (xs >= 0 && ys >= 0 && zs >= 0 &&
xs < mri_src->width && ys < mri_src->height && zs < mri_src->depth)
{
val = MRIgetVoxVal(mri_counts, xs, ys, zs, 0) ;
MRIsetVoxVal(mri_counts, xs, ys, zs, 0, val+1) ;
label = MRIgetVoxVal(mri_seg, x, y, z, 0) ;
if (label == csf_val)
{
val = MRIgetVoxVal(mri_csf, xs, ys, zs, 0) ;
MRIsetVoxVal(mri_csf, xs, ys, zs, 0, val+1) ;
}
else if (label == wm_val)
{
val = MRIgetVoxVal(mri_wm, xs, ys, zs, 0) ;
MRIsetVoxVal(mri_wm, xs, ys, zs, 0, val+1) ;
}
else if (label == subcort_gm_val)
{
val = MRIgetVoxVal(mri_subcort_gm, xs, ys, zs, 0) ;
MRIsetVoxVal(mri_subcort_gm, xs, ys, zs, 0, val+1) ;
}
else if (label == cortex_val)
{
val = MRIgetVoxVal(mri_cortex, xs, ys, zs, 0) ;
MRIsetVoxVal(mri_cortex, xs, ys, zs, 0, val+1) ;
}
else
DiagBreak() ;
}
}
}
}
for (x = 0 ; x < mri_src->width ; x++)
for (y = 0 ; y < mri_src->height ; y++)
for (z = 0 ; z < mri_src->depth ; z++)
{
count = MRIgetVoxVal(mri_counts, x, y, z, 0) ;
if (count >= 1)
{
if (x == Gx && y == Gy && z == Gz)
DiagBreak() ;
val = MRIgetVoxVal(mri_wm, x, y, z, 0) ;
MRIsetVoxVal(mri_wm, x, y, z, 0, val/count) ;
val = MRIgetVoxVal(mri_subcort_gm, x, y, z, 0) ;
MRIsetVoxVal(mri_subcort_gm, x, y, z, 0, val/count) ;
val = MRIgetVoxVal(mri_cortex, x, y, z, 0) ;
MRIsetVoxVal(mri_cortex, x, y, z, 0, val/count) ;
val = MRIgetVoxVal(mri_csf, x, y, z, 0) ;
MRIsetVoxVal(mri_csf, x, y, z, 0, val/count) ;
}
else // sample in other direction
{
V3_X(v1) = x ; V3_Y(v1) = y ; V3_Z(v1) = z ;
MatrixMultiply(m_inv, v1, v2) ;
MatrixMultiply(m_inv, v1, v2) ;
xs = nint(V3_X(v2)) ; ys = nint(V3_Y(v2)) ; zs = nint(V3_Z(v2)) ;
if (xs >= 0 && ys >= 0 && zs >= 0 &&
xs < mri_seg->width && ys < mri_seg->height && zs < mri_seg->depth)
{
label = MRIgetVoxVal(mri_seg, xs, ys, zs, 0) ;
if (label == csf_val)
MRIsetVoxVal(mri_csf, x, y, z, 0, 1) ;
else if (label == wm_val)
MRIsetVoxVal(mri_wm, x, y, z, 0, 1) ;
else if (label == subcort_gm_val)
MRIsetVoxVal(mri_subcort_gm, x, y, z, 0, 1) ;
else if (cortex_val)
MRIsetVoxVal(mri_cortex, x, y, z, 0, 1) ;
else
DiagBreak() ;
}
}
}
VectorFree(&v1) ; VectorFree(&v2) ; MatrixFree(&m_inv) ;
MRIfree(&mri_counts) ;
return(NO_ERROR) ;
}
static int
compute_cluster_statistics(MRI_SURFACE *mris, MRI *mri_profiles, MATRIX **m_covs, VECTOR **v_means, int k) {
int i, vno, cluster, nsamples, num[MAX_CLUSTERS];
int singular, cno_pooled, cno ;
MATRIX *m1, *mpooled, *m_inv_covs[MAX_CLUSTERS] ;
VECTOR *v1 ;
FILE *fp ;
double det, det_pooled ;
memset(num, 0, sizeof(num)) ;
nsamples = mri_profiles->nframes ;
v1 = VectorAlloc(nsamples, MATRIX_REAL) ;
m1 = MatrixAlloc(nsamples, nsamples, MATRIX_REAL) ;
mpooled = MatrixAlloc(nsamples, nsamples, MATRIX_REAL) ;
for (cluster = 0 ; cluster < k ; cluster++) {
VectorClear(v_means[cluster]) ;
MatrixClear(m_covs[cluster]) ;
}
// compute means
// fp = fopen("co.dat", "w") ;
fp = NULL ;
for (vno = 0 ; vno < mris->nvertices ; vno++) {
cluster = mris->vertices[vno].curv ;
for (i = 0 ; i < nsamples ; i++) {
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
if (cluster == 0 && fp)
fprintf(fp, "%f ", VECTOR_ELT(v1, i+1));
}
if (cluster == 0 && fp)
fprintf(fp, "\n") ;
num[cluster]++ ;
VectorAdd(v_means[cluster], v1, v_means[cluster]) ;
}
if (fp)
fclose(fp) ;
for (cluster = 0 ; cluster < k ; cluster++)
if (num[cluster] > 0)
VectorScalarMul(v_means[cluster], 1.0/(double)num[cluster], v_means[cluster]) ;
// compute inverse covariances
for (vno = 0 ; vno < mris->nvertices ; vno++) {
cluster = mris->vertices[vno].curv ;
for (i = 0 ; i < nsamples ; i++)
VECTOR_ELT(v1, i+1) = MRIgetVoxVal(mri_profiles, vno, 0, 0, i) ;
VectorSubtract(v_means[cluster], v1, v1) ;
VectorOuterProduct(v1, v1, m1) ;
MatrixAdd(m_covs[cluster], m1, m_covs[cluster]) ;
MatrixAdd(mpooled, m1, mpooled) ;
}
MatrixScalarMul(mpooled, 1.0/(double)mris->nvertices, mpooled) ;
cno_pooled = MatrixConditionNumber(mpooled) ;
det_pooled = MatrixDeterminant(mpooled) ;
for (cluster = 0 ; cluster < k ; cluster++)
if (num[cluster] > 0)
MatrixScalarMul(m_covs[cluster], 1.0/(double)num[cluster], m_covs[cluster]) ;
// invert all the covariance matrices
MatrixFree(&m1) ;
singular = 0 ;
for (cluster = 0 ; cluster < k ; cluster++) {
m1 = MatrixInverse(m_covs[cluster], NULL) ;
cno = MatrixConditionNumber(m_covs[cluster]) ;
det = MatrixDeterminant(m_covs[cluster]) ;
if (m1 == NULL)
singular++ ;
while (cno > 100*cno_pooled || 100*det < det_pooled) {
if (m1)
MatrixFree(&m1) ;
m1 = MatrixScalarMul(mpooled, 0.1, NULL) ;
MatrixAdd(m_covs[cluster], m1, m_covs[cluster]) ;
MatrixFree(&m1) ;
cno = MatrixConditionNumber(m_covs[cluster]) ;
m1 = MatrixInverse(m_covs[cluster], NULL) ;
det = MatrixDeterminant(m_covs[cluster]) ;
}
m_inv_covs[cluster] = m1 ;
}
for (cluster = 0 ; cluster < k ; cluster++) {
if (m_inv_covs[cluster] == NULL)
DiagBreak() ;
else {
MatrixFree(&m_covs[cluster]) ;
m_covs[cluster] = m_inv_covs[cluster] ;
// MatrixIdentity(m_covs[cluster]->rows, m_covs[cluster]);
}
}
MatrixFree(&mpooled) ;
VectorFree(&v1) ;
return(NO_ERROR) ;
}
void MPI_MatrixMultiplyToVector(double ** mat, double * vec, int N)
{
int i, rowmin, rowmax, sendcount;
int * recvcounts;
double ThisElement;
double * MyVector;
/*
Determine how many elements to receive from each task
*/
recvcounts = malloc(NTasks * sizeof(int));
for (i=0; i < NTasks; i++)
{
if (i != NTasks - 1)
{
recvcounts[i] = ProcBoundaries[i+1] - ProcBoundaries[i];
}
else
{
recvcounts[i] = TransferCount - ProcBoundaries[i];
}
}
/*
Determine how many elements to send
*/
rowmin = ProcBoundaries[ThisTask];
if (ThisTask != NTasks - 1)
rowmax = ProcBoundaries[ThisTask + 1];
else
rowmax = TransferCount - ProcBoundaries[ThisTask];
MyVector = VectorMalloc(recvcounts[ThisTask]);//VectorMalloc(rowmax - rowmin);
//PrintMatrix(mat, recvcounts[ThisTask], TransferCount);
// Get rowspan elements by exploiting the 1D partition
for (i=0; i < /*rowmax - rowmin*/ recvcounts[ThisTask]; i++)
{
ThisElement = Dot(mat[i], vec, N);
//printf("ThisElement = %f\n", ThisElement);
MyVector[i] = ThisElement;
}
//printf("(min, max) on thread %d = %d, %d\n", ThisTask, rowmin, rowmax);
sendcount = recvcounts[ThisTask];//rowmax - rowmin;
//printf("sendcount[%d] = %d\n", ThisTask, sendcount);
/*
for (i=0; i < NTasks; i++)
{
printf("recvcounts[%d] = %d\n", i, recvcounts[i]);
//printf("sendcount[%d] = %d\n", ThisTask, sendcount);
}*/
MPI_Allgatherv(MyVector, sendcount, MPI_DOUBLE, vec, recvcounts, ProcBoundaries, MPI_DOUBLE, MPI_COMM_WORLD);
//for (i=0; i < N; i++)
// printf("Vector[%d] = %f\n",i, vec[i]);
VectorFree(MyVector, sendcount);
}
int
main(int argc, char *argv[]) {
TRANSFORM *transform = NULL ;
char **av, fname[STRLEN], *gca_fname, *subject_name, *cp ;
int ac, nargs, i, n ;
int msec, minutes, seconds, nsubjects ;
struct timeb start ;
GCA *gca ;
MRI *mri_parc, *mri_T1, *mri_PD ;
FILE *fp ;
/* rkt: check for and handle version tag */
nargs = handle_version_option (argc, argv, "$Id: mri_ca_tissue_parms.c,v 1.8 2011/03/02 00:04:14 nicks Exp $", "$Name: stable5 $");
if (nargs && argc - nargs == 1)
exit (0);
argc -= nargs;
Progname = argv[0] ;
ErrorInit(NULL, NULL, NULL) ;
DiagInit(NULL, NULL, NULL) ;
TimerStart(&start) ;
ac = argc ;
av = argv ;
for ( ; argc > 1 && ISOPTION(*argv[1]) ; argc--, argv++) {
nargs = get_option(argc, argv) ;
argc -= nargs ;
argv += nargs ;
}
if (!strlen(subjects_dir)) /* hasn't been set on command line */
{
cp = getenv("SUBJECTS_DIR") ;
if (!cp)
ErrorExit(ERROR_BADPARM, "%s: SUBJECTS_DIR not defined in environment",
Progname);
strcpy(subjects_dir, cp) ;
if (argc < 3)
usage_exit(1) ;
}
gca_fname = argv[1] ;
nsubjects = argc-2 ;
printf("computing average tissue parameters on %d subject\n",
nsubjects) ;
n = 0 ;
printf("reading GCA from %s...\n", gca_fname) ;
gca = GCAread(gca_fname) ;
for (i = 0 ; i < nsubjects ; i++) {
subject_name = argv[i+2] ;
printf("processing subject %s, %d of %d...\n", subject_name,i+1,
nsubjects);
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, parc_dir) ;
if (DIAG_VERBOSE_ON)
printf("reading parcellation from %s...\n", fname) ;
mri_parc = MRIread(fname) ;
if (!mri_parc)
ErrorExit(ERROR_NOFILE, "%s: could not read parcellation file %s",
Progname, fname) ;
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, T1_name) ;
if (DIAG_VERBOSE_ON)
printf("reading co-registered T1 from %s...\n", fname) ;
mri_T1 = MRIread(fname) ;
if (!mri_T1)
ErrorExit(ERROR_NOFILE, "%s: could not read T1 data from file %s",
Progname, fname) ;
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, PD_name) ;
if (DIAG_VERBOSE_ON)
printf("reading co-registered T1 from %s...\n", fname) ;
mri_PD = MRIread(fname) ;
if (!mri_PD)
ErrorExit(ERROR_NOFILE, "%s: could not read PD data from file %s",
Progname, fname) ;
if (xform_name) {
/* VECTOR *v_tmp, *v_tmp2 ;*/
sprintf(fname, "%s/%s/mri/%s", subjects_dir, subject_name, xform_name) ;
printf("reading xform from %s...\n", fname) ;
transform = TransformRead(fname) ;
if (!transform)
ErrorExit(ERROR_NOFILE, "%s: could not read xform from %s",
Progname, fname) ;
#if 0
v_tmp = VectorAlloc(4,MATRIX_REAL) ;
*MATRIX_RELT(v_tmp,4,1)=1.0 ;
v_tmp2 = MatrixMultiply(lta->xforms[0].m_L, v_tmp, NULL) ;
printf("RAS (0,0,0) -->\n") ;
MatrixPrint(stdout, v_tmp2) ;
#endif
if (transform->type == LINEAR_RAS_TO_RAS) {
MATRIX *m_L ;
m_L = ((LTA *)transform->xform)->xforms[0].m_L ;
MRIrasXformToVoxelXform(mri_parc, mri_T1, m_L,m_L) ;
}
#if 0
v_tmp2 = MatrixMultiply(lta->xforms[0].m_L, v_tmp, v_tmp2) ;
printf("voxel (0,0,0) -->\n") ;
MatrixPrint(stdout, v_tmp2) ;
VectorFree(&v_tmp) ;
VectorFree(&v_tmp2) ;
test(mri_parc, mri_T1, mri_PD, lta->xforms[0].m_L) ;
#endif
}
if (histo_parms)
GCAhistogramTissueStatistics(gca,mri_T1,mri_PD,mri_parc,transform,histo_parms);
#if 0
else
GCAaccumulateTissueStatistics(gca, mri_T1, mri_PD, mri_parc, transform) ;
#endif
MRIfree(&mri_parc) ;
MRIfree(&mri_T1) ;
MRIfree(&mri_PD) ;
}
GCAnormalizeTissueStatistics(gca) ;
if (log_fname) {
printf("writing tissue parameters to %s\n", log_fname) ;
fp = fopen(log_fname, "w") ;
for (n = 1 ; n < MAX_GCA_LABELS ; n++) {
GCA_TISSUE_PARMS *gca_tp ;
gca_tp = &gca->tissue_parms[n] ;
if (gca_tp->total_training <= 0)
continue ;
fprintf(fp, "%d %f %f\n", n, gca_tp->T1_mean, gca_tp->PD_mean) ;
}
fclose(fp) ;
}
if (write_flag)
GCAwrite(gca, gca_fname) ;
GCAfree(&gca) ;
msec = TimerStop(&start) ;
seconds = nint((float)msec/1000.0f) ;
minutes = seconds / 60 ;
seconds = seconds % 60 ;
printf("tissue parameter statistic calculation took %d minutes"
" and %d seconds.\n", minutes, seconds) ;
exit(0) ;
return(0) ;
}
MRI *
add_aseg_structures_outside_ribbon(MRI *mri_src, MRI *mri_aseg, MRI *mri_dst,
int wm_val, int gm_val, int csf_val)
{
VECTOR *v1, *v2 ;
MATRIX *m_vox2vox ;
int x, y, z, xa, ya, za, seg_label, aseg_label ;
if (mri_dst == NULL)
mri_dst = MRIcopy(mri_src, NULL) ;
v1 = VectorAlloc(4, MATRIX_REAL) ;
v2 = VectorAlloc(4, MATRIX_REAL) ;
VECTOR_ELT(v1, 4) = 1.0 ; VECTOR_ELT(v2, 4) = 1.0 ;
m_vox2vox = MRIgetVoxelToVoxelXform(mri_src, mri_aseg) ;
for (x = 0 ; x < mri_dst->width ; x++)
{
V3_X(v1) = x ;
for (y = 0 ; y < mri_dst->height ; y++)
{
V3_Y(v1) = y ;
for (z = 0 ; z < mri_dst->depth ; z++)
{
if (x == Gx && y == Gy && z == Gz)
DiagBreak() ;
seg_label = nint(MRIgetVoxVal(mri_dst, x, y, z, 0)) ;
V3_Z(v1) = z ;
MatrixMultiply(m_vox2vox, v1, v2) ;
xa = (int)(nint(V3_X(v2))) ;
ya = (int)(nint(V3_Y(v2))) ;
za = (int)(nint(V3_Z(v2))) ;
if (xa < 0 || ya < 0 || za < 0 ||
xa >= mri_aseg->width || ya >= mri_aseg->height || za >= mri_aseg->depth)
continue ;
if (xa == Gx && ya == Gy && za == Gz)
DiagBreak() ;
aseg_label = nint(MRIgetVoxVal(mri_aseg, xa, ya, za, 0)) ;
if (seg_label != 0 && !IS_MTL(aseg_label)) // already labeled and not amyg/hippo, skip it
continue ;
switch (aseg_label)
{
case Left_Cerebellum_White_Matter:
case Right_Cerebellum_White_Matter:
case Brain_Stem:
MRIsetVoxVal(mri_dst, x, y, z, 0, wm_val) ;
break ;
case Left_Hippocampus:
case Right_Hippocampus:
case Left_Amygdala:
case Right_Amygdala:
case Left_Cerebellum_Cortex:
case Right_Cerebellum_Cortex:
case Left_Pallidum:
case Right_Pallidum:
case Left_Thalamus_Proper:
case Right_Thalamus_Proper:
case Right_Putamen:
case Left_Putamen:
case Right_Caudate:
case Left_Caudate:
case Left_Accumbens_area:
case Right_Accumbens_area: // remove them from cortex
MRIsetVoxVal(mri_dst, x, y, z, 0, gm_val) ;
break ;
default:
break ;
}
}
}
}
VectorFree(&v1) ; VectorFree(&v2) ; MatrixFree(&m_vox2vox) ;
return(mri_dst) ;
}
int
main(int argc, char *argv[]) {
char **av, *label_name, *vol_name, *out_name ;
int ac, nargs ;
int msec, minutes, seconds, i ;
LABEL *area ;
struct timeb start ;
MRI *mri, *mri_seg ;
Real xw, yw, zw, xv, yv, zv, val;
/* rkt: check for and handle version tag */
nargs = handle_version_option (argc, argv, "$Id: mri_label_vals.c,v 1.16 2015/08/24 18:22:05 fischl Exp $", "$Name: $");
if (nargs && argc - nargs == 1)
exit (0);
argc -= nargs;
Progname = argv[0] ;
ErrorInit(NULL, NULL, NULL) ;
DiagInit(NULL, NULL, NULL) ;
TimerStart(&start) ;
ac = argc ;
av = argv ;
for ( ; argc > 1 && ISOPTION(*argv[1]) ; argc--, argv++) {
nargs = get_option(argc, argv) ;
argc -= nargs ;
argv += nargs ;
}
if (argc < 3)
usage_exit(1) ;
vol_name = argv[1] ;
label_name = argv[2] ;
out_name = argv[3] ;
mri = MRIread(vol_name) ;
if (!mri)
ErrorExit(ERROR_NOFILE, "%s: could not read volume from %s",Progname, vol_name) ;
if (scaleup_flag) {
float scale, fov_x, fov_y, fov_z ;
scale = 1.0/MIN(MIN(mri->xsize, mri->ysize),mri->zsize) ;
fprintf(stderr, "scaling voxel sizes up by %2.2f\n", scale) ;
mri->xsize *= scale ;
mri->ysize *= scale ;
mri->zsize *= scale ;
fov_x = mri->xsize * mri->width;
fov_y = mri->ysize * mri->height;
fov_z = mri->zsize * mri->depth;
mri->xend = fov_x / 2.0;
mri->xstart = -mri->xend;
mri->yend = fov_y / 2.0;
mri->ystart = -mri->yend;
mri->zend = fov_z / 2.0;
mri->zstart = -mri->zend;
mri->fov = (fov_x > fov_y ? (fov_x > fov_z ? fov_x : fov_z) : (fov_y > fov_z ? fov_y : fov_z) );
}
if (segmentation_flag >= 0) {
int x, y, z ;
VECTOR *v_seg, *v_mri ;
MATRIX *m_seg_to_mri ;
v_seg = VectorAlloc(4, MATRIX_REAL) ;
v_mri = VectorAlloc(4, MATRIX_REAL) ;
VECTOR_ELT(v_seg, 4) = 1.0 ;
VECTOR_ELT(v_mri, 4) = 1.0 ;
mri_seg = MRIread(argv[2]) ;
if (!mri_seg)
ErrorExit(ERROR_NOFILE, "%s: could not read volume from %s",Progname, argv[2]) ;
if (erode) {
MRI *mri_tmp ;
mri_tmp = MRIclone(mri_seg, NULL) ;
MRIcopyLabel(mri_seg, mri_tmp, segmentation_flag) ;
while (erode-- > 0)
MRIerode(mri_tmp, mri_tmp) ;
MRIcopy(mri_tmp, mri_seg) ;
MRIfree(&mri_tmp) ;
}
m_seg_to_mri = MRIgetVoxelToVoxelXform(mri_seg, mri) ;
for (x = 0 ; x < mri_seg->width ; x++) {
V3_X(v_seg) = x ;
for (y = 0 ; y < mri_seg->height ; y++) {
V3_Y(v_seg) = y ;
for (z = 0 ; z < mri_seg->depth ; z++) {
V3_Z(v_seg) = z ;
if (MRIvox(mri_seg, x, y, z) == segmentation_flag) {
MatrixMultiply(m_seg_to_mri, v_seg, v_mri) ;
xv = V3_X(v_mri) ;
yv = V3_Y(v_mri) ;
zv = V3_Z(v_mri) ;
MRIsampleVolumeType(mri, xv, yv, zv, &val, SAMPLE_NEAREST);
#if 0
if (val < .000001) {
val *= 1000000;
printf("%f*0.000001\n", val);
} else
#endif
if (coords)
printf("%2.1f %2.1f %2.1f %f\n", xv, yv, zv, val);
else
printf("%f\n", val);
}
}
}
}
MatrixFree(&m_seg_to_mri) ;
VectorFree(&v_seg) ;
VectorFree(&v_mri) ;
} else {
if (cras == 1)
fprintf(stderr,"using the label coordinates to be c_(r,a,s) != 0.\n");
if (surface_dir) {
MRI_SURFACE *mris ;
char fname[STRLEN] ;
sprintf(fname, "%s/%s.white", surface_dir, hemi) ;
mris = MRISread(fname) ;
if (mris == NULL)
ErrorExit(ERROR_NOFILE, "%s: could not read surface file %s...\n", Progname,fname) ;
sprintf(fname, "%s/%s.thickness", surface_dir, hemi) ;
if (MRISreadCurvatureFile(mris, fname) != NO_ERROR)
ErrorExit(ERROR_BADPARM, "%s: could not read thickness file %s...\n", Progname,fname) ;
if (annot_prefix) /* read an annotation in and print vals in it */
{
#define MAX_ANNOT 10000
int vno, annot_counts[MAX_ANNOT], index ;
VERTEX *v ;
Real xw, yw, zw, xv, yv, zv, val ;
float annot_means[MAX_ANNOT] ;
FILE *fp ;
memset(annot_means, 0, sizeof(annot_means)) ;
memset(annot_counts, 0, sizeof(annot_counts)) ;
if (MRISreadAnnotation(mris, label_name) != NO_ERROR)
ErrorExit(ERROR_BADPARM, "%s: could not read annotation file %s...\n", Progname,fname) ;
if (mris->ct == NULL)
ErrorExit(ERROR_BADPARM, "%s: annot file does not contain a color table, specifiy one with -t ", Progname);
for (vno = 0 ; vno < mris->nvertices ; vno++) {
v = &mris->vertices[vno] ;
if (v->ripflag)
continue ;
CTABfindAnnotation(mris->ct, v->annotation, &index) ;
if (index >= 0 && index < mris->ct->nentries) {
annot_counts[index]++ ;
xw = v->x + v->curv*.5*v->nx ;
yw = v->y + v->curv*.5*v->ny ;
zw = v->z + v->curv*.5*v->nz ;
if (cras == 1)
MRIworldToVoxel(mri, xw, yw, zw, &xv, &yv, &zv) ;
else
MRIsurfaceRASToVoxel(mri, xw, yw, zw, &xv, &yv, &zv);
MRIsampleVolume(mri, xv, yv, zv, &val) ;
annot_means[index] += val ;
sprintf(fname, "%s-%s-%s.dat", annot_prefix, hemi, mris->ct->entries[index]->name) ;
fp = fopen(fname, "a") ;
fprintf(fp, "%f\n", val) ;
fclose(fp) ;
}
}
}
else /* read label in and print vals in it */
{
area = LabelRead(NULL, label_name) ;
if (!area)
ErrorExit(ERROR_NOFILE, "%s: could not read label from %s",Progname, label_name) ;
}
} else {
area = LabelRead(NULL, label_name) ;
if (!area)
ErrorExit(ERROR_NOFILE, "%s: could not read label from %s",Progname, label_name) ;
for (i = 0 ; i < area->n_points ; i++) {
xw = area->lv[i].x ;
yw = area->lv[i].y ;
zw = area->lv[i].z ;
if (cras == 1)
MRIworldToVoxel(mri, xw, yw, zw, &xv, &yv, &zv) ;
else
MRIsurfaceRASToVoxel(mri, xw, yw, zw, &xv, &yv, &zv);
MRIsampleVolumeType(mri, xv, yv, zv, &val, SAMPLE_NEAREST);
#if 0
if (val < .000001) {
val *= 1000000;
printf("%f*0.000001\n", val);
} else
#endif
printf("%f\n", val);
}
}
}
msec = TimerStop(&start) ;
seconds = nint((float)msec/1000.0f) ;
minutes = seconds / 60 ;
seconds = seconds % 60 ;
if (DIAG_VERBOSE_ON)
fprintf(stderr, "label value extractiong took %d minutes and %d seconds.\n",
minutes, seconds) ;
exit(0) ;
return(0) ;
}
static MATRIX *
pca_matrix(MATRIX *m_in_evectors, double in_means[3],
MATRIX *m_ref_evectors, double ref_means[3]) {
float dx, dy, dz ;
MATRIX *mRot, *m_in_T, *mOrigin, *m_L, *m_R, *m_T, *m_tmp ;
double x_angle, y_angle, z_angle, r11, r21, r31, r32, r33, cosy ;
int row, col ;
m_in_T = MatrixTranspose(m_in_evectors, NULL) ;
mRot = MatrixMultiply(m_ref_evectors, m_in_T, NULL) ;
r11 = mRot->rptr[1][1] ;
r21 = mRot->rptr[2][1] ;
r31 = mRot->rptr[3][1] ;
r32 = mRot->rptr[3][2] ;
r33 = mRot->rptr[3][3] ;
y_angle = atan2(-r31, sqrt(r11*r11+r21*r21)) ;
cosy = cos(y_angle) ;
z_angle = atan2(r21 / cosy, r11 / cosy) ;
x_angle = atan2(r32 / cosy, r33 / cosy) ;
#define MAX_ANGLE (RADIANS(30))
if (fabs(x_angle) > MAX_ANGLE || fabs(y_angle) > MAX_ANGLE ||
fabs(z_angle) > MAX_ANGLE) {
MatrixFree(&m_in_T) ;
MatrixFree(&mRot) ;
printf("eigenvector swap detected: ignoring PCA...\n") ;
return(MatrixIdentity(4, NULL)) ;
}
mOrigin = VectorAlloc(3, MATRIX_REAL) ;
mOrigin->rptr[1][1] = ref_means[0] ;
mOrigin->rptr[2][1] = ref_means[1] ;
mOrigin->rptr[3][1] = ref_means[2] ;
printf("reference volume center of mass at (%2.1f,%2.1f,%2.1f)\n",
ref_means[0], ref_means[1], ref_means[2]) ;
printf("input volume center of mass at (%2.1f,%2.1f,%2.1f)\n",
in_means[0], in_means[1], in_means[2]) ;
dx = ref_means[0] - in_means[0] ;
dy = ref_means[1] - in_means[1] ;
dz = ref_means[2] - in_means[2] ;
printf("translating volume by %2.1f, %2.1f, %2.1f\n",
dx, dy, dz) ;
printf("rotating volume by (%2.2f, %2.2f, %2.2f)\n",
DEGREES(x_angle), DEGREES(y_angle), DEGREES(z_angle)) ;
/* build full rigid transform */
m_R = MatrixAlloc(4,4,MATRIX_REAL) ;
m_T = MatrixAlloc(4,4,MATRIX_REAL) ;
for (row = 1 ; row <= 3 ; row++) {
for (col = 1 ; col <= 3 ; col++) {
*MATRIX_RELT(m_R,row,col) = *MATRIX_RELT(mRot, row, col) ;
}
*MATRIX_RELT(m_T,row,row) = 1.0 ;
}
*MATRIX_RELT(m_R, 4, 4) = 1.0 ;
/* translation so that origin is at ref eigenvector origin */
dx = -ref_means[0] ;
dy = -ref_means[1] ;
dz = -ref_means[2] ;
*MATRIX_RELT(m_T, 1, 4) = dx ;
*MATRIX_RELT(m_T, 2, 4) = dy ;
*MATRIX_RELT(m_T, 3, 4) = dz ;
*MATRIX_RELT(m_T, 4, 4) = 1 ;
m_tmp = MatrixMultiply(m_R, m_T, NULL) ;
*MATRIX_RELT(m_T, 1, 4) = -dx ;
*MATRIX_RELT(m_T, 2, 4) = -dy ;
*MATRIX_RELT(m_T, 3, 4) = -dz ;
MatrixMultiply(m_T, m_tmp, m_R) ;
/* now apply translation to take in centroid to ref centroid */
dx = ref_means[0] - in_means[0] ;
dy = ref_means[1] - in_means[1] ;
dz = ref_means[2] - in_means[2] ;
*MATRIX_RELT(m_T, 1, 4) = dx ;
*MATRIX_RELT(m_T, 2, 4) = dy ;
*MATRIX_RELT(m_T, 3, 4) = dz ;
*MATRIX_RELT(m_T, 4, 4) = 1 ;
m_L = MatrixMultiply(m_R, m_T, NULL) ;
if (Gdiag & DIAG_SHOW && DIAG_VERBOSE_ON) {
printf("m_T:\n") ;
MatrixPrint(stdout, m_T) ;
printf("m_R:\n") ;
MatrixPrint(stdout, m_R) ;
printf("m_L:\n") ;
MatrixPrint(stdout, m_L) ;
}
MatrixFree(&m_R) ;
MatrixFree(&m_T) ;
MatrixFree(&mRot) ;
VectorFree(&mOrigin) ;
return(m_L) ;
}
static void computeCurvature(VerTex *vertex,int nvt,FaCe *face, int nfc,int* ref_tab,int nb,float* curv)
{
int n,m,reference;
VECTOR *v_n, *v_e1,*v_e2,*v;
float nx,ny,nz,area,dx,dy,dz,y,r2,u1,u2,YR2,R4;
v_n=VectorAlloc(3,MATRIX_REAL);
v_e1=VectorAlloc(3,MATRIX_REAL);
v_e2=VectorAlloc(3,MATRIX_REAL);
v=VectorAlloc(3,MATRIX_REAL);
for (n=0; n<nb; n++)
{
reference=ref_tab[n];
//first need to compute normal
nx=ny=nz=area=0;
for (m=0; m<vertex[reference].fnum; m++)
{
nx+=face[vertex[reference].f[m]].nx*face[vertex[reference].f[m]].area;
ny+=face[vertex[reference].f[m]].ny*face[vertex[reference].f[m]].area;
nz+=face[vertex[reference].f[m]].nz*face[vertex[reference].f[m]].area;
area+=face[vertex[reference].f[m]].area;
}
nx/=area;
ny/=area;
nz/=area;
VECTOR_LOAD(v_n,nx,ny,nz);
//now need to compute the tangent plane!
VECTOR_LOAD(v,ny,nz,nx);
V3_CROSS_PRODUCT(v_n,v,v_e1);
if ((V3_LEN_IS_ZERO(v_e1)))
{
if (nz!=0)
VECTOR_LOAD(v,ny,-nz,nx)
else if (ny!=0)
VECTOR_LOAD(v,-ny,nz,nx)
else
VECTOR_LOAD(v,ny,nz,-nx);
V3_CROSS_PRODUCT(v_n,v,v_e1);
}
V3_CROSS_PRODUCT(v_n,v_e1,v_e2);
V3_NORMALIZE(v_e1,v_e1);
V3_NORMALIZE(v_e2,v_e2);
//finally compute curvature by fitting a 1-d quadratic r->a*r*r: curv=2*a
for (YR2=0,R4=0,m=0; m<vertex[reference].vnum; m++)
{
dx=vertex[vertex[reference].v[m]].x-vertex[reference].x;
dy=vertex[vertex[reference].v[m]].y-vertex[reference].y;
dz=vertex[vertex[reference].v[m]].z-vertex[reference].z;
VECTOR_LOAD(v,dx,dy,dz);
y=V3_DOT(v,v_n);
u1=V3_DOT(v_e1,v);
u2=V3_DOT(v_e2,v);
r2=u1*u1+u2*u2;
YR2+=y*r2;
R4+=r2*r2;
}
curv[n]=2*YR2/R4;
}
VectorFree(&v);
VectorFree(&v_n);
VectorFree(&v_e1);
VectorFree(&v_e2);
}
static int
update_histograms(MRI_SURFACE *mris, MRI_SURFACE *mris_avg, float ***histograms, int nbins) {
int vno, vno2, vno_avg ;
double volume_dist, surface_dist, circumference, angle ;
VERTEX *v1, *v2 ;
VECTOR *vec1, *vec2 ;
MHT *mht ;
float **histogram, min_dist ;
mht = MHTfillVertexTableRes(mris_avg, NULL, CURRENT_VERTICES, 2.0) ;
vec1 = VectorAlloc(3, MATRIX_REAL) ;
vec2 = VectorAlloc(3, MATRIX_REAL) ;
v1 = &mris->vertices[0] ;
VECTOR_LOAD(vec1, v1->cx, v1->cy, v1->cz) ; /* radius vector */
circumference = M_PI * 2.0 * V3_LEN(vec1) ;
MRISclearMarks(mris_avg) ;
#if 0
for (vno = 0 ; vno < mris->nvertices ; vno++) {
if ((vno % 1000) == 0) {
printf("\r%d of %d ", vno, mris->nvertices) ;
fflush(stdout) ;
}
v1 = &mris->vertices[vno] ;
VECTOR_LOAD(vec1, v1->cx, v1->cy, v1->cz) ; /* radius vector */
vno_avg = MHTfindClosestVertexNo(mht, mris_avg, v1, &min_dist) ; /* which histogram to increment */
if (vno_avg < 0)
continue ;
if (vno_avg == Gdiag_no)
DiagBreak() ;
histogram = histograms[vno_avg] ;
mris_avg->vertices[vno_avg].marked = 1 ;
for (vno2 = 0 ; vno2 < mris->nvertices ; vno2++) {
if (vno2 == vno)
continue ;
v2 = &mris->vertices[vno2] ;
VECTOR_LOAD(vec2, v2->cx, v2->cy, v2->cz) ; /* radius vector */
volume_dist = sqrt(SQR(v1->origx-v2->origx)+SQR(v1->origy-v2->origy)+SQR(v1->origz-v2->origz)) ;
if (nint(volume_dist) >= nbins || nint(volume_dist) < 0)
continue ;
angle = fabs(Vector3Angle(vec1, vec2)) ;
surface_dist = circumference * angle / (2.0 * M_PI) ;
if (surface_dist > nbins*MAX_SURFACE_SCALE)
surface_dist = nbins*MAX_SURFACE_SCALE ;
if (surface_dist < 1)
surface_dist = 1 ;
histogram[nint(volume_dist)][nint(surface_dist)]++ ;
if (mht->buckets[0][0] != NULL)
DiagBreak() ;
}
}
MHTfree(&mht) ;
#endif
/* map back ones that were missed */
/* printf("\nfilling holes in mapping\n") ;*/
mht = MHTfillVertexTableRes(mris, NULL, CURRENT_VERTICES, 2.0) ;
for (vno_avg = 0 ; vno_avg < mris_avg->nvertices ; vno_avg++) {
if (mris_avg->vertices[vno_avg].marked > 0)
continue ;
if ((vno_avg % 1000) == 0) {
printf("\r%d of %d ", vno_avg, mris_avg->nvertices) ;
fflush(stdout) ;
}
vno = MHTfindClosestVertexNo(mht, mris, &mris_avg->vertices[vno_avg], &min_dist) ;
if (vno < 0)
continue ;
v1 = &mris->vertices[vno] ;
VECTOR_LOAD(vec1, v1->cx, v1->cy, v1->cz) ; /* radius vector */
if (vno_avg < 0)
continue ;
if (vno_avg == Gdiag_no)
DiagBreak() ;
histogram = histograms[vno_avg] ;
mris_avg->vertices[vno_avg].marked = 1 ;
for (vno2 = 0 ; vno2 < mris->nvertices ; vno2++) {
if (vno2 == vno)
continue ;
v2 = &mris->vertices[vno2] ;
VECTOR_LOAD(vec2, v2->cx, v2->cy, v2->cz) ; /* radius vector */
volume_dist = sqrt(SQR(v1->origx-v2->origx)+SQR(v1->origy-v2->origy)+SQR(v1->origz-v2->origz)) ;
if (nint(volume_dist) >= nbins || nint(volume_dist) < 0)
continue ;
angle = fabs(Vector3Angle(vec1, vec2)) ;
surface_dist = circumference * angle / (2.0 * M_PI) ;
if (surface_dist > nbins*MAX_SURFACE_SCALE)
surface_dist = nbins*MAX_SURFACE_SCALE ;
if (surface_dist < 1)
surface_dist = 1 ;
histogram[nint(volume_dist)][nint(surface_dist)]++ ;
}
}
MHTfree(&mht) ;
printf("\n") ;
VectorFree(&vec1) ;
VectorFree(&vec2) ;
return(NO_ERROR) ;
}