FREE(x);
if (xsplines){
for (i = 0; i < ne; i++){
- if (xsplines[i]) FREE(xsplines[i]);
+ FREE(xsplines[i]);
}
FREE(xsplines);
}
$$ = exnewnode(expr.program, $1->index, 1, INTEGER, $3, exnewnode(expr.program, DEFAULT, 1, 0, sw->defcase, sw->firstcase));
expr.swstate = expr.swstate->prev;
- if (sw->base)
- free(sw->base);
+ free(sw->base);
if (sw != &swstate)
free(sw);
expr.declare = 0;
relative_position_constraints data;
if (!d) return;
data = (relative_position_constraints) d;
- if (data->irn) FREE(data->irn);
- if (data->jcn) FREE(data->jcn);
- if (data->val) FREE(data->val);
+ FREE(data->irn);
+ FREE(data->jcn);
+ FREE(data->val);
/* other stuff inside relative_position_constraints is assed back to the user hence no need to deallocator*/
FREE(d);
}
goto RETURN;
}
RETURN:
- if (matching) FREE(matching);
- if (vset) FREE(vset);
- if (irn) FREE(irn);
- if (jcn) FREE(jcn);
- if (val) FREE(val);
+ FREE(matching);
+ FREE(vset);
+ FREE(irn);
+ FREE(jcn);
+ FREE(val);
if (B) SparseMatrix_delete(B);
- if(cluster) FREE(cluster);
- if(clusterp) FREE(clusterp);
+ FREE(cluster);
+ FREE(clusterp);
}
void Multilevel_coarsen(SparseMatrix A, SparseMatrix *cA, SparseMatrix D, SparseMatrix *cD, real *node_wgt, real **cnode_wgt,
if (!sm) return;
if (sm->Lw) SparseMatrix_delete(sm->Lw);
if (sm->Lwd) SparseMatrix_delete(sm->Lwd);
- if (sm->lambda) FREE(sm->lambda);
+ FREE(sm->lambda);
if (sm->data) sm->data_deallocator(sm->data);
FREE(sm);
}
free(pos);
SparseMatrix_delete (A);
if (D) SparseMatrix_delete (D);
- if (edge_label_nodes) FREE(edge_label_nodes);
+ FREE(edge_label_nodes);
}
static int
oned_optimizer_delete(qtree_level_optimizer);
ctrl->max_qtree_level = max_qtree_level;
}
- if (xold) FREE(xold);
+ FREE(xold);
if (A != A0) SparseMatrix_delete(A);
- if (f) FREE(f);
- if (center) FREE(center);
- if (supernode_wgts) FREE(supernode_wgts);
- if (distances) FREE(distances);
+ FREE(f);
+ FREE(center);
+ FREE(supernode_wgts);
+ FREE(distances);
FREE(force);
-
}
oned_optimizer_delete(qtree_level_optimizer);
ctrl->max_qtree_level = max_qtree_level;
}
- if (xold) FREE(xold);
+ FREE(xold);
if (A != A0) SparseMatrix_delete(A);
- if (f) FREE(f);
- if (center) FREE(center);
- if (supernode_wgts) FREE(supernode_wgts);
- if (distances) FREE(distances);
-
+ FREE(f);
+ FREE(center);
+ FREE(supernode_wgts);
+ FREE(distances);
}
static void scale_coord(int n, int dim, real *x, int *id, int *jd, real *d, real dj){
if (ctrl->beautify_leaves) beautify_leaves(dim, A, x);
RETURN:
- if (xold) FREE(xold);
+ FREE(xold);
if (A != A0) SparseMatrix_delete(A);
- if (f) FREE(f);
- if (center) FREE(center);
- if (supernode_wgts) FREE(supernode_wgts);
- if (distances) FREE(distances);
-
+ FREE(f);
+ FREE(center);
+ FREE(supernode_wgts);
+ FREE(distances);
}
if (ctrl->beautify_leaves) beautify_leaves(dim, A, x);
RETURN:
- if (xold) FREE(xold);
+ FREE(xold);
if (A != A0) SparseMatrix_delete(A);
- if (f) FREE(f);
- if (center) FREE(center);
- if (supernode_wgts) FREE(supernode_wgts);
- if (distances) FREE(distances);
-
+ FREE(f);
+ FREE(center);
+ FREE(supernode_wgts);
+ FREE(distances);
}
FREE(J);
FREE(val);
}
- if (valD) FREE(valD);
+ FREE(valD);
return A;
}
do {
next = head->next;
if (head->data) linklist_deallocator(head->data);
- if (head) FREE(head);
+ FREE(head);
head = next;
} while (head);
do {
next = head->next;
if (head->data) linklist_deallocator(head->data);
- if (head) FREE(head);
+ FREE(head);
head = next;
} while (head);
dim = q->dim;
FREE(q->center);
FREE(q->average);
- if (q->data) FREE(q->data);
+ FREE(q->data);
if (q->qts){
for (i = 0; i < 1<<dim; i++){
QuadTree_delete(q->qts[i]);
/* return a sparse matrix skeleton with row dimension m and storage nz. If nz == 0,
only row pointers are allocated */
if (!A) return;
- if (A->ia) FREE(A->ia);
- if (A->ja) FREE(A->ja);
- if (A->a) FREE(A->a);
+ FREE(A->ia);
+ FREE(A->ja);
+ FREE(A->a);
FREE(A);
}
static void SparseMatrix_print_csr(char *c, SparseMatrix A){
C->nz = nz;
RETURN:
- if (mask) FREE(mask);
+ FREE(mask);
return C;
}
}
if (A != A0) SparseMatrix_delete(A);
- if (levelset_ptr) FREE(levelset_ptr);
+ FREE(levelset_ptr);
FREE(mask);
}
B = SparseMatrix_from_coordinate_arrays(nz, m + n, m + n, irn, jcn, val, type, A->size);
SparseMatrix_set_symmetric(B);
SparseMatrix_set_pattern_symmetric(B);
- if (irn) FREE(irn);
- if (jcn) FREE(jcn);
- if (val) FREE(val);
+ FREE(irn);
+ FREE(jcn);
+ FREE(val);
return B;
-
}
SparseMatrix SparseMatrix_to_square_matrix(SparseMatrix A, int bipartite_options){
real *a;
int i;
- if (A->a) FREE(A->a);
+ FREE(A->a);
A->a = MALLOC(sizeof(real)*((size_t)A->nz));
a = (real*) (A->a);
for (i = 0; i < A->nz; i++) a[i] = 1.;
}
}
- if (levelset_ptr) FREE(levelset_ptr);
- if (levelset) FREE(levelset);
- if (mask) FREE(mask);
+ FREE(levelset_ptr);
+ FREE(levelset);
+ FREE(mask);
if (D != D0) SparseMatrix_delete(D);
- if (list) FREE(list);
+ FREE(list);
return flag;
-
}
SparseMatrix SparseMatrix_distance_matrix_khops(int khops, SparseMatrix D0, int weighted){
C = SparseMatrix_from_coordinate_format(B);
SparseMatrix_delete(B);
- if (levelset_ptr) FREE(levelset_ptr);
- if (levelset) FREE(levelset);
- if (mask) FREE(mask);
- if (dist) FREE(dist);
+ FREE(levelset_ptr);
+ FREE(levelset);
+ FREE(mask);
+ FREE(dist);
if (D != D0) SparseMatrix_delete(D);
- if (list) FREE(list);
+ FREE(list);
/* I can not find a reliable way to make the matrix symmetric. Right now I use a mask array to
limit consider of only nodes with in k hops, but even this is not symmetric. e.g.,
. 10 10 10 10