int ML_Epetra::MultiLevelPreconditioner::SetupCoordinates()
{
ML* ml_ptr = 0;
int NumDimensions;
double* in_x_coord = 0;
double* in_y_coord = 0;
double* in_z_coord = 0;
// Check first for node coordinates, then for edge coordinates
for (int ii=0; ii<2; ii++)
{
switch (ii) {
case 0:
ml_ptr = ml_;
//??else ml_ptr = ml_;
in_x_coord = List_.get("x-coordinates", (double *)0);
in_y_coord = List_.get("y-coordinates", (double *)0);
in_z_coord = List_.get("z-coordinates", (double *)0);
break;
case 1:
if (AMGSolver_ == ML_MAXWELL) {
ml_ptr = ml_nodes_;
in_x_coord = List_.get("node: x-coordinates", (double *)0);
in_y_coord = List_.get("node: y-coordinates", (double *)0);
in_z_coord = List_.get("node: z-coordinates", (double *)0);
}
else {
in_x_coord = NULL;
in_y_coord = NULL;
in_z_coord = NULL;
}
break;
}
NumDimensions = 0;
if (!(in_x_coord == 0 && in_y_coord == 0 && in_z_coord == 0))
{
ML_Aggregate_Viz_Stats *grid_info =
(ML_Aggregate_Viz_Stats *) ml_ptr->Grid[LevelID_[0]].Grid;
ML_Operator* AAA = &(ml_ptr->Amat[LevelID_[0]]);
int n = AAA->invec_leng, Nghost = 0;
if (AAA->getrow->pre_comm)
{
if (AAA->getrow->pre_comm->total_rcv_length <= 0)
ML_CommInfoOP_Compute_TotalRcvLength(AAA->getrow->pre_comm);
Nghost = AAA->getrow->pre_comm->total_rcv_length;
}
std::vector<double> tmp(Nghost + n);
for (int i = 0 ; i < Nghost + n ; ++i)
tmp[i] = 0.0;
n /= NumPDEEqns_;
Nghost /= NumPDEEqns_;
if (in_x_coord)
{
NumDimensions++;
double* x_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_x_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
x_coord[i] = tmp[i * NumPDEEqns_];
grid_info->x = x_coord;
}
if (in_y_coord)
{
NumDimensions++;
double* y_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_y_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
y_coord[i] = tmp[i * NumPDEEqns_];
grid_info->y = y_coord;
}
if (in_z_coord)
{
NumDimensions++;
double* z_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_z_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
z_coord[i] = tmp[i * NumPDEEqns_];
grid_info->z = z_coord;
}
grid_info->Ndim = NumDimensions;
} // if (!(in_x_coord == 0 && in_y_coord == 0 && in_z_coord == 0))
} //for (int ii=0; ii<2; ii++)
return(0);
}
// ================================================ ====== ==== ==== == =
// Copied from ml_agg_genP.c
static void ML_Init_Aux(ML_Operator* A, Teuchos::ParameterList &List) {
int i, j, n, count, num_PDEs, BlockRow, BlockCol;
double threshold;
int* columns;
double* values;
int allocated, entries = 0;
int N_dimensions;
int DiagID;
double DiagValue;
int** filter;
double dist;
double *LaplacianDiag;
int Nghost;
// Boundary exchange the coords
double *x_coord=0, *y_coord=0, *z_coord=0;
RefMaxwell_SetupCoordinates(A,List,x_coord,y_coord,z_coord);
int dim=(x_coord!=0) + (y_coord!=0) + (z_coord!=0);
/* Sanity Checks */
if(dim == 0 || ((!x_coord && (y_coord || z_coord)) || (x_coord && !y_coord && z_coord))){
std::cerr<<"Error: Coordinates not defined. This is necessary for aux aggregation (found "<<dim<<" coordinates).\n";
exit(-1);
}
num_PDEs = A->num_PDEs;
N_dimensions = dim;
threshold = A->aux_data->threshold;
ML_Operator_AmalgamateAndDropWeak(A, num_PDEs, 0.0);
n = A->invec_leng;
Nghost = ML_CommInfoOP_Compute_TotalRcvLength(A->getrow->pre_comm);
LaplacianDiag = (double *) ML_allocate((A->getrow->Nrows+Nghost+1)*
sizeof(double));
filter = (int**) ML_allocate(sizeof(int*) * n);
allocated = 128;
columns = (int *) ML_allocate(allocated * sizeof(int));
values = (double *) ML_allocate(allocated * sizeof(double));
for (i = 0 ; i < n ; ++i) {
BlockRow = i;
DiagID = -1;
DiagValue = 0.0;
ML_get_matrix_row(A,1,&i,&allocated,&columns,&values, &entries,0);
for (j = 0; j < entries; j++) {
BlockCol = columns[j];
if (BlockRow != BlockCol) {
dist = 0.0;
switch (N_dimensions) {
case 3:
dist += (z_coord[BlockRow] - z_coord[BlockCol]) * (z_coord[BlockRow] - z_coord[BlockCol]);
case 2:
dist += (y_coord[BlockRow] - y_coord[BlockCol]) * (y_coord[BlockRow] - y_coord[BlockCol]);
case 1:
dist += (x_coord[BlockRow] - x_coord[BlockCol]) * (x_coord[BlockRow] - x_coord[BlockCol]);
}
if (dist == 0.0) {
printf("node %d = %e ", i, x_coord[BlockRow]);
if (N_dimensions > 1) printf(" %e ", y_coord[BlockRow]);
if (N_dimensions > 2) printf(" %e ", z_coord[BlockRow]);
printf("\n");
printf("node %d = %e ", j, x_coord[BlockCol]);
if (N_dimensions > 1) printf(" %e ", y_coord[BlockCol]);
if (N_dimensions > 2) printf(" %e ", z_coord[BlockCol]);
printf("\n");
printf("Operator has inlen = %d and outlen = %d\n",
A->invec_leng, A->outvec_leng);
}
dist = 1.0 / dist;
DiagValue += dist;
}
else if (columns[j] == i) {
DiagID = j;
}
}
if (DiagID == -1) {
fprintf(stderr, "ERROR: matrix has no diagonal!\n"
"ERROR: (file %s, line %d)\n",
__FILE__, __LINE__);
exit(EXIT_FAILURE);
}
LaplacianDiag[BlockRow] = DiagValue;
}
if ( A->getrow->pre_comm != NULL )
ML_exchange_bdry(LaplacianDiag,A->getrow->pre_comm,A->getrow->Nrows,
A->comm, ML_OVERWRITE,NULL);
for (i = 0 ; i < n ; ++i) {
BlockRow = i;
ML_get_matrix_row(A,1,&i,&allocated,&columns,&values, &entries,0);
for (j = 0; j < entries; j++) {
BlockCol = columns[j];
if (BlockRow != BlockCol) {
dist = 0.0;
switch (N_dimensions) {
case 3:
dist += (z_coord[BlockRow] - z_coord[BlockCol]) * (z_coord[BlockRow] - z_coord[BlockCol]);
case 2:
dist += (y_coord[BlockRow] - y_coord[BlockCol]) * (y_coord[BlockRow] - y_coord[BlockCol]);
case 1:
dist += (x_coord[BlockRow] - x_coord[BlockCol]) * (x_coord[BlockRow] - x_coord[BlockCol]);
}
dist = 1.0 / dist;
values[j] = dist;
}
}
count = 0;
for (j = 0 ; j < entries ; ++j) {
if ( (i != columns[j]) &&
(values[j]*values[j] <
LaplacianDiag[BlockRow]*LaplacianDiag[columns[j]]*threshold*threshold)){
columns[count++] = columns[j];
}
}
/* insert the rows */
filter[BlockRow] = (int*) ML_allocate(sizeof(int) * (count + 1));
filter[BlockRow][0] = count;
for (j = 0 ; j < count ; ++j)
filter[BlockRow][j + 1] = columns[j];
}
ML_free(columns);
ML_free(values);
ML_free(LaplacianDiag);
ML_Operator_UnAmalgamateAndDropWeak(A, num_PDEs, 0.0);
A->aux_data->aux_func_ptr = A->getrow->func_ptr;
A->getrow->func_ptr = ML_Aux_Getrow;
A->aux_data->filter = filter;
A->aux_data->filter_size = n;
// Cleanup
ML_free(x_coord);
ML_free(y_coord);
ML_free(z_coord);
}
// ======================================================================
int ML_Operator_Add2(ML_Operator *A, ML_Operator *B, ML_Operator *C,
int matrix_type, double scalarA, double scalarB)
{
int A_allocated = 0, *A_bindx = NULL, B_allocated = 0, *B_bindx = NULL;
double *A_val = NULL, *B_val = NULL, *hashed_vals;
int i, A_length, B_length, *hashed_inds;
int max_nz_per_row = 0, min_nz_per_row=1e6, j;
int hash_val, index_length;
int *columns, *rowptr, nz_ptr, hash_used, global_col;
double *values;
struct ML_CSR_MSRdata *temp;
int *A_gids, *B_gids;
int max_per_proc;
#ifdef ML_WITH_EPETRA
int count;
#endif
if (A->getrow == NULL)
pr_error("ML_Operator_Add: A does not have a getrow function.\n");
if (B->getrow == NULL)
pr_error("ML_Operator_Add: B does not have a getrow function.\n");
if (A->getrow->Nrows != B->getrow->Nrows) {
printf("ML_Operator_Add: Can not add, two matrices do not have the same");
printf(" number of rows %d vs %d",A->getrow->Nrows,B->getrow->Nrows);
exit(1);
}
if (A->invec_leng != B->invec_leng) {
printf("ML_Operator_Add: Can not add, two matrices do not have the same");
printf(" number of columns %d vs %d",A->getrow->Nrows,B->getrow->Nrows);
exit(1);
}
/* let's just count some things */
index_length = A->invec_leng + 1;
if (A->getrow->pre_comm != NULL) {
ML_CommInfoOP_Compute_TotalRcvLength(A->getrow->pre_comm);
index_length += A->getrow->pre_comm->total_rcv_length;
}
if (B->getrow->pre_comm != NULL) {
ML_CommInfoOP_Compute_TotalRcvLength(B->getrow->pre_comm);
index_length += B->getrow->pre_comm->total_rcv_length;
}
ML_create_unique_col_id(A->invec_leng, &A_gids, A->getrow->pre_comm,
&max_per_proc,A->comm);
ML_create_unique_col_id(B->invec_leng, &B_gids, B->getrow->pre_comm,
&max_per_proc,B->comm);
hashed_inds = (int *) ML_allocate(sizeof(int)*index_length);
hashed_vals = (double *) ML_allocate(sizeof(double)*index_length);
for (i = 0; i < index_length; i++) hashed_inds[i] = -1;
for (i = 0; i < index_length; i++) hashed_vals[i] = 0.;
nz_ptr = 0;
for (i = 0 ; i < A->getrow->Nrows; i++) {
hash_used = 0;
ML_get_matrix_row(A, 1, &i, &A_allocated, &A_bindx, &A_val,
&A_length, 0);
for (j = 0; j < A_length; j++) {
global_col = A_gids[A_bindx[j]];
ML_hash_it(global_col, hashed_inds, index_length,&hash_used,&hash_val);
hashed_inds[hash_val] = global_col;
hashed_vals[hash_val] += scalarA * A_val[j];
A_bindx[j] = hash_val;
}
ML_get_matrix_row(B, 1, &i, &B_allocated, &B_bindx, &B_val,
&B_length, 0);
for (j = 0; j < B_length; j++) {
global_col = B_gids[B_bindx[j]];
ML_hash_it(global_col, hashed_inds, index_length,&hash_used, &hash_val);
hashed_inds[hash_val] = global_col;
hashed_vals[hash_val] += scalarB*B_val[j];
B_bindx[j] = hash_val;
}
for (j = 0; j < A_length; j++) {
nz_ptr++;
hashed_inds[A_bindx[j]] = -1;
hashed_vals[A_bindx[j]] = 0.;
}
for (j = 0; j < B_length; j++) {
if (hashed_inds[B_bindx[j]] != -1) {
nz_ptr++;
hashed_inds[B_bindx[j]] = -1;
hashed_vals[B_bindx[j]] = 0.;
}
}
}
nz_ptr++;
columns = 0;
values = 0;
rowptr = (int *) ML_allocate(sizeof(int)*(A->outvec_leng+1));
if (matrix_type == ML_CSR_MATRIX) {
columns= (int *) ML_allocate(sizeof(int)*nz_ptr);
values = (double *) ML_allocate(sizeof(double)*nz_ptr);
}
#ifdef ML_WITH_EPETRA
else if (matrix_type == ML_EpetraCRS_MATRIX) {
columns= (int *) ML_allocate(sizeof(int)*(index_length+1));
values = (double *) ML_allocate(sizeof(double)*(index_length+1));
}
#endif
else {
pr_error("ML_Operator_Add: Unknown matrix type\n");
}
nz_ptr = 0;
rowptr[0] = 0;
for (i = 0 ; i < A->getrow->Nrows; i++) {
hash_used = 0;
ML_get_matrix_row(A, 1, &i, &A_allocated, &A_bindx, &A_val,
&A_length, 0);
for (j = 0; j < A_length; j++) {
global_col = A_gids[A_bindx[j]];
ML_hash_it(global_col, hashed_inds, index_length,&hash_used, &hash_val);
hashed_inds[hash_val] = global_col;
hashed_vals[hash_val] += scalarA * A_val[j];
A_bindx[j] = hash_val;
}
ML_get_matrix_row(B, 1, &i, &B_allocated, &B_bindx, &B_val,
&B_length, 0);
for (j = 0; j < B_length; j++) {
global_col = B_gids[B_bindx[j]];
ML_hash_it(global_col, hashed_inds, index_length,&hash_used, &hash_val);
hashed_inds[hash_val] = global_col;
hashed_vals[hash_val] += scalarB*B_val[j];
B_bindx[j] = hash_val;
}
#ifdef ML_WITH_EPETRA
if (matrix_type == ML_EpetraCRS_MATRIX) {
for (j = 0; j < A_length; j++) {
columns[j] = hashed_inds[A_bindx[j]];
values[j] = hashed_vals[A_bindx[j]];
nz_ptr++;
hashed_inds[A_bindx[j]] = -1;
hashed_vals[A_bindx[j]] = 0.;
}
count = A_length;
for (j = 0; j < B_length; j++) {
if (hashed_inds[B_bindx[j]] != -1) {
columns[count] = hashed_inds[B_bindx[j]];
values[count++] = hashed_vals[B_bindx[j]];
nz_ptr++;
hashed_inds[B_bindx[j]] = -1;
hashed_vals[B_bindx[j]] = 0.;
}
}
ML_Epetra_CRSinsert(C,i,columns,values,count);
}
else {
#endif
for (j = 0; j < A_length; j++) {
columns[nz_ptr] = hashed_inds[A_bindx[j]];
values[nz_ptr] = hashed_vals[A_bindx[j]];
nz_ptr++;
hashed_inds[A_bindx[j]] = -1;
hashed_vals[A_bindx[j]] = 0.;
}
for (j = 0; j < B_length; j++) {
if (hashed_inds[B_bindx[j]] != -1) {
columns[nz_ptr] = hashed_inds[B_bindx[j]];
values[nz_ptr] = hashed_vals[B_bindx[j]];
nz_ptr++;
hashed_inds[B_bindx[j]] = -1;
hashed_vals[B_bindx[j]] = 0.;
}
}
#ifdef ML_WITH_EPETRA
}
#endif
rowptr[i+1] = nz_ptr;
j = rowptr[i+1] - rowptr[i];
if (j > max_nz_per_row)
max_nz_per_row = j;
if (j < min_nz_per_row && j>0)
min_nz_per_row = j;
}
if (matrix_type == ML_CSR_MATRIX) {
temp = (struct ML_CSR_MSRdata *) ML_allocate(sizeof(struct ML_CSR_MSRdata));
if (temp == NULL) pr_error("ML_Operator_Add: no space for temp\n");
temp->columns = columns;
temp->values = values;
temp->rowptr = rowptr;
ML_Operator_Set_ApplyFuncData(C, B->invec_leng, A->outvec_leng,
temp,A->outvec_leng, NULL,0);
ML_Operator_Set_Getrow(C, A->outvec_leng, CSR_getrow);
ML_Operator_Set_ApplyFunc (C, CSR_matvec);
ML_globalcsr2localcsr(C, max_per_proc);
C->data_destroy = ML_CSR_MSRdata_Destroy;
C->max_nz_per_row = max_nz_per_row;
C->min_nz_per_row = min_nz_per_row;
C->N_nonzeros = nz_ptr;
}
#ifdef ML_WITH_EPETRA
else {
ML_free(rowptr);
ML_free(columns);
ML_free(values);
}
#endif
ML_free(A_gids);
ML_free(B_gids);
ML_free(hashed_vals);
ML_free(hashed_inds);
ML_free(A_val);
ML_free(A_bindx);
ML_free(B_val);
ML_free(B_bindx);
return 1;
}
// ================================================ ====== ==== ==== == =
int RefMaxwell_SetupCoordinates(ML_Operator* A, Teuchos::ParameterList &List_, double *&coordx, double *&coordy, double *&coordz)
// Coppied From int ML_Epetra::MultiLevelPreconditioner::SetupCoordinates()
{
double* in_x_coord = 0;
double* in_y_coord = 0;
double* in_z_coord = 0;
int NumPDEEqns_ =1; // Always use 1 because A is a nodal matrix.
// For node coordinates
in_x_coord = List_.get("x-coordinates", (double *)0);
in_y_coord = List_.get("y-coordinates", (double *)0);
in_z_coord = List_.get("z-coordinates", (double *)0);
if (!(in_x_coord == 0 && in_y_coord == 0 && in_z_coord == 0))
{
ML_Operator* AAA = A;
int n = AAA->invec_leng, Nghost = 0;
if (AAA->getrow->pre_comm)
{
if (AAA->getrow->pre_comm->total_rcv_length <= 0)
ML_CommInfoOP_Compute_TotalRcvLength(AAA->getrow->pre_comm);
Nghost = AAA->getrow->pre_comm->total_rcv_length;
}
std::vector<double> tmp(Nghost + n);
for (int i = 0 ; i < Nghost + n ; ++i)
tmp[i] = 0.0;
n /= NumPDEEqns_;
Nghost /= NumPDEEqns_;
if (in_x_coord)
{
double* x_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_x_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
x_coord[i] = tmp[i * NumPDEEqns_];
coordx = x_coord;
}
if (in_y_coord)
{
double* y_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_y_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
y_coord[i] = tmp[i * NumPDEEqns_];
coordy = y_coord;
}
if (in_z_coord)
{
double* z_coord = (double *) ML_allocate(sizeof(double) * (Nghost+n));
for (int i = 0 ; i < n ; ++i)
tmp[i * NumPDEEqns_] = in_z_coord[i];
ML_exchange_bdry(&tmp[0],AAA->getrow->pre_comm, NumPDEEqns_ * n,
AAA->comm, ML_OVERWRITE,NULL);
for (int i = 0 ; i < n + Nghost ; ++i)
z_coord[i] = tmp[i * NumPDEEqns_];
coordz = z_coord;
}
} // if (!(in_x_coord == 0 && in_y_coord == 0 && in_z_coord == 0))
return(0);
}
