void fill_matrix(LinSys * lin_sys, int min_idx, int max_idx) {
unsigned int row_cnt = 0; //row counter
unsigned int local_min, local_max;
for (unsigned int i = 0; i < min_idx; i++) {
row_cnt += rows[i];
}
local_min = row_cnt;
// create block A of matrix
for (unsigned int i = min_idx; i < max_idx; i++) {
std::vector<PetscScalar> a_vals;
a_vals.reserve(rows[i] * rows[i]);
for (unsigned int j=0; j<rows[i]*rows[i]; j++) {
a_vals.push_back( rand()%19 + 1 );
}
std::vector<int> a_rows_idx;
a_rows_idx.reserve(rows[i]);
for (unsigned int j=0; j<rows[i]; j++) {
a_rows_idx.push_back(row_cnt + min_idx + j);
}
int * insert_rows = &a_rows_idx[0];
PetscScalar * insert_vals = &a_vals[0];
lin_sys->mat_set_values(rows[i], insert_rows, rows[i], insert_rows, insert_vals);
row_cnt += rows[i];
}
local_max = row_cnt;
/*for (unsigned int i = max_idx; i < 6; i++) {
row_cnt += rows[i];
}*/
// create block B of matrix
std::vector<PetscScalar> b_vals((local_max - local_min) * (max_idx - min_idx), 1.0);
std::vector<int> b_rows_idx;
std::vector<int> b_cols_idx;
b_rows_idx.reserve(local_max - local_min);
b_cols_idx.reserve(max_idx - min_idx);
for (unsigned int i = local_min; i < local_max; i++) {
b_rows_idx.push_back(i + min_idx);
}
for (unsigned int i = min_idx; i < max_idx; i++) {
b_cols_idx.push_back(local_max + i);
}
int * b_insert_rows = &b_rows_idx[0];
int * b_insert_cols = &b_cols_idx[0];
PetscScalar * b_insert_vals = &b_vals[0];
lin_sys->mat_set_values((local_max - local_min), b_insert_rows, (max_idx - min_idx), b_insert_cols, b_insert_vals);
lin_sys->mat_set_values((max_idx - min_idx), b_insert_cols, (local_max - local_min), b_insert_rows, b_insert_vals); // */
}
void fill_matrix(int rank, Distribution &ds, Distribution &block_ds) {
// set B columns
int n_cols_B=block_ds.size();
std::vector<PetscInt> b_cols(n_cols_B);
for( unsigned int p=0;p<block_ds.np();p++)
for (unsigned int j=block_ds.begin(p); j<block_ds.end(p); j++) {
//int proc=block_ds.get_proc(j);
b_cols[j]=ds.end(p)+j;
}
// create block A of matrix
int local_idx=0;
for (unsigned int i = block_ds.begin(); i < block_ds.end(); i++) {
// make random block values
std::vector<PetscScalar> a_vals(block_size * block_size, 0);
for (unsigned int j=0; j<block_size; j++)
a_vals[ j + j*block_size ]= (rank + 2);
// set rows and columns indices
std::vector<PetscInt> a_rows(block_size);
for (unsigned int j=0; j<block_size; j++) {
a_rows[j]=ds.begin() + block_ds.begin() + local_idx;
local_idx++;
}
mat_set_values(block_size, &a_rows[0], block_size, &a_rows[0], &a_vals[0]);
// set B values
std::vector<PetscScalar> b_vals(block_size*n_cols_B);
for (int j=0; j<block_size*n_cols_B; j++)
b_vals[j] = 1;
// set C values
std::vector<PetscScalar> c_vals(n_cols_B);
for (int j=0; j<n_cols_B; j++)
c_vals[j] = 0;
// must iterate per rows to get correct transpose
for(unsigned int row=0; row<block_size;row++) {
mat_set_values(1, &a_rows[row], 1, &b_cols[rank], &b_vals[row*n_cols_B]);
mat_set_values(1, &b_cols[rank],1, &a_rows[row], &b_vals[row*n_cols_B]);
}
mat_set_values(1, &b_cols[rank], 1, &b_cols[rank], &c_vals[rank]);
}
}
