Lines Matching refs:block
93 // Add a map object for each block in the reduced linear system
94 // and build the row/column block structure of the reduced linear
105 // containing the same y block are vertically contiguous. Along
121 // Add to the chunk until the first block in the row is
130 // block since it is the one to be eliminated.
199 m.block(r, c, block_size, block_size).diagonal()
207 // vector block corresponding to the y block and then apply
209 // matrix corresponding to the block being eliminated and array
211 // to this y block in the normal equations. This computation is
215 // blocks for all the z blocks that share a row block/residual
216 // term with the y block. EliminateRowOuterProduct does the
332 FixedArray<double, 8> sj(row.block.size);
334 typename EigenTypes<kRowBlockSize>::VectorRef(sj.get(), row.block.size) =
336 (b + bs->rows[chunk.start + j].block.position, row.block.size);
344 values + row.cells[c].position, row.block.size, f_block_size,
350 values + e_cell.position, row.block.size, e_block_size,
356 values + e_cell.position, row.block.size, e_block_size,
357 values + e_cell.position, row.block.size, e_block_size,
381 int b_pos = bs->rows[row_block_counter].block.position;
389 (b + b_pos, row.block.size);
392 values + e_cell.position, row.block.size, e_block_size,
398 const int block = block_id - num_eliminate_blocks_;
399 CeresMutexLock l(rhs_locks_[block]);
402 row.block.size, block_size,
403 sj.data(), rhs + lhs_row_layout_[block]);
405 b_pos += row.block.size;
416 // this function computes twp matrices. The diagonal block matrix
424 // which are zero compressed versions of the block sparse matrices E'E
442 int b_pos = bs->rows[row_block_counter].block.position;
447 // contribution of its E block to the matrix EE' (ete), and the
448 // corresponding block in the gradient vector.
461 values + e_cell.position, row.block.size, e_block_size,
462 values + e_cell.position, row.block.size, e_block_size,
467 values + e_cell.position, row.block.size, e_block_size,
481 values + e_cell.position, row.block.size, e_block_size,
482 values + row.cells[c].position, row.block.size, f_block_size,
485 b_pos += row.block.size;
565 const int block = block_id - num_eliminate_blocks_;
567 values + row.cells[c].position, row.block.size, block_size,
568 b + row.block.position,
569 rhs + lhs_row_layout_[block]);
614 values + row.cells[i].position, row.block.size, block1_size,
615 values + row.cells[i].position, row.block.size, block1_size,
632 values + row.cells[i].position, row.block.size, block1_size,
633 values + row.cells[j].position, row.block.size, block2_size,
663 // block += b1.transpose() * b1;
666 values + row.cells[i].position, row.block.size, block1_size,
667 values + row.cells[i].position, row.block.size, block1_size,
681 // block += b1.transpose() * b2;
685 values + row.cells[i].position, row.block.size, block1_size,
686 values + row.cells[j].position, row.block.size, block2_size,
