@Override
public Iterable<Tuple2<MatrixIndexes, MatrixBlock>> call(
Tuple2<MatrixIndexes, MatrixBlock> arg0) throws Exception {
ArrayList<Tuple2<MatrixIndexes, MatrixBlock>> ret =
new ArrayList<Tuple2<MatrixIndexes, MatrixBlock>>();
MatrixIndexes ixIn = arg0._1();
MatrixBlock mb2 = arg0._2();
// get the right hand side matrix
MatrixBlock mb1 = _pmV.getMatrixBlock((int) ixIn.getRowIndex(), 1);
// compute target block indexes
long minPos = UtilFunctions.toLong(mb1.minNonZero());
long maxPos = UtilFunctions.toLong(mb1.max());
long rowIX1 = (minPos - 1) / _brlen + 1;
long rowIX2 = (maxPos - 1) / _brlen + 1;
boolean multipleOuts = (rowIX1 != rowIX2);
if (minPos >= 1) // at least one row selected
{
// output sparsity estimate
double spmb1 = OptimizerUtils.getSparsity(mb1.getNumRows(), 1, mb1.getNonZeros());
long estnnz = (long) (spmb1 * mb2.getNonZeros());
boolean sparse = MatrixBlock.evalSparseFormatInMemory(_brlen, mb2.getNumColumns(), estnnz);
// compute and allocate output blocks
MatrixBlock out1 = new MatrixBlock();
MatrixBlock out2 = multipleOuts ? new MatrixBlock() : null;
out1.reset(_brlen, mb2.getNumColumns(), sparse);
if (out2 != null)
out2.reset(
UtilFunctions.computeBlockSize(_rlen, rowIX2, _brlen), mb2.getNumColumns(), sparse);
// compute core matrix permutation (assumes that out1 has default blocksize,
// hence we do a meta data correction afterwards)
mb1.permutationMatrixMultOperations(mb2, out1, out2);
out1.setNumRows(UtilFunctions.computeBlockSize(_rlen, rowIX1, _brlen));
ret.add(
new Tuple2<MatrixIndexes, MatrixBlock>(
new MatrixIndexes(rowIX1, ixIn.getColumnIndex()), out1));
if (out2 != null)
ret.add(
new Tuple2<MatrixIndexes, MatrixBlock>(
new MatrixIndexes(rowIX2, ixIn.getColumnIndex()), out2));
}
return ret;
}
