/** Finds a job with given key or returns null */
public static final Job findJob(final Key key) {
Job job = null;
for (Job current : Job.all()) {
if (current.self().equals(key)) {
job = current;
break;
}
}
return job;
}
/**
* Extracts the values, applies regularization to numerics, adds appropriate offsets to
* categoricals, and adapts response according to the CaseMode/CaseValue if set.
*/
@Override
public final void map(Chunk[] chunks, NewChunk[] outputs) {
if (_job != null && _job.self() != null && !Job.isRunning(_job.self()))
throw new JobCancelledException();
final int nrows = chunks[0]._len;
final long offset = chunks[0]._start;
chunkInit();
double[] nums = MemoryManager.malloc8d(_dinfo._nums);
int[] cats = MemoryManager.malloc4(_dinfo._cats);
double[] response = MemoryManager.malloc8d(_dinfo._responses);
int start = 0;
int end = nrows;
boolean contiguous = false;
Random skip_rng = null; // random generator for skipping rows
if (_useFraction < 1.0) {
skip_rng = water.util.Utils.getDeterRNG(new Random().nextLong());
if (contiguous) {
final int howmany = (int) Math.ceil(_useFraction * nrows);
if (howmany > 0) {
start = skip_rng.nextInt(nrows - howmany);
end = start + howmany;
}
assert (start < nrows);
assert (end <= nrows);
}
}
long[] shuf_map = null;
if (_shuffle) {
shuf_map = new long[end - start];
for (int i = 0; i < shuf_map.length; ++i) shuf_map[i] = start + i;
Utils.shuffleArray(shuf_map, new Random().nextLong());
}
OUTER:
for (int rr = start; rr < end; ++rr) {
final int r = shuf_map != null ? (int) shuf_map[rr - start] : rr;
if ((_dinfo._nfolds > 0 && (r % _dinfo._nfolds) == _dinfo._foldId)
|| (skip_rng != null && skip_rng.nextFloat() > _useFraction)) continue;
for (Chunk c : chunks) if (c.isNA0(r)) continue OUTER; // skip rows with NAs!
int i = 0, ncats = 0;
for (; i < _dinfo._cats; ++i) {
int c = (int) chunks[i].at80(r);
if (c != 0) cats[ncats++] = c + _dinfo._catOffsets[i] - 1;
}
final int n = chunks.length - _dinfo._responses;
for (; i < n; ++i) {
double d = chunks[i].at0(r);
if (_dinfo._normMul != null)
d = (d - _dinfo._normSub[i - _dinfo._cats]) * _dinfo._normMul[i - _dinfo._cats];
nums[i - _dinfo._cats] = d;
}
for (i = 0; i < _dinfo._responses; ++i) {
response[i] = chunks[chunks.length - _dinfo._responses + i].at0(r);
if (_dinfo._normRespMul != null)
response[i] = (response[i] - _dinfo._normRespSub[i]) * _dinfo._normRespMul[i];
}
if (outputs != null && outputs.length > 0)
processRow(offset + r, nums, ncats, cats, response, outputs);
else processRow(offset + r, nums, ncats, cats, response);
}
chunkDone();
}
