@Override
public void map(Chunk chks[], NewChunk nchks[]) {
long rstart = chks[0]._start;
int rlen = chks[0]._len; // Total row count
int rx = 0; // Which row to in/ex-clude
int rlo = 0; // Lo/Hi for this block of rows
int rhi = rlen;
while (true) { // Still got rows to include?
if (_rows != null) { // Got a row selector?
if (rx >= _rows.length) break; // All done with row selections
long r = _rows[rx++] - 1; // Next row selector
if (r < 0) { // Row exclusion
if (rx > 0 && _rows[rx - 1] < _rows[rx]) throw H2O.unimpl();
long er = Math.abs(r) - 2;
if (er < rstart) continue;
// scoop up all of the rows before the first exclusion
if (rx == 1 && ((int) (er + 1 - rstart)) > 0 && _ex) {
rlo = (int) rstart;
rhi = (int) (er - rstart);
_ex = false;
rx--;
} else {
rlo = (int) (er + 1 - rstart);
// TODO: handle jumbled row indices ( e.g. -c(1,5,3) )
while (rx < _rows.length && (_rows[rx] + 1 == _rows[rx - 1] && rlo < rlen)) {
if (rx < _rows.length - 1 && _rows[rx] < _rows[rx + 1]) throw H2O.unimpl();
rx++;
rlo++; // Exclude consecutive rows
}
rhi = rx >= _rows.length ? rlen : (int) Math.abs(_rows[rx] - 1) - 2;
if (rx < _rows.length - 1 && _rows[rx] < _rows[rx + 1]) throw H2O.unimpl();
}
} else { // Positive row list?
if (r < rstart) continue;
rlo = (int) (r - rstart);
rhi = rlo + 1; // Stop at the next row
while (rx < _rows.length && (_rows[rx] - 1 - rstart) == rhi && rhi < rlen) {
rx++;
rhi++; // Grab sequential rows
}
}
}
// Process this next set of rows
// For all cols in the new set
for (int i = 0; i < _cols.length; i++) {
Chunk oc = chks[_cols[i]];
NewChunk nc = nchks[i];
if (oc._vec.isInt()) { // Slice on integer columns
for (int j = rlo; j < rhi; j++)
if (oc.isNA0(j)) nc.addNA();
else nc.addNum(oc.at80(j), 0);
} else { // Slice on double columns
for (int j = rlo; j < rhi; j++) nc.addNum(oc.at0(j));
}
}
rlo = rhi;
if (_rows == null) break;
}
}
@Test
public void test_inflate_impl() {
for (int l = 0; l < 2; ++l) {
NewChunk nc = new NewChunk(null, 0);
// -32.767, 0.34, 0, 32.767, NA for l==0
// NA, -32.767, 0.34, 0, 32.767, NA for l==1
long[] man = new long[] {-32767, 34, 0, 32767};
int[] exp = new int[] {-3, -2, 1, -3};
if (l == 1) nc.addNA(); // -32768
for (int i = 0; i < man.length; ++i) nc.addNum(man[i], exp[i]);
nc.addNA();
Chunk cc = nc.compress();
Assert.assertEquals(man.length + 1 + l, cc.len());
Assert.assertTrue(cc instanceof C2SChunk);
if (l == 1) {
Assert.assertTrue(cc.isNA0(0));
Assert.assertTrue(cc.isNA(0));
}
for (int i = 0; i < man.length; ++i) {
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) cc.at0(l + i), 0);
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) cc.at(l + i), 0);
}
Assert.assertTrue(cc.isNA0(man.length + l));
Assert.assertTrue(cc.isNA(man.length + l));
nc = cc.inflate_impl(new NewChunk(null, 0));
nc.values(0, nc.len());
Assert.assertEquals(man.length + 1 + l, nc.len());
Assert.assertEquals(man.length + 1 + l, nc.sparseLen());
if (l == 1) {
Assert.assertTrue(nc.isNA0(0));
Assert.assertTrue(nc.isNA(0));
}
for (int i = 0; i < man.length; ++i) {
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) nc.at0(l + i), 0);
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) nc.at(l + i), 0);
}
Assert.assertTrue(nc.isNA0(man.length + l));
Assert.assertTrue(nc.isNA(man.length + l));
Chunk cc2 = nc.compress();
Assert.assertEquals(man.length + 1 + l, cc.len());
if (l == 1) {
Assert.assertTrue(cc2.isNA0(0));
Assert.assertTrue(cc2.isNA(0));
}
for (int i = 0; i < man.length; ++i) {
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) cc2.at0(l + i), 0);
Assert.assertEquals((float) (man[i] * Math.pow(10, exp[i])), (float) cc2.at(l + i), 0);
}
Assert.assertTrue(cc2.isNA0(man.length + l));
Assert.assertTrue(cc2.isNA(man.length + l));
Assert.assertTrue(cc2 instanceof C2SChunk);
Assert.assertTrue(Arrays.equals(cc._mem, cc2._mem));
}
}
public void add2Chunk(NewChunk c) {
if (_ds == null && _ss == null) {
c.addNum(_ls[_lId], _xs[_lId]);
} else {
if (_ls != null) {
c.addUUID(_ls[_lId], Double.doubleToRawLongBits(_ds[_lId]));
} else if (_ss != null) {
int sidx = _is[_lId];
int nextNotNAIdx = _lId + 1;
// Find next not-NA value (_is[idx] != -1)
while (nextNotNAIdx < _is.length && _is[nextNotNAIdx] == -1) nextNotNAIdx++;
int slen = nextNotNAIdx < _is.length ? _is[nextNotNAIdx] - sidx : _sslen - sidx;
// null-BufferedString represents NA value
BufferedString bStr = sidx == -1 ? null : new BufferedString().set(_ss, sidx, slen);
c.addStr(bStr);
} else c.addNum(_ds[_lId]);
}
}
@Override
public NewChunk inflate_impl(NewChunk nc) {
double dx = Math.log10(_scale);
assert water.util.PrettyPrint.fitsIntoInt(dx);
nc.set_sparseLen(0);
nc.set_len(0);
final int len = _len;
for (int i = 0; i < len; i++) {
int res = 0xFF & _mem[i + _OFF];
if (res == C1Chunk._NA) nc.addNA();
else nc.addNum((res + _bias), (int) dx);
}
return nc;
}
public void addNum(long val, int exp) {
if (isUUID() || isString()) addNA();
else if (_ds != null) {
assert _ls == null;
addNum(val * PrettyPrint.pow10(exp));
} else {
if (val == 0) exp = 0; // Canonicalize zero
long t; // Remove extra scaling
while (exp < 0 && exp > -9999999 && (t = val / 10) * 10 == val) {
val = t;
exp++;
}
append2(val, exp);
}
}
@Test
public void test() {
Frame frame = null;
try {
Futures fs = new Futures();
Random random = new Random();
Vec[] vecs = new Vec[1];
AppendableVec vec = new AppendableVec(Vec.newKey(), Vec.T_NUM);
for (int i = 0; i < 2; i++) {
NewChunk chunk = new NewChunk(vec, i);
for (int r = 0; r < 1000; r++) chunk.addNum(random.nextInt(1000));
chunk.close(i, fs);
}
vecs[0] = vec.layout_and_close(fs);
fs.blockForPending();
frame = new Frame(Key.<Frame>make(), null, vecs);
// Make sure we test the multi-chunk case
vecs = frame.vecs();
assert vecs[0].nChunks() > 1;
long rows = frame.numRows();
Vec v = vecs[0];
double min = Double.POSITIVE_INFINITY, max = Double.NEGATIVE_INFINITY, mean = 0, sigma = 0;
for (int r = 0; r < rows; r++) {
double d = v.at(r);
if (d < min) min = d;
if (d > max) max = d;
mean += d;
}
mean /= rows;
for (int r = 0; r < rows; r++) {
double d = v.at(r);
sigma += (d - mean) * (d - mean);
}
sigma = Math.sqrt(sigma / (rows - 1));
double epsilon = 1e-9;
assertEquals(max, v.max(), epsilon);
assertEquals(min, v.min(), epsilon);
assertEquals(mean, v.mean(), epsilon);
assertEquals(sigma, v.sigma(), epsilon);
} finally {
if (frame != null) frame.delete();
}
}
@Override
public void map(Chunk cs) {
int idx = _chunkOffset + cs.cidx();
Key ckey = Vec.chunkKey(_v._key, idx);
if (_cmap != null) {
assert !cs.hasFloat()
: "Input chunk (" + cs.getClass() + ") has float, but is expected to be categorical";
NewChunk nc = new NewChunk(_v, idx);
// loop over rows and update ints for new domain mapping according to vecs[c].domain()
for (int r = 0; r < cs._len; ++r) {
if (cs.isNA(r)) nc.addNA();
else nc.addNum(_cmap[(int) cs.at8(r)], 0);
}
nc.close(_fs);
} else {
DKV.put(ckey, cs.deepCopy(), _fs, true);
}
}
// Fast-path append double data
public void addNum(double d) {
if (isUUID() || isString()) {
addNA();
return;
}
if (_id == null || d != 0) {
if (_ls != null) switch_to_doubles();
if (_ds == null || sparseLen() >= _ds.length) {
append2slowd();
// call addNum again since append2slow might have flipped to sparse
addNum(d);
assert sparseLen() <= _len;
return;
}
if (_id != null) _id[sparseLen()] = _len;
_ds[sparseLen()] = d;
set_sparseLen(sparseLen() + 1);
}
set_len(_len + 1);
assert sparseLen() <= _len;
}
@Test
public void test_inflate_impl() {
final int K = 1 << 16;
for (Double d :
new Double[] {
3.14159265358,
Double.POSITIVE_INFINITY,
Double.NEGATIVE_INFINITY,
Double.MAX_VALUE,
Double.NaN
}) {
NewChunk nc = new NewChunk(null, 0);
for (int i = 0; i < K; ++i) nc.addNum(d);
Assert.assertEquals(K, nc.len());
Assert.assertEquals(K, nc.sparseLen());
Chunk cc = nc.compress();
Assert.assertEquals(K, cc.len());
Assert.assertTrue(cc instanceof C0DChunk);
for (int i = 0; i < K; ++i) Assert.assertEquals(d, cc.at0(i), Math.ulp(d));
for (int i = 0; i < K; ++i) Assert.assertEquals(d, cc.at(i), Math.ulp(d));
nc = cc.inflate_impl(new NewChunk(null, 0));
nc.values(0, nc.len());
Assert.assertEquals(K, nc.len());
Assert.assertEquals(K, nc.sparseLen());
for (int i = 0; i < K; ++i) Assert.assertEquals(d, nc.at0(i), Math.ulp(d));
for (int i = 0; i < K; ++i) Assert.assertEquals(d, nc.at(i), Math.ulp(d));
Chunk cc2 = nc.compress();
Assert.assertEquals(K, cc2.len());
Assert.assertTrue(cc2 instanceof C0DChunk);
for (int i = 0; i < K; ++i) Assert.assertEquals(d, cc2.at0(i), Math.ulp(d));
for (int i = 0; i < K; ++i) Assert.assertEquals(d, cc2.at(i), Math.ulp(d));
Assert.assertTrue(Arrays.equals(cc._mem, cc2._mem));
}
}
public void addZeros(int n) {
if (!sparse()) for (int i = 0; i < n; ++i) addNum(0, 0);
else set_len(_len + n);
}
public void addNA() {
if (isUUID()) addUUID(C16Chunk._LO_NA, C16Chunk._HI_NA);
else if (isString()) addStr(null);
else if (_ds != null) addNum(Double.NaN);
else append2(Long.MAX_VALUE, Integer.MIN_VALUE);
}
@Override
public void map(Chunk c, NewChunk nc) {
double acc = _init;
for (int i = 0; i < c._len; ++i) nc.addNum(acc = op(acc, c.atd(i)));
_chkCumu[c.cidx()] = acc;
}
public Frame deepSlice(Object orows, Object ocols) {
// ocols is either a long[] or a Frame-of-1-Vec
long[] cols;
if (ocols == null) {
cols = (long[]) ocols;
assert cols == null;
} else {
if (ocols instanceof long[]) {
cols = (long[]) ocols;
} else if (ocols instanceof Frame) {
Frame fr = (Frame) ocols;
if (fr.numCols() != 1) {
throw new IllegalArgumentException(
"Columns Frame must have only one column (actually has "
+ fr.numCols()
+ " columns)");
}
long n = fr.anyVec().length();
if (n > MAX_EQ2_COLS) {
throw new IllegalArgumentException(
"Too many requested columns (requested " + n + ", max " + MAX_EQ2_COLS + ")");
}
cols = new long[(int) n];
Vec v = fr._vecs[0];
for (long i = 0; i < v.length(); i++) {
cols[(int) i] = v.at8(i);
}
} else {
throw new IllegalArgumentException(
"Columns is specified by an unsupported data type ("
+ ocols.getClass().getName()
+ ")");
}
}
// Since cols is probably short convert to a positive list.
int c2[] = null;
if (cols == null) {
c2 = new int[numCols()];
for (int i = 0; i < c2.length; i++) c2[i] = i;
} else if (cols.length == 0) {
c2 = new int[0];
} else if (cols[0] > 0) {
c2 = new int[cols.length];
for (int i = 0; i < cols.length; i++)
c2[i] = (int) cols[i] - 1; // Convert 1-based cols to zero-based
} else {
c2 = new int[numCols() - cols.length];
int j = 0;
for (int i = 0; i < numCols(); i++) {
if (j >= cols.length || i < (-cols[j] - 1)) c2[i - j] = i;
else j++;
}
}
for (int i = 0; i < c2.length; i++)
if (c2[i] >= numCols())
throw new IllegalArgumentException(
"Trying to select column " + c2[i] + " but only " + numCols() + " present.");
if (c2.length == 0)
throw new IllegalArgumentException(
"No columns selected (did you try to select column 0 instead of column 1?)");
// Do Da Slice
// orows is either a long[] or a Vec
if (orows == null)
return new DeepSlice((long[]) orows, c2)
.doAll(c2.length, this)
.outputFrame(names(c2), domains(c2));
else if (orows instanceof long[]) {
final long CHK_ROWS = 1000000;
long[] rows = (long[]) orows;
if (rows.length == 0)
return new DeepSlice(rows, c2).doAll(c2.length, this).outputFrame(names(c2), domains(c2));
if (rows[0] < 0)
return new DeepSlice(rows, c2).doAll(c2.length, this).outputFrame(names(c2), domains(c2));
// Vec'ize the index array
AppendableVec av = new AppendableVec("rownames");
int r = 0;
int c = 0;
while (r < rows.length) {
NewChunk nc = new NewChunk(av, c);
long end = Math.min(r + CHK_ROWS, rows.length);
for (; r < end; r++) {
nc.addNum(rows[r]);
}
nc.close(c++, null);
}
Vec c0 = av.close(null); // c0 is the row index vec
Frame fr2 =
new Slice(c2, this)
.doAll(c2.length, new Frame(new String[] {"rownames"}, new Vec[] {c0}))
.outputFrame(names(c2), domains(c2));
UKV.remove(c0._key); // Remove hidden vector
return fr2;
}
Frame frows = (Frame) orows;
Vec vrows = frows.anyVec();
// It's a compatible Vec; use it as boolean selector.
// Build column names for the result.
Vec[] vecs = new Vec[c2.length + 1];
String[] names = new String[c2.length + 1];
for (int i = 0; i < c2.length; ++i) {
vecs[i] = _vecs[c2[i]];
names[i] = _names[c2[i]];
}
vecs[c2.length] = vrows;
names[c2.length] = "predicate";
return new DeepSelect()
.doAll(c2.length, new Frame(names, vecs))
.outputFrame(names(c2), domains(c2));
}