@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 addStr(Chunk c, int row) {
if (c.isNA(row)) addNA();
else {
addStr(c.atStr(new BufferedString(), row));
_isAllASCII &= ((CStrChunk) c)._isAllASCII;
}
}
@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;
}
}
public NewChunk convertEnum2Str(ValueString[] emap) {
NewChunk strChunk = new NewChunk(_vec, _cidx);
int j = 0, l = _len;
for (int i = 0; i < l; ++i) {
if (_id != null && _id.length > 0 && (j < _id.length && _id[j] == i)) // Sparse storage
// adjust for enum ids using 1-based indexing
strChunk.addStr(emap[(int) _ls[j++] - 1]);
else if (_xs[i] != Integer.MIN_VALUE) // Categorical value isn't NA
strChunk.addStr(emap[(int) _ls[i] - 1]);
else strChunk.addNA();
}
if (_id != null) assert j == sparseLen() : "j = " + j + ", sparseLen = " + sparseLen();
return strChunk;
}
@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);
}
}
@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;
}
public void addStr(Chunk c, int row) {
if (c.isNA(row)) addNA();
else addStr(c.atStr(new ValueString(), row));
}
public void addStr(Chunk c, long row) {
if (c.isNA_abs(row)) addNA();
else addStr(c.atStr_abs(new ValueString(), row));
}
