/** Adds invalid value to the column. */
public void addInvalidCol(int colIdx) {
++_colIdx;
if (colIdx >= _ncolumns) return;
++_invalidValues[colIdx];
if (_phase == Pass.ONE) return;
switch (_colTypes[colIdx]) {
case BYTE:
case DBYTE:
_ab.put1(-1);
break;
case SHORT:
case DSHORT:
_ab.put2((short) -1);
break;
case INT:
_ab.put4(Integer.MIN_VALUE);
break;
case LONG:
_ab.put8(Long.MIN_VALUE);
break;
case FLOAT:
_ab.put4f(Float.NaN);
break;
case DOUBLE:
_ab.put8d(Double.NaN);
break;
case STRINGCOL:
// TODO, replace with empty space!
_ab.put1(-1);
break;
default:
assert false : "illegal case: " + _colTypes[colIdx];
}
}
/** Adds string (enum) value to the column. */
public void addStrCol(int colIdx, ValueString str) {
if (colIdx >= _ncolumns) return;
switch (_phase) {
case ONE:
++_colIdx;
// If this is a yet unspecified but non-numeric column, attempt a time-parse
if (_colTypes[colIdx] == UCOL) {
long time = attemptTimeParse(str);
if (time != Long.MIN_VALUE) _colTypes[colIdx] = TCOL;
} else if (_colTypes[colIdx] == TCOL) {
return;
}
// Now attempt to make this an Enum col
Enum e = _enums[colIdx];
if (e == null || e.isKilled()) return;
if (_colTypes[colIdx] == UCOL) _colTypes[colIdx] = ECOL;
e.addKey(str);
++_invalidValues[
colIdx]; // invalid count in phase0 is in fact number of non-numbers (it is used for
// mean computation, is recomputed in 2nd pass)
break;
case TWO:
if (_enums[colIdx] != null) {
++_colIdx;
int id = _enums[colIdx].getTokenId(str);
// we do not expect any misses here
assert 0 <= id && id < _enums[colIdx].size();
switch (_colTypes[colIdx]) {
case BYTE:
_ab.put1(id);
break;
case SHORT:
_ab.put2((char) id);
break;
case INT:
_ab.put4(id);
break;
default:
assert false : "illegal case: " + _colTypes[colIdx];
}
} else if (_colTypes[colIdx] == LONG) {
++_colIdx;
// Times are strings with a numeric column type of LONG
_ab.put8(attemptTimeParse(str));
} else {
addInvalidCol(colIdx);
}
break;
default:
assert (false);
}
}
// TODO: Drop this writeJSON_impl and use the default one.
// TODO: Pull out the help text & metadata into the ParameterSchema for the front-end to display.
public final AutoBuffer writeJSON_impl(AutoBuffer ab) {
ab.putJSON("job", job);
ab.put1(',');
ab.putJSONStr("algo", algo);
ab.put1(',');
ab.putJSONStr("algo_full_name", algo_full_name);
ab.put1(',');
ab.putJSONAEnum("can_build", can_build);
ab.put1(',');
ab.putJSONEnum("visibility", visibility);
ab.put1(',');
ab.putJSONA("messages", messages);
ab.put1(',');
ab.putJSON4("error_count", error_count);
ab.put1(',');
// Builds ModelParameterSchemaV2 objects for each field, and then calls writeJSON on the array
ModelParametersSchemaV3.writeParametersJSON(
ab,
parameters,
createParametersSchema().fillFromImpl((Model.Parameters) parameters.createImpl()));
return ab;
}
@SuppressWarnings("fallthrough")
public void addNumCol(int colIdx, long number, int exp) {
++_colIdx;
if (colIdx >= _ncolumns) return;
switch (_phase) {
case ONE:
double d = number * pow10(exp);
if (d < _min[colIdx]) _min[colIdx] = d;
if (d > _max[colIdx]) _max[colIdx] = d;
_mean[colIdx] += d;
if (exp != 0) {
if (exp < _scale[colIdx]) _scale[colIdx] = exp;
if (_colTypes[colIdx] != DCOL) {
if (Math.abs(number) > MAX_FLOAT_MANTISSA || exp < -35 || exp > 35)
_colTypes[colIdx] = DCOL;
else _colTypes[colIdx] = FCOL;
}
} else if (_colTypes[colIdx] < ICOL) {
_colTypes[colIdx] = ICOL;
}
break;
case TWO:
switch (_colTypes[colIdx]) {
case BYTE:
_ab.put1((byte) (number * pow10i(exp - _scale[colIdx]) - _bases[colIdx]));
break;
case SHORT:
_ab.put2((short) (number * pow10i(exp - _scale[colIdx]) - _bases[colIdx]));
break;
case INT:
_ab.put4((int) (number * pow10i(exp - _scale[colIdx]) - _bases[colIdx]));
break;
case LONG:
_ab.put8(number * pow10i(exp - _scale[colIdx]));
break;
case FLOAT:
_ab.put4f((float) (number * pow10(exp)));
break;
case DOUBLE:
_ab.put8d(number * pow10(exp));
break;
case DBYTE:
_ab.put1((short) (number * pow10i(exp - _scale[colIdx]) - _bases[colIdx]));
break;
case DSHORT:
// scale is computed as negative in the first pass,
// therefore to compute the positive exponent after scale, we add scale and the original
// exponent
_ab.put2((short) (number * pow10i(exp - _scale[colIdx]) - _bases[colIdx]));
break;
case STRINGCOL:
break;
}
// update sigma
if (!Double.isNaN(_mean[colIdx])) {
d = number * pow10(exp) - _mean[colIdx];
_sigma[colIdx] += d * d;
}
break;
default:
assert (false);
}
}
