use of org.knime.core.node.port.pmml.PMMLModelWrapper in project knime-core by knime.
the class DataColumnSpecFilterPMMLNodeModel method createPMMLOut.
private PMMLPortObject createPMMLOut(final PMMLPortObject pmmlIn, final DataTableSpec outSpec, final FilterResult res) throws XmlException {
StringBuffer warningBuffer = new StringBuffer();
if (pmmlIn == null) {
return new PMMLPortObject(createPMMLSpec(null, outSpec, res));
} else {
PMMLDocument pmmldoc;
try (LockedSupplier<Document> supplier = pmmlIn.getPMMLValue().getDocumentSupplier()) {
pmmldoc = PMMLDocument.Factory.parse(supplier.get());
}
// Inspect models to check if they use any excluded columns
List<PMMLModelWrapper> models = PMMLModelWrapper.getModelListFromPMMLDocument(pmmldoc);
for (PMMLModelWrapper model : models) {
MiningSchema ms = model.getMiningSchema();
for (MiningField mf : ms.getMiningFieldList()) {
if (isExcluded(mf.getName(), res)) {
if (warningBuffer.length() != 0) {
warningBuffer.append("\n");
}
warningBuffer.append(model.getModelType().name() + " uses excluded column " + mf.getName());
}
}
}
ArrayList<String> warningFields = new ArrayList<String>();
PMML pmml = pmmldoc.getPMML();
// Now check the transformations if they exist
if (pmml.getTransformationDictionary() != null) {
for (DerivedField df : pmml.getTransformationDictionary().getDerivedFieldList()) {
FieldRef fr = df.getFieldRef();
if (fr != null && isExcluded(fr.getField(), res)) {
warningFields.add(fr.getField());
}
Aggregate a = df.getAggregate();
if (a != null && isExcluded(a.getField(), res)) {
warningFields.add(a.getField());
}
Apply ap = df.getApply();
if (ap != null) {
for (FieldRef fieldRef : ap.getFieldRefList()) {
if (isExcluded(fieldRef.getField(), res)) {
warningFields.add(fieldRef.getField());
break;
}
}
}
Discretize d = df.getDiscretize();
if (d != null && isExcluded(d.getField(), res)) {
warningFields.add(d.getField());
}
MapValues mv = df.getMapValues();
if (mv != null) {
for (FieldColumnPair fcp : mv.getFieldColumnPairList()) {
if (isExcluded(fcp.getField(), res)) {
warningFields.add(fcp.getField());
}
}
}
NormContinuous nc = df.getNormContinuous();
if (nc != null && isExcluded(nc.getField(), res)) {
warningFields.add(nc.getField());
}
NormDiscrete nd = df.getNormDiscrete();
if (nd != null && isExcluded(nd.getField(), res)) {
warningFields.add(nd.getField());
}
}
}
DataDictionary dict = pmml.getDataDictionary();
List<DataField> fields = dict.getDataFieldList();
// Apply filter to spec
int numFields = 0;
for (int i = fields.size() - 1; i >= 0; i--) {
if (isExcluded(fields.get(i).getName(), res)) {
dict.removeDataField(i);
} else {
numFields++;
}
}
dict.setNumberOfFields(new BigInteger(Integer.toString(numFields)));
pmml.setDataDictionary(dict);
pmmldoc.setPMML(pmml);
// generate warnings and set as warning message
for (String s : warningFields) {
if (warningBuffer.length() != 0) {
warningBuffer.append("\n");
}
warningBuffer.append("Transformation dictionary uses excluded column " + s);
}
if (warningBuffer.length() > 0) {
setWarningMessage(warningBuffer.toString().trim());
}
PMMLPortObject outport = null;
try {
outport = new PMMLPortObject(createPMMLSpec(pmmlIn.getSpec(), outSpec, res), pmmldoc);
} catch (IllegalArgumentException e) {
if (res.getIncludes().length == 0) {
throw new IllegalArgumentException("Excluding all columns produces invalid PMML", e);
} else {
throw e;
}
}
return outport;
}
}
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