Examples with Constant org.dmg.pmml.ConstantDocument.Constant used on opensource projects

Example 1 with Constant

use of org.dmg.pmml.ConstantDocument.Constant in project knime-core by knime.

the class MissingCellHandler method createValueReplacingDerivedField.

/**
 * Helper method for creating a derived field that replaces a field's value with a fixed value.
 * @param dataType the data type of the field.
 * @param value the replacement value for the field
 * @return the derived field
 */
protected DerivedField createValueReplacingDerivedField(final DATATYPE.Enum dataType, final String value) {
    DerivedField field = DerivedField.Factory.newInstance();
    if (dataType == org.dmg.pmml.DATATYPE.STRING || dataType == org.dmg.pmml.DATATYPE.BOOLEAN) {
        field.setOptype(org.dmg.pmml.OPTYPE.CATEGORICAL);
    } else {
        field.setOptype(org.dmg.pmml.OPTYPE.CONTINUOUS);
    }
    /*
         * Create the PMML equivalent of: "if fieldVal is missing then x else fieldVal"
         * <Apply function="if">
         *    <Apply function="isMissing">
         *        <FieldRef field="fieldVal"/>
         *    </Apply>
         *    <Constant dataType="___" value="x"/>
         *    <FieldRef field="fieldVal"/>
         * </Apply>
         */
    Apply ifApply = field.addNewApply();
    ifApply.setFunction(IF_FUNCTION_NAME);
    Apply isMissingApply = Apply.Factory.newInstance();
    FieldRef fieldRef = FieldRef.Factory.newInstance();
    fieldRef.setField(m_col.getName());
    isMissingApply.setFieldRefArray(new FieldRef[] { fieldRef });
    isMissingApply.setFunction(IS_MISSING_FUNCTION_NAME);
    ifApply.setApplyArray(new Apply[] { isMissingApply });
    Constant replacement = Constant.Factory.newInstance();
    replacement.setDataType(dataType);
    replacement.setStringValue(value);
    ifApply.setConstantArray(new Constant[] { replacement });
    ifApply.setFieldRefArray(new FieldRef[] { fieldRef });
    field.setDataType(dataType);
    field.setName(m_col.getName());
    field.setDisplayName(m_col.getName());
    return field;
}

Example 2 with Constant

use of org.dmg.pmml.ConstantDocument.Constant in project knime-core by knime.

the class PMMLGeneralRegressionTranslator method exportTo.

/**
 * {@inheritDoc}
 */
@Override
public SchemaType exportTo(final PMMLDocument pmmlDoc, final PMMLPortObjectSpec spec) {
    m_nameMapper = new DerivedFieldMapper(pmmlDoc);
    GeneralRegressionModel reg = pmmlDoc.getPMML().addNewGeneralRegressionModel();
    final JsonObjectBuilder jsonBuilder = Json.createObjectBuilder();
    if (!m_content.getVectorLengths().isEmpty()) {
        LocalTransformations localTransformations = reg.addNewLocalTransformations();
        for (final Entry<? extends String, ? extends Integer> entry : m_content.getVectorLengths().entrySet()) {
            DataColumnSpec columnSpec = spec.getDataTableSpec().getColumnSpec(entry.getKey());
            if (columnSpec != null) {
                final DataType type = columnSpec.getType();
                final DataColumnProperties props = columnSpec.getProperties();
                final boolean bitVector = type.isCompatible(BitVectorValue.class) || (type.isCompatible(StringValue.class) && props.containsProperty("realType") && "BitVector".equals(props.getProperty("realType")));
                final boolean byteVector = type.isCompatible(ByteVectorValue.class) || (type.isCompatible(StringValue.class) && props.containsProperty("realType") && "ByteVector".equals(props.getProperty("realType")));
                final String lengthAsString;
                final int width;
                if (byteVector) {
                    lengthAsString = "3";
                    width = 4;
                } else if (bitVector) {
                    lengthAsString = "1";
                    width = 1;
                } else {
                    throw new UnsupportedOperationException("Not supported type: " + type + " for column: " + columnSpec);
                }
                for (int i = 0; i < entry.getValue().intValue(); ++i) {
                    final DerivedField derivedField = localTransformations.addNewDerivedField();
                    derivedField.setOptype(OPTYPE.CONTINUOUS);
                    derivedField.setDataType(DATATYPE.INTEGER);
                    derivedField.setName(entry.getKey() + "[" + i + "]");
                    Apply apply = derivedField.addNewApply();
                    apply.setFunction("substring");
                    apply.addNewFieldRef().setField(entry.getKey());
                    Constant from = apply.addNewConstant();
                    from.setDataType(DATATYPE.INTEGER);
                    from.setStringValue(bitVector ? Long.toString(entry.getValue().longValue() - i) : Long.toString(i * width + 1L));
                    Constant length = apply.addNewConstant();
                    length.setDataType(DATATYPE.INTEGER);
                    length.setStringValue(lengthAsString);
                }
            }
            jsonBuilder.add(entry.getKey(), entry.getValue().intValue());
        }
    }
    // PMMLPortObjectSpecCreator newSpecCreator = new PMMLPortObjectSpecCreator(spec);
    // newSpecCreator.addPreprocColNames(m_content.getVectorLengths().entrySet().stream()
    // .flatMap(
    // e -> IntStream.iterate(0, o -> o + 1).limit(e.getValue()).mapToObj(i -> e.getKey() + "[" + i + "]"))
    // .collect(Collectors.toList()));
    PMMLMiningSchemaTranslator.writeMiningSchema(spec, reg);
    // if (!m_content.getVectorLengths().isEmpty()) {
    // Extension miningExtension = reg.getMiningSchema().addNewExtension();
    // miningExtension.setExtender(EXTENDER);
    // miningExtension.setName(VECTOR_COLUMNS_WITH_LENGTH);
    // miningExtension.setValue(jsonBuilder.build().toString());
    // }
    reg.setModelType(getPMMLRegModelType(m_content.getModelType()));
    reg.setFunctionName(getPMMLMiningFunction(m_content.getFunctionName()));
    String algorithmName = m_content.getAlgorithmName();
    if (algorithmName != null && !algorithmName.isEmpty()) {
        reg.setAlgorithmName(algorithmName);
    }
    String modelName = m_content.getModelName();
    if (modelName != null && !modelName.isEmpty()) {
        reg.setModelName(modelName);
    }
    String targetReferenceCategory = m_content.getTargetReferenceCategory();
    if (targetReferenceCategory != null && !targetReferenceCategory.isEmpty()) {
        reg.setTargetReferenceCategory(targetReferenceCategory);
    }
    if (m_content.getOffsetValue() != null) {
        reg.setOffsetValue(m_content.getOffsetValue());
    }
    // add parameter list
    ParameterList paramList = reg.addNewParameterList();
    for (PMMLParameter p : m_content.getParameterList()) {
        Parameter param = paramList.addNewParameter();
        param.setName(p.getName());
        String label = p.getLabel();
        if (label != null) {
            param.setLabel(m_nameMapper.getDerivedFieldName(label));
        }
    }
    // add factor list
    FactorList factorList = reg.addNewFactorList();
    for (PMMLPredictor p : m_content.getFactorList()) {
        Predictor predictor = factorList.addNewPredictor();
        predictor.setName(m_nameMapper.getDerivedFieldName(p.getName()));
    }
    // add covariate list
    CovariateList covariateList = reg.addNewCovariateList();
    for (PMMLPredictor p : m_content.getCovariateList()) {
        Predictor predictor = covariateList.addNewPredictor();
        predictor.setName(m_nameMapper.getDerivedFieldName(p.getName()));
    }
    // add PPMatrix
    PPMatrix ppMatrix = reg.addNewPPMatrix();
    for (PMMLPPCell p : m_content.getPPMatrix()) {
        PPCell cell = ppMatrix.addNewPPCell();
        cell.setValue(p.getValue());
        cell.setPredictorName(m_nameMapper.getDerivedFieldName(p.getPredictorName()));
        cell.setParameterName(p.getParameterName());
        String targetCategory = p.getTargetCategory();
        if (targetCategory != null && !targetCategory.isEmpty()) {
            cell.setTargetCategory(targetCategory);
        }
    }
    // add CovMatrix
    if (m_content.getPCovMatrix().length > 0) {
        PCovMatrix pCovMatrix = reg.addNewPCovMatrix();
        for (PMMLPCovCell p : m_content.getPCovMatrix()) {
            PCovCell covCell = pCovMatrix.addNewPCovCell();
            covCell.setPRow(p.getPRow());
            covCell.setPCol(p.getPCol());
            String tCol = p.getTCol();
            String tRow = p.getTRow();
            if (tRow != null || tCol != null) {
                covCell.setTRow(tRow);
                covCell.setTCol(tCol);
            }
            covCell.setValue(p.getValue());
            String targetCategory = p.getTargetCategory();
            if (targetCategory != null && !targetCategory.isEmpty()) {
                covCell.setTargetCategory(targetCategory);
            }
        }
    }
    // add ParamMatrix
    ParamMatrix paramMatrix = reg.addNewParamMatrix();
    for (PMMLPCell p : m_content.getParamMatrix()) {
        PCell pCell = paramMatrix.addNewPCell();
        String targetCategory = p.getTargetCategory();
        if (targetCategory != null) {
            pCell.setTargetCategory(targetCategory);
        }
        pCell.setParameterName(p.getParameterName());
        pCell.setBeta(p.getBeta());
        Integer df = p.getDf();
        if (df != null) {
            pCell.setDf(BigInteger.valueOf(df));
        }
    }
    return GeneralRegressionModel.type;
}