Examples with PMMLPortObjectSpec org.knime.core.node.port.pmml.PMMLPortObjectSpec used on opensource projects

Example 1 with PMMLPortObjectSpec

use of org.knime.core.node.port.pmml.PMMLPortObjectSpec in project knime-core by knime.

the class RuleEngine2PortsNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] inData, final ExecutionContext exec) throws Exception {
    BufferedDataTable data = (BufferedDataTable) inData[DATA_PORT];
    m_rowCount = data.size();
    try {
        Pair<ColumnRearranger, PortObject> rearrangerPair = createColumnRearranger((DataTableSpec) inData[DATA_PORT].getSpec(), new DataTableRowInput((DataTable) inData[RULE_PORT]));
        BufferedDataTable predictedTable = exec.createColumnRearrangeTable(data, rearrangerPair.getFirst(), exec);
        PortObject second = rearrangerPair.getSecond();
        if (m_settings.isPMMLRuleSet()) {
            if (m_settings.isProvideStatistics()) {
                PMMLPortObject po = (PMMLPortObject) rearrangerPair.getSecond();
                PMMLPortObject pmmlPortObject = new PMMLPortObject(m_copy.getSpec(), po);
                // Remove extra model.
                pmmlPortObject.addModelTranslater(new PMMLTranslator() {

                    @Override
                    public void initializeFrom(final PMMLDocument pmmlDoc) {
                    }

                    @Override
                    public SchemaType exportTo(final PMMLDocument pmmlDoc, final PMMLPortObjectSpec spec) {
                        return null;
                    }
                });
                second = pmmlPortObject;
            } else {
                second = m_copy;
            }
        }
        return new PortObject[] { predictedTable, second };
    } finally {
        m_rowCount = -1;
    }
}

Example 2 with PMMLPortObjectSpec

use of org.knime.core.node.port.pmml.PMMLPortObjectSpec in project knime-core by knime.

the class PMMLRuleEditorNodeModel method computeSpecs.

/**
 * Computes the specs after applying the derived fields.
 *
 * @param specs The input table and the possible preprocessing port.
 * @return The computed (original+preproc) input table's specification.
 */
@Deprecated
static DataTableSpec computeSpecs(final PortObjectSpec[] specs) {
    final DataTableSpec tableSpec = (DataTableSpec) specs[0];
    if (specs[1] == null) {
        return tableSpec;
    }
    PMMLPortObjectSpec portObjectSpec = (PMMLPortObjectSpec) specs[1];
    List<DataColumnSpec> preprocessingCols = portObjectSpec.getPreprocessingCols();
    DataTableSpecCreator creator = new DataTableSpecCreator(tableSpec);
    for (DataColumnSpec spec : preprocessingCols) {
        creator.addColumns(spec);
    }
    return creator.createSpec();
}

Example 3 with PMMLPortObjectSpec

use of org.knime.core.node.port.pmml.PMMLPortObjectSpec in project knime-core by knime.

the class PMMLRuleSetPredictorNodeModel method configure.

/**
 * {@inheritDoc}
 */
@Override
protected DataTableSpec[] configure(final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    DataTableSpec original = (DataTableSpec) inSpecs[DATA_INDEX];
    ColumnRearranger rearranger = new ColumnRearranger(original);
    PMMLPortObjectSpec portObjectSpec = (PMMLPortObjectSpec) inSpecs[MODEL_INDEX];
    List<DataColumnSpec> activeColumnList = portObjectSpec.getActiveColumnList();
    List<DataColumnSpec> notFound = new ArrayList<DataColumnSpec>();
    for (DataColumnSpec dataColumnSpec : activeColumnList) {
        if (original.containsName(dataColumnSpec.getName())) {
            DataColumnSpec origSpec = original.getColumnSpec(dataColumnSpec.getName());
            if (!origSpec.getType().equals(dataColumnSpec.getType())) {
                notFound.add(dataColumnSpec);
            }
        } else {
            notFound.add(dataColumnSpec);
        }
    }
    if (!notFound.isEmpty()) {
        StringBuilder sb = new StringBuilder("Incompatible to the table, the following columns are not present, or have a wrong type:");
        for (DataColumnSpec dataColumnSpec : notFound) {
            sb.append("\n   ").append(dataColumnSpec);
        }
        throw new InvalidSettingsException(sb.toString());
    }
    List<DataColumnSpec> targetCols = portObjectSpec.getTargetCols();
    final DataType dataType = targetCols.isEmpty() ? StringCell.TYPE : targetCols.get(0).getType();
    DataColumnSpecCreator specCreator;
    if (m_doReplaceColumn.getBooleanValue()) {
        String col = m_replaceColumn.getStringValue();
        specCreator = new DataColumnSpecCreator(col, dataType);
    } else {
        specCreator = new DataColumnSpecCreator(DataTableSpec.getUniqueColumnName(original, m_outputColumn.getStringValue()), dataType);
    }
    SingleCellFactory dummy = new SingleCellFactory(specCreator.createSpec()) {

        /**
         * {@inheritDoc}
         */
        @Override
        public DataCell getCell(final DataRow row) {
            throw new IllegalStateException();
        }
    };
    if (m_addConfidence.getBooleanValue()) {
        rearranger.append(new SingleCellFactory(new DataColumnSpecCreator(DataTableSpec.getUniqueColumnName(rearranger.createSpec(), m_confidenceColumn.getStringValue()), DoubleCell.TYPE).createSpec()) {

            @Override
            public DataCell getCell(final DataRow row) {
                throw new IllegalStateException();
            }
        });
    }
    if (m_doReplaceColumn.getBooleanValue()) {
        rearranger.replace(dummy, m_replaceColumn.getStringValue());
    } else {
        rearranger.append(dummy);
    }
    return new DataTableSpec[] { rearranger.createSpec() };
}

Example 4 with PMMLPortObjectSpec

use of org.knime.core.node.port.pmml.PMMLPortObjectSpec in project knime-core by knime.

the class DecTreePredictorNodeModel method createOutTableSpec.

private DataTableSpec createOutTableSpec(final PortObjectSpec[] inSpecs) {
    LinkedList<DataCell> predValues = null;
    if (m_showDistribution.getBooleanValue()) {
        predValues = getPredictionValues((PMMLPortObjectSpec) inSpecs[INMODELPORT]);
        if (predValues == null) {
            // no out spec can be determined
            return null;
        }
    }
    int numCols = (predValues == null ? 0 : predValues.size()) + 1;
    DataTableSpec inSpec = (DataTableSpec) inSpecs[INDATAPORT];
    UniqueNameGenerator nameGenerator = new UniqueNameGenerator(inSpec);
    DataColumnSpec[] newCols = new DataColumnSpec[numCols];
    /* Set bar renderer and domain [0,1] as default for the double cells
         * containing the distribution */
    // DataColumnProperties propsRendering = new DataColumnProperties(
    // Collections.singletonMap(
    // DataValueRenderer.PROPERTY_PREFERRED_RENDERER,
    // DoubleBarRenderer.DESCRIPTION));
    DataColumnDomain domain = new DataColumnDomainCreator(new DoubleCell(0.0), new DoubleCell(1.0)).createDomain();
    // add all distribution columns
    for (int i = 0; i < numCols - 1; i++) {
        DataColumnSpecCreator colSpecCreator = nameGenerator.newCreator(predValues.get(i).toString(), DoubleCell.TYPE);
        // colSpecCreator.setProperties(propsRendering);
        colSpecCreator.setDomain(domain);
        newCols[i] = colSpecCreator.createSpec();
    }
    // add the prediction column
    newCols[numCols - 1] = nameGenerator.newColumn("Prediction (DecTree)", StringCell.TYPE);
    DataTableSpec newColSpec = new DataTableSpec(newCols);
    return new DataTableSpec(inSpec, newColSpec);
}

Example 5 with PMMLPortObjectSpec

use of org.knime.core.node.port.pmml.PMMLPortObjectSpec in project knime-core by knime.

the class MLPPredictorNodeModel method configure.

/**
 * The additional columns are created based on the model which is loaded in
 * the execute-method. Therefore, new DataTableSpecs are not available until
 * execute has been called.
 *
 * {@inheritDoc}
 */
@Override
protected PortObjectSpec[] configure(final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    PMMLPortObjectSpec modelspec = (PMMLPortObjectSpec) inSpecs[0];
    DataTableSpec testSpec = (DataTableSpec) inSpecs[1];
    List<DataColumnSpec> targetCols = modelspec.getTargetCols();
    if (targetCols.isEmpty()) {
        throw new InvalidSettingsException("The PMML model" + " does not specify a target column for the prediction.");
    }
    DataColumnSpec targetCol = targetCols.iterator().next();
    /*
         * Check consistency between model and inputs, find columns to work on.
         */
    for (String incol : modelspec.getLearningFields()) {
        if (!testSpec.containsName(incol)) {
            throw new InvalidSettingsException("Could not find " + incol + " in inputspec");
        }
    }
    m_columns = getLearningColumnIndices(testSpec, modelspec);
    MLPClassificationFactory mymlp;
    // Regression
    if (targetCol.getType().isCompatible(DoubleValue.class)) {
        mymlp = new MLPClassificationFactory(true, m_columns, targetCol);
    } else {
        // Classification
        mymlp = new MLPClassificationFactory(false, m_columns, targetCol);
    }
    ColumnRearranger colre = new ColumnRearranger(testSpec);
    colre.append(mymlp);
    return new DataTableSpec[] { colre.createSpec() };
}