Examples with PMMLRuleParser org.knime.base.node.rules.engine.pmml.PMMLRuleParser used on opensource projects

Example 1 with PMMLRuleParser

use of org.knime.base.node.rules.engine.pmml.PMMLRuleParser in project knime-core by knime.

the class RuleEngine2PortsNodeModel method computeRearrangerWithPMML.

/**
 * @param spec
 * @param rules
 * @param flowVars
 * @param ruleIdx
 * @param outcomeIdx
 * @param confidenceIdx
 * @param weightIdx
 * @param validationIdx
 * @param outputColumnName
 * @return
 * @throws InterruptedException
 * @throws InvalidSettingsException
 */
private Pair<ColumnRearranger, PortObject> computeRearrangerWithPMML(final DataTableSpec spec, final RowInput rules, final Map<String, FlowVariable> flowVars, final int ruleIdx, final int outcomeIdx, final int confidenceIdx, final int weightIdx, final int validationIdx, final String outputColumnName) throws InterruptedException, InvalidSettingsException {
    PortObject po;
    ColumnRearranger ret;
    PMMLDocument doc = PMMLDocument.Factory.newInstance();
    final PMML pmmlObj = doc.addNewPMML();
    RuleSetModel ruleSetModel = pmmlObj.addNewRuleSetModel();
    RuleSet ruleSet = ruleSetModel.addNewRuleSet();
    List<DataType> outcomeTypes = new ArrayList<>();
    PMMLRuleParser parser = new PMMLRuleParser(spec, flowVars);
    int lineNo = 0;
    DataRow ruleRow;
    while ((ruleRow = rules.poll()) != null) {
        ++lineNo;
        DataCell rule = ruleRow.getCell(ruleIdx);
        CheckUtils.checkSetting(!rule.isMissing(), "Missing rule in row: " + ruleRow.getKey());
        if (rule instanceof StringValue) {
            StringValue ruleText = (StringValue) rule;
            String r = ruleText.getStringValue().replaceAll("[\r\n]+", " ");
            if (RuleSupport.isComment(r)) {
                continue;
            }
            if (outcomeIdx >= 0) {
                r += " => " + m_settings.asStringFailForMissing(ruleRow.getCell(outcomeIdx));
            }
            ParseState state = new ParseState(r);
            try {
                PMMLPredicate condition = parser.parseBooleanExpression(state);
                SimpleRule simpleRule = ruleSet.addNewSimpleRule();
                setCondition(simpleRule, condition);
                state.skipWS();
                state.consumeText("=>");
                state.skipWS();
                Expression outcome = parser.parseOutcomeOperand(state, null);
                simpleRule.setScore(outcome.toString());
                if (confidenceIdx >= 0) {
                    DataCell confidenceCell = ruleRow.getCell(confidenceIdx);
                    if (!confidenceCell.isMissing()) {
                        if (confidenceCell instanceof DoubleValue) {
                            DoubleValue dv = (DoubleValue) confidenceCell;
                            double confidence = dv.getDoubleValue();
                            simpleRule.setConfidence(confidence);
                        }
                    }
                }
                if (weightIdx >= 0) {
                    DataCell weightCell = ruleRow.getCell(weightIdx);
                    boolean missing = true;
                    if (!weightCell.isMissing()) {
                        if (weightCell instanceof DoubleValue) {
                            DoubleValue dv = (DoubleValue) weightCell;
                            double weight = dv.getDoubleValue();
                            simpleRule.setWeight(weight);
                            missing = false;
                        }
                    }
                    if (missing && m_settings.isHasDefaultWeight()) {
                        simpleRule.setWeight(m_settings.getDefaultWeight());
                    }
                }
                CheckUtils.checkSetting(outcome.isConstant(), "Outcome is not constant in line " + lineNo + " (" + ruleRow.getKey() + ") for rule: " + rule);
                outcomeTypes.add(outcome.getOutputType());
            } catch (ParseException e) {
                ParseException error = Util.addContext(e, r, lineNo);
                throw new InvalidSettingsException("Wrong rule in line: " + ruleRow.getKey() + "\n" + error.getMessage(), error);
            }
        } else {
            CheckUtils.checkSetting(false, "Wrong type (" + rule.getType() + ") of rule: " + rule + "\nin row: " + ruleRow.getKey());
        }
    }
    ColumnRearranger dummy = new ColumnRearranger(spec);
    if (!m_settings.isReplaceColumn()) {
        dummy.append(new SingleCellFactory(new DataColumnSpecCreator(outputColumnName, RuleEngineNodeModel.computeOutputType(outcomeTypes, computeOutcomeType(rules.getDataTableSpec()), true, m_settings.isDisallowLongOutputForCompatibility())).createSpec()) {

            @Override
            public DataCell getCell(final DataRow row) {
                return null;
            }
        });
    }
    PMMLPortObject pmml = createPMMLPortObject(doc, ruleSetModel, ruleSet, parser, dummy.createSpec());
    po = pmml;
    m_copy = copy(pmml);
    String predictionConfidenceColumn = m_settings.getPredictionConfidenceColumn();
    if (predictionConfidenceColumn == null || predictionConfidenceColumn.isEmpty()) {
        predictionConfidenceColumn = RuleEngine2PortsSettings.DEFAULT_PREDICTION_CONFIDENCE_COLUMN;
    }
    ret = PMMLRuleSetPredictorNodeModel.createRearranger(pmml, spec, m_settings.isReplaceColumn(), outputColumnName, m_settings.isComputeConfidence(), DataTableSpec.getUniqueColumnName(dummy.createSpec(), predictionConfidenceColumn), validationIdx);
    return Pair.create(ret, po);
}