Examples with ArrayType org.dmg.pmml.ArrayType used on opensource projects

Example 1 with ArrayType

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

the class TreeModelPMMLTranslator method setValuesFromPMMLSimpleSetPredicate.

private static void setValuesFromPMMLSimpleSetPredicate(final SimpleSetPredicate to, final PMMLSimpleSetPredicate from) {
    to.setField(from.getSplitAttribute());
    final Enum operator;
    final PMMLSetOperator setOp = from.getSetOperator();
    switch(setOp) {
        case IS_IN:
            operator = SimpleSetPredicate.BooleanOperator.IS_IN;
            break;
        case IS_NOT_IN:
            operator = SimpleSetPredicate.BooleanOperator.IS_NOT_IN;
            break;
        default:
            throw new IllegalStateException("Unknown set operator \"" + setOp + "\".");
    }
    to.setBooleanOperator(operator);
    final Set<String> values = from.getValues();
    ArrayType array = to.addNewArray();
    array.setN(BigInteger.valueOf(values.size()));
    org.w3c.dom.Node arrayNode = array.getDomNode();
    arrayNode.appendChild(arrayNode.getOwnerDocument().createTextNode(setToWhitspaceSeparatedString(values)));
    final org.dmg.pmml.ArrayType.Type.Enum type;
    final PMMLArrayType arrayType = from.getArrayType();
    switch(arrayType) {
        case INT:
            type = ArrayType.Type.INT;
            break;
        case REAL:
            type = ArrayType.Type.REAL;
            break;
        case STRING:
            type = ArrayType.Type.STRING;
            break;
        default:
            throw new IllegalStateException("Unknown array type \"" + arrayType + "\".");
    }
    array.setType(type);
}

Example 2 with ArrayType

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

the class PMMLClusterTranslator method exportTo.

/**
 * {@inheritDoc}
 */
@Override
public SchemaType exportTo(final PMMLDocument pmmlDoc, final PMMLPortObjectSpec spec) {
    DerivedFieldMapper mapper = new DerivedFieldMapper(pmmlDoc);
    PMML pmml = pmmlDoc.getPMML();
    ClusteringModelDocument.ClusteringModel clusteringModel = pmml.addNewClusteringModel();
    PMMLMiningSchemaTranslator.writeMiningSchema(spec, clusteringModel);
    // ---------------------------------------------------
    // set clustering model attributes
    clusteringModel.setModelName("k-means");
    clusteringModel.setFunctionName(MININGFUNCTION.CLUSTERING);
    clusteringModel.setModelClass(ModelClass.CENTER_BASED);
    clusteringModel.setNumberOfClusters(BigInteger.valueOf(m_nrOfClusters));
    // ---------------------------------------------------
    // set comparison measure
    ComparisonMeasureDocument.ComparisonMeasure pmmlComparisonMeasure = clusteringModel.addNewComparisonMeasure();
    pmmlComparisonMeasure.setKind(Kind.DISTANCE);
    if (ComparisonMeasure.squaredEuclidean.equals(m_measure)) {
        pmmlComparisonMeasure.addNewSquaredEuclidean();
    } else {
        pmmlComparisonMeasure.addNewEuclidean();
    }
    // set clustering fields
    for (String colName : m_usedColumns) {
        ClusteringFieldDocument.ClusteringField pmmlClusteringField = clusteringModel.addNewClusteringField();
        pmmlClusteringField.setField(mapper.getDerivedFieldName(colName));
        pmmlClusteringField.setCompareFunction(COMPAREFUNCTION.ABS_DIFF);
    }
    // ----------------------------------------------------
    // set clusters
    int i = 0;
    for (double[] prototype : m_prototypes) {
        ClusterDocument.Cluster pmmlCluster = clusteringModel.addNewCluster();
        String name = CLUSTER_NAME_PREFIX + i;
        pmmlCluster.setName(name);
        if (m_clusterCoverage != null && m_clusterCoverage.length == m_prototypes.length) {
            pmmlCluster.setSize(BigInteger.valueOf(m_clusterCoverage[i]));
        }
        i++;
        ArrayType pmmlArray = pmmlCluster.addNewArray();
        pmmlArray.setN(BigInteger.valueOf(prototype.length));
        pmmlArray.setType(Type.REAL);
        StringBuffer buff = new StringBuffer();
        for (double d : prototype) {
            buff.append(d + " ");
        }
        XmlCursor xmlCursor = pmmlArray.newCursor();
        xmlCursor.setTextValue(buff.toString());
        xmlCursor.dispose();
    }
    return ClusteringModel.type;
}

Example 3 with ArrayType

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

the class PMMLClusterTranslator method initializeFrom.

/**
 * {@inheritDoc}
 */
@Override
public void initializeFrom(final PMMLDocument pmmlDoc) {
    PMML pmml = pmmlDoc.getPMML();
    DerivedFieldMapper mapper = new DerivedFieldMapper(pmmlDoc);
    ClusteringModelDocument.ClusteringModel pmmlClusteringModel = pmml.getClusteringModelArray(0);
    // initialize ClusteringFields
    for (ClusteringField cf : pmmlClusteringModel.getClusteringFieldArray()) {
        m_usedColumns.add(mapper.getColumnName(cf.getField()));
        if (COMPAREFUNCTION.ABS_DIFF != cf.getCompareFunction()) {
            LOGGER.error("Comparison Function " + cf.getCompareFunction().toString() + " is not supported!");
            throw new IllegalArgumentException("Only the absolute difference (\"absDiff\") as " + "compare function is supported!");
        }
    }
    // ---------------------------------------------------
    // initialize Clusters
    m_nrOfClusters = pmmlClusteringModel.sizeOfClusterArray();
    m_prototypes = new double[m_nrOfClusters][m_usedColumns.size()];
    m_labels = new String[m_nrOfClusters];
    m_clusterCoverage = new int[m_nrOfClusters];
    for (int i = 0; i < m_nrOfClusters; i++) {
        ClusterDocument.Cluster currentCluster = pmmlClusteringModel.getClusterArray(i);
        m_labels[i] = currentCluster.getName();
        // in KNIME learner: m_labels[i] = "cluster_" + i;
        ArrayType clusterArray = currentCluster.getArray();
        String content = clusterArray.newCursor().getTextValue();
        String[] stringValues;
        content = content.trim();
        if (content.contains(DOUBLE_QUOT)) {
            content = content.replace(BACKSLASH + DOUBLE_QUOT, TAB);
            /* TODO We need to take care of the cases with double quots,
                 * e.g ==> <Array n="3" type="string">"Cheval  Blanc" "TABTAB"
                 "Latour"</Array> */
            stringValues = content.split(DOUBLE_QUOT + SPACE);
            for (int j = 0; j < stringValues.length; j++) {
                stringValues[j] = stringValues[j].replace(DOUBLE_QUOT, "");
                stringValues[j] = stringValues[j].replace(TAB, DOUBLE_QUOT);
                stringValues[j] = stringValues[j].trim();
            }
        } else {
            stringValues = content.split("\\s+");
        }
        for (int j = 0; j < m_usedColumns.size(); j++) {
            m_prototypes[i][j] = Double.valueOf(stringValues[j]);
        }
        if (currentCluster.isSetSize()) {
            m_clusterCoverage[i] = currentCluster.getSize().intValue();
        }
    }
    if (pmmlClusteringModel.isSetMissingValueWeights()) {
        ArrayType weights = pmmlClusteringModel.getMissingValueWeights().getArray();
        String content = weights.newCursor().getTextValue();
        String[] stringValues;
        Double[] weightValues;
        content = content.trim();
        if (content.contains(DOUBLE_QUOT)) {
            content = content.replace(BACKSLASH + DOUBLE_QUOT, TAB);
            /* TODO We need to take care of the cases with double quots,
                 * e.g ==> <Array n="3" type="string">"Cheval  Blanc" "TABTAB"
                 "Latour"</Array> */
            stringValues = content.split(DOUBLE_QUOT + SPACE);
            weightValues = new Double[stringValues.length];
            for (int j = 0; j < stringValues.length; j++) {
                stringValues[j] = stringValues[j].replace(DOUBLE_QUOT, "");
                stringValues[j] = stringValues[j].replace(TAB, DOUBLE_QUOT);
                stringValues[j] = stringValues[j].trim();
                weightValues[j] = Double.valueOf(stringValues[j]);
                if (weightValues[j] == null || weightValues[j].doubleValue() != 1.0) {
                    String msg = "Missing Value Weight not equals one" + " is not supported!";
                    LOGGER.error(msg);
                }
            }
        } else {
            stringValues = content.split("\\s+");
        }
    }
    // ------------------------------------------
    // initialize m_usedColumns from ClusteringField
    ClusteringFieldDocument.ClusteringField[] clusteringFieldArray = pmmlClusteringModel.getClusteringFieldArray();
    for (ClusteringField cf : clusteringFieldArray) {
        m_usedColumns.add(mapper.getColumnName(cf.getField()));
    }
    // --------------------------------------------
    // initialize Comparison Measure
    ComparisonMeasureDocument.ComparisonMeasure pmmlComparisonMeasure = pmmlClusteringModel.getComparisonMeasure();
    if (pmmlComparisonMeasure.isSetSquaredEuclidean()) {
        m_measure = ComparisonMeasure.squaredEuclidean;
    } else if (pmmlComparisonMeasure.isSetEuclidean()) {
        m_measure = ComparisonMeasure.euclidean;
    } else {
        String measure = pmmlComparisonMeasure.getDomNode().getFirstChild().getNodeName();
        throw new IllegalArgumentException("\"" + ComparisonMeasure.euclidean + "\" and \"" + ComparisonMeasure.squaredEuclidean + "\" are the only supported comparison " + "measures! Found " + measure + ".");
    }
    if (Kind.SIMILARITY == pmmlComparisonMeasure.getKind()) {
        LOGGER.error("A Similarity Kind of Comparison Measure is not " + "supported!");
    }
}

Example 4 with ArrayType

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

the class PMMLDecisionTreeTranslator method addTreeNode.

/**
 * A recursive function which converts each KNIME Tree node to a
 * corresponding PMML element.
 *
 * @param pmmlNode the desired PMML element
 * @param node A KNIME DecisionTree node
 */
private static void addTreeNode(final NodeDocument.Node pmmlNode, final DecisionTreeNode node, final DerivedFieldMapper mapper) {
    pmmlNode.setId(String.valueOf(node.getOwnIndex()));
    pmmlNode.setScore(node.getMajorityClass().toString());
    // read in and then exported again
    if (node.getEntireClassCount() > 0) {
        pmmlNode.setRecordCount(node.getEntireClassCount());
    }
    if (node instanceof DecisionTreeNodeSplitPMML) {
        int defaultChild = ((DecisionTreeNodeSplitPMML) node).getDefaultChildIndex();
        if (defaultChild > -1) {
            pmmlNode.setDefaultChild(String.valueOf(defaultChild));
        }
    }
    // adding score and stuff from parent
    DecisionTreeNode parent = node.getParent();
    if (parent == null) {
        // When the parent is null, it is the root Node.
        // For root node, the predicate is always True.
        pmmlNode.addNewTrue();
    } else if (parent instanceof DecisionTreeNodeSplitContinuous) {
        // SimplePredicate case
        DecisionTreeNodeSplitContinuous splitNode = (DecisionTreeNodeSplitContinuous) parent;
        if (splitNode.getIndex(node) == 0) {
            SimplePredicate pmmlSimplePredicate = pmmlNode.addNewSimplePredicate();
            pmmlSimplePredicate.setField(mapper.getDerivedFieldName(splitNode.getSplitAttr()));
            pmmlSimplePredicate.setOperator(Operator.LESS_OR_EQUAL);
            pmmlSimplePredicate.setValue(String.valueOf(splitNode.getThreshold()));
        } else if (splitNode.getIndex(node) == 1) {
            pmmlNode.addNewTrue();
        }
    } else if (parent instanceof DecisionTreeNodeSplitNominalBinary) {
        // SimpleSetPredicate case
        DecisionTreeNodeSplitNominalBinary splitNode = (DecisionTreeNodeSplitNominalBinary) parent;
        SimpleSetPredicate pmmlSimpleSetPredicate = pmmlNode.addNewSimpleSetPredicate();
        pmmlSimpleSetPredicate.setField(mapper.getDerivedFieldName(splitNode.getSplitAttr()));
        pmmlSimpleSetPredicate.setBooleanOperator(SimpleSetPredicate.BooleanOperator.IS_IN);
        ArrayType pmmlArray = pmmlSimpleSetPredicate.addNewArray();
        pmmlArray.setType(ArrayType.Type.STRING);
        DataCell[] splitValues = splitNode.getSplitValues();
        List<Integer> indices = null;
        if (splitNode.getIndex(node) == SplitNominalBinary.LEFT_PARTITION) {
            indices = splitNode.getLeftChildIndices();
        } else if (splitNode.getIndex(node) == SplitNominalBinary.RIGHT_PARTITION) {
            indices = splitNode.getRightChildIndices();
        } else {
            throw new IllegalArgumentException("Split node is neither " + "contained in the right nor in the left partition.");
        }
        StringBuilder classSet = new StringBuilder();
        for (Integer i : indices) {
            if (classSet.length() > 0) {
                classSet.append(" ");
            }
            classSet.append(splitValues[i].toString());
        }
        pmmlArray.setN(BigInteger.valueOf(indices.size()));
        XmlCursor xmlCursor = pmmlArray.newCursor();
        xmlCursor.setTextValue(classSet.toString());
        xmlCursor.dispose();
    } else if (parent instanceof DecisionTreeNodeSplitNominal) {
        DecisionTreeNodeSplitNominal splitNode = (DecisionTreeNodeSplitNominal) parent;
        SimplePredicate pmmlSimplePredicate = pmmlNode.addNewSimplePredicate();
        pmmlSimplePredicate.setField(mapper.getDerivedFieldName(splitNode.getSplitAttr()));
        pmmlSimplePredicate.setOperator(Operator.EQUAL);
        int nodeIndex = parent.getIndex(node);
        pmmlSimplePredicate.setValue(String.valueOf(splitNode.getSplitValues()[nodeIndex].toString()));
    } else if (parent instanceof DecisionTreeNodeSplitPMML) {
        DecisionTreeNodeSplitPMML splitNode = (DecisionTreeNodeSplitPMML) parent;
        int nodeIndex = parent.getIndex(node);
        // get the PMML predicate of the current node from its parent
        PMMLPredicate predicate = splitNode.getSplitPred()[nodeIndex];
        if (predicate instanceof PMMLCompoundPredicate) {
            // surrogates as used in GBT
            exportCompoundPredicate(pmmlNode, (PMMLCompoundPredicate) predicate, mapper);
        } else {
            predicate.setSplitAttribute(mapper.getDerivedFieldName(predicate.getSplitAttribute()));
            // delegate the writing to the predicate translator
            PMMLPredicateTranslator.exportTo(predicate, pmmlNode);
        }
    } else {
        throw new IllegalArgumentException("Node Type " + parent.getClass() + " is not supported!");
    }
    // adding score distribution (class counts)
    Set<Entry<DataCell, Double>> classCounts = node.getClassCounts().entrySet();
    Iterator<Entry<DataCell, Double>> iterator = classCounts.iterator();
    while (iterator.hasNext()) {
        Entry<DataCell, Double> entry = iterator.next();
        DataCell cell = entry.getKey();
        Double freq = entry.getValue();
        ScoreDistribution pmmlScoreDist = pmmlNode.addNewScoreDistribution();
        pmmlScoreDist.setValue(cell.toString());
        pmmlScoreDist.setRecordCount(freq);
    }
    // adding children
    if (!(node instanceof DecisionTreeNodeLeaf)) {
        for (int i = 0; i < node.getChildCount(); i++) {
            addTreeNode(pmmlNode.addNewNode(), node.getChildAt(i), mapper);
        }
    }
}

Example 5 with ArrayType

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

the class PMMLPredicateTranslator method initSimpleSetPred.

/**
 * Converts a {@link PMMLSimpleSetPredicate} ({@code sp}) to a {@link SimpleSetPredicate} ({@code setPred}).
 *
 * @param sp A {@link PMMLSimpleSetPredicate}.
 * @param setPred The {@link SimpleSetPredicate} to initialize.
 * @since 2.9
 */
public static void initSimpleSetPred(final PMMLSimpleSetPredicate sp, final SimpleSetPredicate setPred) {
    setPred.setField(sp.getSplitAttribute());
    setPred.setBooleanOperator(getOperator(sp.getSetOperator()));
    ArrayType array = setPred.addNewArray();
    array.setN(BigInteger.valueOf(sp.getValues().size()));
    array.setType(getType(sp.getArrayType()));
    // how to set content?
    StringBuffer sb = new StringBuffer();
    if (sp.getArrayType() == PMMLArrayType.STRING) {
        for (String value : sp.getValues()) {
            sb.append('"');
            sb.append(value.replace("\"", "\\\""));
            sb.append('"');
            sb.append(' ');
        }
    } else {
        for (String value : sp.getValues()) {
            sb.append(value);
            sb.append(' ');
        }
    }
    XmlCursor xmlCursor = array.newCursor();
    xmlCursor.setTextValue(sb.toString());
    xmlCursor.dispose();
}