Uses of Interface
org.knime.core.data.DataRow

Packages that use DataRow
org.knime.base.data.append.column   
org.knime.base.data.append.row   
org.knime.base.data.bitvector This package contains classes responsible for the representation and conversion of bit vectors. 
org.knime.base.data.filter.column Contains column filter for DataTable objects which includes or excludes a certain number of columns from a given data table. 
org.knime.base.data.filter.row Contains row filter for DataTable objects which uses the FilterRowGenerator interface to dynamically ask for included or excluded rows during itertation. 
org.knime.base.data.join Implementation of a DataTable that joins to underlying tables based on their row key (like a Database join). 
org.knime.base.data.normalize This package contains the utility classes for normalization of DataRows. 
org.knime.base.data.replace   
org.knime.base.data.sort   
org.knime.base.data.statistics This package holds the StatisticsTable. 
org.knime.base.node.flowvariable.tablerowtovariable   
org.knime.base.node.io.arffreader Contains the implementation of a node which reads ARFF files. 
org.knime.base.node.io.def (Obsolete) Node that produces predefined DataTables. 
org.knime.base.node.io.filereader Contains a node implementation that reads in data from an ASCII file. 
org.knime.base.node.mine.bayes.naivebayes.datamodel This package implements the naive bayes algorithm for numerical and nominal attributes. 
org.knime.base.node.mine.bayes.naivebayes.predictor This package contains the classes of the predictor node. 
org.knime.base.node.mine.bfn Contains abstract and util classes to train and perform prediction to rule models, also called BasisFunction models. 
org.knime.base.node.mine.bfn.fuzzy Contains the learner and predictor to train fuzzy rules and apply them to unknown data. 
org.knime.base.node.mine.bfn.radial Contains the PNN learner and predictor. 
org.knime.base.node.mine.cluster.assign This package contains the classes for the Cluster Assigner Node. 
org.knime.base.node.mine.cluster.fuzzycmeans The fuzzycmeans package contains all classes for the Fuzzy c-means node. 
org.knime.base.node.mine.cluster.hierarchical Contains the implementation of a node performing hierarchical clustering. 
org.knime.base.node.mine.cluster.hierarchical.distfunctions Contains distance function implementations for the Hierarchical Clustering node. 
org.knime.base.node.mine.decisiontree2   
org.knime.base.node.mine.decisiontree2.model This package contains code for a decision tree model. 
org.knime.base.node.mine.mds A node that applies multi dimensional scaling (MDS) on high dimensional data. 
org.knime.base.node.mine.mds.distances The package contains distance classes, computing various kinds of distances between DataRows and DataPoints ect. 
org.knime.base.node.mine.mds.mdsprojection A node that applies multi dimensional scaling (MDS) projection on high dimensional data. 
org.knime.base.node.mine.pca This package contains all classes for the PCA (principal component analysis) Node. 
org.knime.base.node.mine.regression Contains nodes and utility classes for linear and polynomial regression. 
org.knime.base.node.mine.regression.linear Contains classes for linear regression. 
org.knime.base.node.mine.sota.distances Contains classes to compute distances for SOTA. 
org.knime.base.node.mine.sota.logic Contains the logic classes of SOTA. 
org.knime.base.node.mine.sota.predictor Contains the Sotapredictor node, which can be used for class prediction of incoming data. 
org.knime.base.node.mine.subgroupminer.freqitemset This package contains the necessary data structures for the subgroup mining. 
org.knime.base.node.mine.svm.predictor This subpackage contains all classes for the SVM Predictor Node. 
org.knime.base.node.parallel.appender   
org.knime.base.node.parallel.builder   
org.knime.base.node.preproc.binner Contains a node to bin/group a number of numeric columns into a string column by predefined intervals. 
org.knime.base.node.preproc.cellsplit Contains the implementation of a node that splits (and replaces) a values in a column into multiple new ones. 
org.knime.base.node.preproc.cellsplitbypos   
org.knime.base.node.preproc.columnTrans This package contains the classes of the Many2One and One2Many column transformation nodes. 
org.knime.base.node.preproc.filter.row Contains a node filtering out rows from an input data table, including only those rows into the output/result table that match a certain criteria. 
org.knime.base.node.preproc.filter.row.rowfilter Contains all filters currently implemented for the row filter node. 
org.knime.base.node.preproc.missingval Implemenation of the node that treats missing values. 
org.knime.base.node.preproc.sample Node that samples rows from an input table. 
org.knime.base.node.preproc.setoperator Contains a node to perform a set operation on two columns from two input tables. 
org.knime.base.node.rules   
org.knime.base.node.util   
org.knime.base.node.viz.histogram.datamodel This package contains all data and visualization models which are used in the different histogram implementations. 
org.knime.base.node.viz.histogram.impl.interactive This is the interactive implementation of the abstract histogram plotter. 
org.knime.base.node.viz.pie.datamodel.fixed This package contains the fixed pie chart data model classes. 
org.knime.base.node.viz.pie.datamodel.interactive This package contains the interactive pie chart data model classes. 
org.knime.base.node.viz.plotter.dendrogram Contains all classes necessary to visualize a hierachical clustering result represented by a DendrogramNode
org.knime.core.data Contains the interface definitions of the DataCell and DataTable and related classes, used to store and access the actual data. 
org.knime.core.data.collection Definitions for KNIME collection types and default implementations. 
org.knime.core.data.container Implementation of a DataContainer
org.knime.core.data.def Provides default implementations for all (except DataTable) abstract classes in the data package.

The default implementations of classes derived from DataCell just store their values in members of the appropriate java type (like DoubleCell has a private member of Java type double, etc.).

The default implementation of DataTable is deprecated and shouldn't be used. 
org.knime.core.node.tableview Node implementation of a table view. 
 

Uses of DataRow in org.knime.base.data.append.column
 

Classes in org.knime.base.data.append.column that implement DataRow
 class AppendedColumnRow
          A DataRow that is extended by one or more cells.
 

Methods in org.knime.base.data.append.column that return DataRow
 DataRow AppendedColumnRowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.base.data.append.column with parameters of type DataRow
 DataCell[] AppendedCellFactory.getAppendedCell(DataRow row)
          Get the new cells for a given row.
 DataCell[] DefaultAppendedCellFactory.getAppendedCell(DataRow row)
          Get the value to row's key.
 

Constructors in org.knime.base.data.append.column with parameters of type DataRow
AppendedColumnRow(DataRow baseRow, DataCell... appendCell)
          Creates new Row with baseRow providing the first cells and appendCell as last cells.
AppendedColumnRow(DataRow baseRow, DataRow appendedRow, boolean[] appendColumn)
          Create a new row with the baseRow providing the first cells and appendedRow providing the following cells.
AppendedColumnRow(RowKey rowKey, DataRow baseRow, DataCell... appendCell)
          Creates new Row with baseRow providing the first cells and appendCell as last cells.
AppendedColumnRow(RowKey rowKey, DataRow baseRow, DataRow appendedRow)
          Create a new row with the baseRow providing the first cells and appendedRow providing the following cells.
AppendedColumnRow(RowKey rowKey, DataRow baseRow, DataRow appendedRow, boolean[] appendColumn)
          Create a new row with the baseRow providing the first cells and appendedRow providing the following cells.
 

Uses of DataRow in org.knime.base.data.append.row
 

Classes in org.knime.base.data.append.row that implement DataRow
 class ResortedCellsRow
          A row that takes a base row and re-sorts the cells in it according to an int[] parameter passed in the constructor.
 

Methods in org.knime.base.data.append.row that return DataRow
 DataRow AppendedRowsIterator.next()
          Returns the next DataRow.
 

Constructors in org.knime.base.data.append.row with parameters of type DataRow
ResortedCellsRow(DataRow row, int[] sort)
          Creates new row with row as underlying base row and sort the new sorting scheme.
 

Uses of DataRow in org.knime.base.data.bitvector
 

Methods in org.knime.base.data.bitvector with parameters of type DataRow
 DataCell IdString2BitVectorCellFactory.getCell(DataRow row)
          Called from getCells.
 DataCell Numeric2BitVectorMeanCellFactory.getCell(DataRow row)
          Called from getCells.
 DataCell Hex2BitVectorCellFactory.getCell(DataRow row)
          Called from getCells.
 DataCell BitString2BitVectorCellFactory.getCell(DataRow row)
          Called from getCells.
 DataCell Numeric2BitVectorThresholdCellFactory.getCell(DataRow row)
          Called from getCells.
 

Uses of DataRow in org.knime.base.data.filter.column
 

Classes in org.knime.base.data.filter.column that implement DataRow
 class FilterColumnRow
          Filter DataRow which extracts particular cells (columns) from an underlying row.
 

Methods in org.knime.base.data.filter.column that return DataRow
 DataRow CloseableFilterColumnRowIterator.next()
          Returns the next DataRow.
 DataRow FilterColumnRowIterator.next()
          Returns the next DataRow.
 

Constructors in org.knime.base.data.filter.column with parameters of type DataRow
FilterColumnRow(DataRow row, int[] columns)
          Inits a new filter column DataRow with the underling row and an array of indices into this row.
 

Uses of DataRow in org.knime.base.data.filter.row
 

Methods in org.knime.base.data.filter.row that return DataRow
 DataRow FilterRowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.base.data.filter.row with parameters of type DataRow
 boolean DoubleCellFilterRowGenerator.isIn(DataRow row)
          Checks if the given row lies within the define interval borders.
 boolean FilterRowGenerator.isIn(DataRow row)
           
 

Uses of DataRow in org.knime.base.data.join
 

Methods in org.knime.base.data.join that return DataRow
 DataRow JoinedTableRowIterator.next()
          Returns the next DataRow.
 DataRow InMemoryIterator.next()
          Returns the next DataRow.
 

Uses of DataRow in org.knime.base.data.normalize
 

Methods in org.knime.base.data.normalize that return DataRow
 DataRow AffineTransRowIterator.next()
          Returns the next DataRow.
 

Uses of DataRow in org.knime.base.data.replace
 

Classes in org.knime.base.data.replace that implement DataRow
 class ReplacedColumnsDataRow
           
 

Methods in org.knime.base.data.replace that return DataRow
 DataRow ReplacedColumnsRowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.base.data.replace with parameters of type DataRow
abstract  DataCell ReplacedCellFactory.getReplacement(DataRow row, int column)
          Computes the data cell that should replace the column-th column in the given row.
 DataCell[] ReplacedCellFactory.getReplacement(DataRow row, int[] columns)
          Returns an array of length 1 containing the replacement of the data cell at the position given in the first element of the columns array.
 DataCell[] ReplacedCellsFactory.getReplacement(DataRow row, int[] columns)
          Computes the data cells that should replace the column-th column in the given row.
 

Constructors in org.knime.base.data.replace with parameters of type DataRow
ReplacedColumnsDataRow(DataRow row, DataCell[] newCells, int[] columns)
          Creates a new replaced column row.
ReplacedColumnsDataRow(DataRow row, DataCell newCell, int column)
          Convenience constructor that replaces one cell only.
 

Uses of DataRow in org.knime.base.data.sort
 

Constructor parameters in org.knime.base.data.sort with type arguments of type DataRow
SortedTable(BufferedDataTable dataTable, Comparator<DataRow> rowComparator, boolean sortInMemory, ExecutionContext exec)
          Creates a new sorted table.
 

Uses of DataRow in org.knime.base.data.statistics
 

Methods in org.knime.base.data.statistics with parameters of type DataRow
protected  void StatisticsTable.calculateMomentInSubClass(DataRow row)
          Deprecated. Derived classes may do additional calculations here.
 

Uses of DataRow in org.knime.base.node.flowvariable.tablerowtovariable
 

Methods in org.knime.base.node.flowvariable.tablerowtovariable with parameters of type DataRow
protected  void TableToVariableNodeModel.pushVariables(DataTableSpec variablesSpec, DataRow currentVariables)
          Pushes the variable as given by the row argument onto the stack.
 

Uses of DataRow in org.knime.base.node.io.arffreader
 

Methods in org.knime.base.node.io.arffreader that return DataRow
 DataRow ARFFRowIterator.next()
          Returns the next DataRow.
 

Uses of DataRow in org.knime.base.node.io.def
 

Constructors in org.knime.base.node.io.def with parameters of type DataRow
DefaultTableNodeFactory(DataRow[] rows, DataTableSpec spec)
          Also this constructor is available in DefaultTable.
DefaultTableNodeFactory(DataRow[] rows, String[] columnNames, DataType[] columnTypes)
          We provide the same constructors as the DefaultTable.
DefaultTableNodeModel(DataRow[] rows, DataTableSpec spec)
          Also this constructor is available in DefaultTable.
DefaultTableNodeModel(DataRow[] rows, String[] columnNames, DataType[] columnTypes)
           
 

Uses of DataRow in org.knime.base.node.io.filereader
 

Methods in org.knime.base.node.io.filereader that return DataRow
(package private)  DataRow FileReaderException.getErrorRow()
           
 DataRow FileReaderPreviewRowIterator.next()
          Returns the next DataRow.
 DataRow FileRowIterator.next()
          Returns the next DataRow.
 

Constructors in org.knime.base.node.io.filereader with parameters of type DataRow
FileReaderException(String msg, DataRow faultyRow, int lineNumber)
          Constructor for an exception that stores the last (partial) row where things went wrong.
 

Uses of DataRow in org.knime.base.node.mine.bayes.naivebayes.datamodel
 

Methods in org.knime.base.node.mine.bayes.naivebayes.datamodel with parameters of type DataRow
 double[] NaiveBayesModel.getClassProbabilities(String[] attributeNames, DataRow row, List<String> classValues, boolean normalize, double laplaceCorrector)
           
 String NaiveBayesModel.getMostLikelyClass(String[] attrNames, DataRow row, double laplaceCorrector)
          Returns the name of the class with the highest probability for the given row.
 void NaiveBayesModel.updateModel(DataRow row, DataTableSpec tableSpec, int classColIdx)
          Updates the current NaiveBayesModel with the values from the given DataRow.
 

Uses of DataRow in org.knime.base.node.mine.bayes.naivebayes.predictor
 

Methods in org.knime.base.node.mine.bayes.naivebayes.predictor with parameters of type DataRow
 DataCell[] NaiveBayesCellFactory.getAppendedCell(DataRow row)
          Get the new cells for a given row.
 DataCell[] NaiveBayesCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.mine.bfn
 

Classes in org.knime.base.node.mine.bfn that implement DataRow
(package private)  class BasisFunctionFilterRow
          Inner class to separate an data input row into a new row which are the first n-1 double cells and returns the class label.
 class BasisFunctionLearnerRow
          General BasisFunctionLearnerRow prototype which provides functions to shrink, cover, and reset rules; and to be compared with others by its coverage.
 

Methods in org.knime.base.node.mine.bfn that return DataRow
 DataRow BasisFunctionLearnerRow.getAnchor()
          Returns the basisfunction's anchor vector.
 DataRow BasisFunctionIterator.next()
          Returns the next DataRow.
 DataRow BasisFunctionPredictorRowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.base.node.mine.bfn with parameters of type DataRow
 void BasisFunctionLearnerRow.addCovered(DataRow row, DataCell classInfo)
          If a new instance of this class is covered.
abstract  BasisFunctionLearnerRow BasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Returns a new row initialised by a DataRow as its initial center vector and a class label.
abstract  boolean BasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow o, DataRow r)
          Compares coverage of this and another row.
abstract  double BasisFunctionPredictorRow.compose(DataRow row, double act)
          Composes the activation of the given array and of the calculated one based on the given row.
 double Distance.compute(DataRow x, DataRow y)
          Computes the Euclidean distance between two normalized rows.
 double Distance.compute(double[] x, DataRow y)
          Computes the Euclidean distance between two normalized vectors.
 double Distance.compute(DoubleValue[] x, DataRow y)
          Computes the Euclidean distance between two normalized vectors.
abstract  double BasisFunctionLearnerRow.computeActivation(DataRow row)
          Computes activation for a given row using this basis function.
abstract  double BasisFunctionPredictorRow.computeActivation(DataRow row)
          Computes the activation based on the given row for this basisfunction.
abstract  double BasisFunctionPredictorRow.computeDistance(DataRow row)
           
abstract  void BasisFunctionLearnerRow.cover(DataRow row)
          Called if a row covers a new DataRow.
(package private)  void BasisFunctionPredictorRow.cover(DataRow row, DataCell classLabel)
          If the same class as this basisfunction is assigned to, the number of correctly covered pattern is increased, otherwise the number of wrong covered ones.
(package private)  void BasisFunctionLearnerRow.coverIntern(DataRow row)
          Covers a new row and decrease covered counter.
abstract  boolean BasisFunctionLearnerRow.covers(DataRow row)
          Returns true if the input row is covered by this row, otherwise false.
abstract  boolean BasisFunctionLearnerRow.explains(DataRow row)
          Returns true if the input row is explained by this row, otherwise false.
 double BasisFunctionAntisymmetricRowOverlap.getAffinityDegree(DataRow row1, DataRow row2)
          
 double DegreeOfAffinity.getAffinityDegree(DataRow dr1, DataRow dr2)
           
 double BasisFunctionRowInclusion.getAffinityDegree(DataRow row1, DataRow row2)
          
 double BasisFunctionSymmetricRowOverlap.getAffinityDegree(DataRow row1, DataRow row2)
           
 DataCell[] BasisFunctionPredictorCellFactory.getCells(DataRow row)
          Predicts given row using the underlying basis function model.
abstract  boolean BasisFunctionLearnerRow.getShrinkValue(DataRow row)
          Called if a new row has to be adjusted.
protected  DataCell[] BasisFunctionPredictorCellFactory.predict(DataRow row, Map<DataCell,List<BasisFunctionPredictorRow>> model)
          Predicts an unknown row to the given model.
abstract  boolean BasisFunctionLearnerRow.shrink(DataRow row)
          Called if a new row has to be adjusted, all conflicting rows are shrunken.
 

Constructors in org.knime.base.node.mine.bfn with parameters of type DataRow
BasisFunctionFilterRow(BasisFunctionLearnerTable model, DataRow row, int[] dataColumns, int[] classColumns, String[] classColumnNames, BasisFunctionLearnerTable.MissingValueReplacementFunction missing)
          Create new basisfunction input data row with data and class columns.
BasisFunctionLearnerRow(RowKey key, DataRow centroid, DataCell classInfo)
          Initialise a new basisfunction rule with one covered pattern since this rule is also covered by itself.
 

Uses of DataRow in org.knime.base.node.mine.bfn.fuzzy
 

Classes in org.knime.base.node.mine.bfn.fuzzy that implement DataRow
 class FuzzyBasisFunctionLearnerRow
          Extends the general BasisFunctionLearnerRow object to act as rectangular fuzzy prototype.
 

Methods in org.knime.base.node.mine.bfn.fuzzy with parameters of type DataRow
 BasisFunctionLearnerRow FuzzyBasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Creates and returns a new row initialised with a class label and a center vector.
 boolean FuzzyBasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow o, DataRow r)
          Compares this basisfunction with the another one by the fuzzy rule's number of covered pattern.
 double FuzzyBasisFunctionPredictorRow.compose(DataRow row, double act)
          Composes the degree of membership by using the disjunction of the tco-norm operator.
 double FuzzyBasisFunctionLearnerRow.computeActivation(DataRow row)
          Computes activation for a given row using this basis function.
 double FuzzyBasisFunctionPredictorRow.computeActivation(DataRow row)
          Returns the compute activation of this input vector.
 double FuzzyBasisFunctionPredictorRow.computeDistance(DataRow row)
          
 void FuzzyBasisFunctionLearnerRow.cover(DataRow row)
          This basis function covers the given row.
 boolean FuzzyBasisFunctionLearnerRow.covers(DataRow row)
          Returns true if the given row is covered by this prototype, that is, if FuzzyBasisFunctionLearnerRow.computeActivation(DataRow) returns a degree greater than MINACT.
 boolean FuzzyBasisFunctionLearnerRow.explains(DataRow row)
          Returns true if the given row is covered by this prototype, that is, if FuzzyBasisFunctionLearnerRow.computeActivation(DataRow) returns a degree equal 1.
 boolean FuzzyBasisFunctionLearnerRow.getShrinkValue(DataRow row)
          Called if a new BasisFunctionLearnerRow has to be adjusted.
 boolean FuzzyBasisFunctionLearnerRow.shrink(DataRow row)
          If a new prototype has to be adjusted.
 

Constructors in org.knime.base.node.mine.bfn.fuzzy with parameters of type DataRow
FuzzyBasisFunctionLearnerRow(RowKey key, DataCell classInfo, DataRow centroid, int norm, int shrink, MutableDouble[] min, MutableDouble[] max)
          Creates a new learner row for fuzzy rules.
 

Uses of DataRow in org.knime.base.node.mine.bfn.radial
 

Classes in org.knime.base.node.mine.bfn.radial that implement DataRow
 class RadialBasisFunctionLearnerRow
          This class extends the general BasisFunctionLearnerRow in order to use radial basis function prototypes for training.
 

Methods in org.knime.base.node.mine.bfn.radial with parameters of type DataRow
 BasisFunctionLearnerRow RadialBasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Creates and returns a new RadialBasisFunctionLearnerRow initialized with a center vector and a class label.
 boolean RadialBasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow best, DataRow row)
          Compares this basis function with the other one by its standard deviation if the number of covered pattern is equal otherwise use this identification.
 double RadialBasisFunctionPredictorRow.compose(DataRow row, double act)
          Sum of the given activation plus the newly calculated one for the given row.
 double RadialBasisFunctionLearnerRow.computeActivation(DataRow row)
          Computes activation for a given row using this basis function.
 double RadialBasisFunctionPredictorRow.computeActivation(DataRow row)
          Calculates the current activation of this basis function given a input row which is always between 0.0 and 1.0 using the the hereinafter called distance function.
 double RadialBasisFunctionPredictorRow.computeDistance(DataRow row)
          Computes the distance between this prototype's center vector and the given row.
 void RadialBasisFunctionLearnerRow.cover(DataRow row)
          Method is empty.
 boolean RadialBasisFunctionLearnerRow.covers(DataRow row)
          Checks if the given row is covered by this basis function.
 boolean RadialBasisFunctionLearnerRow.explains(DataRow row)
          Checks if the given row is explained by this basisfunction.
 boolean RadialBasisFunctionLearnerRow.getShrinkValue(DataRow row)
          Called if a new BasisFunctionLearnerRow has to be adjusted.
 boolean RadialBasisFunctionLearnerRow.shrink(DataRow row)
          Basis functions need to be adjusted if they conflict with other ones.
 

Constructors in org.knime.base.node.mine.bfn.radial with parameters of type DataRow
RadialBasisFunctionLearnerRow(RowKey key, DataCell classInfo, DataRow center, double thetaMinus, double thetaPlus, int distance)
          Creates a new radial basisfunction using the center vector as the anchor of the Gaussian function and also assigns class label for this prototype.
RadialBasisFunctionPredictorRow(RowKey key, DataRow center, DataCell classLabel, double thetaMinus, int distance)
          Creates a new predictor for PNN rules.
 

Uses of DataRow in org.knime.base.node.mine.cluster.assign
 

Methods in org.knime.base.node.mine.cluster.assign with parameters of type DataRow
 double Prototype.getDistance(DataRow row)
          Computes the distance between this prototype and a given DataRow.
 double Prototype.getDistance(DataRow row, int[] indices)
          Computes the distance between this prototype and a given DataRow.
 double Prototype.getSquaredEuclideanDistance(DataRow row, int[] indices)
          Computes the distance between this prototype and a given DataRow.
 

Uses of DataRow in org.knime.base.node.mine.cluster.fuzzycmeans
 

Methods in org.knime.base.node.mine.cluster.fuzzycmeans with parameters of type DataRow
 DataCell[] ClusterMembershipFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.mine.cluster.hierarchical
 

Methods in org.knime.base.node.mine.cluster.hierarchical that return DataRow
 DataRow[] ClusterNode.getAllDataRows()
          Returns all data row (leaf nodes) this sub tree.
 DataRow ClusterNode.getLeafDataPoint()
          Returns the DataRow associated with a leaf node.
 

Constructors in org.knime.base.node.mine.cluster.hierarchical with parameters of type DataRow
ClusterNode(DataRow row, int rowIdx)
          Constructs a new leaf node from a data row.
 

Uses of DataRow in org.knime.base.node.mine.cluster.hierarchical.distfunctions
 

Methods in org.knime.base.node.mine.cluster.hierarchical.distfunctions with parameters of type DataRow
 double ManhattanDist.calcDistance(DataRow firstDataRow, DataRow secondDataRow, int[] includedCols)
          Calculates the distance between two data rows based on the Manhatten distance.
 double MinkowskiDist.calcDistance(DataRow firstDataRow, DataRow secondDataRow, int[] includedCols)
          Calculates the distance between two data rows based on the Minkowski distance.
 double DistanceFunction.calcDistance(DataRow firstDataRow, DataRow secondDataRow, int[] includedCols)
          Calculates the distance between two data rows.
 double EuclideanDist.calcDistance(DataRow firstDataRow, DataRow secondDataRow, int[] includedCols)
          Calculates the distance between two data rows based on the Euclidean distance.
 

Uses of DataRow in org.knime.base.node.mine.decisiontree2
 

Methods in org.knime.base.node.mine.decisiontree2 with parameters of type DataRow
 Boolean PMMLSimplePredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
 Boolean PMMLFalsePredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
 Boolean PMMLSimpleSetPredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
 Boolean PMMLTruePredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
abstract  Boolean PMMLPredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
 Boolean PMMLCompoundPredicate.evaluate(DataRow row, DataTableSpec spec)
          Evaluates the predicate for the passed parameters and returns the result.
 

Uses of DataRow in org.knime.base.node.mine.decisiontree2.model
 

Methods in org.knime.base.node.mine.decisiontree2.model with parameters of type DataRow
abstract  void DecisionTreeNodeSplit.addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Add colors for patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitNominalBinary.addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add colors for a pattern given as a row of values.
 void DecisionTreeNodeSplitPMML.addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Add colors for patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitContinuous.addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add colors for a pattern given as a row of values.
 void DecisionTreeNodeSplitNominal.addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add colors for a pattern given as a row of values.
 void DecisionTree.addCoveredColor(DataRow row, DataTableSpec spec)
          Add color of a new pattern to this tree.
 void DecisionTreeNodeSplit.addCoveredColor(DataRow row, DataTableSpec spec, double weight)
          Add colors for a row of values if they fall within a specific node/branch.
abstract  void DecisionTreeNode.addCoveredColor(DataRow row, DataTableSpec spec, double weight)
          Add colors for a row of values if they fall within a specific node/branch.
 void DecisionTreeNodeLeaf.addCoveredColor(DataRow row, DataTableSpec spec, double weight)
          Add colors for a pattern given as a row of values.
abstract  void DecisionTreeNodeSplit.addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Add patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitNominalBinary.addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitPMML.addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Add patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitContinuous.addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeSplitNominal.addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight)
          Deprecated. Add patterns given as a row of values if they fall within a specific node.
 void DecisionTree.addCoveredPattern(DataRow row, DataTableSpec spec)
          Add a new pattern to this tree for HiLiting purposes.
 void DecisionTreeNodeSplit.addCoveredPattern(DataRow row, DataTableSpec spec, double weight)
          Add patterns given as a row of values if they fall within a specific node.
abstract  void DecisionTreeNode.addCoveredPattern(DataRow row, DataTableSpec spec, double weight)
          Add patterns given as a row of values if they fall within a specific node.
 void DecisionTreeNodeLeaf.addCoveredPattern(DataRow row, DataTableSpec spec, double weight)
          Add patterns given as a row of values.
 DataCell DecisionTreeNode.classifyPattern(DataRow row, DataTableSpec spec)
          Classify a new pattern given as a row of values.
 DataCell DecisionTree.classifyPattern(DataRow row, DataTableSpec spec)
          Classify a new pattern given as a row of values.
abstract  LinkedHashMap<DataCell,Double> DecisionTreeNodeSplit.getClassCounts(DataCell cell, DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplitNominalBinary.getClassCounts(DataCell cell, DataRow row, DataTableSpec spec)
          Deprecated. Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplitPMML.getClassCounts(DataCell cell, DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplitContinuous.getClassCounts(DataCell cell, DataRow row, DataTableSpec spec)
          Deprecated. Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplitNominal.getClassCounts(DataCell cell, DataRow row, DataTableSpec spec)
          Deprecated. Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplit.getClassCounts(DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
abstract  LinkedHashMap<DataCell,Double> DecisionTreeNode.getClassCounts(DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeSplitPMML.getClassCounts(DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTreeNodeLeaf.getClassCounts(DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 LinkedHashMap<DataCell,Double> DecisionTree.getClassCounts(DataRow row, DataTableSpec spec)
          Determine class counts for a new pattern given as a row of values.
 

Uses of DataRow in org.knime.base.node.mine.mds
 

Methods in org.knime.base.node.mine.mds with parameters of type DataRow
 DataCell[] MDSCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.mine.mds.distances
 

Methods in org.knime.base.node.mine.mds.distances with parameters of type DataRow
static double Distances.getCosinusDistance(DataRow row1, DataRow row2, double offset, boolean fuzzy)
          Computes the cosinus distance between the given two rows, with given offset.
 double EuclideanDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given DataRows, row1 and row2.
 double ManhattanDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given DataRows, row1 and row2.
 double DistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given DataRows, row1 and row2.
 double CosinusDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given DataRows, row1 and row2.
static double Distances.getEuclideanDistance(DataRow row1, DataRow row2)
          Calculates the euclidean distance between two DataRows using the Minkowski distance with power 2.
static double Distances.getEuclideanDistance(DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the euclidean distance between two DataRows using the Minkowski distance with power 2.
static double Distances.getManhattanDistance(DataRow row1, DataRow row2)
          Calculates the Manhattan distance between two DataRows using the Minkowski distance with power 1.
static double Distances.getManhattanDistance(DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the Manhattan distance between two DataRows using the Minkowski distance with power 1.
static double Distances.getMinkowskiDistance(int power, DataRow row1, DataRow row2)
          Calculates the Minkowski distance between two rows no matter if they contain fuzzy or number values.
static double Distances.getMinkowskiDistance(int power, DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the Minkowski distance between two rows.
 

Uses of DataRow in org.knime.base.node.mine.mds.mdsprojection
 

Methods in org.knime.base.node.mine.mds.mdsprojection with parameters of type DataRow
protected  void MDSProjectionManager.adjustDataPoint(DataPoint p1, DataPoint p2, DataRow r1, DataRow r2)
          Adjusts the low dimensional mapping of the first data point according to the second data point and its mapping.
 

Uses of DataRow in org.knime.base.node.mine.pca
 

Methods in org.knime.base.node.mine.pca with parameters of type DataRow
protected static DataCell[] PCAReverseNodeModel.convertInputRow(Jama.Matrix eigenvectors, DataRow row, double[] means, int[] inputColumnIndices, int resultDimensions)
          reduce a single input row to the principal components.
protected static DataCell[] PCANodeModel.convertInputRow(Jama.Matrix eigenvectors, DataRow row, double[] means, int[] inputColumnIndices, int resultDimensions, boolean failOnMissing)
          reduce a single input row to the principal components.
 

Uses of DataRow in org.knime.base.node.mine.regression
 

Methods in org.knime.base.node.mine.regression with parameters of type DataRow
 DataCell RegressionPortObject.predict(DataRow row)
          Predict a row, returning the regression value.
 

Uses of DataRow in org.knime.base.node.mine.regression.linear
 

Methods in org.knime.base.node.mine.regression.linear with parameters of type DataRow
 DataCell LinearRegressionContent.predict(DataRow row)
          Predicts the target value for the given row.
 

Uses of DataRow in org.knime.base.node.mine.sota.distances
 

Methods in org.knime.base.node.mine.sota.distances with parameters of type DataRow
static double Distances.getCorrelationDistance(DataRow row1, DataRow row2, double offset, boolean abs, boolean fuzzy)
          Returns the coefficient of correlation distance between the rows with a given offset.
static double Distances.getCorrelationDistance(DataRow row, SotaTreeCell cell, double offset, boolean abs, boolean fuzzy)
          Returns the coefficient of correlation distance between the cells values and the number cells of the given row with a given offset.
static double Distances.getCosinusDistance(DataRow row1, DataRow row2, double offset, boolean fuzzy)
          Computes the cosinus distance between the given two rows, with given offset.
static double Distances.getCosinusDistance(DataRow row, SotaTreeCell cell, double offset, boolean fuzzy)
          Returns the cosinus distance between the cells values and the number cells of the given row with a given offset.
 double EuclideanDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given row1 and row2.
 double ManhattanDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given row1 and row2.
 double DistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given row1 and row2.
 double CosinusDistanceManager.getDistance(DataRow row1, DataRow row2)
          Returns the distance between the given row1 and row2.
 double EuclideanDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double ManhattanDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double DistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double CosinusDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
static double Distances.getEuclideanDistance(DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the euclidean distance between two DataRows using the Minkowski distance with power 2.
static double Distances.getEuclideanDistance(DataRow row, SotaTreeCell cell, boolean fuzzy)
          Returns the euclidean distance between a given DataRow and SotaTreeCell using the Minkowski distance with power 2.
static double Distances.getManhattanDistance(DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the manhattan distance between two DataRows using the Minkowski distance with power 1.
static double Distances.getManhattanDistance(DataRow row, SotaTreeCell cell, boolean fuzzy)
          Returns the manhattan distance between a given DataRow and SotaTreeCell using the Minkowski distance with power 1.
static double Distances.getMean(DataRow row, boolean fuzzy)
          Returns the mean value of the given row.
static double Distances.getMinkowskiDistance(int power, DataRow row1, DataRow row2, boolean fuzzy)
          Calculates the Minkowski distance between two rows.
static double Distances.getMinkowskiDistance(int power, DataRow row, SotaTreeCell cell, boolean fuzzy)
          Calculates the Minkowski distance between a regular DataRow and a SotaTreeCell.
static double Distances.getStandardDeviation(DataRow row, boolean fuzzy)
          Returns the standard deviation of the given row.
 

Uses of DataRow in org.knime.base.node.mine.sota.logic
 

Methods in org.knime.base.node.mine.sota.logic that return DataRow
 DataRow FuzzyHierarchyFilterRowContainer.getRow(int idx)
          Returns the row from the container with index idx.
 

Methods in org.knime.base.node.mine.sota.logic with parameters of type DataRow
abstract  void SotaHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
 void SotaFuzzyHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
 void SotaNumberHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
static double[] SotaFuzzyMath.getCenterOfAllCoreRegions(DataRow cells, DataTableSpec spec)
          Computes the center vector of all core regions of the given FuzzyCells as a double array.
static double SotaFuzzyMath.getCoreDilatationToOtherCore(DataRow cells1, DataRow cells2, DataTableSpec spec)
          Computes the core dilatation of a core region to another core region.
static double SotaFuzzyMath.getMaxCoreDilatation(DataRow cells, DataTableSpec spec)
          Approximates dilatation of Core region, by using Pythagoras.
static int SotaFuzzyMath.getNumberOfFuzzyCells(DataRow cells, DataTableSpec spec)
          Counts the number of FuzzyIntervalValues of given row and returns it.
static boolean SotaUtil.hasMissingValues(DataRow row)
          Returns true if there are missing values in given row and false if not.
 

Uses of DataRow in org.knime.base.node.mine.sota.predictor
 

Methods in org.knime.base.node.mine.sota.predictor with parameters of type DataRow
 DataCell[] SotaPredictorCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.mine.subgroupminer.freqitemset
 

Classes in org.knime.base.node.mine.subgroupminer.freqitemset that implement DataRow
 class FrequentItemSetRow
          This class implements one row of a FrequentItemSetTable.
 

Uses of DataRow in org.knime.base.node.mine.svm.predictor
 

Methods in org.knime.base.node.mine.svm.predictor with parameters of type DataRow
 DataCell[] SVMPredictor.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.parallel.appender
 

Methods in org.knime.base.node.parallel.appender with parameters of type DataRow
 DataCell[] ExtendedCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.parallel.builder
 

Methods in org.knime.base.node.parallel.builder with parameters of type DataRow
protected abstract  void ThreadedTableBuilderNodeModel.processRow(DataRow inRow, BufferedDataTable[] additionalData, RowAppender[] outputTables)
          This method is called once for each row in the first input table.
 

Uses of DataRow in org.knime.base.node.preproc.binner
 

Methods in org.knime.base.node.preproc.binner with parameters of type DataRow
 DataCell[] BinnerColumnFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.preproc.cellsplit
 

Methods in org.knime.base.node.preproc.cellsplit with parameters of type DataRow
 DataCell[] CellSplitterCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.preproc.cellsplitbypos
 

Methods in org.knime.base.node.preproc.cellsplitbypos with parameters of type DataRow
 DataCell[] CellSplitterByPosCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.preproc.columnTrans
 

Methods in org.knime.base.node.preproc.columnTrans with parameters of type DataRow
abstract  int AbstractMany2OneCellFactory.findColumnIndex(DataRow row)
          Find the column names to put in the condensed column.
 int BinaryCellFactory.findColumnIndex(DataRow row)
          Find the column names to put in the condensed column.
 int MinMaxCellFactory.findColumnIndex(DataRow row)
          Find the column names to put in the condensed column.
 int RegExpCellFactory.findColumnIndex(DataRow row)
          Find the column names to put in the condensed column.
 DataCell[] AbstractMany2OneCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 DataCell[] One2ManyCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Uses of DataRow in org.knime.base.node.preproc.filter.row
 

Methods in org.knime.base.node.preproc.filter.row that return DataRow
 DataRow RowFilterIterator.next()
          This implementation may throw an RuntimeCanceledExecutionException if this class has been initialized with a non-null execution monitor.
 

Uses of DataRow in org.knime.base.node.preproc.filter.row.rowfilter
 

Methods in org.knime.base.node.preproc.filter.row.rowfilter with parameters of type DataRow
static boolean MissingCellRowFilter.hasMissingCells(DataRow row)
          Checks if given row contains missing cells and returns true, otherwise false.
 boolean AndRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean RowNoRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean MissingValueRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean NegRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean MissingCellRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean StringCompareRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
abstract  boolean RowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean TrueRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean OrRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean RowIDRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean ColValFilterOldObsolete.matches(DataRow row, int rowIndex)
          Deprecated. Return true if the specified row matches the criteria set in the filter.
 boolean FalseRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean RangeRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 

Uses of DataRow in org.knime.base.node.preproc.missingval
 

Methods in org.knime.base.node.preproc.missingval that return DataRow
 DataRow MissingValueHandlingTableIterator.next()
          Returns the next DataRow.
 

Uses of DataRow in org.knime.base.node.preproc.sample
 

Methods in org.knime.base.node.preproc.sample with parameters of type DataRow
 boolean LinearSamplingRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean RandomFractionRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean RandomNumberRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 boolean StratifiedSamplingRowFilter.matches(DataRow row, int rowIndex)
          Return true if the specified row matches the criteria set in the filter.
 

Uses of DataRow in org.knime.base.node.preproc.setoperator
 

Methods in org.knime.base.node.preproc.setoperator with parameters of type DataRow
 int SingleColRowComparator.compare(DataRow r1, DataRow r2)
          
 

Uses of DataRow in org.knime.base.node.rules
 

Methods in org.knime.base.node.rules with parameters of type DataRow
 boolean RuleNode.evaluate(DataRow row)
          Evaluates this rule node.
 boolean Rule.matches(DataRow row)
          Returns if this rules matches the given row.
 

Uses of DataRow in org.knime.base.node.util
 

Methods in org.knime.base.node.util that return DataRow
 DataRow DataArray.getRow(int idx)
          Returns the row from the container with index idx.
 DataRow DefaultDataArray.getRow(int idx)
          Returns the row from the container with index idx.
 

Uses of DataRow in org.knime.base.node.viz.histogram.datamodel
 

Methods in org.knime.base.node.viz.histogram.datamodel that return types with arguments of type DataRow
 List<DataRow> InteractiveHistogramDataModel.getDataRows()
           
 Iterator<DataRow> InteractiveHistogramDataModel.iterator()
          
 

Constructor parameters in org.knime.base.node.viz.histogram.datamodel with type arguments of type DataRow
InteractiveHistogramVizModel(List<Color> rowColors, AggregationMethod aggrMethod, HistogramLayout layout, DataTableSpec spec, List<DataRow> rows, DataColumnSpec xColSpec, Collection<ColorColumn> aggrColumns, int noOfBins)
          Constructor for class InteractiveHistogramVizModel.
 

Uses of DataRow in org.knime.base.node.viz.histogram.impl.interactive
 

Methods in org.knime.base.node.viz.histogram.impl.interactive with parameters of type DataRow
 int RowByColumnComparator.compare(DataRow o1, DataRow o2)
           
 

Uses of DataRow in org.knime.base.node.viz.pie.datamodel.fixed
 

Methods in org.knime.base.node.viz.pie.datamodel.fixed with parameters of type DataRow
 void FixedPieDataModel.addDataRow(DataRow row, Color rowColor, DataCell pieCell, DataCell aggrCell)
           
 

Uses of DataRow in org.knime.base.node.viz.pie.datamodel.interactive
 

Methods in org.knime.base.node.viz.pie.datamodel.interactive that return types with arguments of type DataRow
 Iterator<DataRow> InteractivePieDataModel.getDataRows()
           
 Iterator<DataRow> InteractivePieDataModel.iterator()
          
 

Methods in org.knime.base.node.viz.pie.datamodel.interactive with parameters of type DataRow
 Color InteractivePieDataModel.getRowColor(DataRow row)
           
 

Uses of DataRow in org.knime.base.node.viz.plotter.dendrogram
 

Methods in org.knime.base.node.viz.plotter.dendrogram that return DataRow
 DataRow DendrogramNode.getLeafDataPoint()
          Returns the DataRow associated with a leaf node.
 

Uses of DataRow in org.knime.core.data
 

Methods in org.knime.core.data that return DataRow
abstract  DataRow RowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.core.data with parameters of type DataRow
 ColorAttr DataTableSpec.getRowColor(DataRow row)
          Returns the color that an object should have when displaying information concerning this row (for instance in a scatterplot).
 ShapeFactory.Shape DataTableSpec.getRowShape(DataRow row)
          Return the shape that an object should have when displaying information concerning this row (for instance in a scatterplot).
 double DataTableSpec.getRowSize(DataRow row)
          Deprecated. use row size factor instead
 double DataTableSpec.getRowSizeFactor(DataRow row)
          Return the size (as a scaling factor) that an object should have when displaying information concerning this row (for instance in a scatterplot).
 

Uses of DataRow in org.knime.core.data.collection
 

Methods in org.knime.core.data.collection with parameters of type DataRow
static BlobSupportDataCellList BlobSupportDataCellList.create(DataRow row, int[] cols)
          Create new list based on selected cell from a DataRow.
static BlobSupportDataCellSet BlobSupportDataCellSet.create(DataRow row, int[] cols)
          Create new set containing selected cells from a DataRow.
static ListCell CollectionCellFactory.createListCell(DataRow row, int[] cols)
          Creates a new ListCell based on selected cells from a DataRow.
static SetCell CollectionCellFactory.createSetCell(DataRow row, int[] cols)
          Create new SetCell containing a set based on selected cell from a DataRow.
 

Uses of DataRow in org.knime.core.data.container
 

Classes in org.knime.core.data.container that implement DataRow
 class BlobSupportDataRow
          Special row implementation that supports to access the wrapper cells of BlobDataCell.
 

Methods in org.knime.core.data.container that return DataRow
 DataRow JoinTableIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.core.data.container with parameters of type DataRow
(package private)  void Buffer.addRow(DataRow r, boolean isCopyOfExisting, boolean forceCopyOfBlobs)
          Adds a row to the buffer.
 void DataContainer.addRowToTable(DataRow row)
          Appends a row to the end of a container.
 void RowAppender.addRowToTable(DataRow row)
          Appends a row to the end of a container.
abstract  DataCell SingleCellFactory.getCell(DataRow row)
          Called from getCells.
 DataCell[] CellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 DataCell[] SingleCellFactory.getCells(DataRow row)
          Get the new cells for a given row.
 

Constructors in org.knime.core.data.container with parameters of type DataRow
BlobSupportDataRow(RowKey key, DataRow oldRow)
          Creates a new data row with a new row ID.
BlobSupportDataRow(String id, DataRow oldRow)
          Creates a new data row with a new row ID.
 

Uses of DataRow in org.knime.core.data.def
 

Classes in org.knime.core.data.def that implement DataRow
 class DefaultRow
          Default row for DataCells which keeps a row identifier and an array of DataCell objects.
 class JoinedRow
          Row that concatenates two given rows.
 

Methods in org.knime.core.data.def that return DataRow
 DataRow JoinedRow.getLeftRow()
           
 DataRow JoinedRow.getRightRow()
           
 DataRow DefaultRowIterator.next()
          Returns the next DataRow.
 

Methods in org.knime.core.data.def that return types with arguments of type DataRow
protected  List<DataRow> DefaultTable.getRowsInList()
          Deprecated. Get a reference to underlying data container.
 

Constructors in org.knime.core.data.def with parameters of type DataRow
DefaultCellIterator(DataRow row)
          Creates a new iterator over a given DataRow.
DefaultRow(RowKey key, DataRow row)
          Creates an new row, using the data of the specified row, and overwrites the row key with the given new one.
DefaultRow(String rowId, DataRow row)
          Creates an new row, using the data of the specified row, and overwrites the row key with the given new one.
DefaultRowIterator(DataRow... rows)
          Constructs a new iterator that traverses an array of DataRow.
DefaultTable(DataRow[] rows, DataTableSpec spec)
          Deprecated. Creates a new table object from an array of DataRow objects, and an array of column names and types.
DefaultTable(DataRow[] rows, String[] columnNames, DataType[] columnTypes)
          Deprecated. Creates a new table object from an array of DataRow objects, and an array of column names and types.
JoinedRow(DataRow left, DataRow right)
          Creates a new row based on two given rows.
 

Constructor parameters in org.knime.core.data.def with type arguments of type DataRow
DefaultRowIterator(Iterable<DataRow> iterable)
          Constructs a new iterator based on an Iterable.
 

Uses of DataRow in org.knime.core.node.tableview
 

Methods in org.knime.core.node.tableview that return DataRow
protected  DataRow TableContentModel.getRow(int row)
          Gets a row with a specified index.
 



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