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java.lang.Objectorg.knime.core.node.NodeModel
org.knime.base.node.mine.pca.PCANodeModel
public class PCANodeModel
The model class that implements the PCA on the input table.
Field Summary | |
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static int |
DATA_INPORT
Index of input data port. |
static int |
DATA_OUTPORT
Index of input data port. |
static String |
DIMENSIONS_SELECTION
config String for selecting whether the number of dimensions or the minimum quality is configured. |
(package private) static String |
FAIL_MISSING
String used for fail on missing config. |
static int |
INFO_OUTPORT
Index of decomposition output port. |
(package private) static String |
INPUT_COLUMNS
|
static int |
MATRIX_OUTPORT
Index of covariance matrix output port. |
(package private) static String |
PCA_COL_PREFIX
description String for dimension. |
(package private) static String |
REMOVE_COLUMNS
config String for remove columns. |
Constructor Summary | |
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PCANodeModel()
One input, one output table. |
Method Summary | |
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protected DataTableSpec[] |
configure(DataTableSpec[] inSpecs)
All IntCell columns are converted to
DoubleCell columns. |
protected static DataCell[] |
convertInputRow(Jama.Matrix eigenvectors,
DataRow row,
double[] means,
int[] inputColumnIndices,
int resultDimensions,
boolean failOnMissing)
reduce a single input row to the principal components. |
static DataColumnSpec[] |
createAddTableSpec(DataTableSpec inSpecs,
int resultDimensions)
create part of table spec to be added to the input table. |
static DataTableSpec |
createCovarianceMatrixSpec(String[] inputColumnNames)
|
static BufferedDataTable |
createCovarianceTable(ExecutionContext exec,
double[][] m,
String[] inputColumnNames)
create data table from covariance matrix. |
static BufferedDataTable |
createDecompositionOutputTable(ExecutionContext exec,
double[] evs,
Jama.Matrix eigenvectors)
create a table containing the given spectral decomposition. |
static DataTableSpec |
createDecompositionTableSpec(int dimensions)
create table spec for output of spectral decomposition. |
protected PortObject[] |
execute(PortObject[] inData,
ExecutionContext exec)
Performs the PCA. |
(package private) static int |
getCovarianceMatrix(ExecutionContext exec,
BufferedDataTable dataTable,
int[] numericIndices,
double[] means,
double[][] dataMatrix)
Converts a DataTable to the 2D-double array representing its
covariance matrix. |
(package private) static int[] |
getDefaultColumns(DataTableSpec dataTableSpec)
get column indices for all double compatible columns. |
(package private) static double[] |
getMeanVector(DataTable dataTable,
int[] numericIndices,
boolean failOnMissingValues,
ExecutionContext exec)
calculate means of all columns. |
protected void |
loadInternals(File nodeInternDir,
ExecutionMonitor exec)
Load internals into the derived NodeModel . |
protected void |
loadValidatedSettingsFrom(NodeSettingsRO settings)
Sets new settings from the passed object in the model. |
protected void |
reset()
Override this function in the derived model and reset your NodeModel . |
protected void |
saveInternals(File nodeInternDir,
ExecutionMonitor exec)
Save internals of the derived NodeModel . |
protected void |
saveSettingsTo(NodeSettingsWO settings)
Adds to the given NodeSettings the model specific
settings. |
protected void |
validateSettings(NodeSettingsRO settings)
Validates the settings in the passed NodeSettings object. |
Methods inherited from class java.lang.Object |
---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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static final String FAIL_MISSING
static final String INPUT_COLUMNS
public static final int DATA_INPORT
public static final int DATA_OUTPORT
public static final int INFO_OUTPORT
public static final int MATRIX_OUTPORT
static final String PCA_COL_PREFIX
static final String REMOVE_COLUMNS
public static final String DIMENSIONS_SELECTION
Constructor Detail |
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PCANodeModel()
Method Detail |
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protected DataTableSpec[] configure(DataTableSpec[] inSpecs) throws InvalidSettingsException
IntCell
columns are converted to
DoubleCell
columns.
This function is called whenever the derived model should re-configure
its output DataTableSpecs. Based on the given input data table spec(s)
and the current model's settings, the derived model has to calculate the
output data table spec and return them.
The passed DataTableSpec elements are never null
but can
be empty. The model may return null
data table spec(s) for
the outputs. But still, the model may be in an executable state. Note,
after the model has been executed this function will not be called
anymore, as the output DataTableSpecs are then being pulled from the
output DataTables. A derived NodeModel
that cannot provide
any DataTableSpecs at its outputs before execution (because the table
structure is unknown at this point) can return an array
containing just null
elements.
Implementation note: This method is called from the
NodeModel.configure(PortObjectSpec[])
method unless that method is
overwritten.
configure
in class NodeModel
inSpecs
- An array of DataTableSpecs (as many as this model has
inputs). Do NOT modify the contents of this array. None of the
DataTableSpecs in the array can be null
but
empty. If the predecessor node is not yet connected, or
doesn't provide a DataTableSpecs at its output port.
null
DataTableSpec elements are changed to empty
once.
InvalidSettingsException
- if the #configure()
failed, that is, the settings are inconsistent with given
DataTableSpec elements.public static DataTableSpec createDecompositionTableSpec(int dimensions)
dimensions
- number of dimension of input
static int[] getDefaultColumns(DataTableSpec dataTableSpec)
dataTableSpec
- table spec
public static DataColumnSpec[] createAddTableSpec(DataTableSpec inSpecs, int resultDimensions)
inSpecs
- input specs (for unique column names)resultDimensions
- number of dimensions in output
protected PortObject[] execute(PortObject[] inData, ExecutionContext exec) throws Exception
PortObject classes
that are defined through the
PortTypes
given in the
constructor
.
Similarly, the returned output objects need to comply with their port
types object class (otherwise an error is reported by the framework).
For a general description of the execute method refer to the description
of the specialized
NodeModel.execute(BufferedDataTable[], ExecutionContext)
methods as it
addresses more use cases.
execute
in class NodeModel
inData
- The input objects.exec
- For BufferedDataTable
creation and progress.
Exception
- If the node execution fails for any reason.public static BufferedDataTable createDecompositionOutputTable(ExecutionContext exec, double[] evs, Jama.Matrix eigenvectors) throws CanceledExecutionException
exec
- execution context for table creationevs
- eigenvalueseigenvectors
- (column contains an eigenvector)
CanceledExecutionException
protected static DataCell[] convertInputRow(Jama.Matrix eigenvectors, DataRow row, double[] means, int[] inputColumnIndices, int resultDimensions, boolean failOnMissing)
eigenvectors
- transposed matrix of eigenvectors (eigenvectors in
rows, number of eigenvectors corresponds to dimensions to be
projected to)row
- the row to convertmeans
- mean values of the columnsinputColumnIndices
- indices of the input columnsresultDimensions
- number of dimensions to project tofailOnMissing
- throw exception if missing values are encountered
static int getCovarianceMatrix(ExecutionContext exec, BufferedDataTable dataTable, int[] numericIndices, double[] means, double[][] dataMatrix) throws CanceledExecutionException
DataTable
to the 2D-double array representing its
covariance matrix. Only numeric attributes are included.
exec
- the execution context for progress report (a subcontext)dataTable
- the DataTable
to convertnumericIndices
- indices of input columnsmeans
- mean values of columnsdataMatrix
- matrix to write covariances to
CanceledExecutionException
- if execution is canceledstatic double[] getMeanVector(DataTable dataTable, int[] numericIndices, boolean failOnMissingValues, ExecutionContext exec) throws CanceledExecutionException
dataTable
- input tablenumericIndices
- indices of columns to usefailOnMissingValues
- if true, throw exception if missing values are
encounteredexec
- execution context
CanceledExecutionException
protected void loadInternals(File nodeInternDir, ExecutionMonitor exec) throws IOException, CanceledExecutionException
NodeModel
. This method is
only called if the Node
was executed. Read all your
internal structures from the given file directory to create your internal
data structure which is necessary to provide all node functionalities
after the workflow is loaded, e.g. view content and/or hilite mapping.
loadInternals
in class NodeModel
nodeInternDir
- The directory to read from.exec
- Used to report progress and to cancel the load process.
IOException
- If an error occurs during reading from this dir.
CanceledExecutionException
- If the loading has been canceled.NodeModel.saveInternals(File,ExecutionMonitor)
protected void saveInternals(File nodeInternDir, ExecutionMonitor exec) throws IOException, CanceledExecutionException
NodeModel
. This method is
only called if the Node
is executed. Write all your
internal structures into the given file directory which are necessary to
recreate this model when the workflow is loaded, e.g. view content and/or
hilite mapping.
saveInternals
in class NodeModel
nodeInternDir
- The directory to write into.exec
- Used to report progress and to cancel the save process.
IOException
- If an error occurs during writing to this dir.
CanceledExecutionException
- If the saving has been canceled.NodeModel.loadInternals(File,ExecutionMonitor)
protected void loadValidatedSettingsFrom(NodeSettingsRO settings) throws InvalidSettingsException
#validateSettings(NodeSettings)
method. The model must set
its internal configuration according to the settings object passed.
loadValidatedSettingsFrom
in class NodeModel
settings
- The settings to read.
InvalidSettingsException
- If a property is not available.NodeModel.saveSettingsTo(NodeSettingsWO)
,
NodeModel.validateSettings(NodeSettingsRO)
protected void reset()
NodeModel
. All components should unregister themselves
from any observables (at least from the hilite handler right now). All
internally stored data structures should be released. User settings
should not be deleted/reset though.
reset
in class NodeModel
protected void saveSettingsTo(NodeSettingsWO settings)
NodeSettings
the model specific
settings. The settings don't need to be complete or consistent. If, right
after startup, no valid settings are available this method can write
either nothing or invalid settings.
Method is called by the Node
if the current settings need
to be saved or transfered to the node's dialog.
saveSettingsTo
in class NodeModel
settings
- The object to write settings into.NodeModel.loadValidatedSettingsFrom(NodeSettingsRO)
,
NodeModel.validateSettings(NodeSettingsRO)
protected void validateSettings(NodeSettingsRO settings) throws InvalidSettingsException
NodeSettings
object.
The specified settings should be checked for completeness and
consistency. It must be possible to load a settings object validated
here without any exception in the
#loadValidatedSettings(NodeSettings)
method. The method
must not change the current settings in the model - it is supposed to
just check them. If some settings are missing, invalid, inconsistent, or
just not right throw an exception with a message useful to the user.
validateSettings
in class NodeModel
settings
- The settings to validate.
InvalidSettingsException
- If the validation of the settings
failed.NodeModel.saveSettingsTo(NodeSettingsWO)
,
NodeModel.loadValidatedSettingsFrom(NodeSettingsRO)
public static BufferedDataTable createCovarianceTable(ExecutionContext exec, double[][] m, String[] inputColumnNames)
exec
- execution contextm
- covariance matrixinputColumnNames
- names of input columns the matrix was created
from
public static DataTableSpec createCovarianceMatrixSpec(String[] inputColumnNames)
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