de.unihalle.informatik.Alida.demo
Class ALDClusterExperiment

java.lang.Object
  extended by de.unihalle.informatik.Alida.operator.ALDOperator
      extended by de.unihalle.informatik.Alida.demo.ALDClusterExperiment
All Implemented Interfaces:
ALDConfigurationValidator

@ALDAOperator(genericExecutionMode=ALL,
              level=APPLICATION)
public class ALDClusterExperiment
extends ALDOperator

Demo operator to cluster experimental data.

First, optionally the data are normalized. Second, again optionally, the data are subjected to a PCA. Finally clustered via k-means.

Author:
posch

Nested Class Summary
 
Nested classes/interfaces inherited from class de.unihalle.informatik.Alida.operator.ALDOperator
ALDOperator.HidingMode
 
Field Summary
private  java.util.List<java.util.Set<java.lang.Integer>> clusters
          Clusters represented as a list of clusters, where each cluster is a set of experiment Ids, i.e. indices into to input experimental data.
private  java.lang.Boolean doNormalize
           
private  java.lang.Boolean doPCA
           
private  ExperimentalData experiment
          Input data
private  ExperimentalData normalizedExperiment
          Normalization experiment in case normalization was requested.
 
Fields inherited from class de.unihalle.informatik.Alida.operator.ALDOperator
completeDAG, name, portHashAccess, verbose, versionProvider
 
Constructor Summary
ALDClusterExperiment()
          Default constructor.
ALDClusterExperiment(ExperimentalData _experiment)
          Constructor.
 
Method Summary
 java.util.List<java.util.Set<java.lang.Integer>> getClusters()
          Get value of result.
 java.lang.Boolean getDoNormalize()
           
 java.lang.Boolean getDoPCA()
           
 ExperimentalData getExperiment()
          Get value of experiment.
 ExperimentalData getNormalizedExperiment()
           
protected  void operate()
          This method does the actual work and needs to be implemented by every subclass.
 void setDoNormalize(java.lang.Boolean doNormalize)
           
 void setDoPCA(java.lang.Boolean doPCA)
           
 void setExperiment(ExperimentalData value)
          Set value of data.
 
Methods inherited from class de.unihalle.informatik.Alida.operator.ALDOperator
deserializeFromXmlFile, fieldContained, getALDPortHashAccessKey, getConstructionMode, getInInoutNames, getInInoutNames, getInNames, getInOutNames, getMissingRequiredInputs, getName, getNumParameters, getOutInoutNames, getOutNames, getParameter, getParameterDescriptor, getParameterNames, getSupplementalNames, getVerbose, getVersion, isConfigured, parametersToXmlObject, print, print, print, printInterface, printInterface, readHistory, readResolve, reinitializeParameterDescriptors, runOp, runOp, runOp, serializeToXmlFile, setConstructionMode, setName, setParameter, setParametersFromXml, setParametersFromXml, setVerbose, toStringVerbose, unconfiguredItems, validate, validateCustom, validateGeneric, writeHistory, writeHistory, writeHistory, writeParametersToXml
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

clusters

@Parameter(label="Clusters",
           direction=OUT,
           description="Clusters")
private transient java.util.List<java.util.Set<java.lang.Integer>> clusters
Clusters represented as a list of clusters, where each cluster is a set of experiment Ids, i.e. indices into to input experimental data.


doNormalize

@Parameter(label="Normalize data",
           direction=IN,
           required=false,
           description="Initially normalize the experimental data")
private java.lang.Boolean doNormalize

doPCA

@Parameter(label="use PCA",
           direction=IN,
           required=false,
           description="apply PCA before clustering")
private java.lang.Boolean doPCA

experiment

@Parameter(label="Experimental data",
           required=true,
           direction=IN,
           description="Experimental data to cluster")
private ExperimentalData experiment
Input data


normalizedExperiment

@Parameter(label="Normalized experimental data",
           direction=OUT,
           description="Normalized experimental data")
private ExperimentalData normalizedExperiment
Normalization experiment in case normalization was requested.

Constructor Detail

ALDClusterExperiment

public ALDClusterExperiment()
                     throws ALDOperatorException
Default constructor.

Throws:
ALDOperatorException

ALDClusterExperiment

public ALDClusterExperiment(ExperimentalData _experiment)
                     throws ALDOperatorException
Constructor.

Parameters:
experiment - Experimental data
Throws:
ALDOperatorException
Method Detail

getClusters

public java.util.List<java.util.Set<java.lang.Integer>> getClusters()
Get value of result. Explanation: Normalized experiment.

Returns:
value of result

getDoNormalize

public java.lang.Boolean getDoNormalize()
Returns:
the doNormalize

getDoPCA

public java.lang.Boolean getDoPCA()
Returns:
the doPCA

getExperiment

public ExperimentalData getExperiment()
Get value of experiment. Explanation: Experimental data to be normalized.

Returns:
value of data

getNormalizedExperiment

public ExperimentalData getNormalizedExperiment()
Returns:
the normalizedExperiment

operate

protected void operate()
                throws ALDOperatorException,
                       ALDProcessingDAGException
Description copied from class: ALDOperator
This method does the actual work and needs to be implemented by every subclass.

Specified by:
operate in class ALDOperator
Throws:
ALDOperatorException
ALDProcessingDAGException

setDoNormalize

public void setDoNormalize(java.lang.Boolean doNormalize)
Parameters:
doNormalize - the doNormalize to set

setDoPCA

public void setDoPCA(java.lang.Boolean doPCA)
Parameters:
doPCA - the doPCA to set

setExperiment

public void setExperiment(ExperimentalData value)
Set value of data. Explanation: Experimental data to be normalized.

Parameters:
value - New value of data