added getContent and getContentType for all the ComputationalAgents
git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/data-analysis/EcologicalEngine@50916 82a268e6-3cf1-43bd-a215-b396298e98cf
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@ -28,6 +28,7 @@ public class DiscrepancyAnalysis extends DataAnalysis {
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int numberofvectors;
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int numberofvectors;
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float maxerror;
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float maxerror;
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String maxdiscrepancyPoint;
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String maxdiscrepancyPoint;
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private HashMap<String, String> output;
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@Override
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@Override
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public HashMap<String, VarCouple> getInputParameters() {
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public HashMap<String, VarCouple> getInputParameters() {
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@ -101,7 +102,7 @@ public class DiscrepancyAnalysis extends DataAnalysis {
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analyzeCompareList(takePoints);
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analyzeCompareList(takePoints);
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calcDiscrepancy();
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calcDiscrepancy();
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HashMap<String, String> output = new HashMap<String, String>();
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output = new HashMap<String, String>();
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output.put("MEAN", "" + mean);
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output.put("MEAN", "" + mean);
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output.put("VARIANCE", "" + variance);
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output.put("VARIANCE", "" + variance);
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output.put("NUMBER_OF_ERRORS", "" + numberoferrors);
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output.put("NUMBER_OF_ERRORS", "" + numberoferrors);
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@ -172,4 +173,14 @@ public class DiscrepancyAnalysis extends DataAnalysis {
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}
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}
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}
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}
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@Override
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public String getContentType() {
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return HashMap.class.getName();
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}
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@Override
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public Object getContent() {
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return output;
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}
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}
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}
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@ -36,6 +36,7 @@ public class DistributionQualityAnalysis extends DataAnalysis {
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float acceptanceThreshold = 0.8f;
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float acceptanceThreshold = 0.8f;
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float rejectionThreshold = 0.3f;
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float rejectionThreshold = 0.3f;
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double bestThreshold = 0.5d;
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double bestThreshold = 0.5d;
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private HashMap<String, String> output;
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public HashMap<String, VarCouple> getInputParameters() {
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public HashMap<String, VarCouple> getInputParameters() {
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@ -166,7 +167,7 @@ public class DistributionQualityAnalysis extends DataAnalysis {
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double omissionrate = calculateOmissionRate(truePositives, falseNegatives);
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double omissionrate = calculateOmissionRate(truePositives, falseNegatives);
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double specificity = calculateSpecificity(trueNegatives, falsePositives);
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double specificity = calculateSpecificity(trueNegatives, falsePositives);
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HashMap<String, String> output = new HashMap<String, String>();
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output = new HashMap<String, String>();
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output.put("TRUE_POSITIVES", "" + truePositives);
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output.put("TRUE_POSITIVES", "" + truePositives);
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output.put("TRUE_NEGATIVES", "" + trueNegatives);
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output.put("TRUE_NEGATIVES", "" + trueNegatives);
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output.put("FALSE_POSITIVES", "" + falsePositives);
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output.put("FALSE_POSITIVES", "" + falsePositives);
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@ -321,4 +322,15 @@ public class DistributionQualityAnalysis extends DataAnalysis {
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}
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}
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@Override
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public String getContentType() {
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return HashMap.class.getName();
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}
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@Override
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public Object getContent() {
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return output;
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}
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}
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}
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@ -18,4 +18,11 @@ public interface ComputationalAgent {
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//gets the weight of the generator: according to this the generator will be placed in the execution order
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//gets the weight of the generator: according to this the generator will be placed in the execution order
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public WEIGHT getWeight();
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public WEIGHT getWeight();
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// gets the type of the content inside the generator: String, File, HashMap.
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public String getContentType();
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// gets the content of the model: e.g. Table indications etc.
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public Object getContent();
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}
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}
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@ -23,10 +23,4 @@ public interface Generator extends ComputationalAgent{
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public void generate() throws Exception;
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public void generate() throws Exception;
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// gets the type of the content inside the generator: String, File etc.
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public String getContentType();
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// gets the content of the model: e.g. Table indications etc.
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public Object getContent();
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}
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}
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@ -41,11 +41,9 @@ public interface Model {
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public void train(AlgorithmConfiguration Input, Model previousModel);
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public void train(AlgorithmConfiguration Input, Model previousModel);
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// gets the type of the content inside the model: e.g. Table Model, Vectorial Model etc.
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public void stop();
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public String getContentType();
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public String getContentType();
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// gets the content of the model: e.g. Table indications etc.
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public Object getContent();
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public Object getContent();
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public void stop();
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}
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}
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@ -19,12 +19,6 @@ public interface Modeler extends ComputationalAgent{
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public void stop();
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public void stop();
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//gets the class name of the model
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public String getModelType();
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// gets the content of the model: e.g. Table indications etc.
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public Object getModelContent();
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public Model getModel();
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public Model getModel();
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}
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}
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@ -36,16 +36,6 @@ public class SimpleModeler implements Modeler{
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return innermodel.getResources();
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return innermodel.getResources();
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}
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}
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@Override
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public String getModelType() {
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return innermodel.getContentType();
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}
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@Override
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public Object getModelContent() {
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return innermodel.getContent();
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}
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@Override
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@Override
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public Model getModel() {
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public Model getModel() {
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return innermodel;
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return innermodel;
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@ -82,7 +72,12 @@ public class SimpleModeler implements Modeler{
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return WEIGHT.LOWEST;
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return WEIGHT.LOWEST;
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}
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}
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public String getContentType() {
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return innermodel.getContentType();
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}
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public Object getContent() {
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return innermodel.getContent();
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}
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}
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}
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@ -182,12 +182,10 @@ public class ModelAquamapsNN implements Model {
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status = 100f;
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status = 100f;
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}
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}
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@Override
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public String getContentType() {
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public String getContentType() {
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return File.class.getName();
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return File.class.getName();
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}
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}
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@Override
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public Object getContent() {
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public Object getContent() {
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return new File(fileName);
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return new File(fileName);
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@ -187,12 +187,10 @@ public class ModelAquamapsNNNS implements Model {
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status = 100f;
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status = 100f;
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}
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}
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@Override
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public String getContentType() {
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public String getContentType() {
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return String.class.getName();
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return String.class.getName();
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}
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}
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@Override
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public Object getContent() {
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public Object getContent() {
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return fileName;
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return fileName;
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@ -335,12 +335,10 @@ public class ModelHSPEN implements Model {
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// take ending time
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// take ending time
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}
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}
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@Override
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public String getContentType() {
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public String getContentType() {
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return String.class.getName();
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return String.class.getName();
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}
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}
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@Override
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public Object getContent() {
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public Object getContent() {
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return outputTable;
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return outputTable;
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}
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}
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