Added ClusteringInput: Caches adjacency matrix, distance matrix, and abstracts usage and creation

src/main/java/de/monticore/lang/monticar/generator/middleware/DistributedTargetGenerator.java

@@ -108,7 +108,7 @@ public class DistributedTargetGenerator extends CMakeGenerator {
 
             //Cluster
             if(clusteringParameters.getAlgorithmParameters().size() > 0) {
-                clusteringResults = AutomaticClusteringHelper.executeClusteringFromParams(componentInstanceSymbol, clusteringParameters.getAlgorithmParameters());
+                clusteringResults = ClusteringResultList.fromParametersList(componentInstanceSymbol, clusteringParameters.getAlgorithmParameters());
                 Optional<Integer> nOpt = clusteringParameters.getNumberOfClusters();
                 for(ClusteringResult c : clusteringResults){
                     String prefix = nOpt.isPresent() && !c.hasNumberOfClusters(nOpt.get()) ? "[IGNORED]" : "";

src/main/java/de/monticore/lang/monticar/generator/middleware/Simulation/MonteCarloIntegration.java

@@ -2,7 +2,7 @@ package de.monticore.lang.monticar.generator.middleware.Simulation;
 
 import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
 import de.monticore.lang.monticar.generator.middleware.clustering.AutomaticClusteringHelper;
-import de.monticore.lang.monticar.generator.middleware.clustering.FlattenArchitecture;
+import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringInput;
 import de.monticore.lang.monticar.generator.middleware.clustering.algorithms.SpectralClusteringAlgorithm;
 import de.monticore.lang.monticar.generator.middleware.clustering.algorithms.SpectralClusteringBuilder;
 
@@ -18,11 +18,12 @@ public class MonteCarloIntegration {
         double sum = 0;
 
         if(index == 1){
+            ClusteringInput clusteringInput = new ClusteringInput(componentInstanceSymbol);
             for(int i = 0; i<iterations; i++){
                 // This would be with Spectral Clustering
                 SpectralClusteringAlgorithm spectralClusteringAlgorithm = new SpectralClusteringAlgorithm();
                 Object[] params = new Object[]{SpectralClusteringBuilder.SpectralParameters.SPECTRAL_NUM_CLUSTERS, numberOfClusters};
-                List<Set<EMAComponentInstanceSymbol>> clusters = spectralClusteringAlgorithm.cluster(componentInstanceSymbol, params);
+                List<Set<EMAComponentInstanceSymbol>> clusters = spectralClusteringAlgorithm.cluster(clusteringInput, params);
 
                 //iterate through all clusters and add all cost of the ROS Tags between clusters
                 sum += AutomaticClusteringHelper.getTypeCostHeuristic(componentInstanceSymbol, clusters);

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/AutomaticClusteringHelper.java

@@ -7,12 +7,10 @@ import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instance
 import de.monticore.lang.embeddedmontiarc.tagging.middleware.ros.RosConnectionSymbol;
 import de.monticore.lang.math._ast.ASTNumberExpression;
 import de.monticore.lang.monticar.common2._ast.ASTCommonMatrixType;
-import de.monticore.lang.monticar.generator.middleware.cli.algorithms.AlgorithmCliParameters;
 import de.monticore.lang.monticar.ts.MCTypeSymbol;
 import de.monticore.lang.monticar.ts.references.MCASTTypeSymbolReference;
 import de.monticore.lang.monticar.ts.references.MCTypeReference;
 import de.monticore.symboltable.CommonSymbol;
-import de.se_rwth.commons.logging.Log;
 import org.jgrapht.Graph;
 import org.jgrapht.alg.ConnectivityInspector;
 import org.jgrapht.graph.DefaultEdge;
@@ -291,18 +289,4 @@ public class AutomaticClusteringHelper {
     }
 
 
-    public static ClusteringResultList executeClusteringFromParams(EMAComponentInstanceSymbol emaComponentInstance, List<AlgorithmCliParameters> algoParams) {
-        ClusteringResultList res = new ClusteringResultList();
-        for (int i = 0; i < algoParams.size(); i++) {
-            System.out.println("Clustering with algorithm " + (i + 1) + "/" + algoParams.size() + ": " + algoParams.get(i).toString());
-            ClusteringResult result = ClusteringResult.fromParameters(emaComponentInstance, algoParams.get(i));
-            if (result.isValid()) {
-                res.add(result);
-            } else {
-                Log.warn("Ignoring the result! It is invalid!");
-            }
-        }
-        return res;
-    }
-
 }

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/ClusteringAlgorithm.java

@@ -7,12 +7,12 @@ import java.util.Set;
 
 // product if for clustering factory
 public interface ClusteringAlgorithm {
-    List<Set<EMAComponentInstanceSymbol>> cluster(EMAComponentInstanceSymbol component, Object... args);
+    List<Set<EMAComponentInstanceSymbol>> cluster(ClusteringInput clusteringInput, Object... args);
 
     //TODO: add arguments as typed state of the algorithms(instead of untyped)
-    default List<Set<EMAComponentInstanceSymbol>> clusterWithState(EMAComponentInstanceSymbol component){
+    default List<Set<EMAComponentInstanceSymbol>> clusterWithState(ClusteringInput clusteringInput){
         Object[] args = getArgs();
-        return cluster(component, args);
+        return cluster(clusteringInput, args);
     }
 
     default Object[] getArgs(){

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/ClusteringInput.java

+package de.monticore.lang.monticar.generator.middleware.clustering;
+
+import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
+import de.monticore.lang.monticar.generator.middleware.helpers.ComponentHelper;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+public class ClusteringInput {
+    private EMAComponentInstanceSymbol instanceSymbol;
+
+    private double[][] adjacencyMatrix;
+    private boolean initAdjMatrix = false;
+
+    private double[][] distanceMatrix;
+    private boolean initDistMatrix = false;
+
+    private List<EMAComponentInstanceSymbol> subcompsOrderedByName;
+    private boolean initSubcomposOrderedByName = false;
+
+    private Map<String, Integer> labelsForSubcomps;
+    private boolean initLabelsForSubcomps = false;
+
+
+    public ClusteringInput(EMAComponentInstanceSymbol instanceSymbol) {
+        this.instanceSymbol = instanceSymbol;
+    }
+
+    public EMAComponentInstanceSymbol getComponent() {
+        return instanceSymbol;
+    }
+
+    public double[][] getAdjacencyMatrix(){
+        if(!initAdjMatrix){
+            initAdjMatrix = true;
+            adjacencyMatrix = AutomaticClusteringHelper.guaranteedConnectedAdjacencyMatrix(getSubcompsOrderedByName(), ComponentHelper.getInnerConnectors(instanceSymbol),getLabelsForSubcomps());
+
+        }
+        return getCopyOf(adjacencyMatrix);
+    }
+
+    public double[][] getDistanceMatrix(){
+        if(!initDistMatrix){
+            initDistMatrix = true;
+            distanceMatrix = AutomaticClusteringHelper.getDistanceMatrix(getAdjacencyMatrix());
+
+        }
+        return getCopyOf(distanceMatrix);
+    }
+
+    public List<EMAComponentInstanceSymbol> getSubcompsOrderedByName(){
+        if(!initSubcomposOrderedByName){
+            initSubcomposOrderedByName = true;
+            subcompsOrderedByName = ComponentHelper.getSubcompsOrderedByName(instanceSymbol);
+        }
+        return new ArrayList<>(subcompsOrderedByName);
+    }
+
+    public Map<String, Integer> getLabelsForSubcomps(){
+        if(!initLabelsForSubcomps){
+            initLabelsForSubcomps = true;
+            labelsForSubcomps = ComponentHelper.getLabelsForSubcomps(subcompsOrderedByName);
+        }
+        return new HashMap<>(labelsForSubcomps);
+    }
+
+    private double[][] getCopyOf(double[][] old){
+        double[][] res = new double[old.length][old[0].length];
+        for (int i = 0; i < old.length; i++) {
+            if (old[i].length >= 0) System.arraycopy(old[i], 0, res[i], 0, old[i].length);
+        }
+        return res;
+    }
+
+
+
+}

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/ClusteringResult.java

@@ -22,16 +22,16 @@ import java.util.Set;
 
 public class ClusteringResult {
     Double score = null;
-    private EMAComponentInstanceSymbol component;
+    private ClusteringInput clusteringInput;
     private AlgorithmCliParameters parameters;
     private List<Set<EMAComponentInstanceSymbol>> clustering;
     private long duration;
     private int componentNumber;
     private boolean valid;
 
-    private ClusteringResult(EMAComponentInstanceSymbol component, AlgorithmCliParameters parameters,
+    private ClusteringResult(ClusteringInput clusteringInput, AlgorithmCliParameters parameters,
                              List<Set<EMAComponentInstanceSymbol>> clustering, long duration, int componentNumber, boolean valid) {
-        this.component = component;
+        this.clusteringInput = clusteringInput;
         this.parameters = parameters;
         this.clustering = clustering;
         this.duration = duration;
@@ -39,15 +39,15 @@ public class ClusteringResult {
         this.valid = valid;
     }
 
-    public static ClusteringResult fromParameters(EMAComponentInstanceSymbol component, AlgorithmCliParameters parameters) {
+    public static ClusteringResult fromParameters(ClusteringInput clusteringInput, AlgorithmCliParameters parameters) {
         List<Set<EMAComponentInstanceSymbol>> res;
         long startTime = System.currentTimeMillis();
 
         try {
-            res = parameters.asClusteringAlgorithm().clusterWithState(component);
+            res = parameters.asClusteringAlgorithm().clusterWithState(clusteringInput);
         } catch (Exception e) {
             Log.warn("Marking this result as invalid. Error clustering the component.", e);
-            return new ClusteringResult(component, parameters, new ArrayList<>(), -1, component.getSubComponents().size(), false);
+            return new ClusteringResult(clusteringInput, parameters, new ArrayList<>(), -1, clusteringInput.getComponent().getSubComponents().size(), false);
         }
 
         long endTime = System.currentTimeMillis();
@@ -69,18 +69,22 @@ public class ClusteringResult {
         for (Set<EMAComponentInstanceSymbol> cluster : res) {
             componentNumber += cluster.size();
         }
-        return new ClusteringResult(component, parameters, res, endTime - startTime, componentNumber, curValid);
+        return new ClusteringResult(clusteringInput, parameters, res, endTime - startTime, componentNumber, curValid);
     }
 
     public double getScore(){
         if(score == null){
-            score = AutomaticClusteringHelper.getTypeCostHeuristic(component, clustering);
+            score = AutomaticClusteringHelper.getTypeCostHeuristic(clusteringInput.getComponent(), clustering);
         }
         return score;
     }
 
     public EMAComponentInstanceSymbol getComponent() {
-        return component;
+        return clusteringInput.getComponent();
+    }
+
+    public ClusteringInput getClusteringInput() {
+        return clusteringInput;
     }
 
     public AlgorithmCliParameters getParameters() {
@@ -115,15 +119,15 @@ public class ClusteringResult {
                         "//Score: " + this.getScore() + "\n" +
                         "//Durration in ms: " + this.getDuration() + "\n";
 
-        String content = MiddlewareTagGenImpl.getFileContent(component, this.clustering);
+        String content = MiddlewareTagGenImpl.getFileContent(clusteringInput.getComponent(), this.clustering);
         res.setFileContent(prefix + content);
         return res;
     }
 
     //TODO: refactor to File?
     public void saveVisualization(String path, String fileName){
-        Graph g = ModelVisualizer.buildGraph(component, parameters.toString());
-        ModelVisualizer.visualizeClustering(g, clustering, component);
+        Graph g = ModelVisualizer.buildGraph(clusteringInput.getComponent(), parameters.toString());
+        ModelVisualizer.visualizeClustering(g, clustering, clusteringInput.getComponent());
         ModelVisualizer.saveGraphAsImage(g, path, fileName);
     }
 

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/ClusteringResultList.java

 package de.monticore.lang.monticar.generator.middleware.clustering;
 
+import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
 import de.monticore.lang.monticar.generator.FileContent;
+import de.monticore.lang.monticar.generator.middleware.cli.algorithms.AlgorithmCliParameters;
 import de.se_rwth.commons.logging.Log;
 
 import java.util.ArrayList;
@@ -14,6 +16,24 @@ public class ClusteringResultList extends ArrayList<ClusteringResult> {
         super();
     }
 
+    public static ClusteringResultList fromParametersList(EMAComponentInstanceSymbol emaComponentInstance, List<AlgorithmCliParameters> algoParams) {
+        ClusteringResultList res = new ClusteringResultList();
+        ClusteringInput clusteringInput = new ClusteringInput(emaComponentInstance);
+        //create AdjacencyMatrix to make execution speed comparision fairer
+        clusteringInput.getAdjacencyMatrix();
+
+        for (int i = 0; i < algoParams.size(); i++) {
+            System.out.println("Clustering with algorithm " + (i + 1) + "/" + algoParams.size() + ": " + algoParams.get(i).toString());
+            ClusteringResult result = ClusteringResult.fromParameters(clusteringInput, algoParams.get(i));
+            if (result.isValid()) {
+                res.add(result);
+            } else {
+                Log.warn("Ignoring the result! It is invalid!");
+            }
+        }
+        return res;
+    }
+
     public Optional<ClusteringResult> getBestResultWithFittingN(int n){
         ClusteringResultList filteredList = new ClusteringResultList();
         for(ClusteringResult c : this){

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/algorithms/AffinityPropagationAlgorithm.java

@@ -3,13 +3,15 @@ package de.monticore.lang.monticar.generator.middleware.clustering.algorithms;
 import com.clust4j.algo.AffinityPropagation;
 import com.clust4j.algo.AffinityPropagationParameters;
 import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
-import de.monticore.lang.monticar.generator.middleware.clustering.AutomaticClusteringHelper;
 import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringAlgorithm;
-import de.monticore.lang.monticar.generator.middleware.helpers.ComponentHelper;
+import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringInput;
 import org.apache.commons.math3.linear.Array2DRowRealMatrix;
 import org.apache.commons.math3.linear.RealMatrix;
 
-import java.util.*;
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
 
 public class AffinityPropagationAlgorithm implements ClusteringAlgorithm {
 
@@ -25,15 +27,9 @@ public class AffinityPropagationAlgorithm implements ClusteringAlgorithm {
     }
 
     @Override
-    public List<Set<EMAComponentInstanceSymbol>> cluster(EMAComponentInstanceSymbol component, Object... args) {
+    public List<Set<EMAComponentInstanceSymbol>> cluster(ClusteringInput clusteringInput, Object... args) {
 
-        List<EMAComponentInstanceSymbol> subcompsOrderedByName = ComponentHelper.getSubcompsOrderedByName(component);
-        Map<String, Integer> labelsForSubcomps = ComponentHelper.getLabelsForSubcomps(subcompsOrderedByName);
-        double[][] adjMatrix = AutomaticClusteringHelper.guaranteedConnectedAdjacencyMatrix(subcompsOrderedByName,
-                ComponentHelper.getInnerConnectors(component),
-                labelsForSubcomps);
-
-        RealMatrix mat = new Array2DRowRealMatrix(adjMatrix);
+        RealMatrix mat = new Array2DRowRealMatrix(clusteringInput.getAdjacencyMatrix());
 
         AffinityPropagation clustering = new AffinityPropagationParameters().fitNewModel(mat);
         final int[] labels = clustering.getLabels();
@@ -45,8 +41,8 @@ public class AffinityPropagationAlgorithm implements ClusteringAlgorithm {
             res.add(new HashSet<>());
         }
 
-        subcompsOrderedByName.forEach(sc -> {
-            int curClusterLabel = labels[labelsForSubcomps.get(sc.getFullName())];
+        clusteringInput.getSubcompsOrderedByName().forEach(sc -> {
+            int curClusterLabel = labels[clusteringInput.getLabelsForSubcomps().get(sc.getFullName())];
             res.get(curClusterLabel).add(sc);
         });
 

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/algorithms/DBSCANClusteringAlgorithm.java

 package de.monticore.lang.monticar.generator.middleware.clustering.algorithms;
 
 import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
-import de.monticore.lang.monticar.generator.middleware.clustering.AutomaticClusteringHelper;
 import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringAlgorithm;
-import de.monticore.lang.monticar.generator.middleware.helpers.ComponentHelper;
+import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringInput;
 import de.se_rwth.commons.logging.Log;
 import smile.clustering.DBSCAN;
 
@@ -23,7 +22,7 @@ public class DBSCANClusteringAlgorithm implements ClusteringAlgorithm {
     }
 
     @Override
-    public List<Set<EMAComponentInstanceSymbol>> cluster(EMAComponentInstanceSymbol component, Object... args) {
+    public List<Set<EMAComponentInstanceSymbol>> cluster(ClusteringInput clusteringInput, Object... args) {
 
         List<Set<EMAComponentInstanceSymbol>> res = new ArrayList<>();
 
@@ -80,24 +79,19 @@ public class DBSCANClusteringAlgorithm implements ClusteringAlgorithm {
         if (error) {
             Log.error("DBSCANClusteringAlgorithm: Mandatory parameter(s) missing!");
         } else {
-            List<EMAComponentInstanceSymbol> subcompsOrderedByName = ComponentHelper.getSubcompsOrderedByName(component);
-            Map<String, Integer> labelsForSubcomps = ComponentHelper.getLabelsForSubcomps(subcompsOrderedByName);
-            double[][] adjMatrix = AutomaticClusteringHelper.guaranteedConnectedAdjacencyMatrix(subcompsOrderedByName,
-                    ComponentHelper.getInnerConnectors(component),
-                    labelsForSubcomps);
-
+            double[][] adjMatrix = clusteringInput.getAdjacencyMatrix();
             DBSCAN clustering;
             DBSCANClusteringBuilder builder = new DBSCANClusteringBuilder(adjMatrix, minPts, radius);
-            clustering = builder.build();
 
+            clustering = builder.build();
             int[] labels = clustering.getClusterLabel();
 
             for (int i = 0; i < clustering.getNumClusters(); i++) {
                 res.add(new HashSet<>());
             }
 
-            subcompsOrderedByName.forEach(sc -> {
-                int curClusterLabel = labels[labelsForSubcomps.get(sc.getFullName())];
+            clusteringInput.getSubcompsOrderedByName().forEach(sc -> {
+                int curClusterLabel = labels[clusteringInput.getLabelsForSubcomps().get(sc.getFullName())];
                 res.get(curClusterLabel).add(sc);
             });
         }

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/algorithms/MarkovClusteringAlgorithm.java

@@ -3,7 +3,7 @@ package de.monticore.lang.monticar.generator.middleware.clustering.algorithms;
 import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
 import de.monticore.lang.monticar.generator.middleware.clustering.AutomaticClusteringHelper;
 import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringAlgorithm;
-import de.monticore.lang.monticar.generator.middleware.helpers.ComponentHelper;
+import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringInput;
 import de.se_rwth.commons.logging.Log;
 import net.sf.javaml.clustering.mcl.SparseMatrix;
 import net.sf.javaml.core.Dataset;
@@ -78,7 +78,7 @@ public class MarkovClusteringAlgorithm implements ClusteringAlgorithm {
     }
 
     @Override
-    public List<Set<EMAComponentInstanceSymbol>> cluster(EMAComponentInstanceSymbol component, Object... args) {
+    public List<Set<EMAComponentInstanceSymbol>> cluster(ClusteringInput clusteringInput, Object... args) {
 
         List<Set<EMAComponentInstanceSymbol>> res = new ArrayList<>();
 
@@ -147,11 +147,7 @@ public class MarkovClusteringAlgorithm implements ClusteringAlgorithm {
         if (error) {
             Log.error("MarkovClusteringAlgorithm: Mandatory parameter(s) missing!");
         } else {
-            List<EMAComponentInstanceSymbol> subcompsOrderedByName = ComponentHelper.getSubcompsOrderedByName(component);
-            Map<String, Integer> labelsForSubcomps = ComponentHelper.getLabelsForSubcomps(subcompsOrderedByName);
-            double[][] adjMatrix = AutomaticClusteringHelper.guaranteedConnectedAdjacencyMatrix(subcompsOrderedByName,
-                    ComponentHelper.getInnerConnectors(component),
-                    labelsForSubcomps);
+            double[][] adjMatrix = clusteringInput.getAdjacencyMatrix();
 
             // |nodes| instances of data with one attribute denoting the node order
             Dataset original_ds= new DefaultDataset();
@@ -181,8 +177,8 @@ public class MarkovClusteringAlgorithm implements ClusteringAlgorithm {
                 res.add(new HashSet<>());
             }
 
-            subcompsOrderedByName.forEach(sc -> {
-                int curClusterLabel = labels[labelsForSubcomps.get(sc.getFullName())];
+            clusteringInput.getSubcompsOrderedByName().forEach(sc -> {
+                int curClusterLabel = labels[clusteringInput.getLabelsForSubcomps().get(sc.getFullName())];
                 res.get(curClusterLabel).add(sc);
             });
         }

src/main/java/de/monticore/lang/monticar/generator/middleware/clustering/algorithms/SpectralClusteringAlgorithm.java

 package de.monticore.lang.monticar.generator.middleware.clustering.algorithms;
 
 import de.monticore.lang.embeddedmontiarc.embeddedmontiarc._symboltable.instanceStructure.EMAComponentInstanceSymbol;
-import de.monticore.lang.monticar.generator.middleware.clustering.AutomaticClusteringHelper;
 import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringAlgorithm;
-import de.monticore.lang.monticar.generator.middleware.helpers.ComponentHelper;
+import de.monticore.lang.monticar.generator.middleware.clustering.ClusteringInput;
 import de.se_rwth.commons.logging.Log;
 import smile.clustering.SpectralClustering;
 
@@ -23,7 +22,7 @@ public class SpectralClusteringAlgorithm implements ClusteringAlgorithm {
     }
 
     @Override
-    public List<Set<EMAComponentInstanceSymbol>> cluster(EMAComponentInstanceSymbol component, Object... args) {
+    public List<Set<EMAComponentInstanceSymbol>> cluster(ClusteringInput clusteringInput, Object... args) {
 
         List<Set<EMAComponentInstanceSymbol>> res = new ArrayList<>();
 
@@ -86,11 +85,7 @@ public class SpectralClusteringAlgorithm implements ClusteringAlgorithm {
         if (error) {
             Log.error("SpectralClusteringAlgorithm: Mandatory parameter(s) missing!");
         } else {
-            List<EMAComponentInstanceSymbol> subcompsOrderedByName = ComponentHelper.getSubcompsOrderedByName(component);
-            Map<String, Integer> labelsForSubcomps = ComponentHelper.getLabelsForSubcomps(subcompsOrderedByName);
-            double[][] adjMatrix = AutomaticClusteringHelper.guaranteedConnectedAdjacencyMatrix(subcompsOrderedByName,
-                    ComponentHelper.getInnerConnectors(component),
-                    labelsForSubcomps);
+            double[][] adjMatrix = clusteringInput.getAdjacencyMatrix();
 
             SpectralClustering clustering;
             SpectralClusteringBuilder builder = new SpectralClusteringBuilder(adjMatrix, numClusters);
@@ -104,8 +99,8 @@ public class SpectralClusteringAlgorithm implements ClusteringAlgorithm {
                 res.add(new HashSet<>());
             }
 
-            subcompsOrderedByName.forEach(sc -> {
-                int curClusterLabel = labels[labelsForSubcomps.get(sc.getFullName())];
+            clusteringInput.getSubcompsOrderedByName().forEach(sc -> {
+                int curClusterLabel = labels[clusteringInput.getLabelsForSubcomps().get(sc.getFullName())];
                 res.get(curClusterLabel).add(sc);
             });
         }

src/test/java/de/monticore/lang/monticar/generator/middleware/AutomaticClusteringTest.java

@@ -49,7 +49,7 @@ public class AutomaticClusteringTest extends AbstractSymtabTest{
 
         SpectralClusteringAlgorithm clusteringAlgorithm = new SpectralClusteringAlgorithm();
         Object[] params = new Object[]{SpectralClusteringBuilder.SpectralParameters.SPECTRAL_NUM_CLUSTERS, 2};
-        List<Set<EMAComponentInstanceSymbol>> clusters = clusteringAlgorithm.cluster(flattendComponent, params);
+        List<Set<EMAComponentInstanceSymbol>> clusters = clusteringAlgorithm.cluster(new ClusteringInput(flattendComponent), params);
 
         AutomaticClusteringHelper.annotateComponentWithRosTagsForClusters(flattendComponent, clusters);
 
@@ -570,8 +570,12 @@ public class AutomaticClusteringTest extends AbstractSymtabTest{
         assertNotNull(componentInstanceSymbol);
 
         List<Set<EMAComponentInstanceSymbol>> clusters = null;
-        if (params != null) clusters = algorithm.cluster(componentInstanceSymbol, params); else
-            clusters = algorithm.cluster(componentInstanceSymbol);
+        ClusteringInput clusteringInput = new ClusteringInput(componentInstanceSymbol);
+        if (params != null){
+            clusters = algorithm.cluster(clusteringInput, params);
+        }else{
+            clusters = algorithm.cluster(clusteringInput);
+        }
 
         Graph graph = ModelVisualizer.buildGraph(componentInstanceSymbol, algoNameShort);
         ModelVisualizer.visualizeClustering(graph, clusters, componentInstanceSymbol);