img.setRGB(x, y, col);

        img.setRGB(y, x, col);

      }

    }

    database.getHierarchy().add(database, smat);

    VisualizerContext context = vispar.newContext(database);

    // Attach visualizers to results

    int maxSize = 20000;

    if(dfl.size() > maxSize) dfl = dfl.subList(0, maxSize);

    System.out.println("Have " + dfl.size() + " terms");

   

    for(int i=0;i<dfl.size();i++) {

      for(int j=i+1;j<dfl.size();j++) {

      }

    }

    System.out.println("Similarity matrix made");

    QTClusterer qt = new QTClusterer(sm);

    qt.makeClusters(0.5);

    }

    System.out.println("Read vectors in: " + (System.currentTimeMillis() - time));

    time = System.currentTimeMillis();

   

    int goodCosines = 0;

    int totalCosines = 0;

    for(int i=0;i<vectors.size();i++) {

      for(int j=i+1;j<vectors.size();j++) {

        double cosine = cosine(vectors.get(i), vectors.get(j));

        if(cosine > 0.05) goodCosines++;

        totalCosines++;

      }

    }

    System.out.println("Fraction of pairwise similarities: " + goodCosines * 1.0 / totalCosines);

    time = System.currentTimeMillis();

    if(true) {   

      Set<Integer> assigned = new HashSet<Integer>();

      Matrix docMatrix = svdh.getVt().transpose();

      for(int i=0;i<docFiles.size();i++) {

        for(int j=i+1;j<docFiles.size();j++) {

          //simMatrix.setSimilarity(i, j, (float)tanimoto(docMatrix, i, j, svals));

        }

      }

      //System.out.println(Math.min(svals.length, docMatrix.getRowDimension()));

      //VirtualSimilarityMatrix simMatrix = new VirtualSimilarityMatrix(docMatrix, docFiles, Math.min(svals.length, docMatrix.getRowDimension()-1));

    String[] topicTypes = {"alchemy","calais","textwiseproper"};

    double[] alphas = {0.25,0.5,0.75,1.0,1.25,1.5,1.75,2.0};

   

    for(double alpha : alphas) {

      for(String topicType : topicTypes) {

        System.out.println(topicType+"\t"+alpha+"\t"+SpearmanRank.srcc(lda,llda));

      }

    }

   

    System.out.println("Finding optimal SRCC K for "+topicType+" "+alpha);

    String[] topics = Tools.getTopics(topicType);

    int maxK = topics.length;

    for(int k=1; k<=maxK; k++) {

      System.out.println(alpha+","+topicType+","+k+","+SpearmanRank.jscSRCC(baseline, llda));

    }

  }