private static void run()

in src/main/java/com/twitter/sbf/simclusters_app/Main.java [49:108]
49 lines of code
4 McCabe index (conditional complexity)

  private static void run() throws IOException {

    // Load graph from file
    System.out.println("Loading bipartite graph from METIS data");
    BipartiteGraph graph = BipartiteGraph.fromFile(config.getMetisFile());
    System.out.println("Load graph: done!");

    //Variable for specifying the type of initialization for the algorithm
    final String evalType;
    if (config.getInitFromRandomNeighborhoods()) {
      evalType = "randomNeighborhoods";
    } else if (config.getInitFromBestNeighborhood()) {
      evalType = "bestNeighborhoods";
    } else if (config.getInitFromNonoverlappingNeighborhood()) {
      evalType = "nonoverlappingNeighborhoods";
    } else {
      evalType = "random";
    }

    //Arguments for SimClusters object
    int k = config.getK();
    AlgorithmConfig paramsForStepTwo = config.getAlgoConfig();
    int thresholdForStepThree = config.getThresholdForStepThree();
    double thresholdForStepOne = config.getThresholdForStepOne();
    boolean retainTopK = config.getRetainTopK();
    int topKParameter = config.getTopKParameter();
    boolean normalizeColumnsRight = config.getNormalizeColumnsRight();
    boolean normalizeRowsLeft = config.getNormalizeRowsLeft();
    boolean applyLogTransform = config.getApplyLogTransform();
    boolean squareWeights = config.getSquareWeights();
    boolean applyStepFour = config.getApplyStepFour();
    double thresholdForStepFour = config.getThresholdForStepFour();
    PrintWriter log = new PrintWriter(System.out);
    //Create SimClusters algorithm object
    SimClustersInMemory algo
        = new SimClustersInMemory(
            graph, k, paramsForStepTwo, thresholdForStepThree, thresholdForStepOne, retainTopK,
        topKParameter, log, normalizeColumnsRight, normalizeRowsLeft, squareWeights, evalType,
        applyStepFour, thresholdForStepFour, applyLogTransform);
    //Run algorithm
    long tic = System.currentTimeMillis();
    BipartiteSparseRepresentations representations =
        algo.runSimClusters();
    long toc = System.currentTimeMillis();

    System.out.println(String.format(
        "Time to learn bipartite sparse representations: %.2f seconds", (toc - tic) / 1000.0
        ));

    // Write output
    System.out.println(
        "Printing left representations to file " + config.getOutputLeftRepFile()
        + " and right representations to file " + config.getOutputRightRepFile()
    );
    PrintWriter leftOutput = new PrintWriter(config.getOutputLeftRepFile());
    PrintWriter rightOutput = new PrintWriter(config.getOutputRightRepFile());
    writeRowsWithScores(representations.leftRepresentations, leftOutput);
    writeRowsWithScores(representations.rightRepresentations, rightOutput);
    System.out.println("Done writing output!");
  }