private Map getMetrics()

in src/main/java/com/twitter/sbf/core/MHAlgorithm.java [479:548]
67 lines of code
7 McCabe index (conditional complexity)

  private Map<String, Object> getMetrics(SparseBinaryMatrix matrix,
                                         int epoch,
                                         double elapsedSeconds,
                                         double acceptRate,
                                         double temperature,
                                         boolean doExpensiveEval) {
    Graph graph = g;
    ImmutableMap.Builder<String, Object> metricsMap = new ImmutableMap.Builder<>();
    metricsMap.put("epoch", epoch);
    metricsMap.put("nnz/vertex", matrix.nnzPerRow());
    metricsMap.put("emptyRow", matrix.emptyRowProportion());
    metricsMap.put("emptyCol", matrix.emptyColProportion());
    metricsMap.put("minSize", matrix.minColSizeAboveZero());
    metricsMap.put("maxSize", matrix.maxColSize());
    metricsMap.put("totalSec", elapsedSeconds);
    metricsMap.put("acceptRate", acceptRate);
    metricsMap.put("temp", temperature);
    metricsMap.put("emptyProposal", emptyProposals * 1.0 / graph.getNumVertices());
    metricsMap.put("sameProposal", sameProposals * 1.0 / graph.getNumVertices());
    if (doExpensiveEval) {
      long tic = System.nanoTime();
      // Evaluate prediction metrics
      PredictionStat stat;
      if (graph.getNumEdges() < 5000L) {
        int subsetSize =
            (config.evalRatio < 1.0) ? ((int) (graph.getNumVertices() * config.evalRatio))
                : graph.getNumVertices();
        int[] evalVertexIds =
            (config.evalRatio < 1.0) ? Util.reservoirSampling(graph.getNumVertices(), subsetSize)
                : graph.getAllVertexIds();
        // Parallel execution using Executor
        ExecutorService executor = Executors.newFixedThreadPool(config.cpu);
        stat = getPredictionStatVertexSampling(graph, matrix, executor, evalVertexIds);
        executor.shutdown();
        try {
          while (!executor.isTerminated()) {
            executor.awaitTermination(20, TimeUnit.MINUTES);
          }
        } catch (InterruptedException e) {
          throw new RuntimeException(e);
        }
        metricsMap.put("orphans", stat.orphanRate());
        metricsMap.put("prec", stat.precision() * 100);
        metricsMap.put("rec", stat.recall() * 100);
        metricsMap.put("f1", stat.f1() * 100);
        metricsMap.put("wtPrec", stat.weightedPrecision() * 100);
        metricsMap.put("wtRec", stat.weightedRecall() * 100);
        metricsMap.put("wtF1", stat.weightedF1() * 100);
      } else {
        Map<String, PredictionStat> ss = getPredictionStatEdgeSampling(graph, matrix, config.rng,
            100000, 1000000, 5000);
        double precision = ss.get("precision").precision();
        double recall = ss.get("recall").recall();
        double wtPrec = ss.get("precision").weightedPrecision();
        double wtRec = ss.get("recall").weightedRecall();
        metricsMap.put("orphans", ss.get("orphans").orphanRate());
        metricsMap.put("prec", precision * 100);
        metricsMap.put("rec", recall * 100);
        metricsMap.put("f1", 200 * precision * recall / (precision + recall));
        metricsMap.put("wtPrec", wtPrec * 100);
        metricsMap.put("wtRec", wtRec * 100);
        metricsMap.put("wtF1", 200 * wtPrec * wtRec / (wtPrec + wtRec));
      }

      long toc = System.nanoTime();
      double evalTime = (toc - tic) * 1e-9;
      metricsMap.put("evalSec", evalTime);
    }
    return metricsMap.build();
  }