public RandomCutForest singlePrecisionForest()

in Java/core/src/main/java/com/amazon/randomcutforest/state/RandomCutForestMapper.java [302:353]
48 lines of code
11 McCabe index (conditional complexity)

    public RandomCutForest singlePrecisionForest(RandomCutForest.Builder<?> builder, RandomCutForestState state,
            IPointStore<float[]> extPointStore, List<ITree<Integer, float[]>> extTrees,
            List<IStreamSampler<Integer>> extSamplers) {

        checkArgument(builder != null, "builder cannot be null");
        checkArgument(extTrees == null || extTrees.size() == state.getNumberOfTrees(), "incorrect number of trees");
        checkArgument(extSamplers == null || extSamplers.size() == state.getNumberOfTrees(),
                "incorrect number of samplers");
        checkArgument(extSamplers != null | state.isSaveSamplerStateEnabled(), " need samplers ");
        checkArgument(extPointStore != null || state.isSaveCoordinatorStateEnabled(), " need coordinator state ");

        Random random = builder.getRandom();
        ComponentList<Integer, float[]> components = new ComponentList<>();
        CompactRandomCutTreeContext context = new CompactRandomCutTreeContext();
        IPointStore<float[]> pointStore = (extPointStore == null)
                ? new PointStoreMapper().toModel(state.getPointStoreState())
                : extPointStore;
        PointStoreCoordinator<float[]> coordinator = new PointStoreCoordinator<>(pointStore);
        coordinator.setTotalUpdates(state.getTotalUpdates());
        context.setPointStore(pointStore);
        context.setMaxSize(state.getSampleSize());
        RandomCutTreeMapper treeMapper = new RandomCutTreeMapper();
        List<CompactRandomCutTreeState> treeStates = state.isSaveTreeStateEnabled()
                ? state.getCompactRandomCutTreeStates()
                : null;
        CompactSamplerMapper samplerMapper = new CompactSamplerMapper();
        List<CompactSamplerState> samplerStates = state.isSaveSamplerStateEnabled() ? state.getCompactSamplerStates()
                : null;
        for (int i = 0; i < state.getNumberOfTrees(); i++) {
            IStreamSampler<Integer> sampler = (extSamplers != null) ? extSamplers.get(i)
                    : samplerMapper.toModel(samplerStates.get(i), random.nextLong());

            ITree<Integer, float[]> tree;
            if (extTrees != null) {
                tree = extTrees.get(i);
            } else if (treeStates != null) {
                tree = treeMapper.toModel(treeStates.get(i), context, random.nextLong());
                sampler.getSample().forEach(s -> tree.addPoint(s.getValue(), s.getSequenceIndex()));
                tree.setConfig(Config.BOUNDING_BOX_CACHE_FRACTION, treeStates.get(i).getBoundingBoxCacheFraction());
            } else {
                // using boundingBoxCahce for the new tree
                tree = new RandomCutTree.Builder().capacity(state.getSampleSize()).randomSeed(random.nextLong())
                        .pointStoreView(pointStore).boundingBoxCacheFraction(state.getBoundingBoxCacheFraction())
                        .centerOfMassEnabled(state.isCenterOfMassEnabled())
                        .storeSequenceIndexesEnabled(state.isStoreSequenceIndexesEnabled()).build();
                sampler.getSample().forEach(s -> tree.addPoint(s.getValue(), s.getSequenceIndex()));
            }
            components.add(new SamplerPlusTree<>(sampler, tree));
        }
        builder.precision(Precision.FLOAT_32);
        return new RandomCutForest(builder, coordinator, components, random);
    }