### Question:
RandomCutForest { public boolean samplersFull() { return executor.getTotalUpdates() >= sampleSize; } protected  RandomCutForest(Builder<?> builder); static Builder builder(); static RandomCutForest defaultForest(int dimensions, long randomSeed); static RandomCutForest defaultForest(int dimensions); int getNumberOfTrees(); int getSampleSize(); int getOutputAfter(); int getDimensions(); double getLambda(); boolean storeSequenceIndexesEnabled(); boolean centerOfMassEnabled(); boolean parallelExecutionEnabled(); int getThreadPoolSize(); void update(double[] point); S traverseForest(double[] point, Function<RandomCutTree, Visitor<R>> visitorFactory,
            BinaryOperator<R> accumulator, Function<R, S> finisher); S traverseForest(double[] point, Function<RandomCutTree, Visitor<R>> visitorFactory,
            Collector<R, ?, S> collector); S traverseForest(double[] point, Function<RandomCutTree, Visitor<R>> visitorFactory,
            ConvergingAccumulator<R> accumulator, Function<R, S> finisher); S traverseForestMulti(double[] point, Function<RandomCutTree, MultiVisitor<R>> visitorFactory,
            BinaryOperator<R> accumulator, Function<R, S> finisher); S traverseForestMulti(double[] point, Function<RandomCutTree, MultiVisitor<R>> visitorFactory,
            Collector<R, ?, S> collector); double getAnomalyScore(double[] point); double getApproximateAnomalyScore(double[] point); DiVector getAnomalyAttribution(double[] point); DiVector getApproximateAnomalyAttribution(double[] point); DensityOutput getSimpleDensity(double[] point); double[] imputeMissingValues(double[] point, int numberOfMissingValues, int[] missingIndexes); double[] extrapolateBasic(double[] point, int horizon, int blockSize, boolean cyclic, int shingleIndex); double[] extrapolateBasic(double[] point, int horizon, int blockSize, boolean cyclic); double[] extrapolateBasic(ShingleBuilder builder, int horizon); List<Neighbor> getNearNeighborsInSample(double[] point, double distanceThreshold); List<Neighbor> getNearNeighborsInSample(double[] point); boolean isOutputReady(); boolean samplersFull(); long getTotalUpdates(); static final int DEFAULT_SAMPLE_SIZE; static final double DEFAULT_OUTPUT_AFTER_FRACTION; static final double DEFAULT_SAMPLE_SIZE_COEFFICIENT_IN_LAMBDA; static final int DEFAULT_NUMBER_OF_TREES; static final boolean DEFAULT_STORE_SEQUENCE_INDEXES_ENABLED; static final boolean DEFAULT_CENTER_OF_MASS_ENABLED; static final boolean DEFAULT_PARALLEL_EXECUTION_ENABLED; static final boolean DEFAULT_APPROXIMATE_ANOMALY_SCORE_HIGH_IS_CRITICAL; static final double DEFAULT_APPROXIMATE_DYNAMIC_SCORE_PRECISION; static final int DEFAULT_APPROXIMATE_DYNAMIC_SCORE_MIN_VALUES_ACCEPTED; }### Answer:
@Test public void testSamplersFull() { long totalUpdates = sampleSize / 2; when(executor.getTotalUpdates()).thenReturn(totalUpdates); assertFalse(forest.samplersFull()); totalUpdates = sampleSize; when(executor.getTotalUpdates()).thenReturn(totalUpdates); assertTrue(forest.samplersFull()); totalUpdates = sampleSize * 10; when(executor.getTotalUpdates()).thenReturn(totalUpdates); assertTrue(forest.samplersFull()); }