Examples with DoubleSummaryStatistics java.util.DoubleSummaryStatistics used on opensource projects

Example 26 with DoubleSummaryStatistics

use of java.util.DoubleSummaryStatistics in project MindsEye by SimiaCryptus.

the class TestUtil method plot.

/**
 * Plot plot canvas.
 *
 * @param history the history
 * @return the plot canvas
 */
public static PlotCanvas plot(@Nonnull final List<StepRecord> history) {
    try {
        final DoubleSummaryStatistics valueStats = history.stream().mapToDouble(x -> x.fitness).filter(x -> x > 0).summaryStatistics();
        double[][] data = history.stream().map(step -> new double[] { step.iteration, Math.log10(Math.max(valueStats.getMin(), step.fitness)) }).filter(x -> Arrays.stream(x).allMatch(Double::isFinite)).toArray(i -> new double[i][]);
        if (Arrays.stream(data).mapToInt(x -> x.length).sum() == 0)
            return null;
        @Nonnull final PlotCanvas plot = ScatterPlot.plot(data);
        plot.setTitle("Convergence Plot");
        plot.setAxisLabels("Iteration", "log10(Fitness)");
        plot.setSize(600, 400);
        return plot;
    } catch (@Nonnull final Exception e) {
        e.printStackTrace(System.out);
        return null;
    }
}

Example 27 with DoubleSummaryStatistics

use of java.util.DoubleSummaryStatistics in project MindsEye by SimiaCryptus.

the class TestUtil method plotTime.

/**
 * Plot plot canvas.
 *
 * @param history the history
 * @return the plot canvas
 */
public static PlotCanvas plotTime(@Nonnull final List<StepRecord> history) {
    try {
        final LongSummaryStatistics timeStats = history.stream().mapToLong(x -> x.epochTime).summaryStatistics();
        final DoubleSummaryStatistics valueStats = history.stream().mapToDouble(x -> x.fitness).filter(x -> x > 0).summaryStatistics();
        @Nonnull final PlotCanvas plot = ScatterPlot.plot(history.stream().map(step -> new double[] { (step.epochTime - timeStats.getMin()) / 1000.0, Math.log10(Math.max(valueStats.getMin(), step.fitness)) }).filter(x -> Arrays.stream(x).allMatch(Double::isFinite)).toArray(i -> new double[i][]));
        plot.setTitle("Convergence Plot");
        plot.setAxisLabels("Time", "log10(Fitness)");
        plot.setSize(600, 400);
        return plot;
    } catch (@Nonnull final Exception e) {
        e.printStackTrace(System.out);
        return null;
    }
}

Example 28 with DoubleSummaryStatistics

use of java.util.DoubleSummaryStatistics in project MindsEye by SimiaCryptus.

the class TestUtil method printHistory.

/**
 * Print history.
 *
 * @param log     the log
 * @param history the history
 */
public static void printHistory(@Nonnull final NotebookOutput log, @Nonnull final List<StepRecord> history) {
    if (!history.isEmpty()) {
        log.out("Convergence Plot: ");
        log.code(() -> {
            final DoubleSummaryStatistics valueStats = history.stream().mapToDouble(x -> x.fitness).filter(x -> x > 0).summaryStatistics();
            @Nonnull final PlotCanvas plot = ScatterPlot.plot(history.stream().map(step -> new double[] { step.iteration, Math.log10(Math.max(valueStats.getMin(), step.fitness)) }).toArray(i -> new double[i][]));
            plot.setTitle("Convergence Plot");
            plot.setAxisLabels("Iteration", "log10(Fitness)");
            plot.setSize(600, 400);
            return plot;
        });
    }
}

Example 29 with DoubleSummaryStatistics

use of java.util.DoubleSummaryStatistics in project MindsEye by SimiaCryptus.

the class SoftmaxActivationLayer method eval.

@Nonnull
@Override
public Result eval(@Nonnull final Result... inObj) {
    final int itemCnt = inObj[0].getData().length();
    @Nonnull final double[] sumA = new double[itemCnt];
    Arrays.stream(inObj).forEach(nnResult -> nnResult.addRef());
    @Nonnull final Tensor[] expA = new Tensor[itemCnt];
    final Tensor[] outputA = IntStream.range(0, itemCnt).mapToObj(dataIndex -> {
        @Nullable final Tensor input = inObj[0].getData().get(dataIndex);
        assert 1 < input.length() : "input.length() = " + input.length();
        @Nullable final Tensor exp;
        final DoubleSummaryStatistics summaryStatistics = DoubleStream.of(input.getData()).filter(x -> Double.isFinite(x)).summaryStatistics();
        final double max = summaryStatistics.getMax();
        // final double min = summaryStatistics.getMin();
        exp = input.map(x -> {
            double xx = Math.exp(x - max);
            return Double.isFinite(xx) ? xx : 0;
        });
        input.freeRef();
        assert Arrays.stream(exp.getData()).allMatch(Double::isFinite);
        assert Arrays.stream(exp.getData()).allMatch(v -> v >= 0);
        // assert exp.sum() > 0;
        final double sum = 0 < exp.sum() ? exp.sum() : 1;
        assert Double.isFinite(sum);
        expA[dataIndex] = exp;
        sumA[dataIndex] = sum;
        @Nullable Tensor result = exp.map(x -> x / sum);
        return result;
    }).toArray(i -> new Tensor[i]);
    assert Arrays.stream(outputA).flatMapToDouble(x -> Arrays.stream(x.getData())).allMatch(v -> Double.isFinite(v));
    return new Result(TensorArray.wrap(outputA), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList data) -> {
        if (inObj[0].isAlive()) {
            final Tensor[] passbackA = IntStream.range(0, itemCnt).mapToObj(dataIndex -> {
                Tensor deltaTensor = data.get(dataIndex);
                @Nullable final double[] delta = deltaTensor.getData();
                @Nullable final double[] expdata = expA[dataIndex].getData();
                @Nonnull final Tensor passback = new Tensor(data.getDimensions());
                final int dim = expdata.length;
                double dot = 0;
                for (int i = 0; i < expdata.length; i++) {
                    dot += delta[i] * expdata[i];
                }
                final double sum = sumA[dataIndex];
                for (int i = 0; i < dim; i++) {
                    double value = 0;
                    value = (sum * delta[i] - dot) * expdata[i] / (sum * sum);
                    passback.set(i, value);
                }
                deltaTensor.freeRef();
                return passback;
            }).toArray(i -> new Tensor[i]);
            assert Arrays.stream(passbackA).flatMapToDouble(x -> Arrays.stream(x.getData())).allMatch(v -> Double.isFinite(v));
            @Nonnull TensorArray tensorArray = TensorArray.wrap(passbackA);
            inObj[0].accumulate(buffer, tensorArray);
        }
    }) {

        @Override
        protected void _free() {
            Arrays.stream(expA).forEach(ReferenceCounting::freeRef);
            Arrays.stream(inObj).forEach(ReferenceCounting::freeRef);
        }

        @Override
        public boolean isAlive() {
            return inObj[0].isAlive();
        }
    };
}

Example 30 with DoubleSummaryStatistics

use of java.util.DoubleSummaryStatistics in project tutorials by eugenp.

the class Java8CollectorsUnitTest method whenSummarizing_shouldSummarize.

@Test
public void whenSummarizing_shouldSummarize() throws Exception {
    final DoubleSummaryStatistics result = givenList.stream().collect(summarizingDouble(String::length));
    assertThat(result.getAverage()).isEqualTo(2);
    assertThat(result.getCount()).isEqualTo(4);
    assertThat(result.getMax()).isEqualTo(3);
    assertThat(result.getMin()).isEqualTo(1);
    assertThat(result.getSum()).isEqualTo(8);
}