Examples with DoubleStatistics com.simiacryptus.util.data.DoubleStatistics used on opensource projects

Example 1 with DoubleStatistics

use of com.simiacryptus.util.data.DoubleStatistics in project MindsEye by SimiaCryptus.

the class EncodingUtil method decompositionSvg.

/**
 * To svg string.
 *
 * @param log              the log
 * @param baseline         the baseline
 * @param signedComponents the signed components
 * @return the string
 */
public static String decompositionSvg(@Nonnull final NotebookOutput log, @Nonnull final Tensor baseline, @Nonnull final List<Tensor> signedComponents) {
    final List<DoubleStatistics> componentStats = signedComponents.stream().map(t -> new DoubleStatistics().accept(t.getData())).collect(Collectors.toList());
    @Nonnull final CharSequence positiveFilter = IntStream.range(0, signedComponents.size()).mapToObj(i -> {
        String name;
        try {
            name = String.format("component_%s.png", EncodingUtil.imageNumber++);
            ImageIO.write(signedComponents.get(i).map(v -> v > 0 ? v * (0xFF / componentStats.get(i).getMax()) : 0).toImage(), "png", log.file(name));
        } catch (@Nonnull final IOException e) {
            throw new RuntimeException(e);
        }
        return String.format("  <feImage xlink:href=\"%s\" result=\"pos_image_%s\" />\n", name, i);
    }).reduce((a, b) -> a + "\n" + b).get();
    @Nonnull final CharSequence negativeFilter = IntStream.range(0, signedComponents.size()).mapToObj(i -> {
        String name;
        try {
            name = String.format("component_%s.png", EncodingUtil.imageNumber++);
            ImageIO.write(signedComponents.get(i).map(v -> v < 0 ? 0xFF - v * (0xFF / componentStats.get(i).getMin()) : 0).toImage(), "png", log.file(name));
        } catch (@Nonnull final IOException e) {
            throw new RuntimeException(e);
        }
        return String.format("  <feImage xlink:href=\"%s\" result=\"neg_image_%s\" />\n", name, i);
    }).reduce((a, b) -> a + "\n" + b).get();
    @Nonnull final CharSequence compositingFilters = IntStream.range(0, signedComponents.size()).mapToObj(i -> {
        final double fPos = componentStats.get(i).getMax() / 0xFF;
        final double fNeg = componentStats.get(i).getMin() / 0xFF;
        return "  <feComposite in=\"" + (i == 0 ? "FillPaint" : "lastResult") + "\" in2=\"neg_image_" + i + "\" result=\"lastResult\" operator=\"arithmetic\" k1=\"0.0\" k2=\"1.0\" k3=\"" + -fNeg + "\" k4=\"" + fNeg + "\"/>\n" + "  <feComposite in=\"lastResult\" in2=\"pos_image_" + i + "\" result=\"lastResult\" operator=\"arithmetic\" k1=\"0.0\" k2=\"1.0\" k3=\"" + fPos + "\" k4=\"" + 0.0 + "\"/>\n";
    }).reduce((a, b) -> a + "\n" + b).get();
    final int red = (int) baseline.get(0, 0, 0);
    final int green = (int) baseline.get(0, 0, 1);
    final int blue = (int) baseline.get(0, 0, 2);
    @Nonnull final CharSequence avgHexColor = Long.toHexString(red + (green << 8) + (blue << 16));
    return "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n" + ("<defs>\n" + "<filter id=\"image\" >\n" + (positiveFilter + "\n" + negativeFilter + "\n" + compositingFilters).replaceAll("\n", "\n\t") + "\n" + "</filter>\n" + "</defs>\n" + "<rect style=\"filter:url(#image);\" setByCoord=\"#" + avgHexColor + "\" width=\"256\" height=\"256\"/>").replaceAll("\n", "\n\t") + "\n</svg>";
}

Example 2 with DoubleStatistics

use of com.simiacryptus.util.data.DoubleStatistics in project MindsEye by SimiaCryptus.

the class ArtistryUtil method paint_Circles.

/**
 * Paint circles.
 *
 * @param canvas the canvas
 * @param scale  the scale
 */
public static void paint_Circles(final Tensor canvas, final int scale) {
    BufferedImage originalImage = canvas.toImage();
    BufferedImage newImage = new BufferedImage(originalImage.getWidth(), originalImage.getHeight(), BufferedImage.TYPE_INT_ARGB);
    Graphics2D graphics = (Graphics2D) newImage.getGraphics();
    IntStream.range(0, 10000).forEach(i -> {
        Random random = new Random();
        int positionX = random.nextInt(originalImage.getWidth());
        int positionY = random.nextInt(originalImage.getHeight());
        int width = 1 + random.nextInt(2 * scale);
        int height = 1 + random.nextInt(2 * scale);
        DoubleStatistics[] stats = { new DoubleStatistics(), new DoubleStatistics(), new DoubleStatistics() };
        canvas.coordStream(false).filter(c -> {
            int[] coords = c.getCoords();
            int x = coords[0];
            int y = coords[1];
            double relX = Math.pow(1 - 2 * ((double) (x - positionX) / width), 2);
            double relY = Math.pow(1 - 2 * ((double) (y - positionY) / height), 2);
            return relX + relY < 1.0;
        }).forEach(c -> stats[c.getCoords()[2]].accept(canvas.get(c)));
        graphics.setStroke(new Stroke() {

            @Override
            public Shape createStrokedShape(final Shape p) {
                return null;
            }
        });
        graphics.setColor(new Color((int) stats[0].getAverage(), (int) stats[1].getAverage(), (int) stats[2].getAverage()));
        graphics.fillOval(positionX, positionY, width, height);
    });
    canvas.set(Tensor.fromRGB(newImage));
}

Example 3 with DoubleStatistics

use of com.simiacryptus.util.data.DoubleStatistics in project MindsEye by SimiaCryptus.

the class TestUtil method renderToImages.

/**
 * Render to images stream.
 *
 * @param tensor    the tensor
 * @param normalize the normalize
 * @return the stream
 */
public static Stream<BufferedImage> renderToImages(@Nonnull final Tensor tensor, final boolean normalize) {
    final DoubleStatistics[] statistics = IntStream.range(0, tensor.getDimensions()[2]).mapToObj(band -> {
        return new DoubleStatistics().accept(tensor.coordStream(false).filter(x -> x.getCoords()[2] == band).mapToDouble(c -> tensor.get(c)).toArray());
    }).toArray(i -> new DoubleStatistics[i]);
    @Nonnull final BiFunction<Double, DoubleStatistics, Double> transform = (value, stats) -> {
        final double width = Math.sqrt(2) * stats.getStandardDeviation();
        final double centered = value - stats.getAverage();
        final double distance = Math.abs(value - stats.getAverage());
        final double positiveMax = stats.getMax() - stats.getAverage();
        final double negativeMax = stats.getAverage() - stats.getMin();
        final double unitValue;
        if (value < centered) {
            if (distance > width) {
                unitValue = 0.25 - 0.25 * ((distance - width) / (negativeMax - width));
            } else {
                unitValue = 0.5 - 0.25 * (distance / width);
            }
        } else {
            if (distance > width) {
                unitValue = 0.75 + 0.25 * ((distance - width) / (positiveMax - width));
            } else {
                unitValue = 0.5 + 0.25 * (distance / width);
            }
        }
        return 0xFF * unitValue;
    };
    tensor.coordStream(true).collect(Collectors.groupingBy(x -> x.getCoords()[2], Collectors.toList()));
    @Nullable final Tensor normal = tensor.mapCoords((c) -> transform.apply(tensor.get(c), statistics[c.getCoords()[2]])).map(v -> Math.min(0xFF, Math.max(0, v)));
    return (normalize ? normal : tensor).toImages().stream();
}

Example 4 with DoubleStatistics

use of com.simiacryptus.util.data.DoubleStatistics in project MindsEye by SimiaCryptus.

the class TestUtil method normalizeBands.

/**
 * Normalize bands tensor.
 *
 * @param image the image
 * @param max   the max
 * @return the tensor
 */
public static Tensor normalizeBands(final Tensor image, final int max) {
    DoubleStatistics[] statistics = IntStream.range(0, image.getDimensions()[2]).mapToObj(i -> new DoubleStatistics()).toArray(i -> new DoubleStatistics[i]);
    image.coordStream(false).forEach(c -> {
        double value = image.get(c);
        statistics[c.getCoords()[2]].accept(value);
    });
    return image.mapCoords(c -> {
        double value = image.get(c);
        DoubleStatistics statistic = statistics[c.getCoords()[2]];
        return max * (value - statistic.getMin()) / (statistic.getMax() - statistic.getMin());
    });
}

Example 5 with DoubleStatistics

use of com.simiacryptus.util.data.DoubleStatistics in project MindsEye by SimiaCryptus.

the class QuantifyOrientationWrapper method orient.

@Override
public LineSearchCursor orient(final Trainable subject, final PointSample measurement, @Nonnull final TrainingMonitor monitor) {
    final LineSearchCursor cursor = inner.orient(subject, measurement, monitor);
    if (cursor instanceof SimpleLineSearchCursor) {
        final DeltaSet<Layer> direction = ((SimpleLineSearchCursor) cursor).direction;
        @Nonnull final StateSet<Layer> weights = ((SimpleLineSearchCursor) cursor).origin.weights;
        final Map<CharSequence, CharSequence> dataMap = weights.stream().collect(Collectors.groupingBy(x -> getId(x), Collectors.toList())).entrySet().stream().collect(Collectors.toMap(x -> x.getKey(), list -> {
            final List<Double> doubleList = list.getValue().stream().map(weightDelta -> {
                final DoubleBuffer<Layer> dirDelta = direction.getMap().get(weightDelta.layer);
                final double denominator = weightDelta.deltaStatistics().rms();
                final double numerator = null == dirDelta ? 0 : dirDelta.deltaStatistics().rms();
                return numerator / (0 == denominator ? 1 : denominator);
            }).collect(Collectors.toList());
            if (1 == doubleList.size())
                return Double.toString(doubleList.get(0));
            return new DoubleStatistics().accept(doubleList.stream().mapToDouble(x -> x).toArray()).toString();
        }));
        monitor.log(String.format("Line search stats: %s", dataMap));
    } else {
        monitor.log(String.format("Non-simple cursor: %s", cursor));
    }
    return cursor;
}