Examples with DoubleRollingArray uk.ac.sussex.gdsc.core.utils.DoubleRollingArray used on opensource projects

Example 1 with DoubleRollingArray

use of uk.ac.sussex.gdsc.core.utils.DoubleRollingArray in project GDSC-SMLM by aherbert.

the class DiffusionRateTest method msdAnalysis.

/**
 * Tabulate the observed MSD for different jump distances.
 *
 * @param points the points
 */
private void msdAnalysis(ArrayList<Point> points) {
    if (myMsdAnalysisSteps == 0) {
        return;
    }
    IJ.showStatus("MSD analysis ...");
    IJ.showProgress(1, myMsdAnalysisSteps);
    // This will only be fast if the list is an array
    final Point[] list = points.toArray(new Point[0]);
    // Compute the base MSD
    final Point origin = new Point(0, 0, 0);
    double sum = origin.distance2(list[0]);
    int count = 1;
    for (int i = 1; i < list.length; i++) {
        final Point last = list[i - 1];
        final Point current = list[i];
        if (last.id == current.id) {
            sum += last.distance2(current);
        } else {
            sum += origin.distance2(current);
        }
        count++;
    }
    // Create a new set of points that have coordinates that
    // are the rolling average over the number of aggregate steps
    final DoubleRollingArray x = new DoubleRollingArray(pluginSettings.aggregateSteps);
    final DoubleRollingArray y = new DoubleRollingArray(pluginSettings.aggregateSteps);
    int id = 0;
    int length = 0;
    for (final Point p : points) {
        if (p.id != id) {
            x.clear();
            y.clear();
        }
        id = p.id;
        x.add(p.x);
        y.add(p.y);
        // Only create a point if the full aggregation size is reached
        if (x.isFull()) {
            list[length++] = new Point(id, x.getAverage(), y.getAverage());
        }
    }
    // Q - is this useful?
    final double p = myPrecision / settings.getPixelPitch();
    final UniformRandomProvider rng = UniformRandomProviders.create();
    final NormalizedGaussianSampler gauss = SamplerUtils.createNormalizedGaussianSampler(rng);
    final int totalSteps = (int) Math.ceil(settings.getSeconds() * settings.getStepsPerSecond() - pluginSettings.aggregateSteps);
    final int limit = Math.min(totalSteps, myMsdAnalysisSteps);
    final Ticker ticker = ImageJUtils.createTicker(limit, 1);
    final TextWindow msdTable = createMsdTable((sum / count) * settings.getStepsPerSecond() / conversionFactor);
    try (BufferedTextWindow bw = new BufferedTextWindow(msdTable)) {
        bw.setIncrement(0);
        for (int step = 1; step <= myMsdAnalysisSteps; step++) {
            sum = 0;
            count = 0;
            for (int i = step; i < length; i++) {
                final Point last = list[i - step];
                final Point current = list[i];
                if (last.id == current.id) {
                    if (p == 0) {
                        sum += last.distance2(current);
                        count++;
                    } else {
                        // is the same if enough samples are present
                        for (int ii = 1; ii-- > 0; ) {
                            sum += last.distance2(current, p, gauss);
                            count++;
                        }
                    }
                }
            }
            if (count == 0) {
                break;
            }
            bw.append(addResult(step, sum, count));
            ticker.tick();
        }
    }
    IJ.showProgress(1);
}