Examples with PlotWindow ij.gui.PlotWindow used on opensource projects

Example 6 with PlotWindow

use of ij.gui.PlotWindow in project GDSC-SMLM by aherbert.

the class BenchmarkFilterAnalysis method scoreAnalysis.

/**
	 * Score analysis.
	 *
	 * @param allAssignments
	 *            The assignments generated from running the filter (or null)
	 * @param filter
	 *            the filter
	 * @return the assignments
	 */
private ArrayList<FractionalAssignment[]> scoreAnalysis(ArrayList<FractionalAssignment[]> allAssignments, DirectFilter filter) {
    if (!scoreAnalysis)
        return null;
    // Build a histogram of the fitted spots that were available to be scored
    double[] signal = signalFactorStats.getValues();
    double[] distance = distanceStats.getValues();
    double[] limits1;
    if (BenchmarkSpotFit.signalFactor > 0 && upperSignalFactor > 0) {
        double range = BenchmarkSpotFit.signalFactor * upperSignalFactor / 100.0;
        limits1 = new double[] { -range, range };
    } else {
        limits1 = Maths.limits(signal);
        // Prevent the auto-range being too big
        final double bound = 3;
        if (limits1[0] < -bound)
            limits1[0] = -bound;
        if (limits1[1] > bound)
            limits1[1] = bound;
    }
    double[] limits2;
    if (BenchmarkSpotFit.distanceInPixels > 0 && upperMatchDistance > 0) {
        double range = simulationParameters.a * BenchmarkSpotFit.distanceInPixels * upperMatchDistance / 100.0;
        limits2 = new double[] { 0, range };
    } else {
        limits2 = Maths.limits(distance);
    }
    //final int bins = Math.max(10, nActual / 100);
    //final int bins = Utils.getBinsSturges(signal.length);
    final int bins = Utils.getBinsSqrt(signal.length);
    double[][] h1 = Utils.calcHistogram(signal, limits1[0], limits1[1], bins);
    double[][] h2 = Utils.calcHistogram(distance, limits2[0], limits2[1], bins);
    // Run the filter manually to get the results that pass.
    if (allAssignments == null)
        allAssignments = getAssignments(filter);
    double[] signal2 = new double[results.size()];
    double[] distance2 = new double[results.size()];
    int count = 0;
    double sumSignal = 0, sumDistance = 0;
    for (FractionalAssignment[] assignments : allAssignments) {
        if (assignments == null)
            continue;
        for (int i = 0; i < assignments.length; i++) {
            final CustomFractionalAssignment c = (CustomFractionalAssignment) assignments[i];
            sumDistance += distance2[count] = c.d;
            sumSignal += signal2[count] = c.getSignalFactor();
            count++;
        }
    }
    signal2 = Arrays.copyOf(signal2, count);
    distance2 = Arrays.copyOf(distance2, count);
    // Build a histogram using the same limits
    double[][] h1b = Utils.calcHistogram(signal2, limits1[0], limits1[1], bins);
    double[][] h2b = Utils.calcHistogram(distance2, limits2[0], limits2[1], bins);
    // Since the distance and signal factor are computed for all fits (single, multi, doublet)
    // there will be far more of them so we normalise and just plot the histogram profile.
    double s1 = 0, s2 = 0, s1b = 0, s2b = 0;
    for (int i = 0; i < h1b[0].length; i++) {
        s1 += h1[1][i];
        s2 += h2[1][i];
        s1b += h1b[1][i];
        s2b += h2b[1][i];
    }
    for (int i = 0; i < h1b[0].length; i++) {
        h1[1][i] /= s1;
        h2[1][i] /= s2;
        h1b[1][i] /= s1b;
        h2b[1][i] /= s2b;
    }
    // Draw distance histogram first
    String title2 = TITLE + " Distance Histogram";
    Plot2 plot2 = new Plot2(title2, "Distance (nm)", "Frequency");
    plot2.setLimits(limits2[0], limits2[1], 0, Maths.maxDefault(Maths.max(h2[1]), h2b[1]));
    plot2.setColor(Color.black);
    plot2.addLabel(0, 0, String.format("Blue = Fitted (%s); Red = Filtered (%s)", Utils.rounded(distanceStats.getMean()), Utils.rounded(sumDistance / count)));
    plot2.setColor(Color.blue);
    plot2.addPoints(h2[0], h2[1], Plot2.BAR);
    plot2.setColor(Color.red);
    plot2.addPoints(h2b[0], h2b[1], Plot2.BAR);
    PlotWindow pw2 = Utils.display(title2, plot2);
    if (Utils.isNewWindow())
        wo.add(pw2);
    // Draw signal factor histogram
    String title1 = TITLE + " Signal Factor Histogram";
    Plot2 plot1 = new Plot2(title1, "Signal Factor", "Frequency");
    plot1.setLimits(limits1[0], limits1[1], 0, Maths.maxDefault(Maths.max(h1[1]), h1b[1]));
    plot1.setColor(Color.black);
    plot1.addLabel(0, 0, String.format("Blue = Fitted (%s); Red = Filtered (%s)", Utils.rounded(signalFactorStats.getMean()), Utils.rounded(sumSignal / count)));
    plot1.setColor(Color.blue);
    plot1.addPoints(h1[0], h1[1], Plot2.BAR);
    plot1.setColor(Color.red);
    plot1.addPoints(h1b[0], h1b[1], Plot2.BAR);
    PlotWindow pw1 = Utils.display(title1, plot1);
    if (Utils.isNewWindow())
        wo.add(pw1);
    return allAssignments;
}

Example 7 with PlotWindow

use of ij.gui.PlotWindow in project GDSC-SMLM by aherbert.

the class BackgroundEstimator method plot.

private void plot(WindowOrganiser wo, double[] xValues, double[] data1, double[] data2, double[] data3, String title, String title1, String title2, String title3) {
    // Get limits
    double[] a = Maths.limits(xValues);
    double[] b = Maths.limits(data1);
    b = Maths.limits(b, data2);
    if (data3 != null)
        b = Maths.limits(b, data3);
    title = imp.getTitle() + " " + title;
    Plot2 plot = new Plot2(title, "Slice", title);
    double range = b[1] - b[0];
    if (range == 0)
        range = 1;
    plot.setLimits(a[0], a[1], b[0] - 0.05 * range, b[1] + 0.05 * range);
    plot.setColor(Color.blue);
    plot.addPoints(xValues, data1, Plot2.LINE);
    plot.draw();
    Statistics stats = new Statistics(data1);
    String label = String.format("%s (Blue) = %s +/- %s", title1, Utils.rounded(stats.getMean()), Utils.rounded(stats.getStandardDeviation()));
    plot.setColor(Color.red);
    plot.addPoints(xValues, data2, Plot2.LINE);
    stats = new Statistics(data2);
    label += String.format(", %s (Red) = %s +/- %s", title2, Utils.rounded(stats.getMean()), Utils.rounded(stats.getStandardDeviation()));
    if (data3 != null) {
        plot.setColor(Color.green);
        plot.addPoints(xValues, data3, Plot2.LINE);
        stats = new Statistics(data3);
        label += String.format(", %s (Green) = %s +/- %s", title3, Utils.rounded(stats.getMean()), Utils.rounded(stats.getStandardDeviation()));
    }
    plot.setColor(Color.black);
    plot.addLabel(0, 0, label);
    PlotWindow pw = Utils.display(title, plot);
    if (Utils.isNewWindow())
        wo.add(pw);
}

Example 8 with PlotWindow

use of ij.gui.PlotWindow in project GDSC-SMLM by aherbert.

the class BenchmarkSpotFilter method showFailuresPlot.

private void showFailuresPlot(BenchmarkFilterResult filterResult) {
    double[][] h = filterResult.cumul;
    StoredData data = filterResult.stats;
    String xTitle = "Failures";
    final int id = Utils.showHistogram(TITLE, data, xTitle, 1, 0, 0);
    if (Utils.isNewWindow())
        windowOrganiser.add(id);
    String title = TITLE + " " + xTitle + " Cumulative";
    Plot2 plot = new Plot2(title, xTitle, "Frequency");
    double xMin = (data.size() == 0) ? 1 : h[0][0];
    double xMax = (data.size() == 0) ? 1 : h[0][h[0].length - 1] + 1;
    double xPadding = 0.05 * (xMax - xMin);
    plot.setLimits(xMin - xPadding, xMax, 0, 1.05);
    plot.setColor(Color.blue);
    plot.addPoints(h[0], h[1], Plot2.BAR);
    PlotWindow pw = Utils.display(title, plot);
    if (Utils.isNewWindow())
        windowOrganiser.add(pw);
}

Example 9 with PlotWindow

use of ij.gui.PlotWindow in project GDSC-SMLM by aherbert.

the class BenchmarkSpotFilter method showPlot.

private void showPlot(BenchmarkFilterResult filterResult) {
    double[] r = filterResult.r;
    double[] p = filterResult.p;
    double[] j = filterResult.j;
    double[] c = filterResult.c;
    int fractionIndex = filterResult.fractionIndex;
    int maxIndex = filterResult.maxIndex;
    double auc = filterResult.auc;
    double auc2 = filterResult.auc2;
    double slope = filterResult.slope;
    double[] i1 = filterResult.i1;
    double[] i2 = filterResult.i2;
    double[] intensity = filterResult.intensity;
    double[] rank = new double[intensity.length];
    final double topIntensity = (intensity.length == 1) ? 0 : intensity[1];
    for (int i = 1; i < rank.length; i++) {
        if (rankByIntensity)
            rank[i] = topIntensity - intensity[i];
        else
            rank[i] = i;
    }
    String title = TITLE + " Performance";
    Plot2 plot = new Plot2(title, (rankByIntensity) ? "Relative Intensity" : "Spot Rank", "");
    double[] limits = Maths.limits(rank);
    plot.setLimits(limits[0], limits[1], 0, 1.05);
    plot.setColor(Color.blue);
    plot.addPoints(rank, p, Plot2.LINE);
    //plot.addPoints(rank, maxp, Plot2.DOT);
    plot.setColor(Color.red);
    plot.addPoints(rank, r, Plot2.LINE);
    plot.setColor(Color.black);
    plot.addPoints(rank, j, Plot2.LINE);
    // Plot correlation - update the scale to be 0-1?
    plot.setColor(Color.yellow);
    plot.addPoints(rank, c, Plot2.LINE);
    plot.setColor(Color.magenta);
    plot.drawLine(rank[fractionIndex], 0, rank[fractionIndex], Maths.max(p[fractionIndex], r[fractionIndex], j[fractionIndex], c[fractionIndex]));
    plot.setColor(Color.pink);
    plot.drawLine(rank[maxIndex], 0, rank[maxIndex], Maths.max(p[maxIndex], r[maxIndex], j[maxIndex], c[maxIndex]));
    plot.setColor(Color.black);
    plot.addLabel(0, 0, "Precision=Blue, Recall=Red, Jaccard=Black, Correlation=Yellow");
    PlotWindow pw = Utils.display(title, plot);
    if (Utils.isNewWindow())
        windowOrganiser.add(pw);
    title = TITLE + " Precision-Recall";
    plot = new Plot2(title, "Recall", "Precision");
    plot.setLimits(0, 1, 0, 1.05);
    plot.setColor(Color.red);
    plot.addPoints(r, p, Plot2.LINE);
    //plot.setColor(Color.magenta);
    //plot.addPoints(r, maxp, Plot2.LINE);
    plot.drawLine(r[r.length - 1], p[r.length - 1], r[r.length - 1], 0);
    plot.setColor(Color.black);
    plot.addLabel(0, 0, "AUC = " + Utils.rounded(auc) + ", AUC2 = " + Utils.rounded(auc2));
    PlotWindow pw2 = Utils.display(title, plot);
    if (Utils.isNewWindow())
        windowOrganiser.add(pw2);
    title = TITLE + " Intensity";
    plot = new Plot2(title, "Candidate", "Spot");
    double[] limits1 = Maths.limits(i1);
    double[] limits2 = Maths.limits(i2);
    plot.setLimits(limits1[0], limits1[1], limits2[0], limits2[1]);
    plot.addLabel(0, 0, String.format("Correlation=%s; Slope=%s", Utils.rounded(c[c.length - 1]), Utils.rounded(slope)));
    plot.setColor(Color.red);
    plot.addPoints(i1, i2, Plot.DOT);
    if (slope > 1)
        plot.drawLine(limits1[0], limits1[0] * slope, limits1[1], limits1[1] * slope);
    else
        plot.drawLine(limits2[0] / slope, limits2[0], limits2[1] / slope, limits2[1]);
    PlotWindow pw3 = Utils.display(title, plot);
    if (Utils.isNewWindow())
        windowOrganiser.add(pw3);
}

Example 10 with PlotWindow

use of ij.gui.PlotWindow in project GDSC-SMLM by aherbert.

the class BenchmarkSpotFit method showDoubleHistogram.

private double[] showDoubleHistogram(StoredDataStatistics[][] stats, final int index, WindowOrganiser wo, double[][] matchScores) {
    final String xLabel = filterCriteria[index].name;
    LowerLimit lower = filterCriteria[index].lower;
    UpperLimit upper = filterCriteria[index].upper;
    double[] jaccard = null;
    double[] metric = null;
    double maxJaccard = 0;
    if (index <= FILTER_PRECISION && (settings.showFilterScoreHistograms || upper.requiresJaccard || lower.requiresJaccard)) {
        // Jaccard score verses the range of the metric
        for (final double[] d : matchScores) {
            if (!Double.isFinite(d[index])) {
                System.out.printf("Error in fit data [%d]: %s%n", index, d[index]);
            }
        }
        // Do not use Double.compare(double, double) so we get exceptions in the sort for inf/nan
        Arrays.sort(matchScores, (o1, o2) -> {
            if (o1[index] < o2[index]) {
                return -1;
            }
            if (o1[index] > o2[index]) {
                return 1;
            }
            return 0;
        });
        final int scoreIndex = FILTER_PRECISION + 1;
        final int n = results.size();
        double tp = 0;
        double fp = 0;
        jaccard = new double[matchScores.length + 1];
        metric = new double[jaccard.length];
        for (int k = 0; k < matchScores.length; k++) {
            final double score = matchScores[k][scoreIndex];
            tp += score;
            fp += (1 - score);
            jaccard[k + 1] = tp / (fp + n);
            metric[k + 1] = matchScores[k][index];
        }
        metric[0] = metric[1];
        maxJaccard = MathUtils.max(jaccard);
        if (settings.showFilterScoreHistograms) {
            final String title = TITLE + " Jaccard " + xLabel;
            final Plot plot = new Plot(title, xLabel, "Jaccard");
            plot.addPoints(metric, jaccard, Plot.LINE);
            // Remove outliers
            final double[] limitsx = MathUtils.limits(metric);
            final Percentile p = new Percentile();
            final double l = p.evaluate(metric, 25);
            final double u = p.evaluate(metric, 75);
            final double iqr = 1.5 * (u - l);
            limitsx[1] = Math.min(limitsx[1], u + iqr);
            plot.setLimits(limitsx[0], limitsx[1], 0, MathUtils.max(jaccard));
            ImageJUtils.display(title, plot, wo);
        }
    }
    // [0] is all
    // [1] is matches
    // [2] is no match
    final StoredDataStatistics s1 = stats[0][index];
    final StoredDataStatistics s2 = stats[1][index];
    final StoredDataStatistics s3 = stats[2][index];
    if (s1.getN() == 0) {
        return new double[4];
    }
    final DescriptiveStatistics d = s1.getStatistics();
    double median = 0;
    Plot plot = null;
    String title = null;
    if (settings.showFilterScoreHistograms) {
        median = d.getPercentile(50);
        final String label = String.format("n = %d. Median = %s nm", s1.getN(), MathUtils.rounded(median));
        final HistogramPlot histogramPlot = new HistogramPlotBuilder(TITLE, s1, xLabel).setMinBinWidth(filterCriteria[index].minBinWidth).setRemoveOutliersOption((filterCriteria[index].restrictRange) ? 1 : 0).setPlotLabel(label).build();
        final PlotWindow plotWindow = histogramPlot.show(wo);
        if (plotWindow == null) {
            IJ.log("Failed to show the histogram: " + xLabel);
            return new double[4];
        }
        title = plotWindow.getTitle();
        // Reverse engineer the histogram settings
        plot = histogramPlot.getPlot();
        final double[] xvalues = histogramPlot.getPlotXValues();
        final int bins = xvalues.length;
        final double yMin = xvalues[0];
        final double binSize = xvalues[1] - xvalues[0];
        final double yMax = xvalues[0] + (bins - 1) * binSize;
        if (s2.getN() > 0) {
            final double[] values = s2.getValues();
            final double[][] hist = HistogramPlot.calcHistogram(values, yMin, yMax, bins);
            if (hist[0].length > 0) {
                plot.setColor(Color.red);
                plot.addPoints(hist[0], hist[1], Plot.BAR);
                ImageJUtils.display(title, plot);
            }
        }
        if (s3.getN() > 0) {
            final double[] values = s3.getValues();
            final double[][] hist = HistogramPlot.calcHistogram(values, yMin, yMax, bins);
            if (hist[0].length > 0) {
                plot.setColor(Color.blue);
                plot.addPoints(hist[0], hist[1], Plot.BAR);
                ImageJUtils.display(title, plot);
            }
        }
    }
    // Do cumulative histogram
    final double[][] h1 = MathUtils.cumulativeHistogram(s1.getValues(), true);
    final double[][] h2 = MathUtils.cumulativeHistogram(s2.getValues(), true);
    final double[][] h3 = MathUtils.cumulativeHistogram(s3.getValues(), true);
    if (settings.showFilterScoreHistograms) {
        title = TITLE + " Cumul " + xLabel;
        plot = new Plot(title, xLabel, "Frequency");
        // Find limits
        double[] xlimit = MathUtils.limits(h1[0]);
        xlimit = MathUtils.limits(xlimit, h2[0]);
        xlimit = MathUtils.limits(xlimit, h3[0]);
        // Restrict using the inter-quartile range
        if (filterCriteria[index].restrictRange) {
            final double q1 = d.getPercentile(25);
            final double q2 = d.getPercentile(75);
            final double iqr = (q2 - q1) * 2.5;
            xlimit[0] = MathUtils.max(xlimit[0], median - iqr);
            xlimit[1] = MathUtils.min(xlimit[1], median + iqr);
        }
        plot.setLimits(xlimit[0], xlimit[1], 0, 1.05);
        plot.addPoints(h1[0], h1[1], Plot.LINE);
        plot.setColor(Color.red);
        plot.addPoints(h2[0], h2[1], Plot.LINE);
        plot.setColor(Color.blue);
        plot.addPoints(h3[0], h3[1], Plot.LINE);
    }
    // Determine the maximum difference between the TP and FP
    double maxx1 = 0;
    double maxx2 = 0;
    double max1 = 0;
    double max2 = 0;
    // We cannot compute the delta histogram, or use percentiles
    if (s2.getN() == 0) {
        upper = UpperLimit.ZERO;
        lower = LowerLimit.ZERO;
    }
    final boolean requireLabel = (settings.showFilterScoreHistograms && filterCriteria[index].requireLabel);
    if (requireLabel || upper.requiresDeltaHistogram() || lower.requiresDeltaHistogram()) {
        if (s2.getN() != 0 && s3.getN() != 0) {
            final LinearInterpolator li = new LinearInterpolator();
            final PolynomialSplineFunction f1 = li.interpolate(h2[0], h2[1]);
            final PolynomialSplineFunction f2 = li.interpolate(h3[0], h3[1]);
            for (final double x : h1[0]) {
                if (x < h2[0][0] || x < h3[0][0]) {
                    continue;
                }
                try {
                    final double v1 = f1.value(x);
                    final double v2 = f2.value(x);
                    final double diff = v2 - v1;
                    if (diff > 0) {
                        if (max1 < diff) {
                            max1 = diff;
                            maxx1 = x;
                        }
                    } else if (max2 > diff) {
                        max2 = diff;
                        maxx2 = x;
                    }
                } catch (final OutOfRangeException ex) {
                    // Because we reached the end
                    break;
                }
            }
        }
    }
    if (plot != null) {
        // We use bins=1 on charts where we do not need a label
        if (requireLabel) {
            final String label = String.format("Max+ %s @ %s, Max- %s @ %s", MathUtils.rounded(max1), MathUtils.rounded(maxx1), MathUtils.rounded(max2), MathUtils.rounded(maxx2));
            plot.setColor(Color.black);
            plot.addLabel(0, 0, label);
        }
        ImageJUtils.display(title, plot, wo);
    }
    // Now compute the bounds using the desired limit
    double lowerBound;
    double upperBound;
    switch(lower) {
        case MAX_NEGATIVE_CUMUL_DELTA:
            // Switch to percentiles if we have no delta histogram
            if (maxx2 < 0) {
                lowerBound = maxx2;
                break;
            }
        // fall-through
        case ONE_PERCENT:
            lowerBound = getPercentile(h2, 0.01);
            break;
        case MIN:
            lowerBound = getPercentile(h2, 0.0);
            break;
        case ZERO:
            lowerBound = 0;
            break;
        case HALF_MAX_JACCARD_VALUE:
            lowerBound = getXValue(metric, jaccard, maxJaccard * 0.5);
            break;
        default:
            throw new IllegalStateException("Missing lower limit method");
    }
    switch(upper) {
        case MAX_POSITIVE_CUMUL_DELTA:
            // Switch to percentiles if we have no delta histogram
            if (maxx1 > 0) {
                upperBound = maxx1;
                break;
            }
        // fall-through
        case NINETY_NINE_PERCENT:
            upperBound = getPercentile(h2, 0.99);
            break;
        case NINETY_NINE_NINE_PERCENT:
            upperBound = getPercentile(h2, 0.999);
            break;
        case ZERO:
            upperBound = 0;
            break;
        case MAX_JACCARD2:
            upperBound = getXValue(metric, jaccard, maxJaccard) * 2;
            // System.out.printf("MaxJ = %.4f @ %.3f\n", maxJ, u / 2);
            break;
        default:
            throw new IllegalStateException("Missing upper limit method");
    }
    final double min = getPercentile(h1, 0);
    final double max = getPercentile(h1, 1);
    return new double[] { lowerBound, upperBound, min, max };
}