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

Example 46 with Plot

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

the class BenchmarkSpotFit method showDoubleHistogram.

private double[] showDoubleHistogram(StoredDataStatistics[][] stats, final int i, WindowOrganiser wo, double[][] matchScores, double nPredicted) {
    String xLabel = filterCriteria[i].name;
    LowerLimit lower = filterCriteria[i].lower;
    UpperLimit upper = filterCriteria[i].upper;
    double[] j = null;
    double[] metric = null;
    double maxJ = 0;
    if (i <= FILTER_PRECISION && (showFilterScoreHistograms || upper.requiresJaccard || lower.requiresJaccard)) {
        // Jaccard score verses the range of the metric
        Arrays.sort(matchScores, new Comparator<double[]>() {

            public int compare(double[] o1, double[] o2) {
                if (o1[i] < o2[i])
                    return -1;
                if (o1[i] > o2[i])
                    return 1;
                return 0;
            }
        });
        final int scoreIndex = FILTER_PRECISION + 1;
        int n = results.size();
        double tp = 0;
        double fp = 0;
        j = new double[matchScores.length + 1];
        metric = new double[j.length];
        for (int k = 0; k < matchScores.length; k++) {
            final double score = matchScores[k][scoreIndex];
            tp += score;
            fp += (1 - score);
            j[k + 1] = tp / (fp + n);
            metric[k + 1] = matchScores[k][i];
        }
        metric[0] = metric[1];
        maxJ = Maths.max(j);
        if (showFilterScoreHistograms) {
            String title = TITLE + " Jaccard " + xLabel;
            Plot plot = new Plot(title, xLabel, "Jaccard", metric, j);
            // Remove outliers
            double[] limitsx = Maths.limits(metric);
            Percentile p = new Percentile();
            double l = p.evaluate(metric, 25);
            double u = p.evaluate(metric, 75);
            double iqr = 1.5 * (u - l);
            limitsx[1] = Math.min(limitsx[1], u + iqr);
            plot.setLimits(limitsx[0], limitsx[1], 0, Maths.max(j));
            PlotWindow pw = Utils.display(title, plot);
            if (Utils.isNewWindow())
                wo.add(pw);
        }
    }
    // [0] is all
    // [1] is matches
    // [2] is no match
    StoredDataStatistics s1 = stats[0][i];
    StoredDataStatistics s2 = stats[1][i];
    StoredDataStatistics s3 = stats[2][i];
    if (s1.getN() == 0)
        return new double[4];
    DescriptiveStatistics d = s1.getStatistics();
    double median = 0;
    Plot2 plot = null;
    String title = null;
    if (showFilterScoreHistograms) {
        median = d.getPercentile(50);
        String label = String.format("n = %d. Median = %s nm", s1.getN(), Utils.rounded(median));
        int id = Utils.showHistogram(TITLE, s1, xLabel, filterCriteria[i].minBinWidth, (filterCriteria[i].restrictRange) ? 1 : 0, 0, label);
        if (id == 0) {
            IJ.log("Failed to show the histogram: " + xLabel);
            return new double[4];
        }
        if (Utils.isNewWindow())
            wo.add(id);
        title = WindowManager.getImage(id).getTitle();
        // Reverse engineer the histogram settings
        plot = Utils.plot;
        double[] xValues = Utils.xValues;
        int bins = xValues.length;
        double yMin = xValues[0];
        double binSize = xValues[1] - xValues[0];
        double yMax = xValues[0] + (bins - 1) * binSize;
        if (s2.getN() > 0) {
            double[] values = s2.getValues();
            double[][] hist = Utils.calcHistogram(values, yMin, yMax, bins);
            if (hist[0].length > 0) {
                plot.setColor(Color.red);
                plot.addPoints(hist[0], hist[1], Plot2.BAR);
                Utils.display(title, plot);
            }
        }
        if (s3.getN() > 0) {
            double[] values = s3.getValues();
            double[][] hist = Utils.calcHistogram(values, yMin, yMax, bins);
            if (hist[0].length > 0) {
                plot.setColor(Color.blue);
                plot.addPoints(hist[0], hist[1], Plot2.BAR);
                Utils.display(title, plot);
            }
        }
    }
    // Do cumulative histogram
    double[][] h1 = Maths.cumulativeHistogram(s1.getValues(), true);
    double[][] h2 = Maths.cumulativeHistogram(s2.getValues(), true);
    double[][] h3 = Maths.cumulativeHistogram(s3.getValues(), true);
    if (showFilterScoreHistograms) {
        title = TITLE + " Cumul " + xLabel;
        plot = new Plot2(title, xLabel, "Frequency");
        // Find limits
        double[] xlimit = Maths.limits(h1[0]);
        xlimit = Maths.limits(xlimit, h2[0]);
        xlimit = Maths.limits(xlimit, h3[0]);
        // Restrict using the inter-quartile range 
        if (filterCriteria[i].restrictRange) {
            double q1 = d.getPercentile(25);
            double q2 = d.getPercentile(75);
            double iqr = (q2 - q1) * 2.5;
            xlimit[0] = Maths.max(xlimit[0], median - iqr);
            xlimit[1] = Maths.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 = (showFilterScoreHistograms && filterCriteria[i].requireLabel);
    if (requireLabel || upper.requiresDeltaHistogram() || lower.requiresDeltaHistogram()) {
        if (s2.getN() != 0 && s3.getN() != 0) {
            LinearInterpolator li = new LinearInterpolator();
            PolynomialSplineFunction f1 = li.interpolate(h2[0], h2[1]);
            PolynomialSplineFunction f2 = li.interpolate(h3[0], h3[1]);
            for (double x : h1[0]) {
                if (x < h2[0][0] || x < h3[0][0])
                    continue;
                try {
                    double v1 = f1.value(x);
                    double v2 = f2.value(x);
                    double diff = v2 - v1;
                    if (diff > 0) {
                        if (max1 < diff) {
                            max1 = diff;
                            maxx1 = x;
                        }
                    } else {
                        if (max2 > diff) {
                            max2 = diff;
                            maxx2 = x;
                        }
                    }
                } catch (OutOfRangeException e) {
                    // Because we reached the end
                    break;
                }
            }
        } else {
            // Switch to percentiles if we have no delta histogram
            if (upper.requiresDeltaHistogram())
                upper = UpperLimit.NINETY_NINE_PERCENT;
            if (lower.requiresDeltaHistogram())
                lower = LowerLimit.ONE_PERCENT;
        }
    //			System.out.printf("Bounds %s : %s, pos %s, neg %s, %s\n", xLabel, Utils.rounded(getPercentile(h2, 0.01)),
    //					Utils.rounded(maxx1), Utils.rounded(maxx2), Utils.rounded(getPercentile(h1, 0.99)));
    }
    if (showFilterScoreHistograms) {
        // We use bins=1 on charts where we do not need a label
        if (requireLabel) {
            String label = String.format("Max+ %s @ %s, Max- %s @ %s", Utils.rounded(max1), Utils.rounded(maxx1), Utils.rounded(max2), Utils.rounded(maxx2));
            plot.setColor(Color.black);
            plot.addLabel(0, 0, label);
        }
        PlotWindow pw = Utils.display(title, plot);
        if (Utils.isNewWindow())
            wo.add(pw.getImagePlus().getID());
    }
    // Now compute the bounds using the desired limit
    double l, u;
    switch(lower) {
        case ONE_PERCENT:
            l = getPercentile(h2, 0.01);
            break;
        case MAX_NEGATIVE_CUMUL_DELTA:
            l = maxx2;
            break;
        case ZERO:
            l = 0;
            break;
        case HALF_MAX_JACCARD_VALUE:
            l = getValue(metric, j, maxJ * 0.5);
            break;
        default:
            throw new RuntimeException("Missing lower limit method");
    }
    switch(upper) {
        case MAX_POSITIVE_CUMUL_DELTA:
            u = maxx1;
            break;
        case NINETY_NINE_PERCENT:
            u = getPercentile(h2, 0.99);
            break;
        case NINETY_NINE_NINE_PERCENT:
            u = getPercentile(h2, 0.999);
            break;
        case ZERO:
            u = 0;
            break;
        case MAX_JACCARD2:
            u = getValue(metric, j, maxJ) * 2;
            //System.out.printf("MaxJ = %.4f @ %.3f\n", maxJ, u / 2);
            break;
        default:
            throw new RuntimeException("Missing upper limit method");
    }
    double min = getPercentile(h1, 0);
    double max = getPercentile(h1, 1);
    return new double[] { l, u, min, max };
}

Example 47 with Plot

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

the class BenchmarkSpotFilter method plot.

private void plot(int i, ArrayList<BatchResult[]> batchResults) {
    if (!batchPlot[i])
        return;
    Color[] colors = new Color[] { Color.red, Color.gray, Color.green, Color.blue, Color.magenta };
    String name = batchPlotNames[i];
    String title = TITLE + " Performance " + name;
    Plot plot = new Plot(title, "Relative width", name);
    final double scale = 1.0 / config.getHWHMMin();
    for (BatchResult[] batchResult : batchResults) {
        if (batchResult == null || batchResult.length == 0)
            continue;
        float[][] data = extractData(batchResult, i, scale);
        int colorIndex = batchResult[0].dataFilter.ordinal();
        plot.setColor(colors[colorIndex]);
        colors[colorIndex] = colors[colorIndex].darker();
        plot.addPoints(data[0], data[1], null, (batchResult.length > 1) ? Plot.LINE : Plot.CIRCLE, batchResult[0].getName());
    }
    plot.setColor(Color.black);
    plot.addLegend(null);
    if (name.contains("Time"))
        plot.setAxisYLog(true);
    PlotWindow pw = Utils.display(title, plot);
    // Seems to only work after drawing
    plot.setLimitsToFit(true);
    if (Utils.isNewWindow())
        windowOrganiser.add(pw);
}

Example 48 with Plot

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

the class PSFCreator method subtractBackgroundAndWindow.

/**
	 * Subtract the background from the spot, compute the intensity within half the box region distance from the centre
	 * and smooth the intensity profile. In interactive mode the user must choose to accept the profile or reject.
	 * If accepted the smoothed profile is user to normalise the image and then the image is rolled off to zero
	 * using a Tukey window function.
	 * 
	 * @param spot
	 * @param background
	 *            The minimum level, all below this is background and set to zero
	 * @param spotWidth
	 * @param spotHeight
	 * @param n
	 *            The spot number
	 * @param loess
	 *            The smoothing interpolator
	 * @return True if accepted
	 */
private boolean subtractBackgroundAndWindow(float[][] spot, final float background, final int spotWidth, final int spotHeight, double[] centre, LoessInterpolator loess) {
    //ImageWindow imageWindow = new ImageWindow();
    for (int i = 0; i < spot.length; i++) {
        for (int j = 0; j < spot[i].length; j++) spot[i][j] = FastMath.max(spot[i][j] - background, 0);
    }
    // Create a distance map from the centre
    if (lastWidth != spotWidth || lastHeight != spotHeight) {
        final double cx = spotWidth * 0.5;
        final double cy = spotHeight * 0.5;
        minx = FastMath.max(0, (int) (cx - boxRadius * 0.5));
        maxx = FastMath.min(spotWidth, (int) Math.ceil(cx + boxRadius * 0.5));
        miny = FastMath.max(0, (int) (cy - boxRadius * 0.5));
        maxy = FastMath.min(spotHeight, (int) Math.ceil(cy + boxRadius * 0.5));
        // Precompute square distances
        double[] dx2 = new double[maxx - minx + 1];
        for (int x = minx, i = 0; x < maxx; x++, i++) {
            // Use pixel centres with 0.5 offset
            final double dx = x + 0.5 - cx;
            dx2[i] = dx * dx;
        }
        dmap = new boolean[dx2.length * (maxy - miny + 1)];
        final double d2 = boxRadius * boxRadius / 4;
        for (int y = miny, j = 0; y < maxy; y++) {
            final double dy = (y + 0.5 - cy);
            final double dy2 = dy * dy;
            final double limit = d2 - dy2;
            for (int x = minx, i = 0; x < maxx; x++, i++, j++) {
                dmap[j] = (dx2[i] < limit);
            }
        }
        lastWidth = spotWidth;
        lastHeight = spotHeight;
    }
    // Calculate the intensity profile within half the box radius from the centre
    double[] xValues = new double[spot.length];
    double[] yValues = new double[spot.length];
    for (int i = 0; i < spot.length; i++) {
        xValues[i] = i + 1;
        double sum = 0;
        for (int y = miny, j = 0; y < maxy; y++) {
            int index = y * spotWidth + minx;
            for (int x = minx; x < maxx; x++, index++, j++) if (dmap[j])
                sum += spot[i][index];
        }
        yValues[i] = sum;
    }
    double[] newY = loess.smooth(xValues, yValues);
    // falls towards zero at the ends)
    for (int i = 0; i < newY.length; i++) if (newY[i] < 0)
        newY[i] = yValues[i];
    if (interactiveMode) {
        Utils.hide(TITLE_AMPLITUDE);
        Utils.hide(TITLE_PSF_PARAMETERS);
        final int n = (int) centre[4];
        String title = TITLE_INTENSITY;
        Plot plot = new Plot(title, "Slice", "Sum", xValues, yValues);
        plot.setColor(Color.red);
        plot.addPoints(xValues, newY, Plot.LINE);
        plot.setColor(Color.green);
        double[] limits = Maths.limits(yValues);
        plot.drawLine(centre[2], limits[0], centre[2], limits[1]);
        plot.setColor(Color.black);
        plot.addLabel(0, 0, "Spot " + n);
        Utils.display(title, plot);
        GenericDialog gd = new GenericDialog(TITLE);
        gd.enableYesNoCancel();
        gd.hideCancelButton();
        gd.addMessage(String.format("Add spot %d to the PSF?\n(The intensity profile is the sum within half the box region)", n));
        if (yesNoPosition != null) {
            gd.centerDialog(false);
            gd.setLocation(yesNoPosition);
        }
        gd.showDialog();
        yesNoPosition = gd.getLocation();
        if (!gd.wasOKed())
            return false;
    }
    for (int i = 0; i < spot.length; i++) {
        // Normalise
        final float scale = (float) (newY[i] / yValues[i]);
        for (int j = 0; j < spot[i].length; j++) spot[i][j] *= scale;
        // Use a Tukey window to roll-off the image edges
        //spot[i] = imageWindow.applySeperable(spot[i], spotWidth, spotHeight, ImageWindow.WindowFunction.Tukey);
        spot[i] = ImageWindow.applyWindow(spot[i], spotWidth, spotHeight, ImageWindow.WindowFunction.TUKEY);
    }
    return true;
}

Example 49 with Plot

use of ij.gui.Plot in project vcell by virtualcell.

the class PlotCellRegionStats method run.

@Override
public void run() {
    Plot plot = new ColorPlot("Cell region mean intensity", "Time", "Mean intensity");
    StringBuilder legendLabels = new StringBuilder();
    for (int i = 0; i < datasets.size(); i++) {
        RandomAccessibleInterval<T> data = datasets.get(i);
        if (data instanceof Dataset) {
            legendLabels.append(((Dataset) data).getName());
            legendLabels.append(": ");
        }
        RandomAccessibleInterval<T> cropped = ops.transform().crop(data, mask);
        displayService.createDisplay(cropped);
    }
}

Example 50 with Plot

use of ij.gui.Plot in project mcib3d-core by mcib3d.

the class Segment3DSpots method gaussianFit.

/**
 * @param x
 * @param y
 * @param z
 * @param plotb
 * @return
 */
public double[] gaussianFit(int x, int y, int z, boolean plotb) {
    double[] gaussFit;
    double[] params;
    if (WATERSHED) {
        gaussFit = rawImage.radialDistribution(x, y, z, GAUSS_MAXR, Object3D.MEASURE_INTENSITY_AVG, watershedImage);
    } else {
        gaussFit = rawImage.radialDistribution(x, y, z, GAUSS_MAXR);
    }
    params = ArrayUtil.fitGaussian(gaussFit, 3, GAUSS_MAXR);
    // plot
    if (plotb) {
        double[] xx = new double[gaussFit.length];
        for (int i = 0; i < xx.length; i++) {
            xx[i] = i;
        }
        Plot plot = new Plot("Rad", "X", "Y", xx, gaussFit);
        plot.show();
    }
    return params;
}