Examples with IJImagePeakResults gdsc.smlm.ij.results.IJImagePeakResults used on opensource projects

Example 11 with IJImagePeakResults

use of gdsc.smlm.ij.results.IJImagePeakResults in project GDSC-SMLM by aherbert.

the class PeakFit method initialiseFitting.

/**
	 * Set-up the fitting using all the configured properties. Prepare the output results.
	 */
public boolean initialiseFitting() {
    if (source == null)
        return false;
    // Do this to ensure the serialised configuration is correct
    updateFitConfiguration(config);
    results.setSource(source);
    if (maximaIdentification)
        results.setName(source.getName() + " (Maxima)");
    else if (fitMaxima)
        results.setName(source.getName() + " (" + getSolverName() + " Fit Maxima)");
    else
        results.setName(source.getName() + " (" + getSolverName() + ")");
    results.setBounds(bounds);
    Calibration cal = calibration.clone();
    // Account for the frame integration
    // TODO - Should we change this so that if integrate frames is used then the data 
    // are converted to ExtendedPeakResult with a start and end frame
    //cal.exposureTime *= integrateFrames;
    //if (interlacedData)
    //{
    //	cal.exposureTime *= ((double)dataBlock / (dataBlock + dataSkip));
    //}
    results.setCalibration(cal);
    results.setConfiguration(XmlUtils.toXML(config));
    addMemoryResults(results, false);
    addImageResults(results);
    addFileResults(results);
    addTableResults(results);
    addDefaultResults(results);
    results.begin();
    if (simpleFit && showImage) {
        for (PeakResults r : results.toArray()) {
            if (r instanceof IJImagePeakResults) {
                ImagePlus i = ((IJImagePeakResults) r).getImagePlus();
                Utils.log("Super-resolution image title = " + i.getTitle());
                WindowManager.toFront(i.getWindow());
            }
        }
    }
    return true;
}

Example 12 with IJImagePeakResults

use of gdsc.smlm.ij.results.IJImagePeakResults in project GDSC-SMLM by aherbert.

the class FRCTest method canComputeMirrored.

@Test
public void canComputeMirrored() {
    // Sample lines through an image to create a structure.
    int size = 1024;
    double[][] data = new double[size * 2][];
    RandomGenerator r = new Well19937c(30051977);
    for (int x = 0, y = 0, y2 = size, i = 0; x < size; x++, y++, y2--) {
        data[i++] = new double[] { x + r.nextGaussian() * 5, y + r.nextGaussian() * 5 };
        data[i++] = new double[] { x + r.nextGaussian() * 5, y2 + r.nextGaussian() * 5 };
    }
    // Create 2 images
    Rectangle bounds = new Rectangle(0, 0, size, size);
    IJImagePeakResults i1 = createImage(bounds);
    IJImagePeakResults i2 = createImage(bounds);
    int[] indices = Utils.newArray(data.length, 0, 1);
    MathArrays.shuffle(indices, r);
    for (int i : indices) {
        IJImagePeakResults image = i1;
        i1 = i2;
        i2 = image;
        image.add((float) data[i][0], (float) data[i][1], 1);
    }
    i1.end();
    i2.end();
    ImageProcessor ip1 = i1.getImagePlus().getProcessor();
    ImageProcessor ip2 = i2.getImagePlus().getProcessor();
    // Test
    FRC frc = new FRC();
    FloatProcessor[] fft1, fft2;
    fft1 = frc.getComplexFFT(ip1);
    fft2 = frc.getComplexFFT(ip2);
    float[] dataA1 = (float[]) fft1[0].getPixels();
    float[] dataB1 = (float[]) fft1[1].getPixels();
    float[] dataA2 = (float[]) fft2[0].getPixels();
    float[] dataB2 = (float[]) fft2[1].getPixels();
    float[] numeratorE = new float[dataA1.length];
    float[] absFFT1E = new float[dataA1.length];
    float[] absFFT2E = new float[dataA1.length];
    FRC.compute(numeratorE, absFFT1E, absFFT2E, dataA1, dataB1, dataA2, dataB2);
    Assert.assertTrue("numeratorE", FRC.checkSymmetry(numeratorE, size));
    Assert.assertTrue("absFFT1E", FRC.checkSymmetry(absFFT1E, size));
    Assert.assertTrue("absFFT2E", FRC.checkSymmetry(absFFT2E, size));
    float[] numeratorA = new float[dataA1.length];
    float[] absFFT1A = new float[dataA1.length];
    float[] absFFT2A = new float[dataA1.length];
    FRC.computeMirrored(size, numeratorA, absFFT1A, absFFT2A, dataA1, dataB1, dataA2, dataB2);
    //for (int y=0, i=0; y<size; y++)
    //	for (int x=0; x<size; x++, i++)
    //	{
    //		System.out.printf("[%d,%d = %d] %f ?= %f\n", x, y, i, numeratorE[i], numeratorA[i]);
    //	}
    Assert.assertArrayEquals("numerator", numeratorE, numeratorA, 0);
    Assert.assertArrayEquals("absFFT1", absFFT1E, absFFT1A, 0);
    Assert.assertArrayEquals("absFFT2", absFFT2E, absFFT2A, 0);
    FRC.computeMirroredFast(size, numeratorA, absFFT1A, absFFT2A, dataA1, dataB1, dataA2, dataB2);
    // Check this.
    for (int y = 1; y < size; y++) for (int x = 1, i = y * size + 1; x < size; x++, i++) {
        Assert.assertEquals("numerator", numeratorE[i], numeratorA[i], 0);
        Assert.assertEquals("absFFT1", absFFT1E[i], absFFT1A[i], 0);
        Assert.assertEquals("absFFT2", absFFT2E[i], absFFT2A[i], 0);
    }
}

Example 13 with IJImagePeakResults

use of gdsc.smlm.ij.results.IJImagePeakResults in project GDSC-SMLM by aherbert.

the class FRCTest method computeMirroredIsFaster.

@Test
public void computeMirroredIsFaster() {
    // Sample lines through an image to create a structure.
    final int size = 2048;
    double[][] data = new double[size * 2][];
    RandomGenerator r = new Well19937c(30051977);
    for (int x = 0, y = 0, y2 = size, i = 0; x < size; x++, y++, y2--) {
        data[i++] = new double[] { x + r.nextGaussian() * 5, y + r.nextGaussian() * 5 };
        data[i++] = new double[] { x + r.nextGaussian() * 5, y2 + r.nextGaussian() * 5 };
    }
    // Create 2 images
    Rectangle bounds = new Rectangle(0, 0, size, size);
    IJImagePeakResults i1 = createImage(bounds);
    IJImagePeakResults i2 = createImage(bounds);
    int[] indices = Utils.newArray(data.length, 0, 1);
    MathArrays.shuffle(indices, r);
    for (int i : indices) {
        IJImagePeakResults image = i1;
        i1 = i2;
        i2 = image;
        image.add((float) data[i][0], (float) data[i][1], 1);
    }
    i1.end();
    i2.end();
    ImageProcessor ip1 = i1.getImagePlus().getProcessor();
    ImageProcessor ip2 = i2.getImagePlus().getProcessor();
    // Test
    FRC frc = new FRC();
    FloatProcessor[] fft1, fft2;
    fft1 = frc.getComplexFFT(ip1);
    fft2 = frc.getComplexFFT(ip2);
    final float[] dataA1 = (float[]) fft1[0].getPixels();
    final float[] dataB1 = (float[]) fft1[1].getPixels();
    final float[] dataA2 = (float[]) fft2[0].getPixels();
    final float[] dataB2 = (float[]) fft2[1].getPixels();
    final float[] numerator = new float[dataA1.length];
    final float[] absFFT1 = new float[dataA1.length];
    final float[] absFFT2 = new float[dataA1.length];
    TimingService ts = new TimingService(10);
    ts.execute(new MyTimingTask("compute") {

        public Object run(Object data) {
            FRC.compute(numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
            return null;
        }
    });
    ts.execute(new MyTimingTask("computeMirrored") {

        public Object run(Object data) {
            FRC.computeMirrored(size, numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
            return null;
        }
    });
    ts.execute(new MyTimingTask("computeMirroredFast") {

        public Object run(Object data) {
            FRC.computeMirroredFast(size, numerator, absFFT1, absFFT2, dataA1, dataB1, dataA2, dataB2);
            return null;
        }
    });
    ts.repeat(ts.getSize());
    ts.report();
}

Example 14 with IJImagePeakResults

use of gdsc.smlm.ij.results.IJImagePeakResults in project GDSC-SMLM by aherbert.

the class SphericalDistributionTest method drawImage.

private void drawImage(boolean useRejctionMethod) {
    MemoryPeakResults results = new MemoryPeakResults();
    results.setSortAfterEnd(true);
    int radius = 10;
    Rectangle bounds = new Rectangle(0, 0, radius * 2, radius * 2);
    SphericalDistribution dist = new SphericalDistribution(radius, rand);
    dist.setUseRejectionMethod(useRejctionMethod);
    float scale = 10;
    results.begin();
    for (int i = 100000; i-- > 0; ) {
        double[] xyz = dist.next();
        int peak = (int) (1 + scale * radius + Math.round(scale * xyz[2]));
        float[] params = new float[7];
        params[Gaussian2DFunction.X_POSITION] = radius + (float) xyz[0];
        params[Gaussian2DFunction.Y_POSITION] = radius + (float) xyz[1];
        results.addf(peak, 0, 0, 0, 0, 0, params, null);
    }
    results.end();
    IJImagePeakResults image = new IJImagePeakResults((useRejctionMethod) ? "Rejection Method" : "Transformation Method", bounds, scale);
    image.setRollingWindowSize(1);
    image.begin();
    image.addAll(results.getResults());
    // Place breakpoint here in debug mode to view the image. 
    // It should have an even colour through the stack.
    image.end();
}