use of org.apache.commons.math3.random.RandomGenerator 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);
}
}
use of org.apache.commons.math3.random.RandomGenerator 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();
}
use of org.apache.commons.math3.random.RandomGenerator in project GDSC-SMLM by aherbert.
the class PrecomputedFunctionTest method precomputedGradient1FunctionWrapsPrecomputedValues.
@Test
public void precomputedGradient1FunctionWrapsPrecomputedValues() {
int n = 3;
RandomGenerator r = new Well19937c(30051977);
Gradient1Function f0 = new FakeGradientFunction(3, n);
int size = f0.size();
double[] b1 = new PseudoRandomGenerator(size, r).getSequence();
double[] b2 = new PseudoRandomGenerator(size, r).getSequence();
Gradient1Function f1 = PrecomputedGradient1Function.wrapGradient1Function(f0, b1);
Gradient1Function f2 = PrecomputedGradient1Function.wrapGradient1Function(f1, b2);
double[] p = new double[n];
for (int i = 0; i < n; i++) p[i] = r.nextDouble();
double[] d0 = new double[n];
double[] d1 = new double[n];
double[] d2 = new double[n];
double[] v0 = evaluateGradient1Function(f0, p, d0);
double[] v1 = evaluateGradient1Function(f1, p, d1);
double[] v2 = evaluateGradient1Function(f2, p, d2);
for (int i = 0; i < v0.length; i++) {
double e = v0[i] + b1[i] + b2[i];
double o1 = v1[i] + b2[i];
double o2 = v2[i];
Assert.assertEquals("o1", e, o1, 0);
Assert.assertEquals("o2", e, o2, 1e-6);
}
Assert.assertArrayEquals("d1", d0, d1, 0);
Assert.assertArrayEquals("d2", d0, d2, 0);
}
use of org.apache.commons.math3.random.RandomGenerator in project GDSC-SMLM by aherbert.
the class PrecomputedFunctionTest method precomputedValueFunctionWrapsPrecomputedValues.
@Test
public void precomputedValueFunctionWrapsPrecomputedValues() {
int n = 3;
RandomGenerator r = new Well19937c(30051977);
ValueFunction f0 = new FakeGradientFunction(3, n);
int size = f0.size();
double[] b1 = new PseudoRandomGenerator(size, r).getSequence();
double[] b2 = new PseudoRandomGenerator(size, r).getSequence();
ValueFunction f1 = PrecomputedValueFunction.wrapValueFunction(f0, b1);
ValueFunction f2 = PrecomputedValueFunction.wrapValueFunction(f1, b2);
double[] p = new double[n];
for (int i = 0; i < n; i++) p[i] = r.nextDouble();
double[] v0 = evaluateValueFunction(f0, p);
double[] v1 = evaluateValueFunction(f1, p);
double[] v2 = evaluateValueFunction(f2, p);
for (int i = 0; i < v0.length; i++) {
double e = v0[i] + b1[i] + b2[i];
double o1 = v1[i] + b2[i];
double o2 = v2[i];
Assert.assertEquals("o1", e, o1, 0);
Assert.assertEquals("o2", e, o2, 1e-6);
}
}
use of org.apache.commons.math3.random.RandomGenerator in project GDSC-SMLM by aherbert.
the class PrecomputedFunctionTest method precomputedGradient2FunctionWrapsPrecomputedValues.
@Test
public void precomputedGradient2FunctionWrapsPrecomputedValues() {
int n = 3;
RandomGenerator r = new Well19937c(30051977);
Gradient2Function f0 = new FakeGradientFunction(3, n);
int size = f0.size();
double[] b1 = new PseudoRandomGenerator(size, r).getSequence();
double[] b2 = new PseudoRandomGenerator(size, r).getSequence();
Gradient2Function f1 = PrecomputedGradient2Function.wrapGradient2Function(f0, b1);
Gradient2Function f2 = PrecomputedGradient2Function.wrapGradient2Function(f1, b2);
double[] p = new double[n];
for (int i = 0; i < n; i++) p[i] = r.nextDouble();
double[] d0 = new double[n];
double[] d1 = new double[n];
double[] d2 = new double[n];
double[] d20 = new double[n];
double[] d21 = new double[n];
double[] d22 = new double[n];
double[] v0 = evaluateGradient2Function(f0, p, d0, d20);
double[] v1 = evaluateGradient2Function(f1, p, d1, d21);
double[] v2 = evaluateGradient2Function(f2, p, d2, d22);
for (int i = 0; i < v0.length; i++) {
double e = v0[i] + b1[i] + b2[i];
double o1 = v1[i] + b2[i];
double o2 = v2[i];
Assert.assertEquals("o1", e, o1, 0);
Assert.assertEquals("o2", e, o2, 1e-6);
}
Assert.assertArrayEquals("d1", d0, d1, 0);
Assert.assertArrayEquals("d2", d0, d2, 0);
Assert.assertArrayEquals("d21", d20, d21, 0);
Assert.assertArrayEquals("d22", d20, d22, 0);
}
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