Examples with ConvolutionValueProcedure uk.ac.sussex.gdsc.smlm.utils.Convolution.ConvolutionValueProcedure used on opensource projects

Example 1 with ConvolutionValueProcedure

use of uk.ac.sussex.gdsc.smlm.utils.Convolution.ConvolutionValueProcedure in project GDSC-SMLM by aherbert.

the class ConvolutionTest method canComputeScaledConvolutionWithEarlyExit.

@SeededTest
void canComputeScaledConvolutionWithEarlyExit(RandomSeed seed) {
    final UniformRandomProvider random = RngUtils.create(seed.getSeed());
    int size = 10;
    final int sizeLoops = 4;
    final int sLoops = 2;
    for (int i = 0; i < sizeLoops; i++) {
        double sd = 0.5;
        for (int j = 0; j < sLoops; j++) {
            final double[] data = randomData(random, size);
            final double[] kernel = createKernel(sd);
            for (int scale = 2; scale < 5; scale++) {
                final double[] e = Convolution.convolve(kernel, data, scale);
                final double[] o = new double[e.length];
                final int limit = data.length;
                Convolution.convolve(kernel, data, scale, new ConvolutionValueProcedure() {

                    int index = 0;

                    @Override
                    public boolean execute(double value) {
                        o[index++] = value;
                        return index < limit;
                    }
                });
                int index = 0;
                for (; index < limit; index++) {
                    Assertions.assertEquals(e[index], o[index]);
                }
                while (index < o.length) {
                    Assertions.assertEquals(0, o[index++]);
                }
            }
            sd *= 2;
        }
        size *= 2;
    }
}

Example 2 with ConvolutionValueProcedure

use of uk.ac.sussex.gdsc.smlm.utils.Convolution.ConvolutionValueProcedure in project GDSC-SMLM by aherbert.

the class ConvolutionTest method canComputeScaledConvolution.

@SeededTest
void canComputeScaledConvolution(RandomSeed seed) {
    final UniformRandomProvider random = RngUtils.create(seed.getSeed());
    final TDoubleArrayList list = new TDoubleArrayList();
    int size = 10;
    for (int i = 0; i < sizeLoops; i++) {
        double sd = 0.5;
        for (int j = 0; j < sdLoops; j++) {
            final double[] data = randomData(random, size);
            final double[] kernel = createKernel(sd);
            for (int scale = 2; scale < 5; scale++) {
                final double[] e = convolve(kernel, data, list, scale);
                final double[] o = Convolution.convolve(kernel, data, scale);
                final double[] o2 = new double[o.length];
                Convolution.convolve(kernel, data, scale, new ConvolutionValueProcedure() {

                    int index = 0;

                    @Override
                    public boolean execute(double value) {
                        o2[index++] = value;
                        return true;
                    }
                });
                Assertions.assertArrayEquals(e, o);
                Assertions.assertArrayEquals(e, o2);
            }
            sd *= 2;
        }
        size *= 2;
    }
}