Examples with FakeGradientFunction gdsc.smlm.function.FakeGradientFunction used on opensource projects

Example 11 with FakeGradientFunction

use of gdsc.smlm.function.FakeGradientFunction in project GDSC-SMLM by aherbert.

the class LVMGradientProcedureTest method gradientProcedureUnrolledComputesSameAsGradientProcedure.

private void gradientProcedureUnrolledComputesSameAsGradientProcedure(int nparams, Type type, boolean precomputed) {
    int iter = 10;
    rdg = new RandomDataGenerator(new Well19937c(30051977));
    ArrayList<double[]> paramsList = new ArrayList<double[]>(iter);
    ArrayList<double[]> yList = new ArrayList<double[]>(iter);
    createFakeData(nparams, iter, paramsList, yList);
    Gradient1Function func = new FakeGradientFunction(blockWidth, nparams);
    if (precomputed) {
        double[] b = Utils.newArray(func.size(), 0.1, 1.3);
        func = PrecomputedGradient1Function.wrapGradient1Function(func, b);
    }
    String name = String.format("[%d] %b", nparams, type);
    for (int i = 0; i < paramsList.size(); i++) {
        LVMGradientProcedure p1 = createProcedure(type, yList.get(i), func);
        p1.gradient(paramsList.get(i));
        LVMGradientProcedure p2 = LVMGradientProcedureFactory.create(yList.get(i), func, type);
        p2.gradient(paramsList.get(i));
        // Exactly the same ...
        Assert.assertEquals(name + " Result: Not same @ " + i, p1.value, p2.value, 0);
        Assert.assertArrayEquals(name + " Observations: Not same beta @ " + i, p1.beta, p2.beta, 0);
        Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, p1.getAlphaLinear(), p2.getAlphaLinear(), 0);
        double[][] am1 = p1.getAlphaMatrix();
        double[][] am2 = p2.getAlphaMatrix();
        for (int j = 0; j < nparams; j++) Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, am1[j], am2[j], 0);
    }
}

Example 12 with FakeGradientFunction

use of gdsc.smlm.function.FakeGradientFunction in project GDSC-SMLM by aherbert.

the class PoissonGradientProcedureTest method gradientProcedureIsNotSlowerThanGradientCalculator.

private void gradientProcedureIsNotSlowerThanGradientCalculator(final int nparams) {
    org.junit.Assume.assumeTrue(speedTests || TestSettings.RUN_SPEED_TESTS);
    final int iter = 1000;
    rdg = new RandomDataGenerator(new Well19937c(30051977));
    final ArrayList<double[]> paramsList = new ArrayList<double[]>(iter);
    createFakeParams(nparams, iter, paramsList);
    final int n = blockWidth * blockWidth;
    final FakeGradientFunction func = new FakeGradientFunction(blockWidth, nparams);
    GradientCalculator calc = GradientCalculatorFactory.newCalculator(nparams, false);
    for (int i = 0; i < paramsList.size(); i++) calc.fisherInformationMatrix(n, paramsList.get(i), func);
    for (int i = 0; i < paramsList.size(); i++) {
        PoissonGradientProcedure p = PoissonGradientProcedureFactory.create(func);
        p.computeFisherInformation(paramsList.get(i));
    }
    // Realistic loops for an optimisation
    final int loops = 15;
    // Run till stable timing
    Timer t1 = new Timer() {

        @Override
        void run() {
            for (int i = 0, k = 0; i < iter; i++) {
                GradientCalculator calc = GradientCalculatorFactory.newCalculator(nparams, false);
                for (int j = loops; j-- > 0; ) calc.fisherInformationMatrix(n, paramsList.get(k++ % iter), func);
            }
        }
    };
    long time1 = t1.getTime();
    Timer t2 = new Timer(t1.loops) {

        @Override
        void run() {
            for (int i = 0, k = 0; i < iter; i++) {
                PoissonGradientProcedure p = PoissonGradientProcedureFactory.create(func);
                for (int j = loops; j-- > 0; ) p.computeFisherInformation(paramsList.get(k++ % iter));
            }
        }
    };
    long time2 = t2.getTime();
    log("GradientCalculator = %d : PoissonGradientProcedure %d = %d : %fx\n", time1, nparams, time2, (1.0 * time1) / time2);
    if (TestSettings.ASSERT_SPEED_TESTS) {
        // Add contingency
        Assert.assertTrue(time2 < time1 * 1.5);
    }
}

Example 13 with FakeGradientFunction

use of gdsc.smlm.function.FakeGradientFunction in project GDSC-SMLM by aherbert.

the class PoissonGradientProcedureTest method gradientProcedureComputesSameAsGradientCalculator.

private void gradientProcedureComputesSameAsGradientCalculator(int nparams) {
    int iter = 10;
    rdg = new RandomDataGenerator(new Well19937c(30051977));
    ArrayList<double[]> paramsList = new ArrayList<double[]>(iter);
    createFakeParams(nparams, iter, paramsList);
    int n = blockWidth * blockWidth;
    FakeGradientFunction func = new FakeGradientFunction(blockWidth, nparams);
    GradientCalculator calc = GradientCalculatorFactory.newCalculator(nparams, false);
    String name = String.format("[%d]", nparams);
    for (int i = 0; i < paramsList.size(); i++) {
        PoissonGradientProcedure p = PoissonGradientProcedureFactory.create(func);
        p.computeFisherInformation(paramsList.get(i));
        double[][] m = calc.fisherInformationMatrix(n, paramsList.get(i), func);
        // Exactly the same ...
        double[] al = p.getLinear();
        Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, al, new DenseMatrix64F(m).data, 0);
        double[][] am = p.getMatrix();
        for (int j = 0; j < nparams; j++) Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, am[j], m[j], 0);
    }
}

Example 14 with FakeGradientFunction

use of gdsc.smlm.function.FakeGradientFunction in project GDSC-SMLM by aherbert.

the class LSQLVMGradientProcedureTest method gradientProcedureUnrolledComputesSameAsGradientProcedure.

private void gradientProcedureUnrolledComputesSameAsGradientProcedure(int nparams) {
    int iter = 10;
    rdg = new RandomDataGenerator(new Well19937c(30051977));
    ArrayList<double[]> paramsList = new ArrayList<double[]>(iter);
    ArrayList<double[]> yList = new ArrayList<double[]>(iter);
    createFakeData(nparams, iter, paramsList, yList);
    FakeGradientFunction func = new FakeGradientFunction(blockWidth, nparams);
    String name = GradientCalculator.class.getSimpleName();
    for (int i = 0; i < paramsList.size(); i++) {
        BaseLSQLVMGradientProcedure p1 = LSQLVMGradientProcedureFactory.create(yList.get(i), func);
        p1.gradient(paramsList.get(i));
        BaseLSQLVMGradientProcedure p2 = new LSQLVMGradientProcedure(yList.get(i), func);
        p2.gradient(paramsList.get(i));
        // Exactly the same ...
        Assert.assertEquals(name + " Result: Not same @ " + i, p1.value, p2.value, 0);
        Assert.assertArrayEquals(name + " Observations: Not same beta @ " + i, p1.beta, p2.beta, 0);
        Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, p1.getAlphaLinear(), p2.getAlphaLinear(), 0);
        double[][] am1 = p1.getAlphaMatrix();
        double[][] am2 = p2.getAlphaMatrix();
        for (int j = 0; j < nparams; j++) Assert.assertArrayEquals(name + " Observations: Not same alpha @ " + i, am1[j], am2[j], 0);
    }
}

Example 15 with FakeGradientFunction

use of gdsc.smlm.function.FakeGradientFunction in project GDSC-SMLM by aherbert.

the class LSQLVMGradientProcedureTest method gradientProcedureLinearIsFasterThanGradientProcedureMatrix.

private void gradientProcedureLinearIsFasterThanGradientProcedureMatrix(final int nparams, final BaseLSQLVMGradientProcedureFactory factory1, final BaseLSQLVMGradientProcedureFactory factory2, boolean doAssert) {
    org.junit.Assume.assumeTrue(speedTests || TestSettings.RUN_SPEED_TESTS);
    final int iter = 100;
    rdg = new RandomDataGenerator(new Well19937c(30051977));
    final ArrayList<double[]> paramsList = new ArrayList<double[]>(iter);
    final ArrayList<double[]> yList = new ArrayList<double[]>(iter);
    createData(1, iter, paramsList, yList);
    // Remove the timing of the function call by creating a dummy function
    final Gradient1Function func = new FakeGradientFunction(blockWidth, nparams);
    for (int i = 0; i < paramsList.size(); i++) {
        BaseLSQLVMGradientProcedure p = factory1.createProcedure(yList.get(i), func);
        p.gradient(paramsList.get(i));
        p.gradient(paramsList.get(i));
        BaseLSQLVMGradientProcedure p2 = factory2.createProcedure(yList.get(i), func);
        p2.gradient(paramsList.get(i));
        p2.gradient(paramsList.get(i));
        // Check they are the same
        Assert.assertArrayEquals("A " + i, p.getAlphaLinear(), p2.getAlphaLinear(), 0);
        Assert.assertArrayEquals("B " + i, p.beta, p2.beta, 0);
    }
    // Realistic loops for an optimisation
    final int loops = 15;
    // Run till stable timing
    Timer t1 = new Timer() {

        @Override
        void run() {
            for (int i = 0, k = 0; i < paramsList.size(); i++) {
                BaseLSQLVMGradientProcedure p = factory1.createProcedure(yList.get(i), func);
                for (int j = loops; j-- > 0; ) p.gradient(paramsList.get(k++ % iter));
            }
        }
    };
    long time1 = t1.getTime();
    Timer t2 = new Timer(t1.loops) {

        @Override
        void run() {
            for (int i = 0, k = 0; i < paramsList.size(); i++) {
                BaseLSQLVMGradientProcedure p2 = factory2.createProcedure(yList.get(i), func);
                for (int j = loops; j-- > 0; ) p2.gradient(paramsList.get(k++ % iter));
            }
        }
    };
    long time2 = t2.getTime();
    log("Standard %s = %d : Unrolled %s %d = %d : %fx\n", factory1.getClass().getSimpleName(), time1, factory2.getClass().getSimpleName(), nparams, time2, (1.0 * time1) / time2);
    if (doAssert)
        Assert.assertTrue(time2 < time1);
}