Package org.apache.commons.math3.analysis.function

Examples of org.apache.commons.math3.analysis.function.Sin

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    }

    /** Test of transformer for the sine function. */
    @Test
    public void testSinFunction() {
        UnivariateFunction f = new Sin();
        FastCosineTransformer transformer;
        transformer = new FastCosineTransformer(DctNormalization.STANDARD_DCT_I);
        double min, max, result[], tolerance = 1E-12;
        int N = 9;

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    /**
     * Test of solver for the sine function.
     */
    @Test
    public void testSinFunction() {
        UnivariateFunction f = new Sin();
        UnivariateSolver solver = new MullerSolver();
        double min, max, expected, result, tolerance;

        min = 3.0; max = 4.0; expected = FastMath.PI;
        tolerance = FastMath.max(solver.getAbsoluteAccuracy(),
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    /**
     * Test of parameters for the solver.
     */
    @Test
    public void testParameters() {
        UnivariateFunction f = new Sin();
        UnivariateSolver solver = new MullerSolver();

        try {
            // bad interval
            double root = solver.solve(100, f, 1, -1);
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*/
public final class BrentOptimizerTest {

    @Test
    public void testSinMin() {
        UnivariateFunction f = new Sin();
        UnivariateOptimizer optimizer = new BrentOptimizer(1e-10, 1e-14);
        Assert.assertEquals(3 * Math.PI / 2, optimizer.optimize(200, f, GoalType.MINIMIZE, 4, 5).getPoint(), 1e-8);
        Assert.assertTrue(optimizer.getEvaluations() <= 50);
        Assert.assertEquals(200, optimizer.getMaxEvaluations());
        Assert.assertEquals(3 * Math.PI / 2, optimizer.optimize(200, f, GoalType.MINIMIZE, 1, 5).getPoint(), 1e-8);
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        }
    }

    @Test
    public void testSinMinWithValueChecker() {
        final UnivariateFunction f = new Sin();
        final ConvergenceChecker<UnivariatePointValuePair> checker = new SimpleUnivariateValueChecker(1e-5, 1e-14);
        // The default stopping criterion of Brent's algorithm should not
        // pass, but the search will stop at the given relative tolerance
        // for the function value.
        final UnivariateOptimizer optimizer = new BrentOptimizer(1e-10, 1e-14, checker);
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        }
    }

    @Test
    public void testMinEndpoints() {
        UnivariateFunction f = new Sin();
        UnivariateOptimizer optimizer = new BrentOptimizer(1e-8, 1e-14);

        // endpoint is minimum
        double result = optimizer.optimize(50, f, GoalType.MINIMIZE, 3 * Math.PI / 2, 5).getPoint();
        Assert.assertEquals(3 * Math.PI / 2, result, 1e-6);
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    @Test
    public void testKeepInitIfBest() {
        final double minSin = 3 * Math.PI / 2;
        final double offset = 1e-8;
        final double delta = 1e-7;
        final UnivariateFunction f1 = new Sin();
        final UnivariateFunction f2 = new StepFunction(new double[] { minSin, minSin + offset, minSin + 2 * offset},
                                                       new double[] { 0, -1, 0 });
        final UnivariateFunction f = FunctionUtils.add(f1, f2);
        // A slightly less stringent tolerance would make the test pass
        // even with the previous implementation.
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    @Test
    public void testMath855() {
        final double minSin = 3 * Math.PI / 2;
        final double offset = 1e-8;
        final double delta = 1e-7;
        final UnivariateFunction f1 = new Sin();
        final UnivariateFunction f2 = new StepFunction(new double[] { minSin, minSin + offset, minSin + 5 * offset },
                                                       new double[] { 0, -1, 0 });
        final UnivariateFunction f = FunctionUtils.add(f1, f2);
        final UnivariateOptimizer optimizer = new BrentOptimizer(1e-8, 1e-100);
        final UnivariatePointValuePair result
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    /**
     *
     */
    @Test
    public void testSinZero() {
        DifferentiableUnivariateFunction f = new Sin();
        double result;

        NewtonSolver solver = new NewtonSolver();
        result = solver.solve(100, f, 3, 4);
        Assert.assertEquals(result, FastMath.PI, solver.getAbsoluteAccuracy());
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public class UnivariateMultiStartOptimizerTest {

    @Test
    public void testSinMin() {
        UnivariateFunction f = new Sin();
        UnivariateOptimizer underlying = new BrentOptimizer(1e-10, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(44428400075l);
        UnivariateMultiStartOptimizer<UnivariateFunction> optimizer =
            new UnivariateMultiStartOptimizer<UnivariateFunction>(underlying, 10, g);
        optimizer.optimize(300, f, GoalType.MINIMIZE, -100.0, 100.0);
        UnivariatePointValuePair[] optima = optimizer.getOptima();
        for (int i = 1; i < optima.length; ++i) {
            double d = (optima[i].getPoint() - optima[i-1].getPoint()) / (2 * FastMath.PI);
            Assert.assertTrue(FastMath.abs(d - FastMath.rint(d)) < 1.0e-8);
            Assert.assertEquals(-1.0, f.value(optima[i].getPoint()), 1.0e-10);
            Assert.assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1.0e-10);
        }
        Assert.assertTrue(optimizer.getEvaluations() > 200);
        Assert.assertTrue(optimizer.getEvaluations() < 300);
    }
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Related Classes of org.apache.commons.math3.analysis.function.Sin

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.FunctionUtilsTest
  • org.apache.commons.math3.analysis.integration.IterativeLegendreGaussIntegratorTest
  • org.apache.commons.math3.analysis.integration.MidPointIntegratorTest
  • org.apache.commons.math3.analysis.integration.RombergIntegratorTest
  • org.apache.commons.math3.analysis.integration.SimpsonIntegratorTest
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