Examples of org.apache.commons.math3.analysis.UnivariateFunction

Package org.apache.commons.math3.analysis

Examples of org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.analysis.UnivariateFunction
x value that caused the problem. private final double x; public LocalException(double x) { this.x = x; } public double getX() { return x; } } private static class MyFunction implements UnivariateFunction { public double value(double x) { double y = hugeFormula(x); if (somethingBadHappens) { throw new LocalException(x); } return y; } } public void compute() { try { solver.solve(maxEval, new MyFunction(a, b, c), min, max); } catch (LocalException le) { // Retrieve the x value. } } As shown, the exception is local to the user's code and it is guaranteed that Apache Commons Math will not catch it.

        final double maximumX = 3;
        final int numberOfSamples = 100;
        final double interpolationTolerance = 0.37;
        final double maxTolerance = 3.8;


        UnivariateFunction f = new UnivariateFunction()
        {
            public double value( double x )
            {
                return ( 3 * x * x * x ) - ( 0.5 * x * x ) + ( 1 * x ) - 1;
            }

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        {
            xValues[i] = minimumX + delta * (double) i;
            yValues[i] = f.value( xValues[i] );
        }


        UnivariateFunction interpolation = new AkimaSplineInterpolator().interpolate( xValues, yValues );


        for ( int i = 0; i < numberOfElements; i++ )
        {
            currentX = xValues[i];
            expected = f.value( currentX );
            actual = interpolation.value( currentX );
            assertTrue( Precision.equals( expected, actual ) );
        }


        final RandomGenerator rng = new Well19937c( 1234567L ); // "tol" depends on the seed.
        final UniformRealDistribution distX =
            new UniformRealDistribution( rng, xValues[0], xValues[xValues.length - 1] );


        double sumError = 0;
        for ( int i = 0; i < numberOfSamples; i++ )
        {
            currentX = distX.sample();
            expected = f.value( currentX );
            actual = interpolation.value( currentX );
            sumError += FastMath.abs( actual - expected );
            assertEquals( expected, actual, maxTolerance );
        }


        assertEquals( 0.0, ( sumError / (double) numberOfSamples ), tolerance );

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        Assert.assertTrue(sin.value(result[1]) > 0);
    }


    @Test(expected=NoBracketingException.class)
    public void testBracketLinear(){
        UnivariateSolverUtils.bracket(new UnivariateFunction() {
            public double value(double x) {
                return 1 - x;
            }
        }, 1000, Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 1.0, 1.0, 100);
    }

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        }, 1000, Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 1.0, 1.0, 100);
    }


    @Test
    public void testBracketExponential(){
        double[] result = UnivariateSolverUtils.bracket(new UnivariateFunction() {
            public double value(double x) {
                return 1 - x;
            }
        }, 1000, Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, 1.0, 2.0, 10);
        Assert.assertTrue(result[0] <= 1);

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        UnivariateSolverUtils.bracket(sin, 1.5, 0, 2.0, 0);
    }


    @Test
    public void testMisc() {
        UnivariateFunction f = new QuinticFunction();
        double result;
        // Static solve method
        result = UnivariateSolverUtils.solve(f, -0.2, 0.2);
        Assert.assertEquals(result, 0, 1E-8);
        result = UnivariateSolverUtils.solve(f, -0.1, 0.3);

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            public double value(double x) {
                return q.value(x);
            }


            public UnivariateFunction derivative() {
                return new UnivariateFunction() {
                    public double value(double x) {
                        return q.value(new DerivativeStructure(1, 1, 0, x)).getPartialDerivative(1);
                    }
                };
            }

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/**
 */
public final class BisectionSolverTest {
    @Test
    public void testSinZero() {
        UnivariateFunction f = new Sin();
        double result;


        BisectionSolver solver = new BisectionSolver();
        result = solver.solve(100, f, 3, 4);
        Assert.assertEquals(result, FastMath.PI, solver.getAbsoluteAccuracy());

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        Assert.assertEquals(result, FastMath.PI, solver.getAbsoluteAccuracy());
    }


    @Test
    public void testQuinticZero() {
        UnivariateFunction f = new QuinticFunction();
        double result;


        BisectionSolver solver = new BisectionSolver();
        result = solver.solve(100, f, -0.2, 0.2);
        Assert.assertEquals(result, 0, solver.getAbsoluteAccuracy());

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        Assert.assertTrue(solver.getEvaluations() > 0);
    }


    @Test
    public void testMath369() {
        UnivariateFunction f = new Sin();
        BisectionSolver solver = new BisectionSolver();
        Assert.assertEquals(FastMath.PI, solver.solve(100, f, 3.0, 3.2, 3.1), solver.getAbsoluteAccuracy());
    }

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


        min = 3.0; max = 4.0; expected = FastMath.PI;
        tolerance = FastMath.max(solver.getAbsoluteAccuracy(),

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Related Classes of org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.analysis.differentiation.FiniteDifferencesDifferentiatorTest

org.apache.commons.math3.analysis.function.GaussianTest

org.apache.commons.math3.analysis.function.HarmonicOscillatorTest

org.apache.commons.math3.analysis.function.LogisticTest

org.apache.commons.math3.analysis.function.LogitTest

org.apache.commons.math3.analysis.function.SigmoidTest

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

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.function.SincTest

org.apache.commons.math3.analysis.function.SqrtTest

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