Package org.apache.commons.math3.optimization

Examples of org.apache.commons.math3.optimization.PointValuePair$DataTransferObject

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        Rosenbrock rosenbrock = new Rosenbrock();
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-3);
        optimizer.setSimplex(new NelderMeadSimplex(new double[][] {
                    { -1.2,  1 }, { 0.9, 1.2 } , {  3.5, -2.3 }
                }));
        PointValuePair optimum =
            optimizer.optimize(100, rosenbrock, GoalType.MINIMIZE, new double[] { -1.2, 1 });

        Assert.assertEquals(rosenbrock.getCount(), optimizer.getEvaluations());
        Assert.assertTrue(optimizer.getEvaluations() > 40);
        Assert.assertTrue(optimizer.getEvaluations() < 50);
        Assert.assertTrue(optimum.getValue() < 8e-4);
    }
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    public void testPowell() {

        Powell powell = new Powell();
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-3);
        optimizer.setSimplex(new NelderMeadSimplex(4));
        PointValuePair optimum =
            optimizer.optimize(200, powell, GoalType.MINIMIZE, new double[] { 3, -1, 0, 1 });
        Assert.assertEquals(powell.getCount(), optimizer.getEvaluations());
        Assert.assertTrue(optimizer.getEvaluations() > 110);
        Assert.assertTrue(optimizer.getEvaluations() < 130);
        Assert.assertTrue(optimum.getValue() < 2e-3);
    }
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                    return factors.operate(variables);
                }
            }, new double[] { 2.0, -3.0 });
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
        optimizer.setSimplex(new NelderMeadSimplex(2));
        PointValuePair optimum =
            optimizer.optimize(200, ls, GoalType.MINIMIZE, new double[] { 10, 10 });
        Assert.assertEquals( 2, optimum.getPointRef()[0], 3e-5);
        Assert.assertEquals(-3, optimum.getPointRef()[1], 4e-4);
        Assert.assertTrue(optimizer.getEvaluations() > 60);
        Assert.assertTrue(optimizer.getEvaluations() < 80);
        Assert.assertTrue(optimum.getValue() < 1.0e-6);
    }
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                    return factors.operate(variables);
                }
            }, new double[] { 2, -3 }, new double[] { 10, 0.1 });
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
        optimizer.setSimplex(new NelderMeadSimplex(2));
        PointValuePair optimum =
            optimizer.optimize(200, ls, GoalType.MINIMIZE, new double[] { 10, 10 });
        Assert.assertEquals( 2, optimum.getPointRef()[0], 5e-5);
        Assert.assertEquals(-3, optimum.getPointRef()[1], 8e-4);
        Assert.assertTrue(optimizer.getEvaluations() > 60);
        Assert.assertTrue(optimizer.getEvaluations() < 80);
        Assert.assertTrue(optimum.getValue() < 1e-6);
    }
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            }, new double[] { 2, -3 }, new Array2DRowRealMatrix(new double [][] {
                    { 1, 1.2 }, { 1.2, 2 }
                }));
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
        optimizer.setSimplex(new NelderMeadSimplex(2));
        PointValuePair optimum =
            optimizer.optimize(200, ls, GoalType.MINIMIZE, new double[] { 10, 10 });
        Assert.assertEquals( 2, optimum.getPointRef()[0], 2e-3);
        Assert.assertEquals(-3, optimum.getPointRef()[1], 8e-4);
        Assert.assertTrue(optimizer.getEvaluations() > 60);
        Assert.assertTrue(optimizer.getEvaluations() < 80);
        Assert.assertTrue(optimum.getValue() < 1e-6);
    }
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    @Test(expected = NumberIsTooLargeException.class)
    public void testInitOutofbounds1() {
        double[] startPoint = point(DIM,3);
        double[] insigma = point(DIM, 0.3);
        double[][] boundaries = boundaries(DIM,-1,2);
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, insigma, boundaries,
                GoalType.MINIMIZE, LAMBDA, true, 0, 1e-13,
                1e-13, 1e-6, 100000, expected);
    }
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    @Test(expected = NumberIsTooSmallException.class)
    public void testInitOutofbounds2() {
        double[] startPoint = point(DIM, -2);
        double[] insigma = point(DIM, 0.3);
        double[][] boundaries = boundaries(DIM,-1,2);
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, insigma, boundaries,
                GoalType.MINIMIZE, LAMBDA, true, 0, 1e-13,
                1e-13, 1e-6, 100000, expected);
    }
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    @Test(expected = DimensionMismatchException.class)
    public void testBoundariesDimensionMismatch() {
        double[] startPoint = point(DIM,0.5);
        double[] insigma = point(DIM, 0.3);
        double[][] boundaries = boundaries(DIM+1,-1,2);
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, insigma, boundaries,
                GoalType.MINIMIZE, LAMBDA, true, 0, 1e-13,
                1e-13, 1e-6, 100000, expected);
    }
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    @Test(expected = NotPositiveException.class)
    public void testInputSigmaNegative() {
        double[] startPoint = point(DIM,0.5);
        double[] insigma = point(DIM,-0.5);
        double[][] boundaries = null;
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, insigma, boundaries,
                GoalType.MINIMIZE, LAMBDA, true, 0, 1e-13,
                1e-13, 1e-6, 100000, expected);
    }
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    @Test(expected = OutOfRangeException.class)
    public void testInputSigmaOutOfRange() {
        double[] startPoint = point(DIM,0.5);
        double[] insigma = point(DIM, 1.1);
        double[][] boundaries = boundaries(DIM,-0.5,0.5);
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, insigma, boundaries,
                GoalType.MINIMIZE, LAMBDA, true, 0, 1e-13,
                1e-13, 1e-6, 100000, expected);
    }
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Related Classes of org.apache.commons.math3.optimization.PointValuePair$DataTransferObject

  • 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.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
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