Package org.apache.commons.math3.optimization

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

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    @Test
    public void testAckley() {
        double[] startPoint = point(DIM,0.1);
        double[][] boundaries = null;
        PointValuePair expected =
            new PointValuePair(point(DIM,0.0),0.0);
        doTest(new Ackley(), startPoint, boundaries,
                GoalType.MINIMIZE,
                1e-7, 1e-5, 1000, expected);
    }
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    @Test
    public void testRastrigin() {
        double[] startPoint = point(DIM,1.0);

        double[][] boundaries = null;
        PointValuePair expected =
            new PointValuePair(point(DIM,0.0),0.0);
        doTest(new Rastrigin(), startPoint, boundaries,
                GoalType.MINIMIZE,
                1e-13, 1e-6, 1000, expected);
    }
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    @Test
    public void testConstrainedRosen() {
        double[] startPoint = point(DIM,0.1);

        double[][] boundaries = boundaries(DIM,-1,2);
        PointValuePair expected =
            new PointValuePair(point(DIM,1.0),0.0);
        doTest(new Rosen(), startPoint, boundaries,
                GoalType.MINIMIZE,
                1e-13, 1e-6, 2000, expected);
    }
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    //       makes it run for several hours before completing
    @Ignore @Test
    public void testConstrainedRosenWithMoreInterpolationPoints() {
        final double[] startPoint = point(DIM, 0.1);
        final double[][] boundaries = boundaries(DIM, -1, 2);
        final PointValuePair expected = new PointValuePair(point(DIM, 1.0), 0.0);

        // This should have been 78 because in the code the hard limit is
        // said to be
        //   ((DIM + 1) * (DIM + 2)) / 2 - (2 * DIM + 1)
        // i.e. 78 in this case, but the test fails for 48, 59, 62, 63, 64,
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//        PointValuePair result = optim.optimize(100000, func, goal, startPoint);
        final double[] lB = boundaries == null ? null : boundaries[0];
        final double[] uB = boundaries == null ? null : boundaries[1];
        final int numIterpolationPoints = 2 * dim + 1 + additionalInterpolationPoints;
        BOBYQAOptimizer optim = new BOBYQAOptimizer(numIterpolationPoints);
        PointValuePair result = boundaries == null ?
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint)) :
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),
                           new SimpleBounds(lB, uB));
//        System.out.println(func.getClass().getName() + " = "
//              + optim.getEvaluations() + " f(");
//        for (double x: result.getPoint())  System.out.print(x + " ");
//        System.out.println(") = " +  result.getValue());
        Assert.assertEquals(assertMsg, expected.getValue(), result.getValue(), fTol);
        for (int i = 0; i < dim; i++) {
            Assert.assertEquals(expected.getPoint()[i],
                                result.getPoint()[i], pointTol);
        }

//         System.out.println(func.getClass().getName() + " END"); // XXX
    }
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        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0 });
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);
    }
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                              new double[] { 4.0, 6.0, 1.0 });

        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0 });
        Assert.assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);

    }
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                { 0, 0, 0, 0, 0, 2 }
        }, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0, 0, 0, 0 });
        for (int i = 0; i < problem.target.length; ++i) {
            Assert.assertEquals(0.55 * i, optimum.getPoint()[i], 1.0e-10);
        }
    }
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                {  0, -1, 1 }
        }, new double[] { 1, 1, 1});
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0 });
        Assert.assertEquals(1.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(2.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPoint()[2], 1.0e-10);

    }
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        constraints.add(new LinearConstraint(new double[] { 1, 0 }, Relationship.LEQ, 2));
        constraints.add(new LinearConstraint(new double[] { 0, 1 }, Relationship.LEQ, 3));
        constraints.add(new LinearConstraint(new double[] { 1, 1 }, Relationship.EQ, 4));

        SimplexSolver solver = new SimplexSolver();
        PointValuePair solution = solver.optimize(f, constraints, GoalType.MAXIMIZE, false);
        Assert.assertEquals(2.0, solution.getPoint()[0], 0.0);
        Assert.assertEquals(2.0, solution.getPoint()[1], 0.0);
        Assert.assertEquals(57.0, solution.getValue(), 0.0);
    }
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Related Classes of org.apache.commons.math3.optimization.PointValuePair

  • 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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