Package org.apache.commons.math.optimization

Examples of org.apache.commons.math.optimization.RealPointValuePair

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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
        assertEquals(1.0, optimum.getPoint()[1], 1.0e-8);

    }
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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        assertTrue(optimum.getValue() > 0.1);

    }
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        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-30, 1.0e-30));
        BrentSolver solver = new BrentSolver();
        solver.setAbsoluteAccuracy(1.0e-13);
        solver.setRelativeAccuracy(1.0e-15);
        optimizer.setLineSearchSolver(solver);
        RealPointValuePair optimum =
            optimizer.optimize(circle, GoalType.MINIMIZE, new double[] { 98.680, 47.345 });
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        assertEquals(69.960161753, circle.getRadius(center), 1.0e-8);
        assertEquals(96.075902096, center.x, 1.0e-8);
        assertEquals(48.135167894, center.y, 1.0e-8);
    }
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    if(method.equals("Nelder-Mead")) {

      NelderMead optimizer = new NelderMead();
      try {
        RealPointValuePair res = optimizer.optimize(g, GoalType.MINIMIZE, par.toDoubleArray());
        ListVector.Builder result = new ListVector.Builder();
        result.add(new DoubleArrayVector(res.getPoint()));
        result.add(new DoubleArrayVector(res.getValue()));
        result.add(new IntArrayVector(IntVector.NA, IntVector.NA));
        result.add(new IntArrayVector(0));
        result.add(Null.INSTANCE);
        return result.build();
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            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 0 });
        assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        assertEquals(0.0, optimum.getValue(), 1.0e-10);
    }
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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 0, 0 });
        assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
        assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
        assertEquals(0.0, optimum.getValue(), 1.0e-10);

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

    }
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                return d;
            }
        });
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-13, 1.0e-13));

        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 0, 0, 0, 0, 0, 0 });
        assertEquals( 3.0, optimum.getPoint()[0], 1.0e-10);
        assertEquals( 4.0, optimum.getPoint()[1], 1.0e-10);
        assertEquals(-1.0, optimum.getPoint()[2], 1.0e-10);
        assertEquals(-2.0, optimum.getPoint()[3], 1.0e-10);
        assertEquals( 1.0 + epsilon, optimum.getPoint()[4], 1.0e-10);
        assertEquals( 1.0 - epsilon, optimum.getPoint()[5], 1.0e-10);

    }
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        }, new double[] { 1, 1, 1 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
                optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 0, 0, 0 });
        assertTrue(optimum.getValue() > 0.5);
    }
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Related Classes of org.apache.commons.math.optimization.RealPointValuePair

  • com.opengamma.analytics.math.util.wrapper.CommonsMathWrapperTest
  • org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  • org.apache.commons.math.optimization.direct.MultiDirectional
  • org.apache.commons.math.optimization.direct.MultiDirectionalTest
  • org.apache.commons.math.optimization.direct.NelderMead
  • org.apache.commons.math.optimization.direct.NelderMeadTest
  • org.apache.commons.math.optimization.direct.PowellOptimizer
  • org.apache.commons.math.optimization.direct.PowellOptimizerTest
  • org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  • org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizerTest
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