Package org.apache.commons.math3.optim

Examples of org.apache.commons.math3.optim.InitialGuess

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        final double[] result = optimizer.optimize(new MaxEval(10000),
                                                   new ObjectiveFunction(fitnessFunction),
                                                   GoalType.MINIMIZE,
                                                   new CMAESOptimizer.PopulationSize(5),
                                                   new CMAESOptimizer.Sigma(sigma),
                                                   new InitialGuess(start),
                                                   new SimpleBounds(lower, upper)).getPoint();
        Assert.assertTrue("Out of bounds (" + result[0] + " > " + upper[0] + ")",
                          result[0] <= upper[0]);
    }
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                                                   new ObjectiveFunction(fitnessFunction),
                                                   GoalType.MINIMIZE,
                                                   SimpleBounds.unbounded(1),
                                                   new CMAESOptimizer.PopulationSize(5),
                                                   new CMAESOptimizer.Sigma(new double[] { 1e-1 }),
                                                   new InitialGuess(start));
        final double resNoBound = result.getPoint()[0];

        // Optimum is near the lower bound.
        final double[] lower = { -20 };
        final double[] upper = { 5e16 };
        final double[] sigma = { 10 };
        result = optimizer.optimize(new MaxEval(100000),
                                    new ObjectiveFunction(fitnessFunction),
                                    GoalType.MINIMIZE,
                                    new CMAESOptimizer.PopulationSize(5),
                                    new CMAESOptimizer.Sigma(sigma),
                                    new InitialGuess(start),
                                    new SimpleBounds(lower, upper));
        final double resNearLo = result.getPoint()[0];

        // Optimum is near the upper bound.
        lower[0] = -5e16;
        upper[0] = 20;
        result = optimizer.optimize(new MaxEval(100000),
                                    new ObjectiveFunction(fitnessFunction),
                                    GoalType.MINIMIZE,
                                    new CMAESOptimizer.PopulationSize(5),
                                    new CMAESOptimizer.Sigma(sigma),
                                    new InitialGuess(start),
                                    new SimpleBounds(lower, upper));
        final double resNearHi = result.getPoint()[0];

        // System.out.println("resNoBound=" + resNoBound +
        //                    " resNearLo=" + resNearLo +
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                                                  0, new MersenneTwister(), false, null);
        PointValuePair result = boundaries == null ?
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new InitialGuess(startPoint),
                           SimpleBounds.unbounded(dim),
                           new CMAESOptimizer.Sigma(inSigma),
                           new CMAESOptimizer.PopulationSize(lambda)) :
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new SimpleBounds(boundaries[0],
                                            boundaries[1]),
                           new InitialGuess(startPoint),
                           new CMAESOptimizer.Sigma(inSigma),
                           new CMAESOptimizer.PopulationSize(lambda));

        // System.out.println("sol=" + Arrays.toString(result.getPoint()));
        Assert.assertEquals(expected.getValue(), result.getValue(), fTol);
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    @Test
    public void testGetIterations() {
        AbstractLeastSquaresOptimizer optim = createOptimizer();
        optim.optimize(new MaxEval(100), new Target(new double[] { 1 }),
                       new Weight(new double[] { 1 }),
                       new InitialGuess(new double[] { 3 }),
                       new ModelFunction(new MultivariateVectorFunction() {
                               public double[] value(double[] point) {
                                   return new double[] {
                                       FastMath.pow(point[0], 4)
                                   };
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            optimizer.optimize(new MaxEval(100),
                               problem.getModelFunction(),
                               problem.getModelFunctionJacobian(),
                               problem.getTarget(),
                               new Weight(new double[] { 1 }),
                               new InitialGuess(new double[] { 0 }));
        Assert.assertEquals(0, optimizer.getRMS(), 1e-10);
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1e-10);
        Assert.assertEquals(3.0, optimum.getValue()[0], 1e-10);
    }
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            optimizer.optimize(new MaxEval(100),
                               problem.getModelFunction(),
                               problem.getModelFunctionJacobian(),
                               problem.getTarget(),
                               new Weight(new double[] { 1, 1, 1 }),
                               new InitialGuess(new double[] { 0, 0 }));
        Assert.assertEquals(0, optimizer.getRMS(), 1e-10);
        Assert.assertEquals(7, optimum.getPoint()[0], 1e-10);
        Assert.assertEquals(3, optimum.getPoint()[1], 1e-10);
        Assert.assertEquals(4, optimum.getValue()[0], 1e-10);
        Assert.assertEquals(6, optimum.getValue()[1], 1e-10);
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            optimizer.optimize(new MaxEval(100),
                               problem.getModelFunction(),
                               problem.getModelFunctionJacobian(),
                               problem.getTarget(),
                               new Weight(new double[] { 1, 1, 1, 1, 1, 1 }),
                               new InitialGuess(new double[] { 0, 0, 0, 0, 0, 0 }));
        Assert.assertEquals(0, optimizer.getRMS(), 1e-10);
        for (int i = 0; i < problem.target.length; ++i) {
            Assert.assertEquals(0.55 * i, optimum.getPoint()[i], 1e-10);
        }
    }
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            optimizer.optimize(new MaxEval(100),
                               problem.getModelFunction(),
                               problem.getModelFunctionJacobian(),
                               problem.getTarget(),
                               new Weight(new double[] { 1, 1, 1 }),
                               new InitialGuess(new double[] { 0, 0, 0 }));
        Assert.assertEquals(0, optimizer.getRMS(), 1e-10);
        Assert.assertEquals(1, optimum.getPoint()[0], 1e-10);
        Assert.assertEquals(2, optimum.getPoint()[1], 1e-10);
        Assert.assertEquals(3, optimum.getPoint()[2], 1e-10);
    }
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            optimizer.optimize(new MaxEval(100),
                               problem.getModelFunction(),
                               problem.getModelFunctionJacobian(),
                               problem.getTarget(),
                               new Weight(new double[] { 1, 1, 1, 1, 1, 1 }),
                               new InitialGuess(new double[] { 0, 0, 0, 0, 0, 0 }));
        Assert.assertEquals(0, optimizer.getRMS(), 1e-10);
        Assert.assertEquals(3, optimum.getPoint()[0], 1e-10);
        Assert.assertEquals(4, optimum.getPoint()[1], 1e-10);
        Assert.assertEquals(-1, optimum.getPoint()[2], 1e-10);
        Assert.assertEquals(-2, optimum.getPoint()[3], 1e-10);
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        optimizer.optimize(new MaxEval(100),
                           problem.getModelFunction(),
                           problem.getModelFunctionJacobian(),
                           problem.getTarget(),
                           new Weight(new double[] { 1, 1, 1 }),
                           new InitialGuess(new double[] { 0, 0, 0 }));
    }
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Related Classes of org.apache.commons.math3.optim.InitialGuess

  • 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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