Package org.apache.commons.math3.optim

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

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    @Test(expected=MathUnsupportedOperationException.class)
    public void testConstraintsUnsupported() {
        createOptimizer().optimize(new MaxEval(100),
                                   new Target(new double[] { 2 }),
                                   new Weight(new double[] { 1 }),
                                   new InitialGuess(new double[] { 1, 2 }),
                                   new SimpleBounds(new double[] { -10, 0 },
                                                    new double[] { 20, 30 }));
    }
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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.assertTrue(FastMath.sqrt(optimizer.getTargetSize()) * optimizer.getRMS() > 0.6);

        optimizer.computeCovariances(optimum.getPoint(), 1.5e-14);
    }
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            optimizer.optimize(new MaxEval(maxCostEval),
                               problem,
                               problemJacobian,
                               new Target(new double[] { 0, 0, 0, 0, 0 }),
                               new Weight(new double[] { 1, 1, 1, 1, 1 }),
                               new InitialGuess(new double[] { 98.680, 47.345 }));
            Assert.assertTrue(!shouldFail);
        } catch (DimensionMismatchException ee) {
            Assert.assertTrue(shouldFail);
        } catch (TooManyEvaluationsException ee) {
            Assert.assertTrue(shouldFail);
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            = optimizer.optimize(new MaxEval(100),
                                 problem.getModelFunction(),
                                 problem.getModelFunctionJacobian(),
                                 new Target(dataPoints[1]),
                                 new Weight(weights),
                                 new InitialGuess(new double[] { 10, 900, 80, 27, 225 }));

        final double[] solution = optimum.getPoint();
        final double[] expectedSolution = { 10.4, 958.3, 131.4, 33.9, 205.0 };

        final double[][] covarMatrix = optimizer.computeCovariances(solution, 1e-14);
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        final PointVectorValuePair optimum = optimizer.optimize(new MaxEval(100),
                                                                circle.getModelFunction(),
                                                                circle.getModelFunctionJacobian(),
                                                                new Target(circle.target()),
                                                                new Weight(circle.weight()),
                                                                new InitialGuess(init));

        final double[] paramFound = optimum.getPoint();

        // Retrieve errors estimation.
        final double[] asymptoticStandardErrorFound = optimizer.computeSigma(paramFound, 1e-14);
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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(1.5, optimum.getPoint()[0], 1e-10);
        Assert.assertEquals(3.0, optimum.getValue()[0], 1e-10);
        PointVectorValuePair[] optima = optimizer.getOptima();
        Assert.assertEquals(10, optima.length);
        for (int i = 0; i < optima.length; i++) {
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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 }),
                           new SimpleBounds(new double[] { -1.0e-10 }, new double[] {  1.0e-10 }));
        PointVectorValuePair[] optima = optimizer.getOptima();
        // only the first start should have succeeded
        Assert.assertEquals(1, optima.length);
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        MultiStartMultivariateVectorOptimizer optimizer
            = new MultiStartMultivariateVectorOptimizer(underlyingOptimizer, 10, generator);
        optimizer.optimize(new MaxEval(100),
                           new Target(new double[] { 0 }),
                           new Weight(new double[] { 1 }),
                           new InitialGuess(new double[] { 0 }),
                           new ModelFunction(new MultivariateVectorFunction() {
                                   public double[] value(double[] point) {
                                       throw new TestException();
                                   }
                               }));
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            = optimizer.optimize(new MaxEval(maxEval),
                                 model.getModelFunction(),
                                 model.getModelFunctionJacobian(),
                                 new Target(target),
                                 new Weight(weights),
                                 new InitialGuess(initialGuess));
        // Extract the coefficients.
        return optimum.getPointRef();
    }
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        PointValuePair result = boundaries == null ?
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           SimpleBounds.unbounded(dim),
                           new InitialGuess(startPoint)) :
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new InitialGuess(startPoint),
                           new SimpleBounds(boundaries[0],
                                            boundaries[1]));
//        System.out.println(func.getClass().getName() + " = "
//              + optim.getEvaluations() + " f(");
//        for (double x: result.getPoint())  System.out.print(x + " ");
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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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