Java Code Examples for org.apache.commons.math.exception.util.LocalizedFormats#NO_CONVERGENCE_WITH_ANY_START_POINT

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Example 1
Source File: Cardumen_0052_s.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 2
Source File: Cardumen_0052_t.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = i == 0 ? max : min - (0.5 * (bound1 - max));
            optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 3
Source File: Cardumen_00119_t.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal, org.apache.commons.math.util.FastMath.max(min, min), org.apache.commons.math.util.FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 4
Source File: Cardumen_00119_s.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 5
Source File: Math_62_MultiStartUnivariateRealOptimizer_s.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 6
Source File: Math_62_MultiStartUnivariateRealOptimizer_t.java    From coming with MIT License 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                             final double min, final double max,
                                             final double startValue)
    throws FunctionEvaluationException {
    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double s = (i == 0) ? startValue : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal, min, max, s);
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 7
Source File: MultiStartUnivariateRealOptimizer.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f,
                                             final GoalType goal,
                                             final double min, final double max)
    throws FunctionEvaluationException {

    optima = new UnivariateRealPointValuePair[starts];
    totalEvaluations = 0;

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {
        try {
            final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
            final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
            optima[i] = optimizer.optimize(f, goal,
                                           FastMath.min(bound1, bound2),
                                           FastMath.max(bound1, bound2));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException ce) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the point with the best objective function value.
    return optima[0];
}
Example 8
Source File: BaseMultiStartMultivariateRealOptimizer.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * @param f Function to optimize.
 * @param goal Goal type ({@link GoalType#MINIMIZE} or
 * {@link GoalType#MAXIMIZE}).
 * @param startPoint Start point.
 */
public RealPointValuePair optimize(final FUNC f,
                                   final GoalType goal,
                                   double[] startPoint)
    throws FunctionEvaluationException {
    optima = new RealPointValuePair[starts];

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {

        try {
            optima[i] = optimizer.optimize(f, goal,
                                           (i == 0 ? startPoint :
                                            generator.nextVector()));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException oe) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(goal);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the found point given the best objective function value.
    return optima[0];
}
Example 9
Source File: BaseMultiStartMultivariateVectorialOptimizer.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/**
 * {@inheritDoc}
 */
public VectorialPointValuePair optimize(final FUNC f,
                                        double[] target, double[] weights,
                                        double[] startPoint)
    throws FunctionEvaluationException {

    optima = new VectorialPointValuePair[starts];

    // Multi-start loop.
    for (int i = 0; i < starts; ++i) {

        try {
            optima[i] = optimizer.optimize(f, target, weights,
                                           (i == 0 ? startPoint :
                                            generator.nextVector()));
        } catch (FunctionEvaluationException fee) {
            optima[i] = null;
        } catch (ConvergenceException oe) {
            optima[i] = null;
        }

        final int usedEvaluations = optimizer.getEvaluations();
        optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
        totalEvaluations += usedEvaluations;
    }

    sortPairs(target, weights);

    if (optima[0] == null) {
        throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                       starts);
    }

    // Return the found point given the best objective function value.
    return optima[0];
}
Example 10
Source File: 1_MultiStartUnivariateRealOptimizer.java    From SimFix with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
    public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
                                                 final double min, final double max,
                                                 final double startValue)
        throws FunctionEvaluationException {
        optima = new UnivariateRealPointValuePair[starts];
        totalEvaluations = 0;

        // Multi-start loop.
        for (int i = 0; i < starts; ++i) {
            try {
// start of generated patch
 final double bound1=min;
 final double bound2=min*(FastMath.abs(min)+FastMath.abs(bound1));
optima[i]=optimizer.optimize(f,goal,FastMath.min(bound1,bound2),FastMath.max(bound1,bound2));
// end of generated patch
/* start of original code
                final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min);
                final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min);
                optima[i] = optimizer.optimize(f, goal, FastMath.min(bound1, bound2), FastMath.max(bound1, bound2));
 end of original code*/
            } catch (FunctionEvaluationException fee) {
                optima[i] = null;
            } catch (ConvergenceException ce) {
                optima[i] = null;
            }

            final int usedEvaluations = optimizer.getEvaluations();
            optimizer.setMaxEvaluations(optimizer.getMaxEvaluations() - usedEvaluations);
            totalEvaluations += usedEvaluations;
        }

        sortPairs(goal);

        if (optima[0] == null) {
            throw new ConvergenceException(LocalizedFormats.NO_CONVERGENCE_WITH_ANY_START_POINT,
                                           starts);
        }

        // Return the point with the best objective function value.
        return optima[0];
    }