Package org.apache.commons.math.optimization

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

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                }

                // tests for termination and stringent tolerances
                // (2.2204e-16 is the machine epsilon for IEEE754)
                if ((Math.abs(actRed) <= 2.2204e-16) && (preRed <= 2.2204e-16) && (ratio <= 2.0)) {
                    throw new OptimizationException("cost relative tolerance is too small ({0})," +
                            " no further reduction in the" +
                            " sum of squares is possible",
                            costRelativeTolerance);
                } else if (delta <= 2.2204e-16 * xNorm) {
                    throw new OptimizationException("parameters relative tolerance is too small" +
                            " ({0}), no further improvement in" +
                            " the approximate solution is possible",
                            parRelativeTolerance);
                } else if (maxCosine <= 2.2204e-16)  {
                    throw new OptimizationException("orthogonality tolerance is too small ({0})," +
                            " solution is orthogonal to the jacobian",
                            orthoTolerance);
                }

            }
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                for (int j = k; j < jacobian.length; ++j) {
                    double aki = jacobian[j][permutation[i]];
                    norm2 += aki * aki;
                }
                if (Double.isInfinite(norm2) || Double.isNaN(norm2)) {
                    throw new OptimizationException(
                            "unable to perform Q.R decomposition on the {0}x{1} jacobian matrix",
                            rows, cols);
                }
                if (norm2 > ak2) {
                    nextColumn = i;
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     * of iterations is exceeded
     */
    protected void incrementIterationsCounter()
        throws OptimizationException {
        if (++iterations > maxIterations) {
            throw new OptimizationException(new MaxIterationsExceededException(maxIterations));
        }
    }
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            // compute the covariances matrix
            RealMatrix inverse =
                new LUDecompositionImpl(MatrixUtils.createRealMatrix(jTj)).getSolver().getInverse();
            return inverse.getData();
        } catch (InvalidMatrixException ime) {
            throw new OptimizationException("unable to compute covariances: singular problem");
        }

    }
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     * lesser or equal to number of parameters)
     */
    public double[] guessParametersErrors()
        throws FunctionEvaluationException, OptimizationException {
        if (rows <= cols) {
            throw new OptimizationException(
                    "no degrees of freedom ({0} measurements, {1} parameters)",
                    rows, cols);
        }
        double[] errors = new double[cols];
        final double c = Math.sqrt(getChiSquare() / (rows - cols));
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     * of iterations is exceeded
     */
    protected void incrementIterationsCounter()
        throws OptimizationException {
        if (++iterations > maxIterations) {
            throw new OptimizationException(new MaxIterationsExceededException(maxIterations));
        }
    }
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     * of iterations is exceeded
     */
    protected void incrementIterationsCounter()
        throws OptimizationException {
        if (++iterations > maxIterations) {
            throw new OptimizationException(new MaxIterationsExceededException(maxIterations));
        }
    }
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                                         bracket.getLo(),
                                         bracket.getHi(),
                                         bracket.getMid());
                valueAtOptimum = optim.getFunctionValue();
            } catch (MaxIterationsExceededException e) {
                throw new OptimizationException(e);
            }
        }
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     * of iterations is exceeded
     */
    protected void incrementIterationsCounter()
        throws OptimizationException {
        if (++iterations > maxIterations) {
            throw new OptimizationException(new MaxIterationsExceededException(maxIterations));
        }
    }
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                   }
                }
                // tests for termination and stringent tolerances
                // (2.2204e-16 is the machine epsilon for IEEE754)
                if ((FastMath.abs(actRed) <= 2.2204e-16) && (preRed <= 2.2204e-16) && (ratio <= 2.0)) {
                    throw new OptimizationException(LocalizedFormats.TOO_SMALL_COST_RELATIVE_TOLERANCE,
                            costRelativeTolerance);
                } else if (delta <= 2.2204e-16 * xNorm) {
                    throw new OptimizationException(LocalizedFormats.TOO_SMALL_PARAMETERS_RELATIVE_TOLERANCE,
                            parRelativeTolerance);
                } else if (maxCosine <= 2.2204e-16)  {
                    throw new OptimizationException(LocalizedFormats.TOO_SMALL_ORTHOGONALITY_TOLERANCE,
                            orthoTolerance);
                }

            }

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  • org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  • org.apache.commons.math.optimization.fitting.HarmonicFitter
  • org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  • org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  • org.apache.commons.math.optimization.general.GaussNewtonOptimizer
  • org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  • org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
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