Package org.apache.commons.math3.analysis.function

Examples of org.apache.commons.math3.analysis.function.Log10


                return false;
            }
            final int    n = FastMath.max(1, (int) FastMath.ceil(FastMath.abs(dt) / maxCheckInterval));
            final double h = dt / n;

            final UnivariateFunction f = new UnivariateFunction() {
                public double value(final double t) throws LocalMaxCountExceededException {
                    try {
                        interpolator.setInterpolatedTime(t);
                        return handler.g(t, getCompleteState(interpolator));
                    } catch (MaxCountExceededException mcee) {
                        throw new LocalMaxCountExceededException(mcee);
                    }
                }
            };

            double ta = t0;
            double ga = g0;
            for (int i = 0; i < n; ++i) {

                // evaluate handler value at the end of the substep
                final double tb = t0 + (i + 1) * h;
                interpolator.setInterpolatedTime(tb);
                final double gb = handler.g(tb, getCompleteState(interpolator));

                // check events occurrence
                if (g0Positive ^ (gb >= 0)) {
                    // there is a sign change: an event is expected during this step

                    // variation direction, with respect to the integration direction
                    increasing = gb >= ga;

                    // find the event time making sure we select a solution just at or past the exact root
                    final double root;
                    if (solver instanceof BracketedUnivariateSolver<?>) {
                        @SuppressWarnings("unchecked")
                        BracketedUnivariateSolver<UnivariateFunction> bracketing =
                                (BracketedUnivariateSolver<UnivariateFunction>) solver;
                        root = forward ?
                               bracketing.solve(maxIterationCount, f, ta, tb, AllowedSolution.RIGHT_SIDE) :
                               bracketing.solve(maxIterationCount, f, tb, ta, AllowedSolution.LEFT_SIDE);
                    } else {
                        final double baseRoot = forward ?
                                                solver.solve(maxIterationCount, f, ta, tb) :
                                                solver.solve(maxIterationCount, f, tb, ta);
                        final int remainingEval = maxIterationCount - solver.getEvaluations();
                        BracketedUnivariateSolver<UnivariateFunction> bracketing =
                                new PegasusSolver(solver.getRelativeAccuracy(), solver.getAbsoluteAccuracy());
                        root = forward ?
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, ta, tb, AllowedSolution.RIGHT_SIDE) :
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, tb, ta, AllowedSolution.LEFT_SIDE);
                    }

                    if ((!Double.isNaN(previousEventTime)) &&
                        (FastMath.abs(root - ta) <= convergence) &&
                        (FastMath.abs(root - previousEventTime) <= convergence)) {
                        // we have either found nothing or found (again ?) a past event,
                        // retry the substep excluding this value, and taking care to have the
                        // required sign in case the g function is noisy around its zero and
                        // crosses the axis several times
                        do {
                            ta = forward ? ta + convergence : ta - convergence;
                            ga = f.value(ta);
                        } while ((g0Positive ^ (ga >= 0)) && (forward ^ (ta >= tb)));
                        --i;
                    } else if (Double.isNaN(previousEventTime) ||
                               (FastMath.abs(previousEventTime - root) > convergence)) {
                        pendingEventTime = root;
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        TestUtils.assertEquals(f.getClass().getSimpleName(), expected, actual, 1E-16);
    }

    protected UnivariateFunction[] createFunctions() {
        return new UnivariateFunction[] {
            new Power(2.0), new Exp(), new Expm1(), new Log(), new Log10(),
            new Log1p(), new Cosh(), new Sinh(), new Tanh(), new Cos(),
            new Sin(), new Tan(), new Acos(), new Asin(), new Atan(),
            new Inverse(), new Abs(), new Sqrt(), new Cbrt(), new Ceil(),
            new Floor(), new Rint(), new Signum(), new Ulp()
        };
View Full Code Here

        TestUtils.assertEquals(f.getClass().getSimpleName(), expected, actual, 1E-16);
    }

    private UnivariateFunction[] createFunctions() {
        return new UnivariateFunction[] {
            new Power(2.0), new Exp(), new Expm1(), new Log(), new Log10(),
            new Log1p(), new Cosh(), new Sinh(), new Tanh(), new Cos(),
            new Sin(), new Tan(), new Acos(), new Asin(), new Atan(),
            new Inverse(), new Abs(), new Sqrt(), new Cbrt(), new Ceil(),
            new Floor(), new Rint(), new Signum(), new Ulp()
        };
View Full Code Here

        v_mapLogToSelf.mapToSelf(new Log());
        double[] result_mapLogToSelf = {0d,6.931471805599453e-01d, 1.098612288668110e+00d};
        assertClose("compare vectors" ,result_mapLogToSelf,v_mapLogToSelf.toArray(),normTolerance);

        //octave =  log10(v1)
        RealVector v_mapLog10 = v1.map(new Log10());
        double[] result_mapLog10 = {0d,3.010299956639812e-01d, 4.771212547196624e-01d};
        assertClose("compare vectors" ,result_mapLog10,v_mapLog10.toArray(),normTolerance);

        //octave =  log(v1)
        RealVector v_mapLog10ToSelf = v1.copy();
        v_mapLog10ToSelf.mapToSelf(new Log10());
        double[] result_mapLog10ToSelf = {0d,3.010299956639812e-01d, 4.771212547196624e-01d};
        assertClose("compare vectors" ,result_mapLog10ToSelf,v_mapLog10ToSelf.toArray(),normTolerance);

        //octave =  ???
        RealVector v_mapLog1p = v1.map(new Log1p());
View Full Code Here

        v_mapLogToSelf.mapToSelf(new Log());
        double[] result_mapLogToSelf = {0d,6.931471805599453e-01d, 1.098612288668110e+00d};
        assertClose("compare vectors" ,result_mapLogToSelf,v_mapLogToSelf.toArray(),normTolerance);

        //octave =  log10(v1)
        RealVector v_mapLog10 = v1.map(new Log10());
        double[] result_mapLog10 = {0d,3.010299956639812e-01d, 4.771212547196624e-01d};
        assertClose("compare vectors" ,result_mapLog10,v_mapLog10.toArray(),normTolerance);

        //octave =  log(v1)
        RealVector v_mapLog10ToSelf = v1.copy();
        v_mapLog10ToSelf.mapToSelf(new Log10());
        double[] result_mapLog10ToSelf = {0d,3.010299956639812e-01d, 4.771212547196624e-01d};
        assertClose("compare vectors" ,result_mapLog10ToSelf,v_mapLog10ToSelf.toArray(),normTolerance);

        //octave =  ???
        RealVector v_mapLog1p = v1.map(new Log1p());
View Full Code Here

                        final double baseRoot = forward ?
                                                solver.solve(maxIterationCount, f, ta, tb) :
                                                solver.solve(maxIterationCount, f, tb, ta);
                        final int remainingEval = maxIterationCount - solver.getEvaluations();
                        BracketedUnivariateSolver<UnivariateFunction> bracketing =
                                new PegasusSolver(solver.getRelativeAccuracy(), solver.getAbsoluteAccuracy());
                        root = forward ?
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, ta, tb, AllowedSolution.RIGHT_SIDE) :
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, tb, ta, AllowedSolution.LEFT_SIDE);
View Full Code Here

                // tests for termination and stringent tolerances
                if (FastMath.abs(actRed) <= TWO_EPS &&
                    preRed <= TWO_EPS &&
                    ratio <= 2.0) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_COST_RELATIVE_TOLERANCE,
                                                   costRelativeTolerance);
                } else if (delta <= TWO_EPS * xNorm) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_PARAMETERS_RELATIVE_TOLERANCE,
                                                   parRelativeTolerance);
                } else if (maxCosine <= TWO_EPS) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_ORTHOGONALITY_TOLERANCE,
                                                   orthoTolerance);
                }
            }
        }
    }
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                for (int j = k; j < nR; ++j) {
                    double aki = weightedJacobian[j][permutation[i]];
                    norm2 += aki * aki;
                }
                if (Double.isInfinite(norm2) || Double.isNaN(norm2)) {
                    throw new ConvergenceException(LocalizedFormats.UNABLE_TO_PERFORM_QR_DECOMPOSITION_ON_JACOBIAN,
                                                   nR, nC);
                }
                if (norm2 > ak2) {
                    nextColumn = i;
                    ak2        = norm2;
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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 ConvergenceException(LocalizedFormats.TOO_SMALL_COST_RELATIVE_TOLERANCE,
                                                   costRelativeTolerance);
                } else if (delta <= 2.2204e-16 * xNorm) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_PARAMETERS_RELATIVE_TOLERANCE,
                                                   parRelativeTolerance);
                } else if (maxCosine <= 2.2204e-16)  {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_ORTHOGONALITY_TOLERANCE,
                                                   orthoTolerance);
                }
            }
        }
    }
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                for (int j = k; j < nR; ++j) {
                    double aki = weightedJacobian[j][permutation[i]];
                    norm2 += aki * aki;
                }
                if (Double.isInfinite(norm2) || Double.isNaN(norm2)) {
                    throw new ConvergenceException(LocalizedFormats.UNABLE_TO_PERFORM_QR_DECOMPOSITION_ON_JACOBIAN,
                                                   nR, nC);
                }
                if (norm2 > ak2) {
                    nextColumn = i;
                    ak2        = norm2;
View Full Code Here

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