Package org.apache.commons.math3.analysis.integration

Examples of org.apache.commons.math3.analysis.integration.RombergIntegrator


                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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      lastJ = j;
    }
    k[k.length - 1] = n - lastJ;

    // now verify probabilities by comparing to integral of pdf
    UnivariateIntegrator integrator = new RombergIntegrator();
    for (int i = 0; i < xs.length - 1; i++) {
      double delta = integrator.integrate(1000000, new UnivariateFunction() {
        @Override
        public double value(double v) {
          return dist.pdf(v);
        }
      }, xs[i], xs[i + 1]);
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                    public double value(final double x) {
                        return x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                return integrator.integrate(Integer.MAX_VALUE, f, x0, x4);
            }

            public double getNumericalVariance() {
                final double meanX = getNumericalMean();
                final UnivariateFunction f = new UnivariateFunction() {

                    public double value(final double x) {
                        return x * x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                final double meanX2 = integrator.integrate(Integer.MAX_VALUE,
                        f, x0, x4);
                return meanX2 - meanX * meanX;
            }

            public double getSupportLowerBound() {
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      final double freq = 1d / 3600d;
      final double min = 0;// j * .10d;
      final SineIntensity intensity = new SineIntensity(
          1d, freq, relHeight, min);

      final UnivariateIntegrator ri = new RombergIntegrator(16, 32);// new
      // TrapezoidIntegrator();//
      // new
      // SimpsonIntegrator();//
      // new
      // RombergIntegrator();

      final double val = ri.integrate(10000000, new IntensityFunctionWrapper(
          intensity), 0, lengthOfScenario);
      System.out
          .printf("%1d relative height: %1.3f%n", i, relHeight);

      final double newAmpl = orders / val;

      final SineIntensity finalIntensity = new SineIntensity(
          newAmpl, freq, relHeight, newAmpl * min);
      final double compensatedArea = ri.integrate(10000000,
          new IntensityFunctionWrapper(
              finalIntensity), 0, lengthOfScenario);
      // System.out.printf("compensated area: %1.3f%n", compensatedArea);

      final List<Double> sineTimes = FluentIterable
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                    public double value(final double x) {
                        return x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                return integrator.integrate(Integer.MAX_VALUE, f, x0, x4);
            }

            public double getNumericalVariance() {
                final double meanX = getNumericalMean();
                final UnivariateFunction f = new UnivariateFunction() {

                    public double value(final double x) {
                        return x * x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                final double meanX2 = integrator.integrate(Integer.MAX_VALUE,
                        f, x0, x4);
                return meanX2 - meanX * meanX;
            }

            public double getSupportLowerBound() {
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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