Examples of org.jquantlib.math.integrals.GaussKronrodAdaptive

org.jquantlib.math.integrals.GaussKronrodAdaptive
Integral of a 1-dimensional function using the Gauss-Kronrod methods
This class provide a non-adaptive integration procedure which uses fixed Gauss-Kronrod abscissae to sample the integrand at a maximum of 87 points. It is provided for fast integration of smooth functions.
This function applies the Gauss-Kronrod 10-point, 21-point, 43-point and 87-point integration rules in succession until an estimate of the integral of f over (a, b) is achieved within the desired absolute and relative error limits, epsabs and epsrel. The function returns the final approximation, result, an estimate of the absolute error, abserr and the number of function evaluations used, neval. The Gauss-Kronrod rules are designed in such a way that each rule uses all the results of its predecessors, in order to minimize the total number of function evaluations. @author Ueli Hofstetter


    @Test
    public void testGaussKronrodAdaptive() {
        QL.info("Testing adaptive Gauss-Kronrod integration...");
        final int maxEvaluations = 1000;
        testSeveral(new GaussKronrodAdaptive(tolerance, maxEvaluations));
    }

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          QL.require(!x.empty() , "can not handle given x here"); // QA:[RG]::verified // TODO: message


          double tmp=0.0;
          final Var_Helper helper = new Var_Helper(this, i, j);


          final GaussKronrodAdaptive integrator = new GaussKronrodAdaptive(1e-10, 10000);
          for (int k=0; k<64; ++k) {
            tmp+=integrator.op(helper, k*t/64., (k+1)*t/64.);
        }
          return tmp;
      }

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        final Matrix tmp = new Matrix(size_, size_);
        for (int i = 0; i < size_; ++i) {
            for (int j = 0; j <= i; ++j) {
                final Var_Helper helper = new Var_Helper(this, i, j);
                final GaussKronrodAdaptive integrator = new GaussKronrodAdaptive(1e-10, 10000);
                for(int k = 0; k<64; ++k) {
                    tmp.set(i, j, tmp.get(i, j)+integrator.op(helper, k*t/64.0,(k+1)*t/64.0));
                }
                tmp.set(j,i, tmp.get(i, j));
            }
        }

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        final Matrix tmp = new Matrix(size_, size_);
        for (int i = 0; i < size_; ++i) {
            for (int j = 0; j <= i; ++j) {
                final Var_Helper helper = new Var_Helper(this, i, j);
                final GaussKronrodAdaptive integrator = new GaussKronrodAdaptive(1e-10, 10000);
                for(int k = 0; k<64; ++k) {
                    tmp.set(i, j, tmp.get(i, j)+integrator.op(helper, k*t/64.0,(k+1)*t/64.0));
                }
                tmp.set(j,i, tmp.get(i, j));
            }
        }

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          QL.require(!x.empty() , "can not handle given x here"); // TODO: message


          double tmp=0.0;
          final Var_Helper helper = new Var_Helper(this, i, j);


          final GaussKronrodAdaptive integrator = new GaussKronrodAdaptive(1e-10, 10000);
          for (int k=0; k<64; ++k) {
            tmp+=integrator.op(helper, k*t/64., (k+1)*t/64.);
        }
          return tmp;
      }

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    @Test
    public void testGaussKronrodAdaptive() {
        QL.info("Testing adaptive Gauss-Kronrod integration...");
        final int maxEvaluations = 1000;
        testSeveral(new GaussKronrodAdaptive(tolerance, maxEvaluations));
    }

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org.jquantlib.legacy.libormarkets.LfmCovarianceProxy

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org.jquantlib.testsuite.math.integrals.IntegralsTest

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