Example usage for org.apache.commons.math.analysis.solvers BrentSolver BrentSolver

Introduction

In this page you can find the example usage for org.apache.commons.math.analysis.solvers BrentSolver BrentSolver.

Prototype

public BrentSolver(int maximumIterations, double absoluteAccuracy) 

Source Link

Document

Contstruct a solver with the given maximum iterations and absolute accuracy.

Usage

From source file:org.renjin.primitives.optimize.Roots.java

/**
 * Searches the interval from lower to upper for a root (i.e., zero) of the function f with
 * respect to its first argument.//from  w w w. j  a  v a 2  s .c  o m
 *
 * <p>
 * This internal primitive is used by the uniroot() function in the stats package.
 *
 * <p>
 * This implementation wraps the Commons Math {@link BrentSolver}; there are however
 *
 */
public static DoubleVector zeroin2(@Current Context context, @Current Environment rho, Function fn,
        double lower, double upper, double fLower, double fUpper, double tol, int maximumIterations) {

    BrentSolver solver = new BrentSolver(maximumIterations, tol);

    double root;
    int iterations;
    double estimatedPrecision = DoubleVector.EPSILON; // not exposed by commons math impl

    try {
        root = solver.solve(new UnivariateRealClosure(context, rho, fn), lower, upper);
        iterations = 1; // the Commons math impl doesn't expose this
    } catch (MaxIterationsExceededException e) {
        root = DoubleVector.NA;
        iterations = -1;
    } catch (FunctionEvaluationException e) {
        throw new EvalException(e);
    }

    return new DoubleArrayVector(root, iterations, estimatedPrecision);
}

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From source file:org.renjin.stats.internals.optimize.Roots.java

/**
 * Searches the interval from lower to upper for a root (i.e., zero) of the function f with
 * respect to its first argument./*from ww w . j  ava2 s. c o m*/
 *
 * <p>
 * This internal primitive is used by the uniroot() function in the stats package.
 *
 * <p>
 * This implementation wraps the Commons Math {@link BrentSolver}; there are however
 *
 */
@Internal
public static DoubleVector zeroin2(@Current Context context, @Current Environment rho, Function fn,
        double lower, double upper, double fLower, double fUpper, double tol, int maximumIterations) {

    BrentSolver solver = new BrentSolver(maximumIterations, tol);

    double root;
    int iterations;
    double estimatedPrecision = DoubleVector.EPSILON; // not exposed by commons math impl

    try {
        root = solver.solve(maximumIterations, new UnivariateRealClosure(context, rho, fn), lower, upper);
        iterations = 1; // the Commons math impl doesn't expose this
    } catch (MaxIterationsExceededException e) {
        root = DoubleVector.NA;
        iterations = -1;
    } catch (FunctionEvaluationException e) {
        throw new EvalException(e);
    }

    return new DoubleArrayVector(root, iterations, estimatedPrecision);
}

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From source file:r.base.optimize.Roots.java

/**
 * Searches the interval from lower to upper for a root (i.e., zero) of the function f with
 * respect to its first argument.// w w  w  . j  a va 2 s  . c  om
 *
 * <p>
 * This internal primitive is used by the uniroot() function in the stats package.
 *
 * <p>
 * This implementation wraps the Commons Math {@link BrentSolver}; there are however
 *
 */
public static DoubleVector zeroin2(@Current Context context, @Current Environment rho, Function fn,
        double lower, double upper, double fLower, double fUpper, double tol, int maximumIterations) {

    BrentSolver solver = new BrentSolver(maximumIterations, tol);

    double root;
    int iterations;
    double estimatedPrecision = DoubleVector.EPSILON; // not exposed by commons math impl

    try {
        root = solver.solve(new UnivariateRealClosure(context, rho, fn), lower, upper);
        iterations = 1; // the Commons math impl doesn't expose this
    } catch (MaxIterationsExceededException e) {
        root = DoubleVector.NA;
        iterations = -1;
    } catch (FunctionEvaluationException e) {
        throw new EvalException(e);
    }

    return new DoubleVector(root, iterations, estimatedPrecision);
}

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