Documentation of 'edu.stanford.rsl.jpop.SimpleFunctionOptimizer' Java class
SimpleFunctionOptimizer
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Class SimpleFunctionOptimizer


  • public class SimpleFunctionOptimizer
extends java.lang.Object
    This class was is based on the Fortran-Java translation of Steve Verrill of fzero and fmin. The code was adopted and altered to fit into a hierarchical object-oriented program structure.

    • Constructor Detail

      • SimpleFunctionOptimizer

        public SimpleFunctionOptimizer()

    • Method Detail

      • getLeftEndPoint

        public double getLeftEndPoint()
        Returns:
        the leftEndPoint of the search interval.

      • setLeftEndPoint

        public void setLeftEndPoint(double leftEndPoint)
        Sets the left end point of the search interval.
        Default is Double.MIN_VALUE.
        Parameters:
        leftEndPoint - the leftEndPoint to set

      • getRightEndPoint

        public double getRightEndPoint()
        Returns:
        the rightEndPoint of the search interval.

      • setRightEndPoint

        public void setRightEndPoint(double rightEndPoint)
        Sets the right end point of the search interval.
        Defaults to Double.MAX_VALUE.
        Parameters:
        rightEndPoint - the rightEndPoint to set

      • getAbsoluteTolerance

        public double getAbsoluteTolerance()
        Returns:
        the absoluteTolerance

      • setAbsoluteTolerance

        public void setAbsoluteTolerance(double absoluteTolerance)
        Sets the absolute tolerance of the search.
        Defaults to 3.0E-08. 1.1102e-16 is machine precision.
        Parameters:
        absoluteTolerance - the absoluteTolerance to set

      • getRelativeTolerance

        public double getRelativeTolerance()
        Returns:
        the relativeTolerance

      • setRelativeTolerance

        public void setRelativeTolerance(double relativeTolerance)
        Sets the relative tolerance.
        Defaults to 3.0E-04. 1.1102e-16 is machine precision.
        Parameters:
        relativeTolerance - the relativeTolerance to set

      • isPrintWarnings

        public boolean isPrintWarnings()
        Returns:
        the printWarnings

      • setPrintWarnings

        public void setPrintWarnings(boolean printWarnings)
        Turns warnings on or off.
        Default is on.
        Parameters:
        printWarnings - the printWarnings to set

      • isUseInitialGuess

        public boolean isUseInitialGuess()
        Returns:
        the useInitialGuess

      • setUseInitialGuess

        public void setUseInitialGuess(boolean useInitialGuess)
        Turns the use of an initial guess on or off.
        Default is off.
        Parameters:
        useInitialGuess - the useInitialGuess to set

      • getInitialGuess

        public double getInitialGuess()
        Returns:
        the initialGuess

      • setInitialGuess

        public void setInitialGuess(double initialGuess)
        An initial guess of a zero can be set.
        The value will only be used if useInitialGuess is true.

        A guess of a zero of the function could help in speeding up convergence. If evaluate(leftEndPoint) and evaluate(initialGuess) have opposite signs, a root will be found in the interval (leftEndPoint,inititalGuess); if not, but evaluate(initialGuess) and evaluate(rightEndPoint) have opposite signs, a root will be found in the interval (initialGuess,rightEndPoint); otherwise, the interval (leftEndPoint,rightEndPoint) will be searched for a possible root.
        Parameters:
        initialGuess - the initialGuess to set

      • minimize

        public double minimize(SimpleOptimizableFunction function)
        Minimizes a SimpleOptimizableFunction. Searches between leftEndPoint and rightEndPoint with a tolerance of absoluteTolerance. Parameters must be set using the respective getters and setters.
        Parameters:
        function - the function to minimize.
        Returns:
        the position of the minimum.

      • fmin

        @Deprecated
public static double fmin(double leftEndPoint,
                                      double rightEndPoint,
                                      SimpleOptimizableFunction function,
                                      double toleranceFactor)
        Deprecated. 

        This method performs a 1-dimensional minimization. It implements Brent's method which combines a golden-section search and parabolic interpolation. The introductory comments from the FORTRAN version are provided below. This method is a translation from FORTRAN to Java of the Netlib function fmin. In the Netlib listing no author is given. Translated by Steve Verrill, March 24, 1998.

        Parameters:
        leftEndPoint - Left endpoint of initial interval
        rightEndPoint - Right endpoint of initial interval
        function - A class that defines a method, evaluate(), to minimize. The class must implement the SimpleOptimizableFunction interface. evaluate must have one double valued argument.
        toleranceFactor - Desired length of the interval in which the minimum will be determined to lie (This should be greater than, roughly, 3.0e-8.)
        Returns:
        the minimal value;

      • findRoot

        public double findRoot(SimpleOptimizableFunction function)
        Method to find a root of a function between leftEndPoint and rightEndPoint.
        May use an initial guess to speed to convergence.

        Accuracy can be adjusted using relativeTolerance and absoluteTolerance. Use setters of this class to adjust the parameters or to disable the printing of warnings.
        Parameters:
        function -
        Returns:

      • fzero

        @Deprecated
public static void fzero(SimpleOptimizableFunction function,
                                     double[] b,
                                     double[] c,
                                     double r,
                                     double re,
                                     double ae,
                                     int[] iflag)
        Deprecated. 

        This method searches for a zero of a function f(x) between the given values b and c until the width of the interval (b,c) has collapsed to within a tolerance specified by the stopping criterion, Math.abs(b-c) <= 2.0*(rw*Math.abs(b)+ae). The method used is an efficient combination of bisection and the secant rule. The introductory comments from the FORTRAN version are provided below. This method is a translation from FORTRAN to Java of the Netlib (actually it is in the SLATEC library which is available at Netlib) function dfzero. In the FORTRAN code, L.F. Shampine and H.A. Watts are listed as the authors. Translated by Steve Verrill, April 17, 2001.

        Parameters:
        function - A class that defines a method, evaluate, that returns a value that is to be zeroed. The class must implement the SimpleOptimizableFunction interface. evaluate must have one double valued argument.
        b[1] - One end point of the initial interval. The value returned for b[1] is usually the better approximation to a zero of evaluate.
        c[1] - The other end point of the initial interval.
        r - Initial guess of a zero. A (better) guess of a zero of evaluate() which could help in speeding up convergence. If evaluate(b) and evaluate(r) have opposite signs, a root will be found in the interval (b,r); if not, but evaluate(r) and evaluate(c) have opposite signs, a root will be found in the interval (r,c); otherwise, the interval (b,c) will be searched for a possible root. When no better guess is known, it is recommended that r be set to b or c; because if r is not interior to the interval (b,c), it will be ignored.
        re - Relative error used for rw in the stopping criterion. If the requested re is less than machine precision, then rw is set to approximately machine precision.
        ae - Absolute error used in the stopping criterion. If the given interval (b,c) contains the origin, then a nonzero value should be chosen for AE.
        iflag[1] - A status code. User must check iflag[1] after each call. Control returns to the user from dfzero in all cases. 1: b is within the requested tolerance of a zero. The interval (b,c) collapsed to the requested tolerance, the function changes sign in (b,c), and evaluate(x) decreased in magnitude as (b,c) collapsed. 2: evaluate(b) = 0. However, the interval (b,c) may not have collapsed to the requested tolerance. 3: b may be near a singular point of evaluate(x). The interval (b,c) collapsed to the requested tol- erance and the function changes sign in (b,c), but evaluate(x) increased in magnitude as (b,c) collapsed,i.e. Math.abs(evaluate(b out)) > Math.max(Math.abs(evaluate(b in)), Math.abs(evaluate(c in))) 4: No change in sign of evaluate(x) was found although the interval (b,c) collapsed to the requested tolerance. The user must examine this case and decide whether b is near a local minimum of evaluate(x), or b is near a zero of even multiplicity, or neither of these. 5: Too many (> 500) function evaluations used.
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