Class AlgorithmFRAP.FitWholeNLConModel2

    • Field Detail

      • xData

        private double[] xData
      • yData

        private float[] yData
      • abscissa

        double abscissa
        DOCUMENT ME!
      • absEps

        double absEps
        DOCUMENT ME!
      • errStatus

        int[] errStatus
        DOCUMENT ME!
      • estErr

        double[] estErr
        DOCUMENT ME!
      • evaluations

        int[] evaluations
        DOCUMENT ME!
      • relEps

        double relEps
        DOCUMENT ME!
      • result

        double[] result
        DOCUMENT ME!
    • Constructor Detail

      • FitWholeNLConModel2

        public FitWholeNLConModel2​(int nPoints,
                                   double[] xData,
                                   float[] yData,
                                   double[] initial,
                                   double abscissa,
                                   double relEps,
                                   double absEps,
                                   double[] result,
                                   double[] estErr,
                                   int[] evaluations,
                                   int[] errStatus)
        Creates a new FitWholeNLConModel2 object.
        Parameters:
        nPoints - DOCUMENT ME!
        xData - DOCUMENT ME!
        yData - DOCUMENT ME!
        initial - DOCUMENT ME!
        abscissa - DOCUMENT ME!
        relEps - DOCUMENT ME!
        absEps - DOCUMENT ME!
        result - DOCUMENT ME!
        estErr - DOCUMENT ME!
        evaluations - DOCUMENT ME!
        errStatus - DOCUMENT ME!
    • Method Detail

      • dumpResults

        public void dumpResults()
        Display results of displaying exponential fitting parameters.
      • fitToFunction

        public void fitToFunction​(double[] a,
                                  double[] residuals,
                                  double[][] covarMat)
        Fit to function.
        Specified by:
        fitToFunction in class NLConstrainedEngine
        Parameters:
        a - The x value of the data point.
        residuals - The best guess parameter values.
        covarMat - The derivative values of y with respect to fitting parameters.