Package com.irurueta.numerical.fitting

Class SingleDimensionFitter

java.lang.Object
com.irurueta.numerical.fitting.Fitter
com.irurueta.numerical.fitting.SingleDimensionFitter
Direct Known Subclasses:
LevenbergMarquardtSingleDimensionFitter, SingleDimensionLinearFitter
public abstract class SingleDimensionFitter extends Fitter
Base class to fit a single dimension function y = f(x) by using provided data (x, y)

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    protected double[]
    a
    Estimated parameters of single dimensional function.
    protected double
    chisq
    Estimated chi square value of input data.
    protected com.irurueta.algebra.Matrix
    covar
    Covariance of estimated parameters of single dimensional function.
    protected int
    ndat
    Number of samples (x, y) in provided input data.
    protected double[]
    sig
    Standard deviations of each pair of points (x,y).
    protected double[]
    x
    Input points x where function f(x) is evaluated.
    protected double[]
    y
    Result of evaluation of linear single dimensional function f(x) at provided x points.

    Fields inherited from class com.irurueta.numerical.fitting.Fitter

    resultAvailable

  • Constructor Summary

    Constructors
    Modifier
    Constructor
    Description
    protected
    SingleDimensionFitter()
    Constructor.
    protected
    SingleDimensionFitter(double[] x, double[] y, double sig)
    Constructor.
    protected
    SingleDimensionFitter(double[] x, double[] y, double[] sig)
    Constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    double[]
    getA()
    Returns estimated parameters of linear single dimensional function.
    double
    getChisq()
    Returns estimated chi square value of input data.
    com.irurueta.algebra.Matrix
    getCovar()
    Returns covariance of estimated parameters of linear single dimensional function.
    double[]
    getSig()
    Returns standard deviations of each pair of points (x,y).
    double[]
    getX()
    Returns input points x where function f(x) is evaluated.
    double[]
    getY()
    Returns result of evaluation of linear single dimensional function f(x) at provided x points.
    final void
    setInputData(double[] x, double[] y, double sig)
    Sets required input data to start function fitting and assuming constant standard deviation errors in input data.
    final void
    setInputData(double[] x, double[] y, double[] sig)
    Sets required input data to start function fitting.

    Methods inherited from class com.irurueta.numerical.fitting.Fitter

    fit, isReady, isResultAvailable

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Field Details

    • x

      protected double[] x
      Input points x where function f(x) is evaluated.

    • y

      protected double[] y
      Result of evaluation of linear single dimensional function f(x) at provided x points. This is provided as input data along with x array.

    • sig

      protected double[] sig
      Standard deviations of each pair of points (x,y).

    • ndat

      protected int ndat
      Number of samples (x, y) in provided input data.

    • a

      protected double[] a
      Estimated parameters of single dimensional function.

    • covar

      protected com.irurueta.algebra.Matrix covar
      Covariance of estimated parameters of single dimensional function.

    • chisq

      protected double chisq
      Estimated chi square value of input data.

  • Constructor Details

    • SingleDimensionFitter

      protected SingleDimensionFitter()
      Constructor.

    • SingleDimensionFitter

      protected SingleDimensionFitter(double[] x, double[] y, double[] sig)
      Constructor.
      Parameters:
      x - input points x where function f(x) is evaluated.
      y - result of evaluation of linear single dimensional function f(x) at provided x points.
      sig - standard deviations of each pair of points (x, y).
      Throws:
      IllegalArgumentException - if provided arrays don't have the same length.

    • SingleDimensionFitter

      protected SingleDimensionFitter(double[] x, double[] y, double sig)
      Constructor.
      Parameters:
      x - input points x where function f(x) is evaluated.
      y - result of evaluation of linear single dimensional function f(x) at provided x points.
      sig - standard deviation of all pair of points assuming that standard deviations are constant.
      Throws:
      IllegalArgumentException - if provided arrays don't have the same length.

  • Method Details

    • getX

      public double[] getX()
      Returns input points x where function f(x) is evaluated.
      Returns:
      input points x.

    • getY

      public double[] getY()
      Returns result of evaluation of linear single dimensional function f(x) at provided x points. This is provided as input data along with x array.
      Returns:
      sampled function evaluations.

    • getSig

      public double[] getSig()
      Returns standard deviations of each pair of points (x,y).
      Returns:
      standard deviations of each pair of points (x,y).

    • setInputData

      public final void setInputData(double[] x, double[] y, double[] sig)
      Sets required input data to start function fitting.
      Parameters:
      x - input points x where a linear single dimensional function f(x) = a * f0(x) + b * f1(x) + ...
      y - result of evaluation of linear single dimensional function f(x) at provided x points. This is provided as input data along with x array.
      sig - standard deviations of each pair of points (x,y).
      Throws:
      IllegalArgumentException - if provided arrays don't have the same size.

    • setInputData

      public final void setInputData(double[] x, double[] y, double sig)
      Sets required input data to start function fitting and assuming constant standard deviation errors in input data.
      Parameters:
      x - input points x where a linear single dimensional function f(x) = a * f0(x) + b * f1(x) + ...
      y - result of evaluation of linear single dimensional function f(x) at provided x points.
      sig - standard deviation of all pair of points assuming that standard deviations are constant.
      Throws:
      IllegalArgumentException - if provided arrays don't have the same size.

    • getA

      public double[] getA()
      Returns estimated parameters of linear single dimensional function.
      Returns:
      estimated parameters.

    • getCovar

      public com.irurueta.algebra.Matrix getCovar()
      Returns covariance of estimated parameters of linear single dimensional function.
      Returns:
      covariance of estimated parameters.

    • getChisq

      public double getChisq()
      Returns estimated chi square value of input data.
      Returns:
      estimated chi square value of input data.