Package com.irurueta.numerical.fitting

Class MultiDimensionFitter

java.lang.Object
com.irurueta.numerical.fitting.Fitter
com.irurueta.numerical.fitting.MultiDimensionFitter
Direct Known Subclasses:
LevenbergMarquardtMultiDimensionFitter, MultiDimensionLinearFitter
public abstract class MultiDimensionFitter extends Fitter
Base class to fit a multi dimension function y = f(x1, x2, ...) by using provided data (x, y)

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    protected double[]
    a
    Estimated parameters of linear single dimensional function
    protected double
    chisq
    Estimated chi square value of input data
    protected com.irurueta.algebra.Matrix
    covar
    Covariance of estimated parameters of linear 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 com.irurueta.algebra.Matrix
    x
    Input points x where a multidimensional function f(x1, x2, ...) is evaluated where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values
    protected double[]
    y
    Result of evaluation of multidimensional function f(x1, x2, ...) at provided x points.

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

    resultAvailable

  • Constructor Summary

    Constructors
    Modifier
    Constructor
    Description
    protected
    MultiDimensionFitter()
    Constructor
    protected
    MultiDimensionFitter(com.irurueta.algebra.Matrix x, double[] y, double sig)
    Constructor
    protected
    MultiDimensionFitter(com.irurueta.algebra.Matrix 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).
    com.irurueta.algebra.Matrix
    getX()
    Returns input points x where a multidimensional function f(x1, x2, ...) is evaluated and where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values
    double[]
    getY()
    Returns result of evaluation of multidimensional function f(x) at provided x points.
    final void
    setInputData(com.irurueta.algebra.Matrix 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(com.irurueta.algebra.Matrix 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 com.irurueta.algebra.Matrix x
      Input points x where a multidimensional function f(x1, x2, ...) is evaluated where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values

    • y

      protected double[] y
      Result of evaluation of multidimensional function f(x1, x2, ...) at provided x points. This is provided as input data along 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 linear single dimensional function

    • covar

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

    • chisq

      protected double chisq
      Estimated chi square value of input data

  • Constructor Details

    • MultiDimensionFitter

      protected MultiDimensionFitter()
      Constructor

    • MultiDimensionFitter

      protected MultiDimensionFitter(com.irurueta.algebra.Matrix x, double[] y, double[] sig)
      Constructor
      Parameters:
      x - input points x where a multidimensional function f(x1, x2, ...) is evaluated
      y - result of evaluation of multidimensional function f(x1, x2, ...) at provided x points
      sig - standard deviations of each pair of points (x, y)
      Throws:
      IllegalArgumentException - if provided matrix rows and arrays don't have the same length

    • MultiDimensionFitter

      protected MultiDimensionFitter(com.irurueta.algebra.Matrix x, double[] y, double sig)
      Constructor
      Parameters:
      x - input points x where a multidimensional function f(x1, x2, ...) is evaluated
      y - result of evaluation of linear multidimensional function f(x1, x2, ...) at provided x points
      sig - standard deviation of all pair of points assuming that standard deviations are constant
      Throws:
      IllegalArgumentException - if provided matrix rows and arrays don't have the same length

  • Method Details

    • getX

      public com.irurueta.algebra.Matrix getX()
      Returns input points x where a multidimensional function f(x1, x2, ...) is evaluated and where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values
      Returns:
      input point x

    • getY

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

    • 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(com.irurueta.algebra.Matrix x, double[] y, double[] sig)
      Sets required input data to start function fitting
      Parameters:
      x - input points x where a multidimensional function f(x1, x2, ...) is evaluated and where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values
      y - result of evaluation of multidimensional function f(x1, x2, ...) 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(com.irurueta.algebra.Matrix 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 multidimensional function f(x1, x2, ...) is evaluated and where each column of the matrix represents each dimension of the point and each row is related to each sample corresponding to provided y pairs of values
      y - result of evaluation of multidimensional function f(x1, x2, ...) at provided x points. This is provided as input data along with x array
      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