Sigmoid.Parametric (Apache Commons Math 3.6.1 API)

java.lang.Object

org.apache.commons.math3.analysis.function.Sigmoid.Parametric

All Implemented Interfaces:: ParametricUnivariateFunction

Enclosing class:: Sigmoid

public static class Sigmoid.Parametric extends Object implements ParametricUnivariateFunction

Parametric function where the input array contains the parameters of the sigmoid function, ordered as follows:

Lower asymptote
Higher asymptote

Constructor Summary

Constructors

Constructor

Description

Parametric()
Method Summary

Modifier and Type

Method

Description

double[]

gradient(double x, double... param)

Computes the value of the gradient at x.

double

value(double x, double... param)

Computes the value of the sigmoid at x.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details
- Parametric
  
  public Parametric()
Method Details
- value
  
  public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException
  
  Computes the value of the sigmoid at x.
  
  Specified by:
  
  value in interface ParametricUnivariateFunction
  
  Parameters:
  
  x - Value for which the function must be computed.
  
  param - Values of lower asymptote and higher asymptote.
  
  Returns:
  
  the value of the function.
  
  Throws:
  
  NullArgumentException - if param is null.
  
  DimensionMismatchException - if the size of param is not 2.
- gradient
  
  public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException
  
  Computes the value of the gradient at x. The components of the gradient vector are the partial derivatives of the function with respect to each of the parameters (lower asymptote and higher asymptote).
  
  Specified by:
  
  gradient in interface ParametricUnivariateFunction
  
  Parameters:
  
  x - Value at which the gradient must be computed.
  
  param - Values for lower asymptote and higher asymptote.
  
  Returns:
  
  the gradient vector at x.
  
  Throws:
  
  NullArgumentException - if param is null.
  
  DimensionMismatchException - if the size of param is not 2.