com.opengamma.strata.math.impl.function

Class ParameterizedSurface

java.lang.Object

com.opengamma.strata.math.impl.function.ParameterizedFunction<DoublesPair,DoubleArray,Double>

com.opengamma.strata.math.impl.function.ParameterizedSurface

public abstract class ParameterizedSurface
extends ParameterizedFunction<DoublesPair,DoubleArray,Double>

A parameterised surface that gives the both the surface (the function z=f(xy) where xy is a 2D point and z is a scalar) and the surface sensitivity (dz/dp where p is one of the parameters) for given parameters.

Constructor Summary

Constructors

Constructor and Description
ParameterizedSurface()

Method Summary

Modifier and Type	Method and Description
Function<DoublesPair,DoubleArray>	getZParameterSensitivity(DoubleArray params) For a function of two variables (surface) that can be written as $z=f(x, y;\boldsymbol{\theta})$ where x, y & z are scalars and $\boldsymbol{\theta})$ is a vector of parameters (i.e.

Methods inherited from class com.opengamma.strata.math.impl.function.ParameterizedFunction

asFunctionOfArguments, asFunctionOfParameters, evaluate, getNumberOfParameters

Methods inherited from class java.lang.Object

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

Constructor Detail

ParameterizedSurface

public ParameterizedSurface()

Method Detail

getZParameterSensitivity

public Function<DoublesPair,DoubleArray> getZParameterSensitivity(DoubleArray params)

For a function of two variables (surface) that can be written as $z=f(x, y;\boldsymbol{\theta})$ where x, y & z are scalars and $\boldsymbol{\theta})$ is a vector of parameters (i.e. $x,y,z \in \mathbb{R}$ and $\boldsymbol{\theta} \in \mathbb{R}^n$) this returns the function $g : \mathbb{R} \to \mathbb{R}^n; x,y \mapsto g(x,y)$, which is the function's (curves') sensitivity to its parameters, i.e. $g(x,y) = \frac{\partial f(x,y;\boldsymbol{\theta})}{\partial \boldsymbol{\theta}}$

The default calculation is performed using finite difference (via ScalarFieldFirstOrderDifferentiator) but it is expected that this will be overridden by concrete subclasses.

Parameters:

params - The value of the parameters ($\boldsymbol{\theta}$) at which the sensitivity is calculated

Returns:

The sensitivity as a function with a DoublesPair (x,y) as its single argument and a vector as its return value