Uses of Interface pal.math.MultivariateFunction (Fiji Javadocs 0-SNAPSHOT API)

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Packages that use MultivariateFunction
Package Description

landmarks

pal.math

Uses of MultivariateFunction in landmarks

Classes in landmarks that implement MultivariateFunction
Modifier and Type Class and Description

static class AffineFromLandmarks.CandidateAffine

class TransformationAttempt

Uses of MultivariateFunction in pal.math

Subinterfaces of MultivariateFunction in pal.math
Modifier and Type	Interface and Description
`interface`	`MFWithGradient` interface for a function of several variables with a gradient

Classes in pal.math that implement MultivariateFunction
Modifier and Type	Class and Description
`class`	`BoundsCheckedFunction` returns a very large number instead of the function value if arguments are out of bound (useful for minimization with minimizers that don't check argument boundaries)

Methods in pal.math with parameters of type MultivariateFunction
Modifier and Type	Method and Description
`static double[]`	NumericalDerivative.`diagonalHessian(MultivariateFunction f, double[] x)` determine diagonal of Hessian
`double`	MultivariateMinimum.`findMinimum(MultivariateFunction f, double[] xvec)` Find minimum close to vector x
`double`	MultivariateMinimum.`findMinimum(MultivariateFunction f, double[] xvec, int fxFracDigits, int xFracDigits)` Find minimum close to vector x (desired fractional digits for each parameter is specified)
`static double[]`	MathUtils.`getRandomArguments(MultivariateFunction mf)`
`static double[]`	NumericalDerivative.`gradient(MultivariateFunction f, double[] x)` determine gradient
`static void`	NumericalDerivative.`gradient(MultivariateFunction f, double[] x, double[] grad)` determine gradient
`void`	StochasticOSearch.`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)`
`void`	OrthogonalSearch.`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)`
`abstract void`	MultivariateMinimum.`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)` The actual optimization routine (needs to be implemented in a subclass of MultivariateMinimum).
`void`	GeneralizedDEOptimizer.`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)` The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
`void`	DifferentialEvolution.`optimize(MultivariateFunction func, double[] xvec, double tolfx, double tolx)`
`void`	ConjugateGradientSearch.`optimize(MultivariateFunction f, double[] x, double tolfx, double tolx)`
`void`	ConjugateDirectionSearch.`optimize(MultivariateFunction f, double[] xvector, double tolfx, double tolx)`

Constructors in pal.math with parameters of type MultivariateFunction
Constructor and Description
`BoundsCheckedFunction(MultivariateFunction func)` construct bound-checked multivariate function (a large number will be returned on function evaluation if argument is out of bounds; default is 1000000)
`BoundsCheckedFunction(MultivariateFunction func, double largeNumber)` construct constrained multivariate function
`LineFunction(MultivariateFunction func)` construct univariate function from multivariate function
`OrthogonalLineFunction(MultivariateFunction func)` construct univariate function from multivariate function

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