FitFunction (ImgLib2 Javadocs 0-SNAPSHOT API)

All Known Implementing Classes:

EllipticGaussianOrtho, Gaussian
```
public interface FitFunction
```
Interface for fitting-target functions.
Functions defined here are scalar, multi-dimensional ones. We impose that they can return a gradient, so as to use various curve-fitting scheme.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`double`	`grad(double[] x, double[] a, int ak)` Evaluates the gradient value of the function, taken with respect to the `ak`^th parameter, evaluated at point `x`.
`double`	`hessian(double[] x, double[] a, int r, int c)` Evaluates the hessian value of the function, taken with respect to the `r`^th and `c`^th parameters, evaluated at point `x`.
`double`	`val(double[] x, double[] a)` Evaluates this function at point `x`.

- Method Detail
  - val
```
double val(double[] x,
           double[] a)
```
    Evaluates this function at point x. The function is otherwise defined over an array of parameters a, that is the target of the fitting procedure.
    
    Parameters:
    
    x - the multidimensional to evaluate the function at
    
    a - the set of parameters that defines the function
    
    Returns:
    
    a double value, the function evaluated at x
  - grad
```
double grad(double[] x,
            double[] a,
            int ak)
```
    Evaluates the gradient value of the function, taken with respect to the ak^th parameter, evaluated at point x.
    
    Parameters:
    
    x - the point to evaluate the gradient at
    
    a - the set of parameters that defines the function
    
    ak - the index of the parameter to compute the gradient
    
    Returns:
    
    the kth component of the gradient df(x,a)/da_k
    
    See Also:
    
    val(double[], double[])
  - hessian
```
double hessian(double[] x,
               double[] a,
               int r,
               int c)
```
    Evaluates the hessian value of the function, taken with respect to the r^th and c^th parameters, evaluated at point x.
    
    Parameters:
    
    x - the point to evaluate the gradient at
    
    a - the set of parameters that defines the function
    
    r - the index of the first parameter to compute the gradient
    
    c - the index of the second parameter to compute the gradient
    
    Returns:
    
    the (r, c) element of the hessian matrix d²f(x,a)/(da_r da_c)
    
    See Also:
    
    val(double[], double[])

Interface FitFunction

Method Summary

Method Detail

val

grad

hessian