package edu.stanford.nlp.optimization;
/**
* An interface for once-differentiable double-valued functions over
* double arrays. NOTE: it'd be good to have an AbstractDiffFunction
* that wrapped a Function with a finite-difference approximation.
*
* @author <a href="mailto:klein@cs.stanford.edu">Dan Klein</a>
* @version 1.0
* @see Function
* @since 1.0
*/
public interface DiffFloatFunction extends FloatFunction {
/**
* Returns the first-derivative vector at the input location.
*
* @param x a <code>double[]</code> input vector
* @return the vector of first partial derivatives.
*/
float[] derivativeAt(float[] x);
}