package edu.stanford.nlp.optimization;/** * The interface for unconstrained function minimizers. * * Implementations may also vary in their requirements for the * arguments.  For example, implementations may or may not care if the * <code>initial</code> feasible vector turns out to be non-feasible * (or null!).  Similarly, some methods may insist that objectives * and/or constraint <code>Function</code> objects actually be * <code>DiffFunction</code> objects. * * @author <a href="mailto:klein@cs.stanford.edu">Dan Klein</a> * @version 1.0 * @since 1.0 */public interface Minimizer {  /**   * Attempts to find an unconstrained minimum of the objective   * <code>function</code> starting at <code>initial</code>, within   * <code>functionTolerance</code>.   *   * @param function the objective function   * @param functionTolerance a <code>double</code> value   * @param initial a initial feasible point   */  double[] minimize(Function function, double functionTolerance, double[] initial);}