package edu.stanford.nlp.optimization;/** * The interface for constrained function minimizers.   * * Not all cases need to be supported by all implementations.  For * example, in implementation might support inequality constraints * only. * * 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 ConstrainedMinimizer extends Minimizer {  /**   * The general case, allowing both equality and inequality   * constraints.  A given implementation can throw an   * UnsupportedOperationException if it cannot handle the constraints   * it is supplied.   *   * It is expected that <code>minimize(function, functionTolerance,   * [], 0, [], 0, initial)</code> behave exactly like the   * <code>minimize(function, functionTolerance, initial)</code>   * method inherited from <code>Minimizer</code>.   *   * @param function the objective function   * @param functionTolerance a <code>double</code> value   * @param eqConstraints an array of zero or more equality constraints   * @param eqConstraintTolerance the violation tolerace for equality constraints   * @param ineqConstraints an array of zero or more inequality constraints   * @param ineqConstraintTolerance the violation tolerace for equality constraints   * @param initial a initial feasible (!) point   * @return a minimizing feasible point   */  double[] minimize(Function function, double functionTolerance, Function[] eqConstraints, double eqConstraintTolerance, Function[] ineqConstraints, double ineqConstraintTolerance, double[] initial); }