/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package opennlp.tools.ml.model;

/**
 * This interface allows one to implement a prior distribution for use in
 * maximum entropy model training.
 */
public interface Prior {

  /**
   * Populates the specified array with the log of the distribution for the specified context.
   * The returned array will be overwritten and needs to be re-initialized with every call to this method.
   * @param dist An array to be populated with the log of the prior distribution.
   * @param context The indices of the contextual predicates for an event.
   */
  void logPrior(double[] dist, int[] context);

  /**
   * Populates the specified array with the log of the distribution for the specified context.
   * The returned array will be overwritten and needs to be re-initialized with every call to this method.
   * @param dist An array to be populated with the log of the prior distribution.
   * @param context The indices of the contextual predicates for an event.
   * @param values The values associated with the context.
   */
  void logPrior(double[] dist, int[] context, float[] values);

  /**
   * Populates the specified array with the log of the distribution for the specified context.
   * The returned array will be overwritten and needs to be re-initialized with every call to this method.
   * @param dist An array to be populated with the log of the prior distribution.
   * @param context The indices of the contextual predicates for an event.
   * @param values The values associated with the context.
   */
  void logPrior(double[] dist, Context[] context, float[] values);

  /**
   * Method to specify the label for the outcomes and contexts. This is used to map
   * integer outcomes and contexts to their string values. This method is called prior
   * to any call to {@link #logPrior}.
   * @param outcomeLabels An array of each outcome label.
   * @param contextLabels An array of each context label.
   */
  void setLabels(String[] outcomeLabels, String[] contextLabels);
}
