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ELKI - Main Module – Open-Source Data-Mining Framework with Index Acceleration

There is a newer version: 0.7.5

package de.lmu.ifi.dbs.elki.data.uncertain;
/*
 This file is part of ELKI:
 Environment for Developing KDD-Applications Supported by Index-Structures

 Copyright (C) 2015
 Ludwig-Maximilians-Universität München
 Lehr- und Forschungseinheit für Datenbanksysteme
 ELKI Development Team

 This program is free software: you can redistribute it and/or modify
 it under the terms of the GNU Affero General Public License as published by
 the Free Software Foundation, either version 3 of the License, or
 (at your option) any later version.

 This program is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 GNU Affero General Public License for more details.

 You should have received a copy of the GNU Affero General Public License
 along with this program.  If not, see .
 */

import de.lmu.ifi.dbs.elki.data.DoubleVector;

/**
 * Interface for discrete uncertain objects, that are represented by a finite
 * (possibly weighted) number of samples.
 *
 * @author Erich Schubert
 * @since 0.7.0
 */
public interface DiscreteUncertainObject extends UncertainObject {
  /**
   * Get the number of samples available (or -1 for infinite).
   *
   * @return Number of samples, negative indicates infinite.
   */
  int getNumberSamples();

  /**
   * Get the i'th vector.
   *
   * @param i Index
   * @return Vector
   */
  DoubleVector getSample(int i);

  /**
   * Get the weight of the i'th vector.
   *
   * @param i Index
   * @return Weight
   */
  double getWeight(int i);
}