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The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

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/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU 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 General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see .
 */

/**
 * TransferableImage.java
 * Copyright (C) 2010 University of Waikato, Hamilton, New Zealand
 */
package meka.gui.core;

import java.awt.datatransfer.DataFlavor;
import java.awt.datatransfer.Transferable;
import java.awt.datatransfer.UnsupportedFlavorException;
import java.awt.image.BufferedImage;
import java.io.IOException;
import java.io.Serializable;

/**
 * A container for images.
 *
 * @author  fracpete (fracpete at waikato dot ac dot nz)
 * @version $Revision: 4584 $
 */
public class TransferableImage
  implements Serializable, Transferable {

  /** for serialization. */
  private static final long serialVersionUID = 7613537409206432362L;

  /** the image to transfer. */
  protected BufferedImage m_Data;

  /**
   * Initializes the container.
   *
   * @param data	the string to transfer
   */
  public TransferableImage(BufferedImage data) {
    super();

    m_Data = data;
  }

  /**
   * Returns an array of DataFlavor objects indicating the flavors the data
   * can be provided in.  The array should be ordered according to preference
   * for providing the data (from most richly descriptive to least descriptive).
   *
   * @return 		an array of data flavors in which this data can be transferred
   */
  public DataFlavor[] getTransferDataFlavors() {
    return new DataFlavor[]{DataFlavor.imageFlavor};
  }

  /**
   * Returns whether or not the specified data flavor is supported for
   * this object.
   *
   * @param flavor 	the requested flavor for the data
   * @return 		boolean indicating whether or not the data flavor is supported
   */
  public boolean isDataFlavorSupported(DataFlavor flavor) {
    return (flavor.equals(DataFlavor.imageFlavor));
  }

  /**
   * Returns an object which represents the data to be transferred.  The class
   * of the object returned is defined by the representation class of the flavor.
   *
   * @param flavor 		the requested flavor for the data
   * @return			the transferred string
   * @throws IOException    if the data is no longer available
   *              		in the requested flavor.
   * @throws UnsupportedFlavorException    if the requested data flavor is
   *              				not supported.
   * @see DataFlavor#getRepresentationClass
   */
  public Object getTransferData(DataFlavor flavor) throws UnsupportedFlavorException, IOException {
    if (flavor.equals(DataFlavor.imageFlavor))
      return m_Data;
    else
      throw new UnsupportedFlavorException(flavor);
  }

  /**
   * Returns the underlying image.
   *
   * @return		the image
   */
  public BufferedImage getData() {
    return m_Data;
  }

  /**
   * Returns a string representation of the underlying image.
   *
   * @return		the string representation
   */
  public String toString() {
    return m_Data.toString();
  }
}