content: // ===============================================================================
  // Authors: AFRL/RQQD
  // Organization: Air Force Research Laboratory, Aerospace Systems Directorate, Power and Control Division
  // 
  // Copyright (c) 2017 Government of the United State of America, as represented by
  // the Secretary of the Air Force.  No copyright is claimed in the United States under
  // Title 17, U.S. Code.  All Other Rights Reserved.
  // ===============================================================================
  
  /*
   * GRAL: GRAphing Library for Java(R)
   *
   * (C) Copyright 2009-2013 Erich Seifert <dev[at]erichseifert.de>,
   * Michael Seifert <mseifert[at]error-reports.org>
   *
   * This file is part of GRAL.
   *
   * GRAL is free software: you can redistribute it and/or modify
   * it under the terms of the GNU Lesser General Public License as published by
   * the Free Software Foundation, either version 3 of the License, or
   * (at your option) any later version.
   *
   * GRAL 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 Lesser General Public License for more details.
   *
   * You should have received a copy of the GNU Lesser General Public License
   * along with GRAL.  If not, see <http://www.gnu.org/licenses/>.
   */
  package de.erichseifert.gral.data.filters;
  
  import java.io.IOException;
  import java.io.ObjectInputStream;
  
  import de.erichseifert.gral.data.DataSource;
  import de.erichseifert.gral.util.DataUtils;
  import de.erichseifert.gral.util.MathUtils;
  
  /**
   * <p>Class that applies a specified kernel to a data source to convolve it.</p>
   * <p>Functionality includes:</p>
   * <ul>
   *   <li>Getting and setting the {@code Kernel} used for convolution</li>
   * </ul>
   */
  public class Convolution extends Filter {
  	/** Version id for serialization. */
  	private static final long serialVersionUID = 7155205321415314271L;
  
  	/** Kernel that provides the values to convolve the data source. */
  	private final Kernel kernel;
  
  	/**
  	 * Initialized a new instance with the specified data source, convolution
  	 * kernel, edge handling mode, and columns to be filtered.
  	 * @param original DataSource to be filtered.
  	 * @param kernel Kernel to be used.
  	 * @param mode Mode of filtering.
  	 * @param cols Column indexes.
  	 */
  	public Convolution(DataSource original, Kernel kernel, Mode mode, int... cols) {
  		super(original, mode, cols);
  		this.kernel = kernel;
  		filter();
  	}
  
  	/**
  	 * Returns the kernel.
  	 * @return Kernel used for convolution.
  	 */
  	public Kernel getKernel() {
  		return kernel;
  	}
  
  	@Override
  	protected void filter() {
  		clear();
  		for (int rowIndex = 0; rowIndex < getRowCount(); rowIndex++) {
  			Double[] filteredRow = new Double[getColumnCountFiltered()];
  			for (int colIndex = 0; colIndex < filteredRow.length; colIndex++) {
  				int colIndexOriginal = getIndexOriginal(colIndex);
  				filteredRow[colIndex] = convolve(colIndexOriginal, rowIndex);
  			}
  			add(filteredRow);
  		}
  	}
  
  	/**
  	 * Calculates the convolved value of the data with the specified column
  	 * and row.
  	 * @param col Column index.
  	 * @param row Row index.
  	 * @return Convolved value using the set kernel.
  	 */
  	private double convolve(int col, int row) {
  		Kernel kernel = getKernel();
  		if (kernel == null) {
  			Comparable<?> original = getOriginal(col, row);
  			return DataUtils.getValueOrDefault((Number) original, Double.NaN);
  		}
  		double sum = 0.0;
  		for (int k = kernel.getMinIndex(); k <= kernel.getMaxIndex(); k++) {
  			int r = row + k;
  			Comparable<?> original = getOriginal(col, r);
  			double v = DataUtils.getValueOrDefault((Number) original, Double.NaN);
  			if (!MathUtils.isCalculatable(v)) {
  				return v;
  			}
  			sum += kernel.get(k) * v;
  		}
  		return sum;
  	}
  
  	/**
  	 * Custom deserialization method.
  	 * @param in Input stream.
  	 * @throws ClassNotFoundException if a serialized class doesn't exist anymore.
  	 * @throws IOException if there is an error while reading data from the
  	 *         input stream.
  	 */
  	private void readObject(ObjectInputStream in)
  			throws ClassNotFoundException, IOException {
  		// Normal deserialization
  		in.defaultReadObject();
  
  		// Update caches
  		dataUpdated(this);
  	}
  }
  