/*
 * Copyright (C) 2008-2015 by Holger Arndt
 *
 * This file is part of the Java Data Mining Package (JDMP).
 * See the NOTICE file distributed with this work for additional
 * information regarding copyright ownership and licensing.
 *
 * JDMP 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 2
 * of the License, or (at your option) any later version.
 *
 * JDMP 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 JDMP; if not, write to the
 * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
 * Boston, MA  02110-1301  USA
 */

package org.jdmp.core.algorithm.basic;

import java.util.HashMap;
import java.util.Map;

import org.jdmp.core.algorithm.AbstractAlgorithm;
import org.jdmp.core.variable.Variable;
import org.ujmp.core.Matrix;
import org.ujmp.core.util.MathUtil;

public class Sensitivity extends AbstractAlgorithm {
	private static final long serialVersionUID = -6760913071366248714L;

	public static final String DESCRIPTION = "target = sensitivity(source)";

	public Sensitivity(Variable... variables) {
		super();
		setDescription(DESCRIPTION);
		addVariableKey(SOURCE);
		addVariableKey(TARGET);
		setEdgeLabel(SOURCE, "Source");
		setEdgeLabel(TARGET, "Target");
		setEdgeDirection(SOURCE, EdgeDirection.Incoming);
		setEdgeDirection(TARGET, EdgeDirection.Outgoing);
		setVariables(variables);
	}

	public Map calculateObjects(Map input) {
		Map result = new HashMap();

		Matrix source = MathUtil.getMatrix(input.get(SOURCE));

		Matrix target = Matrix.Factory.zeros(source.getRowCount(), 1);

		long cols = source.getColumnCount();
		long rows = source.getRowCount();
		for (int k = 0; k < rows; k++) {
			int tp = 0;
			int fn = 0;
			for (int r = 0; r < rows; r++) {
				for (int c = 0; c < cols; c++) {
					int count = source.getAsInt(r, c);
					boolean expected = r == k;
					boolean predicted = c == k;
					if (expected && predicted) {
						tp += count;
					} else if (expected && (!predicted)) {
						fn += count;
					}
				}
			}
			target.setAsDouble(MathUtil.sensitivity(tp, fn), k, 0);
		}
		result.put(TARGET, target);
		return result;
	}

}