/* * 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 2 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, write to the Free Software * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. */ /* * ResultMatrix.java * Copyright (C) 2005 University of Waikato, Hamilton, New Zealand * */ package weka.experiment; import weka.core.Option; import weka.core.OptionHandler; import weka.core.RevisionHandler; import weka.core.Utils; import java.io.Serializable; import java.util.Enumeration; import java.util.Vector; /** * This matrix is a container for the datasets and classifier setups and * their statistics. Derived classes output the data in different formats. * Derived classes need to implement the following methods: *

toStringMatrix()
toStringKey()
toStringHeader()
toStringSummary()
toStringRanking()

* * * @author FracPete (fracpete at waikato dot ac dot nz) * @version $Revision: 5346 $ * @see #toStringMatrix() * @see #toStringKey() * @see #toStringHeader() * @see #toStringSummary() * @see #toStringRanking() */ public abstract class ResultMatrix implements Serializable, RevisionHandler, OptionHandler { /** for serialization. */ private static final long serialVersionUID = 4487179306428209739L; /** tie. */ public final static int SIGNIFICANCE_TIE = 0; /** win. */ public final static int SIGNIFICANCE_WIN = 1; /** loss. */ public final static int SIGNIFICANCE_LOSS = 2; /** tie string. */ public String TIE_STRING = " "; /** win string. */ public String WIN_STRING = "v"; /** loss string. */ public String LOSS_STRING = "*"; /** the left parentheses for enumerating cols/rows. */ public String LEFT_PARENTHESES = "("; /** the right parentheses for enumerating cols/rows. */ public String RIGHT_PARENTHESES = ")"; /** the column names. */ protected String[] m_ColNames = null; /** the row names. */ protected String[] m_RowNames = null; /** whether a column is hidden. */ protected boolean[] m_ColHidden = null; /** whether a row is hidden. */ protected boolean[] m_RowHidden = null; /** the significance. */ protected int[][] m_Significance = null; /** the values. */ protected double[][] m_Mean = null; /** the standard deviation. */ protected double[][] m_StdDev = null; /** the counts for the different datasets. */ protected double[] m_Counts = null; /** the standard mean precision. */ protected int m_MeanPrec; /** the standard std. deviation preicision. */ protected int m_StdDevPrec; /** whether std. deviations are printed as well. */ protected boolean m_ShowStdDev; /** whether the average for each column should be printed. */ protected boolean m_ShowAverage; /** whether the names or numbers are output as column declarations. */ protected boolean m_PrintColNames; /** whether the names or numbers are output as row declarations. */ protected boolean m_PrintRowNames; /** whether a "(x)" is printed before each column name with "x" as the * index. */ protected boolean m_EnumerateColNames; /** whether a "(x)" is printed before each row name with "x" as the index. */ protected boolean m_EnumerateRowNames; /** the size of the names of the columns. */ protected int m_ColNameWidth; /** the size of the names of the rows. */ protected int m_RowNameWidth; /** the size of the mean columns. */ protected int m_MeanWidth; /** the size of the std dev columns. */ protected int m_StdDevWidth; /** the size of the significance columns. */ protected int m_SignificanceWidth; /** the size of the counts. */ protected int m_CountWidth; /** contains the keys for the header. */ protected Vector m_HeaderKeys = null; /** contains the values for the header. */ protected Vector m_HeaderValues = null; /** the non-significant wins. */ protected int[][] m_NonSigWins = null; /** the significant wins. */ protected int[][] m_Wins = null; /** the wins in ranking. */ protected int[] m_RankingWins = null; /** the losses in ranking. */ protected int[] m_RankingLosses = null; /** the difference between wins and losses. */ protected int[] m_RankingDiff = null; /** the ordering of the rows. */ protected int[] m_RowOrder = null; /** the ordering of the columns. */ protected int[] m_ColOrder = null; /** whether to remove the filter name from the dataaset name. */ protected boolean m_RemoveFilterName = false; /** * initializes the matrix as 1x1 matrix. */ public ResultMatrix() { this(1, 1); } /** * initializes the matrix with the given dimensions. * * @param cols the number of columns * @param rows the number of rows */ public ResultMatrix(int cols, int rows) { setSize(cols, rows); clear(); } /** * initializes the matrix with the values from the given matrix. * * @param matrix the matrix to get the values from */ public ResultMatrix(ResultMatrix matrix) { assign(matrix); } /** * Returns a string describing the matrix. * * @return a description suitable for * displaying in the experimenter gui */ public abstract String globalInfo(); /** * Returns an enumeration of all the available options.. * * @return an enumeration of all available options. */ public Enumeration listOptions() { Vector