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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

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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 .
 */

/*
 * ResultMatrixPlainText.java
 * Copyright (C) 2005-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.experiment;

import weka.core.RevisionUtils;
import weka.core.Utils;

/**
 *  Generates the output as plain text (for fixed width
 * fonts).
 * 

* * * Valid options are: *

* *

 * -mean-prec <int>
 *  The number of decimals after the decimal point for the mean.
 *  (default: 2)
 * 
* *
 * -stddev-prec <int>
 *  The number of decimals after the decimal point for the mean.
 *  (default: 2)
 * 
* *
 * -col-name-width <int>
 *  The maximum width for the column names (0 = optimal).
 *  (default: 0)
 * 
* *
 * -row-name-width <int>
 *  The maximum width for the row names (0 = optimal).
 *  (default: 25)
 * 
* *
 * -mean-width <int>
 *  The width of the mean (0 = optimal).
 *  (default: 0)
 * 
* *
 * -stddev-width <int>
 *  The width of the standard deviation (0 = optimal).
 *  (default: 0)
 * 
* *
 * -sig-width <int>
 *  The width of the significance indicator (0 = optimal).
 *  (default: 0)
 * 
* *
 * -count-width <int>
 *  The width of the counts (0 = optimal).
 *  (default: 5)
 * 
* *
 * -show-stddev
 *  Whether to display the standard deviation column.
 *  (default: no)
 * 
* *
 * -show-avg
 *  Whether to show the row with averages.
 *  (default: no)
 * 
* *
 * -remove-filter
 *  Whether to remove the classname package prefixes from the
 *  filter names in datasets.
 *  (default: no)
 * 
* *
 * -print-col-names
 *  Whether to output column names or just numbers representing them.
 *  (default: no)
 * 
* *
 * -print-row-names
 *  Whether to output row names or just numbers representing them.
 *  (default: no)
 * 
* *
 * -enum-col-names
 *  Whether to enumerate the column names (prefixing them with 
 *  '(x)', with 'x' being the index).
 *  (default: no)
 * 
* *
 * -enum-row-names
 *  Whether to enumerate the row names (prefixing them with 
 *  '(x)', with 'x' being the index).
 *  (default: no)
 * 
* * * * @author FracPete (fracpete at waikato dot ac dot nz) * @version $Revision: 10204 $ */ public class ResultMatrixPlainText extends ResultMatrix { /** for serialization. */ private static final long serialVersionUID = 1502934525382357937L; /** * initializes the matrix as 1x1 matrix. */ public ResultMatrixPlainText() { this(1, 1); } /** * initializes the matrix with the given dimensions. * * @param cols the number of columns * @param rows the number of rows */ public ResultMatrixPlainText(int cols, int rows) { super(cols, rows); } /** * initializes the matrix with the values from the given matrix. * * @param matrix the matrix to get the values from */ public ResultMatrixPlainText(ResultMatrix matrix) { super(matrix); } /** * Returns a string describing the matrix. * * @return a description suitable for displaying in the experimenter gui */ @Override public String globalInfo() { return "Generates the output as plain text (for fixed width fonts)."; } /** * returns the name of the output format. * * @return the display name */ @Override public String getDisplayName() { return "Plain Text"; } /** * returns the default width for the row names. * * @return the width */ @Override public int getDefaultRowNameWidth() { return 25; } /** * returns the default width for the counts. * * @return the width */ @Override public int getDefaultCountWidth() { return 5; } /** * returns the header of the matrix as a string. * * @return the header * @see #m_HeaderKeys * @see #m_HeaderValues */ @Override public String toStringHeader() { int i; int size; String[][] data; String result; result = ""; // fill in data data = new String[m_HeaderKeys.size()][2]; for (i = 0; i < m_HeaderKeys.size(); i++) { data[i][0] = m_HeaderKeys.get(i).toString() + ":"; data[i][1] = m_HeaderValues.get(i).toString(); } // pad size = getColSize(data, 0); for (i = 0; i < data.length; i++) { data[i][0] = padString(data[i][0], size); } // build result for (i = 0; i < data.length; i++) { result += data[i][0] + " " + data[i][1] + "\n"; } return result; } /** * returns the matrix as plain text. * * @return the matrix */ @Override public String toStringMatrix() { StringBuffer result; String[][] cells; int i; int j; int n; int k; int size; String line; int indexBase; StringBuffer head; StringBuffer body; StringBuffer foot; int[] startMeans; int[] startSigs; int maxLength; result = new StringBuffer(); head = new StringBuffer(); body = new StringBuffer(); foot = new StringBuffer(); cells = toArray(); startMeans = new int[getColCount()]; startSigs = new int[getColCount() - 1]; maxLength = 0; // pad numbers for (n = 1; n < cells[0].length; n++) { size = getColSize(cells, n, true, true); for (i = 1; i < cells.length - 1; i++) { cells[i][n] = padString(cells[i][n], size, true); } } // index of base column in array indexBase = 1; if (getShowStdDev()) { indexBase++; } if (getShowStdDev()) { } // output data (without "(v/ /*)") j = 0; k = 0; for (i = 1; i < cells.length - 1; i++) { if (isAverage(i)) { body.append(padString("", maxLength).replaceAll(".", "-") + "\n"); } line = ""; for (n = 0; n < cells[0].length; n++) { // record starts if (i == 1) { if (isMean(n)) { startMeans[j] = line.length(); j++; } if (isSignificance(n)) { startSigs[k] = line.length(); k++; } } if (n == 0) { line += padString(cells[i][n], getRowNameWidth()); if (!isAverage(i)) { line += padString( "(" + Utils.doubleToString(getCount(getDisplayRow(i - 1)), 0) + ")", getCountWidth(), true); } else { line += padString("", getCountWidth(), true); } } else { // additional space before means if (isMean(n)) { line += " "; } // print cell if (getShowStdDev()) { if (isMean(n - 1)) { if (!cells[i][n].trim().equals("")) { line += "(" + cells[i][n] + ")"; } else { line += " " + cells[i][n] + " "; } } else { line += " " + cells[i][n]; } } else { line += " " + cells[i][n]; } } // add separator after base column if (n == indexBase) { line += " |"; } } // record overall length if (i == 1) { maxLength = line.length(); } body.append(line + "\n"); } // column names line = padString(cells[0][0], startMeans[0]); i = -1; for (n = 1; n < cells[0].length; n++) { if (isMean(n)) { i++; if (i == 0) { line = padString(line, startMeans[i] - getCountWidth()); } else if (i == 1) { line = padString(line, startMeans[i] - " |".length()); } else if (i > 1) { line = padString(line, startMeans[i]); } if (i == 1) { line += " |"; } line += " " + cells[0][n]; } } line = padString(line, maxLength); head.append(line + "\n"); head.append(line.replaceAll(".", "-") + "\n"); body.append(line.replaceAll(".", "-") + "\n"); // output wins/losses/ties if (getColCount() > 1) { line = padString(cells[cells.length - 1][0], startMeans[1] - 2, true) + " |"; i = 0; for (n = 1; n < cells[cells.length - 1].length; n++) { if (isSignificance(n)) { line = padString(line, startSigs[i] + 1 - cells[cells.length - 1][n].length()); line += " " + cells[cells.length - 1][n]; i++; } } line = padString(line, maxLength); } else { line = padString(cells[cells.length - 1][0], line.length() - 2) + " |"; } foot.append(line + "\n"); // assemble output result.append(head.toString()); result.append(body.toString()); result.append(foot.toString()); return result.toString(); } /** * returns returns a key for all the col names, for better readability if the * names got cut off. * * @return the key */ @Override public String toStringKey() { String result; int i; result = "Key:\n"; for (i = 0; i < getColCount(); i++) { if (getColHidden(i)) { continue; } result += LEFT_PARENTHESES + (i + 1) + RIGHT_PARENTHESES + " " + removeFilterName(m_ColNames[i]) + "\n"; } return result; } /** * returns the summary as string. * * @return the summary */ @Override public String toStringSummary() { String result; String titles; int resultsetLength; int i; int j; if (m_NonSigWins == null) { return "-summary data not set-"; } result = ""; titles = ""; resultsetLength = 1 + Math.max( (int) (Math.log(getColCount()) / Math.log(10)), (int) (Math.log(getRowCount()) / Math.log(10))); for (i = 0; i < getColCount(); i++) { if (getColHidden(i)) { continue; } titles += " " + Utils.padLeft("" + getSummaryTitle(i), resultsetLength * 2 + 3); } result += titles + " (No. of datasets where [col] >> [row])\n"; for (i = 0; i < getColCount(); i++) { if (getColHidden(i)) { continue; } for (j = 0; j < getColCount(); j++) { if (getColHidden(j)) { continue; } result += " "; if (j == i) { result += Utils.padLeft("-", resultsetLength * 2 + 3); } else { result += Utils.padLeft("" + m_NonSigWins[i][j] + " (" + m_Wins[i][j] + ")", resultsetLength * 2 + 3); } } result += " | " + getSummaryTitle(i) + " = " + getColName(i) + '\n'; } return result; } /** * returns the ranking in a string representation. * * @return the ranking */ @Override public String toStringRanking() { int biggest; int width; String result; int[] ranking; int i; int curr; if (m_RankingWins == null) { return "-ranking data not set-"; } biggest = Math.max(m_RankingWins[Utils.maxIndex(m_RankingWins)], m_RankingLosses[Utils.maxIndex(m_RankingLosses)]); width = Math.max(2 + (int) (Math.log(biggest) / Math.log(10)), ">-<".length()); result = Utils.padLeft(">-<", width) + ' ' + Utils.padLeft(">", width) + ' ' + Utils.padLeft("<", width) + " Resultset\n"; ranking = Utils.sort(m_RankingDiff); for (i = getColCount() - 1; i >= 0; i--) { curr = ranking[i]; if (getColHidden(curr)) { continue; } result += Utils.padLeft("" + m_RankingDiff[curr], width) + ' ' + Utils.padLeft("" + m_RankingWins[curr], width) + ' ' + Utils.padLeft("" + m_RankingLosses[curr], width) + ' ' + removeFilterName(m_ColNames[curr]) + '\n'; } return result; } /** * Returns the revision string. * * @return the revision */ @Override public String getRevision() { return RevisionUtils.extract("$Revision: 10204 $"); } /** * for testing only. * * @param args ignored */ public static void main(String[] args) { ResultMatrix matrix; int i; int n; matrix = new ResultMatrixPlainText(3, 3); // set header matrix.addHeader("header1", "value1"); matrix.addHeader("header2", "value2"); matrix.addHeader("header2", "value3"); // set values for (i = 0; i < matrix.getRowCount(); i++) { for (n = 0; n < matrix.getColCount(); n++) { matrix.setMean(n, i, (i + 1) * n); matrix.setStdDev(n, i, ((double) (i + 1) * n) / 100); if (i == n) { if (i % 2 == 1) { matrix.setSignificance(n, i, SIGNIFICANCE_WIN); } else { matrix.setSignificance(n, i, SIGNIFICANCE_LOSS); } } } } System.out.println("\n\n--> " + matrix.getDisplayName()); System.out.println("\n1. complete\n"); System.out.println(matrix.toStringHeader() + "\n"); System.out.println(matrix.toStringMatrix() + "\n"); System.out.println(matrix.toStringKey()); System.out.println("\n2. complete with std deviations\n"); matrix.setShowStdDev(true); System.out.println(matrix.toStringMatrix()); System.out.println("\n3. cols numbered\n"); matrix.setPrintColNames(false); System.out.println(matrix.toStringMatrix()); System.out.println("\n4. second col missing\n"); matrix.setColHidden(1, true); System.out.println(matrix.toStringMatrix()); System.out.println("\n5. last row missing, rows numbered too\n"); matrix.setRowHidden(2, true); matrix.setPrintRowNames(false); System.out.println(matrix.toStringMatrix()); System.out.println("\n6. mean prec to 3\n"); matrix.setMeanPrec(3); matrix.setPrintRowNames(false); System.out.println(matrix.toStringMatrix()); } }




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