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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This is the stable version. Apart from bugfixes, this version
does not receive any other updates.
/*
* 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.
*/
/*
* ResultMatrixPlainText.java
* Copyright (C) 2005 University of Waikato, Hamilton, New Zealand
*
*/
package weka.experiment;
import weka.core.RevisionUtils;
import weka.core.Utils;
/**
* This matrix is a container for the datasets and classifier setups and
* their statistics. It outputs the matrix in plain text (columns).
*
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision: 1.8 $
*/
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
*/
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 the name of the output format
*/
public String getDisplayName() {
return "Plain Text";
}
/**
* removes the stored data but retains the dimensions of the matrix
*/
public void clear() {
super.clear();
setRowNameWidth(25);
setCountWidth(5);
}
/**
* returns the header of the matrix as a string
* @see #m_HeaderKeys
* @see #m_HeaderValues
*/
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
*/
public String toStringMatrix() {
StringBuffer result;
String[][] cells;
int i;
int j;
int n;
int k;
int size;
String line;
int indexBase;
int indexSecond;
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++;
// index of second column in array
indexSecond = indexBase + 1;
if (getShowStdDev())
indexSecond++;
// 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
*/
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
*/
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
*/
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
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.8 $");
}
/**
* for testing only
*/
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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