/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
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 http://www.gnu.org/licenses/
**********************************************************************/
package keel.Algorithms.RE_SL_Methods.P_FCS1;
/**
* <p>
* @author Written by Alberto Fern�ndez (University of Granada) 01/01/2007
* @author Modified by Francisco Jos� Berlanga (University of Ja�n) 09/12/2008
* @version 1.0
* @since JDK 1.6
* </p>
*/
import java.util.StringTokenizer;
import java.util.ArrayList;
import org.core.Files;
public class parseParameters {
/**
* <p>
* It reads the configuration file (data-set files and parameters)
* </p>
*/
private String algorithmName;
private String trainingFile, validationFile, testFile;
private ArrayList <String> inputFiles;
private String outputTrFile, outputTstFile;
private ArrayList <String> outputFiles;
private ArrayList <String> parameters;
/**
* <p>
* Default constructor
* </p>
*/
public parseParameters() {
inputFiles = new ArrayList<String>();
outputFiles = new ArrayList<String>();
parameters = new ArrayList<String>();
}
/**
* <p>
* It obtains all the necesary information from the configuration file.<br/>
* First of all it reads the name of the input data-sets, training, validation and test.<br/>
* Then it reads the name of the output files, where the training (validation) and test outputs will be stored<br/>
* Finally it read the parameters of the algorithm, such as the random seed.<br/>
* </p>
* @param fileName Name of the configuration file
*/
public void parseConfigurationFile(String fileName) {
StringTokenizer line;
String file = Files.readFile(fileName); //file is an string containing the whole file
line = new StringTokenizer(file, "\n\r");
readName(line); //We read the algorithm name
readInputFiles(line); //We read all the input files
readOutputFiles(line); //We read all the output files
readAllParameters(line); //We read all the possible parameters
};
/**
* <p>
* It reads the name of the algorithm from the configuration file
* @param line StringTokenizer It is the line containing the algorithm name.
* </p>
*/
private void readName(StringTokenizer line){
StringTokenizer data = new StringTokenizer(line.nextToken(), " = \" ");
data.nextToken();
algorithmName = new String(data.nextToken());
while(data.hasMoreTokens()){
algorithmName += " "+data.nextToken(); //We read the algorithm name
}
}
/**
* <p>
* We read the input data-set files and all the possible input files
* @param line StringTokenizer It is the line containing the input files.
* </p>
*/
private void readInputFiles(StringTokenizer line){
String new_line = line.nextToken(); //We read the input data line
StringTokenizer data = new StringTokenizer(new_line, " = \" ");
data.nextToken(); //inputFile
trainingFile = data.nextToken();
validationFile = data.nextToken();
testFile = data.nextToken();
while(data.hasMoreTokens()){
inputFiles.add(data.nextToken());
}
}
/**
* <p>
* We read the output files for training and test and all the possible remaining output files
* @param line StringTokenizer It is the line containing the output files.
* </p>
*/
private void readOutputFiles(StringTokenizer line){
String new_line = line.nextToken(); //We read the input data line
StringTokenizer data = new StringTokenizer(new_line, " = \" ");
data.nextToken(); //inputFile
outputTrFile = data.nextToken();
outputTstFile = data.nextToken();
while(data.hasMoreTokens()){
outputFiles.add(data.nextToken());
}
}
/**
* <p>
* We read all the possible parameters of the algorithm
* @param line StringTokenizer It contains all the parameters.
* </p>
*/
private void readAllParameters(StringTokenizer line){
String new_line,cadena;
StringTokenizer data;
while (line.hasMoreTokens()) { //While there is more parameters...
new_line = line.nextToken();
data = new StringTokenizer(new_line, " = ");
cadena = new String("");
while (data.hasMoreTokens()){
cadena = data.nextToken(); //parameter name
}
parameters.add(cadena); //parameter value
}
//If the algorithm is non-deterministic the first parameter is the Random SEED
}
/**
* <p>
* It returns the name of the file containing the training data
* @return String the name of the file containing the training data
* </p>
*/
public String getTrainingInputFile(){
return this.trainingFile;
}
/**
* <p>
* It returns the name of the file containing the test data
* @return String the name of the file containing the test data
* </p>
*/
public String getTestInputFile(){
return this.testFile;
}
/**
* <p>
* It returns the name of the file containing the validation data
* @return String the name of the file containing the validation data
* </p>
*/
public String getValidationInputFile(){
return this.validationFile;
}
/**
* <p>
* It returns the name of the file containing the output for the training data
* @return String the name of the file containing the output for the training data
* </p>
*/
public String getTrainingOutputFile(){
return this.outputTrFile;
}
/**
* <p>
* It returns the name of the file containing the output for the test data
* @return String the name of the file containing the output for the test data
* </p>
*/
public String getTestOutputFile(){
return this.outputTstFile;
}
/**
* <p>
* It returns the name of the algorithm
* @return String the name of the algorithm
* </p>
*/
public String getAlgorithmName(){
return this.algorithmName;
}
/**
* <p>
* It returns all the parameters as an array of Strings
* @return String [] all the parameters of the algorithm
* </p>
*/
public String [] getParameters(){
String [] param = (String []) parameters.toArray();
return param;
}
/**
* <p>
* It returns the parameter in the position "pos"
* @param pos int Position of the parameter
* @return String [] the parameter of the algorithm in position "pos"
* </p>
*/
public String getParameter(int pos){
return (String)parameters.get(pos);
}
/**
* <p>
* It returns all the input files
* @return String [] all the input files
* </p>
*/
public String [] getInputFiles(){
return (String []) inputFiles.toArray();
}
/**
* <p>
* It returns the input file in the position "pos"
* @param pos int Position of the input file
* @return String [] the input file of the algorithm in position "pos"
* </p>
*/
public String getInputFile(int pos){
return (String)this.inputFiles.get(pos);
}
/**
* <p>
* It returns all the output files
* @return String [] all the output files
* </p>
*/
public String [] getOutputFiles(){
return (String [])this.outputFiles.toArray();
}
/**
* <p>
* It returns the output file in the position "pos"
* @param pos int Position of the output file
* @return String [] the output file of the algorithm in position "pos"
* </p>
*/
public String getOutputFile(int pos){
return (String)this.outputFiles.get(pos);
}
}