/***********************************************************************
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.UnsupervisedLearning.AssociationRules.IntervalRuleLearning.MODENAR;
import java.io.IOException;
import keel.Dataset.*;
public class myDataset {
public static final int NOMINAL = 0;
public static final int INTEGER = 1;
public static final int REAL = 2;
private double[][] realTransactions = null; //transactions array
private boolean[][] missing = null; //possible missing values
private int[] type = null; //possible missing values
private double[] emax; //max value of an attribute
private double[] emin; //min value of an attribute
private int nTrans; // Number of transactions
private int nInputs; // Number of inputs
private int nOutputs; // Number of outputs
private int nVars; // Number of variables
private InstanceSet IS; //The whole instance set
/**
* Init a new set of instances
*/
public myDataset() {
IS = new InstanceSet();
}
/**
* Outputs an array of transactions with their corresponding attribute values.
* @return double[][] an array of transactions with their corresponding attribute values
*/
public double[][] getRealTransactions() {
return realTransactions;
}
/**
* It returns an array with the maximum values of the attributes
* @return double[] an array with the maximum values of the attributes
*/
public double[] getemax() {
return emax;
}
/**
* It returns an array with the minimum values of the attributes
* @return double[] an array with the minimum values of the attributes
*/
public double[] getemin() {
return emin;
}
/**
* It returns the upper bound of the variable
* @param variable Id otf the attribute
* @return double the upper bound of the variable
*/
public double getMax(int variable) {
return emax[variable];
}
/**
* It returns the lower bound of the variable
* @param variable Id of the attribute
* @return double the lower bound of the variable
*/
public double getMin(int variable) {
return emin[variable];
}
/**
* It gets the size of the data-set
* @return int the number of transactions in the data-set
*/
public int getnTrans() {
return nTrans;
}
/**
* It gets the number of variables of the data-set
* @return int the number of variables of the data-set
*/
public int getnVars() {
return nVars;
}
/**
* This function checks if the attribute value is missing
* @param i int Example id
* @param j int Variable id
* @return boolean True is the value is missing, else it returns false
*/
public boolean isMissing(int i, int j) {
return missing[i][j];
}
/**
* This function checks if the attribute value is missing
* @param i int Example id
* @param j int Variable id
* @return boolean True is the value is missing, else it returns false
*/
public boolean isNominal(int i) {
if (type[i] != myDataset.NOMINAL) return (false);
else return (true);
}
/**
* It reads the whole input data-set and it stores each transaction in
* local array
* @param datasetFile String name of the file containing the data-set
* @throws IOException If there occurs any problem with the reading of the data-set
*/
public void readDataSet(String datasetFile) throws
IOException {
int i, j, k;
try {
// Load in memory a data-set that contains a Frequent Items Mining problem
IS.readSet(datasetFile, true);
this.nTrans = IS.getNumInstances();
this.nInputs = Attributes.getInputNumAttributes();
this.nOutputs = Attributes.getOutputNumAttributes();
this.nVars = this.nInputs + this.nOutputs;
// Initialize and fill our own tables
realTransactions = new double[nTrans][nVars];
missing = new boolean[nTrans][nVars];
type = new int[nVars];
// Maximum and minimum of inputs
emax = new double[nVars];
emin = new double[nVars];
for (i = 0; i < nVars; i++) {
type[i] = Attributes.getAttribute(i).getType();
if (type[i] != myDataset.NOMINAL ) {
emax[i] = Attributes.getAttribute(i).getMaxAttribute();
emin[i] = Attributes.getAttribute(i).getMinAttribute();
}
else {
emin[i] = 0;
emax[i] = Attributes.getAttribute(i).getNumNominalValues() - 1;
}
}
// All values are casted into double/integer
for (i=0; i < nTrans; i++) {
Instance inst = IS.getInstance(i);
for (j=0; j < nInputs; j++) {
realTransactions[i][j] = IS.getInputNumericValue(i, j);
missing[i][j] = inst.getInputMissingValues(j);
if (missing[i][j]) realTransactions[i][j] = emin[j] - 1;
}
if (this.nOutputs > 0) {
for (k=0; k < this.nOutputs; k++, j++) {
realTransactions[i][j] = IS.getOutputNumericValue(i, k);
/*missing[i][j] = inst.getInputMissingValues(j);
if (missing[i][j]) realTransactions[i][j] = emin[j] - 1;*/
}
}
}
}
catch (Exception e) {
System.out.println("DBG: Exception in readSet");
e.printStackTrace();
}
}
/**
* Devuelve el universo de discuros de las variables de entrada y salida
* @return double[][] El rango minimo y maximo de cada variable
*/
public double [][] getRanks() {
int i, j;
double [][] ranks = new double[this.getnVars()][2];
for (i = 0; i < this.nInputs; i++){
if (Attributes.getInputAttribute(i).getNumNominalValues() > 0){
ranks[i][0] = 0;
ranks[i][1] = Attributes.getInputAttribute(i).getNumNominalValues()-1;
}else{
ranks[i][0] = Attributes.getInputAttribute(i).getMinAttribute();
ranks[i][1] = Attributes.getInputAttribute(i).getMaxAttribute();
}
}
for (j = 0; j < this.nOutputs; j++, i++){
if (Attributes.getOutputAttribute(j).getNumNominalValues() > 0){
ranks[i][0] = 0;
ranks[i][1] = Attributes.getOutputAttribute(j).getNumNominalValues()-1;
}else{
ranks[i][0] = Attributes.getOutputAttribute(j).getMinAttribute();
ranks[i][1] = Attributes.getOutputAttribute(j).getMaxAttribute();
}
}
return ranks;
}
/**
* It checks if the data-set has any real value
* @return boolean True if it has some real values, else false.
*/
public boolean hasRealAttributes() {
return Attributes.hasRealAttributes();
}
/**
* It checks if the data-set has any numerical value (real or integer)
* @return boolean True if it has some numerical values, else false.
*/
public boolean hasNumericalAttributes() {
return (Attributes.hasIntegerAttributes() ||
Attributes.hasRealAttributes());
}
/**
* It checks if the data-set has any missing value
* @return boolean True if it has some missing values, else false.
*/
public boolean hasMissingAttributes() {
return (this.sizeWithoutMissing() < this.getnTrans());
}
/**
* It return the size of the data-set without having account the missing values
* @return int the size of the data-set without having account the missing values
*/
public int sizeWithoutMissing() {
int tam = 0;
for (int i = 0; i < nTrans; i++) {
int j;
for (j = 1; (j < nVars) && (!isMissing(i, j)); j++) {
;
}
if (j == nVars) {
tam++;
}
}
return tam;
}
/**
* It returns the number of different values in the case of a nominal variable
* @param attribute Id of the variable
* @return the number of different values in the case of a nominal variable
*/
public int numberValues(int attribute) {
return Attributes.getInputAttribute(attribute).getNumNominalValues();
}
/**
* It returns an array indicating the position of the missing values on a specific example
* @param pos int Id of the example
* @return boolean[] an array indicating the position of the missing values on the example
*/
public boolean [] getMissing(int pos){
return this.missing[pos];
}
/**
* It returns the names of the variables
* @return String[] an array with the names of the variables
*/
public String[] names() {
String nombres[] = new String[nVars];
for (int i = 0; i < nVars; i++) {
nombres[i] = Attributes.getInputAttribute(i).getName();
}
return nombres;
}
/**
* It returns the name of the variable in "pos"
* @param pos int Id of the variable
* @return String the name of the attribute
*/
public String getNameVar(int pos) {
return Attributes.getInputAttribute(pos).getName();
}
/**
* It returns the type of the attribute in "n_attr"
* @param n_attr int Id of the attribute
* @return int the type of the attribute
*/
public int getAttributeType(int n_attr) {
if (Attributes.getAttribute(n_attr).getType() == Attributes.getAttribute(0).INTEGER) return this.INTEGER;
if (Attributes.getAttribute(n_attr).getType() == Attributes.getAttribute(0).REAL) return this.REAL;
if (Attributes.getAttribute(n_attr).getType() == Attributes.getAttribute(0).NOMINAL) return this.NOMINAL;
return (-1);
}
}