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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.
*/
/*
* BinarySparseInstance.java
* Copyright (C) 2002 University of Waikato, Hamilton, New Zealand
*
*/
package weka.core;
import java.util.Enumeration;
/**
* Class for storing a binary-data-only instance as a sparse vector. A
* sparse instance only requires storage for those attribute values
* that are non-zero. Since the objective is to reduce storage
* requirements for datasets with large numbers of default values,
* this also includes nominal attributes -- the first nominal value
* (i.e. that which has index 0) will not require explicit storage, so
* rearrange your nominal attribute value orderings if
* necessary. Missing values are not supported, and will be treated as
* 1 (true).
*
* @version $Revision: 1.13 $
*/
public class BinarySparseInstance
extends SparseInstance {
/** for serialization */
private static final long serialVersionUID = -5297388762342528737L;
/**
* Constructor that generates a sparse instance from the given
* instance. Reference to the dataset is set to null.
* (ie. the instance doesn't have access to information about the
* attribute types)
*
* @param instance the instance from which the attribute values
* and the weight are to be copied
*/
public BinarySparseInstance(Instance instance) {
m_Weight = instance.m_Weight;
m_Dataset = null;
m_NumAttributes = instance.numAttributes();
if (instance instanceof SparseInstance) {
m_AttValues = null;
m_Indices = ((SparseInstance)instance).m_Indices;
} else {
int[] tempIndices = new int[instance.numAttributes()];
int vals = 0;
for (int i = 0; i < instance.numAttributes(); i++) {
if (instance.value(i) != 0) {
tempIndices[vals] = i;
vals++;
}
}
m_AttValues = null;
m_Indices = new int[vals];
System.arraycopy(tempIndices, 0, m_Indices, 0, vals);
}
}
/**
* Constructor that copies the info from the given instance.
* Reference to the dataset is set to null.
* (ie. the instance doesn't have access to information about the
* attribute types)
*
* @param instance the instance from which the attribute
* info is to be copied
*/
public BinarySparseInstance(SparseInstance instance) {
m_AttValues = null;
m_Indices = instance.m_Indices;
m_Weight = instance.m_Weight;
m_NumAttributes = instance.m_NumAttributes;
m_Dataset = null;
}
/**
* Constructor that generates a sparse instance from the given
* parameters. Reference to the dataset is set to null.
* (ie. the instance doesn't have access to information about the
* attribute types)
*
* @param weight the instance's weight
* @param attValues a vector of attribute values
*/
public BinarySparseInstance(double weight, double[] attValues) {
m_Weight = weight;
m_Dataset = null;
m_NumAttributes = attValues.length;
int[] tempIndices = new int[m_NumAttributes];
int vals = 0;
for (int i = 0; i < m_NumAttributes; i++) {
if (attValues[i] != 0) {
tempIndices[vals] = i;
vals++;
}
}
m_AttValues = null;
m_Indices = new int[vals];
System.arraycopy(tempIndices, 0, m_Indices, 0, vals);
}
/**
* Constructor that inititalizes instance variable with given
* values. Reference to the dataset is set to null. (ie. the instance
* doesn't have access to information about the attribute types)
*
* @param weight the instance's weight
* @param indices the indices of the given values in the full vector
* @param maxNumValues the maximium number of values that can be stored
*/
public BinarySparseInstance(double weight,
int[] indices, int maxNumValues) {
m_AttValues = null;
m_Indices = indices;
m_Weight = weight;
m_NumAttributes = maxNumValues;
m_Dataset = null;
}
/**
* Constructor of an instance that sets weight to one, all values to
* 1, and the reference to the dataset to null. (ie. the instance
* doesn't have access to information about the attribute types)
*
* @param numAttributes the size of the instance
*/
public BinarySparseInstance(int numAttributes) {
m_AttValues = null;
m_NumAttributes = numAttributes;
m_Indices = new int[numAttributes];
for (int i = 0; i < m_Indices.length; i++) {
m_Indices[i] = i;
}
m_Weight = 1;
m_Dataset = null;
}
/**
* Produces a shallow copy of this instance. The copy doesn't have
* access to a dataset.
*
* @return the shallow copy
*/
public Object copy() {
return new BinarySparseInstance(this);
}
/**
* Merges this instance with the given instance and returns
* the result. Dataset is set to null.
*
* @param inst the instance to be merged with this one
* @return the merged instances
*/
public Instance mergeInstance(Instance inst) {
int [] indices = new int [numValues() + inst.numValues()];
int m = 0;
for (int j = 0; j < numValues(); j++) {
indices[m++] = index(j);
}
for (int j = 0; j < inst.numValues(); j++) {
if (inst.valueSparse(j) != 0) {
indices[m++] = numAttributes() + inst.index(j);
}
}
if (m != indices.length) {
// Need to truncate
int [] newInd = new int [m];
System.arraycopy(indices, 0, newInd, 0, m);
indices = newInd;
}
return new BinarySparseInstance(1.0, indices, numAttributes() +
inst.numAttributes());
}
/**
* Does nothing, since we don't support missing values.
*
* @param array containing the means and modes
*/
public void replaceMissingValues(double[] array) {
// Does nothing, since we don't store missing values.
}
/**
* Sets a specific value in the instance to the given value
* (internal floating-point format). Performs a deep copy
* of the vector of attribute values before the value is set.
*
* @param attIndex the attribute's index
* @param value the new attribute value (If the corresponding
* attribute is nominal (or a string) then this is the new value's
* index as a double).
*/
public void setValue(int attIndex, double value) {
int index = locateIndex(attIndex);
if ((index >= 0) && (m_Indices[index] == attIndex)) {
if (value == 0) {
int[] tempIndices = new int[m_Indices.length - 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, index);
System.arraycopy(m_Indices, index + 1, tempIndices, index,
m_Indices.length - index - 1);
m_Indices = tempIndices;
}
} else {
if (value != 0) {
int[] tempIndices = new int[m_Indices.length + 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, index + 1);
tempIndices[index + 1] = attIndex;
System.arraycopy(m_Indices, index + 1, tempIndices, index + 2,
m_Indices.length - index - 1);
m_Indices = tempIndices;
}
}
}
/**
* Sets a specific value in the instance to the given value
* (internal floating-point format). Performs a deep copy
* of the vector of attribute values before the value is set.
*
* @param indexOfIndex the index of the attribute's index
* @param value the new attribute value (If the corresponding
* attribute is nominal (or a string) then this is the new value's
* index as a double).
*/
public void setValueSparse(int indexOfIndex, double value) {
if (value == 0) {
int[] tempIndices = new int[m_Indices.length - 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, indexOfIndex);
System.arraycopy(m_Indices, indexOfIndex + 1, tempIndices, indexOfIndex,
m_Indices.length - indexOfIndex - 1);
m_Indices = tempIndices;
}
}
/**
* Returns the values of each attribute as an array of doubles.
*
* @return an array containing all the instance attribute values
*/
public double[] toDoubleArray() {
double[] newValues = new double[m_NumAttributes];
for (int i = 0; i < m_Indices.length; i++) {
newValues[m_Indices[i]] = 1.0;
}
return newValues;
}
/**
* Returns the description of one instance in sparse format.
* If the instance doesn't have access to a dataset, it returns the
* internal floating-point values. Quotes string values that contain
* whitespace characters.
*
* @return the instance's description as a string
*/
public String toString() {
StringBuffer text = new StringBuffer();
text.append('{');
for (int i = 0; i < m_Indices.length; i++) {
if (i > 0) {
text.append(",");
}
if (m_Dataset == null) {
text.append(m_Indices[i] + " 1");
} else {
if (m_Dataset.attribute(m_Indices[i]).isNominal() ||
m_Dataset.attribute(m_Indices[i]).isString()) {
text.append(m_Indices[i] + " " +
Utils.quote(m_Dataset.attribute(m_Indices[i]).
value(1)));
} else {
text.append(m_Indices[i] + " 1");
}
}
}
text.append('}');
if (m_Weight != 1.0) {
text.append(",{" + Utils.doubleToString(m_Weight, 6) + "}");
}
return text.toString();
}
/**
* Returns an instance's attribute value in internal format.
*
* @param attIndex the attribute's index
* @return the specified value as a double (If the corresponding
* attribute is nominal (or a string) then it returns the value's index as a
* double).
*/
public double value(int attIndex) {
int index = locateIndex(attIndex);
if ((index >= 0) && (m_Indices[index] == attIndex)) {
return 1.0;
} else {
return 0.0;
}
}
/**
* Returns an instance's attribute value in internal format.
* Does exactly the same thing as value() if applied to an Instance.
*
* @param indexOfIndex the index of the attribute's index
* @return the specified value as a double (If the corresponding
* attribute is nominal (or a string) then it returns the value's index as a
* double).
*/
public final double valueSparse(int indexOfIndex) {
int index = m_Indices[indexOfIndex]; // Throws if out of bounds
return 1;
}
/**
* Deletes an attribute at the given position (0 to
* numAttributes() - 1).
*
* @param position the attribute's position
*/
void forceDeleteAttributeAt(int position) {
int index = locateIndex(position);
m_NumAttributes--;
if ((index >= 0) && (m_Indices[index] == position)) {
int[] tempIndices = new int[m_Indices.length - 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, index);
for (int i = index; i < m_Indices.length - 1; i++) {
tempIndices[i] = m_Indices[i + 1] - 1;
}
m_Indices = tempIndices;
} else {
int[] tempIndices = new int[m_Indices.length];
System.arraycopy(m_Indices, 0, tempIndices, 0, index + 1);
for (int i = index + 1; i < m_Indices.length - 1; i++) {
tempIndices[i] = m_Indices[i] - 1;
}
m_Indices = tempIndices;
}
}
/**
* Inserts an attribute at the given position
* (0 to numAttributes()) and sets its value to 1.
*
* @param position the attribute's position
*/
void forceInsertAttributeAt(int position) {
int index = locateIndex(position);
m_NumAttributes++;
if ((index >= 0) && (m_Indices[index] == position)) {
int[] tempIndices = new int[m_Indices.length + 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, index);
tempIndices[index] = position;
for (int i = index; i < m_Indices.length; i++) {
tempIndices[i + 1] = m_Indices[i] + 1;
}
m_Indices = tempIndices;
} else {
int[] tempIndices = new int[m_Indices.length + 1];
System.arraycopy(m_Indices, 0, tempIndices, 0, index + 1);
tempIndices[index + 1] = position;
for (int i = index + 1; i < m_Indices.length; i++) {
tempIndices[i + 1] = m_Indices[i] + 1;
}
m_Indices = tempIndices;
}
}
/**
* Main method for testing this class.
*
* @param options the command line options - ignored
*/
public static void main(String[] options) {
try {
// Create numeric attributes "length" and "weight"
Attribute length = new Attribute("length");
Attribute weight = new Attribute("weight");
// Create vector to hold nominal values "first", "second", "third"
FastVector my_nominal_values = new FastVector(3);
my_nominal_values.addElement("first");
my_nominal_values.addElement("second");
// Create nominal attribute "position"
Attribute position = new Attribute("position", my_nominal_values);
// Create vector of the above attributes
FastVector attributes = new FastVector(3);
attributes.addElement(length);
attributes.addElement(weight);
attributes.addElement(position);
// Create the empty dataset "race" with above attributes
Instances race = new Instances("race", attributes, 0);
// Make position the class attribute
race.setClassIndex(position.index());
// Create empty instance with three attribute values
BinarySparseInstance inst = new BinarySparseInstance(3);
// Set instance's values for the attributes "length", "weight", and "position"
inst.setValue(length, 5.3);
inst.setValue(weight, 300);
inst.setValue(position, "first");
// Set instance's dataset to be the dataset "race"
inst.setDataset(race);
// Print the instance
System.out.println("The instance: " + inst);
// Print the first attribute
System.out.println("First attribute: " + inst.attribute(0));
// Print the class attribute
System.out.println("Class attribute: " + inst.classAttribute());
// Print the class index
System.out.println("Class index: " + inst.classIndex());
// Say if class is missing
System.out.println("Class is missing: " + inst.classIsMissing());
// Print the instance's class value in internal format
System.out.println("Class value (internal format): " + inst.classValue());
// Print a shallow copy of this instance
SparseInstance copy = (SparseInstance) inst.copy();
System.out.println("Shallow copy: " + copy);
// Set dataset for shallow copy
copy.setDataset(inst.dataset());
System.out.println("Shallow copy with dataset set: " + copy);
// Print out all values in internal format
System.out.print("All stored values in internal format: ");
for (int i = 0; i < inst.numValues(); i++) {
if (i > 0) {
System.out.print(",");
}
System.out.print(inst.valueSparse(i));
}
System.out.println();
// Set all values to zero
System.out.print("All values set to zero: ");
while (inst.numValues() > 0) {
inst.setValueSparse(0, 0);
}
for (int i = 0; i < inst.numValues(); i++) {
if (i > 0) {
System.out.print(",");
}
System.out.print(inst.valueSparse(i));
}
System.out.println();
// Set all values to one
System.out.print("All values set to one: ");
for (int i = 0; i < inst.numAttributes(); i++) {
inst.setValue(i, 1);
}
for (int i = 0; i < inst.numValues(); i++) {
if (i > 0) {
System.out.print(",");
}
System.out.print(inst.valueSparse(i));
}
System.out.println();
// Unset dataset for copy, delete first attribute, and insert it again
copy.setDataset(null);
copy.deleteAttributeAt(0);
copy.insertAttributeAt(0);
copy.setDataset(inst.dataset());
System.out.println("Copy with first attribute deleted and inserted: " + copy);
// Same for second attribute
copy.setDataset(null);
copy.deleteAttributeAt(1);
copy.insertAttributeAt(1);
copy.setDataset(inst.dataset());
System.out.println("Copy with second attribute deleted and inserted: " + copy);
// Same for last attribute
copy.setDataset(null);
copy.deleteAttributeAt(2);
copy.insertAttributeAt(2);
copy.setDataset(inst.dataset());
System.out.println("Copy with third attribute deleted and inserted: " + copy);
// Enumerate attributes (leaving out the class attribute)
System.out.println("Enumerating attributes (leaving out class):");
Enumeration enu = inst.enumerateAttributes();
while (enu.hasMoreElements()) {
Attribute att = (Attribute) enu.nextElement();
System.out.println(att);
}
// Headers are equivalent?
System.out.println("Header of original and copy equivalent: " +
inst.equalHeaders(copy));
// Test for missing values
System.out.println("Length of copy missing: " + copy.isMissing(length));
System.out.println("Weight of copy missing: " + copy.isMissing(weight.index()));
System.out.println("Length of copy missing: " +
Instance.isMissingValue(copy.value(length)));
System.out.println("Missing value coded as: " + Instance.missingValue());
// Prints number of attributes and classes
System.out.println("Number of attributes: " + copy.numAttributes());
System.out.println("Number of classes: " + copy.numClasses());
// Replace missing values
double[] meansAndModes = {2, 3, 0};
copy.replaceMissingValues(meansAndModes);
System.out.println("Copy with missing value replaced: " + copy);
// Setting and getting values and weights
copy.setClassMissing();
System.out.println("Copy with missing class: " + copy);
copy.setClassValue(0);
System.out.println("Copy with class value set to first value: " + copy);
copy.setClassValue("second");
System.out.println("Copy with class value set to \"second\": " + copy);
copy.setMissing(1);
System.out.println("Copy with second attribute set to be missing: " + copy);
copy.setMissing(length);
System.out.println("Copy with length set to be missing: " + copy);
copy.setValue(0, 0);
System.out.println("Copy with first attribute set to 0: " + copy);
copy.setValue(weight, 1);
System.out.println("Copy with weight attribute set to 1: " + copy);
copy.setValue(position, "second");
System.out.println("Copy with position set to \"second\": " + copy);
copy.setValue(2, "first");
System.out.println("Copy with last attribute set to \"first\": " + copy);
System.out.println("Current weight of instance copy: " + copy.weight());
copy.setWeight(2);
System.out.println("Current weight of instance copy (set to 2): " + copy.weight());
System.out.println("Last value of copy: " + copy.toString(2));
System.out.println("Value of position for copy: " + copy.toString(position));
System.out.println("Last value of copy (internal format): " + copy.value(2));
System.out.println("Value of position for copy (internal format): " +
copy.value(position));
} catch (Exception e) {
e.printStackTrace();
}
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.13 $");
}
}
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