/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
package smile.feature;
import org.junit.After;
import org.junit.AfterClass;
import org.junit.Before;
import org.junit.BeforeClass;
import org.junit.Test;
import static org.junit.Assert.*;
import smile.data.Attribute;
import smile.data.AttributeDataset;
import smile.data.NominalAttribute;
import smile.data.parser.ArffParser;
import smile.data.parser.DelimitedTextParser;
import smile.math.Math;
/**
*
* @author Haifeng Li
*/
public class NumericAttributeFeatureTest {
public NumericAttributeFeatureTest() {
}
@BeforeClass
public static void setUpClass() throws Exception {
}
@AfterClass
public static void tearDownClass() throws Exception {
}
@Before
public void setUp() {
}
@After
public void tearDown() {
}
/**
* Test of attributes method, of class NumericAttributeFeature.
*/
@SuppressWarnings("unused")
@Test
public void testAttributes() {
System.out.println("attributes");
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset data = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
double[][] x = data.toArray(new double[data.size()][]);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), NumericAttributeFeature.Scaling.LOGARITHM);
Attribute[] attributes = naf.attributes();
assertEquals(256, attributes.length);
for (int i = 0; i < attributes.length; i++) {
System.out.println(attributes[i]);
assertEquals(Attribute.Type.NUMERIC, attributes[i].getType());
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testNONE() {
System.out.println("NONE");
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset data = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
double[][] x = data.toArray(new double[data.size()][]);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), NumericAttributeFeature.Scaling.NONE);
Attribute[] attributes = naf.attributes();
assertEquals(256, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
assertEquals(x[i][j], y[j], 1E-7);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testLOGARITHM() {
System.out.println("LOGARITHM");
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset data = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
double[][] x = data.toArray(new double[data.size()][]);
for (int i = 0; i < x.length; i++) {
for (int j = 0; j < x[i].length; j++) {
x[i][j] += 2.0;
}
}
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), NumericAttributeFeature.Scaling.LOGARITHM);
Attribute[] attributes = naf.attributes();
assertEquals(256, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
assertEquals(Math.log(x[i][j]), y[j], 1E-7);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testNORMALIZATION() {
System.out.println("NORMALIZATION");
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset data = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
double[][] x = data.toArray(new double[data.size()][]);
double[] min = Math.colMin(x);
double[] max = Math.colMax(x);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), NumericAttributeFeature.Scaling.NORMALIZATION, x);
Attribute[] attributes = naf.attributes();
assertEquals(256, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
assertEquals((x[i][j]-min[j])/(max[j]-min[j]), y[j], 1E-7);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testSTANDARDIZATION() {
System.out.println("STANDARDIZATION");
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset data = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
double[][] x = data.toArray(new double[data.size()][]);
double[] mean = Math.colMean(x);
double[] sd = Math.colSd(x);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), NumericAttributeFeature.Scaling.STANDARDIZATION, x);
Attribute[] attributes = naf.attributes();
assertEquals(256, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
assertEquals((x[i][j]-mean[j])/sd[j], y[j], 1E-7);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testNORMALIZATIONWinsorization() {
System.out.println("NORMALIZATION Winsorization");
ArffParser parser = new ArffParser();
try {
AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/regression/abalone.arff"));
double[][] x = data.toArray(new double[data.size()][]);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), 0.05, 0.95, x);
Attribute[] attributes = naf.attributes();
assertEquals(data.attributes().length-1, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
assertTrue(y[j] <= 1.0 && y[j] >= 0.0);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
/**
* Test of f method, of class NumericAttributeFeature.
*/
@Test
public void testROBUSTSTANDARDIZATION() {
System.out.println("ROBUST STANDARDIZATION");
ArffParser parser = new ArffParser();
try {
AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/regression/abalone.arff"));
double[][] x = data.toArray(new double[data.size()][]);
NumericAttributeFeature naf = new NumericAttributeFeature(data.attributes(), x);
Attribute[] attributes = naf.attributes();
assertEquals(data.attributes().length-1, attributes.length);
for (int i = 0; i < x.length; i++) {
double[] y = new double[attributes.length];
for (int j = 0; j < y.length; j++) {
y[j] = naf.f(x[i], j);
}
}
} catch (Exception ex) {
System.err.println(ex);
}
}
}