/*******************************************************************************
* 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.neighbor;
import java.io.BufferedReader;
import java.util.ArrayList;
import java.util.List;
import org.junit.After;
import org.junit.AfterClass;
import org.junit.Before;
import org.junit.BeforeClass;
import org.junit.Test;
import smile.data.AttributeDataset;
import smile.data.NominalAttribute;
import smile.data.parser.DelimitedTextParser;
import smile.math.Math;
import smile.math.distance.EditDistance;
import smile.math.distance.EuclideanDistance;
import smile.stat.distribution.MultivariateGaussianDistribution;
/**
*
* @author Haifeng Li
*/
public class LinearSearchSpeedTest {
public LinearSearchSpeedTest() {
}
@BeforeClass
public static void setUpClass() throws Exception {
}
@AfterClass
public static void tearDownClass() throws Exception {
}
@Before
public void setUp() {
}
@After
public void tearDown() {
}
/**
* Test of range method, of class LinearSearch.
*/
@Test
public void testString() {
System.out.println("string");
List<String> words = new ArrayList<>();
long start = System.currentTimeMillis();
try {
BufferedReader input = smile.data.parser.IOUtils.getTestDataReader("neighbor/index.noun");
String line = input.readLine();
while (line != null) {
if (!line.startsWith(" ")) {
String[] w = line.split("\\s");
words.add(w[0].replace('_', ' '));
}
line = input.readLine();
}
} catch (Exception e) {
System.err.println(e);
}
double time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Loading string data: %.2fs%n", time);
String[] data = words.toArray(new String[words.size()]);
LinearSearch<String> naive = new LinearSearch<>(data, new EditDistance(50, true));
start = System.currentTimeMillis();
List<Neighbor<String, String>> neighbors = new ArrayList<>();
for (int i = 1000; i < 1100; i++) {
naive.range(words.get(i), 1, neighbors);
neighbors.clear();
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Linear string search: %.2fs%n", time);
}
/**
* Test of nearest method, of class LinearSearch.
*/
@Test
public void testToy() {
System.out.println("toy data");
long start = System.currentTimeMillis();
double[] mu1 = {1.0, 1.0, 1.0};
double[][] sigma1 = {{1.0, 0.0, 0.0}, {0.0, 1.0, 0.0}, {0.0, 0.0, 1.0}};
double[] mu2 = {-2.0, -2.0, -2.0};
double[][] sigma2 = {{1.0, 0.3, 0.8}, {0.3, 1.0, 0.5}, {0.8, 0.5, 1.0}};
double[] mu3 = {4.0, 2.0, 3.0};
double[][] sigma3 = {{1.0, 0.8, 0.3}, {0.8, 1.0, 0.5}, {0.3, 0.5, 1.0}};
double[] mu4 = {3.0, 5.0, 1.0};
double[][] sigma4 = {{1.0, 0.5, 0.5}, {0.5, 1.0, 0.5}, {0.5, 0.5, 1.0}};
double[][] data = new double[10000][];
MultivariateGaussianDistribution g1 = new MultivariateGaussianDistribution(mu1, sigma1);
for (int i = 0; i < 2000; i++) {
data[i] = g1.rand();
}
MultivariateGaussianDistribution g2 = new MultivariateGaussianDistribution(mu2, sigma2);
for (int i = 0; i < 3000; i++) {
data[2000 + i] = g2.rand();
}
MultivariateGaussianDistribution g3 = new MultivariateGaussianDistribution(mu3, sigma3);
for (int i = 0; i < 3000; i++) {
data[5000 + i] = g3.rand();
}
MultivariateGaussianDistribution g4 = new MultivariateGaussianDistribution(mu4, sigma4);
for (int i = 0; i < 2000; i++) {
data[8000 + i] = g4.rand();
}
double time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Generating toy data (four Gaussians): %.2fs%n", time);
LinearSearch<double[]> naive = new LinearSearch<>(data, new EuclideanDistance());
start = System.currentTimeMillis();
for (int i = 0; i < 1000; i++) {
naive.nearest(data[Math.randomInt(data.length)]);
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("NN: %.2fs%n", time);
start = System.currentTimeMillis();
for (int i = 0; i < 1000; i++) {
naive.knn(data[Math.randomInt(data.length)], 10);
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("10-NN: %.2fs%n", time);
start = System.currentTimeMillis();
List<Neighbor<double[], double[]>> n = new ArrayList<>();
for (int i = 0; i < 1000; i++) {
naive.range(data[Math.randomInt(data.length)], 1.0, n);
n.clear();
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Range: %.2fs%n", time);
}
/**
* Test of nearest method, of class LinearSearch.
*/
@Test
public void testUSPS() {
System.out.println("USPS");
double[][] x = null;
double[][] testx = null;
long start = System.currentTimeMillis();
DelimitedTextParser parser = new DelimitedTextParser();
parser.setResponseIndex(new NominalAttribute("class"), 0);
try {
AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
x = train.toArray(new double[train.size()][]);
testx = test.toArray(new double[test.size()][]);
} catch (Exception ex) {
System.err.println(ex);
}
double time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Loading USPS: %.2fs%n", time);
LinearSearch<double[]> naive = new LinearSearch<>(x, new EuclideanDistance());
start = System.currentTimeMillis();
for (int i = 0; i < testx.length; i++) {
naive.nearest(testx[i]);
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("NN: %.2fs%n", time);
start = System.currentTimeMillis();
for (int i = 0; i < testx.length; i++) {
naive.knn(testx[i], 10);
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("10-NN: %.2fs%n", time);
start = System.currentTimeMillis();
List<Neighbor<double[], double[]>> n = new ArrayList<>();
for (int i = 0; i < testx.length; i++) {
naive.range(testx[i], 8.0, n);
n.clear();
}
time = (System.currentTimeMillis() - start) / 1000.0;
System.out.format("Range: %.2fs%n", time);
}
}