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/*
* Copyright (C) 2017 The Android Open Source Project
*
* 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 com.android.internal.ml.clustering;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
import android.annotation.SuppressLint;
import androidx.test.filters.SmallTest;
import androidx.test.runner.AndroidJUnit4;
import org.junit.Assert;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import java.util.Arrays;
import java.util.List;
import java.util.Random;
@SmallTest
@RunWith(AndroidJUnit4.class)
public class KMeansTest {
// Error tolerance (epsilon)
private static final double EPS = 0.01;
private KMeans mKMeans;
@Before
public void setUp() {
// Setup with a random seed to have predictable results
mKMeans = new KMeans(new Random(0), 30, 0);
}
@Test
public void getCheckDataSanityTest() {
try {
mKMeans.checkDataSetSanity(new float[][] {
{0, 1, 2},
{1, 2, 3}
});
} catch (IllegalArgumentException e) {
Assert.fail("Valid data didn't pass sanity check");
}
try {
mKMeans.checkDataSetSanity(new float[][] {
null,
{1, 2, 3}
});
Assert.fail("Data has null items and passed");
} catch (IllegalArgumentException e) {}
try {
mKMeans.checkDataSetSanity(new float[][] {
{0, 1, 2, 4},
{1, 2, 3}
});
Assert.fail("Data has invalid shape and passed");
} catch (IllegalArgumentException e) {}
try {
mKMeans.checkDataSetSanity(null);
Assert.fail("Null data should throw exception");
} catch (IllegalArgumentException e) {}
}
@Test
public void sqDistanceTest() {
float a[] = {4, 10};
float b[] = {5, 2};
float sqDist = (float) (Math.pow(a[0] - b[0], 2) + Math.pow(a[1] - b[1], 2));
assertEquals("Squared distance not valid", mKMeans.sqDistance(a, b), sqDist, EPS);
}
@Test
public void nearestMeanTest() {
KMeans.Mean meanA = new KMeans.Mean(0, 1);
KMeans.Mean meanB = new KMeans.Mean(1, 1);
List<KMeans.Mean> means = Arrays.asList(meanA, meanB);
KMeans.Mean nearest = mKMeans.nearestMean(new float[] {1, 1}, means);
assertEquals("Unexpected nearest mean for point {1, 1}", nearest, meanB);
}
@SuppressLint("DefaultLocale")
@Test
public void scoreTest() {
List<KMeans.Mean> closeMeans = Arrays.asList(new KMeans.Mean(0, 0.1f, 0.1f),
new KMeans.Mean(0, 0.1f, 0.15f),
new KMeans.Mean(0.1f, 0.2f, 0.1f));
List<KMeans.Mean> farMeans = Arrays.asList(new KMeans.Mean(0, 0, 0),
new KMeans.Mean(0, 0.5f, 0.5f),
new KMeans.Mean(1, 0.9f, 0.9f));
double closeScore = KMeans.score(closeMeans);
double farScore = KMeans.score(farMeans);
assertTrue(String.format("Score of well distributed means should be greater than "
+ "close means but got: %f, %f", farScore, closeScore), farScore > closeScore);
}
@Test
public void predictTest() {
float[] expectedCentroid1 = {1, 1, 1};
float[] expectedCentroid2 = {0, 0, 0};
float[][] X = new float[][] {
{1, 1, 1},
{1, 1, 1},
{1, 1, 1},
{0, 0, 0},
{0, 0, 0},
{0, 0, 0},
};
final int numClusters = 2;
// Here we assume that we won't get stuck into a local optima.
// It's fine because we're seeding a random, we won't ever have
// unstable results but in real life we need multiple initialization
// and score comparison
List<KMeans.Mean> means = mKMeans.predict(numClusters, X);
assertEquals("Expected number of clusters is invalid", numClusters, means.size());
boolean exists1 = false, exists2 = false;
for (KMeans.Mean mean : means) {
if (Arrays.equals(mean.getCentroid(), expectedCentroid1)) {
exists1 = true;
} else if (Arrays.equals(mean.getCentroid(), expectedCentroid2)) {
exists2 = true;
} else {
throw new AssertionError("Unexpected mean: " + mean);
}
}
assertTrue("Expected means were not predicted, got: " + means,
exists1 && exists2);
}
}
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