com.clust4j.metrics.scoring.TestMetrics.java Source code

Introduction

Here is the source code for com.clust4j.metrics.scoring.TestMetrics.java

Source

/*******************************************************************************
 *    Copyright 2015, 2016 Taylor G Smith
 *
 *    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.clust4j.metrics.scoring;

import static org.junit.Assert.*;

import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.linear.Array2DRowRealMatrix;
import org.junit.Test;

import com.clust4j.TestSuite;
import com.clust4j.data.DataSet;
import com.clust4j.metrics.scoring.SupervisedMetric;
import com.clust4j.utils.VecUtils;

import static com.clust4j.metrics.scoring.UnsupervisedMetric.SILHOUETTE;

public class TestMetrics {
    final static DataSet IRIS = TestSuite.IRIS_DATASET.copy();

    @Test
    public void testAcc() {
        assertTrue(SupervisedMetric.BINOMIAL_ACCURACY.evaluate(new int[] { 1, 1, 1, 0 },
                new int[] { 1, 1, 1, 1 }) == 0.75);
    }

    @Test
    public void testSilhouetteScore() {
        Array2DRowRealMatrix X = IRIS.getData();
        final int[] labels = IRIS.getLabels();

        double silhouette = SILHOUETTE.evaluate(X, labels);
        assertTrue(silhouette == 0.5032506980665507);
    }

    @Test(expected = DimensionMismatchException.class)
    public void testSilhouetteScoreDME() {
        Array2DRowRealMatrix X = IRIS.getData();
        final int[] labels = new int[] { 1, 2, 3 };

        SILHOUETTE.evaluate(X, labels);
    }

    @Test
    public void testSilhouetteScoreNaN() {
        Array2DRowRealMatrix X = IRIS.getData();
        final int[] labels = VecUtils.repInt(1, X.getRowDimension());

        assertTrue(Double.isNaN(SILHOUETTE.evaluate(X, labels)));
    }

    @Test(expected = DimensionMismatchException.class)
    public void testDME() {
        SupervisedMetric.BINOMIAL_ACCURACY.evaluate(new int[] { 1, 2 }, new int[] { 1, 2, 3 });
    }

    @Test
    public void testIndexAffinityExceptionHandling() {
        final int[] a = new int[] { 0, 0, 0, 1, 1 };
        final int[] b = new int[] { 0, 0, 0, 1, 2 };

        boolean c = false;
        try {
            SupervisedMetric.INDEX_AFFINITY.evaluate(a, new int[] { 0, 0 });
        } catch (DimensionMismatchException d) {
            c = true;
        } finally {
            assertTrue(c);
        }

        c = false;
        try {
            SupervisedMetric.INDEX_AFFINITY.evaluate(new int[] {}, new int[] {});
        } catch (IllegalArgumentException d) {
            c = true;
        } finally {
            assertTrue(c);
        }

        c = false;
        try {
            SupervisedMetric.INDEX_AFFINITY.evaluate(a, b);
        } catch (IllegalArgumentException d) {
            c = true;
        } finally {
            assertTrue(c);
        }

        assertTrue(SupervisedMetric.INDEX_AFFINITY.evaluate(new int[] { 0 }, new int[] { 9 }) == 1.0);
        assertTrue(SupervisedMetric.INDEX_AFFINITY.evaluate(new int[] { 0, 1, 2 }, new int[] { 9, 5, 4 }) == 1.0);
    }
}