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Stefan Hahmann
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Add unit tests for BranchPcaFeature and SpotPcaFeature
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‎src/test/java/org/mastodon/mamut/feature/branch/dimensionalityreduction/pca/BranchPcaFeatureTest.java‎

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/*-
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* #%L
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* mastodon-deep-lineage
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* %%
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* Copyright (C) 2022 - 2024 Stefan Hahmann
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package org.mastodon.mamut.feature.branch.dimensionalityreduction.pca;
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import static org.junit.jupiter.api.Assertions.assertFalse;
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import static org.junit.jupiter.api.Assertions.assertNotEquals;
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import static org.junit.jupiter.api.Assertions.assertNotNull;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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import java.io.IOException;
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import java.util.Collections;
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import java.util.Iterator;
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import java.util.List;
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import java.util.function.Supplier;
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import net.imglib2.util.Cast;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.Test;
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import org.mastodon.feature.Dimension;
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import org.mastodon.feature.FeatureModel;
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import org.mastodon.feature.FeatureProjection;
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import org.mastodon.feature.FeatureProjectionSpec;
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import org.mastodon.mamut.feature.AbstractFeatureTest;
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import org.mastodon.mamut.feature.FeatureComputerTestUtils;
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import org.mastodon.mamut.feature.FeatureSerializerTestUtils;
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import org.mastodon.mamut.feature.FeatureUtils;
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import org.mastodon.mamut.feature.branch.BranchDisplacementDurationFeature;
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import org.mastodon.mamut.feature.branch.exampleGraph.ExampleGraph7;
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import org.mastodon.mamut.feature.branch.sinuosity.BranchSinuosityFeature;
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import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionAlgorithm;
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import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionController;
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import org.mastodon.mamut.feature.dimensionalityreduction.util.InputDimension;
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import org.mastodon.mamut.model.Model;
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import org.mastodon.mamut.model.branch.BranchLink;
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import org.mastodon.mamut.model.branch.BranchSpot;
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import org.scijava.Context;
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public class BranchPcaFeatureTest extends AbstractFeatureTest< BranchSpot >
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{
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private BranchPcaFeature pcaFeature;
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private final ExampleGraph7 graph7 = new ExampleGraph7();
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private FeatureProjectionSpec spec0;
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private FeatureProjectionSpec spec1;
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@BeforeEach
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public void setUp()
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{
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try (Context context = new Context())
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{
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Model model = graph7.getModel();
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FeatureModel featureModel = model.getFeatureModel();
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// declare some features as input dimensions
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BranchDisplacementDurationFeature branchDisplacementDurationFeature = Cast.unchecked(
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FeatureComputerTestUtils.getFeature( context, model, BranchDisplacementDurationFeature.SPEC ) );
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featureModel.declareFeature( branchDisplacementDurationFeature );
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BranchSinuosityFeature branchSinuosityFeature = Cast.unchecked(
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FeatureComputerTestUtils.getFeature( context, model, BranchSinuosityFeature.BRANCH_SINUOSITY_FEATURE_SPEC ) );
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featureModel.declareFeature( branchSinuosityFeature );
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List< InputDimension< BranchSpot > > inputDimensions =
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InputDimension.getListFromFeatureModel( featureModel, BranchSpot.class, BranchLink.class );
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// set up the controller and compute the feature
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Supplier< List< InputDimension< BranchSpot > > > inputDimensionsSupplier = () -> inputDimensions;
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DimensionalityReductionController controller = new DimensionalityReductionController( graph7.getModel(), context );
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controller.setModelGraph( false );
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controller.setAlgorithm( DimensionalityReductionAlgorithm.PCA );
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controller.computeFeature( inputDimensionsSupplier );
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pcaFeature = FeatureUtils.getFeature( graph7.getModel(), BranchPcaFeature.BranchSpotPcaFeatureSpec.class );
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assertNotNull( pcaFeature );
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spec0 = new FeatureProjectionSpec( pcaFeature.getProjectionName( 0 ), Dimension.NONE );
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spec1 = new FeatureProjectionSpec( pcaFeature.getProjectionName( 1 ), Dimension.NONE );
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}
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}
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@Test
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@Override
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public void testFeatureComputation()
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{
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assertNotNull( pcaFeature );
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FeatureProjection< BranchSpot > projection0 = getProjection( pcaFeature, spec0 );
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FeatureProjection< BranchSpot > projection1 = getProjection( pcaFeature, spec1 );
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Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
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BranchSpot branchSpot = branchSpotIterator.next();
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assertFalse( Double.isNaN( projection0.value( branchSpot ) ) );
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assertNotEquals( 0, projection0.value( branchSpot ) );
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assertFalse( Double.isNaN( projection1.value( branchSpot ) ) );
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assertNotEquals( 0, projection1.value( branchSpot ) );
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}
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@Test
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@Override
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public void testFeatureSerialization() throws IOException
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{
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BranchPcaFeature pcaFeatureReloaded;
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try (Context context = new Context())
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{
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pcaFeatureReloaded =
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( BranchPcaFeature ) FeatureSerializerTestUtils.saveAndReload( context, graph7.getModel(), this.pcaFeature );
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}
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assertNotNull( pcaFeatureReloaded );
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Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
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BranchSpot branchSpot = branchSpotIterator.next();
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// check that the feature has correct values after saving and reloading
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assertTrue( FeatureSerializerTestUtils.checkFeatureProjectionEquality( this.pcaFeature, pcaFeatureReloaded,
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Collections.singleton( branchSpot ) ) );
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}
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@Test
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@Override
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public void testFeatureInvalidate()
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{
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Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
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BranchSpot branchSpot = branchSpotIterator.next();
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// test, if features are not NaN before invalidation
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assertFalse( Double.isNaN( getProjection( pcaFeature, spec0 ).value( branchSpot ) ) );
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assertFalse( Double.isNaN( getProjection( pcaFeature, spec1 ).value( branchSpot ) ) );
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// invalidate feature
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pcaFeature.invalidate( branchSpot );
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// test, if features are NaN after invalidation
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assertTrue( Double.isNaN( getProjection( pcaFeature, spec0 ).value( branchSpot ) ) );
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assertTrue( Double.isNaN( getProjection( pcaFeature, spec1 ).value( branchSpot ) ) );
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}
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}

‎src/test/java/org/mastodon/mamut/feature/spot/dimensionalityreduction/pca/SpotPcaFeatureTest.java‎

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/*-
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* #%L
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* mastodon-deep-lineage
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* %%
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* Copyright (C) 2022 - 2024 Stefan Hahmann
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package org.mastodon.mamut.feature.spot.dimensionalityreduction.pca;
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import static org.junit.jupiter.api.Assertions.assertFalse;
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import static org.junit.jupiter.api.Assertions.assertNotEquals;
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import static org.junit.jupiter.api.Assertions.assertNotNull;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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import java.io.IOException;
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import java.util.Collections;
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import java.util.Iterator;
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import java.util.List;
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import java.util.function.Supplier;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.Test;
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import org.mastodon.feature.Dimension;
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import org.mastodon.feature.FeatureModel;
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import org.mastodon.feature.FeatureProjection;
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import org.mastodon.feature.FeatureProjectionSpec;
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import org.mastodon.mamut.feature.AbstractFeatureTest;
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import org.mastodon.mamut.feature.FeatureSerializerTestUtils;
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import org.mastodon.mamut.feature.FeatureUtils;
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import org.mastodon.mamut.feature.branch.exampleGraph.ExampleGraph7;
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import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionAlgorithm;
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import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionController;
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import org.mastodon.mamut.feature.dimensionalityreduction.util.InputDimension;
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import org.mastodon.mamut.model.Link;
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import org.mastodon.mamut.model.Spot;
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import org.scijava.Context;
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public class SpotPcaFeatureTest extends AbstractFeatureTest< Spot >
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{
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private SpotPcaFeature spotPcaFeature;
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private final ExampleGraph7 graph7 = new ExampleGraph7();
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private FeatureProjectionSpec spec0;
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private FeatureProjectionSpec spec1;
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@BeforeEach
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public void setUp()
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{
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try (Context context = new Context())
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{
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FeatureModel featureModel = graph7.getModel().getFeatureModel();
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DimensionalityReductionController controller = new DimensionalityReductionController( graph7.getModel(), context );
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controller.setAlgorithm( DimensionalityReductionAlgorithm.PCA );
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Supplier< List< InputDimension< Spot > > > inputDimensionsSupplier =
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() -> InputDimension.getListFromFeatureModel( featureModel, Spot.class, Link.class );
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controller.computeFeature( inputDimensionsSupplier );
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spotPcaFeature = FeatureUtils.getFeature( graph7.getModel(), SpotPcaFeature.SpotPcaFeatureSpec.class );
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assertNotNull( spotPcaFeature );
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spec0 = new FeatureProjectionSpec( spotPcaFeature.getProjectionName( 0 ), Dimension.NONE );
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spec1 = new FeatureProjectionSpec( spotPcaFeature.getProjectionName( 1 ), Dimension.NONE );
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}
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}
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@Test
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@Override
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public void testFeatureComputation()
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{
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assertNotNull( spotPcaFeature );
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FeatureProjection< Spot > projection0 = getProjection( spotPcaFeature, spec0 );
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FeatureProjection< Spot > projection1 = getProjection( spotPcaFeature, spec1 );
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Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
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Spot spot0 = spotIterator.next();
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assertTrue( Double.isNaN( projection0.value( spot0 ) ) );
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assertTrue( Double.isNaN( projection1.value( spot0 ) ) );
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Spot spot1 = spotIterator.next();
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assertFalse( Double.isNaN( projection0.value( spot1 ) ) );
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assertFalse( Double.isNaN( projection1.value( spot1 ) ) );
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assertNotEquals( 0, projection0.value( spot1 ) );
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assertNotEquals( 0, projection1.value( spot1 ) );
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}
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@Test
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@Override
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public void testFeatureSerialization() throws IOException
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{
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SpotPcaFeature spotPcaFeatureReloaded;
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try (Context context = new Context())
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{
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spotPcaFeatureReloaded =
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( SpotPcaFeature ) FeatureSerializerTestUtils.saveAndReload( context, graph7.getModel(), spotPcaFeature );
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}
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assertNotNull( spotPcaFeatureReloaded );
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// check that the feature has correct values after saving and reloading
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Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
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spotIterator.next();
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Spot spot1 = spotIterator.next();
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assertTrue( FeatureSerializerTestUtils.checkFeatureProjectionEquality(
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spotPcaFeature, spotPcaFeatureReloaded,
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Collections.singleton( spot1 ) ) );
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}
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@Test
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@Override
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public void testFeatureInvalidate()
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{
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// test, if features are not NaN before invalidation
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Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
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spotIterator.next();
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Spot spot1 = spotIterator.next();
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assertFalse( Double.isNaN( getProjection( spotPcaFeature, spec0 ).value( spot1 ) ) );
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assertFalse( Double.isNaN( getProjection( spotPcaFeature, spec1 ).value( spot1 ) ) );
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// invalidate feature
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spotPcaFeature.invalidate( spot1 );
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// test, if features are NaN after invalidation
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assertTrue( Double.isNaN( getProjection( spotPcaFeature, spec0 ).value( spot1 ) ) );
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assertTrue( Double.isNaN( getProjection( spotPcaFeature, spec1 ).value( spot1 ) ) );
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}
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}

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