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Add unit tests for BranchPcaFeature and SpotPcaFeature
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stefanhahmann committed Dec 3, 2024
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/*-
* #%L
* mastodon-deep-lineage
* %%
* Copyright (C) 2022 - 2024 Stefan Hahmann
* %%
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
* #L%
*/
package org.mastodon.mamut.feature.branch.dimensionalityreduction.pca;

import static org.junit.jupiter.api.Assertions.assertFalse;
import static org.junit.jupiter.api.Assertions.assertNotEquals;
import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertTrue;

import java.io.IOException;
import java.util.Collections;
import java.util.Iterator;
import java.util.List;
import java.util.function.Supplier;

import net.imglib2.util.Cast;

import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
import org.mastodon.feature.Dimension;
import org.mastodon.feature.FeatureModel;
import org.mastodon.feature.FeatureProjection;
import org.mastodon.feature.FeatureProjectionSpec;
import org.mastodon.mamut.feature.AbstractFeatureTest;
import org.mastodon.mamut.feature.FeatureComputerTestUtils;
import org.mastodon.mamut.feature.FeatureSerializerTestUtils;
import org.mastodon.mamut.feature.FeatureUtils;
import org.mastodon.mamut.feature.branch.BranchDisplacementDurationFeature;
import org.mastodon.mamut.feature.branch.exampleGraph.ExampleGraph7;
import org.mastodon.mamut.feature.branch.sinuosity.BranchSinuosityFeature;
import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionAlgorithm;
import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionController;
import org.mastodon.mamut.feature.dimensionalityreduction.util.InputDimension;
import org.mastodon.mamut.model.Model;
import org.mastodon.mamut.model.branch.BranchLink;
import org.mastodon.mamut.model.branch.BranchSpot;
import org.scijava.Context;

public class BranchPcaFeatureTest extends AbstractFeatureTest< BranchSpot >
{
private BranchPcaFeature pcaFeature;

private final ExampleGraph7 graph7 = new ExampleGraph7();

private FeatureProjectionSpec spec0;

private FeatureProjectionSpec spec1;

@BeforeEach
public void setUp()
{
try (Context context = new Context())
{
Model model = graph7.getModel();
FeatureModel featureModel = model.getFeatureModel();

// declare some features as input dimensions
BranchDisplacementDurationFeature branchDisplacementDurationFeature = Cast.unchecked(
FeatureComputerTestUtils.getFeature( context, model, BranchDisplacementDurationFeature.SPEC ) );
featureModel.declareFeature( branchDisplacementDurationFeature );
BranchSinuosityFeature branchSinuosityFeature = Cast.unchecked(
FeatureComputerTestUtils.getFeature( context, model, BranchSinuosityFeature.BRANCH_SINUOSITY_FEATURE_SPEC ) );
featureModel.declareFeature( branchSinuosityFeature );
List< InputDimension< BranchSpot > > inputDimensions =
InputDimension.getListFromFeatureModel( featureModel, BranchSpot.class, BranchLink.class );

// set up the controller and compute the feature
Supplier< List< InputDimension< BranchSpot > > > inputDimensionsSupplier = () -> inputDimensions;
DimensionalityReductionController controller = new DimensionalityReductionController( graph7.getModel(), context );
controller.setModelGraph( false );
controller.setAlgorithm( DimensionalityReductionAlgorithm.PCA );
controller.computeFeature( inputDimensionsSupplier );
pcaFeature = FeatureUtils.getFeature( graph7.getModel(), BranchPcaFeature.BranchSpotPcaFeatureSpec.class );
assertNotNull( pcaFeature );
spec0 = new FeatureProjectionSpec( pcaFeature.getProjectionName( 0 ), Dimension.NONE );
spec1 = new FeatureProjectionSpec( pcaFeature.getProjectionName( 1 ), Dimension.NONE );

}
}

@Test
@Override
public void testFeatureComputation()
{
assertNotNull( pcaFeature );
FeatureProjection< BranchSpot > projection0 = getProjection( pcaFeature, spec0 );
FeatureProjection< BranchSpot > projection1 = getProjection( pcaFeature, spec1 );
Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
BranchSpot branchSpot = branchSpotIterator.next();
assertFalse( Double.isNaN( projection0.value( branchSpot ) ) );
assertNotEquals( 0, projection0.value( branchSpot ) );
assertFalse( Double.isNaN( projection1.value( branchSpot ) ) );
assertNotEquals( 0, projection1.value( branchSpot ) );
}

@Test
@Override
public void testFeatureSerialization() throws IOException
{
BranchPcaFeature pcaFeatureReloaded;
try (Context context = new Context())
{
pcaFeatureReloaded =
( BranchPcaFeature ) FeatureSerializerTestUtils.saveAndReload( context, graph7.getModel(), this.pcaFeature );
}
assertNotNull( pcaFeatureReloaded );
Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
BranchSpot branchSpot = branchSpotIterator.next();
// check that the feature has correct values after saving and reloading
assertTrue( FeatureSerializerTestUtils.checkFeatureProjectionEquality( this.pcaFeature, pcaFeatureReloaded,
Collections.singleton( branchSpot ) ) );
}

@Test
@Override
public void testFeatureInvalidate()
{
Iterator< BranchSpot > branchSpotIterator = graph7.getModel().getBranchGraph().vertices().iterator();
BranchSpot branchSpot = branchSpotIterator.next();

// test, if features are not NaN before invalidation
assertFalse( Double.isNaN( getProjection( pcaFeature, spec0 ).value( branchSpot ) ) );
assertFalse( Double.isNaN( getProjection( pcaFeature, spec1 ).value( branchSpot ) ) );

// invalidate feature
pcaFeature.invalidate( branchSpot );

// test, if features are NaN after invalidation
assertTrue( Double.isNaN( getProjection( pcaFeature, spec0 ).value( branchSpot ) ) );
assertTrue( Double.isNaN( getProjection( pcaFeature, spec1 ).value( branchSpot ) ) );
}
}
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/*-
* #%L
* mastodon-deep-lineage
* %%
* Copyright (C) 2022 - 2024 Stefan Hahmann
* %%
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
* #L%
*/
package org.mastodon.mamut.feature.spot.dimensionalityreduction.pca;

import static org.junit.jupiter.api.Assertions.assertFalse;
import static org.junit.jupiter.api.Assertions.assertNotEquals;
import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertTrue;

import java.io.IOException;
import java.util.Collections;
import java.util.Iterator;
import java.util.List;
import java.util.function.Supplier;

import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
import org.mastodon.feature.Dimension;
import org.mastodon.feature.FeatureModel;
import org.mastodon.feature.FeatureProjection;
import org.mastodon.feature.FeatureProjectionSpec;
import org.mastodon.mamut.feature.AbstractFeatureTest;
import org.mastodon.mamut.feature.FeatureSerializerTestUtils;
import org.mastodon.mamut.feature.FeatureUtils;
import org.mastodon.mamut.feature.branch.exampleGraph.ExampleGraph7;
import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionAlgorithm;
import org.mastodon.mamut.feature.dimensionalityreduction.DimensionalityReductionController;
import org.mastodon.mamut.feature.dimensionalityreduction.util.InputDimension;
import org.mastodon.mamut.model.Link;
import org.mastodon.mamut.model.Spot;
import org.scijava.Context;

public class SpotPcaFeatureTest extends AbstractFeatureTest< Spot >
{
private SpotPcaFeature spotPcaFeature;

private final ExampleGraph7 graph7 = new ExampleGraph7();

private FeatureProjectionSpec spec0;

private FeatureProjectionSpec spec1;

@BeforeEach
public void setUp()
{
try (Context context = new Context())
{
FeatureModel featureModel = graph7.getModel().getFeatureModel();
DimensionalityReductionController controller = new DimensionalityReductionController( graph7.getModel(), context );
controller.setAlgorithm( DimensionalityReductionAlgorithm.PCA );
Supplier< List< InputDimension< Spot > > > inputDimensionsSupplier =
() -> InputDimension.getListFromFeatureModel( featureModel, Spot.class, Link.class );
controller.computeFeature( inputDimensionsSupplier );
spotPcaFeature = FeatureUtils.getFeature( graph7.getModel(), SpotPcaFeature.SpotPcaFeatureSpec.class );
assertNotNull( spotPcaFeature );
spec0 = new FeatureProjectionSpec( spotPcaFeature.getProjectionName( 0 ), Dimension.NONE );
spec1 = new FeatureProjectionSpec( spotPcaFeature.getProjectionName( 1 ), Dimension.NONE );
}
}

@Test
@Override
public void testFeatureComputation()
{
assertNotNull( spotPcaFeature );
FeatureProjection< Spot > projection0 = getProjection( spotPcaFeature, spec0 );
FeatureProjection< Spot > projection1 = getProjection( spotPcaFeature, spec1 );
Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
Spot spot0 = spotIterator.next();
assertTrue( Double.isNaN( projection0.value( spot0 ) ) );
assertTrue( Double.isNaN( projection1.value( spot0 ) ) );
Spot spot1 = spotIterator.next();
assertFalse( Double.isNaN( projection0.value( spot1 ) ) );
assertFalse( Double.isNaN( projection1.value( spot1 ) ) );
assertNotEquals( 0, projection0.value( spot1 ) );
assertNotEquals( 0, projection1.value( spot1 ) );
}

@Test
@Override
public void testFeatureSerialization() throws IOException
{
SpotPcaFeature spotPcaFeatureReloaded;
try (Context context = new Context())
{
spotPcaFeatureReloaded =
( SpotPcaFeature ) FeatureSerializerTestUtils.saveAndReload( context, graph7.getModel(), spotPcaFeature );
}
assertNotNull( spotPcaFeatureReloaded );
// check that the feature has correct values after saving and reloading
Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
spotIterator.next();
Spot spot1 = spotIterator.next();
assertTrue( FeatureSerializerTestUtils.checkFeatureProjectionEquality(
spotPcaFeature, spotPcaFeatureReloaded,
Collections.singleton( spot1 ) ) );
}

@Test
@Override
public void testFeatureInvalidate()
{
// test, if features are not NaN before invalidation
Iterator< Spot > spotIterator = graph7.getModel().getGraph().vertices().iterator();
spotIterator.next();
Spot spot1 = spotIterator.next();
assertFalse( Double.isNaN( getProjection( spotPcaFeature, spec0 ).value( spot1 ) ) );
assertFalse( Double.isNaN( getProjection( spotPcaFeature, spec1 ).value( spot1 ) ) );

// invalidate feature
spotPcaFeature.invalidate( spot1 );

// test, if features are NaN after invalidation
assertTrue( Double.isNaN( getProjection( spotPcaFeature, spec0 ).value( spot1 ) ) );
assertTrue( Double.isNaN( getProjection( spotPcaFeature, spec1 ).value( spot1 ) ) );
}
}

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