tests/org.eclipse.stem.tests.diseasemodels/src/org/eclipse/stem/diseasemodels/standard/tests/DeterministicSEIRScenarioTest.java - stem/org.eclipse.stem - Git at Google

 // DeterministicSEIRScenarioTest.java
 package org.eclipse.stem.diseasemodels.standard.tests;

 /*******************************************************************************
  * Copyright (c) 2006 IBM Corporation and others.
  * All rights reserved. This program and the accompanying materials
  * are made available under the terms of the Eclipse Public License v1.0
  * which accompanies this distribution, and is available at
  * http://www.eclipse.org/legal/epl-v10.html
  *
  * Contributors:
  *     IBM Corporation - initial API and implementation
  *******************************************************************************/

 import java.util.ArrayList;
 import java.util.Collection;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;

 import org.eclipse.stem.core.graph.LabelValue;
 import org.eclipse.stem.core.model.Model;
 import org.eclipse.stem.core.model.NodeDecorator;
 import org.eclipse.stem.core.scenario.Scenario;
 import org.eclipse.stem.diseasemodels.standard.SEIRLabelValue;
 import org.eclipse.stem.diseasemodels.standard.impl.SEIRLabelValueImpl;

 /**
  * This class is a JUnit test case for a Deterministic SEIR disease model
  * scenario.
  *
  * <ul>
  * <li>&mu; = {@link DiseaseModelTest#MORTALITY_RATE} = 0.01</li>
  * <li>&beta; = {@link SITest#TRANSMISSION_RATE} = 0.1</li>
  * <li>&sigma; = {@link SITest#RECOVERY_RATE} = 0.01</li>
  * <li>x = {@link SITest#INFECTIOUS_MORTALITY} = 0.1 </li>
  * <li>&mu;<sub>i</sub> = {@link SITest#INFECTIOUS_MORTAILY_RATE} = 0.1</li>
  * <li>&gamma; = {@link SIRTest#IMMUNITY_LOSS_RATE} = 0.1</li>
  * <li>&phi; = {@link SEIRTest#INCUBATION_RATE} = 0.1</li>
  * <li>Area<sub>l</sub> = 1.0</li>
  * <li>Area = 1.0</li>
  * <li>P = S + I = {@link DiseaseModelTestUtil#TEST_POPULATION_COUNT} = 100</li>
  * </ul>
  * <h2>1x1 Deterministic SEIR Scenario</h2>
  *
  */
 public class DeterministicSEIRScenarioTest extends SEIRDiseaseModelScenarioTest {

 	private static final String DISEASE_URI_PREFIX = "DeterministicSEIR";

 	private static Map<String, Integer> expectedNumberOfLabelsToUpdate = new HashMap<String, Integer>();

 	private static Map<String, SEIRLabelValue[][][]> expectedDiseaseModelStates = new HashMap<String, SEIRLabelValue[][][]>();

 	static {

 		// 1x1
 		expectedDiseaseModelStates.put(TEST_SCENARIO1x1_KEY,
 				new SEIRLabelValue[][][] {
 				// Step 0
 						{ {
 						// N[0,0]
 						new SEIRLabelValueImpl(98.90, 0.10, 0.89, 0.01,	0.10) } },

 						// Step 1
 						{ {
 						// N[0,0]
 						new SEIRLabelValueImpl(98.81, 0.18, 0.80, 0.02, 0.19) } } }
 				// SEIRLabelValue

 				); // put(TEST_SCENARIO1x1_KEY)

 		// 1x2
 		expectedDiseaseModelStates
 				.put(TEST_SCENARIO1x2_KEY,
 						new SEIRLabelValue[][][] {
 						// Step 0
 								{ {
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0) } },

 								// Step 1
 								{ {
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0) } },
 								// Step 2
 								{ {
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0) } } } // new
 				// SEIRLabelValue
 				); // put(TEST_SCENARIO1x2_KEY)

 		// 1x3
 		expectedDiseaseModelStates
 				.put(TEST_SCENARIO1x3_KEY,
 						new SEIRLabelValue[][][] {
 						// Step 0
 								{ {

 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 								// Step 1
 								{ {
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 								// Step 2
 								{ {
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} } } // new SEIRLabelValue

 				); // put(TEST_SCENARIO1x3_KEY)

 		// 2x2
 		expectedDiseaseModelStates.put(TEST_SCENARIO2x2_KEY,
 				new SEIRLabelValue[][][] {
 				// Step 0
 						{
 								{

 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 						// Step 1
 						{
 								{
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1z
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 						// Step 2
 						{
 								{
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} } } // new SEIRLabelValue

 				); // put(TEST_SCENARIO2x2_KEY)

 		// 3x3
 		expectedDiseaseModelStates.put(TEST_SCENARIO3x3_KEY,
 				new SEIRLabelValue[][][] {
 				// Step 0
 						{
 								{

 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[2,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 						// Step 1
 						{
 								{
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[2,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} },

 						// Step 2
 						{
 								{
 								// N[0,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[0,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[1,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[1,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								},
 								{

 								// N[2,0]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,1]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0),
 										// N[2,2]
 										new SEIRLabelValueImpl(100, 0, 0, 0, 0,
 												0)

 								} } } // new SEIRLabelValue

 				); // put(TEST_SCENARIO3x3_KEY)

 		// Fill out the map that specifies how many labels should be updated by
 		// a disease model for each test.
 		for (TestSpec testSpec : testSpecifications) {
 			expectedNumberOfLabelsToUpdate
 					.put(
 							testSpec.scenarioDiseaseKey,
 							new Integer(
 									computeExpectedNumberOfLabels(expectedDiseaseModelStates
 											.get(testSpec.scenarioDiseaseKey))));
 		} // for each test specification

 	} // static

 	/**
 	 * @see org.eclipse.stem.diseasemodels.standard.tests.DiseaseModelScenarioTest#getDiseaseModelsToTest()
 	 */
 	@Override
 	public List<NodeDecorator> getDiseaseModelsToTest() {
 		final List<NodeDecorator> retValue = new ArrayList<NodeDecorator>();
 		retValue.add(DeterministicSEIRDiseaseModelTest.createFixture());
 		return retValue;
 	} // getDiseaseModelsToTest

 	@Override
 	protected int getNumberOfSteps(final String diseaseScenarioKey) {
 		SEIRLabelValue[][][] temp = expectedDiseaseModelStates
 				.get(diseaseScenarioKey);
 		return temp.length;
 	} // getNumberOfSteps

 	@Override
 	protected int getExpectedNumberOfLabelsToUpdate(
 			final String diseaseScenarioKey) {
 		Integer temp = expectedNumberOfLabelsToUpdate.get(diseaseScenarioKey);
 		return temp.intValue();
 	} // getExpectedNumberOfLabelsToUpdate

 	@Override
 	protected LabelValue[][] getExpectedDiseaseModelState(
 			final String diseaseScenarioKey, final int step) {
 		final SEIRLabelValue[][][] seirLabelValue = expectedDiseaseModelStates
 				.get(diseaseScenarioKey);
 		return seirLabelValue[step];
 	} // getExpectedDiseaseModelState

 	protected String getDiseaseURIPrefix() {
 		return DISEASE_URI_PREFIX;
 	} // getDiseaseURIPrefix

 	/**
 	 * @param numRows
 	 *            the number of rows in the lattice
 	 * @param numColumns
 	 *            the number of columns in the lattice
 	 * @return a scenario with nodes in a lattice with a deterministic SEIR
 	 *         disease model and one population member infected in Node [0][0]
 	 */
 	public static Scenario createScenario(final int numRows,
 			final int numColumns) {
 		final Collection<NodeDecorator> diseaseModels = new ArrayList<NodeDecorator>();

 		diseaseModels.add(DeterministicSEIRDiseaseModelTest.createFixture());

 		final Model model = DiseaseModelTestUtil.createLatticeModel(
 				diseaseModels, numRows, numColumns,
 				DiseaseModelTestUtil.TEST_POPULATION_COUNT,
 				DiseaseModelTestUtil.TEST_AREA);

 		final Scenario retValue = DiseaseModelTestUtil.createLatticeScenario(
 				SIDiseaseModelScenarioTest.createInfectors(model), model);

 		assert retValue.sane();

 		return retValue;
 	} // createFixture

 } // DeterministicSEIRScenarioTest
	// DeterministicSEIRScenarioTest.java
	package org.eclipse.stem.diseasemodels.standard.tests;

	/*******************************************************************************
	* Copyright (c) 2006 IBM Corporation and others.
	* All rights reserved. This program and the accompanying materials
	* are made available under the terms of the Eclipse Public License v1.0
	* which accompanies this distribution, and is available at
	* http://www.eclipse.org/legal/epl-v10.html
	*
	* Contributors:
	* IBM Corporation - initial API and implementation
	*******************************************************************************/

	import java.util.ArrayList;
	import java.util.Collection;
	import java.util.HashMap;
	import java.util.List;
	import java.util.Map;

	import org.eclipse.stem.core.graph.LabelValue;
	import org.eclipse.stem.core.model.Model;
	import org.eclipse.stem.core.model.NodeDecorator;
	import org.eclipse.stem.core.scenario.Scenario;
	import org.eclipse.stem.diseasemodels.standard.SEIRLabelValue;
	import org.eclipse.stem.diseasemodels.standard.impl.SEIRLabelValueImpl;

	/**
	* This class is a JUnit test case for a Deterministic SEIR disease model
	* scenario.
	*
	* <ul>
	* <li>μ = {@link DiseaseModelTest#MORTALITY_RATE} = 0.01</li>
	* <li>β = {@link SITest#TRANSMISSION_RATE} = 0.1</li>
	* <li>σ = {@link SITest#RECOVERY_RATE} = 0.01</li>
	* <li>x = {@link SITest#INFECTIOUS_MORTALITY} = 0.1 </li>
	* <li>μ<sub>i</sub> = {@link SITest#INFECTIOUS_MORTAILY_RATE} = 0.1</li>
	* <li>γ = {@link SIRTest#IMMUNITY_LOSS_RATE} = 0.1</li>
	* <li>φ = {@link SEIRTest#INCUBATION_RATE} = 0.1</li>
	* <li>Area<sub>l</sub> = 1.0</li>
	* <li>Area = 1.0</li>
	* <li>P = S + I = {@link DiseaseModelTestUtil#TEST_POPULATION_COUNT} = 100</li>
	* </ul>
	* <h2>1x1 Deterministic SEIR Scenario</h2>
	*
	*/
	public class DeterministicSEIRScenarioTest extends SEIRDiseaseModelScenarioTest {

	private static final String DISEASE_URI_PREFIX = "DeterministicSEIR";

	private static Map<String, Integer> expectedNumberOfLabelsToUpdate = new HashMap<String, Integer>();

	private static Map<String, SEIRLabelValue[][][]> expectedDiseaseModelStates = new HashMap<String, SEIRLabelValue[][][]>();

	static {

	// 1x1
	expectedDiseaseModelStates.put(TEST_SCENARIO1x1_KEY,
	new SEIRLabelValue[][][] {
	// Step 0
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(98.90, 0.10, 0.89, 0.01, 0.10) } },

	// Step 1
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(98.81, 0.18, 0.80, 0.02, 0.19) } } }
	// SEIRLabelValue

	); // put(TEST_SCENARIO1x1_KEY)

	// 1x2
	expectedDiseaseModelStates
	.put(TEST_SCENARIO1x2_KEY,
	new SEIRLabelValue[][][] {
	// Step 0
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0) } },

	// Step 1
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0) } },
	// Step 2
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0) } } } // new
	// SEIRLabelValue
	); // put(TEST_SCENARIO1x2_KEY)

	// 1x3
	expectedDiseaseModelStates
	.put(TEST_SCENARIO1x3_KEY,
	new SEIRLabelValue[][][] {
	// Step 0
	{ {

	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 1
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 2
	{ {
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} } } // new SEIRLabelValue

	); // put(TEST_SCENARIO1x3_KEY)

	// 2x2
	expectedDiseaseModelStates.put(TEST_SCENARIO2x2_KEY,
	new SEIRLabelValue[][][] {
	// Step 0
	{
	{

	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 1
	{
	{
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1z
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 2
	{
	{
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} } } // new SEIRLabelValue

	); // put(TEST_SCENARIO2x2_KEY)

	// 3x3
	expectedDiseaseModelStates.put(TEST_SCENARIO3x3_KEY,
	new SEIRLabelValue[][][] {
	// Step 0
	{
	{

	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[2,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 1
	{
	{
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[2,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} },

	// Step 2
	{
	{
	// N[0,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[0,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[1,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[1,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	},
	{

	// N[2,0]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,1]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0),
	// N[2,2]
	new SEIRLabelValueImpl(100, 0, 0, 0, 0,
	0)

	} } } // new SEIRLabelValue

	); // put(TEST_SCENARIO3x3_KEY)

	// Fill out the map that specifies how many labels should be updated by
	// a disease model for each test.
	for (TestSpec testSpec : testSpecifications) {
	expectedNumberOfLabelsToUpdate
	.put(
	testSpec.scenarioDiseaseKey,
	new Integer(
	computeExpectedNumberOfLabels(expectedDiseaseModelStates
	.get(testSpec.scenarioDiseaseKey))));
	} // for each test specification

	} // static

	/**
	* @see org.eclipse.stem.diseasemodels.standard.tests.DiseaseModelScenarioTest#getDiseaseModelsToTest()
	*/
	@Override
	public List<NodeDecorator> getDiseaseModelsToTest() {
	final List<NodeDecorator> retValue = new ArrayList<NodeDecorator>();
	retValue.add(DeterministicSEIRDiseaseModelTest.createFixture());
	return retValue;
	} // getDiseaseModelsToTest

	@Override
	protected int getNumberOfSteps(final String diseaseScenarioKey) {
	SEIRLabelValue[][][] temp = expectedDiseaseModelStates
	.get(diseaseScenarioKey);
	return temp.length;
	} // getNumberOfSteps

	@Override
	protected int getExpectedNumberOfLabelsToUpdate(
	final String diseaseScenarioKey) {
	Integer temp = expectedNumberOfLabelsToUpdate.get(diseaseScenarioKey);
	return temp.intValue();
	} // getExpectedNumberOfLabelsToUpdate

	@Override
	protected LabelValue[][] getExpectedDiseaseModelState(
	final String diseaseScenarioKey, final int step) {
	final SEIRLabelValue[][][] seirLabelValue = expectedDiseaseModelStates
	.get(diseaseScenarioKey);
	return seirLabelValue[step];
	} // getExpectedDiseaseModelState

	protected String getDiseaseURIPrefix() {
	return DISEASE_URI_PREFIX;
	} // getDiseaseURIPrefix

	/**
	* @param numRows
	* the number of rows in the lattice
	* @param numColumns
	* the number of columns in the lattice
	* @return a scenario with nodes in a lattice with a deterministic SEIR
	* disease model and one population member infected in Node [0][0]
	*/
	public static Scenario createScenario(final int numRows,
	final int numColumns) {
	final Collection<NodeDecorator> diseaseModels = new ArrayList<NodeDecorator>();

	diseaseModels.add(DeterministicSEIRDiseaseModelTest.createFixture());

	final Model model = DiseaseModelTestUtil.createLatticeModel(
	diseaseModels, numRows, numColumns,
	DiseaseModelTestUtil.TEST_POPULATION_COUNT,
	DiseaseModelTestUtil.TEST_AREA);

	final Scenario retValue = DiseaseModelTestUtil.createLatticeScenario(
	SIDiseaseModelScenarioTest.createInfectors(model), model);

	assert retValue.sane();

	return retValue;
	} // createFixture

	} // DeterministicSEIRScenarioTest