| // DeterministicSIScenarioTest.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.HashMap; |
| import java.util.List; |
| import java.util.Map; |
| |
| import org.eclipse.stem.core.graph.LabelValue; |
| import org.eclipse.stem.core.model.NodeDecorator; |
| import org.eclipse.stem.diseasemodels.standard.SILabelValue; |
| import org.eclipse.stem.diseasemodels.standard.impl.SIImpl; |
| import org.eclipse.stem.diseasemodels.standard.impl.SILabelValueImpl; |
| |
| /** |
| * This class is a JUnit test case for a Deterministic SI disease model |
| * scenario. |
| * |
| * <ul> |
| * <li>S - The number of <code>Susceptible</code> population members. Members |
| * enter this state by being born or by "recovering" from being |
| * <code>Infectious</code>. They leave this state either by death or by |
| * entering the <code>Infectious</code> state. |
| * {@link SITest#TRANSMISSION_RATE} = 0.1, {@link SITest#RECOVERY_RATE} = 0.1 |
| * |
| * Initialized to {@link DiseaseModelTestUtil#TEST_POPULATION_COUNT} = 100 </li> |
| * <li>I - The number of <code>Infectious</code> population members. |
| * Initialized to {@link SIDiseaseModelScenarioTest#NUMBER_TO_INFECT} = 1 </li> |
| * |
| * <li>B - The number of <code>Births</code> of new (Susceptible) population |
| * members. |
| * |
| * |
| * </ul> |
| * <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>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 SI Scenario</h2> |
| * |
| * @see DiseaseModelTestUtil#TEST_POPULATION_COUNT |
| * @see SIDiseaseModelScenarioTest#NUMBER_TO_INFECT |
| * @see DiseaseModelTestUtil#TEST_AREA |
| * @see SITest#INFECTIOUS_MORTALITY |
| * @see SITest#TRANSMISSION_RATE |
| * @see SITest#NON_LINEARITY_COEFFICIENT |
| * @see SITest#RECOVERY_RATE |
| * @see SIImpl |
| */ |
| public class DeterministicSIScenarioTest extends SIDiseaseModelScenarioTest { |
| |
| private static final String DISEASE_URI_PREFIX = "DeterministicSI"; |
| |
| private static Map<String, Integer> expectedNumberOfLabelsToUpdate = new HashMap<String, Integer>(); |
| |
| private static Map<String, SILabelValue[][][]> expectedDiseaseModelStates = new HashMap<String, SILabelValue[][][]>(); |
| |
| static { |
| |
| // 1x1 |
| expectedDiseaseModelStates.put(TEST_SCENARIO1x1_KEY, |
| new SILabelValue[][][] { |
| // Step 0 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(98.91, 0.99, 0.0, 0.1) } }, |
| |
| // Step 1 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(98.82, 0.98, 0.0, 0.2) } } } |
| // SILabelValue |
| |
| ); // put(TEST_SCENARIO1x1_KEY) |
| |
| // 1x2 |
| expectedDiseaseModelStates.put(TEST_SCENARIO1x2_KEY, |
| new SILabelValue[][][] { |
| // Step 0 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) } }, |
| |
| // Step 1 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) } }, |
| // Step 2 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) } } } // new |
| // SILabelValue |
| ); // put(TEST_SCENARIO1x2_KEY) |
| |
| // 1x3 |
| expectedDiseaseModelStates.put(TEST_SCENARIO1x3_KEY, |
| new SILabelValue[][][] { |
| // Step 0 |
| { { |
| |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 1 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 2 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } } } // new SILabelValue |
| |
| ); // put(TEST_SCENARIO1x3_KEY) |
| |
| // 2x2 |
| expectedDiseaseModelStates.put(TEST_SCENARIO2x2_KEY, |
| new SILabelValue[][][] { |
| // Step 0 |
| { { |
| |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 1 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 2 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } } } // new SILabelValue |
| |
| ); // put(TEST_SCENARIO2x2_KEY) |
| |
| // 3x3 |
| expectedDiseaseModelStates.put(TEST_SCENARIO3x3_KEY, |
| new SILabelValue[][][] { |
| // Step 0 |
| { { |
| |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[2,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 1 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[2,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } }, |
| |
| // Step 2 |
| { { |
| // N[0,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[0,2] |
| new SILabelValueImpl(100, 0, 0,0) |
| |
| }, { |
| |
| // N[1,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[1,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| }, { |
| |
| // N[2,0] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,1] |
| new SILabelValueImpl(100, 0, 0, 0), |
| // N[2,2] |
| new SILabelValueImpl(100, 0, 0, 0) |
| |
| } } } // new SILabelValue |
| |
| ); // 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(DeterministicSIDiseaseModelTest.createFixture()); |
| return retValue; |
| } // getDiseaseModelsToTest |
| |
| @Override |
| protected int getNumberOfSteps(final String diseaseScenarioKey) { |
| SILabelValue[][][] 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 SILabelValue[][][] siLabelValue = expectedDiseaseModelStates |
| .get(diseaseScenarioKey); |
| return siLabelValue[step]; |
| } // getExpectedDiseaseModelState |
| |
| protected String getDiseaseURIPrefix() { |
| return DISEASE_URI_PREFIX; |
| } // getDiseaseURIPrefix |
| } // DeterministicSIScenarioTest |