/*
* This file is part of ADDIS (Aggregate Data Drug Information System).
* ADDIS is distributed from http://drugis.org/.
* Copyright © 2009 Gert van Valkenhoef, Tommi Tervonen.
* Copyright © 2010 Gert van Valkenhoef, Tommi Tervonen, Tijs Zwinkels,
* Maarten Jacobs, Hanno Koeslag, Florin Schimbinschi, Ahmad Kamal, Daniel
* Reid.
* Copyright © 2011 Gert van Valkenhoef, Ahmad Kamal, Daniel Reid, Florin
* Schimbinschi.
* Copyright © 2012 Gert van Valkenhoef, Daniel Reid, Joël Kuiper, Wouter
* Reckman.
* Copyright © 2013 Gert van Valkenhoef, Joël Kuiper.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package org.drugis.addis.presentation;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.drugis.addis.ExampleData;
import org.drugis.addis.entities.Arm;
import org.drugis.addis.entities.BasicContinuousMeasurement;
import org.drugis.addis.entities.BasicMeasurement;
import org.drugis.addis.entities.DoseUnit;
import org.drugis.addis.entities.Drug;
import org.drugis.addis.entities.Endpoint;
import org.drugis.addis.entities.FixedDose;
import org.drugis.addis.entities.Indication;
import org.drugis.addis.entities.OutcomeMeasure.Direction;
import org.drugis.addis.entities.Study;
import org.drugis.addis.entities.StudyOutcomeMeasure;
import org.drugis.addis.entities.Variable;
import org.drugis.addis.entities.analysis.RandomEffectsMetaAnalysis;
import org.drugis.addis.entities.relativeeffect.AxisType;
import org.drugis.addis.entities.relativeeffect.BasicMeanDifference;
import org.drugis.addis.entities.relativeeffect.BasicOddsRatio;
import org.drugis.addis.entities.relativeeffect.BasicRelativeEffect;
import org.drugis.addis.entities.relativeeffect.BasicRiskRatio;
import org.drugis.addis.entities.relativeeffect.RelativeEffect;
import org.drugis.addis.entities.treatment.TreatmentDefinition;
import org.drugis.addis.forestplot.ForestPlot;
import org.drugis.common.Interval;
import org.junit.Before;
import org.junit.Test;
public class ForestPlotPresentationTest {
private static final double s_mean1 = 0.50;
private static final double s_mean2 = 0.25;
private static final double s_stdDev1 = 0.2;
private static final double s_stdDev2 = 2.5;
private static final int s_subjSize = 35;
private static final int s_baseSize = 41;
private REMAForestPlotPresentation d_pm;
private BasicContinuousMeasurement d_mBase1;
private BasicContinuousMeasurement d_mSubj1;
private BasicContinuousMeasurement d_mBase2;
private BasicContinuousMeasurement d_mSubj2;
private Study d_s2;
private Study d_s1;
private Endpoint d_endpoint;
private Drug d_subject;
private Drug d_baseline;
@Before
public void setUp() {
d_s1 = new Study("X", new Indication(0L, ""));
ExampleData.addDefaultEpochs(d_s1);
d_endpoint = new Endpoint("E", Endpoint.convertVarType(Variable.Type.CONTINUOUS));
d_s1.getEndpoints().add(new StudyOutcomeMeasure<Endpoint>(d_endpoint));
d_baseline = new Drug("DrugA", "");
d_subject = new Drug("DrugB", "");
Arm pBase = d_s1.createAndAddArm("base", s_baseSize, d_baseline, new FixedDose(10, DoseUnit.createMilliGramsPerDay()));
Arm pSubj = d_s1.createAndAddArm("subj", s_subjSize, d_subject, new FixedDose(10, DoseUnit.createMilliGramsPerDay()));
d_mBase1 = new BasicContinuousMeasurement(s_mean1, s_stdDev1, pBase.getSize());
d_mSubj1 = new BasicContinuousMeasurement(s_mean2, s_stdDev2, pSubj.getSize());
d_s2 = new Study("Y", new Indication(0L, ""));
ExampleData.addDefaultEpochs(d_s2);
d_s2.getEndpoints().add(new StudyOutcomeMeasure<Endpoint>(d_endpoint));
Arm pBase2 = d_s2.createAndAddArm("base2", s_baseSize, d_baseline, new FixedDose(10, DoseUnit.createMilliGramsPerDay()));
Arm pSubj2 = d_s2.createAndAddArm("subj2", s_subjSize, d_subject, new FixedDose(10, DoseUnit.createMilliGramsPerDay()));
d_mBase2 = new BasicContinuousMeasurement(s_mean2, s_stdDev2, pBase2.getSize());
d_mSubj2 = new BasicContinuousMeasurement(s_mean1, s_stdDev1, pSubj2.getSize());
ExampleData.addDefaultMeasurementMoments(d_s1);
ExampleData.addDefaultMeasurementMoments(d_s2);
d_s1.setMeasurement(d_s1.findStudyOutcomeMeasure(d_endpoint), pBase, d_mBase1);
d_s1.setMeasurement(d_s1.findStudyOutcomeMeasure(d_endpoint), pSubj, d_mSubj1);
d_s2.setMeasurement(d_s2.findStudyOutcomeMeasure(d_endpoint), pBase2, d_mBase2);
d_s2.setMeasurement(d_s2.findStudyOutcomeMeasure(d_endpoint), pSubj2, d_mSubj2);
List<Study> studies = new ArrayList<Study>();
studies.add(d_s1);
studies.add(d_s2);
RandomEffectsMetaAnalysis analysis = ExampleData.buildRandomEffectsMetaAnalysis("null", d_endpoint, studies, TreatmentDefinition.createTrivial(d_baseline), TreatmentDefinition.createTrivial(d_subject));
d_pm = new REMAForestPlotPresentation(analysis, BasicMeanDifference.class);
}
@Test
public void testGetListedRelativeEffects() {
assertEquals(3, d_pm.getNumRelativeEffects());
assertRelativeEffectEqual(
new BasicMeanDifference(d_mBase1, d_mSubj1),
d_pm.getRelativeEffectAt(0));
assertRelativeEffectEqual(
new BasicMeanDifference(d_mBase2, d_mSubj2),
d_pm.getRelativeEffectAt(1));
}
@Test
public void testGetScale() {
assertEquals( (int) Math.round(ForestPlot.BARWIDTH / 2.0), (int) d_pm.getScale().getBin(0.0).bin);
int expectedBin = (int) Math.round( (2 - 1.09) / (4.0 / (ForestPlot.BARWIDTH - 1)) );
assertEquals(expectedBin + 1, (int) d_pm.getScale().getBin(-1.09).bin);
assertTrue(!d_pm.getScale().getBin(-1.09).outOfBoundsMin);
assertEquals(ForestPlot.BARWIDTH - expectedBin, (int) d_pm.getScale().getBin(1.09).bin);
assertTrue(!d_pm.getScale().getBin(1.09).outOfBoundsMax);
}
@Test
public void testGetRange() {
// known intervals: "0.25 (-0.53, 1.03)" & "-0.25 (-1.09, 0.59)"
Interval<Double> interval = d_pm.getRange();
assertEquals(-2.0, interval.getLowerBound(), 0.01);
assertEquals(2.0, interval.getUpperBound(), 0.01);
}
@Test
public void testGetRangeUndefined() {
Study zeroRate = ExampleData.buildRateStudy("ZeroRate 2012", 0, 120, 10, 118);
RandomEffectsMetaAnalysis rema = ExampleData.buildRandomEffectsMetaAnalysis("meta",
ExampleData.buildEndpointHamd(),
Collections.singletonList(zeroRate),
TreatmentDefinition.createTrivial(ExampleData.buildDrugFluoxetine()),
TreatmentDefinition.createTrivial(ExampleData.buildDrugSertraline()));
assertEquals(new Interval<Double>(0.5, 2.0), new REMAForestPlotPresentation(rema, BasicOddsRatio.class).getRange());
assertEquals(new Interval<Double>(0.5, 2.0), new REMAForestPlotPresentation(rema, BasicRiskRatio.class).getRange());
}
@Test
public void testGetDrugsLabel() {
assertEquals("DrugA", d_pm.getLowValueFavors());
assertEquals("DrugB", d_pm.getHighValueFavors());
}
@Test
public void testGetStudiesLabel() {
assertEquals("X", d_pm.getStudyLabelAt(0));
assertEquals("Y", d_pm.getStudyLabelAt(1));
}
@Test
public void testGetCIlabel() {
// known intervals: "0.25 (-0.53, 1.03)" & "-0.25 (-1.09, 0.59)"
String interval1 = "0.25 (-0.53, 1.03)";
String interval2 = "-0.25 (-1.09, 0.59)";
assertEquals(interval1, d_pm.getCIlabelAt(1));
assertEquals(interval2, d_pm.getCIlabelAt(0));
}
@Test
public void testGetScaleType() {
assertEquals(AxisType.LINEAR, d_pm.getScaleType());
}
@Test
public void testGetScaleZero() {
assertEquals(151, (int)d_pm.getScale().getBin(0.0).bin);
}
@Test
public void testGetDiamondSize() {
for (Arm pg : d_s2.getArms()) {
BasicMeasurement m = (BasicMeasurement)d_s2.getMeasurement(d_endpoint, pg);
m.setSampleSize(m.getSampleSize() * 10);
}
List<Study> studies = new ArrayList<Study>();
studies.add(d_s1);
studies.add(d_s2);
RandomEffectsMetaAnalysis analysis = ExampleData.buildRandomEffectsMetaAnalysis("null", d_endpoint, studies, TreatmentDefinition.createTrivial(d_baseline), TreatmentDefinition.createTrivial(d_subject));
REMAForestPlotPresentation pm = new REMAForestPlotPresentation(analysis, BasicMeanDifference.class);
assertEquals(5, pm.getDiamondSize(0));
assertEquals(21, pm.getDiamondSize(1));
}
@Test
public void testLogarithmic() {
Interval<Double> logint = REMAForestPlotPresentation.niceIntervalLog(0.0624, 4.1);
assertEquals(logint.getLowerBound(), 1D/32D, 0.001);
assertEquals(logint.getUpperBound(), 8D, 0.001);
}
@Test
public void testGetTickVals() {
// known intervals: "0.25 (-0.53, 1.03)" & "-0.25 (-1.09, 0.59)"
List<String> tickVals = d_pm.getTickVals();
assertEquals(3, tickVals.size());
assertEquals("-2", tickVals.get(0));
assertEquals("0", tickVals.get(1));
assertEquals("2", tickVals.get(2));
}
@Test
public void testGetTicks() {
// known intervals: "0.25 (-0.53, 1.03)" & "-0.25 (-1.09, 0.59)"
List<Integer> ticks = d_pm.getTicks();
assertEquals(3, ticks.size());
assertEquals(1, (int)ticks.get(0));
assertEquals(151, (int)ticks.get(1));
assertEquals(301, (int)ticks.get(2));
}
@Test
public void testLabelsForLowerIsBetter() {
d_endpoint.setDirection(Direction.LOWER_IS_BETTER);
assertEquals("DrugB", d_pm.getLowValueFavors());
assertEquals("DrugA", d_pm.getHighValueFavors());
}
private static void assertRelativeEffectEqual(RelativeEffect<?> expected,
RelativeEffect<?> actual) {
assertEquals(expected.getClass(), actual.getClass());
assertEquals(expected.getConfidenceInterval(), actual.getConfidenceInterval());
if (expected instanceof BasicRelativeEffect<?>) {
BasicRelativeEffect<?> e = (BasicRelativeEffect<?>) expected;
BasicRelativeEffect<?> a = (BasicRelativeEffect<?>) actual;
assertEquals(e.getBaseline(), a.getBaseline());
assertEquals(e.getSubject(), a.getSubject());
}
}
}