largeRCRF-Java/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRiskResponseCombiner.java

89 lines
3.8 KiB
Java

package ca.joeltherrien.randomforest.competingrisk;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctions;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskResponseCombiner;
import ca.joeltherrien.randomforest.utils.MathFunction;
import org.junit.jupiter.api.Test;
import static ca.joeltherrien.randomforest.TestUtils.closeEnough;
import java.util.ArrayList;
import java.util.List;
public class TestCompetingRiskResponseCombiner {
private CompetingRiskFunctions generateFunctions(){
final List<CompetingRiskResponse> data = new ArrayList<>();
data.add(new CompetingRiskResponse(1, 1.0));
data.add(new CompetingRiskResponse(1, 1.0));
data.add(new CompetingRiskResponse(1, 2.0));
data.add(new CompetingRiskResponse(2, 1.5));
data.add(new CompetingRiskResponse(2, 2.0));
data.add(new CompetingRiskResponse(0, 1.5));
data.add(new CompetingRiskResponse(0, 2.5));
final CompetingRiskResponseCombiner combiner = new CompetingRiskResponseCombiner(new int[]{1,2}, null);
return combiner.combine(data);
}
@Test
public void testCompetingRiskResponseCombiner(){
final CompetingRiskFunctions functions = generateFunctions();
final MathFunction survivalCurve = functions.getSurvivalCurve();
// time = 1.0 1.5 2.0 2.5
// surv = 0.7142857 0.5714286 0.1904762 0.1904762
final double margin = 0.0000001;
closeEnough(0.7142857, survivalCurve.evaluate(1.0).getY(), margin);
closeEnough(0.5714286, survivalCurve.evaluate(1.5).getY(), margin);
closeEnough(0.1904762, survivalCurve.evaluate(2.0).getY(), margin);
closeEnough(0.1904762, survivalCurve.evaluate(2.5).getY(), margin);
// Time = 1.0 1.5 2.0 2.5
/* Cumulative hazard function. Each row for one event.
[,1] [,2] [,3] [,4]
[1,] 0.2857143 0.2857143 0.6190476 0.6190476
[2,] 0.0000000 0.2000000 0.5333333 0.5333333
*/
final MathFunction cumHaz1 = functions.getCauseSpecificHazardFunction(1);
closeEnough(0.2857143, cumHaz1.evaluate(1.0).getY(), margin);
closeEnough(0.2857143, cumHaz1.evaluate(1.5).getY(), margin);
closeEnough(0.6190476, cumHaz1.evaluate(2.0).getY(), margin);
closeEnough(0.6190476, cumHaz1.evaluate(2.5).getY(), margin);
final MathFunction cumHaz2 = functions.getCauseSpecificHazardFunction(2);
closeEnough(0.0, cumHaz2.evaluate(1.0).getY(), margin);
closeEnough(0.2, cumHaz2.evaluate(1.5).getY(), margin);
closeEnough(0.5333333, cumHaz2.evaluate(2.0).getY(), margin);
closeEnough(0.5333333, cumHaz2.evaluate(2.5).getY(), margin);
/* Time = 1.0 1.5 2.0 2.5
Cumulative Incidence Curve. Each row for one event.
[,1] [,2] [,3] [,4]
[1,] 0.2857143 0.2857143 0.4761905 0.4761905
[2,] 0.0000000 0.1428571 0.3333333 0.3333333
*/
final MathFunction cic1 = functions.getCumulativeIncidenceFunction(1);
closeEnough(0.2857143, cic1.evaluate(1.0).getY(), margin);
closeEnough(0.2857143, cic1.evaluate(1.5).getY(), margin);
closeEnough(0.4761905, cic1.evaluate(2.0).getY(), margin);
closeEnough(0.4761905, cic1.evaluate(2.5).getY(), margin);
final MathFunction cic2 = functions.getCumulativeIncidenceFunction(2);
closeEnough(0.0, cic2.evaluate(1.0).getY(), margin);
closeEnough(0.1428571, cic2.evaluate(1.5).getY(), margin);
closeEnough(0.3333333, cic2.evaluate(2.0).getY(), margin);
closeEnough(0.3333333, cic2.evaluate(2.5).getY(), margin);
}
}