Add test verifying that CIFs are averaged together in the same way as randomForestSRC

src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRiskFunctionCombiner.java

@@ -0,0 +1,123 @@
+/*
+ * Copyright (c) 2019 Joel Therrien.
+ *     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 <https://www.gnu.org/licenses/>.
+ */
+
+package ca.joeltherrien.randomforest.competingrisk;
+
+import ca.joeltherrien.randomforest.TestUtils;
+import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctions;
+import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
+import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskFunctionCombiner;
+import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskResponseCombiner;
+import ca.joeltherrien.randomforest.utils.RightContinuousStepFunction;
+import ca.joeltherrien.randomforest.utils.Utils;
+import org.junit.jupiter.api.Test;
+
+import java.util.List;
+
+public class TestCompetingRiskFunctionCombiner {
+    private final int[] events = new int[]{1,2};
+
+    private CompetingRiskFunctions createFunction(List<CompetingRiskResponse> responses){
+        final CompetingRiskResponseCombiner responseCombiner = new CompetingRiskResponseCombiner(events);
+
+        return responseCombiner.combine(responses);
+    }
+
+    /* Data used in R code to compare with randomForestSRC
+
+    data <- data.frame(u     =c(1,1,2,3,3,   2,2,3,4,4),
+                   delta =c(2,1,1,1,0,   2,1,1,1,0))
+     */
+
+    @Test
+    public void testFuncionCombiner(){
+        final List<CompetingRiskResponse> set1 = Utils.easyList(
+              new CompetingRiskResponse(2, 1.0),
+              new CompetingRiskResponse(1, 1.0),
+                new CompetingRiskResponse(1, 2.0),
+                new CompetingRiskResponse(1, 3.0),
+                new CompetingRiskResponse(0, 3.0)
+        );
+
+        final List<CompetingRiskResponse> set2 = Utils.easyList(
+                new CompetingRiskResponse(2, 2.0),
+                new CompetingRiskResponse(1, 2.0),
+                new CompetingRiskResponse(1, 3.0),
+                new CompetingRiskResponse(1, 4.0),
+                new CompetingRiskResponse(0, 4.0)
+        );
+
+        final CompetingRiskFunctions fun1 = createFunction(set1);
+        final CompetingRiskFunctions fun2 = createFunction(set2);
+
+        final CompetingRiskFunctionCombiner combiner = new CompetingRiskFunctionCombiner(new int[]{1,2}, null);
+
+        final CompetingRiskFunctions combinedFunction = combiner.combine(Utils.easyList(fun1, fun2));
+
+        final RightContinuousStepFunction cif_1 = combinedFunction.getCumulativeIncidenceFunction(1);
+        final RightContinuousStepFunction cif_2 = combinedFunction.getCumulativeIncidenceFunction(2);
+
+        /* Result from randomForestSRC
+                , , CIF.1
+
+             [,1] [,2] [,3] [,4]
+        [1,]  0.1  0.3  0.5  0.6
+
+        , , CIF.2
+
+             [,1] [,2] [,3] [,4]
+        [1,]  0.1  0.2  0.2  0.2
+         */
+
+        TestUtils.closeEnough(0.1, cif_1.evaluate(1.0), 0.01);
+        TestUtils.closeEnough(0.3, cif_1.evaluate(2.0), 0.01);
+        TestUtils.closeEnough(0.5, cif_1.evaluate(3.0), 0.01);
+        TestUtils.closeEnough(0.6, cif_1.evaluate(4.0), 0.01);
+
+        TestUtils.closeEnough(0.1, cif_2.evaluate(1.0), 0.01);
+        TestUtils.closeEnough(0.2, cif_2.evaluate(2.0), 0.01);
+        TestUtils.closeEnough(0.2, cif_2.evaluate(3.0), 0.01);
+        TestUtils.closeEnough(0.2, cif_2.evaluate(4.0), 0.01);
+
+
+    }
+
+
+}
+
+/* Code to get randomForestSRC results; last tested on version 2.9.0
+
+library(randomForestSRC)
+data <- data.frame(u     =c(1,1,2,3,3,   2,2,3,4,4),
+                   delta =c(2,1,1,1,0,   2,1,1,1,0),
+                   x     =c(0,0,0,0,0,   1,1,1,1,1))
+
+bootstrap.matrix <- matrix(0, nrow=nrow(data), ncol=2)
+bootstrap.matrix[1:5,1] <- 1
+bootstrap.matrix[6:10,2] <- 1
+
+
+model.rfsrc <- rfsrc(Surv(u, delta) ~ x, data,
+                     nodedepth = 0, splitrule="logrank",
+                     bootstrap="by.user", samp=bootstrap.matrix,
+                     ntree=2
+                     )
+
+new.data <- data.frame(x=c(1))
+
+prediction <- predict(model.rfsrc, new.data)
+prediction$cif
+ */