Migrate to Java 1.8

pom.xml

@@ -9,9 +9,9 @@
     <version>1.0-SNAPSHOT</version>
 
     <properties>
-        <java.version>1.10</java.version>
+        <java.version>1.8</java.version>
-        <maven.compiler.target>1.10</maven.compiler.target>
+        <maven.compiler.target>1.8</maven.compiler.target>
-        <maven.compiler.source>1.10</maven.compiler.source>
+        <maven.compiler.source>1.8</maven.compiler.source>
         <jackson.version>2.9.6</jackson.version>
     </properties>
 

src/main/java/ca/joeltherrien/randomforest/Main.java

@@ -161,10 +161,10 @@ public class Main {
         yVarSettings.set("name", new TextNode("y"));
 
         final Settings settings =  Settings.builder()
-                .covariates(List.of(
+                .covariates(Utils.easyList(
                         new NumericCovariateSettings("x1"),
                         new BooleanCovariateSettings("x2"),
-                        new FactorCovariateSettings("x3", List.of("cat", "mouse", "dog"))
+                        new FactorCovariateSettings("x3", Utils.easyList("cat", "mouse", "dog"))
                         )
                 )
                 .dataFileLocation("data.csv")

src/main/java/ca/joeltherrien/randomforest/utils/Utils.java

@@ -64,5 +64,92 @@ public class Utils {
         }
     }
 
+    /**
+     * Replacement for Java 9's List.of
+     *
+     * @param array
+     * @param <T>
+     * @return A list
+     */
+    public static <T> List<T> easyList(T... array){
+        final List<T> list = new ArrayList<>(array.length);
+
+        for(final T item : array){
+            list.add(item);
+        }
+
+        return list;
+
+    }
+
+    /**
+     * Replacement for Java 9's Map.of
+     *
+     * @param array
+     * @return A map
+     */
+    public static Map easyMap(Object... array){
+        if(array.length % 2 != 0){
+            throw new IllegalArgumentException("Must provide a value for every key");
+        }
+
+        final Map map = new HashMap();
+        for(int i=0; i<array.length; i+=2){
+            map.put(array[i], array[i+1]);
+        }
+
+        return map;
+    }
+
+    /**
+     * Replacement for Java 9's Map.of
+     * @return A map
+     */
+    public static <K,V> Map<K,V> easyMap(K k1, V v1){
+        final Map<K,V> map = new HashMap<>();
+        map.put(k1, v1);
+
+        return map;
+    }
+
+    /**
+     * Replacement for Java 9's Map.of
+     * @return A map
+     */
+    public static <K,V> Map<K,V> easyMap(K k1, V v1, K k2, V v2){
+        final Map<K,V> map = new HashMap<>();
+        map.put(k1, v1);
+        map.put(k2, v2);
+
+        return map;
+    }
+
+    /**
+     * Replacement for Java 9's Map.of
+     * @return A map
+     */
+    public static <K,V> Map<K,V> easyMap(K k1, V v1, K k2, V v2, K k3, V v3){
+        final Map<K,V> map = new HashMap<>();
+        map.put(k1, v1);
+        map.put(k2, v2);
+        map.put(k3, v3);
+
+        return map;
+    }
+
+    /**
+     * Replacement for Java 9's Map.of
+     * @return A map
+     */
+    public static <K,V> Map<K,V> easyMap(K k1, V v1, K k2, V v2, K k3, V v3, K k4, V v4){
+        final Map<K,V> map = new HashMap<>();
+        map.put(k1, v1);
+        map.put(k2, v2);
+        map.put(k3, v3);
+        map.put(k4, v4);
+
+        return map;
+    }
+
 
 }

src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java

@@ -8,6 +8,7 @@ import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctio
 import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
 import ca.joeltherrien.randomforest.tree.Forest;
 import ca.joeltherrien.randomforest.tree.ForestTrainer;
+import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.*;
 import org.junit.jupiter.api.Test;
 import static org.junit.jupiter.api.Assertions.*;
@@ -35,7 +36,7 @@ public class TestSavingLoading {
         final ObjectNode responseCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
         responseCombinerSettings.set("type", new TextNode("CompetingRiskResponseCombiner"));
         responseCombinerSettings.set("events",
-                new ArrayNode(JsonNodeFactory.instance, List.of(new IntNode(1), new IntNode(2)))
+                new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
         );
         // not setting times
 
@@ -43,7 +44,7 @@ public class TestSavingLoading {
         final ObjectNode treeCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
         treeCombinerSettings.set("type", new TextNode("CompetingRiskFunctionCombiner"));
         treeCombinerSettings.set("events",
-                new ArrayNode(JsonNodeFactory.instance, List.of(new IntNode(1), new IntNode(2)))
+                new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
         );
         // not setting times
 
@@ -53,7 +54,7 @@ public class TestSavingLoading {
         yVarSettings.set("delta", new TextNode("status"));
 
         return Settings.builder()
-                .covariates(List.of(
+                .covariates(Utils.easyList(
                         new NumericCovariateSettings("ageatfda"),
                         new BooleanCovariateSettings("idu"),
                         new BooleanCovariateSettings("black"),
@@ -78,7 +79,7 @@ public class TestSavingLoading {
     }
 
     public CovariateRow getPredictionRow(List<Covariate> covariates){
-        return CovariateRow.createSimple(Map.of(
+        return CovariateRow.createSimple(Utils.easyMap(
                 "ageatfda", "35",
                 "idu", "false",
                 "black", "false",

src/test/java/ca/joeltherrien/randomforest/TestUtils.java

@@ -77,7 +77,7 @@ public class TestUtils {
 
     @Test
     public void reduceListToSize(){
-        final List<Integer> testList = List.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
+        final List<Integer> testList = Utils.easyList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
 
         for(int i=0; i<100; i++) { // want to test many times to ensure it doesn't work just due to randomness
             final List<Integer> testList1 = new ArrayList<>(testList);

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

@@ -9,6 +9,7 @@ import ca.joeltherrien.randomforest.tree.Node;
 import ca.joeltherrien.randomforest.tree.TreeTrainer;
 import ca.joeltherrien.randomforest.utils.MathFunction;
 import ca.joeltherrien.randomforest.utils.Point;
+import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.*;
 import org.junit.jupiter.api.Test;
 
@@ -37,7 +38,7 @@ public class TestCompetingRisk {
         final ObjectNode responseCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
         responseCombinerSettings.set("type", new TextNode("CompetingRiskResponseCombiner"));
         responseCombinerSettings.set("events",
-                new ArrayNode(JsonNodeFactory.instance, List.of(new IntNode(1), new IntNode(2)))
+                new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
         );
         // not setting times
 
@@ -45,7 +46,7 @@ public class TestCompetingRisk {
         final ObjectNode treeCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
         treeCombinerSettings.set("type", new TextNode("CompetingRiskFunctionCombiner"));
         treeCombinerSettings.set("events",
-                new ArrayNode(JsonNodeFactory.instance, List.of(new IntNode(1), new IntNode(2)))
+                new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
         );
         // not setting times
 
@@ -55,7 +56,7 @@ public class TestCompetingRisk {
         yVarSettings.set("delta", new TextNode("status"));
 
         return Settings.builder()
-                .covariates(List.of(
+                .covariates(Utils.easyList(
                         new NumericCovariateSettings("ageatfda"),
                         new BooleanCovariateSettings("idu"),
                         new BooleanCovariateSettings("black"),
@@ -84,7 +85,7 @@ public class TestCompetingRisk {
     }
 
     public CovariateRow getPredictionRow(List<Covariate> covariates){
-        return CovariateRow.createSimple(Map.of(
+        return CovariateRow.createSimple(Utils.easyMap(
                 "ageatfda", "35",
                 "idu", "false",
                 "black", "false",
@@ -96,7 +97,7 @@ public class TestCompetingRisk {
     public void testSingleTree() throws IOException {
         final Settings settings = getSettings();
         settings.setDataFileLocation("src/test/resources/wihs.bootstrapped.csv");
-        settings.setCovariates(List.of(
+        settings.setCovariates(Utils.easyList(
                 new BooleanCovariateSettings("idu"),
                 new BooleanCovariateSettings("black")
                 )); // by only using BooleanCovariates (only one split rule) we can guarantee identical results with randomForestSRC on one tree.
@@ -199,7 +200,7 @@ public class TestCompetingRisk {
     @Test
     public void testLogRankSingleGroupDifferentiatorTwoBooleans() throws IOException {
         final Settings settings = getSettings();
-        settings.setCovariates(List.of(
+        settings.setCovariates(Utils.easyList(
                 new BooleanCovariateSettings("idu"),
                 new BooleanCovariateSettings("black")
         ));

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

@@ -5,6 +5,7 @@ import ca.joeltherrien.randomforest.responses.competingrisk.*;
 import ca.joeltherrien.randomforest.tree.Forest;
 import ca.joeltherrien.randomforest.utils.MathFunction;
 import ca.joeltherrien.randomforest.utils.Point;
+import ca.joeltherrien.randomforest.utils.Utils;
 import org.junit.jupiter.api.Test;
 
 import java.util.Collections;
@@ -26,7 +27,7 @@ public class TestCompetingRiskErrorRateCalculator {
         final CompetingRiskResponse response4 = new CompetingRiskResponse(1, 3.0);
 
         final double[] mortalityArray = new double[]{1, 4, 3, 9};
-        final List<CompetingRiskResponse> responseList = List.of(response1, response2, response3, response4);
+        final List<CompetingRiskResponse> responseList = Utils.easyList(response1, response2, response3, response4);
 
         final int event = 1;
 
@@ -52,7 +53,7 @@ public class TestCompetingRiskErrorRateCalculator {
         final CompetingRiskResponse response3 = new CompetingRiskResponse(2, 8.0);
         final CompetingRiskResponse response4 = new CompetingRiskResponse(1, 3.0);
 
-        final List<Row<CompetingRiskResponse>> dataset = List.of(
+        final List<Row<CompetingRiskResponse>> dataset = Utils.easyList(
                 new Row<>(Collections.emptyMap(), 1, response1),
                 new Row<>(Collections.emptyMap(), 2, response2),
                 new Row<>(Collections.emptyMap(), 3, response3),

src/test/java/ca/joeltherrien/randomforest/covariates/FactorCovariateTest.java

@@ -1,6 +1,7 @@
 package ca.joeltherrien.randomforest.covariates;
 
 
+import ca.joeltherrien.randomforest.utils.Utils;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.function.Executable;
 
@@ -55,7 +56,7 @@ public class FactorCovariateTest {
 
 
     private FactorCovariate createTestCovariate(){
-        final List<String> levels = List.of("DOG", "CAT", "MOUSE");
+        final List<String> levels = Utils.easyList("DOG", "CAT", "MOUSE");
 
         return new FactorCovariate("pet", levels);
     }

src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java

@@ -7,6 +7,7 @@ import ca.joeltherrien.randomforest.covariates.BooleanCovariateSettings;
 import ca.joeltherrien.randomforest.covariates.Covariate;
 import ca.joeltherrien.randomforest.covariates.FactorCovariateSettings;
 import ca.joeltherrien.randomforest.covariates.NumericCovariateSettings;
+import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.JsonNodeFactory;
 import com.fasterxml.jackson.databind.node.ObjectNode;
 import com.fasterxml.jackson.databind.node.TextNode;
@@ -37,8 +38,8 @@ public class TestLoadingCSV {
         final Settings settings = Settings.builder()
                 .dataFileLocation(filename)
                 .covariates(
-                        List.of(new NumericCovariateSettings("x1"),
+                        Utils.easyList(new NumericCovariateSettings("x1"),
-                                new FactorCovariateSettings("x2", List.of("dog", "cat", "mouse")),
+                                new FactorCovariateSettings("x2", Utils.easyList("dog", "cat", "mouse")),
                                 new BooleanCovariateSettings("x3"))
                 )
                 .yVarSettings(yVarSettings)

src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java

@@ -4,6 +4,7 @@ import ca.joeltherrien.randomforest.Settings;
 import static org.junit.jupiter.api.Assertions.assertEquals;
 
 import ca.joeltherrien.randomforest.covariates.*;
+import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.JsonNodeFactory;
 import com.fasterxml.jackson.databind.node.ObjectNode;
 import com.fasterxml.jackson.databind.node.TextNode;
@@ -31,10 +32,10 @@ public class TestPersistence {
         yVarSettings.set("name", new TextNode("y"));
 
         final Settings settingsOriginal =  Settings.builder()
-                .covariates(List.of(
+                .covariates(Utils.easyList(
                         new NumericCovariateSettings("x1"),
                         new BooleanCovariateSettings("x2"),
-                        new FactorCovariateSettings("x3", List.of("cat", "mouse", "dog"))
+                        new FactorCovariateSettings("x3", Utils.easyList("cat", "mouse", "dog"))
                         )
                 )
                 .dataFileLocation("data.csv")

src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java

@@ -9,6 +9,7 @@ import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
 import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
 import ca.joeltherrien.randomforest.tree.Node;
 import ca.joeltherrien.randomforest.tree.TreeTrainer;
+import ca.joeltherrien.randomforest.utils.Utils;
 
 import java.util.*;
 import java.util.stream.Collectors;
@@ -48,7 +49,7 @@ public class TrainSingleTree {
             trainingSet.add(generateRow(x1, x2, i));
         }
 
-        final List<Covariate> covariateNames = List.of(x1Covariate, x2Covariate);
+        final List<Covariate> covariateNames = Utils.easyList(x1Covariate, x2Covariate);
 
         final TreeTrainer<Double, Double> treeTrainer = TreeTrainer.<Double, Double>builder()
                 .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
@@ -99,7 +100,7 @@ public class TrainSingleTree {
 	public static Row<Double> generateRow(Covariate.Value<Double> x1, Covariate.Value<Double> x2, int id){
 	    double y = generateResponse(x1.getValue(), x2.getValue());
 
-	    final Map<String, Covariate.Value> map = Map.of("x1", x1, "x2", x2);
+	    final Map<String, Covariate.Value> map = Utils.easyMap("x1", x1, "x2", x2);
 
         return new Row<>(map, id, y);
 
@@ -107,7 +108,7 @@ public class TrainSingleTree {
 
 
     public static CovariateRow generateCovariateRow(Covariate.Value x1, Covariate.Value x2, int id){
-        final Map<String, Covariate.Value> map = Map.of("x1", x1, "x2", x2);
+        final Map<String, Covariate.Value> map = Utils.easyMap("x1", x1, "x2", x2);
 
         return new CovariateRow(map, id);
 

src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java

@@ -9,6 +9,7 @@ import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
 import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
 import ca.joeltherrien.randomforest.tree.Node;
 import ca.joeltherrien.randomforest.tree.TreeTrainer;
+import ca.joeltherrien.randomforest.utils.Utils;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -29,7 +30,7 @@ public class TrainSingleTreeFactor {
 
         final Covariate<Double> x1Covariate = new NumericCovariate("x1");
         final Covariate<Double> x2Covariate = new NumericCovariate("x2");
-        final FactorCovariate x3Covariate = new FactorCovariate("x3", List.of("cat", "dog", "mouse"));
+        final FactorCovariate x3Covariate = new FactorCovariate("x3", Utils.easyList("cat", "dog", "mouse"));
 
         final List<Covariate.Value<Double>> x1List = DoubleStream
                 .generate(() -> random.nextDouble()*10.0)
@@ -69,7 +70,7 @@ public class TrainSingleTreeFactor {
             trainingSet.add(generateRow(x1, x2, x3, i));
         }
 
-        final List<Covariate> covariateNames = List.of(x1Covariate, x2Covariate);
+        final List<Covariate> covariateNames = Utils.easyList(x1Covariate, x2Covariate);
 
         final TreeTrainer<Double, Double> treeTrainer = TreeTrainer.<Double, Double>builder()
                 .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
@@ -127,7 +128,7 @@ public class TrainSingleTreeFactor {
 	public static Row<Double> generateRow(Covariate.Value<Double> x1, Covariate.Value<Double> x2, Covariate.Value<String> x3, int id){
 	    double y = generateResponse(x1.getValue(), x2.getValue(), x3.getValue());
 
-	    final Map<String, Covariate.Value> map = Map.of("x1", x1, "x2", x2);
+	    final Map<String, Covariate.Value> map = Utils.easyMap("x1", x1, "x2", x2);
 
         return new Row<>(map, id, y);
 
@@ -135,7 +136,7 @@ public class TrainSingleTreeFactor {
 
 
     public static CovariateRow generateCovariateRow(Covariate.Value x1, Covariate.Value x2, Covariate.Value x3, int id){
-        final Map<String, Covariate.Value> map = Map.of("x1", x1, "x2", x2, "x3", x3);
+        final Map<String, Covariate.Value> map = Utils.easyMap("x1", x1, "x2", x2, "x3", x3);
 
         return new CovariateRow(map, id);