diff --git a/pmd-rules.xml b/pmd-rules.xml new file mode 100644 index 0000000..abad748 --- /dev/null +++ b/pmd-rules.xml @@ -0,0 +1,93 @@ + + + + + + The default ruleset used by the Maven PMD Plugin, when no other ruleset is specified. + It contains the rules of the old (pre PMD 6.0.0) rulesets java-basic, java-empty, java-imports, + java-unnecessary, java-unusedcode. + + This ruleset might be used as a starting point for an own customized ruleset [0]. + + [0] https://pmd.github.io/latest/pmd_userdocs_understanding_rulesets.html + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/pom.xml b/pom.xml index 5d6ba5b..6d22d2b 100644 --- a/pom.xml +++ b/pom.xml @@ -13,6 +13,9 @@ 1.8 1.8 2.9.6 + + UTF-8 + UTF-8 @@ -89,9 +92,27 @@ + + org.apache.maven.plugins + maven-pmd-plugin + 3.11.0 + + + package + + check + + + + + + + ${project.basedir}/pmd-rules.xml + + + - \ No newline at end of file diff --git a/src/main/java/ca/joeltherrien/randomforest/Bootstrapper.java b/src/main/java/ca/joeltherrien/randomforest/Bootstrapper.java index b73db9d..a7577db 100644 --- a/src/main/java/ca/joeltherrien/randomforest/Bootstrapper.java +++ b/src/main/java/ca/joeltherrien/randomforest/Bootstrapper.java @@ -4,20 +4,20 @@ import lombok.RequiredArgsConstructor; import java.util.ArrayList; import java.util.List; -import java.util.concurrent.ThreadLocalRandom; +import java.util.Random; @RequiredArgsConstructor public class Bootstrapper { final private List originalData; - public List bootstrap(){ + public List bootstrap(Random random){ final int n = originalData.size(); final List newList = new ArrayList<>(n); for(int i=0; i getCovariateValue(Covariate covariate){ + public Covariate.Value getCovariateValue(Covariate covariate){ return valueArray[covariate.getIndex()]; } diff --git a/src/main/java/ca/joeltherrien/randomforest/DataLoader.java b/src/main/java/ca/joeltherrien/randomforest/DataLoader.java index 25e8465..5118fdc 100644 --- a/src/main/java/ca/joeltherrien/randomforest/DataLoader.java +++ b/src/main/java/ca/joeltherrien/randomforest/DataLoader.java @@ -58,7 +58,7 @@ public class DataLoader { throw new IllegalArgumentException("Tree directory must be a directory!"); } - final File[] treeFiles = folder.listFiles(((file, s) -> s.endsWith(".tree"))); + final File[] treeFiles = folder.listFiles((file, s) -> s.endsWith(".tree")); final List treeFileList = Arrays.asList(treeFiles); Collections.sort(treeFileList, Comparator.comparing(File::getName)); diff --git a/src/main/java/ca/joeltherrien/randomforest/Main.java b/src/main/java/ca/joeltherrien/randomforest/Main.java index f9b7194..f5a7731 100644 --- a/src/main/java/ca/joeltherrien/randomforest/Main.java +++ b/src/main/java/ca/joeltherrien/randomforest/Main.java @@ -1,9 +1,9 @@ package ca.joeltherrien.randomforest; -import ca.joeltherrien.randomforest.covariates.BooleanCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings; import ca.joeltherrien.randomforest.covariates.Covariate; -import ca.joeltherrien.randomforest.covariates.FactorCovariateSettings; -import ca.joeltherrien.randomforest.covariates.NumericCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.FactorCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskErrorRateCalculator; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctions; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; diff --git a/src/main/java/ca/joeltherrien/randomforest/Row.java b/src/main/java/ca/joeltherrien/randomforest/Row.java index 850f035..00c5078 100644 --- a/src/main/java/ca/joeltherrien/randomforest/Row.java +++ b/src/main/java/ca/joeltherrien/randomforest/Row.java @@ -17,6 +17,8 @@ public class Row extends CovariateRow { } + + public Y getResponse() { return this.response; } diff --git a/src/main/java/ca/joeltherrien/randomforest/Settings.java b/src/main/java/ca/joeltherrien/randomforest/Settings.java index ee40a35..c89681c 100644 --- a/src/main/java/ca/joeltherrien/randomforest/Settings.java +++ b/src/main/java/ca/joeltherrien/randomforest/Settings.java @@ -1,7 +1,7 @@ package ca.joeltherrien.randomforest; import ca.joeltherrien.randomforest.covariates.Covariate; -import ca.joeltherrien.randomforest.covariates.CovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.CovariateSettings; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponseWithCensorTime; import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskFunctionCombiner; @@ -10,7 +10,6 @@ import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.GrayL import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.GrayLogRankSingleGroupDifferentiator; import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankMultipleGroupDifferentiator; import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankSingleGroupDifferentiator; -import ca.joeltherrien.randomforest.responses.regression.MeanGroupDifferentiator; import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner; import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator; import ca.joeltherrien.randomforest.tree.GroupDifferentiator; @@ -68,9 +67,6 @@ public class Settings { GROUP_DIFFERENTIATOR_MAP.put(name.toLowerCase(), groupDifferentiatorConstructor); } static{ - registerGroupDifferentiatorConstructor("MeanGroupDifferentiator", - (node) -> new MeanGroupDifferentiator() - ); registerGroupDifferentiatorConstructor("WeightedVarianceGroupDifferentiator", (node) -> new WeightedVarianceGroupDifferentiator() ); diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariate.java index 8959bc4..741fc2a 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariate.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariate.java @@ -1,14 +1,15 @@ package ca.joeltherrien.randomforest.covariates; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.tree.Split; +import ca.joeltherrien.randomforest.utils.SingletonIterator; import lombok.Getter; import lombok.RequiredArgsConstructor; -import java.util.Collection; -import java.util.Collections; -import java.util.List; +import java.util.*; @RequiredArgsConstructor -public final class BooleanCovariate implements Covariate{ +public final class BooleanCovariate implements Covariate { @Getter private final String name; @@ -16,11 +17,13 @@ public final class BooleanCovariate implements Covariate{ @Getter private final int index; + private boolean hasNAs = false; + private final BooleanSplitRule splitRule = new BooleanSplitRule(); // there's only one possible rule for BooleanCovariates. @Override - public Collection generateSplitRules(List> data, int number) { - return Collections.singleton(splitRule); + public Iterator> generateSplitRuleUpdater(List> data, int number, Random random) { + return new SingletonIterator<>(this.splitRule.applyRule(data)); } @Override @@ -31,6 +34,7 @@ public final class BooleanCovariate implements Covariate{ @Override public Value createValue(String value) { if(value == null || value.equalsIgnoreCase("na")){ + hasNAs = true; return createValue( (Boolean) null); } @@ -45,6 +49,11 @@ public final class BooleanCovariate implements Covariate{ } } + @Override + public boolean hasNAs() { + return hasNAs; + } + @Override public String toString(){ return "BooleanCovariate(name=" + name + ")"; @@ -74,6 +83,7 @@ public final class BooleanCovariate implements Covariate{ } } + public class BooleanSplitRule implements SplitRule{ @Override diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/Covariate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/Covariate.java index 9fa77ef..95c64df 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/Covariate.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/Covariate.java @@ -5,10 +5,7 @@ import ca.joeltherrien.randomforest.Row; import ca.joeltherrien.randomforest.tree.Split; import java.io.Serializable; -import java.util.ArrayList; -import java.util.Collection; -import java.util.LinkedList; -import java.util.List; +import java.util.*; import java.util.concurrent.ThreadLocalRandom; public interface Covariate extends Serializable { @@ -17,7 +14,7 @@ public interface Covariate extends Serializable { int getIndex(); - Collection> generateSplitRules(final List> data, final int number); + Iterator> generateSplitRuleUpdater(final List> data, final int number, final Random random); Value createValue(V value); @@ -29,6 +26,8 @@ public interface Covariate extends Serializable { */ Value createValue(String value); + boolean hasNAs(); + interface Value extends Serializable{ Covariate getParent(); @@ -39,6 +38,17 @@ public interface Covariate extends Serializable { } + interface SplitRuleUpdater extends Iterator>{ + Split currentSplit(); + boolean currentSplitValid(); + SplitUpdate nextUpdate(); + } + + interface SplitUpdate { + SplitRule getSplitRule(); + Collection> rowsMovedToLeftHand(); + } + interface SplitRule extends Serializable{ Covariate getParent(); @@ -51,7 +61,7 @@ public interface Covariate extends Serializable { * @param * @return */ - default Split applyRule(List> rows) { + default Split applyRule(List> rows) { final List> leftHand = new LinkedList<>(); final List> rightHand = new LinkedList<>(); @@ -59,7 +69,7 @@ public interface Covariate extends Serializable { for(final Row row : rows) { - final Value value = (Value) row.getCovariateValue(getParent()); + final Value value = row.getCovariateValue(getParent()); if(value.isNA()){ missingValueRows.add(row); @@ -77,11 +87,11 @@ public interface Covariate extends Serializable { } - return new Split<>(leftHand, rightHand, missingValueRows); + return new Split<>(this, leftHand, rightHand, missingValueRows); } default boolean isLeftHand(CovariateRow row, final double probabilityNaLeftHand){ - final Value value = (Value) row.getCovariateValue(getParent()); + final Value value = row.getCovariateValue(getParent()); if(value.isNA()){ return ThreadLocalRandom.current().nextDouble() <= probabilityNaLeftHand; diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariate.java index 402cb7d..e0f4101 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariate.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariate.java @@ -1,10 +1,11 @@ package ca.joeltherrien.randomforest.covariates; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.tree.Split; import lombok.EqualsAndHashCode; import lombok.Getter; import java.util.*; -import java.util.concurrent.ThreadLocalRandom; public final class FactorCovariate implements Covariate{ @@ -18,6 +19,8 @@ public final class FactorCovariate implements Covariate{ private final FactorValue naValue; private final int numberOfPossiblePairings; + private boolean hasNAs; + public FactorCovariate(final String name, final int index, List levels){ this.name = name; @@ -42,17 +45,14 @@ public final class FactorCovariate implements Covariate{ @Override - public Set generateSplitRules(List> data, int number) { - final Set splitRules = new HashSet<>(); + public Iterator> generateSplitRuleUpdater(List> data, int number, Random random) { + final Set> splits = new HashSet<>(); // This is to ensure we don't get stuck in an infinite loop for small factors number = Math.min(number, numberOfPossiblePairings); - final Random random = ThreadLocalRandom.current(); final List levels = new ArrayList<>(factorLevels.values()); - - - while(splitRules.size() < number){ + while(splits.size() < number){ Collections.shuffle(levels, random); final Set leftSideValues = new HashSet<>(); leftSideValues.add(levels.get(0)); @@ -63,16 +63,18 @@ public final class FactorCovariate implements Covariate{ } } - splitRules.add(new FactorSplitRule(leftSideValues)); + splits.add(new FactorSplitRule(leftSideValues).applyRule(data)); } - return splitRules; + return splits.iterator(); } + @Override public FactorValue createValue(String value) { if(value == null || value.equalsIgnoreCase("na")){ + this.hasNAs = true; return this.naValue; } @@ -85,6 +87,12 @@ public final class FactorCovariate implements Covariate{ return factorValue; } + + @Override + public boolean hasNAs() { + return hasNAs; + } + @Override public String toString(){ return "FactorCovariate(name=" + name + ")"; diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java similarity index 51% rename from src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariate.java rename to src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java index a268ba8..9b23d08 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariate.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java @@ -1,17 +1,22 @@ -package ca.joeltherrien.randomforest.covariates; +package ca.joeltherrien.randomforest.covariates.numeric; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.covariates.Covariate; +import ca.joeltherrien.randomforest.utils.IndexedIterator; +import ca.joeltherrien.randomforest.utils.UniqueSubsetValueIterator; +import ca.joeltherrien.randomforest.utils.UniqueValueIterator; import lombok.EqualsAndHashCode; import lombok.Getter; import lombok.RequiredArgsConstructor; import lombok.ToString; import java.util.*; -import java.util.concurrent.ThreadLocalRandom; import java.util.stream.Collectors; +import java.util.stream.Stream; @RequiredArgsConstructor @ToString -public final class NumericCovariate implements Covariate{ +public final class NumericCovariate implements Covariate { @Getter private final String name; @@ -19,42 +24,51 @@ public final class NumericCovariate implements Covariate{ @Getter private final int index; + private boolean hasNAs = false; + @Override - public Collection generateSplitRules(List> data, int number) { + public NumericSplitRuleUpdater generateSplitRuleUpdater(List> data, int number, Random random) { + Stream> stream = data.stream(); - final Random random = ThreadLocalRandom.current(); - - // only work with non-NA values - data = data.stream().filter(value -> !value.isNA()).collect(Collectors.toList()); - //data = data.stream().filter(value -> !value.isNA()).distinct().collect(Collectors.toList()); // TODO which to use? - - // for this implementation we need to shuffle the data - final List> shuffledData; - if(number >= data.size()){ - shuffledData = new ArrayList<>(data); - Collections.shuffle(shuffledData, random); + if(hasNAs()){ + stream = stream.filter(row -> !row.getCovariateValue(this).isNA()); } - else{ // only need the top number entries - shuffledData = new ArrayList<>(number); - final Set indexesToUse = new HashSet<>(); - //final List indexesToUse = new ArrayList<>(); // TODO which to use? - while(indexesToUse.size() < number){ - final int index = random.nextInt(data.size()); + data = stream + .sorted((r1, r2) -> { + Double d1 = r1.getCovariateValue(this).getValue(); + Double d2 = r2.getCovariateValue(this).getValue(); - if(indexesToUse.add(index)){ - shuffledData.add(data.get(index)); - } + return d1.compareTo(d2); + }) + .collect(Collectors.toList()); + + Iterator sortedDataIterator = data.stream() + .map(row -> row.getCovariateValue(this).getValue()) + .iterator(); + + + final IndexedIterator dataIterator; + if(number == 0){ + dataIterator = new UniqueValueIterator<>(sortedDataIterator); + } + else{ + final TreeSet indexSet = new TreeSet<>(); + + final int maxIndex = data.size(); + + for(int i=0; i( + new UniqueValueIterator<>(sortedDataIterator), + indexSet.toArray(new Integer[indexSet.size()]) + ); + } - return shuffledData.stream() - .mapToDouble(v -> v.getValue()) - .mapToObj(threshold -> new NumericSplitRule(threshold)) - .collect(Collectors.toSet()); - // by returning a set we'll make everything far more efficient as a lot of rules can repeat due to bootstrapping - + return new NumericSplitRuleUpdater<>(this, data, dataIterator); } @@ -66,12 +80,19 @@ public final class NumericCovariate implements Covariate{ @Override public NumericValue createValue(String value) { if(value == null || value.equalsIgnoreCase("na")){ + this.hasNAs = true; return createValue((Double) null); } return createValue(Double.parseDouble(value)); } + + @Override + public boolean hasNAs() { + return hasNAs; + } + @EqualsAndHashCode public class NumericValue implements Covariate.Value{ @@ -102,7 +123,7 @@ public final class NumericCovariate implements Covariate{ private final double threshold; - private NumericSplitRule(final double threshold){ + NumericSplitRule(final double threshold){ this.threshold = threshold; } diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitRuleUpdater.java b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitRuleUpdater.java new file mode 100644 index 0000000..4f1586c --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitRuleUpdater.java @@ -0,0 +1,84 @@ +package ca.joeltherrien.randomforest.covariates.numeric; + +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.covariates.Covariate; +import ca.joeltherrien.randomforest.tree.Split; +import ca.joeltherrien.randomforest.utils.IndexedIterator; + +import java.util.Collections; +import java.util.List; + +public class NumericSplitRuleUpdater implements Covariate.SplitRuleUpdater { + + private final NumericCovariate covariate; + private final List> orderedData; + private final IndexedIterator dataIterator; + + private Split currentSplit; + + public NumericSplitRuleUpdater(final NumericCovariate covariate, final List> orderedData, final IndexedIterator iterator){ + this.covariate = covariate; + this.orderedData = orderedData; + this.dataIterator = iterator; + + final List> leftHandList = Collections.emptyList(); + final List> rightHandList = orderedData; + + this.currentSplit = new Split<>( + covariate.new NumericSplitRule(Double.MIN_VALUE), + leftHandList, + rightHandList, + Collections.emptyList()); + + } + + @Override + public Split currentSplit() { + return this.currentSplit; + } + + @Override + public boolean currentSplitValid() { + return currentSplit.getLeftHand().size() > 0 && currentSplit.getRightHand().size() > 0; + } + + @Override + public NumericSplitUpdate nextUpdate() { + if(hasNext()){ + final int currentPosition = dataIterator.getIndex(); + final Double splitValue = dataIterator.next(); + final int newPosition = dataIterator.getIndex(); + + final List> rowsMoved = orderedData.subList(currentPosition, newPosition); + + final NumericCovariate.NumericSplitRule splitRule = covariate.new NumericSplitRule(splitValue); + + // Update current split + this.currentSplit = new Split<>( + splitRule, + Collections.unmodifiableList(orderedData.subList(0, newPosition)), + Collections.unmodifiableList(orderedData.subList(newPosition, orderedData.size())), + Collections.emptyList()); + + + return new NumericSplitUpdate<>(splitRule, rowsMoved); + } + + return null; + } + + @Override + public boolean hasNext() { + return dataIterator.hasNext(); + } + + @Override + public Split next() { + if(hasNext()){ + nextUpdate(); + } + + return this.currentSplit(); + } + +} diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitUpdate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitUpdate.java new file mode 100644 index 0000000..f2757c0 --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericSplitUpdate.java @@ -0,0 +1,24 @@ +package ca.joeltherrien.randomforest.covariates.numeric; + +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.covariates.Covariate; +import lombok.AllArgsConstructor; + +import java.util.Collection; + +@AllArgsConstructor +public class NumericSplitUpdate implements Covariate.SplitUpdate { + + private final NumericCovariate.NumericSplitRule numericSplitRule; + private final Collection> rowsMoved; + + @Override + public NumericCovariate.NumericSplitRule getSplitRule() { + return numericSplitRule; + } + + @Override + public Collection> rowsMovedToLeftHand() { + return rowsMoved; + } +} diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariateSettings.java b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/BooleanCovariateSettings.java similarity index 75% rename from src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariateSettings.java rename to src/main/java/ca/joeltherrien/randomforest/covariates/settings/BooleanCovariateSettings.java index 5f57c15..ba6366e 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/BooleanCovariateSettings.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/BooleanCovariateSettings.java @@ -1,5 +1,6 @@ -package ca.joeltherrien.randomforest.covariates; +package ca.joeltherrien.randomforest.covariates.settings; +import ca.joeltherrien.randomforest.covariates.BooleanCovariate; import lombok.Data; import lombok.NoArgsConstructor; diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/CovariateSettings.java b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/CovariateSettings.java similarity index 87% rename from src/main/java/ca/joeltherrien/randomforest/covariates/CovariateSettings.java rename to src/main/java/ca/joeltherrien/randomforest/covariates/settings/CovariateSettings.java index 4d850ac..9b9f93c 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/CovariateSettings.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/CovariateSettings.java @@ -1,5 +1,6 @@ -package ca.joeltherrien.randomforest.covariates; +package ca.joeltherrien.randomforest.covariates.settings; +import ca.joeltherrien.randomforest.covariates.Covariate; import com.fasterxml.jackson.annotation.JsonSubTypes; import com.fasterxml.jackson.annotation.JsonTypeInfo; import lombok.Getter; diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariateSettings.java b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/FactorCovariateSettings.java similarity index 82% rename from src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariateSettings.java rename to src/main/java/ca/joeltherrien/randomforest/covariates/settings/FactorCovariateSettings.java index 9d7ece5..f40213c 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/FactorCovariateSettings.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/FactorCovariateSettings.java @@ -1,5 +1,6 @@ -package ca.joeltherrien.randomforest.covariates; +package ca.joeltherrien.randomforest.covariates.settings; +import ca.joeltherrien.randomforest.covariates.FactorCovariate; import lombok.Data; import lombok.NoArgsConstructor; diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariateSettings.java b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/NumericCovariateSettings.java similarity index 74% rename from src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariateSettings.java rename to src/main/java/ca/joeltherrien/randomforest/covariates/settings/NumericCovariateSettings.java index 9cdf898..84a69a7 100644 --- a/src/main/java/ca/joeltherrien/randomforest/covariates/NumericCovariateSettings.java +++ b/src/main/java/ca/joeltherrien/randomforest/covariates/settings/NumericCovariateSettings.java @@ -1,5 +1,6 @@ -package ca.joeltherrien.randomforest.covariates; +package ca.joeltherrien.randomforest.covariates.settings; +import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate; import lombok.Data; import lombok.NoArgsConstructor; diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskGraySetsImpl.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskGraySetsImpl.java index 6650dcb..2eced4c 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskGraySetsImpl.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskGraySetsImpl.java @@ -1,37 +1,77 @@ package ca.joeltherrien.randomforest.responses.competingrisk; -import ca.joeltherrien.randomforest.utils.MathFunction; -import lombok.Builder; -import lombok.Getter; +import java.util.Arrays; -import java.util.List; -import java.util.Map; +public class CompetingRiskGraySetsImpl implements CompetingRiskSets { -/** - * Represents a response from CompetingRiskUtils#calculateGraySetsEfficiently - * - */ -@Builder -@Getter -public class CompetingRiskGraySetsImpl implements CompetingRiskSets{ + final double[] times; // length m array + int[][] riskSetLeft; // J x m array + final int[][] riskSetTotal; // J x m array + int[][] numberOfEventsLeft; // J+1 x m array + final int[][] numberOfEventsTotal; // J+1 x m array - private final List eventTimes; - private final MathFunction[] riskSet; - private final Map numberOfEvents; - - @Override - public MathFunction getRiskSet(int event){ - return(riskSet[event-1]); + public CompetingRiskGraySetsImpl(double[] times, int[][] riskSetLeft, int[][] riskSetTotal, int[][] numberOfEventsLeft, int[][] numberOfEventsTotal) { + this.times = times; + this.riskSetLeft = riskSetLeft; + this.riskSetTotal = riskSetTotal; + this.numberOfEventsLeft = numberOfEventsLeft; + this.numberOfEventsTotal = numberOfEventsTotal; } @Override - public int getNumberOfEvents(Double time, int event){ - if(numberOfEvents.containsKey(time)){ - return numberOfEvents.get(time)[event]; + public double[] getDistinctTimes() { + return times; + } + + @Override + public int getRiskSetLeft(int timeIndex, int event) { + return riskSetLeft[event-1][timeIndex]; + } + + @Override + public int getRiskSetTotal(int timeIndex, int event) { + return riskSetTotal[event-1][timeIndex]; + } + + + @Override + public int getNumberOfEventsLeft(int timeIndex, int event) { + return numberOfEventsLeft[event][timeIndex]; + } + + @Override + public int getNumberOfEventsTotal(int timeIndex, int event) { + return numberOfEventsTotal[event][timeIndex]; + } + + @Override + public void update(CompetingRiskResponseWithCensorTime rowMovedToLeft) { + final double time = rowMovedToLeft.getU(); + final int k = Arrays.binarySearch(times, time); + final int delta_m_1 = rowMovedToLeft.getDelta() - 1; + final double censorTime = rowMovedToLeft.getC(); + + for(int j=0; j= t, in I(...) + for(int i=0; i<=k; i++){ + riskSetLeftJ[i]++; + } + + // second iteration; only if delta-1 != j + // corresponds to the second part, U_i < t & delta_i != j & C_i > t + if(delta_m_1 != j && !rowMovedToLeft.isCensored()){ + int i = k+1; + while(i < times.length && times[i] < censorTime){ + riskSetLeftJ[i]++; + i++; + } + } + } - return 0; + numberOfEventsLeft[rowMovedToLeft.getDelta()][k]++; } - - } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSets.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSets.java index 9a53d3e..d9a72b5 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSets.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSets.java @@ -1,13 +1,13 @@ package ca.joeltherrien.randomforest.responses.competingrisk; -import ca.joeltherrien.randomforest.utils.MathFunction; +public interface CompetingRiskSets { -import java.util.List; + double[] getDistinctTimes(); + int getRiskSetLeft(int timeIndex, int event); + int getRiskSetTotal(int timeIndex, int event); + int getNumberOfEventsLeft(int timeIndex, int event); + int getNumberOfEventsTotal(int timeIndex, int event); -public interface CompetingRiskSets { - - MathFunction getRiskSet(int event); - int getNumberOfEvents(Double time, int event); - List getEventTimes(); + void update(T rowMovedToLeft); } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSetsImpl.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSetsImpl.java index 44a9dd8..7fd8ba3 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSetsImpl.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskSetsImpl.java @@ -1,36 +1,59 @@ package ca.joeltherrien.randomforest.responses.competingrisk; -import ca.joeltherrien.randomforest.utils.MathFunction; -import lombok.Builder; -import lombok.Getter; +import java.util.Arrays; -import java.util.List; -import java.util.Map; +public class CompetingRiskSetsImpl implements CompetingRiskSets { -/** - * Represents a response from CompetingRiskUtils#calculateSetsEfficiently - * - */ -@Builder -@Getter -public class CompetingRiskSetsImpl implements CompetingRiskSets{ + final double[] times; // length m array + int[] riskSetLeft; // length m array + final int[] riskSetTotal; // length m array + int[][] numberOfEventsLeft; // J+1 x m array + final int[][] numberOfEventsTotal; // J+1 x m array - private final List eventTimes; - private final MathFunction riskSet; - private final Map numberOfEvents; - @Override - public MathFunction getRiskSet(int event){ - return riskSet; + public CompetingRiskSetsImpl(double[] times, int[] riskSetLeft, int[] riskSetTotal, int[][] numberOfEventsLeft, int[][] numberOfEventsTotal) { + this.times = times; + this.riskSetLeft = riskSetLeft; + this.riskSetTotal = riskSetTotal; + this.numberOfEventsLeft = numberOfEventsLeft; + this.numberOfEventsTotal = numberOfEventsTotal; } @Override - public int getNumberOfEvents(Double time, int event){ - if(numberOfEvents.containsKey(time)){ - return numberOfEvents.get(time)[event]; + public double[] getDistinctTimes() { + return times; + } + + @Override + public int getRiskSetLeft(int timeIndex, int event) { + return riskSetLeft[timeIndex]; + } + + @Override + public int getRiskSetTotal(int timeIndex, int event) { + return riskSetTotal[timeIndex]; + } + + + @Override + public int getNumberOfEventsLeft(int timeIndex, int event) { + return numberOfEventsLeft[event][timeIndex]; + } + + @Override + public int getNumberOfEventsTotal(int timeIndex, int event) { + return numberOfEventsTotal[event][timeIndex]; + } + + @Override + public void update(CompetingRiskResponse rowMovedToLeft) { + final double time = rowMovedToLeft.getU(); + final int k = Arrays.binarySearch(times, time); + + for(int i=0; i<=k; i++){ + riskSetLeft[i]++; } - return 0; + numberOfEventsLeft[rowMovedToLeft.getDelta()][k]++; } - } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskUtils.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskUtils.java index 3a612b1..94dc48e 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskUtils.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskUtils.java @@ -1,11 +1,9 @@ package ca.joeltherrien.randomforest.responses.competingrisk; -import ca.joeltherrien.randomforest.utils.LeftContinuousStepFunction; import ca.joeltherrien.randomforest.utils.StepFunction; -import ca.joeltherrien.randomforest.utils.VeryDiscontinuousStepFunction; import java.util.*; -import java.util.stream.DoubleStream; +import java.util.stream.Stream; public class CompetingRiskUtils { @@ -102,18 +100,30 @@ public class CompetingRiskUtils { } - public static CompetingRiskSetsImpl calculateSetsEfficiently(final List responses, int[] eventsOfFocus){ - final int n = responses.size(); - int[] numberOfCurrentEvents = new int[eventsOfFocus.length+1]; - final Map numberOfEvents = new HashMap<>(); + public static CompetingRiskSetsImpl calculateSetsEfficiently(final List initialLeftHand, + final List initialRightHand, + int[] eventsOfFocus, + boolean calculateRiskSets){ - final List eventTimes = new ArrayList<>(n); - final List eventAndCensorTimes = new ArrayList<>(n); - final List riskSetNumberList = new ArrayList<>(n); + final double[] distinctEventTimes = Stream.concat( + initialLeftHand.stream(), + initialRightHand.stream()) + //.filter(y -> !y.isCensored()) + .map(CompetingRiskResponse::getU) + .mapToDouble(Double::doubleValue) + .sorted() + .distinct() + .toArray(); + + + final int m = distinctEventTimes.length; + final int[][] numberOfCurrentEventsTotal = new int[eventsOfFocus.length+1][m]; + + // Left Hand First // need to first sort responses - Collections.sort(responses, (y1, y2) -> { + Collections.sort(initialLeftHand, (y1, y2) -> { if(y1.getU() < y2.getU()){ return -1; } @@ -125,127 +135,191 @@ public class CompetingRiskUtils { } }); + final int nLeft = initialLeftHand.size(); + final int nRight = initialRightHand.size(); + + final int[][] numberOfCurrentEventsLeft = new int[eventsOfFocus.length+1][m]; + final int[] riskSetArrayLeft = new int[m]; + final int[] riskSetArrayTotal = new int[m]; - for(int i=0; i currentResponse.getU(); - numberOfCurrentEvents[currentResponse.getDelta()]++; + for(int k=0; k currentResponse.getU(); + + final int k = Arrays.binarySearch(distinctEventTimes, currentResponse.getU()); + + numberOfCurrentEventsLeft[currentResponse.getDelta()][k]++; + numberOfCurrentEventsTotal[currentResponse.getDelta()][k]++; if(lastOfTime){ int totalNumberOfCurrentEvents = 0; - for(int e = 1; e < numberOfCurrentEvents.length; e++){ // exclude censored events - totalNumberOfCurrentEvents += numberOfCurrentEvents[e]; + for(int e = 1; e < eventsOfFocus.length+1; e++){ // exclude censored events + totalNumberOfCurrentEvents += numberOfCurrentEventsLeft[e][k]; } - final double currentTime = currentResponse.getU(); + // Calculate risk set values + // Note that we only decrease values in the *future* + if(calculateRiskSets){ + final int decreaseBy = totalNumberOfCurrentEvents + numberOfCurrentEventsLeft[0][k]; + for(int j=k+1; j 0){ // add numberOfCurrentEvents - // Add point - eventTimes.add(currentTime); - numberOfEvents.put(currentTime, numberOfCurrentEvents); + } } - // Always do risk set - // remember that the LeftContinuousFunction takes into account that at this currentTime the risk value is the previous value - final int riskSet = n - (i+1); - riskSetNumberList.add(riskSet); - eventAndCensorTimes.add(currentTime); - - // reset counters - numberOfCurrentEvents = new int[eventsOfFocus.length+1]; } } - final double[] riskSetArray = new double[eventAndCensorTimes.size()]; - final double[] timesArray = new double[eventAndCensorTimes.size()]; - for(int i=0; i { + if(y1.getU() < y2.getU()){ + return -1; + } + else if(y1.getU() > y2.getU()){ + return 1; + } + else{ + return 0; + } + }); + + // Right Hand + int[] currentEventsRight = new int[eventsOfFocus.length+1]; + for(int i=0; i currentResponse.getU(); + + final int k = Arrays.binarySearch(distinctEventTimes, currentResponse.getU()); + + currentEventsRight[currentResponse.getDelta()]++; + numberOfCurrentEventsTotal[currentResponse.getDelta()][k]++; + + if(lastOfTime){ + int totalNumberOfCurrentEvents = 0; + for(int e = 1; e < eventsOfFocus.length+1; e++){ // exclude censored events + totalNumberOfCurrentEvents += currentEventsRight[e]; + } + + // Calculate risk set values + // Note that we only decrease values in the *future* + if(calculateRiskSets){ + final int decreaseBy = totalNumberOfCurrentEvents + currentEventsRight[0]; + for(int j=k+1; j responses, int[] eventsOfFocus){ - final List sillyList = responses; // annoying Java generic work-around - final CompetingRiskSetsImpl originalSets = calculateSetsEfficiently(sillyList, eventsOfFocus); - final double[] allTimes = DoubleStream.concat( - responses.stream() - .mapToDouble(CompetingRiskResponseWithCensorTime::getC), - responses.stream() - .mapToDouble(CompetingRiskResponseWithCensorTime::getU) - ).sorted().distinct().toArray(); + public static CompetingRiskGraySetsImpl calculateGraySetsEfficiently(final List initialLeftHand, + final List initialRightHand, + int[] eventsOfFocus){ + final List leftHandGenericsSuck = initialLeftHand; + final List rightHandGenericsSuck = initialRightHand; + final CompetingRiskSetsImpl normalSets = calculateSetsEfficiently( + leftHandGenericsSuck, + rightHandGenericsSuck, + eventsOfFocus, false); - final VeryDiscontinuousStepFunction[] riskSets = new VeryDiscontinuousStepFunction[eventsOfFocus.length]; + final double[] times = normalSets.times; + final int[][] numberOfEventsLeft = normalSets.numberOfEventsLeft; + final int[][] numberOfEventsTotal = normalSets.numberOfEventsTotal; - for(final int event : eventsOfFocus){ - final double[] yAt = new double[allTimes.length]; - final double[] yRight = new double[allTimes.length]; + // FYI; initialLeftHand and initialRightHand have both now been sorted + // Time to calculate the Gray modified risk sets + final int[][] riskSetsLeft = new int[eventsOfFocus.length][times.length]; + final int[][] riskSetsTotal = new int[eventsOfFocus.length][times.length]; - for(final CompetingRiskResponseWithCensorTime response : responses){ - if(response.getDelta() == event){ - // traditional case only; increment on time t when I(t <= Ui) - final double time = response.getU(); - final int index = Arrays.binarySearch(allTimes, time); + // Left hand first + for(final CompetingRiskResponseWithCensorTime response : initialLeftHand){ + final double time = response.getU(); + final int k = Arrays.binarySearch(times, time); + final int delta_m_1 = response.getDelta() - 1; + final double censorTime = response.getC(); - if(index < 0){ // TODO remove once code is stable - throw new IllegalStateException("Index shouldn't be negative!"); - } + for(int j=0; j= t, in I(...) + for(int i=0; i<=k; i++){ + riskSetLeftJ[i]++; + riskSetTotalJ[i]++; + } + + // second iteration; only if delta-1 != j + // corresponds to the second part, U_i < t & delta_i != j & C_i > t + if(delta_m_1 != j && !response.isCensored()){ + int i = k+1; + while(i < times.length && times[i] < censorTime){ + riskSetLeftJ[i]++; + riskSetTotalJ[i]++; + i++; } } - else{ - // need to increment on time t on following conditions; I(t <= Ui | t < Ci) - // Fact: Ci >= Ui. - // increment yAt up to Ci. If Ui==Ci, increment yAt at Ci. - final double time = response.getC(); - final int index = Arrays.binarySearch(allTimes, time); - - if(index < 0){ // TODO remove once code is stable - throw new IllegalStateException("Index shouldn't be negative!"); - } - - for(int i=0; i= t, in I(...) + for(int i=0; i<=k; i++){ + riskSetTotalJ[i]++; + } + + // second iteration; only if delta-1 != j + // corresponds to the second part, U_i < t & delta_i != j & C_i > t + if(delta_m_1 != j && !response.isCensored()){ + int i = k+1; + while(i < times.length && times[i] < censorTime){ + riskSetTotalJ[i]++; + i++; + } + } + + } + + } + + return new CompetingRiskGraySetsImpl(times, riskSetsLeft, riskSetsTotal, numberOfEventsLeft, numberOfEventsTotal); } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java index f6efdeb..703ebfc 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java @@ -1,60 +1,132 @@ package ca.joeltherrien.randomforest.responses.competingrisk.differentiator; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.covariates.Covariate; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets; import ca.joeltherrien.randomforest.tree.GroupDifferentiator; +import ca.joeltherrien.randomforest.tree.Split; +import ca.joeltherrien.randomforest.tree.SplitAndScore; import lombok.AllArgsConstructor; import lombok.Data; +import java.util.Iterator; import java.util.List; -import java.util.stream.Stream; +import java.util.stream.Collectors; /** * See page 761 of Random survival forests for competing risks by Ishwaran et al. The class is abstract as Gray's test * modifies the abstract method. * */ -public abstract class CompetingRiskGroupDifferentiator implements GroupDifferentiator{ +public abstract class CompetingRiskGroupDifferentiator implements GroupDifferentiator { + + abstract protected CompetingRiskSets createCompetingRiskSets(List leftHand, List rightHand); + + abstract protected Double getScore(final CompetingRiskSets competingRiskSets); @Override - public abstract Double differentiate(List leftHand, List rightHand); + public SplitAndScore differentiate(Iterator> splitIterator) { + if(splitIterator instanceof Covariate.SplitRuleUpdater){ + return differentiateWithSplitUpdater((Covariate.SplitRuleUpdater) splitIterator); + } + else{ + return differentiateWithBasicIterator(splitIterator); + } + } + + private SplitAndScore differentiateWithBasicIterator(Iterator> splitIterator){ + Double bestScore = null; + Split bestSplit = null; + + while(splitIterator.hasNext()){ + final Split candidateSplit = splitIterator.next(); + + final List leftHand = candidateSplit.getLeftHand().stream().map(Row::getResponse).collect(Collectors.toList()); + final List rightHand = candidateSplit.getRightHand().stream().map(Row::getResponse).collect(Collectors.toList()); + + if(leftHand.isEmpty() || rightHand.isEmpty()){ + continue; + } + + final CompetingRiskSets competingRiskSets = createCompetingRiskSets(leftHand, rightHand); + + final Double score = getScore(competingRiskSets); + + if(Double.isFinite(score) && (bestScore == null || score > bestScore)){ + bestScore = score; + bestSplit = candidateSplit; + } + } + + if(bestSplit == null){ + return null; + } + + return new SplitAndScore<>(bestSplit, bestScore); + } + + private SplitAndScore differentiateWithSplitUpdater(Covariate.SplitRuleUpdater splitRuleUpdater) { + + final List leftInitialSplit = splitRuleUpdater.currentSplit().getLeftHand() + .stream().map(Row::getResponse).collect(Collectors.toList()); + final List rightInitialSplit = splitRuleUpdater.currentSplit().getRightHand() + .stream().map(Row::getResponse).collect(Collectors.toList()); + + final CompetingRiskSets competingRiskSets = createCompetingRiskSets(leftInitialSplit, rightInitialSplit); + + Double bestScore = null; + Split bestSplit = null; + + while(splitRuleUpdater.hasNext()){ + for(Row rowMoved : splitRuleUpdater.nextUpdate().rowsMovedToLeftHand()){ + competingRiskSets.update(rowMoved.getResponse()); + } + + final Double score = getScore(competingRiskSets); + + if(Double.isFinite(score) && (bestScore == null || score > bestScore)){ + bestScore = score; + bestSplit = splitRuleUpdater.currentSplit(); + } + } + + if(bestSplit == null){ + return null; + } + + return new SplitAndScore<>(bestSplit, bestScore); + + } /** * Calculates the log rank value (or the Gray's test value) for a *specific* event cause. * * @param eventOfFocus - * @param competingRiskSetsLeft A summary of the different sets used in the calculation for the left side - * @param competingRiskSetsRight A summary of the different sets used in the calculation for the right side + * @param competingRiskSets A summary of the different sets used in the calculation * @return */ - LogRankValue specificLogRankValue(final int eventOfFocus, final CompetingRiskSets competingRiskSetsLeft, final CompetingRiskSets competingRiskSetsRight){ - - final double[] distinctEventTimes = Stream.concat( - competingRiskSetsLeft.getEventTimes().stream(), - competingRiskSetsRight.getEventTimes().stream()) - .mapToDouble(Double::doubleValue) - .sorted() - .distinct() - .toArray(); + LogRankValue specificLogRankValue(final int eventOfFocus, final CompetingRiskSets competingRiskSets){ double summation = 0.0; double variance = 0.0; - for(final double time_k : distinctEventTimes){ + final double[] distinctTimes = competingRiskSets.getDistinctTimes(); + + for(int k = 0; k leftHand, List rightHand) { - if(leftHand.size() == 0 || rightHand.size() == 0){ - return null; - } - - final CompetingRiskGraySetsImpl competingRiskSetsLeft = CompetingRiskUtils.calculateGraySetsEfficiently(leftHand, events); - final CompetingRiskGraySetsImpl competingRiskSetsRight = CompetingRiskUtils.calculateGraySetsEfficiently(rightHand, events); + protected CompetingRiskSets createCompetingRiskSets(List leftHand, List rightHand){ + return CompetingRiskUtils.calculateGraySetsEfficiently(leftHand, rightHand, events); + } + @Override + protected Double getScore(final CompetingRiskSets competingRiskSets){ double numerator = 0.0; double denominatorSquared = 0.0; for(final int eventOfFocus : events){ - final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSetsLeft, competingRiskSetsRight); + final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSets); numerator += valueOfInterest.getNumerator()*valueOfInterest.getVarianceSqrt(); denominatorSquared += valueOfInterest.getVariance(); @@ -37,7 +35,6 @@ public class GrayLogRankMultipleGroupDifferentiator extends CompetingRiskGroupDi } return Math.abs(numerator / Math.sqrt(denominatorSquared)); - } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankSingleGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankSingleGroupDifferentiator.java index 48e3b6f..afe66db 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankSingleGroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankSingleGroupDifferentiator.java @@ -1,7 +1,7 @@ package ca.joeltherrien.randomforest.responses.competingrisk.differentiator; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskGraySetsImpl; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponseWithCensorTime; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskUtils; import lombok.RequiredArgsConstructor; @@ -18,18 +18,14 @@ public class GrayLogRankSingleGroupDifferentiator extends CompetingRiskGroupDiff private final int[] events; @Override - public Double differentiate(List leftHand, List rightHand) { - if(leftHand.size() == 0 || rightHand.size() == 0){ - return null; - } - - final CompetingRiskGraySetsImpl competingRiskSetsLeft = CompetingRiskUtils.calculateGraySetsEfficiently(leftHand, events); - final CompetingRiskGraySetsImpl competingRiskSetsRight = CompetingRiskUtils.calculateGraySetsEfficiently(rightHand, events); - - final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSetsLeft, competingRiskSetsRight); + protected CompetingRiskSets createCompetingRiskSets(List leftHand, List rightHand){ + return CompetingRiskUtils.calculateGraySetsEfficiently(leftHand, rightHand, events); + } + @Override + protected Double getScore(final CompetingRiskSets competingRiskSets){ + final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSets); return Math.abs(valueOfInterest.getNumerator() / valueOfInterest.getVarianceSqrt()); - } } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankMultipleGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankMultipleGroupDifferentiator.java index 2ad2424..6465b44 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankMultipleGroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankMultipleGroupDifferentiator.java @@ -1,7 +1,7 @@ package ca.joeltherrien.randomforest.responses.competingrisk.differentiator; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSetsImpl; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskUtils; import lombok.RequiredArgsConstructor; @@ -17,19 +17,17 @@ public class LogRankMultipleGroupDifferentiator extends CompetingRiskGroupDiffer private final int[] events; @Override - public Double differentiate(List leftHand, List rightHand) { - if(leftHand.size() == 0 || rightHand.size() == 0){ - return null; - } - - final CompetingRiskSetsImpl competingRiskSetsLeft = CompetingRiskUtils.calculateSetsEfficiently(leftHand, events); - final CompetingRiskSetsImpl competingRiskSetsRight = CompetingRiskUtils.calculateSetsEfficiently(rightHand, events); + protected CompetingRiskSets createCompetingRiskSets(List leftHand, List rightHand){ + return CompetingRiskUtils.calculateSetsEfficiently(leftHand, rightHand, events, true); + } + @Override + protected Double getScore(final CompetingRiskSets competingRiskSets){ double numerator = 0.0; double denominatorSquared = 0.0; for(final int eventOfFocus : events){ - final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSetsLeft, competingRiskSetsRight); + final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSets); numerator += valueOfInterest.getNumerator()*valueOfInterest.getVarianceSqrt(); denominatorSquared += valueOfInterest.getVariance(); @@ -37,7 +35,7 @@ public class LogRankMultipleGroupDifferentiator extends CompetingRiskGroupDiffer } return Math.abs(numerator / Math.sqrt(denominatorSquared)); - } + } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankSingleGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankSingleGroupDifferentiator.java index 107964e..7c633b1 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankSingleGroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankSingleGroupDifferentiator.java @@ -1,7 +1,7 @@ package ca.joeltherrien.randomforest.responses.competingrisk.differentiator; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSetsImpl; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskUtils; import lombok.RequiredArgsConstructor; @@ -18,18 +18,14 @@ public class LogRankSingleGroupDifferentiator extends CompetingRiskGroupDifferen private final int[] events; @Override - public Double differentiate(List leftHand, List rightHand) { - if(leftHand.size() == 0 || rightHand.size() == 0){ - return null; - } - - final CompetingRiskSetsImpl competingRiskSetsLeft = CompetingRiskUtils.calculateSetsEfficiently(leftHand, events); - final CompetingRiskSetsImpl competingRiskSetsRight = CompetingRiskUtils.calculateSetsEfficiently(rightHand, events); - - final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSetsLeft, competingRiskSetsRight); + protected CompetingRiskSets createCompetingRiskSets(List leftHand, List rightHand){ + return CompetingRiskUtils.calculateSetsEfficiently(leftHand, rightHand, events, true); + } + @Override + protected Double getScore(final CompetingRiskSets competingRiskSets){ + final LogRankValue valueOfInterest = specificLogRankValue(eventOfFocus, competingRiskSets); return Math.abs(valueOfInterest.getNumerator() / valueOfInterest.getVarianceSqrt()); - } } diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/regression/MeanGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/regression/MeanGroupDifferentiator.java deleted file mode 100644 index 75bc129..0000000 --- a/src/main/java/ca/joeltherrien/randomforest/responses/regression/MeanGroupDifferentiator.java +++ /dev/null @@ -1,26 +0,0 @@ -package ca.joeltherrien.randomforest.responses.regression; - -import ca.joeltherrien.randomforest.tree.GroupDifferentiator; - -import java.util.List; - -public class MeanGroupDifferentiator implements GroupDifferentiator { - - @Override - public Double differentiate(List leftHand, List rightHand) { - - double leftHandSize = leftHand.size(); - double rightHandSize = rightHand.size(); - - if(leftHandSize == 0 || rightHandSize == 0){ - return null; - } - - double leftHandMean = leftHand.stream().mapToDouble(db -> db/leftHandSize).sum(); - double rightHandMean = rightHand.stream().mapToDouble(db -> db/rightHandSize).sum(); - - return Math.abs(leftHandMean - rightHandMean); - - } - -} diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java index 25f7e6e..9ae4673 100644 --- a/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java @@ -1,13 +1,13 @@ package ca.joeltherrien.randomforest.responses.regression; -import ca.joeltherrien.randomforest.tree.GroupDifferentiator; +import ca.joeltherrien.randomforest.tree.SimpleGroupDifferentiator; import java.util.List; -public class WeightedVarianceGroupDifferentiator implements GroupDifferentiator { +public class WeightedVarianceGroupDifferentiator extends SimpleGroupDifferentiator { @Override - public Double differentiate(List leftHand, List rightHand) { + public Double getScore(List leftHand, List rightHand) { final double leftHandSize = leftHand.size(); final double rightHandSize = rightHand.size(); diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java b/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java index 37ee4ce..b6330cc 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java @@ -14,8 +14,10 @@ import java.io.IOException; import java.io.ObjectOutputStream; import java.util.ArrayList; import java.util.List; +import java.util.Random; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; +import java.util.concurrent.ThreadLocalRandom; import java.util.concurrent.atomic.AtomicInteger; import java.util.stream.Collectors; import java.util.stream.Stream; @@ -45,17 +47,17 @@ public class ForestTrainer { this.covariates = covariates; this.treeResponseCombiner = settings.getTreeCombiner(); this.treeTrainer = new TreeTrainer<>(settings, covariates); - } public Forest trainSerial(){ final List> trees = new ArrayList<>(ntree); final Bootstrapper> bootstrapper = new Bootstrapper<>(data); + final Random random = new Random(); for(int j=0; j { } - final File[] treeFiles = folder.listFiles(((file, s) -> s.endsWith(".tree"))); + final File[] treeFiles = folder.listFiles((file, s) -> s.endsWith(".tree")); final ExecutorService executorService = Executors.newFixedThreadPool(threads); final AtomicInteger treeCount = new AtomicInteger(treeFiles.length); // tracks how many trees are finished @@ -162,9 +164,9 @@ public class ForestTrainer { } - private Tree trainTree(final Bootstrapper> bootstrapper){ - final List> bootstrappedData = bootstrapper.bootstrap(); - return treeTrainer.growTree(bootstrappedData); + private Tree trainTree(final Bootstrapper> bootstrapper, Random random){ + final List> bootstrappedData = bootstrapper.bootstrap(random); + return treeTrainer.growTree(bootstrappedData, random); } public void saveTree(final Tree tree, String name) throws IOException { @@ -193,7 +195,8 @@ public class ForestTrainer { @Override public void run() { - final Tree tree = trainTree(bootstrapper); + // ThreadLocalRandom should make sure we don't duplicate seeds + final Tree tree = trainTree(bootstrapper, ThreadLocalRandom.current()); // should be okay as the list structure isn't changing treeList.set(treeIndex, tree); @@ -216,7 +219,8 @@ public class ForestTrainer { @Override public void run() { - final Tree tree = trainTree(bootstrapper); + // ThreadLocalRandom should make sure we don't duplicate seeds + final Tree tree = trainTree(bootstrapper, ThreadLocalRandom.current()); try { saveTree(tree, filename); diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java index cbd1247..66e8cbc 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java @@ -1,15 +1,17 @@ package ca.joeltherrien.randomforest.tree; -import java.util.List; +import java.util.Iterator; /** * When choosing an optimal node to split on, we choose the split that maximizes the difference between the two groups. - * The GroupDifferentiator has one method that outputs a score to show how different groups are. The larger the score, - * the greater the difference. + * The GroupDifferentiator has one method that cycles through an iterator of Splits (FYI; check if the iterator is an + * instance of Covariate.SplitRuleUpdater; in which case you get access to the rows that change between splits) * + * If you want to implement a very trivial GroupDifferentiator that just takes two Lists as arguments, try extending + * SimpleGroupDifferentiator. */ public interface GroupDifferentiator { - Double differentiate(List leftHand, List rightHand); + SplitAndScore differentiate(Iterator> splitIterator); } diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java new file mode 100644 index 0000000..596f81e --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java @@ -0,0 +1,50 @@ +package ca.joeltherrien.randomforest.tree; + +import ca.joeltherrien.randomforest.Row; + +import java.util.Iterator; +import java.util.List; +import java.util.stream.Collectors; + +public abstract class SimpleGroupDifferentiator implements GroupDifferentiator { + + @Override + public SplitAndScore differentiate(Iterator> splitIterator) { + Double bestScore = null; + Split bestSplit = null; + + while(splitIterator.hasNext()){ + final Split candidateSplit = splitIterator.next(); + + final List leftHand = candidateSplit.getLeftHand().stream().map(Row::getResponse).collect(Collectors.toList()); + final List rightHand = candidateSplit.getRightHand().stream().map(Row::getResponse).collect(Collectors.toList()); + + if(leftHand.isEmpty() || rightHand.isEmpty()){ + continue; + } + + final Double score = getScore(leftHand, rightHand); + + if(score != null && (bestScore == null || score > bestScore)){ + bestScore = score; + bestSplit = candidateSplit; + } + } + + if(bestSplit == null){ + return null; + } + + return new SplitAndScore<>(bestSplit, bestScore); + } + + /** + * Return a score; higher is better. + * + * @param leftHand + * @param rightHand + * @return + */ + public abstract Double getScore(List leftHand, List rightHand); + +} diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/Split.java b/src/main/java/ca/joeltherrien/randomforest/tree/Split.java index e566e64..b55444c 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/Split.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/Split.java @@ -1,19 +1,21 @@ package ca.joeltherrien.randomforest.tree; import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.covariates.Covariate; import lombok.Data; import java.util.List; /** - * Very simple class that contains three lists; it's essentially a thruple. + * Very simple class that contains three lists and a SplitRule. * * @author joel * */ @Data -public class Split { +public final class Split { + public final Covariate.SplitRule splitRule; public final List> leftHand; public final List> rightHand; public final List> naHand; diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/SplitAndScore.java b/src/main/java/ca/joeltherrien/randomforest/tree/SplitAndScore.java new file mode 100644 index 0000000..1160680 --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/tree/SplitAndScore.java @@ -0,0 +1,15 @@ +package ca.joeltherrien.randomforest.tree; + +import lombok.AllArgsConstructor; +import lombok.Getter; + +@AllArgsConstructor +public class SplitAndScore { + + @Getter + private final Split split; + + @Getter + private final Double score; + +} diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/SplitNode.java b/src/main/java/ca/joeltherrien/randomforest/tree/SplitNode.java index 8837170..d43e273 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/SplitNode.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/SplitNode.java @@ -3,8 +3,10 @@ package ca.joeltherrien.randomforest.tree; import ca.joeltherrien.randomforest.CovariateRow; import ca.joeltherrien.randomforest.covariates.Covariate; import lombok.Builder; +import lombok.ToString; @Builder +@ToString public class SplitNode implements Node { private final Node leftHand; diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/TerminalNode.java b/src/main/java/ca/joeltherrien/randomforest/tree/TerminalNode.java index 917c10d..cc96d03 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/TerminalNode.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/TerminalNode.java @@ -2,8 +2,10 @@ package ca.joeltherrien.randomforest.tree; import ca.joeltherrien.randomforest.CovariateRow; import lombok.RequiredArgsConstructor; +import lombok.ToString; @RequiredArgsConstructor +@ToString public class TerminalNode implements Node { private final Y responseValue; @@ -14,6 +16,4 @@ public class TerminalNode implements Node { } - - } diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java b/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java index 12d3d03..de29e80 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java @@ -29,4 +29,8 @@ public class Tree implements Node { return Arrays.binarySearch(this.bootstrapRowIds, id) >= 0; } + @Override + public String toString(){ + return rootNode.toString(); + } } diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java index 0e359b4..d1d141d 100644 --- a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java +++ b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java @@ -8,7 +8,6 @@ import lombok.AllArgsConstructor; import lombok.Builder; import java.util.*; -import java.util.concurrent.ThreadLocalRandom; import java.util.stream.Collectors; @Builder @@ -47,20 +46,21 @@ public class TreeTrainer { this.covariates = covariates; } - public Tree growTree(List> data){ + public Tree growTree(List> data, Random random){ - final Node rootNode = growNode(data, 0); + final Node rootNode = growNode(data, 0, random); return new Tree<>(rootNode, data.stream().mapToInt(Row::getId).toArray()); } - private Node growNode(List> data, int depth){ + private Node growNode(List> data, int depth, Random random){ // See https://kogalur.github.io/randomForestSRC/theory.html#section3.1 (near bottom) if(data.size() >= 2*nodeSize && depth < maxNodeDepth && !nodeIsPure(data)){ - final List covariatesToTry = selectCovariates(this.mtry); - final SplitRuleAndSplit bestSplitRuleAndSplit = findBestSplitRule(data, covariatesToTry); + final List covariatesToTry = selectCovariates(this.mtry, random); + final Split bestSplit = findBestSplitRule(data, covariatesToTry, random); - if(bestSplitRuleAndSplit.splitRule == null){ + + if(bestSplit == null){ return new TerminalNode<>( responseCombiner.combine( @@ -71,14 +71,34 @@ public class TreeTrainer { } - final Split split = bestSplitRuleAndSplit.split; - // Note that NAs have already been handled + + // Now that we have the best split; we need to handle any NAs that were dropped off + final double probabilityLeftHand = (double) bestSplit.leftHand.size() / + (double) (bestSplit.leftHand.size() + bestSplit.rightHand.size()); + + // Assign missing values to the split if necessary + if(bestSplit.getSplitRule().getParent().hasNAs()){ + for(Row row : data) { + if(row.getCovariateValue(bestSplit.getSplitRule().getParent()).isNA()) { + final boolean randomDecision = random.nextDouble() <= probabilityLeftHand; + + if(randomDecision){ + bestSplit.getLeftHand().add(row); + } + else{ + bestSplit.getRightHand().add(row); + } + + } + } + } - final Node leftNode = growNode(split.leftHand, depth+1); - final Node rightNode = growNode(split.rightHand, depth+1); - return new SplitNode<>(leftNode, rightNode, bestSplitRuleAndSplit.splitRule, bestSplitRuleAndSplit.probabilityLeftHand); + final Node leftNode = growNode(bestSplit.leftHand, depth+1, random); + final Node rightNode = growNode(bestSplit.rightHand, depth+1, random); + + return new SplitNode<>(leftNode, rightNode, bestSplit.getSplitRule(), probabilityLeftHand); } else{ @@ -92,13 +112,13 @@ public class TreeTrainer { } - private List selectCovariates(int mtry){ + private List selectCovariates(int mtry, Random random){ if(mtry >= covariates.size()){ return covariates; } final List splitCovariates = new ArrayList<>(covariates); - Collections.shuffle(splitCovariates, ThreadLocalRandom.current()); + Collections.shuffle(splitCovariates, random); if (splitCovariates.size() > mtry) { splitCovariates.subList(mtry, splitCovariates.size()).clear(); @@ -107,63 +127,28 @@ public class TreeTrainer { return splitCovariates; } - private SplitRuleAndSplit findBestSplitRule(List> data, List covariatesToTry){ - SplitRuleAndSplit bestSplitRuleAndSplit = new SplitRuleAndSplit(); - double bestSplitScore = 0.0; - boolean first = true; + private Split findBestSplitRule(List> data, List covariatesToTry, Random random){ - for(final Covariate covariate : covariatesToTry){ + SplitAndScore bestSplitAndScore = null; + final GroupDifferentiator noGenericDifferentiator = groupDifferentiator; // cause Java generics suck - final int numberToTry = numberOfSplits==0 ? data.size() : numberOfSplits; + for(final Covariate covariate : covariatesToTry) { + final Iterator iterator = covariate.generateSplitRuleUpdater(data, this.numberOfSplits, random); - final Collection splitRulesToTry = covariate - .generateSplitRules( - data - .stream() - .map(row -> row.getCovariateValue(covariate)) - .collect(Collectors.toList()) - , numberToTry); + final SplitAndScore candidateSplitAndScore = noGenericDifferentiator.differentiate(iterator); - for(final Covariate.SplitRule possibleRule : splitRulesToTry){ - final Split possibleSplit = possibleRule.applyRule(data); - - // We have to handle any NAs - if(possibleSplit.leftHand.size() == 0 && possibleSplit.rightHand.size() == 0 && possibleSplit.naHand.size() > 0){ - throw new IllegalArgumentException("Can't apply " + this + " when there are rows with missing data and no non-missing value rows"); - } - - final double probabilityLeftHand = (double) possibleSplit.leftHand.size() / (double) (possibleSplit.leftHand.size() + possibleSplit.rightHand.size()); - - final Random random = ThreadLocalRandom.current(); - for(final Row missingValueRow : possibleSplit.naHand){ - final boolean randomDecision = random.nextDouble() <= probabilityLeftHand; - if(randomDecision){ - possibleSplit.leftHand.add(missingValueRow); - } - else{ - possibleSplit.rightHand.add(missingValueRow); - } - } - - final Double score = groupDifferentiator.differentiate( - possibleSplit.leftHand.stream().map(row -> row.getResponse()).collect(Collectors.toList()), - possibleSplit.rightHand.stream().map(row -> row.getResponse()).collect(Collectors.toList()) - ); - - - if(score != null && !Double.isNaN(score) && (score > bestSplitScore || first)){ - bestSplitRuleAndSplit.splitRule = possibleRule; - bestSplitRuleAndSplit.split = possibleSplit; - bestSplitRuleAndSplit.probabilityLeftHand = probabilityLeftHand; - - bestSplitScore = score; - first = false; - } + if(candidateSplitAndScore != null && (bestSplitAndScore == null || + candidateSplitAndScore.getScore() > bestSplitAndScore.getScore())) { + bestSplitAndScore = candidateSplitAndScore; } } - return bestSplitRuleAndSplit; + if(bestSplitAndScore == null){ + return null; + } + + return bestSplitAndScore.getSplit(); } @@ -186,10 +171,4 @@ public class TreeTrainer { return true; } - private class SplitRuleAndSplit{ - private Covariate.SplitRule splitRule = null; - private Split split = null; - private double probabilityLeftHand; - } - } diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/IndexedIterator.java b/src/main/java/ca/joeltherrien/randomforest/utils/IndexedIterator.java new file mode 100644 index 0000000..d82e0ec --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/utils/IndexedIterator.java @@ -0,0 +1,9 @@ +package ca.joeltherrien.randomforest.utils; + +import java.util.Iterator; + +public interface IndexedIterator extends Iterator { + + int getIndex(); + +} diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/SingletonIterator.java b/src/main/java/ca/joeltherrien/randomforest/utils/SingletonIterator.java new file mode 100644 index 0000000..ca6df8b --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/utils/SingletonIterator.java @@ -0,0 +1,29 @@ +package ca.joeltherrien.randomforest.utils; + +import lombok.RequiredArgsConstructor; + +import java.util.Iterator; + +@RequiredArgsConstructor +public class SingletonIterator implements Iterator { + + private final E value; + + private boolean beenCalled = false; + + + @Override + public boolean hasNext() { + return !beenCalled; + } + + @Override + public E next() { + if(!beenCalled){ + beenCalled = true; + return value; + } + + return null; + } +} diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/UniqueSubsetValueIterator.java b/src/main/java/ca/joeltherrien/randomforest/utils/UniqueSubsetValueIterator.java new file mode 100644 index 0000000..0b7b481 --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/utils/UniqueSubsetValueIterator.java @@ -0,0 +1,61 @@ +package ca.joeltherrien.randomforest.utils; + + +/** + * Iterator that wraps around a UniqueValueIterator. It continues to iterate until it gets to one of the prespecified indexes, + * and then proceeds just past that to the end of the existing values it's at. + * + * The wrapped iterator must be from a sorted collection of some sort such that equal values are clumped together. + * I.e. "b b c c c d d a a" is okay but "a b b c c a" is not as 'a' appears twice at different locations + * + * @param + */ +public class UniqueSubsetValueIterator implements IndexedIterator { + + private final UniqueValueIterator iterator; + private final Integer[] indexValues; + + private int currentIndexSpot = 0; + + public UniqueSubsetValueIterator(final UniqueValueIterator iterator, final Integer[] indexValues){ + this.iterator = iterator; + this.indexValues = indexValues; + } + + @Override + public boolean hasNext() { + return iterator.hasNext() && iterator.getIndex() <= indexValues[indexValues.length-1]; + } + + @Override + public E next() { + if(hasNext()){ + final int indexToStopBy = indexValues[currentIndexSpot]; + + while(iterator.getIndex() <= indexToStopBy){ + iterator.next(); + } + + for(int i = currentIndexSpot + 1; i < indexValues.length; i++){ + if(iterator.getIndex() <= indexValues[i]){ + currentIndexSpot = i; + break; + } + } + + + return iterator.getCurrentValue(); + + } + + return null; + + } + + @Override + public int getIndex(){ + return iterator.getIndex(); + } + + +} diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/UniqueValueIterator.java b/src/main/java/ca/joeltherrien/randomforest/utils/UniqueValueIterator.java new file mode 100644 index 0000000..b585152 --- /dev/null +++ b/src/main/java/ca/joeltherrien/randomforest/utils/UniqueValueIterator.java @@ -0,0 +1,71 @@ +package ca.joeltherrien.randomforest.utils; + + +import lombok.Getter; + +import java.util.Iterator; + +/** + * Iterator that wraps around another iterator. It continues to iterate until it gets to the *end* of a sequence of identical values. + * It also tracks the current index in the original iterator. + * + * The wrapped iterator must be from a sorted collection of some sort such that equal values are clumped together. + * I.e. "b b c c c d d a a" is okay but "a b b c c a" is not as 'a' appears twice at different locations + * + * @param + */ +public class UniqueValueIterator implements IndexedIterator { + + private final Iterator wrappedIterator; + + @Getter private E currentValue = null; + @Getter private E nextValue; + + public UniqueValueIterator(final Iterator wrappedIterator){ + this.wrappedIterator = wrappedIterator; + this.nextValue = wrappedIterator.next(); + } + + // Count must return the index of the last value of the sequence returned by next() + @Getter + private int index = 0; + + @Override + public boolean hasNext() { + return nextValue != null; + } + + @Override + public E next() { + + int count = 1; + while(wrappedIterator.hasNext()){ + final E currentIteratorValue = wrappedIterator.next(); + + if(currentIteratorValue.equals(nextValue)){ + count++; + } + else{ + index +=count; + currentValue = nextValue; + nextValue = currentIteratorValue; + + return currentValue; + } + + } + + if(nextValue != null){ + index += count; + currentValue = nextValue; + nextValue = null; + + return currentValue; + } + else{ + return null; + } + + + } +} diff --git a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java index 7e59727..c3849c8 100644 --- a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java +++ b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java @@ -1,8 +1,8 @@ package ca.joeltherrien.randomforest; -import ca.joeltherrien.randomforest.covariates.BooleanCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings; import ca.joeltherrien.randomforest.covariates.Covariate; -import ca.joeltherrien.randomforest.covariates.NumericCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskFunctionCombiner; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctions; import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCalculatingCompetingRiskSets.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCalculatingCompetingRiskSets.java deleted file mode 100644 index e6fec68..0000000 --- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCalculatingCompetingRiskSets.java +++ /dev/null @@ -1,214 +0,0 @@ -package ca.joeltherrien.randomforest.competingrisk; - -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskGraySetsImpl; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponseWithCensorTime; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSetsImpl; -import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskUtils; -import org.junit.jupiter.api.Test; - -import java.util.ArrayList; -import java.util.List; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -public class TestCalculatingCompetingRiskSets { - - public List generateData(){ - final List data = new ArrayList<>(); - - data.add(new CompetingRiskResponseWithCensorTime(1, 1, 3)); - data.add(new CompetingRiskResponseWithCensorTime(1, 1, 3)); - data.add(new CompetingRiskResponseWithCensorTime(0, 1, 1)); - data.add(new CompetingRiskResponseWithCensorTime(1, 2, 2.5)); - data.add(new CompetingRiskResponseWithCensorTime(2, 3, 4)); - data.add(new CompetingRiskResponseWithCensorTime(0, 3, 3)); - data.add(new CompetingRiskResponseWithCensorTime(1, 4, 4)); - data.add(new CompetingRiskResponseWithCensorTime(0, 5, 5)); - data.add(new CompetingRiskResponseWithCensorTime(2, 6, 7)); - - return data; - } - - @Test - public void testCalculatingSets(){ - final List data = generateData(); - - final CompetingRiskSetsImpl sets = CompetingRiskUtils.calculateSetsEfficiently(data, new int[]{1,2}); - - final List times = sets.getEventTimes(); - assertEquals(5, times.size()); - - // Times - assertEquals(1.0, times.get(0).doubleValue()); - assertEquals(2.0, times.get(1).doubleValue()); - assertEquals(3.0, times.get(2).doubleValue()); - assertEquals(4.0, times.get(3).doubleValue()); - assertEquals(6.0, times.get(4).doubleValue()); - - // Number of Events - assertEquals(2, sets.getNumberOfEvents(1.0, 1)); - assertEquals(0, sets.getNumberOfEvents(1.0, 2)); - - assertEquals(1, sets.getNumberOfEvents(2.0, 1)); - assertEquals(0, sets.getNumberOfEvents(2.0, 2)); - - assertEquals(0, sets.getNumberOfEvents(3.0, 1)); - assertEquals(1, sets.getNumberOfEvents(3.0, 2)); - - assertEquals(1, sets.getNumberOfEvents(4.0, 1)); - assertEquals(0, sets.getNumberOfEvents(4.0, 2)); - - assertEquals(0, sets.getNumberOfEvents(6.0, 1)); - assertEquals(1, sets.getNumberOfEvents(6.0, 2)); - - // Make sure it doesn't break for other times - assertEquals(0, sets.getNumberOfEvents(5.5, 1)); - assertEquals(0, sets.getNumberOfEvents(5.5, 2)); - - - // Risk set - assertEquals(9, sets.getRiskSet(1).evaluate(0.5)); - assertEquals(9, sets.getRiskSet(2).evaluate(0.5)); - - assertEquals(9, sets.getRiskSet(1).evaluate(1.0)); - assertEquals(9, sets.getRiskSet(2).evaluate(1.0)); - - assertEquals(6, sets.getRiskSet(1).evaluate(1.5)); - assertEquals(6, sets.getRiskSet(2).evaluate(1.5)); - - assertEquals(6, sets.getRiskSet(1).evaluate(2.0)); - assertEquals(6, sets.getRiskSet(2).evaluate(2.0)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.3)); - assertEquals(5, sets.getRiskSet(2).evaluate(2.3)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.5)); - assertEquals(5, sets.getRiskSet(2).evaluate(2.5)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.7)); - assertEquals(5, sets.getRiskSet(2).evaluate(2.7)); - - assertEquals(5, sets.getRiskSet(1).evaluate(3.0)); - assertEquals(5, sets.getRiskSet(2).evaluate(3.0)); - - assertEquals(3, sets.getRiskSet(1).evaluate(3.5)); - assertEquals(3, sets.getRiskSet(2).evaluate(3.5)); - - assertEquals(3, sets.getRiskSet(1).evaluate(4.0)); - assertEquals(3, sets.getRiskSet(2).evaluate(4.0)); - - assertEquals(2, sets.getRiskSet(1).evaluate(4.5)); - assertEquals(2, sets.getRiskSet(2).evaluate(4.5)); - - assertEquals(2, sets.getRiskSet(1).evaluate(5.0)); - assertEquals(2, sets.getRiskSet(2).evaluate(5.0)); - - assertEquals(1, sets.getRiskSet(1).evaluate(5.5)); - assertEquals(1, sets.getRiskSet(2).evaluate(5.5)); - - assertEquals(1, sets.getRiskSet(1).evaluate(6.0)); - assertEquals(1, sets.getRiskSet(2).evaluate(6.0)); - - assertEquals(0, sets.getRiskSet(1).evaluate(6.5)); - assertEquals(0, sets.getRiskSet(2).evaluate(6.5)); - - assertEquals(0, sets.getRiskSet(1).evaluate(7.0)); - assertEquals(0, sets.getRiskSet(2).evaluate(7.0)); - - assertEquals(0, sets.getRiskSet(1).evaluate(7.5)); - assertEquals(0, sets.getRiskSet(2).evaluate(7.5)); - - } - - @Test - public void testCalculatingGraySets(){ - final List data = generateData(); - - final CompetingRiskGraySetsImpl sets = CompetingRiskUtils.calculateGraySetsEfficiently(data, new int[]{1,2}); - - final List times = sets.getEventTimes(); - assertEquals(5, times.size()); - - // Times - assertEquals(1.0, times.get(0).doubleValue()); - assertEquals(2.0, times.get(1).doubleValue()); - assertEquals(3.0, times.get(2).doubleValue()); - assertEquals(4.0, times.get(3).doubleValue()); - assertEquals(6.0, times.get(4).doubleValue()); - - // Number of Events - assertEquals(2, sets.getNumberOfEvents(1.0, 1)); - assertEquals(0, sets.getNumberOfEvents(1.0, 2)); - - assertEquals(1, sets.getNumberOfEvents(2.0, 1)); - assertEquals(0, sets.getNumberOfEvents(2.0, 2)); - - assertEquals(0, sets.getNumberOfEvents(3.0, 1)); - assertEquals(1, sets.getNumberOfEvents(3.0, 2)); - - assertEquals(1, sets.getNumberOfEvents(4.0, 1)); - assertEquals(0, sets.getNumberOfEvents(4.0, 2)); - - assertEquals(0, sets.getNumberOfEvents(6.0, 1)); - assertEquals(1, sets.getNumberOfEvents(6.0, 2)); - - // Make sure it doesn't break for other times - assertEquals(0, sets.getNumberOfEvents(5.5, 1)); - assertEquals(0, sets.getNumberOfEvents(5.5, 2)); - - - // Risk set - assertEquals(9, sets.getRiskSet(1).evaluate(0.5)); - assertEquals(9, sets.getRiskSet(2).evaluate(0.5)); - - assertEquals(9, sets.getRiskSet(1).evaluate(1.0)); - assertEquals(9, sets.getRiskSet(2).evaluate(1.0)); - - assertEquals(6, sets.getRiskSet(1).evaluate(1.5)); - assertEquals(8, sets.getRiskSet(2).evaluate(1.5)); - - assertEquals(6, sets.getRiskSet(1).evaluate(2.0)); - assertEquals(8, sets.getRiskSet(2).evaluate(2.0)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.3)); - assertEquals(8, sets.getRiskSet(2).evaluate(2.3)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.5)); - assertEquals(7, sets.getRiskSet(2).evaluate(2.5)); - - assertEquals(5, sets.getRiskSet(1).evaluate(2.7)); - assertEquals(7, sets.getRiskSet(2).evaluate(2.7)); - - assertEquals(5, sets.getRiskSet(1).evaluate(3.0)); - assertEquals(5, sets.getRiskSet(2).evaluate(3.0)); - - assertEquals(4, sets.getRiskSet(1).evaluate(3.5)); - assertEquals(3, sets.getRiskSet(2).evaluate(3.5)); - - assertEquals(3, sets.getRiskSet(1).evaluate(4.0)); - assertEquals(3, sets.getRiskSet(2).evaluate(4.0)); - - assertEquals(2, sets.getRiskSet(1).evaluate(4.5)); - assertEquals(2, sets.getRiskSet(2).evaluate(4.5)); - - assertEquals(2, sets.getRiskSet(1).evaluate(5.0)); - assertEquals(2, sets.getRiskSet(2).evaluate(5.0)); - - assertEquals(1, sets.getRiskSet(1).evaluate(5.5)); - assertEquals(1, sets.getRiskSet(2).evaluate(5.5)); - - assertEquals(1, sets.getRiskSet(1).evaluate(6.0)); - assertEquals(1, sets.getRiskSet(2).evaluate(6.0)); - - assertEquals(1, sets.getRiskSet(1).evaluate(6.5)); - assertEquals(0, sets.getRiskSet(2).evaluate(6.5)); - - assertEquals(0, sets.getRiskSet(1).evaluate(7.0)); - assertEquals(0, sets.getRiskSet(2).evaluate(7.0)); - - assertEquals(0, sets.getRiskSet(1).evaluate(7.5)); - assertEquals(0, sets.getRiskSet(2).evaluate(7.5)); - - } - -} diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java index ea2d7dd..a48d38c 100644 --- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java +++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java @@ -1,8 +1,15 @@ package ca.joeltherrien.randomforest.competingrisk; -import ca.joeltherrien.randomforest.*; -import ca.joeltherrien.randomforest.covariates.*; -import ca.joeltherrien.randomforest.responses.competingrisk.*; +import ca.joeltherrien.randomforest.CovariateRow; +import ca.joeltherrien.randomforest.DataLoader; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.Settings; +import ca.joeltherrien.randomforest.covariates.Covariate; +import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskErrorRateCalculator; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctions; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; import ca.joeltherrien.randomforest.tree.Forest; import ca.joeltherrien.randomforest.tree.ForestTrainer; import ca.joeltherrien.randomforest.tree.Node; @@ -12,12 +19,14 @@ import ca.joeltherrien.randomforest.utils.Utils; import com.fasterxml.jackson.databind.node.*; import org.junit.jupiter.api.Test; -import static ca.joeltherrien.randomforest.TestUtils.assertCumulativeFunction; -import static ca.joeltherrien.randomforest.TestUtils.closeEnough; -import static org.junit.jupiter.api.Assertions.*; - import java.io.IOException; import java.util.List; +import java.util.Random; + +import static ca.joeltherrien.randomforest.TestUtils.assertCumulativeFunction; +import static ca.joeltherrien.randomforest.TestUtils.closeEnough; +import static org.junit.jupiter.api.Assertions.assertEquals; +import static org.junit.jupiter.api.Assertions.assertTrue; public class TestCompetingRisk { @@ -104,7 +113,7 @@ public class TestCompetingRisk { final List> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation()); final TreeTrainer treeTrainer = new TreeTrainer<>(settings, covariates); - final Node node = treeTrainer.growTree(dataset); + final Node node = treeTrainer.growTree(dataset, new Random()); final CovariateRow newRow = getPredictionRow(covariates); @@ -157,7 +166,7 @@ public class TestCompetingRisk { final List> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation()); final TreeTrainer treeTrainer = new TreeTrainer<>(settings, covariates); - final Node node = treeTrainer.growTree(dataset); + final Node node = treeTrainer.growTree(dataset, new Random()); final CovariateRow newRow = getPredictionRow(covariates); @@ -281,6 +290,34 @@ public class TestCompetingRisk { assertEquals(359, countEventTwo); } + /** + * Used to time how long the algorithm takes + * + * @param args Not used. + * @throws IOException + */ + public static void main(String[] args) throws IOException { + // timing + final TestCompetingRisk tcr = new TestCompetingRisk(); + + final Settings settings = tcr.getSettings(); + settings.setNtree(300); // results are too variable at 100 + + final List covariates = settings.getCovariates(); + final List> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), + settings.getTrainingDataLocation()); + final ForestTrainer forestTrainer = new ForestTrainer<>(settings, dataset, covariates); + + final long startTime = System.currentTimeMillis(); + for(int i=0; i<50; i++){ + forestTrainer.trainSerial(); + } + final long endTime = System.currentTimeMillis(); + + final double diffTime = endTime - startTime; + System.out.println(diffTime / 1000.0 / 50.0); + } + @Test public void testLogRankSingleGroupDifferentiatorAllCovariates() throws IOException { diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java new file mode 100644 index 0000000..9836ee3 --- /dev/null +++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java @@ -0,0 +1,89 @@ +package ca.joeltherrien.randomforest.competingrisk; + +import ca.joeltherrien.randomforest.DataLoader; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.Settings; +import ca.joeltherrien.randomforest.covariates.Covariate; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; +import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankMultipleGroupDifferentiator; +import ca.joeltherrien.randomforest.tree.Split; +import ca.joeltherrien.randomforest.utils.SingletonIterator; +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; +import lombok.AllArgsConstructor; +import org.junit.jupiter.api.Test; + +import java.io.IOException; +import java.util.Collections; +import java.util.Iterator; +import java.util.List; +import java.util.stream.Collectors; + +import static org.junit.jupiter.api.Assertions.assertTrue; + +public class TestLogRankMultipleGroupDifferentiator { + + private Iterator> turnIntoSplitIterator(List> leftList, + List> rightList){ + return new SingletonIterator>(new Split(null, leftList, rightList, Collections.emptyList())); + } + + public static Data loadData(String filename) throws IOException { + final ObjectNode yVarSettings = new ObjectNode(JsonNodeFactory.instance); + yVarSettings.set("type", new TextNode("CompetingRiskResponse")); + yVarSettings.set("delta", new TextNode("delta")); + yVarSettings.set("u", new TextNode("u")); + + final Settings settings = Settings.builder() + .trainingDataLocation(filename) + .covariateSettings( + Utils.easyList(new NumericCovariateSettings("x2")) + ) + .yVarSettings(yVarSettings) + .build(); + + final List covariates = settings.getCovariates(); + + final DataLoader.ResponseLoader loader = settings.getResponseLoader(); + final List> rows = DataLoader.loadData(covariates, loader, settings.getTrainingDataLocation()); + + return new Data<>(rows, covariates); + } + + @Test + public void testSplitRule() throws IOException { + final LogRankMultipleGroupDifferentiator groupDifferentiator = new LogRankMultipleGroupDifferentiator(new int[]{1,2}); + + final List> data = loadData("src/test/resources/test_split_data.csv").getRows(); + + final List> group1Bad = data.subList(0, 196); + final List> group2Bad = data.subList(196, data.size()); + + final double scoreBad = groupDifferentiator.differentiate(turnIntoSplitIterator(group1Bad, group2Bad)).getScore(); + + final List> group1Good = data.subList(0, 199); + final List> group2Good= data.subList(199, data.size()); + + final double scoreGood = groupDifferentiator.differentiate(turnIntoSplitIterator(group1Good, group2Good)).getScore(); + + // expected results calculated manually using survival::survdiff in R; see issue #10 in Gitea + closeEnough(71.41135, scoreBad, 0.00001); + closeEnough(71.5354, scoreGood, 0.00001); + + } + + private void closeEnough(double expected, double actual, double margin){ + assertTrue(Math.abs(expected - actual) < margin, "Expected " + expected + " but saw " + actual); + } + + @lombok.Data + @AllArgsConstructor + public static class Data { + private List> rows; + private List covariateList; + } + +} diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java index ef79b65..03856b0 100644 --- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java +++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java @@ -1,52 +1,74 @@ package ca.joeltherrien.randomforest.competingrisk; -import ca.joeltherrien.randomforest.responses.competingrisk.*; +import ca.joeltherrien.randomforest.Row; +import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse; import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankSingleGroupDifferentiator; +import ca.joeltherrien.randomforest.tree.GroupDifferentiator; +import ca.joeltherrien.randomforest.tree.Split; +import ca.joeltherrien.randomforest.utils.SingletonIterator; import org.junit.jupiter.api.Test; +import java.io.IOException; import java.util.ArrayList; +import java.util.Collections; +import java.util.Iterator; import java.util.List; +import java.util.stream.Collectors; +import static org.junit.jupiter.api.Assertions.assertEquals; import static org.junit.jupiter.api.Assertions.assertTrue; public class TestLogRankSingleGroupDifferentiator { - private List generateData1(){ - final List data = new ArrayList<>(); + private double getScore(final GroupDifferentiator groupDifferentiator, List> left, List> right){ + final Iterator> iterator = new SingletonIterator<>( + new Split<>(null, left, right, Collections.emptyList())); - 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(1, 1.5)); - data.add(new CompetingRiskResponse(0, 2.0)); - data.add(new CompetingRiskResponse(0, 1.5)); - data.add(new CompetingRiskResponse(0, 2.5)); + return groupDifferentiator.differentiate(iterator).getScore(); + + } + + int count = 1; + private Row createRow(Y response){ + return new Row<>(null, count++, response); + } + + private List> generateData1(){ + final List> data = new ArrayList<>(); + + data.add(createRow(new CompetingRiskResponse(1, 1.0))); + data.add(createRow(new CompetingRiskResponse(1, 1.0))); + data.add(createRow(new CompetingRiskResponse(1, 2.0))); + data.add(createRow(new CompetingRiskResponse(1, 1.5))); + data.add(createRow(new CompetingRiskResponse(0, 2.0))); + data.add(createRow(new CompetingRiskResponse(0, 1.5))); + data.add(createRow(new CompetingRiskResponse(0, 2.5))); return data; } - private List generateData2(){ - final List data = new ArrayList<>(); + private List> generateData2(){ + final List> data = new ArrayList<>(); - data.add(new CompetingRiskResponse(1, 2.0)); - data.add(new CompetingRiskResponse(1, 2.0)); - data.add(new CompetingRiskResponse(1, 4.0)); - data.add(new CompetingRiskResponse(1, 3.0)); - data.add(new CompetingRiskResponse(0, 4.0)); - data.add(new CompetingRiskResponse(0, 3.0)); - data.add(new CompetingRiskResponse(0, 5.0)); + data.add(createRow(new CompetingRiskResponse(1, 2.0))); + data.add(createRow(new CompetingRiskResponse(1, 2.0))); + data.add(createRow(new CompetingRiskResponse(1, 4.0))); + data.add(createRow(new CompetingRiskResponse(1, 3.0))); + data.add(createRow(new CompetingRiskResponse(0, 4.0))); + data.add(createRow(new CompetingRiskResponse(0, 3.0))); + data.add(createRow(new CompetingRiskResponse(0, 5.0))); return data; } @Test public void testCompetingRiskResponseCombiner(){ - final List data1 = generateData1(); - final List data2 = generateData2(); + final List> data1 = generateData1(); + final List> data2 = generateData2(); final LogRankSingleGroupDifferentiator differentiator = new LogRankSingleGroupDifferentiator(1, new int[]{1}); - final double score = differentiator.differentiate(data1, data2); + final double score = getScore(differentiator, data1, data2); final double margin = 0.000001; // Tested using 855 method @@ -55,6 +77,28 @@ public class TestLogRankSingleGroupDifferentiator { } + @Test + public void testCorrectSplit() throws IOException { + final LogRankSingleGroupDifferentiator groupDifferentiator = + new LogRankSingleGroupDifferentiator(1, new int[]{1,2}); + + final List> data = TestLogRankMultipleGroupDifferentiator. + loadData("src/test/resources/test_single_split.csv").getRows(); + + final List> group1Good = data.subList(0, 221); + final List> group2Good = data.subList(221, data.size()); + + final double scoreGood = getScore(groupDifferentiator, group1Good, group2Good); + + final List> group1Bad = data.subList(0, 222); + final List> group2Bad = data.subList(222, data.size()); + + final double scoreBad = getScore(groupDifferentiator, group1Bad, group2Bad); + + // Apparently not all groups are unique when splitting + assertEquals(scoreGood, scoreBad); + } + private void closeEnough(double expected, double actual, double margin){ assertTrue(Math.abs(expected - actual) < margin, "Expected " + expected + " but saw " + actual); } diff --git a/src/test/java/ca/joeltherrien/randomforest/covariates/FactorCovariateTest.java b/src/test/java/ca/joeltherrien/randomforest/covariates/FactorCovariateTest.java index 7d80a8c..adbf3d2 100644 --- a/src/test/java/ca/joeltherrien/randomforest/covariates/FactorCovariateTest.java +++ b/src/test/java/ca/joeltherrien/randomforest/covariates/FactorCovariateTest.java @@ -5,8 +5,9 @@ import ca.joeltherrien.randomforest.utils.Utils; import org.junit.jupiter.api.Test; import org.junit.jupiter.api.function.Executable; -import java.util.Collection; +import java.util.ArrayList; import java.util.List; +import java.util.Random; import static org.junit.jupiter.api.Assertions.*; @@ -46,7 +47,10 @@ public class FactorCovariateTest { void testAllSubsets(){ final FactorCovariate petCovariate = createTestCovariate(); - final Collection splitRules = petCovariate.generateSplitRules(null, 100); + final List> splitRules = new ArrayList<>(); + + petCovariate.generateSplitRuleUpdater(null, 100, new Random()) + .forEachRemaining(split -> splitRules.add(split.getSplitRule())); assertEquals(splitRules.size(), 3); diff --git a/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java b/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java index 82262df..1fbb40f 100644 --- a/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java +++ b/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java @@ -3,10 +3,10 @@ package ca.joeltherrien.randomforest.csv; import ca.joeltherrien.randomforest.DataLoader; import ca.joeltherrien.randomforest.Row; import ca.joeltherrien.randomforest.Settings; -import ca.joeltherrien.randomforest.covariates.BooleanCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings; import ca.joeltherrien.randomforest.covariates.Covariate; -import ca.joeltherrien.randomforest.covariates.FactorCovariateSettings; -import ca.joeltherrien.randomforest.covariates.NumericCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.FactorCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; import ca.joeltherrien.randomforest.utils.Utils; import com.fasterxml.jackson.databind.node.JsonNodeFactory; import com.fasterxml.jackson.databind.node.ObjectNode; @@ -15,7 +15,6 @@ import org.junit.jupiter.api.Test; import java.io.IOException; import java.util.List; -import java.util.stream.Collectors; import static org.junit.jupiter.api.Assertions.assertEquals; import static org.junit.jupiter.api.Assertions.assertTrue; diff --git a/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java b/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java index 901cdb1..79a0e6b 100644 --- a/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java +++ b/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java @@ -3,7 +3,9 @@ package ca.joeltherrien.randomforest.settings; import ca.joeltherrien.randomforest.Settings; import static org.junit.jupiter.api.Assertions.assertEquals; -import ca.joeltherrien.randomforest.covariates.*; +import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.FactorCovariateSettings; +import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings; import ca.joeltherrien.randomforest.utils.Utils; import com.fasterxml.jackson.databind.node.JsonNodeFactory; import com.fasterxml.jackson.databind.node.ObjectNode; diff --git a/src/test/java/ca/joeltherrien/randomforest/utils/TestSingletonIterator.java b/src/test/java/ca/joeltherrien/randomforest/utils/TestSingletonIterator.java new file mode 100644 index 0000000..03805a7 --- /dev/null +++ b/src/test/java/ca/joeltherrien/randomforest/utils/TestSingletonIterator.java @@ -0,0 +1,25 @@ +package ca.joeltherrien.randomforest.utils; + +import org.junit.jupiter.api.Test; + +import static org.junit.jupiter.api.Assertions.*; + +public class TestSingletonIterator { + + @Test + public void verifyBehaviour(){ + final Integer element = 5; + + final SingletonIterator iterator = new SingletonIterator<>(element); + + assertTrue(iterator.hasNext()); + assertTrue(iterator.hasNext()); + + assertEquals(Integer.valueOf(5), iterator.next()); + + assertFalse(iterator.hasNext()); + assertNull(iterator.next()); + + } + +} diff --git a/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueSubsetValueIterator.java b/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueSubsetValueIterator.java new file mode 100644 index 0000000..0eb0051 --- /dev/null +++ b/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueSubsetValueIterator.java @@ -0,0 +1,68 @@ +package ca.joeltherrien.randomforest.utils; + +import org.junit.jupiter.api.Test; + +import java.util.Arrays; +import java.util.List; + +import static org.junit.jupiter.api.Assertions.*; + +public class TestUniqueSubsetValueIterator { + + @Test + public void testIterator1(){ + final List testData = Arrays.asList( + 1,1,2,3,5,5,5,6,7,7 + ); + + final Integer[] indexes = new Integer[]{2,3,4,5}; + + final UniqueValueIterator uniqueValueIterator = new UniqueValueIterator<>(testData.iterator()); + final UniqueSubsetValueIterator iterator = new UniqueSubsetValueIterator<>(uniqueValueIterator, indexes); + + // we expect to get 2, 3, and 5 back. 5 should happen only once + + assertEquals(iterator.getIndex(), 0); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 2); + assertEquals(iterator.getIndex(), 3); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 3); + assertEquals(iterator.getIndex(), 4); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 5); + assertEquals(iterator.getIndex(), 7); + assertFalse(iterator.hasNext()); + + + } + + @Test + public void testIterator2(){ + final List testData = Arrays.asList( + 1,1,2,3,5,5,5,6,7,7 + ); + + final Integer[] indexes = new Integer[]{1,8}; + + final UniqueValueIterator uniqueValueIterator = new UniqueValueIterator<>(testData.iterator()); + final UniqueSubsetValueIterator iterator = new UniqueSubsetValueIterator<>(uniqueValueIterator, indexes); + + assertEquals(iterator.getIndex(), 0); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 1); + assertEquals(iterator.getIndex(), 2); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 7); + assertEquals(iterator.getIndex(), 10); + assertFalse(iterator.hasNext()); + + + } + +} diff --git a/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueValueIterator.java b/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueValueIterator.java new file mode 100644 index 0000000..16d6cc0 --- /dev/null +++ b/src/test/java/ca/joeltherrien/randomforest/utils/TestUniqueValueIterator.java @@ -0,0 +1,112 @@ +package ca.joeltherrien.randomforest.utils; + +import org.junit.jupiter.api.Test; + +import java.util.Arrays; +import java.util.List; + +import static org.junit.jupiter.api.Assertions.*; + +public class TestUniqueValueIterator { + + @Test + public void testIterator1(){ + final List testData = Arrays.asList( + 1,1,2,3,5,5,5,6,7,7 + ); + + final UniqueValueIterator iterator = new UniqueValueIterator<>(testData.iterator()); + + assertEquals(iterator.getIndex(), 0); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 1); + assertEquals(iterator.getIndex(), 2); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 2); + assertEquals(iterator.getIndex(), 3); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 3); + assertEquals(iterator.getIndex(), 4); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 5); + assertEquals(iterator.getIndex(), 7); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 6); + assertEquals(iterator.getIndex(), 8); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 7); + assertEquals(iterator.getIndex(), 10); + assertTrue(!iterator.hasNext()); + + } + + @Test + public void testIterator2(){ + final List testData = Arrays.asList( + 1,2,3,5,5,5,6,7 // same numbers; but 1 and 7 only appear once each + ); + + final UniqueValueIterator iterator = new UniqueValueIterator<>(testData.iterator()); + + assertEquals(iterator.getIndex(), 0); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 1); + assertEquals(iterator.getIndex(), 1); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 2); + assertEquals(iterator.getIndex(), 2); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 3); + assertEquals(iterator.getIndex(), 3); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 5); + assertEquals(iterator.getIndex(), 6); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 6); + assertEquals(iterator.getIndex(), 7); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 7); + assertEquals(iterator.getIndex(), 8); + assertFalse(iterator.hasNext()); + + } + + @Test + public void testIterator3(){ + final List testData = Arrays.asList( + 1,1,1,1,1,1,1,2,2,2,2,2,3 + ); + + final UniqueValueIterator iterator = new UniqueValueIterator<>(testData.iterator()); + + assertEquals(iterator.getIndex(), 0); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 1); + assertEquals(iterator.getIndex(), 7); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 2); + assertEquals(iterator.getIndex(), 12); + assertTrue(iterator.hasNext()); + + assertEquals(iterator.next().intValue(), 3); + assertEquals(iterator.getIndex(), 13); + assertFalse(iterator.hasNext()); + + + } + +} diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java index f453cd9..d87442b 100644 --- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java +++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java @@ -2,7 +2,7 @@ package ca.joeltherrien.randomforest.workshop; import ca.joeltherrien.randomforest.*; import ca.joeltherrien.randomforest.covariates.Covariate; -import ca.joeltherrien.randomforest.covariates.NumericCovariate; +import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate; import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner; import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator; import ca.joeltherrien.randomforest.tree.ForestTrainer; diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java index 88a855e..547eb09 100644 --- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java +++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java @@ -3,7 +3,7 @@ package ca.joeltherrien.randomforest.workshop; import ca.joeltherrien.randomforest.covariates.Covariate; import ca.joeltherrien.randomforest.CovariateRow; -import ca.joeltherrien.randomforest.covariates.NumericCovariate; +import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate; import ca.joeltherrien.randomforest.Row; import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner; import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator; @@ -54,13 +54,14 @@ public class TrainSingleTree { .covariates(covariateNames) .responseCombiner(new MeanResponseCombiner()) .maxNodeDepth(30) + .mtry(2) .nodeSize(5) .numberOfSplits(0) .build(); final long startTime = System.currentTimeMillis(); - final Node baseNode = treeTrainer.growTree(trainingSet); + final Node baseNode = treeTrainer.growTree(trainingSet, new Random()); final long endTime = System.currentTimeMillis(); System.out.println(((double)(endTime - startTime))/1000.0); diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java index 6c2d430..e126624 100644 --- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java +++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java @@ -4,7 +4,7 @@ package ca.joeltherrien.randomforest.workshop; import ca.joeltherrien.randomforest.*; import ca.joeltherrien.randomforest.covariates.Covariate; import ca.joeltherrien.randomforest.covariates.FactorCovariate; -import ca.joeltherrien.randomforest.covariates.NumericCovariate; +import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate; import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner; import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator; import ca.joeltherrien.randomforest.tree.Node; @@ -13,7 +13,6 @@ import ca.joeltherrien.randomforest.utils.Utils; import java.util.ArrayList; import java.util.List; -import java.util.Map; import java.util.Random; import java.util.stream.Collectors; import java.util.stream.DoubleStream; @@ -21,8 +20,6 @@ import java.util.stream.DoubleStream; public class TrainSingleTreeFactor { public static void main(String[] args) { - System.out.println("Hello world!"); - final Random random = new Random(123); final int n = 10000; @@ -84,7 +81,7 @@ public class TrainSingleTreeFactor { final long startTime = System.currentTimeMillis(); - final Node baseNode = treeTrainer.growTree(trainingSet); + final Node baseNode = treeTrainer.growTree(trainingSet, random); final long endTime = System.currentTimeMillis(); System.out.println(((double)(endTime - startTime))/1000.0); diff --git a/src/test/resources/test_single_split.csv b/src/test/resources/test_single_split.csv new file mode 100644 index 0000000..e1e63b5 --- /dev/null +++ b/src/test/resources/test_single_split.csv @@ -0,0 +1,437 @@ +"T","J","x1","x2","x3","set","C","u","delta" +2.36878896318231,2,-0.940736926269951,-2.74741651651697,-0.664166655908226,"d1",5.29132863866294,2.36878896318231,2 +0.0400548702796549,2,-0.22357985281977,-2.6784315261127,-1.45393397969899,"d1",24.0450198381188,0.0400548702796549,2 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