Add convenience methods to improve R interface performance
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4 changed files with 52 additions and 5 deletions
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@ -5,6 +5,7 @@ import lombok.Builder;
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import java.util.Collection;
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import java.util.Collection;
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import java.util.Collections;
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import java.util.Collections;
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import java.util.List;
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import java.util.stream.Collectors;
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import java.util.stream.Collectors;
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@Builder
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@Builder
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@ -16,17 +17,29 @@ public class Forest<O, FO> { // O = output of trees, FO = forest output. In prac
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public FO evaluate(CovariateRow row){
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public FO evaluate(CovariateRow row){
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return treeResponseCombiner.combine(
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return treeResponseCombiner.combine(
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trees.parallelStream()
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trees.stream()
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.map(node -> node.evaluate(row))
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.map(node -> node.evaluate(row))
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.collect(Collectors.toList())
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.collect(Collectors.toList())
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);
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);
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}
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}
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/**
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* Used primarily in the R package interface to avoid R loops; and for easier parallelization.
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*
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* @param rowList List of CovariateRows to evaluate
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* @return A List of predictions.
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*/
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public List<FO> evaluate(List<CovariateRow> rowList){
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return rowList.parallelStream()
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.map(this::evaluate)
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.collect(Collectors.toList());
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}
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public FO evaluateOOB(CovariateRow row){
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public FO evaluateOOB(CovariateRow row){
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return treeResponseCombiner.combine(
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return treeResponseCombiner.combine(
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trees.parallelStream()
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trees.stream()
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.filter(tree -> !tree.idInBootstrapSample(row.getId()))
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.filter(tree -> !tree.idInBootstrapSample(row.getId()))
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.map(node -> node.evaluate(row))
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.map(node -> node.evaluate(row))
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.collect(Collectors.toList())
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.collect(Collectors.toList())
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34
src/main/java/ca/joeltherrien/randomforest/utils/RUtils.java
Normal file
34
src/main/java/ca/joeltherrien/randomforest/utils/RUtils.java
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@ -0,0 +1,34 @@
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package ca.joeltherrien.randomforest.utils;
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import java.util.List;
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/**
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* These static methods are designed to make the R interface more performant; and to avoid using R loops.
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*
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*/
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public final class RUtils {
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public static double[] extractTimes(final MathFunction function){
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final List<Point> pointList = function.getPoints();
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final double[] times = new double[pointList.size()];
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for(int i=0; i<pointList.size(); i++){
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times[i] = pointList.get(i).getTime();
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}
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return times;
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}
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public static double[] extractY(final MathFunction function){
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final List<Point> pointList = function.getPoints();
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final double[] times = new double[pointList.size()];
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for(int i=0; i<pointList.size(); i++){
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times[i] = pointList.get(i).getY();
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}
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return times;
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}
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}
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@ -3,7 +3,7 @@ package ca.joeltherrien.randomforest.utils;
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import java.util.*;
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import java.util.*;
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import java.util.concurrent.ThreadLocalRandom;
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import java.util.concurrent.ThreadLocalRandom;
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public class Utils {
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public final class Utils {
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public static MathFunction estimateOneMinusECDF(final double[] times){
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public static MathFunction estimateOneMinusECDF(final double[] times){
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final Point defaultPoint = new Point(0.0, 1.0);
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final Point defaultPoint = new Point(0.0, 1.0);
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@ -325,8 +325,8 @@ public class TestCompetingRisk {
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*/
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*/
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// Consistency results
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// Consistency results
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closeEnough(0.395, errorRates[0], 0.01);
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closeEnough(0.395, errorRates[0], 0.02);
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closeEnough(0.345, errorRates[1], 0.01);
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closeEnough(0.345, errorRates[1], 0.02);
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System.out.println(errorRateCalculator.calculateNaiveMortalityError(new int[]{1,2}));
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System.out.println(errorRateCalculator.calculateNaiveMortalityError(new int[]{1,2}));
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