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FeatureVector no longer uses fastutil Hash Map #2939

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Merged
merged 1 commit into from
Sep 16, 2025
Merged

FeatureVector no longer uses fastutil Hash Map #2939

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30 changes: 13 additions & 17 deletions src/main/java/io/anserini/util/FeatureVector.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,18 +16,18 @@

package io.anserini.util;

import it.unimi.dsi.fastutil.objects.Object2FloatOpenHashMap;

import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;

public class FeatureVector {
private Object2FloatOpenHashMap<String> features = new Object2FloatOpenHashMap<String>();
private Map<String, Float> features = new HashMap<>();

public enum Order {
FEATURE_DESCENDING, FEATURE_ASCENDING, VALUE_DESCENDING, VALUE_ASCENDING
Expand All @@ -36,16 +36,12 @@ public enum Order {
public FeatureVector() {}

public void addFeatureValue(String feature, float value) {
if (!features.containsKey(feature)) {
features.put(feature, value);
} else {
features.put(feature, features.getFloat(feature) + value);
}
features.put(feature, features.getOrDefault(feature, 0.0f) + value);
}

public FeatureVector pruneToSize(int k) {
List<FeatureValuePair> pairs = getOrderedFeatures();
Object2FloatOpenHashMap<String> pruned = new Object2FloatOpenHashMap<>();
Map<String, Float> pruned = new HashMap<>();

for (FeatureValuePair pair : pairs) {
pruned.put(pair.getFeature(), pair.getValue());
Expand All @@ -60,17 +56,17 @@ public FeatureVector pruneToSize(int k) {

public FeatureVector scaleToUnitL2Norm() {
double norm = computeL2Norm();
for (String f : features.keySet()) {
features.put(f, (float) (features.getFloat(f) / norm));
for (Map.Entry<String, Float> e : features.entrySet()) {
e.setValue((float) (e.getValue() / norm));
}

return this;
}

public FeatureVector scaleToUnitL1Norm() {
double norm = computeL1Norm();
for (String f : features.keySet()) {
features.put(f, (float) (features.getFloat(f) / norm));
for (Map.Entry<String, Float> e : features.entrySet()) {
e.setValue((float) (e.getValue() / norm));
}

return this;
Expand All @@ -81,7 +77,7 @@ public Set<String> getFeatures() {
}

public float getValue(String feature) {
return features.containsKey(feature) ? features.getFloat(feature) : 0.0f;
return features.getOrDefault(feature, 0.0f);
}

public Iterator<String> iterator() {
Expand All @@ -95,15 +91,15 @@ public boolean contains(String feature) {
public double computeL2Norm() {
double norm = 0.0;
for (String term : features.keySet()) {
norm += Math.pow(features.getFloat(term), 2.0);
norm += Math.pow(features.getOrDefault(term, 0.0f), 2.0);
}
return Math.sqrt(norm);
}

public double computeL1Norm() {
double norm = 0.0;
for (String term : features.keySet()) {
norm += Math.abs(features.getFloat(term));
norm += Math.abs(features.getOrDefault(term, 0.0f));
}
return norm;
}
Expand All @@ -125,7 +121,7 @@ private List<FeatureValuePair> getOrderedFeatures(Order order) {
Iterator<String> featureIterator = features.keySet().iterator();
while (featureIterator.hasNext()) {
String feature = featureIterator.next();
float value = features.getFloat(feature);
float value = features.getOrDefault(feature, 0.0f);
FeatureValuePair featureValuePair = new FeatureValuePair(feature, value);
pairs.add(featureValuePair);
}
Expand Down