tidy

Author: vigyasharma

lucene/core/src/java/org/apache/lucene/search/DoubleValuesSource.java

@@ -281,7 +281,7 @@ public static DoubleValues similarityToQueryVector(
               + " does not have the expected vector encoding: "
               + VectorEncoding.FLOAT32);
     }
-    return new FloatVectorSimilarityValuesSource(queryVector, vectorField, true).getValues(ctx, null);
+    return new FloatVectorSimilarityValuesSource(queryVector, vectorField).getValues(ctx, null);
   }
 
   /**

lucene/core/src/java/org/apache/lucene/search/FloatVectorSimilarityValuesSource.java

@@ -20,7 +20,6 @@
 import java.io.IOException;
 import java.util.Arrays;
 import java.util.Objects;
-
 import org.apache.lucene.index.FieldInfo;
 import org.apache.lucene.index.FloatVectorValues;
 import org.apache.lucene.index.KnnVectorValues;
@@ -39,6 +38,7 @@ class FloatVectorSimilarityValuesSource extends VectorSimilarityValuesSource {
   /**
    * Creates a {@link DoubleValuesSource} that returns vector similarity score between provided
    * query vector and field for documents. Uses the scorer exposed by configured vectors reader.
+   *
    * @param vector the query vector
    * @param fieldName the field name of the {@link org.apache.lucene.document.KnnFloatVectorField}
    */
@@ -52,10 +52,11 @@ public FloatVectorSimilarityValuesSource(float[] vector, String fieldName) {
    *
    * @param vector the query vector
    * @param fieldName the field name of the {@link org.apache.lucene.document.KnnFloatVectorField}
-   * @param useFullPrecision uses full precision raw vectors for similarity computation if true, otherwise
-   *                         the configured vectors reader is used, which may be quantized or full precision.
+   * @param useFullPrecision uses full precision raw vectors for similarity computation if true,
+   *     otherwise the configured vectors reader is used, which may be quantized or full precision.
    */
-  public FloatVectorSimilarityValuesSource(float[] vector, String fieldName, boolean useFullPrecision) {
+  public FloatVectorSimilarityValuesSource(
+      float[] vector, String fieldName, boolean useFullPrecision) {
     super(fieldName);
     this.queryVector = vector;
     this.useFullPrecision = useFullPrecision;
@@ -89,7 +90,8 @@ public VectorScorer getScorer(LeafReaderContext ctx) throws IOException {
 
       @Override
       public float score() throws IOException {
-        return vectorSimilarityFunction.compare(queryVector, vectorValues.vectorValue(iterator.index()));
+        return vectorSimilarityFunction.compare(
+            queryVector, vectorValues.vectorValue(iterator.index()));
       }
 
       @Override

lucene/core/src/test/org/apache/lucene/search/TestQuantizedVectorSimilarityValueSource.java

@@ -1,5 +1,7 @@
 package org.apache.lucene.search;
 
+import java.util.ArrayList;
+import java.util.List;
 import org.apache.lucene.codecs.Codec;
 import org.apache.lucene.codecs.KnnVectorsFormat;
 import org.apache.lucene.codecs.lucene99.Lucene99HnswScalarQuantizedVectorsFormat;
@@ -21,9 +23,6 @@
 import org.junit.Before;
 import org.junit.Test;
 
-import java.util.ArrayList;
-import java.util.List;
-
 public class TestQuantizedVectorSimilarityValueSource extends LuceneTestCase {
 
   private Codec savedCodec;
@@ -77,13 +76,17 @@ public void testFullPrecisionVectorSimilarityDVS() throws Exception {
     int numVectors = atLeast(NUM_VECTORS);
     int numSegments = random().nextInt(2, 10);
     final VectorSimilarityFunction vectorSimilarityFunction =
-        VectorSimilarityFunction.values()[random().nextInt(VectorSimilarityFunction.values().length)];
+        VectorSimilarityFunction.values()[
+            random().nextInt(VectorSimilarityFunction.values().length)];
 
     try (Directory dir = newDirectory()) {
       int id = 0;
 
       // index some 4 bit quantized vectors
-      try (IndexWriter w = new IndexWriter(dir, newIndexWriterConfig().setCodec(TestUtil.alwaysKnnVectorsFormat(getKnnFormat(4))))) {
+      try (IndexWriter w =
+          new IndexWriter(
+              dir,
+              newIndexWriterConfig().setCodec(TestUtil.alwaysKnnVectorsFormat(getKnnFormat(4))))) {
         for (int j = 0; j < numSegments; j++) {
           for (int i = 0; i < numVectors; i++) {
             Document doc = new Document();
@@ -111,7 +114,10 @@ public void testFullPrecisionVectorSimilarityDVS() throws Exception {
       }
 
       // index some 7 bit quantized vectors
-      try (IndexWriter w = new IndexWriter(dir, newIndexWriterConfig().setCodec(TestUtil.alwaysKnnVectorsFormat(getKnnFormat(7))))) {
+      try (IndexWriter w =
+          new IndexWriter(
+              dir,
+              newIndexWriterConfig().setCodec(TestUtil.alwaysKnnVectorsFormat(getKnnFormat(7))))) {
         for (int j = 0; j < numSegments; j++) {
           for (int i = 0; i < numVectors; i++) {
             Document doc = new Document();
@@ -139,12 +145,14 @@ public void testFullPrecisionVectorSimilarityDVS() throws Exception {
       }
 
       float[] queryVector = TestVectorUtil.randomVector(VECTOR_DIMENSION);
-      FloatVectorSimilarityValuesSource fpSimValueSource = new FloatVectorSimilarityValuesSource(queryVector, KNN_FIELD, true);
-      FloatVectorSimilarityValuesSource quantizedSimValueSource = new FloatVectorSimilarityValuesSource(queryVector, KNN_FIELD);
+      FloatVectorSimilarityValuesSource fpSimValueSource =
+          new FloatVectorSimilarityValuesSource(queryVector, KNN_FIELD, true);
+      FloatVectorSimilarityValuesSource quantizedSimValueSource =
+          new FloatVectorSimilarityValuesSource(queryVector, KNN_FIELD);
 
       try (IndexReader reader = DirectoryReader.open(dir)) {
         FieldExistsQuery query = new FieldExistsQuery(KNN_FIELD);
-        for (LeafReaderContext ctx: reader.leaves()) {
+        for (LeafReaderContext ctx : reader.leaves()) {
           DoubleValues fpSimValues = fpSimValueSource.getValues(ctx, null);
           DoubleValues quantizedSimValues = quantizedSimValueSource.getValues(ctx, null);
           // validate when segment has no vectors
@@ -154,7 +162,8 @@ public void testFullPrecisionVectorSimilarityDVS() throws Exception {
             continue;
           }
           StoredFields storedFields = ctx.reader().storedFields();
-          VectorScorer quantizedScorer = ctx.reader().getFloatVectorValues(KNN_FIELD).scorer(queryVector);
+          VectorScorer quantizedScorer =
+              ctx.reader().getFloatVectorValues(KNN_FIELD).scorer(queryVector);
           DocIdSetIterator disi = quantizedScorer.iterator();
           while (disi.nextDoc() != DocIdSetIterator.NO_MORE_DOCS) {
             int doc = disi.docID();