- * A multi-vector is a collection of multiple vectors that represent a single document or query. - * MultiVectorSimilarityFunction is used to determine nearest neighbors during - * indexing and search on multi-vectors. + * + *
A multi-vector is a collection of multiple vectors that represent a single document or query. + * MultiVectorSimilarityFunction is used to determine nearest neighbors during indexing and search + * on multi-vectors. */ public class MultiVectorSimilarityFunction { @@ -33,9 +33,8 @@ public class MultiVectorSimilarityFunction { public enum Aggregation { /** - * Sum_Max Similarity between two multi-vectors. Computes the sum of maximum similarity - * found for each vector in the first multi-vector against all vectors in the second - * multi-vector. + * Sum_Max Similarity between two multi-vectors. Computes the sum of maximum similarity found + * for each vector in the first multi-vector against all vectors in the second multi-vector. */ SUM_MAX { @Override @@ -103,8 +102,8 @@ public class MultiVectorSimilarityFunction { /** * Computes and aggregates similarity over multiple vector values. - *
- * Assumes all vector values in both provided multi-vectors have the same dimension. Slices + * + *
Assumes all vector values in both provided multi-vectors have the same dimension. Slices * inner and outer float[] multi-vectors into dimension sized vector values for comparison. * * @param outer first multi-vector @@ -121,8 +120,8 @@ public class MultiVectorSimilarityFunction { /** * Computes and aggregates similarity over multiple vector values. - *
- * Assumes all vector values in both provided multi-vectors have the same dimension. Slices + * + *
Assumes all vector values in both provided multi-vectors have the same dimension. Slices * inner and outer byte[] multi-vectors into dimension sized vector values for comparison. * * @param outer first multi-vector diff --git a/lucene/core/src/test/org/apache/lucene/index/TestMultiVectorSimilarityFunction.java b/lucene/core/src/test/org/apache/lucene/index/TestMultiVectorSimilarityFunction.java index f92ba505e92..a4d0fcfdd3d 100644 --- a/lucene/core/src/test/org/apache/lucene/index/TestMultiVectorSimilarityFunction.java +++ b/lucene/core/src/test/org/apache/lucene/index/TestMultiVectorSimilarityFunction.java @@ -11,46 +11,60 @@ public class TestMultiVectorSimilarityFunction extends LuceneTestCase { final int dimension = 3; final VectorSimilarityFunction vectorSim = VectorSimilarityFunction.DOT_PRODUCT; - float[][] a = new float[][] { - VectorUtil.l2normalize(new float[]{1.f, 4.f, -3.f}), - VectorUtil.l2normalize(new float[]{8.f, 3.f, -7.f}) - }; - float[][] b = new float[][] { - VectorUtil.l2normalize(new float[]{-5.f, 2.f, 4.f}), - VectorUtil.l2normalize(new float[]{7.f, 1.f, -3.f}), - VectorUtil.l2normalize(new float[]{-5.f, 8.f, 3.f}) - }; - + float[][] a = + new float[][] { + VectorUtil.l2normalize(new float[] {1.f, 4.f, -3.f}), + VectorUtil.l2normalize(new float[] {8.f, 3.f, -7.f}) + }; + float[][] b = + new float[][] { + VectorUtil.l2normalize(new float[] {-5.f, 2.f, 4.f}), + VectorUtil.l2normalize(new float[] {7.f, 1.f, -3.f}), + VectorUtil.l2normalize(new float[] {-5.f, 8.f, 3.f}) + }; float result = 0f; - float[] a0_bDot = new float[] {vectorSim.compare(a[0], b[0]), vectorSim.compare(a[0], b[1]), vectorSim.compare(a[0], b[2])}; + float[] a0_bDot = + new float[] { + vectorSim.compare(a[0], b[0]), + vectorSim.compare(a[0], b[1]), + vectorSim.compare(a[0], b[2]) + }; float max = Float.MIN_VALUE; - for (float k: a0_bDot) { + for (float k : a0_bDot) { max = Float.max(max, k); } result += max; - float[] a1_bDot = new float[] {vectorSim.compare(a[1], b[0]), vectorSim.compare(a[1], b[1]), vectorSim.compare(a[1], b[2])}; + float[] a1_bDot = + new float[] { + vectorSim.compare(a[1], b[0]), + vectorSim.compare(a[1], b[1]), + vectorSim.compare(a[1], b[2]) + }; max = Float.MIN_VALUE; - for (float k: a1_bDot) { + for (float k : a1_bDot) { max = Float.max(max, k); } result += max; float[] a_Packed = new float[a.length * dimension]; int i = 0; - for (float[] v: a) { + for (float[] v : a) { System.arraycopy(v, 0, a_Packed, i, dimension); i += dimension; } float[] b_Packed = new float[b.length * dimension]; i = 0; - for (float[] v: b) { + for (float[] v : b) { System.arraycopy(v, 0, b_Packed, i, dimension); i += dimension; } - MultiVectorSimilarityFunction mvSim = new MultiVectorSimilarityFunction(VectorSimilarityFunction.DOT_PRODUCT, MultiVectorSimilarityFunction.Aggregation.SUM_MAX); + MultiVectorSimilarityFunction mvSim = + new MultiVectorSimilarityFunction( + VectorSimilarityFunction.DOT_PRODUCT, + MultiVectorSimilarityFunction.Aggregation.SUM_MAX); float score = mvSim.compare(a_Packed, b_Packed, dimension); assertEquals(result, score, 0.0001f); } @@ -59,7 +73,10 @@ public class TestMultiVectorSimilarityFunction extends LuceneTestCase { public void testDimensionCheck() { float[] a = {1f, 2f, 3f, 4f, 5f, 6f}; float[] b = {1f, 2f, 3f, 4f, 5f, 6f, 7f, 8f, 9f}; - MultiVectorSimilarityFunction mvSim = new MultiVectorSimilarityFunction(VectorSimilarityFunction.DOT_PRODUCT, MultiVectorSimilarityFunction.Aggregation.SUM_MAX); + MultiVectorSimilarityFunction mvSim = + new MultiVectorSimilarityFunction( + VectorSimilarityFunction.DOT_PRODUCT, + MultiVectorSimilarityFunction.Aggregation.SUM_MAX); assertThrows(IllegalArgumentException.class, () -> mvSim.compare(a, b, 2)); } }