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Implement MagnitudeVector and add corresponding test cases #781

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5b5182e
feat(vector): implement MagnitudeVector and add test cases
SYaoJun Mar 22, 2026
7b4142b
remove reduandant code in match
SYaoJun Mar 22, 2026
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60 changes: 58 additions & 2 deletions geaflow-ai/src/main/java/org/apache/geaflow/ai/index/vector/MagnitudeVector.java
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Original file line number Diff line number Diff line change
Expand Up @@ -19,20 +19,76 @@

package org.apache.geaflow.ai.index.vector;

import java.util.Objects;

public class MagnitudeVector implements IVector {

private final double magnitude;

public MagnitudeVector() {
this.magnitude = 0.0;
}

public MagnitudeVector(double magnitude) {
this.magnitude = magnitude;
}

public double getMagnitude() {
return magnitude;
}

@Override
public double match(IVector other) {
return 0;
if (!(other instanceof MagnitudeVector)) {

@kitalkuyo-gita kitalkuyo-gita Jul 29, 2026

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Code snippet: if (!(other instanceof MagnitudeVector)) { throw new IllegalArgumentException("Other vector must be a MagnitudeVector"); }

Problem: This can cause runtime exceptions when calling match without explicitly performing type checking when combining multiple IVectors (EmbeddingVector, KeywordVector, TraversalVector, etc.) in VectorSearch, potentially interrupting the search process.

Recommendation: For IVectors of different types, it's advisable to return 0.0 (indicating dissimilarity/not included in the scoring), or have a more explicit contract defined by the IVector interface (e.g., match supports different types and returns 0). Returning 0 is more robust and consistent with the design comment in paste ("if not same type return 0.0").

throw new IllegalArgumentException("Other vector must be a MagnitudeVector");
}

MagnitudeVector otherVec = (MagnitudeVector) other;
double otherMagnitude = otherVec.magnitude;

return computeSimilarity(otherMagnitude);

}

private double computeSimilarity(double otherMagnitude) {
if (this.magnitude == 0.0 && otherMagnitude == 0.0) {

@kitalkuyo-gita kitalkuyo-gita Jul 29, 2026

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In the code, "magnitude" typically refers to metrics such as degree or PageRank—values ​​that are generally non-negative (≥0)—though certain centrality measures (e.g., specific eigenvector-based or normalized metrics) can be negative. The current implementation handles this using Math.abs, ensuring the calculation proceeds; however, it is advisable to either explicitly define the valid range (≥0) in the class documentation or formally document the meaning of negative values ​​if they are permitted.

Recommendation: Add Javadoc to the constructor specifying the expected range, or implement validation within the constructor (throwing an IllegalArgumentException if only non-negative values ​​are allowed).

return 1.0;
}

double diff = Math.abs(this.magnitude - otherMagnitude);
double max = Math.max(Math.abs(this.magnitude), Math.abs(otherMagnitude));

if (max == 0.0) {
return 1.0;
}

return 1.0 - (diff / max);
}

@Override
public VectorType getType() {
return VectorType.MagnitudeVector;
}

@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
MagnitudeVector that = (MagnitudeVector) o;
return Double.compare(that.magnitude, magnitude) == 0;
}

@Override
public int hashCode() {
return Objects.hash(magnitude);
}

@Override
public String toString() {
return "MagnitudeVector{}";
return "MagnitudeVector{magnitude=" + magnitude + '}';
}
}
54 changes: 54 additions & 0 deletions geaflow-ai/src/test/java/org/apache/geaflow/ai/GraphMemoryTest.java
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Expand Up @@ -27,9 +27,11 @@
import org.apache.geaflow.ai.index.EntityAttributeIndexStore;
import org.apache.geaflow.ai.index.IndexStore;
import org.apache.geaflow.ai.index.vector.EmbeddingVector;
import org.apache.geaflow.ai.index.vector.IVector;
import org.apache.geaflow.ai.index.vector.KeywordVector;
import org.apache.geaflow.ai.index.vector.MagnitudeVector;
import org.apache.geaflow.ai.index.vector.TraversalVector;
import org.apache.geaflow.ai.index.vector.VectorType;
import org.apache.geaflow.ai.search.VectorSearch;
import org.apache.geaflow.ai.verbalization.Context;
import org.apache.geaflow.ai.verbalization.SubgraphSemanticPromptFunction;
Expand All @@ -38,6 +40,9 @@
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertNotEquals;

public class GraphMemoryTest {

private static final Logger LOGGER = LoggerFactory.getLogger(GraphMemoryTest.class);
Expand All @@ -52,6 +57,55 @@ public void testVectorSearch() {
LOGGER.info(String.valueOf(search));
}

// ========== MagnitudeVector Tests ==========

@Test
public void testMagnitudeVectorConstructorAndGetter() {
MagnitudeVector vector = new MagnitudeVector(0.85);
assertEquals(vector.getMagnitude(), 0.85, 0.0001);
}

@Test
public void testMagnitudeVectorMatchExactSameValue() {
MagnitudeVector v1 = new MagnitudeVector(5.0);
MagnitudeVector v2 = new MagnitudeVector(5.0);

assertEquals(v1.match(v2), 1.0, 0.0001);
}

@Test
public void testMagnitudeVectorMatchDifferentValues() {
MagnitudeVector v1 = new MagnitudeVector(10.0);
MagnitudeVector v2 = new MagnitudeVector(5.0);

// Expected: 1 - |10-5|/max(10,5) = 1 - 5/10 = 0.5
assertEquals(v1.match(v2), 0.5, 0.0001);
}
@Test
public void testMagnitudeVectorEqualsAndHashCode() {
MagnitudeVector v1 = new MagnitudeVector(5.0);
MagnitudeVector v2 = new MagnitudeVector(5.0);
MagnitudeVector v3 = new MagnitudeVector(10.0);

assertEquals(v1, v2);
assertEquals(v1.hashCode(), v2.hashCode());
assertNotEquals(v1, v3);
}

@Test
public void testMagnitudeVectorToString() {
MagnitudeVector vector = new MagnitudeVector(0.75);
String str = vector.toString();

assertEquals(str, "MagnitudeVector{magnitude=0.75}");
}

@Test
public void testMagnitudeVectorGetType() {
MagnitudeVector vector = new MagnitudeVector(1.0);
assertEquals(vector.getType(), VectorType.MagnitudeVector);
}

@Test
public void testEmptyMainPipeline() {
GraphMemoryServer server = new GraphMemoryServer();
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