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authorArne Juul <arnej@yahooinc.com>2023-06-26 06:31:44 +0000
committerArne Juul <arnej@yahooinc.com>2023-06-26 08:37:46 +0000
commit643a09268b71ea0ebf128552874f1a3ee15aca2e (patch)
tree0d224c2130b9f9c213152c4fe0a2a00ecf625b1d /vespajlib/src/test
parentf374e7d08c7e492130956c757ebdbd6cccdda74f (diff)
add euclidean_distance
Diffstat (limited to 'vespajlib/src/test')
-rw-r--r--vespajlib/src/test/java/com/yahoo/tensor/functions/EuclideanDistanceTestCase.java43
1 files changed, 43 insertions, 0 deletions
diff --git a/vespajlib/src/test/java/com/yahoo/tensor/functions/EuclideanDistanceTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/functions/EuclideanDistanceTestCase.java
new file mode 100644
index 00000000000..9d06c313ecc
--- /dev/null
+++ b/vespajlib/src/test/java/com/yahoo/tensor/functions/EuclideanDistanceTestCase.java
@@ -0,0 +1,43 @@
+// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+package com.yahoo.tensor.functions;
+
+import com.yahoo.tensor.Tensor;
+import com.yahoo.tensor.TensorType;
+import org.junit.Test;
+
+import java.util.List;
+
+import static org.junit.Assert.assertEquals;
+
+/**
+ * @author arnej
+ */
+public class EuclideanDistanceTestCase {
+
+ @Test
+ public void testVectorDistances() {
+ var a = Tensor.from("tensor(x[3]):[1.0, 2.0, 3.0]");
+ var b = Tensor.from("tensor(x[3]):[4.0, 2.0, 7.0]");
+ var c = Tensor.from("tensor(x[3]):[1.0, 6.0, 6.0]");
+ var op = new EuclideanDistance<>(new ConstantTensor<>(a), new ConstantTensor<>(b), "x");
+ Tensor result = op.evaluate();
+ assertEquals(5.0, result.asDouble(), 0.000001);
+ op = new EuclideanDistance<>(new ConstantTensor<>(b), new ConstantTensor<>(a), "x");
+ result = op.evaluate();
+ assertEquals(5.0, result.asDouble(), 0.000001);
+ op = new EuclideanDistance<>(new ConstantTensor<>(c), new ConstantTensor<>(a), "x");
+ result = op.evaluate();
+ assertEquals(5.0, result.asDouble(), 0.000001);
+ }
+
+ @Test
+ public void testDistancesInMixed() {
+ var a = Tensor.from("tensor(c{},x[3]):{foo:[1.0, 2.0, 3.0],bar:[0.0, 0.0, 0.0]}");
+ var b = Tensor.from("tensor(c{},x[3]):{foo:[4.0, 2.0, 7.0],bar:[12.0, 0.0, 5.0]}");
+ var op = new EuclideanDistance<>(new ConstantTensor<>(a), new ConstantTensor<>(b), "x");
+ Tensor result = op.evaluate();
+ var expect = Tensor.from("tensor(c{}):{foo:5.0,bar:13.0}");
+ assertEquals(expect, result);
+ }
+
+}