From a5bb2a3f63c4800bccbb0ca006e9600e061a4d99 Mon Sep 17 00:00:00 2001
From: Simon Ding <me@simonding.de>
Date: Thu, 24 Feb 2022 11:31:14 +0100
Subject: [PATCH] Test for clustering result

---
 .../clustering/ClusteringResultTest.java      | 58 +++++++++++++++++++
 1 file changed, 58 insertions(+)
 create mode 100644 jplag/src/test/java/de/jplag/clustering/ClusteringResultTest.java

diff --git a/jplag/src/test/java/de/jplag/clustering/ClusteringResultTest.java b/jplag/src/test/java/de/jplag/clustering/ClusteringResultTest.java
new file mode 100644
index 0000000000..7a6a5e7285
--- /dev/null
+++ b/jplag/src/test/java/de/jplag/clustering/ClusteringResultTest.java
@@ -0,0 +1,58 @@
+package de.jplag.clustering;
+
+import static org.junit.Assert.assertEquals;
+
+import java.util.List;
+
+import org.apache.commons.math3.linear.Array2DRowRealMatrix;
+import org.apache.commons.math3.linear.RealMatrix;
+import org.junit.Test;
+
+public class ClusteringResultTest {
+
+    @Test
+    public void perfectClustering() {
+        RealMatrix similarity = new Array2DRowRealMatrix(4, 4);
+
+        // These are similar
+        setEntries(similarity, 0, 1, 1f);
+        setEntries(similarity, 2, 3, 1f);
+
+        // Others are dissimilar
+
+        ClusteringResult<Integer> result = ClusteringResult
+                .fromIntegerCollections(List.of(List.of(0, 1), List.of(2, 3)), similarity);
+
+        // The maximum of the metric is 1 - 1/k for k clusters
+        assertEquals(0.5, result.getCommunityStrength(), 0.00001);
+    }
+
+    @Test
+    public void uniformClustering() {
+        RealMatrix similarity = new Array2DRowRealMatrix(4, 4);
+
+        // We'd obtain such weights by pre-selecting the clusters,
+        // then randomly picking two clusters and adding weight between random of each
+        // cluster
+
+        // These are similar
+        setEntries(similarity, 0, 1, 0.1f);
+        setEntries(similarity, 2, 3, 0.1f);
+
+        // Others are dissimilar
+        setEntries(similarity, 0, 2, 0.05f);
+        setEntries(similarity, 0, 3, 0.05f);
+        setEntries(similarity, 1, 2, 0.05f);
+        setEntries(similarity, 1, 3, 0.05f);
+
+        ClusteringResult<Integer> result = ClusteringResult
+                .fromIntegerCollections(List.of(List.of(0, 1), List.of(2, 3)), similarity);
+
+        assertEquals(0.0, result.getCommunityStrength(), 0.00001);
+    }
+
+    private static void setEntries(RealMatrix matrix, int i, int j, double value) {
+        matrix.setEntry(i, j, value);
+        matrix.setEntry(j, i, value);
+    }
+}