diff --git a/.gitignore b/.gitignore
index 43f7525..6c4f40c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,11 +6,10 @@ build.xml
 nbbuild.xml
 manifest.mf
 nbproject/
-test/
+/test/
 src/PublicationClustering.java
 /dist/
 test_network.ser
-test*
 *.txt
 bin/
 .classpath
diff --git a/src/test/java/nl/cwts/networkanalysis/TestNetworkLayout.java b/src/test/java/nl/cwts/networkanalysis/TestNetworkLayout.java
new file mode 100644
index 0000000..9bf6a15
--- /dev/null
+++ b/src/test/java/nl/cwts/networkanalysis/TestNetworkLayout.java
@@ -0,0 +1,64 @@
+package nl.cwts.networkanalysis;
+
+import static org.junit.jupiter.api.Assertions.assertArrayEquals;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import java.util.Random;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+
+import nl.cwts.util.LargeDoubleArray;
+import nl.cwts.util.LargeIntArray;
+
+public class TestNetworkLayout
+{
+    Network testNetwork;
+
+    @BeforeEach
+    public void setUp()
+    {
+        int[][] edges = { { 0, 0, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6, 6, 7 }, { 1, 9, 4, 6, 9, 5, 7, 8, 9, 4, 5, 7, 8, 9, 5, 6, 8, 9, 6, 7, 8, 7, 9, 8 } };
+        double[] edgeWeights = { 16, 90, 1, 1, 82, 2, 13, 72, 5, 13, 1, 2, 2, 2, 5, 15, 4, 2, 139, 6, 7, 4, 1, 15 };
+        LargeIntArray[] edges2 = new LargeIntArray[2];
+        edges2[0] = new LargeIntArray(edges[0]);
+        edges2[1] = new LargeIntArray(edges[1]);
+        LargeDoubleArray edgeWeights2 = new LargeDoubleArray(edgeWeights);
+        testNetwork = new Network(10, true, edges2, edgeWeights2, false, true);
+    }
+
+    @Test
+    public void testTotalEdgeWeightAfterNormalization()
+    {
+        Network normalizedNetworkNoNormalization = testNetwork.createNetworkWithoutNodeWeights();
+        assertEquals(500, testNetwork.getTotalEdgeWeight(), 1e-10);
+        assertEquals(500, normalizedNetworkNoNormalization.getTotalEdgeWeight(), 1e-10);
+
+        Network normalizedNetworkAssociationStrength = testNetwork.createNormalizedNetworkUsingAssociationStrength();
+        assertEquals(500, testNetwork.getTotalEdgeWeight(), 1e-10);
+        assertEquals(500, normalizedNetworkNoNormalization.getTotalEdgeWeight(), 1e-10);
+        assertEquals(59.01145827229578, normalizedNetworkAssociationStrength.getTotalEdgeWeight(), 1e-10);
+
+        Network normalizedNetworkFractionalization = testNetwork.createNormalizedNetworkUsingFractionalization();
+        assertEquals(500, testNetwork.getTotalEdgeWeight(), 1e-10);
+        assertEquals(500, normalizedNetworkNoNormalization.getTotalEdgeWeight(), 1e-10);
+        assertEquals(59.01145827229578, normalizedNetworkAssociationStrength.getTotalEdgeWeight(), 1e-10);
+        assertEquals(50, normalizedNetworkFractionalization.getTotalEdgeWeight(), 1e-10);
+    }
+
+    @Test
+    public void testGradientDescentVOSLayoutAlgorithm()
+    {
+        int attraction = 2;
+        int repulsion = -2;
+        GradientDescentVOSLayoutAlgorithm algorithm = new GradientDescentVOSLayoutAlgorithm(attraction, repulsion, 0, new Random(0));
+        testNetwork = testNetwork.createNormalizedNetworkUsingAssociationStrength();
+        Layout layout = algorithm.findLayout(testNetwork);
+        layout.standardize(true);
+
+        Layout expectedLayout = new Layout(new double[][] { { 1.136341835, 0.879152105, -0.512331857, -0.032236745, -0.146102352, -0.528511035, -0.754004637, -0.542296378, -0.22047403, 0.720463094 }, { -0.149931232, 0.318787053, -0.661664094, 0.007739771, 0.280012379, 0.612571137, 0.328330118, -0.205903696, -0.460960297, -0.068981139 } });
+        for (int i = 0; i < testNetwork.getNNodes(); i++)
+            assertArrayEquals(expectedLayout.getCoordinates(i), layout.getCoordinates(i), 1e-8);
+        assertEquals(55.06823414047805, algorithm.calcQuality(testNetwork, layout), 1e-10);
+    }
+}