@Test
public void testLinearThresholdKtree() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting LT test on KTree \n");
KTree<DiffusionEdge> KT8 = new KTree(8, "DiffusionEdge");
for (int i = 0; i < 92; i++) {
KT8.addRandomVertex();
}
DiffusionMechanism diffuse = new DiffusionMechanism();
diffuse.setThreshold(0.0);
System.out.println("Setting Threshold to 0%\n");
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = KT8.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.LinearThreshold(KT8, seed);
System.out.println(rst.getStats());
assertEquals(KT8.getVertexCount(), rst.getInfectionSize());
diffuse.setThreshold(1.0);
System.out.println("Setting Threshold to 100%\n");
rst = diffuse.LinearThreshold(KT8, seed);
System.out.println(rst.getStats());
assertEquals(3, rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testLinearThresholdER() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting LT test on Ephemeral Erdos-Renyi Graph\n");
ERModel<TimeStampEdge> ER100 = new ERModel<>(0.75, 100, "TimeStampEdge");
EphemeralDiffusion diffuse = new EphemeralDiffusion();
System.out.println(
"Setting timestamp parameters to N = 10 with a bound of 10\n"
+ "Equivalent to IC on normal graph with at most 10 infection periods\n");
diffuse.setTimestampParams(10, 10);
diffuse.setThreshold(0);
System.out.println("Setting threshold to 0%\n");
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = ER100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.LinearThreshold(ER100, seed);
System.out.println(rst.getStats());
assertEquals(ER100.getVertexCount(), rst.getInfectionSize());
diffuse.setThreshold(1.0);
System.out.println("Setting infection probability to 100%\n");
rst = diffuse.LinearThreshold(ER100, seed);
System.out.println(rst.getStats());
assertEquals(3, rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testLinearThresholdBA() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting LT test on Barabosi-Albert Graph\n");
Barabasi_AlbertModel<DiffusionEdge> BA100 = new Barabasi_AlbertModel<>(3, 2, "DiffusionEdge");
for (int i = 0; i < 97; i++) {
BA100.addRandomNode();
}
DiffusionMechanism diffuse = new DiffusionMechanism();
diffuse.setThreshold(0.0);
System.out.println("Setting Threshold to 0%\n");
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = BA100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.LinearThreshold(BA100, seed);
System.out.println(rst.getStats());
assertEquals(BA100.getVertexCount(), rst.getInfectionSize());
diffuse.setThreshold(1.0);
System.out.println("Setting Threshold to 100%\n");
rst = diffuse.LinearThreshold(BA100, seed);
System.out.println(rst.getStats());
assertEquals(seed.size(), rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testLinearThresholdER() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting LT test on Erdos-Renyi Graph\n");
ERModel<DiffusionEdge> ER100 = new ERModel<>(1.0, 100, "DiffusionEdge");
DiffusionMechanism diffuse = new DiffusionMechanism();
diffuse.setThreshold(0.0);
System.out.println("setting Threshold to 0%\n");
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = ER100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.LinearThreshold(ER100, seed);
System.out.println(rst.getStats());
assertEquals(ER100.getVertexCount(), rst.getInfectionSize());
System.out.println("setting Threshold to 100%\n");
diffuse.setThreshold(1.0);
rst = diffuse.LinearThreshold(ER100, seed);
System.out.println(rst.getStats());
assertEquals(3, rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testInitialCascadeER() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting IC test on Erdos-Renyi Graph\n");
ERModel<DiffusionEdge> ER100 = new ERModel<>(0.75, 100, "DiffusionEdge");
DiffusionMechanism diffuse = new DiffusionMechanism();
diffuse.setInfectProb(1.0);
System.out.println("Setting infection probability to 100%\n");
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = ER100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.InitialCascade(ER100, seed);
System.out.println(rst.getStats());
assertEquals(ER100.getVertexCount(), rst.getInfectionSize());
diffuse.setInfectProb(0.0);
System.out.println("Setting infection probability to 0%\n");
rst = diffuse.InitialCascade(ER100, seed);
System.out.println(rst.getStats());
assertEquals(3, rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testPushPullBA() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting PP test on ephemeral Barabosi-Albert Graph\n");
Barabasi_AlbertModel<TimeStampEdge> BA100 = new Barabasi_AlbertModel<>(3, 2, "TimeStampEdge");
for (int i = 0; i < 97; i++) {
BA100.addRandomNode();
}
EphemeralDiffusion diffuse = new EphemeralDiffusion();
System.out.println(
"Setting timestamp parameters to N = 10 with a bound of 10\n"
+ "Equivalent to IC on normal graph with at most 10 infection periods\n");
diffuse.setTimestampParams(10, 10);
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = BA100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.PushPull(BA100, seed);
System.out.println(rst.getStats());
assertEquals(BA100.getVertexCount(), rst.getInfectionSize());
}
@Test
public void testPushPullKtree() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting PP test on Ephemeral KTree\n");
KTree<TimeStampEdge> KT8 = new KTree(8, "TimeStampEdge");
for (int i = 0; i < 100; i++) {
KT8.addRandomVertex();
}
EphemeralDiffusion diffuse = new EphemeralDiffusion();
System.out.println(
"Setting timestamp parameters to N = 10 with a bound of 10\n"
+ "Equivalent to IC on normal graph with at most 10 infection periods\n");
diffuse.setTimestampParams(10, 10);
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = KT8.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.PushPull(KT8, seed);
System.out.println(rst.getStats());
assertEquals(KT8.getVertexCount(), rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testPushPullKtree() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting PP test on KTree\n");
KTree<DiffusionEdge> KT8 = new KTree(8, "DiffusionEdge");
for (int i = 0; i < 100; i++) {
KT8.addRandomVertex();
}
DiffusionMechanism diffuse = new DiffusionMechanism();
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = KT8.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.PushPull(KT8, seed);
System.out.println(rst.getStats());
assertEquals(KT8.getVertexCount(), rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testTimeRespectinDiffusionBA() throws Exception {
System.out.println("-------------------------------------------");
System.out.println(
"Starting Time Respecting Diffusion test on ephemeral Barabosi-Albert Graph\n");
Barabasi_AlbertModel<TimeStampEdge> BA100 = new Barabasi_AlbertModel<>(3, 2, "TimeStampEdge");
for (int i = 0; i < 97; i++) {
BA100.addRandomNode();
}
EphemeralDiffusion diffuse = new EphemeralDiffusion();
System.out.println("Setting timestamp parameters to N = 10 with a bound of 10\n");
diffuse.setTimestampParams(10, 10);
diffuse.setInfectProb(1.0);
System.out.println("Setting infection probability to 100%\n");
System.out.println("Setting the lifespan of an infection to 10");
diffuse.setInfectionLifeTime(10);
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = BA100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.TimeRespectingCascade(BA100, seed);
System.out.println(rst.getStats());
assertEquals(BA100.getVertexCount(), rst.getInfectionSize());
diffuse.setInfectionLifeTime(2);
diffuse.setInfectProb(0.5);
System.out.println("Setting prob to 20% with lifetime of 2\n");
rst = diffuse.TimeRespectingCascade(BA100, seed);
System.out.println(rst.getStats());
assertTrue(
(seed.size() < rst.getInfectionSize()) && rst.getInfectionSize() < BA100.getVertexCount());
System.out.println("Test Complete");
}
@Test
public void testTimeRespectingDiffusionER() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting Time Respecting Diffusion test on ephemeral Erdos-Renyi graph \n");
ERModel<TimeStampEdge> ER8 = new ERModel<>(0.75, 8, "TimeStampEdge");
for (int i = 0; i < 92; i++) {
ER8.addRandomNode();
}
EphemeralDiffusion diffuse = new EphemeralDiffusion();
diffuse.setInfectProb(1.0);
System.out.println("Setting infection probability to 100%\n");
System.out.println("Setting timestamp parameters to N = 10 with a bound of 10\n");
diffuse.setTimestampParams(10, 10);
System.out.println("Setting the lifespan of an infection to 10");
diffuse.setInfectionLifeTime(10);
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = ER8.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.TimeRespectingCascade(ER8, seed);
System.out.println(rst.getStats());
assertEquals(ER8.getVertexCount(), rst.getInfectionSize());
diffuse.setInfectProb(0.0);
System.out.println("Setting infection probability to 0%\n");
rst = diffuse.TimeRespectingCascade(ER8, seed);
System.out.println(rst.getStats());
assertEquals(3, rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testPushPullER() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting PP test on Erdos-Renyi Graph\n");
ERModel<DiffusionEdge> ER100 = new ERModel<>(0.75, 100, "DiffusionEdge");
DiffusionMechanism diffuse = new DiffusionMechanism();
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = ER100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.PushPull(ER100, seed);
System.out.println(rst.getStats());
assertEquals(ER100.getVertexCount(), rst.getInfectionSize());
System.out.println("Test Complete");
}
@Test
public void testPushPullBA() throws Exception {
System.out.println("-------------------------------------------");
System.out.println("Starting PP test on Barabosi-Albert Graph\n");
Barabasi_AlbertModel<DiffusionEdge> BA100 = new Barabasi_AlbertModel<>(3, 2, "DiffusionEdge");
for (int i = 0; i < 97; i++) {
BA100.addRandomNode();
}
DiffusionMechanism diffuse = new DiffusionMechanism();
ArrayList<DiffusionVertex> seed = new ArrayList<>();
Iterator<DiffusionVertex> iter = BA100.getVertices().iterator();
for (int i = 0; i < 3; i++) {
seed.add(iter.next());
}
ResultSet rst = diffuse.PushPull(BA100, seed);
System.out.println(rst.getStats());
assertEquals(BA100.getVertexCount(), rst.getInfectionSize());
}