/**
* Testing the mapper is fairly straightforward: there are two matrices to be processed
* simultaneously (cut matrix of sensitivities, and the affinity matrix), and since both are
* symmetric, two entries from each will be grouped together with the same key (or, in the case of
* an entry along the diagonal, only two entries).
*
* <p>The correct grouping of these quad or pair vertices is the only output of the mapper.
*
* @throws Exception
*/
@Test
public void testEigencutsAffinityCutsMapper() throws Exception {
EigencutsAffinityCutsMapper mapper = new EigencutsAffinityCutsMapper();
Configuration conf = new Configuration();
conf.setInt(EigencutsKeys.AFFINITY_DIMENSIONS, this.affinity.length);
// set up the writer
DummyRecordWriter<Text, VertexWritable> writer = new DummyRecordWriter<Text, VertexWritable>();
Mapper<IntWritable, VectorWritable, Text, VertexWritable>.Context context =
DummyRecordWriter.build(mapper, conf, writer);
// perform the maps
for (int i = 0; i < this.affinity.length; i++) {
VectorWritable aff = new VectorWritable(new DenseVector(this.affinity[i]));
VectorWritable sens = new VectorWritable(new DenseVector(this.sensitivity[i]));
IntWritable key = new IntWritable(i);
mapper.map(key, aff, context);
mapper.map(key, sens, context);
}
// were the vertices constructed correctly? if so, then for two 4x4
// matrices, there should be 10 unique keys with 56 total entries
assertEquals("Number of keys", 10, writer.getKeys().size());
for (int i = 0; i < this.affinity.length; i++) {
for (int j = 0; j < this.affinity.length; j++) {
Text key = new Text(Math.max(i, j) + "_" + Math.min(i, j));
List<VertexWritable> values = writer.getValue(key);
// if we're on a diagonal, there should only be 2 entries
// otherwise, there should be 4
if (i == j) {
assertEquals("Diagonal entry", 2, values.size());
for (VertexWritable v : values) {
assertFalse("Diagonal values are zero", v.getValue() > 0);
}
} else {
assertEquals("Off-diagonal entry", 4, values.size());
if (i + j == 3) { // all have values greater than 0
for (VertexWritable v : values) {
assertTrue("Off-diagonal non-zero entries", v.getValue() > 0);
}
}
}
}
}
}
/**
* This is by far the trickiest step. However, an easy condition is if we have only two vertices -
* indicating vertices on the diagonal of the two matrices - then we simply exit (since the
* algorithm does not operate on the diagonal; it makes no sense to perform cuts by isolating data
* points from themselves).
*
* <p>If there are four points, then first we must separate the two which belong to the affinity
* matrix from the two that are sensitivities. In theory, each pair should have exactly the same
* value (symmetry). If the sensitivity is below a certain threshold, then we set the two values
* of the affinity matrix to 0 (but not before adding the affinity values to the diagonal, so as
* to maintain the overall sum of the row of the affinity matrix).
*
* @throws Exception
*/
@Test
public void testEigencutsAffinityCutsCombiner() throws Exception {
Configuration conf = new Configuration();
Path affinity = new Path("affinity");
Path sensitivity = new Path("sensitivity");
conf.set(EigencutsKeys.AFFINITY_PATH, affinity.getName());
conf.setInt(EigencutsKeys.AFFINITY_DIMENSIONS, this.affinity.length);
// since we need the working paths to distinguish the vertex types,
// we can't use the mapper (since we have no way of manually setting
// the Context.workingPath() )
Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
// now, set up the combiner
EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
DummyRecordWriter<Text, VertexWritable> redWriter =
new DummyRecordWriter<Text, VertexWritable>();
Reducer<Text, VertexWritable, Text, VertexWritable>.Context redContext =
DummyRecordWriter.build(combiner, conf, redWriter, Text.class, VertexWritable.class);
// perform the combining
for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
combiner.reduce(entry.getKey(), entry.getValue(), redContext);
}
// test the number of cuts, there should be 2
assertEquals(
"Number of cuts detected",
4,
redContext.getCounter(EigencutsAffinityCutsJob.CUTSCOUNTER.NUM_CUTS).getValue());
// loop through all the results; let's see if they match up to our
// affinity matrix (and all the cuts appear where they should
Map<Text, List<VertexWritable>> results = redWriter.getData();
for (Map.Entry<Text, List<VertexWritable>> entry : results.entrySet()) {
List<VertexWritable> row = entry.getValue();
IntWritable key = new IntWritable(Integer.parseInt(entry.getKey().toString()));
double calcDiag = 0.0;
double trueDiag = sumOfRowCuts(key.get(), this.sensitivity);
for (VertexWritable e : row) {
// should the value have been cut, e.g. set to 0?
if (key.get() == e.getCol()) {
// we have our diagonal
calcDiag += e.getValue();
} else if (this.sensitivity[key.get()][e.getCol()] == 0.0) {
// no, corresponding affinity should have same value as before
assertEquals(
"Preserved affinity value",
this.affinity[key.get()][e.getCol()],
e.getValue(),
EPSILON);
} else {
// yes, corresponding affinity value should be 0
assertEquals("Cut affinity value", 0.0, e.getValue(), EPSILON);
}
}
// check the diagonal has the correct sum
assertEquals("Diagonal sum from cuts", trueDiag, calcDiag, EPSILON);
}
}