@Test
public void testAffinitymatrixInputReducer() throws Exception {
AffinityMatrixInputMapper mapper = new AffinityMatrixInputMapper();
Configuration conf = getConfiguration();
conf.setInt(Keys.AFFINITY_DIMENSIONS, RAW_DIMENSIONS);
// set up the dummy writer and the M/R context
DummyRecordWriter<IntWritable, MatrixEntryWritable> mapWriter = new DummyRecordWriter<>();
Mapper<LongWritable, Text, IntWritable, MatrixEntryWritable>.Context mapContext =
DummyRecordWriter.build(mapper, conf, mapWriter);
// loop through all the points and test each one is converted
// successfully to a DistributedRowMatrix.MatrixEntry
for (String s : RAW) {
mapper.map(new LongWritable(), new Text(s), mapContext);
}
// store the data for checking later
Map<IntWritable, List<MatrixEntryWritable>> map = mapWriter.getData();
// now reduce the data
AffinityMatrixInputReducer reducer = new AffinityMatrixInputReducer();
DummyRecordWriter<IntWritable, VectorWritable> redWriter = new DummyRecordWriter<>();
Reducer<IntWritable, MatrixEntryWritable, IntWritable, VectorWritable>.Context redContext =
DummyRecordWriter.build(
reducer, conf, redWriter, IntWritable.class, MatrixEntryWritable.class);
for (IntWritable key : mapWriter.getKeys()) {
reducer.reduce(key, mapWriter.getValue(key), redContext);
}
// check that all the elements are correctly ordered
assertEquals("Number of reduce results", RAW_DIMENSIONS, redWriter.getData().size());
for (IntWritable row : redWriter.getKeys()) {
List<VectorWritable> list = redWriter.getValue(row);
assertEquals("Should only be one vector", 1, list.size());
// check that the elements in the array are correctly ordered
Vector v = list.get(0).get();
for (Vector.Element e : v.all()) {
// find this value in the original map
MatrixEntryWritable toCompare = new MatrixEntryWritable();
toCompare.setRow(-1);
toCompare.setCol(e.index());
toCompare.setVal(e.get());
assertTrue("This entry was correctly placed in its row", map.get(row).contains(toCompare));
}
}
}
/**
* 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);
}
}
}
}
}
}
/**
* Fairly straightforward: the task here is to reassemble the rows of the affinity matrix. The
* tricky part is that any specific element in the list of elements which does NOT lay on the
* diagonal will be so because it did not drop below the sensitivity threshold, hence it was not
* "cut".
*
* <p>On the flip side, there will be many entries whose coordinate is now set to the diagonal,
* indicating they were previously affinity entries whose sensitivities were below the threshold,
* and hence were "cut" - set to 0 at their original coordinates, and had their values added to
* the diagonal entry (hence the numerous entries with the coordinate of the diagonal).
*
* @throws Exception
*/
@Test
public void testEigencutsAffinityCutsReducer() 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> comWriter =
new DummyRecordWriter<Text, VertexWritable>();
Reducer<Text, VertexWritable, Text, VertexWritable>.Context comContext =
DummyRecordWriter.build(combiner, conf, comWriter, Text.class, VertexWritable.class);
// perform the combining
for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
combiner.reduce(entry.getKey(), entry.getValue(), comContext);
}
// finally, set up the reduction writers
EigencutsAffinityCutsReducer reducer = new EigencutsAffinityCutsReducer();
DummyRecordWriter<IntWritable, VectorWritable> redWriter =
new DummyRecordWriter<IntWritable, VectorWritable>();
Reducer<Text, VertexWritable, IntWritable, VectorWritable>.Context redContext =
DummyRecordWriter.build(reducer, conf, redWriter, Text.class, VertexWritable.class);
// perform the reduction
for (Text key : comWriter.getKeys()) {
reducer.reduce(key, comWriter.getValue(key), redContext);
}
// now, check that the affinity matrix is correctly formed
for (IntWritable row : redWriter.getKeys()) {
List<VectorWritable> results = redWriter.getValue(row);
// there should only be 1 vector
assertEquals("Only one vector with a given row number", 1, results.size());
Vector therow = results.get(0).get();
for (Vector.Element e : therow.all()) {
// check the diagonal
if (row.get() == e.index()) {
assertEquals(
"Correct diagonal sum of cuts",
sumOfRowCuts(row.get(), this.sensitivity),
e.get(),
EPSILON);
} else {
// not on the diagonal...if it was an element labeled to be cut,
// it should have a value of 0. Otherwise, it should have kept its
// previous value
if (this.sensitivity[row.get()][e.index()] == 0.0) {
// should be what it was originally
assertEquals(
"Preserved element", this.affinity[row.get()][e.index()], e.get(), EPSILON);
} else {
// should be 0
assertEquals("Cut element", 0.0, e.get(), EPSILON);
}
}
}
}
}
