/** Test adding translation vectors */
@Test
public void testTranslation() {
int testdim = 5;
AffineTransformation t = new AffineTransformation(testdim);
assertTrue(t.getDimensionality() == testdim);
Matrix tm = t.getTransformation();
assertEquals(
"initial transformation matrix should be unity", tm, Matrix.unitMatrix(testdim + 1));
// translation vector
double[] tv = new double[testdim];
for (int i = 0; i < testdim; i++) {
tv[i] = i + testdim;
}
t.addTranslation(tv);
Matrix tm2 = t.getTransformation();
// Manually do the same changes to the matrix tm
for (int i = 0; i < testdim; i++) {
tm.set(i, testdim, i + testdim);
}
// Compare the results
assertEquals("Translation wasn't added correctly to matrix.", tm, tm2);
// test application to a vector
double[] v1 = new double[testdim];
double[] v2t = new double[testdim];
for (int i = 0; i < testdim; i++) {
v1[i] = i * i + testdim;
v2t[i] = i * i + i + 2 * testdim;
}
double[] v1t = t.apply(v1);
assertTrue("Vector wasn't translated properly forward.", Arrays.equals(v2t, v1t));
double[] v2b = t.applyInverse(v2t);
assertTrue("Vector wasn't translated properly backwards.", Arrays.equals(v1, v2b));
double[] v1b = t.applyInverse(v1t);
assertTrue("Vector wasn't translated properly back and forward.", Arrays.equals(v1, v1b));
// Translation
double[] vd = minus(v1, v2b);
double[] vtd = minus(v1t, v2t);
assertTrue("Translation changed vector difference.", Arrays.equals(vd, vtd));
// Translation shouldn't change relative vectors.
assertTrue(
"Relative vectors weren't left unchanged by translation!",
Arrays.equals(v1, t.applyRelative(v1)));
assertTrue(
"Relative vectors weren't left unchanged by translation!",
Arrays.equals(v2t, t.applyRelative(v2t)));
assertTrue(
"Relative vectors weren't left unchanged by translation!",
Arrays.equals(v1t, t.applyRelative(v1t)));
assertTrue(
"Relative vectors weren't left unchanged by translation!",
Arrays.equals(v2b, t.applyRelative(v2b)));
}
/**
* Run the algorithm
*
* @param relation Data relation
* @return Outlier result
*/
public OutlierResult run(Relation<V> relation) {
DoubleMinMax mm = new DoubleMinMax();
// resulting scores
WritableDoubleDataStore oscores =
DataStoreUtil.makeDoubleStorage(
relation.getDBIDs(), DataStoreFactory.HINT_TEMP | DataStoreFactory.HINT_HOT);
// Compute mean and covariance Matrix
CovarianceMatrix temp = CovarianceMatrix.make(relation);
double[] mean = temp.getMeanVector(relation).toArray();
// debugFine(mean.toString());
Matrix covarianceMatrix = temp.destroyToNaiveMatrix();
// debugFine(covarianceMatrix.toString());
Matrix covarianceTransposed =
covarianceMatrix.cheatToAvoidSingularity(SINGULARITY_CHEAT).inverse();
// Normalization factors for Gaussian PDF
final double fakt =
(1.0
/ (Math.sqrt(
MathUtil.powi(MathUtil.TWOPI, RelationUtil.dimensionality(relation))
* covarianceMatrix.det())));
// for each object compute Mahalanobis distance
for (DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
double[] x = minusEquals(relation.get(iditer).toArray(), mean);
// Gaussian PDF
final double mDist = transposeTimesTimes(x, covarianceTransposed, x);
final double prob = fakt * Math.exp(-mDist * .5);
mm.put(prob);
oscores.putDouble(iditer, prob);
}
final OutlierScoreMeta meta;
if (invert) {
double max = mm.getMax() != 0 ? mm.getMax() : 1.;
for (DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
oscores.putDouble(iditer, (max - oscores.doubleValue(iditer)) / max);
}
meta = new BasicOutlierScoreMeta(0.0, 1.0);
} else {
meta = new InvertedOutlierScoreMeta(mm.getMin(), mm.getMax(), 0.0, Double.POSITIVE_INFINITY);
}
DoubleRelation res =
new MaterializedDoubleRelation(
"Gaussian Model Outlier Score", "gaussian-model-outlier", oscores, relation.getDBIDs());
return new OutlierResult(meta, res);
}
/** Test identity transform */
@Test
public void testIdentityTransform() {
int testdim = 5;
AffineTransformation t = new AffineTransformation(testdim);
assertTrue(t.getDimensionality() == testdim);
Matrix tm = t.getTransformation();
assertEquals(
"initial transformation matrix should be unity", tm, Matrix.unitMatrix(testdim + 1));
// test application to a vector
double[] dv = new double[testdim];
for (int i = 0; i < testdim; i++) {
dv[i] = i * i + testdim;
}
double[] v3 = t.apply(dv);
assertTrue("identity transformation wasn't identical", Arrays.equals(dv, v3));
double[] v4 = t.applyInverse(dv);
assertTrue("inverse of identity wasn't identity", Arrays.equals(dv, v4));
}
/** Test direct inclusion of matrices */
@Test
public void testMatrix() {
int testdim = 5;
int axis1 = 1;
int axis2 = 3;
assert (axis1 < testdim);
assert (axis2 < testdim);
// don't change the angle; we'll be using that executing the rotation
// three times will be identity (approximately)
double angle = Math.toRadians(360 / 3);
AffineTransformation t = new AffineTransformation(testdim);
assertTrue(t.getDimensionality() == testdim);
Matrix tm = t.getTransformation();
assertEquals(
"initial transformation matrix should be unity", tm, Matrix.unitMatrix(testdim + 1));
// rotation matrix
double[][] rm = new double[testdim][testdim];
for (int i = 0; i < testdim; i++) {
rm[i][i] = 1;
}
// add the rotation
rm[axis1][axis1] = +Math.cos(angle);
rm[axis1][axis2] = -Math.sin(angle);
rm[axis2][axis1] = +Math.sin(angle);
rm[axis2][axis2] = +Math.cos(angle);
t.addMatrix(new Matrix(rm));
Matrix tm2 = t.getTransformation();
// We know that we didn't do any translations and tm is the unity matrix
// so we can manually do the rotation on it, too.
tm.set(axis1, axis1, +Math.cos(angle));
tm.set(axis1, axis2, -Math.sin(angle));
tm.set(axis2, axis1, +Math.sin(angle));
tm.set(axis2, axis2, +Math.cos(angle));
// Compare the results
assertEquals("Rotation wasn't added correctly to matrix.", tm, tm2);
// test application to a vector
double[] v1 = new double[testdim];
for (int i = 0; i < testdim; i++) {
v1[i] = i * i + testdim;
}
double[] v2 = t.apply(v1);
double[] v3 = t.applyInverse(v2);
assertTrue("Forward-Backward didn't work correctly.", euclideanLength(minus(v1, v3)) < 0.0001);
double[] v4 = t.apply(t.apply(t.apply(v1)));
assertTrue(
"Triple-Rotation by 120 degree didn't work", euclideanLength(minus(v1, v4)) < 0.0001);
// Rotation shouldn't disagree for relative vectors.
// (they just are not affected by translation!)
assertTrue(
"Relative vectors were affected differently by pure rotation!",
Arrays.equals(v2, t.applyRelative(v1)));
// should do the same as built-in rotation!
AffineTransformation t2 = new AffineTransformation(testdim);
t2.addRotation(axis1, axis2, angle);
double[] t2v2 = t2.apply(v1);
assertTrue(
"Manual rotation and AffineTransformation.addRotation disagree.",
euclideanLength(minus(v2, t2v2)) < 0.0001);
}
