@Test
public void testBug27() {
double[] tfVector = {0.0, 0.5, 0.0, 0.4, 0.0};
DenseVector dense = new DenseVector(tfVector, false);
SparseVector vectorTF = new SparseVector(dense);
vectorTF.compact();
assertTrue(vectorTF.getUsed() == 2); // vectorTF.getUsed() returns 5
for (Iterator<VectorEntry> it = vectorTF.iterator(); it.hasNext(); ) {
VectorEntry ve = it.next();
int index = ve.index();
double value = ve.get();
assertTrue(tfVector[index] == value);
}
}
@Test
public void testGetRawData() {
SparseVector vector = new SparseVector(Integer.MAX_VALUE);
double[] data = vector.getRawData();
assertTrue(data != null);
assertTrue(data.length == 0);
assertSame(data, vector.data);
assertEquals(data.length, vector.getRawIndex().length);
vector.set(2, 1.0);
vector.set(1, 0.0);
vector.set(4, 2.0);
data = vector.getRawData();
assertSame(data, vector.data);
assertEquals(data.length, vector.getRawIndex().length);
// In this case, the raw index is larger than the used, so the raw
// indices have more entries than the other one.
assertTrue(data.length > vector.getUsed());
assertTrue(data.length > vector.getIndex().length);
}
@Override
public Vector transMultAdd(double alpha, Vector x, Vector y) {
if (!(x instanceof DenseVector) || !(y instanceof DenseVector))
return super.transMultAdd(alpha, x, y);
checkTransMultAdd(x, y);
double[] xd = ((DenseVector) x).getData(), yd = ((DenseVector) y).getData();
// y = 1/alpha * y
y.scale(1. / alpha);
// y = A'x + y
for (int i = 0; i < numRows; ++i) {
SparseVector v = rowD[i];
int[] index = v.getIndex();
double[] data = v.getData();
int length = v.getUsed();
for (int j = 0; j < length; ++j) yd[index[j]] += data[j] * xd[i];
}
// y = alpha*y = alpha * A'x + y
return y.scale(alpha);
}