public final double dotProduct(SparseVector v) {
if (indices.length == 0) return 0;
if (index2location == null) setIndex2Location();
double ret = 0;
int vNumLocs = v.numLocations();
if (isBinary()) {
// this vector is binary
for (int i = 0; i < vNumLocs; i++) {
int index = v.indexAtLocation(i);
if (index >= index2location.length) break;
if (index2location[index] >= 0) ret += v.valueAtLocation(i);
}
} else if (v.isBinary()) {
// the other vector is binary
for (int i = 0; i < vNumLocs; i++) {
int index = v.indexAtLocation(i);
if (index >= index2location.length) break;
int location = index2location[index];
if (location >= 0) ret += values[location];
}
} else {
for (int i = 0; i < vNumLocs; i++) {
int index = v.indexAtLocation(i);
if (index >= index2location.length) break;
int location = index2location[index];
if (location >= 0) ret += values[location] * v.valueAtLocation(i);
}
}
return ret;
}
public final void plusEqualsSparse(SparseVector v) {
if (indices.length == 0) return;
if (index2location == null) setIndex2Location();
for (int i = 0; i < v.numLocations(); i++) {
int index = v.indexAtLocation(i);
if (index >= index2location.length) break;
int location = index2location[index];
if (location >= 0) values[location] += v.valueAtLocation(i);
}
}
// Access by index into sparse array, efficient for sparse and dense matrices
public int numLocations() {
return values.numLocations();
}