/**
* Constructor.
*
* @param d the dimensionality of data.
* @param L the number of hash tables.
* @param k the number of random projection hash functions, which is usually set to log(N) where N
* is the dataset size.
* @param w the width of random projections. It should be sufficiently away from 0. But we should
* not choose an w value that is too large, which will increase the query time.
* @param H the size of universal hash tables.
*/
public LSH(int d, int L, int k, double w, int H) {
if (d < 2) {
throw new IllegalArgumentException("Invalid input space dimension: " + d);
}
if (L < 1) {
throw new IllegalArgumentException("Invalid number of hash tables: " + L);
}
if (k < 1) {
throw new IllegalArgumentException(
"Invalid number of random projections per hash value: " + k);
}
if (w <= 0.0) {
throw new IllegalArgumentException("Invalid width of random projections: " + w);
}
if (H < 1) {
throw new IllegalArgumentException("Invalid size of hash tables: " + H);
}
this.d = d;
this.L = L;
this.k = k;
this.w = w;
this.H = H;
keys = new ArrayList<double[]>();
data = new ArrayList<E>();
r1 = new int[k];
r2 = new int[k];
for (int i = 0; i < k; i++) {
r1[i] = Math.randomInt(MAX_HASH_RND);
r2[i] = Math.randomInt(MAX_HASH_RND);
}
hash = new ArrayList<Hash>(L);
for (int i = 0; i < L; i++) {
hash.add(new Hash());
}
}
/** Generate a random neighbor which differs in only one medoid with current clusters. */
private double getRandomNeighbor(T[] data, T[] medoids, int[] y, double[] d) {
int n = data.length;
int index = Math.randomInt(k);
T medoid = null;
boolean dup;
do {
dup = false;
medoid = data[Math.randomInt(n)];
for (int i = 0; i < k; i++) {
if (medoid == medoids[i]) {
dup = true;
break;
}
}
} while (dup);
medoids[index] = medoid;
for (int i = 0; i < n; i++) {
double dist = distance.d(data[i], medoid);
if (d[i] > dist) {
y[i] = index;
d[i] = dist;
} else if (y[i] == index) {
d[i] = dist;
y[i] = index;
for (int j = 0; j < k; j++) {
if (j != index) {
dist = distance.d(data[i], medoids[j]);
if (d[i] > dist) {
y[i] = j;
d[i] = dist;
}
}
}
}
}
return Math.sum(d);
}
