void
KCenterClustering::ClusterIncrement( int * nClusters, double * maxRadius )
{
if( numClusters == 0 )
{
// randomly pick one node as the first center.
srand( (unsigned)time( NULL ) );
int nc = rand() % N; // new center
// add the ind-th node to the first center.
pCenters[0] = nc;
// compute the distances from each node to the first center.
// initialize the circular linked list, the center is the
// sentinel node.
const double *x_nc, *x_j;
x_nc = px + nc*d;
x_j = px;
for (int j = 0; j < N; x_j += d, j++)
{
dist_C[j] = (j==nc)? 0.0:ddist(d, x_j, x_nc);
cnext[j] = j+1;
cprev[j] = j-1;
}
cnext[N-1] = 0; // link the tail to the head.
cprev[0] = N-1; // link the head to the tail.
// compute the radius of the first cluster and the farthest
// node to the center.
nc = idmax(N,dist_C);
far2c[0] = nc;
r[0] = dist_C[nc];
MaxClusterRadius=sqrt(r[0]);
numClusters++;
}
else
{
if( numClusters < K && MaxClusterRadius > 0 )
{
int i = numClusters;
int nc;
const double *x_nc, *x_j;
//find the maximum of vector dist_C, i.e., find the node
//that is farthest away from C. It is a new center.
nc = idmax(i,r);
nc = far2c[nc];
pCenters[i] = nc; //add the ind-th node to the current center.
r[i] = dist_C[nc] = 0.0;pci[nc]=i;
far2c[i] = nc;
cnext[cprev[nc]] = cnext[nc]; // delete nc
cprev[cnext[nc]] = cprev[nc];
cnext[nc] = cprev[nc] = nc; //self-loop
//update the distances from each point to the current center.
x_nc = px + nc*d;
for (int j = 0; j < i; j++)
{
int ct_j = pCenters[j];
x_j = px + ct_j*d;
double dc2cq = ddist(d, x_j, x_nc) / 4;
if (dc2cq < r[j]) // neighbor cluster
{
r[j] = 0.0;
far2c[j] = ct_j;
int k = cnext[ct_j];
while (k != ct_j) // visit the circular linked list
{
int nextk = cnext[k];
//compare the distances from new center
//and from current center.
double dist2c_k = dist_C[k];
if ( dc2cq < dist2c_k )
{
x_j = px + k*d;
double dd = ddist(d, x_j, x_nc);
if ( dd < dist2c_k )
{
dist_C[k] = dd; // update distances to center
pci[k]=i;
if (r[i] < dd) // find max r
{
r[i] = dd;
far2c[i] = k;
}
cnext[cprev[k]] = nextk; // delete nextk from ct_j
cprev[nextk] = cprev[k];
cnext[k] = cnext[nc]; // insert nextk to nc
cprev[cnext[nc]] = k;
cnext[nc] = k;
cprev[k] = nc;
}
else if ( r[j] < dist2c_k )
{
r[j] = dist2c_k;
far2c[j] = k;
}
}
else if ( r[j] < dist2c_k )
{
r[j] = dist2c_k;
far2c[j] = k;
} // if d < 2 r_k
k = nextk;
} // while k
} // if d < 2 r
} // for j
numClusters++;
nc = idmax(numClusters,r);
MaxClusterRadius=sqrt(r[nc]);
} // if( numClusters < K && MaxClusterRadius > 0 )
} // else ( numClusters > 0 )
if( nClusters != NULL )
*nClusters = numClusters;
if( maxRadius != NULL )
*maxRadius = MaxClusterRadius;
}
void Kcenter(double *x , int d , int Nx , int K ,
double *xc , int *indxc , int *indx , int *xboxsz ,
double *dist_C)
{
double *x_ind , *x_j;
register double temp ;
int i , j , ind , nd , ibase;
/* randomly pick one node as the first center. */
/* srand( (unsigned)time( NULL ) ); */
/* ind = rand() % Nx; */
ind = 1;
*indxc++ = ind;
x_j = x;
x_ind = x + ind*d;
for (j = 0 ; j < Nx ; x_j += d , j++)
{
dist_C[j] = (j==ind) ? 0.0 : ddist(x_j , x_ind , d);
indx[j] = 0;
}
for(i = 1 ; i < K ; i++)
{
ind = idmax(dist_C , Nx);
*indxc++ = ind;
x_j = x;
x_ind = x + ind*d;
for (j = 0 ; j < Nx ; x_j += d, j++)
{
temp = (j==ind) ? 0.0 : ddist(x_j , x_ind , d);
if (temp < dist_C[j])
{
dist_C[j] = temp;
indx[j] = i;
}
}
}
for (i = 0 ; i < K ; i++)
{
xboxsz[i] = 0;
}
for (i = 0; i < d*K; i++)
{
xc[i] = 0.0;
}
for (i = 0 , nd = 0 ; i < Nx ; i++ , nd += d)
{
xboxsz[indx[i]]++;
ibase = indx[i]*d;
for (j = 0 ; j < d; j++)
{
xc[j + ibase ] += x[j + nd];
}
}
for (i = 0 , ibase = 0 ; i < K ; i++ , ibase += d)
{
temp = 1.0/xboxsz[i];
for (j = 0; j < d; j++)
{
xc[j + ibase] *= temp;
}
}
}
int
KCenterClustering::Cluster()
{
// randomly pick one node as the first center.
srand( (unsigned)time( NULL ) );
int nc = rand() % N; // new center
// add the ind-th node to the first center.
pCenters[0] = nc;
// compute the distances from each node to the first center.
// initialize the circular linked list, the center is the
// sentinel node.
const double *x_nc, *x_j;
x_nc = px + nc*d;
x_j = px;
for (int j = 0; j < N; x_j += d, j++)
{
dist_C[j] = (j==nc)? 0.0:ddist(d, x_j, x_nc);
cnext[j] = j+1;
cprev[j] = j-1;
}
cnext[N-1] = 0; // link the tail to the head.
cprev[0] = N-1; // link the head to the tail.
// compute the radius of the first cluster and the farthest
// node to the center.
nc = idmax(N,dist_C);
far2c[0] = nc;
r[0] = dist_C[nc];
MaxClusterRadius=sqrt(r[0]);
numClusters = 1;
for(int i = 1; i < K && MaxClusterRadius > 0; i++)
{
//find the maximum of vector dist_C, i.e., find the node
//that is farthest away from C. It is a new center.
nc = idmax(i,r);
nc = far2c[nc];
pCenters[i] = nc; //add the ind-th node to the current center.
r[i] = dist_C[nc] = 0.0;pci[nc]=i;
far2c[i] = nc;
cnext[cprev[nc]] = cnext[nc]; // delete nc
cprev[cnext[nc]] = cprev[nc];
cnext[nc] = cprev[nc] = nc; //self-loop
//update the distances from each point to the current center.
x_nc = px + nc*d;
for (int j = 0; j < i; j++)
{
int ct_j = pCenters[j];
x_j = px + ct_j*d;
double dc2cq = ddist(d, x_j, x_nc) / 4;
if (dc2cq < r[j]) // neighbor cluster
{
r[j] = 0.0;
far2c[j] = ct_j;
int k = cnext[ct_j];
while (k != ct_j) // visit the circular linked list
{
int nextk = cnext[k];
//compare the distances from new center
//and from current center.
double dist2c_k = dist_C[k];
if ( dc2cq < dist2c_k )
{
x_j = px + k*d;
double dd = ddist(d, x_j, x_nc);
if ( dd < dist2c_k )
{
dist_C[k] = dd; // update distances to center
pci[k]=i;
if (r[i] < dd) // find max r
{
r[i] = dd;
far2c[i] = k;
}
cnext[cprev[k]] = nextk; // delete nextk from ct_j
cprev[nextk] = cprev[k];
cnext[k] = cnext[nc]; // insert nextk to nc
cprev[cnext[nc]] = k;
cnext[nc] = k;
cprev[k] = nc;
}
else if ( r[j] < dist2c_k )
{
r[j] = dist2c_k;
far2c[j] = k;
}
}
else if ( r[j] < dist2c_k )
{
r[j] = dist2c_k;
far2c[j] = k;
} // if d < 2 r_k
k = nextk;
} // while k
} // if d < 2 r
} // for j
// added by vlad 2/6/07 to make sure that we don't keep clustering once each cluster has radius 0
// otherwise some clusters will have no pts assigned to them
nc = idmax(i+1,r);
MaxClusterRadius=sqrt(r[nc]);
numClusters = i+1;
} // for i
// commented by vlad 2/6/07 to move it above inside of the loop
//nc = idmax(K,r);
//MaxClusterRadius=sqrt(r[nc]);
//numClusters = K; // added by Vlad 1/24/07
return numClusters;
}
