/**
* Returns a random subsample of X of size n which has minimum (amongst
* a set of NSAMPLES similar subsamples) maximum distance between points.
*/
ivec MaxMinDesign::subsample(mat X, int n)
{
if (n <= 0)
cerr << "Invalid sample size in MaxMinDesign::subsample(...)" << endl;
double maxMinDist = 0.0;
ivec bestSubsample = randperm(X.rows());
for (int i=0; i<nsamples; i++) {
// Generate random subsample
ivec irand = randperm(X.rows());
ivec irandn = irand(0,n-1);
mat S = X.get_rows(irandn);
// Compute max distance in this subsample
double minDist = distanceMin(S);
// Keep subsample if has min max distance
if (minDist > maxMinDist) {
bestSubsample = irandn;
maxMinDist = minDist;
cout << "New min distance: " << maxMinDist << endl;
}
}
return bestSubsample;
}
ivec GreedyMaxMinDesign::subsample(mat X, int n)
{
if (n <= 0)
cerr << "Invalid sample size in GreedyMaxMinDesign::subsample(...)" << endl;
int imax;
ivec isample(n); // Indices of points in sample
ivec iremain; // Indices of remaining points
vec D; // Vector of min distances to sample
iremain = to_ivec(linspace(0,X.rows()-1,X.rows()));
// Start with location of maximum Z
max(X.get_col(X.cols()-1), imax);
isample(0) = imax;
iremain.del(imax);
// Add points having maximum minimum distance to sample
// until subsample size is reached
for (int i=1; i<n; i++)
{
vec xnew = X.get_row(isample(i-1)); // Last point added
vec Dnew = dist(X.get_rows(iremain), xnew); // Distances to xnew
// Update minimum distances to sample
if (D.length() == 0)
D = Dnew;
else
D = min(D,Dnew);
// Find point with max min distance
max(D,imax);
// Add it to sample
isample(i) = iremain(imax);
// And delete it from remainder
iremain.del(imax);
D.del(imax);
}
return isample;
}
