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crate::ix!();
pub fn approximate_best_subset(
groups: &Vec<OutputGroup>,
n_total_lower: &Amount,
n_target_value: &Amount,
vf_best: &mut Vec<u8>,
n_best: &mut Amount,
iterations: Option<i32>) {
let iterations: i32 = iterations.unwrap_or(1000);
todo!();
/*
std::vector<char> vfIncluded;
vfBest.assign(groups.size(), true);
nBest = nTotalLower;
FastRandomContext insecure_rand;
for (int nRep = 0; nRep < iterations && nBest != nTargetValue; nRep++)
{
vfIncluded.assign(groups.size(), false);
CAmount nTotal = 0;
bool fReachedTarget = false;
for (int nPass = 0; nPass < 2 && !fReachedTarget; nPass++)
{
for (unsigned int i = 0; i < groups.size(); i++)
{
//The solver here uses a randomized algorithm,
//the randomness serves no real security purpose but is just
//needed to prevent degenerate behavior and it is important
//that the rng is fast. We do not use a constant random sequence,
//because there may be some privacy improvement by making
//the selection random.
if (nPass == 0 ? insecure_rand.randbool() : !vfIncluded[i])
{
nTotal += groups[i].GetSelectionAmount();
vfIncluded[i] = true;
if (nTotal >= nTargetValue)
{
fReachedTarget = true;
if (nTotal < nBest)
{
nBest = nTotal;
vfBest = vfIncluded;
}
nTotal -= groups[i].GetSelectionAmount();
vfIncluded[i] = false;
}
}
}
}
}
*/
}