void
generateMT
(
int stripe
)
{
// Randomly estimate the best pair of sub-patches
boost::mt19937 rng(abs(stripe+1) * std::time(NULL));
if (Sample::generateSplit(m_samples, &rng, m_patch_size, m_splits[stripe]))
{
// Process each patch with the selected R1 and R2
std::vector<IntIndex> val_set(m_samples.size());
for (unsigned int i=0; i < m_samples.size(); ++i)
{
val_set[i].first = m_samples[i]->evalTest(m_splits[stripe]);
val_set[i].second = i;
}
std::sort(val_set.begin(), val_set.end()); // sort by f_theta
findThreshold(m_samples, val_set, m_splits[stripe], &rng);
m_splits[stripe].oob = 0;
}
else
{
m_splits[stripe].threshold = 0;
m_splits[stripe].info = boost::numeric::bounds<double>::lowest();
m_splits[stripe].oob = boost::numeric::bounds<double>::highest();
}
};
void generate_mt(int stripe) {
boost::mt19937 rng_thread(abs(stripe + 1) * std::time(NULL));
if (Sample::generateSplit(data, &rng_thread, fp, splits[stripe], split_mode, depth)) {
std::vector<IntIndex> valSet(data.size());
for (unsigned int l = 0; l < data.size(); ++l) {
valSet[l].first = data[l]->evalTest(splits[stripe]);
valSet[l].second = l;
}
std::sort(valSet.begin(), valSet.end());
findThreshold(data, valSet, splits[stripe], &rng_thread);
splits[stripe].oob = 0;
} else {
splits[stripe].threshold = 0;
splits[stripe].info = boost::numeric::bounds<double>::lowest();
splits[stripe].gain = boost::numeric::bounds<double>::lowest();
splits[stripe].oob = boost::numeric::bounds<double>::highest();
}
}
