DiscreteModel::DiscreteModel(const vectori &categories,
bopt_params parameters):
BayesOptBase(categories.size(),parameters)
{
mDims = categories.size();
utils::buildGrid(categories,mInputSet);
}
/*! @brief construct a tree of Parts
*
* Given a set of Part components (filters, parents, w, bias), recursively construct
* a tree of Parts
* @param filters
* @param parents
* @return
*/
Part Part::constructPartHierarchy(vector2DMat& filters, vectori& parents) {
// error checking
assert(filters.size() == parents.size());
// construct the Part tree, from the root node
return constructPartHierarchyRecursive(filters, parents, 0, 0);
}
int main() {
optimize_io
int i, n, a, b;
lli t, x;
cin >> N;
for (i = 0; i < N; ++i) {
cin >> x;
PB(A, MP(x, i + 1));
sum += x;
}
sort(ALL(A));
for (i = 0; i < N; ++i) {
t = sum - A[i].X;
x = t / 2;
if ((2 * x) == t) {
a = lower(x);
b = upper(x);
n = b - a;
if (n > 0 and a < N and A[a].X == x and !(n == 1 and x == A[i].X)) {
PB(ans, A[i].Y);
}
}
}
cout << ans.size() << '\n';
for (i = 0, n = ans.size(); i < n; ++i) {
cout << ans[i] << ' ';
}
cout << '\n';
return 0;
}
//! convert a vector of integers from Matlab 1-based indexing to C++ 0-based indexing
static inline void zeroIndex(vectori& idx) {
for (unsigned int n = 0; n < idx.size(); ++n) idx[n] -= 1;
}
static vectori find(vectori vals, int val) {
vectori idx;
for (unsigned int n = 0; n < vals.size(); ++n) if(vals[n] == val) idx.push_back(n);
return idx;
}