void reverse_arcs(RawArray<CircleArc> arcs) {
if(arcs.empty()) return;
arcs.reverse();
const auto temp_q = arcs.front().q;
for(int i = 0,j = 1; j<arcs.size(); i=j++) {
arcs[i].q = -arcs[j].q;
}
arcs.back().q = -temp_q;
}
template<int axis> static inline int spatial_partition(RawArray<Perturbed2> X, Random& random) {
// We use exact arithmetic to perform the partition, which is important in case many points are coincident
#define LESS(i,j) (i!=j && axis_less<axis>(X[i],X[j]))
// We partition by picking three elements at random, and running partition based on the middle element.
const int n = X.size();
int i0 = random.uniform<int>(0,n),
i1 = random.uniform<int>(0,n),
i2 = random.uniform<int>(0,n);
if (!LESS(i0,i1)) swap(i0,i1);
if (!LESS(i1,i2)) swap(i1,i2);
if (!LESS(i0,i1)) swap(i0,i1);
const auto Xmid = X[i1];
swap(X[i1],X.back());
// Perform the partition. We use the version of partition from Wikipedia: http://en.wikipedia.org/wiki/Quicksort#In-place_version
int mid = 0;
for (const int i : range(n-1))
if (axis_less<axis>(X[i],Xmid))
swap(X[i],X[mid++]);
return mid;
}
// Safely expose snap_divs to python for testing purposes
static Array<Quantized> snap_divs_test(RawArray<mp_limb_t,2> values, const bool take_sqrt) {
GEODE_ASSERT(values.m && !values.back().contains_only(0));
Array<Quantized> result(values.m-1);
snap_divs(result,values,take_sqrt);
return result;
}
