clu1.calc_dist();
clu0.dist + clu1.dist
}
- #[allow(clippy::cyclomatic_complexity)]
+ #[allow(clippy::cognitive_complexity)]
pub fn quantise(&mut self, src: &[T], dst: &mut [T]) -> usize {
if src.is_empty() || dst.len() != self.clusters.len() {
return 0;
}
// put points into the nearest clusters
- indices.truncate(0);
+ indices.clear();
for entry in entries.iter() {
let mut bestidx = 0;
let mut bestdist = std::u32::MAX;
}
let dmean = dist / (dst.len() as u64);
- low_u.truncate(0);
- high_u.truncate(0);
+ low_u.clear();
+ high_u.clear();
let mut used = vec![false; dst.len()];
for (i, cluster) in self.clusters.iter().enumerate() {
if cluster.dist < dmean {