use scirs2_core::numeric::Float;
use super::functions::prefetch_read;
use super::functions::Distance;
use super::types::ManhattanDistance;
impl<T: Float> Default for ManhattanDistance<T> {
fn default() -> Self {
Self::new()
}
}
impl<T: Float + Send + Sync> Distance<T> for ManhattanDistance<T> {
fn distance(&self, a: &[T], b: &[T]) -> T {
if a.len() != b.len() {
return T::nan();
}
if let Some(result) = Self::try_simd_f64(a, b) {
return result;
}
if let Some(result) = Self::try_simd_f32(a, b) {
return result;
}
let len = a.len();
let mut sum = T::zero();
let chunks = len / 4;
for i in 0..chunks {
let base = i * 4;
if base + 8 < len {
let end_idx = (base + 8).min(len);
prefetch_read(&a[base + 4..end_idx]);
prefetch_read(&b[base + 4..end_idx]);
}
let diff0_abs = (a[base] - b[base]).abs();
let diff1_abs = (a[base + 1] - b[base + 1]).abs();
let diff2_abs = (a[base + 2] - b[base + 2]).abs();
let diff3_abs = (a[base + 3] - b[base + 3]).abs();
sum = sum + diff0_abs + diff1_abs + diff2_abs + diff3_abs;
}
for i in (chunks * 4)..len {
sum = sum + (a[i] - b[i]).abs();
}
sum
}
fn min_distance_point_rectangle(&self, point: &[T], mins: &[T], maxes: &[T]) -> T {
let mut sum = T::zero();
for i in 0..point.len() {
let coord = point[i];
let min_val = mins[i];
let max_val = maxes[i];
let clamped = coord.max(min_val).min(max_val);
let diff = (coord - clamped).abs();
sum = sum + diff;
}
sum
}
}