WIP: Rework trait system

Author: hhirtz

src/algorithms/fiduccia_mattheyses.rs

@@ -1,28 +1,22 @@
 use itertools::Itertools;
-use nalgebra::{allocator::Allocator, DefaultAllocator, DimName};
 use sprs::CsMatView;
 
-use crate::partition::Partition;
-use crate::PointND;
 use crate::ProcessUniqueId;
 use std::collections::HashMap;
 
-pub fn fiduccia_mattheyses<'a, D>(
-    initial_partition: &mut Partition<'a, PointND<D>, f64>,
+pub fn fiduccia_mattheyses(
+    ids: &mut [ProcessUniqueId],
     adjacency: CsMatView<f64>,
+    weights: &[f64],
     max_passes: impl Into<Option<usize>>,
     max_flips_per_pass: impl Into<Option<usize>>,
     max_imbalance_per_flip: impl Into<Option<f64>>,
     max_bad_move_in_a_row: usize,
-) where
-    D: DimName,
-    DefaultAllocator: Allocator<f64, D>,
-    <DefaultAllocator as Allocator<f64, D>>::Buffer: Send + Sync,
+)
 {
     let max_passes = max_passes.into();
     let max_flips_per_pass = max_flips_per_pass.into();
     let max_imbalance_per_flip = max_imbalance_per_flip.into();
-    let (_points, weights, ids) = initial_partition.as_raw_mut();
 
     fiduccia_mattheyses_impl(
         weights,

src/algorithms/kernighan_lin.rs

@@ -3,27 +3,20 @@
 //! At each iteration, two nodes of different partition will be swapped, decreasing the overall cutsize
 //! of the partition. The swap is performed in such a way that the added partition imbalanced is controlled.
 
-use crate::geometry::PointND;
-use crate::partition::Partition;
 use crate::ProcessUniqueId;
 
 use itertools::Itertools;
-use nalgebra::allocator::Allocator;
-use nalgebra::DefaultAllocator;
-use nalgebra::DimName;
 use sprs::CsMatView;
 
-pub(crate) fn kernighan_lin<'a, D>(
-    initial_partition: &mut Partition<'a, PointND<D>, f64>,
+pub(crate) fn kernighan_lin(
+    ids: &mut [ProcessUniqueId],
     adjacency: CsMatView<f64>,
+    weights: &[f64],
     max_passes: impl Into<Option<usize>>,
     max_flips_per_pass: impl Into<Option<usize>>,
     max_imbalance_per_flip: impl Into<Option<f64>>,
     max_bad_move_in_a_row: usize,
-) where
-    D: DimName,
-    DefaultAllocator: Allocator<f64, D>,
-    <DefaultAllocator as Allocator<f64, D>>::Buffer: Send + Sync,
+)
 {
     // To adapt Kernighan-Lin to a partition of more than 2 parts,
     // we apply the algorithm to each pair of adjacent parts (two parts
@@ -33,7 +26,6 @@ pub(crate) fn kernighan_lin<'a, D>(
     let max_passes = max_passes.into();
     let max_flips_per_pass = max_flips_per_pass.into();
     let max_imbalance_per_flip = max_imbalance_per_flip.into();
-    let (_points, weights, ids) = initial_partition.as_raw_mut();
 
     kernighan_lin_2_impl(
         weights,
@@ -46,18 +38,15 @@ pub(crate) fn kernighan_lin<'a, D>(
     );
 }
 
-fn kernighan_lin_2_impl<D>(
+fn kernighan_lin_2_impl(
     weights: &[f64],
     adjacency: CsMatView<f64>,
     initial_partition: &mut [ProcessUniqueId],
     max_passes: Option<usize>,
     max_flips_per_pass: Option<usize>,
     _max_imbalance_per_flip: Option<f64>,
     max_bad_move_in_a_row: usize,
-) where
-    D: DimName,
-    DefaultAllocator: Allocator<f64, D>,
-    <DefaultAllocator as Allocator<f64, D>>::Buffer: Send + Sync,
+)
 {
     let unique_ids = initial_partition
         .iter()

src/algorithms/kk.rs

@@ -1,6 +1,5 @@
 use std::collections::BinaryHeap;
 use std::ops::Sub;
-use std::ops::SubAssign;
 
 use num::Zero;
 
@@ -53,7 +52,7 @@ where
 /// Implementation of the Karmarkar-Karp algorithm
 pub fn kk<T, I>(partition: &mut [usize], weights: I, num_parts: usize)
 where
-    T: Zero + Ord + Sub<Output = T> + SubAssign + Copy,
+    T: Zero + Ord + Sub<Output = T> + Copy,
     I: IntoIterator<Item = T>,
     <I as IntoIterator>::IntoIter: ExactSizeIterator,
 {
@@ -110,7 +109,7 @@ where
 
         let emin = e[e.len() - 1].0;
         for ei in &mut e {
-            ei.0 -= emin;
+            ei.0 = ei.0 - emin;
         }
         opposites.push(tuples);
         m.push(e);