WIP: rework Partitioner trait family

This simplifies the family of traits from before into one "Partition"
trait.

src/algorithms.rs

@@ -1,12 +1,62 @@
-pub mod ckk;
-pub mod fiduccia_mattheyses;
-pub mod graph_growth;
-pub mod greedy;
-pub mod hilbert_curve;
-pub mod k_means;
-pub mod kernighan_lin;
-pub mod kk;
-pub mod multi_jagged;
-pub mod recursive_bisection;
-pub mod vn;
-pub mod z_curve;
+mod ckk;
+mod fiduccia_mattheyses;
+mod graph_growth;
+mod greedy;
+mod hilbert_curve;
+mod k_means;
+mod kernighan_lin;
+mod kk;
+mod multi_jagged;
+mod recursive_bisection;
+mod vn;
+mod z_curve;
+
+pub use ckk::CompleteKarmarkarKarp;
+pub use fiduccia_mattheyses::FiducciaMattheyses;
+pub use graph_growth::GraphGrowth;
+pub use greedy::Greedy;
+pub use hilbert_curve::HilbertCurve;
+pub use k_means::KMeans;
+pub use kernighan_lin::KernighanLin;
+pub use kk::KarmarkarKarp;
+pub use multi_jagged::MultiJagged;
+pub use recursive_bisection::Rcb;
+pub use recursive_bisection::Rib;
+pub use vn::VnBest;
+pub use z_curve::ZCurve;
+
+/// Map mesh elements to parts randomly.
+///
+/// # Example
+///
+/// ```rust
+/// use coupe::Partitioner;
+/// use coupe::Point2D;
+/// use coupe::Random;
+/// use rand;
+///
+/// let num_parts = 3;
+/// let points: &[Point2D] = &[Point2D::new(1., 0.), Point2D::new(0., 1.)];
+///
+/// let r = Random::new(rand::thread_rng(), num_parts);
+/// r.partition(points, &[1., 1.]);
+/// ```
+pub struct Random<R> {
+    pub rng: R,
+    pub part_count: usize,
+}
+
+impl<R> crate::Partition<()> for Random<R>
+where
+    R: rand::Rng,
+{
+    type Metadata = ();
+    type Error = std::convert::Infallible;
+
+    fn partition(&mut self, part_ids: &mut [usize], _: ()) -> Result<Self::Metadata, Self::Error> {
+        for part_id in part_ids {
+            *part_id = self.rng.gen_range(0..self.part_count);
+        }
+        Ok(())
+    }
+}

src/algorithms/ckk.rs

@@ -92,7 +92,7 @@ where
     false
 }
 
-pub fn ckk_bipart<I, T>(partition: &mut [usize], weights: I, tolerance: f64) -> bool
+fn ckk_bipart<I, T>(partition: &mut [usize], weights: I, tolerance: f64) -> bool
 where
     I: IntoIterator<Item = T>,
     T: Sum + Add<Output = T> + Sub<Output = T>,
@@ -114,4 +114,43 @@ where
     ckk_bipart_rec(partition, &mut weights, tolerance, &mut steps)
 }
 
+/// The exact variant of the [Karmarkar-Karp][crate::KarmarkarKarp] algorithm.
+///
+/// # Example
+///
+/// ```rust
+/// use coupe::Partitioner;
+/// use coupe::Point2D;
+/// use coupe::CompleteKarmarkarKarp;
+///
+/// let tolerance = 0.1;
+/// let points: &[Point2D] = &[Point2D::new(1., 0.), Point2D::new(0., 1.)];
+///
+/// let ckk = CompleteKarmarkarKarp::new(tolerance);
+/// ckk.partition(points, &[1., 1.]);
+/// ```
+pub struct CompleteKarmarkarKarp {
+    pub tolerance: f64,
+}
+
+impl<W> crate::Partition<W> for CompleteKarmarkarKarp
+where
+    W: IntoIterator,
+    W::Item: Sum + Add<Output = W::Item> + Sub<Output = W::Item>,
+    W::Item: FromPrimitive + ToPrimitive,
+    W::Item: Ord + Default + Copy,
+{
+    type Metadata = ();
+    type Error = std::convert::Infallible;
+
+    fn partition(
+        &mut self,
+        part_ids: &mut [usize],
+        weights: W,
+    ) -> Result<Self::Metadata, Self::Error> {
+        ckk_bipart(part_ids, weights, self.tolerance);
+        Ok(())
+    }
+}
+
 // TODO tests

src/algorithms/fiduccia_mattheyses.rs

@@ -1,12 +1,11 @@
 use itertools::Itertools;
 use sprs::CsMatView;
 
-use crate::partition::Partition;
-use crate::PointND;
 use std::collections::HashMap;
 
-pub fn fiduccia_mattheyses<'a, const D: usize>(
-    initial_partition: &mut Partition<'a, PointND<D>, f64>,
+fn fiduccia_mattheyses<'a>(
+    part_ids: &mut [usize],
+    weights: &[f64],
     adjacency: CsMatView<f64>,
     max_passes: impl Into<Option<usize>>,
     max_flips_per_pass: impl Into<Option<usize>>,
@@ -16,12 +15,11 @@ pub fn fiduccia_mattheyses<'a, const D: usize>(
     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(
+        part_ids,
         weights,
-        adjacency.view(),
-        ids,
+        adjacency,
         max_passes,
         max_flips_per_pass,
         max_imbalance_per_flip,
@@ -30,9 +28,9 @@ pub fn fiduccia_mattheyses<'a, const D: usize>(
 }
 
 fn fiduccia_mattheyses_impl(
+    initial_partition: &mut [usize],
     weights: &[f64],
     adjacency: CsMatView<f64>,
-    initial_partition: &mut [usize],
     max_passes: Option<usize>,
     max_flips_per_pass: Option<usize>,
     max_imbalance_per_flip: Option<f64>,
@@ -250,3 +248,113 @@ fn fiduccia_mattheyses_impl(
 
     println!("final cut size: {}", new_cut_size);
 }
+
+/// FiducciaMattheyses
+///
+/// An implementation of the Fiduccia Mattheyses topologic algorithm
+/// for graph partitioning. This implementation is an extension of the
+/// original algorithm to handle partitioning into more than two parts.
+///
+/// This algorithm repeats an iterative pass during which a set of graph nodes are assigned to
+/// a new part, reducing the overall cutsize of the partition. As opposed to the
+/// Kernighan-Lin algorithm, during each pass iteration, only one node is flipped at a time.
+/// The algorithm thus does not preserve partition weights balance and may produce an unbalanced
+/// partition.
+///
+/// Original algorithm from "A Linear-Time Heuristic for Improving Network Partitions"
+/// by C.M. Fiduccia and R.M. Mattheyses.
+///
+/// # Example
+///
+/// ```rust
+/// use coupe::Point2D;
+/// use coupe::TopologicPartitionImprover;
+/// use coupe::partition::Partition;
+/// use sprs::CsMat;
+///
+/// //    swap
+/// // 0  1  0  1
+/// // +--+--+--+
+/// // |  |  |  |
+/// // +--+--+--+
+/// // 0  0  1  1
+/// let points = vec![
+///      Point2D::new(0., 0.),
+///      Point2D::new(1., 0.),
+///      Point2D::new(2., 0.),
+///      Point2D::new(3., 0.),
+///      Point2D::new(0., 1.),
+///      Point2D::new(1., 1.),
+///      Point2D::new(2., 1.),
+///      Point2D::new(3., 1.),
+///  ];
+///
+///  let ids = vec![0, 0, 1, 1, 0, 1, 0, 1];
+///  let weights = vec![1.; 8];
+///
+///  let mut partition = Partition::from_ids(&points, &weights, ids);
+///
+///  let mut adjacency = CsMat::empty(sprs::CSR, 8);
+///  adjacency.reserve_outer_dim(8);
+///  eprintln!("shape: {:?}", adjacency.shape());
+///  adjacency.insert(0, 1, 1.);
+///  adjacency.insert(1, 2, 1.);
+///  adjacency.insert(2, 3, 1.);
+///  adjacency.insert(4, 5, 1.);
+///  adjacency.insert(5, 6, 1.);
+///  adjacency.insert(6, 7, 1.);
+///  adjacency.insert(0, 4, 1.);
+///  adjacency.insert(1, 5, 1.);
+///  adjacency.insert(2, 6, 1.);
+///  adjacency.insert(3, 7, 1.);
+///  
+///  // symmetry
+///  adjacency.insert(1, 0, 1.);
+///  adjacency.insert(2, 1, 1.);
+///  adjacency.insert(3, 2, 1.);
+///  adjacency.insert(5, 4, 1.);
+///  adjacency.insert(6, 5, 1.);
+///  adjacency.insert(7, 6, 1.);
+///  adjacency.insert(4, 0, 1.);
+///  adjacency.insert(5, 1, 1.);
+///  adjacency.insert(6, 2, 1.);
+///  adjacency.insert(7, 3, 1.);
+///
+/// // 1 iteration
+/// let algo = coupe::FiducciaMattheyses::new(None, None, None, 1);
+///
+/// let partition = algo.improve_partition(partition, adjacency.view());
+///
+/// let new_ids = partition.into_ids();
+/// assert_eq!(new_ids[5], 0);
+/// assert_eq!(new_ids[6], 1);
+/// ```
+#[derive(Debug, Clone, Copy)]
+pub struct FiducciaMattheyses {
+    pub max_passes: Option<usize>,
+    pub max_flips_per_pass: Option<usize>,
+    pub max_imbalance_per_flip: Option<f64>,
+    pub max_bad_move_in_a_row: usize,
+}
+
+impl<'a> crate::Partition<(CsMatView<'a, f64>, &'a [f64])> for FiducciaMattheyses {
+    type Metadata = ();
+    type Error = std::convert::Infallible;
+
+    fn partition(
+        &mut self,
+        part_ids: &mut [usize],
+        (adjacency, weights): (CsMatView<f64>, &'a [f64]),
+    ) -> Result<Self::Metadata, Self::Error> {
+        fiduccia_mattheyses(
+            part_ids,
+            weights,
+            adjacency,
+            self.max_passes,
+            self.max_flips_per_pass,
+            self.max_imbalance_per_flip,
+            self.max_bad_move_in_a_row,
+        );
+        Ok(())
+    }
+}

src/algorithms/graph_growth.rs

@@ -1,12 +1,16 @@
 use rand::seq::SliceRandom;
 use sprs::CsMatView;
 
-pub fn graph_growth(weights: &[f64], adjacency: CsMatView<f64>, num_parts: usize) -> Vec<usize> {
+fn graph_growth(
+    initial_ids: &mut [usize],
+    weights: &[f64],
+    adjacency: CsMatView<f64>,
+    num_parts: usize,
+) {
     let (shape_x, shape_y) = adjacency.shape();
     assert_eq!(shape_x, shape_y);
     assert_eq!(weights.len(), shape_x);
 
-    let mut initial_ids = vec![0; weights.len()];
     // let total_weight = weights.iter().sum::<f64>();
     // let weight_per_part = total_weight / num_parts as f64;
     let max_expansion_per_pass = 20;
@@ -54,6 +58,92 @@ pub fn graph_growth(weights: &[f64], adjacency: CsMatView<f64>, num_parts: usize
             }
         }
     }
+}
+
+/// Graph Growth algorithm
+///
+/// A topologic algorithm that generates a partition from a topologic mesh.
+/// Given a number k of parts, the algorithm selects k nodes randomly and assigns them to a different part.
+/// Then, at each iteration, each part is expanded to neighbor nodes that are not yet assigned to a part
+///
+/// # Example
+///
+/// ```rust
+/// use coupe::Point2D;
+/// use coupe::TopologicPartitioner;
+/// use coupe::partition::Partition;
+/// use sprs::CsMat;
+///
+/// // +--+--+--+
+/// // |  |  |  |
+/// // +--+--+--+
+///
+/// let points = vec![
+///      Point2D::new(0., 0.),
+///      Point2D::new(1., 0.),
+///      Point2D::new(2., 0.),
+///      Point2D::new(3., 0.),
+///      Point2D::new(0., 1.),
+///      Point2D::new(1., 1.),
+///      Point2D::new(2., 1.),
+///      Point2D::new(3., 1.),
+///  ];
+///
+///  let weights = vec![1.; 8];
+///
+///  let mut adjacency = CsMat::empty(sprs::CSR, 8);
+///  adjacency.reserve_outer_dim(8);
+///  eprintln!("shape: {:?}", adjacency.shape());
+///  adjacency.insert(0, 1, 1.);
+///  adjacency.insert(1, 2, 1.);
+///  adjacency.insert(2, 3, 1.);
+///  adjacency.insert(4, 5, 1.);
+///  adjacency.insert(5, 6, 1.);
+///  adjacency.insert(6, 7, 1.);
+///  adjacency.insert(0, 4, 1.);
+///  adjacency.insert(1, 5, 1.);
+///  adjacency.insert(2, 6, 1.);
+///  adjacency.insert(3, 7, 1.);
+///  
+///  // symmetry
+///  adjacency.insert(1, 0, 1.);
+///  adjacency.insert(2, 1, 1.);
+///  adjacency.insert(3, 2, 1.);
+///  adjacency.insert(5, 4, 1.);
+///  adjacency.insert(6, 5, 1.);
+///  adjacency.insert(7, 6, 1.);
+///  adjacency.insert(4, 0, 1.);
+///  adjacency.insert(5, 1, 1.);
+///  adjacency.insert(6, 2, 1.);
+///  adjacency.insert(7, 3, 1.);
+///
+/// let gg = coupe::GraphGrowth::new(2);
+///
+/// let _partition = gg.partition(points.as_slice(), &weights, adjacency.view());
+/// ```
+#[derive(Debug, Clone, Copy)]
+pub struct GraphGrowth {
+    pub part_count: usize,
+}
 
-    initial_ids
+impl<'a, W> crate::Partition<(CsMatView<'a, f64>, W)> for GraphGrowth
+where
+    W: AsRef<[f64]>,
+{
+    type Metadata = ();
+    type Error = std::convert::Infallible;
+
+    fn partition(
+        &mut self,
+        part_ids: &mut [usize],
+        (adjacency, weights): (CsMatView<f64>, W),
+    ) -> Result<Self::Metadata, Self::Error> {
+        graph_growth(
+            part_ids,
+            weights.as_ref(),
+            adjacency.view(),
+            self.part_count,
+        );
+        Ok(())
+    }
 }