Work on week 3 assignment 2

src/dijkstra.rs

@@ -1,4 +1,8 @@
-use crate::util::DirectedWeightedGraph;
+#[derive(Debug)]
+pub struct DirectedWeightedGraph {
+    pub nodes: Vec<Vec<(usize, usize)>>,
+    pub distance: Vec<usize>,
+}
 
 pub fn dijkstra(g: &mut DirectedWeightedGraph) -> () {
     let mut x: Vec<usize> = vec![0];

src/k_clustering.rs

@@ -1,10 +1,63 @@
-use crate::prims::WeightedGraph;
+use std::collections::HashSet;
-use std::convert::TryInto;
 
-pub fn k_clustering(graph: &WeightedGraph) -> i32 {
+#[derive(Debug, Clone, Copy)]
-	for vertex in graph {
+pub struct Edge {
-		println!("{:?}", vertex.edges.len());
+    pub weight: i32,
-	}
+    pub source_id: usize,
-	graph.len().try_into().unwrap()
+    pub target_id: usize,
 }
 
+pub struct WeightedGraph {
+    pub n_nodes: usize,
+    pub cluster: Vec<usize>,
+    pub edges: Vec<Edge>,
+}
+
+pub fn k_clustering(graph: &mut WeightedGraph) -> usize {
+    let k: usize = 4;
+
+    let mut cluster_count = graph.n_nodes;
+    let mut clusters: Vec<Vec<usize>> = (0..graph.n_nodes).map(|x| vec![x]).collect();
+    println!("{:?}", clusters);
+
+    // Sort edges by decreasing weight
+    graph
+        .edges
+        .sort_by(|a, b| b.weight.partial_cmp(&a.weight).unwrap());
+
+    for edge in &graph.edges {
+        let ca_id = graph.cluster[edge.source_id];
+        let cb_id = graph.cluster[edge.target_id];
+
+        if ca_id == cb_id {
+            continue; // Nodes are already in the same cluster
+        }
+
+        let ca: &mut Vec<usize> = &mut clusters[ca_id];
+        let cb = clusters[cb_id].clone();
+
+        for node in cb {
+            ca.push(node);
+        }
+
+        // clusters[ca].append(&mut clusters[cb]);
+
+        // clusters[]
+        // clusters[cluster_target].clear();
+        // graph.cluster[edge.target_id]= cluster_source;
+
+        cluster_count -= 1;
+
+        if cluster_count <= k {
+            break;
+        }
+    }
+
+    for cluster in &clusters {
+        if cluster.len() > 0 {
+            // println!("{:?}", cluster);
+        }
+    }
+
+    graph.n_nodes
+}

src/main.rs

@@ -1,6 +1,7 @@
 mod dijkstra;
 mod heap;
 mod jobs;
+mod k_clustering;
 mod merge_sort;
 mod min_cut;
 mod prims;
@@ -8,18 +9,17 @@ mod quick_sort;
 mod ssc;
 mod two_sum;
 mod util;
-mod k_clustering;
 
 use crate::dijkstra::dijkstra;
 use crate::heap::heap;
 use crate::jobs::{jobs_1, jobs_2};
+use crate::k_clustering::k_clustering;
 use crate::merge_sort::merge_sort_inversions;
 use crate::min_cut::min_cut;
 use crate::prims::prims;
 use crate::quick_sort::quick_sort;
 use crate::ssc::ssc;
 use crate::two_sum::find_two_sums;
-use crate::k_clustering::k_clustering;
 use std::cmp::min;
 
 #[allow(dead_code)]
@@ -96,7 +96,7 @@ fn c3a1() {
     let mut jobs = util::read_jobs("data/c3a1_jobs.txt").unwrap();
     let r1 = jobs_1(&mut jobs);
     let r2 = jobs_2(&mut jobs);
-    let g = util::read_weighted_graph("data/c3a1_edges.txt").unwrap();
+    let g = util::read_weighted_graph_prims("data/c3a1_edges.txt").unwrap();
     let r3 = prims(&g);
     println!("r1 = {}; r2 = {}; r3 = {} ", r1, r2, r3);
 
@@ -105,8 +105,8 @@ fn c3a1() {
 
 #[allow(dead_code)]
 fn c3a2() {
-	let graph = util::read_weighted_graph("data/c3a2_clustering.txt").unwrap();
+    let mut graph = util::read_weighted_graph_clustering("data/c3a2_clustering.txt").unwrap();
-	let r1 = k_clustering(&graph);
+    let r1 = k_clustering(&mut graph);
     println!("r1 = {:?}", r1);
 }
 

src/min_cut.rs

@@ -1,7 +1,12 @@
-use crate::util::Graph;
 use rand::Rng;
 use std::convert::TryInto;
 
+#[derive(Debug, Clone)]
+pub struct Graph {
+    pub nodes: Vec<u32>,
+    pub edges: Vec<(u32, u32)>,
+}
+
 pub fn min_cut(mut g: Graph) -> u32 {
     let mut rng = rand::thread_rng();
     // println!("min_cut({:?})\n", g);

src/ssc.rs

@@ -1,6 +1,13 @@
-use crate::util::DirectedGraph;
 use std::collections::HashMap;
 
+#[derive(Debug)]
+pub struct DirectedGraph {
+    pub nodes: Vec<Vec<usize>>,
+    pub explored: Vec<bool>,
+    pub time: Vec<usize>,
+    pub leader: Vec<usize>,
+}
+
 fn dfs(g: &mut DirectedGraph, node: usize, time: &mut usize) -> () {
     let mut nodes: Vec<(usize, usize)> = vec![(node, 0)];
     g.explored[node] = true;

src/util.rs

@@ -1,30 +1,13 @@
-use crate::jobs::{Job, Jobs};
+use crate::jobs;
-use crate::prims::{Edge, Vertex, WeightedGraph};
+use crate::k_clustering;
+use crate::min_cut;
+use crate::prims;
+use crate::ssc;
 use std::fs::File;
 use std::io;
 use std::io::{BufRead, BufReader, Error, ErrorKind};
 use std::vec::Vec;
 
-#[derive(Debug, Clone)]
-pub struct Graph {
-    pub nodes: Vec<u32>,
-    pub edges: Vec<(u32, u32)>,
-}
-
-#[derive(Debug)]
-pub struct DirectedGraph {
-    pub nodes: Vec<Vec<usize>>,
-    pub explored: Vec<bool>,
-    pub time: Vec<usize>,
-    pub leader: Vec<usize>,
-}
-
-#[derive(Debug)]
-pub struct DirectedWeightedGraph {
-    pub nodes: Vec<Vec<(usize, usize)>>,
-    pub distance: Vec<usize>,
-}
-
 pub fn read_to_vector(path: &str) -> Result<Vec<i64>, io::Error> {
     let file = File::open(path)?;
     let br = BufReader::new(file);
@@ -40,8 +23,8 @@ pub fn read_to_vector(path: &str) -> Result<Vec<i64>, io::Error> {
     Ok(v)
 }
 
-pub fn read_to_graph(path: &str) -> Result<Graph, io::Error> {
+pub fn read_to_graph(path: &str) -> Result<min_cut::Graph, io::Error> {
-    let mut g = Graph {
+    let mut g = min_cut::Graph {
         nodes: vec![],
         edges: vec![],
     };
@@ -84,16 +67,18 @@ fn get_node_size(path: &str) -> Result<usize, io::Error> {
     Ok(node_size)
 }
 
-pub fn read_to_directed_graph(path: &str) -> Result<(DirectedGraph, DirectedGraph), io::Error> {
+pub fn read_to_directed_graph(
+    path: &str,
+) -> Result<(ssc::DirectedGraph, ssc::DirectedGraph), io::Error> {
     let nodes: usize = get_node_size(path).unwrap();
-    let mut g = DirectedGraph {
+    let mut g = ssc::DirectedGraph {
         nodes: vec![vec![]; nodes],
         explored: vec![false; nodes],
         time: vec![0; nodes],
         leader: vec![0; nodes],
     };
 
-    let mut g_dash = DirectedGraph {
+    let mut g_dash = ssc::DirectedGraph {
         nodes: vec![vec![]; nodes],
         explored: vec![false; nodes],
         time: vec![0; nodes],
@@ -116,9 +101,11 @@ pub fn read_to_directed_graph(path: &str) -> Result<(DirectedGraph, DirectedGrap
     Ok((g, g_dash))
 }
 
-pub fn read_to_directed_weighted_graph(path: &str) -> Result<DirectedWeightedGraph, io::Error> {
+pub fn read_to_directed_weighted_graph(
+    path: &str,
+) -> Result<crate::dijkstra::DirectedWeightedGraph, io::Error> {
     let nodes: usize = get_node_size(path).unwrap();
-    let mut g = DirectedWeightedGraph {
+    let mut g = crate::dijkstra::DirectedWeightedGraph {
         nodes: vec![vec![]; nodes],
         distance: vec![1000000; nodes], // initial distance based on instructions
     };
@@ -141,7 +128,7 @@ pub fn read_to_directed_weighted_graph(path: &str) -> Result<DirectedWeightedGra
     Ok(g)
 }
 
-pub fn read_jobs(path: &str) -> Result<Jobs, io::Error> {
+pub fn read_jobs(path: &str) -> Result<jobs::Jobs, io::Error> {
     let mut jobs = Vec::new();
     let file = File::open(path)?;
     let br = BufReader::new(file);
@@ -152,7 +139,7 @@ pub fn read_jobs(path: &str) -> Result<Jobs, io::Error> {
         let mut nodes = line.split_whitespace();
         let weight = nodes.next().unwrap().parse().unwrap();
         let length = nodes.next().unwrap().parse().unwrap();
-        let job = Job {
+        let job = jobs::Job {
             weight: weight,
             length: length,
         };
@@ -162,7 +149,7 @@ pub fn read_jobs(path: &str) -> Result<Jobs, io::Error> {
     Ok(jobs)
 }
 
-pub fn read_weighted_graph(path: &str) -> Result<WeightedGraph, io::Error> {
+pub fn read_weighted_graph_prims(path: &str) -> Result<prims::WeightedGraph, io::Error> {
     let mut g = Vec::new();
     let file = File::open(path)?;
     let br = BufReader::new(file);
@@ -173,7 +160,7 @@ pub fn read_weighted_graph(path: &str) -> Result<WeightedGraph, io::Error> {
     // let n_edges: usize = fields.next().unwrap().parse().unwrap();
 
     for i in 0..n_nodes {
-        let node = Vertex {
+        let node = prims::Vertex {
             id: i,
             edges: vec![],
         };
@@ -187,14 +174,14 @@ pub fn read_weighted_graph(path: &str) -> Result<WeightedGraph, io::Error> {
         let id_b: usize = nodes.next().unwrap().parse::<usize>().unwrap() - 1;
         let weight = nodes.next().unwrap().parse().unwrap();
 
-        let edge = Edge {
+        let edge = prims::Edge {
             weight: weight,
             source_id: id_a,
             target_id: id_b,
         };
         g[id_a].edges.push(edge);
 
-        let edge = Edge {
+        let edge = crate::prims::Edge {
             weight: weight,
             source_id: id_b,
             target_id: id_a,
@@ -204,3 +191,35 @@ pub fn read_weighted_graph(path: &str) -> Result<WeightedGraph, io::Error> {
 
     Ok(g)
 }
+
+pub fn read_weighted_graph_clustering(
+    path: &str,
+) -> Result<k_clustering::WeightedGraph, io::Error> {
+    let file = File::open(path)?;
+    let mut lines = BufReader::new(file).lines();
+    let line = lines.next().unwrap().unwrap();
+    let n_nodes: usize = line.parse().unwrap();
+
+    let mut g = k_clustering::WeightedGraph {
+        n_nodes: n_nodes,
+        cluster: (0..n_nodes).collect(),
+        edges: Vec::new(),
+    };
+
+    for line in lines {
+        let line = line?;
+        let mut nodes = line.split_whitespace();
+        let id_a: usize = nodes.next().unwrap().parse::<usize>().unwrap() - 1;
+        let id_b: usize = nodes.next().unwrap().parse::<usize>().unwrap() - 1;
+        let weight = nodes.next().unwrap().parse().unwrap();
+
+        let edge = k_clustering::Edge {
+            weight: weight,
+            source_id: id_a,
+            target_id: id_b,
+        };
+        g.edges.push(edge)
+    }
+
+    Ok(g)
+}