Start to implement K-clustering

.gitignore

@@ -17,3 +17,6 @@ algos.sublime-workspace
 # Data for the exercises. Some files are big so don't check them in.
 data/c2a4.txt
 data/c2a4.back.txt
+data/c3a2_clustering.txt
+data/c3a2_clustering_big.txt
+

src/k_clustering.rs

@@ -0,0 +1,10 @@
+use crate::prims::WeightedGraph;
+use std::convert::TryInto;
+
+pub fn k_clustering(graph: &WeightedGraph) -> i32 {
+	for vertex in graph {
+		println!("{:?}", vertex.edges.len());
+	}
+	graph.len().try_into().unwrap()
+}
+

src/main.rs

@@ -8,6 +8,7 @@ mod quick_sort;
 mod ssc;
 mod two_sum;
 mod util;
+mod k_clustering;
 
 use crate::dijkstra::dijkstra;
 use crate::heap::heap;
@@ -18,6 +19,7 @@ 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)]
@@ -103,7 +105,9 @@ fn c3a1() {
 
 #[allow(dead_code)]
 fn c3a2() {
-    println!("let's go");
+	let graph = util::read_weighted_graph("data/c3a2_clustering.txt").unwrap();
+	let r1 = k_clustering(&graph);
+	println!("r1 = {:?}", r1);
 }
 
 fn main() {