135 lines
3.5 KiB
Rust
135 lines
3.5 KiB
Rust
mod dijkstra;
|
|
mod heap;
|
|
mod jobs;
|
|
mod k_clustering;
|
|
mod k_clustering_big;
|
|
mod merge_sort;
|
|
mod min_cut;
|
|
mod prims;
|
|
mod quick_sort;
|
|
mod ssc;
|
|
mod two_sum;
|
|
mod util;
|
|
|
|
use crate::dijkstra::dijkstra;
|
|
use crate::heap::heap;
|
|
use crate::jobs::{jobs_1, jobs_2};
|
|
use crate::k_clustering::k_clustering;
|
|
use crate::k_clustering_big::k_clustering_big;
|
|
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 std::cmp::min;
|
|
|
|
#[allow(dead_code)]
|
|
fn c1a2() {
|
|
let vec = util::read_to_vector("data/c1a2.txt").unwrap();
|
|
let (_sorted, inversions) = merge_sort_inversions(vec);
|
|
println!("c1a2={:?}", inversions);
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c1a3() {
|
|
let mut vec = util::read_to_vector("data/c1a3.txt").unwrap();
|
|
let mut comp_acc: usize = 0;
|
|
quick_sort(&mut vec, &mut comp_acc);
|
|
println!("c1a3={:?}", comp_acc);
|
|
// 1: 162085, 2: 164123, 3: 138382
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c1a4() {
|
|
let g = util::read_to_graph("data/c1a4.txt").unwrap();
|
|
let mut smallest_min_cut = u32::MAX;
|
|
let iterations = g.nodes.len().pow(1);
|
|
for _ in 0..iterations {
|
|
let new_min_cut = min_cut(g.clone());
|
|
if new_min_cut < smallest_min_cut {
|
|
smallest_min_cut = new_min_cut;
|
|
}
|
|
}
|
|
println!("c1a4={:?}", smallest_min_cut);
|
|
// 17
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c2a1() {
|
|
// I have not checked in the graph file, because it has 70MB. This is a tiny test example.
|
|
let g = util::read_to_directed_graph("data/c2a1_test.txt").unwrap();
|
|
let sizes = ssc(g.0, g.1);
|
|
let max_size = min(sizes.len(), 5);
|
|
println!("{:?}", &sizes[0..max_size]);
|
|
// [434821, 968, 459, 313, 211]
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c2a2() {
|
|
let mut requested_vertices: Vec<usize> = vec![7, 37, 59, 82, 99, 115, 133, 165, 188, 197];
|
|
let mut g = util::read_to_directed_weighted_graph("data/c2a2.txt").unwrap();
|
|
dijkstra(&mut g);
|
|
for i in 0..requested_vertices.len() {
|
|
requested_vertices[i] = g.distance[requested_vertices[i] - 1];
|
|
}
|
|
println!("{:?}", requested_vertices);
|
|
// [2599, 2610, 2947, 2052, 2367, 2399, 2029, 2442, 2505, 3068]
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c2a3() {
|
|
let v = util::read_to_vector("data/c2a3.txt").unwrap();
|
|
let r = heap(&v);
|
|
println!("c2a3={:?}", r);
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c2a4() {
|
|
let mut v = util::read_to_vector("data/c2a4.txt").unwrap();
|
|
let r = find_two_sums(&mut v);
|
|
println!("c2a4={:?}", r);
|
|
// c2a4=427
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c3a1() {
|
|
// belongs to 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_prims("data/c3a1_edges.txt").unwrap();
|
|
let r3 = prims(&g);
|
|
println!("r1 = {}; r2 = {}; r3 = {} ", r1, r2, r3);
|
|
|
|
// r1 = 69119377652; r2 = 67311454237; r3 = -3612829
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c3a2() {
|
|
let mut graph = util::read_weighted_graph_clustering("data/c3a2_clustering.txt").unwrap();
|
|
let r1 = k_clustering(&mut graph);
|
|
let graph = util::read_k_cluster_big("data/c3a2_clustering_big.txt").unwrap();
|
|
let r2 = k_clustering_big(&graph);
|
|
println!("r1 = {} r2 = {}", r1, r2);
|
|
// r1 = 106 r2 = 6118
|
|
}
|
|
|
|
#[allow(dead_code)]
|
|
fn c3a3() {
|
|
println!("continue here");
|
|
}
|
|
|
|
fn main() {
|
|
// c1a2();
|
|
// c1a3();
|
|
// c1a4();
|
|
// c2a1();
|
|
// c2a2();
|
|
// c2a3();
|
|
// c2a4();
|
|
// c3a1();
|
|
// c3a2();
|
|
c3a3();
|
|
}
|