pub fn compute_sf<'a>(
all_links: &'a [Link],
all_stops: &HashSet<String>,
destination: &str,
od_matrix: &HashMap<String, HashMap<String, f64>>,
) -> SFResult<'a>Expand description
compute_sf computes the Spiess-Florian algorithm
Examples found in repository?
examples/paper/main.rs (line 27)
5fn main() {
6 let all_nodes: HashSet<String> = ["A", "X", "X2", "Y", "Y3", "B"]
7 .iter()
8 .map(|s| s.to_string())
9 .collect();
10 let all_links = vec![
11 Link::new("A", "B", "Line 1", 25.0, 6.0),
12 Link::new("A", "X2", "Line 2", 7.0, 6.0),
13 Link::new("X2", "X", "Line 2", 0.0, 0.0),
14 Link::new("X", "X2", "Line 2", 0.0, 6.0),
15 Link::new("X2", "Y", "Line 2", 6.0, 0.0),
16 Link::new("Y3", "Y", "Line 3", 0.0, 15.0),
17 Link::new("Y", "B", "Line 4", 10.0, 3.0),
18 Link::new("X", "Y3", "Line 3", 4.0, 15.0),
19 Link::new("Y", "Y3", "Line 3", 0.0, 15.0),
20 Link::new("Y3", "B", "Line 3", 4.0, 0.0),
21 ];
22 let destination_node = "B";
23 let od_matrix: HashMap<String, HashMap<String, f64>> = HashMap::from([(
24 "A".to_string(),
25 HashMap::from([("B".to_string(), 1.0)]),
26 )]);
27 let res = compute_sf(&all_links, &all_nodes, destination_node, &od_matrix);
28 println!("Optimal strategy:");
29 println!("\tNode labels:");
30 for (node_id, node_label) in &res.strategy.labels {
31 println!("\t\tu_{{i}} = {}: {:.6}", node_id, node_label);
32 }
33 println!("\tNodes probablities:");
34 for (node_id, freq) in &res.strategy.freqs {
35 println!("\t\tf_{{i}} = {}: {:.6}", node_id, freq);
36 }
37 println!("\tAttractive links set:");
38 for link in &res.strategy.a_set {
39 println!("\t\t a = (i, j) = ({}, {})", link.from_node, link.to_node);
40 }
41 println!("Volumes:");
42 println!("\tLinks volumes:");
43 for (from_node, to_map) in &res.volumes.links {
44 for (to_node, volume) in to_map {
45 println!("\t\tv_{{i, j}} = ({}, {}): {:.6}", from_node, to_node, volume);
46 }
47 }
48 println!("\tNodes volumes:");
49 for (node_id, volume) in &res.volumes.nodes {
50 println!("\t\tv_{{i}} = {}: {:.6}", node_id, volume);
51 }
52}