Expand description
§dynalgo
dynalgo is a tiny RUST library designed to produce animated SVG images that can illustrate graph algorithms in action.
The library focuces on providing a convenient tiny API for making animations in SVG SMIL format when developping algorithms working with graph structures.
The crate offers a basic graph structure representation. Interesting point is that each graph structure modification results in an animation rendered in SVG SMIL format into a HTML page. Several graphs animations can be rendered together in the same HTML page (side to side).
Dynalgo automatically layout nodes according to imaginary springs forces applying to them. Custom animations can be made by playing with the nodes and links graphical representations.
The Algo module provides animated algorithms applying to graph.
§Example: traversing a maze
use dynalgo::graph::Graph;
let config = "😀 0 0
😁 45 0
😂 90 0
😃 135 0
😄 180 0
😅 225 0
😆 270 0
😇 315 0
😈 0 45
😉 45 45
😊 90 45
😋 135 45
😌 180 45
😍 225 45
😎 270 45
😏 315 45
😐 0 90
😑 45 90
😒 90 90
😓 135 90
😔 180 90
😕 225 90
😖 270 90
😗 315 90
😘 0 135
😙 45 135
😚 90 135
😛 135 135
😜 180 135
😝 225 135
😞 270 135
😟 315 135
😠 0 180
😡 45 180
😢 90 180
😣 135 180
😤 180 180
😥 225 180
😦 270 180
😧 315 180
😨 0 225
😩 45 225
😪 90 225
😫 135 225
😬 180 225
😭 225 225
😮 270 225
😯 315 225
😰 0 270
😱 45 270
😲 90 270
😳 135 270
😴 180 270
😵 225 270
😶 270 270
😷 315 270
😸 0 315
😹 45 315
😺 90 315
😻 135 315
😼 180 315
😽 225 315
😾 270 315
😿 315 315
😀 - 😁 0
😁 - 😉 0
😂 - 😃 0
😂 - 😊 0
😃 - 😄 0
😄 - 😅 0
😅 - 😍 0
😆 - 😎 0
😇 - 😏 0
😈 - 😉 0
😈 - 😐 0
😊 - 😒 0
😋 - 😓 0
😌 - 😔 0
😎 - 😏 0
😎 - 😖 0
😐 - 😑 0
😐 - 😘 0
😑 - 😒 0
😒 - 😓 0
😓 - 😛 0
😔 - 😕 0
😕 - 😖 0
😕 - 😝 0
😗 - 😟 0
😘 - 😠 0
😙 - 😚 0
😚 - 😢 0
😜 - 😝 0
😝 - 😥 0
😞 - 😟 0
😞 - 😦 0
😠 - 😡 0
😡 - 😢 0
😡 - 😩 0
😢 - 😪 0
😣 - 😤 0
😤 - 😬 0
😥 - 😦 0
😥 - 😭 0
😦 - 😧 0
😦 - 😮 0
😧 - 😯 0
😨 - 😩 0
😩 - 😱 0
😪 - 😫 0
😪 - 😲 0
😫 - 😬 0
😬 - 😴 0
😮 - 😶 0
😯 - 😷 0
😰 - 😱 0
😱 - 😹 0
😳 - 😻 0
😴 - 😼 0
😵 - 😶 0
😶 - 😾 0
😷 - 😿 0
😸 - 😹 0
😹 - 😺 0
😻 - 😼 0
😼 - 😽 0
😽 - 😾 0";
let node_start = '😀';
let node_searched = '😿';
let mut freezed_maze = Graph::new();
let mut unfreezed_maze = Graph::new();
for graph in [&mut freezed_maze, &mut unfreezed_maze].iter_mut() {
graph.from_str(config);
graph.fill_node(node_start, (0, 0, 196));
graph.fill_node(node_searched, (0, 0, 196));
}
deep_first_search(
&mut freezed_maze,
node_start,
node_searched,
&mut Vec::new(),
);
unfreezed_maze.pause();
for node in unfreezed_maze.nodes() {
unfreezed_maze.unfreeze_node(node);
}
unfreezed_maze.resume();
deep_first_search(
&mut unfreezed_maze,
node_start,
node_searched,
&mut Vec::new(),
);
Graph::to_html( vec![("Dynalgo maze example", vec![&freezed_maze, &unfreezed_maze])] ).unwrap();
fn deep_first_search(
graph: &mut Graph,
node_from: char,
node_searched: char,
visited: &mut Vec<char>,
) -> bool {
visited.push(node_from);
graph.color_node(node_from, (0, 255, 0));
if node_from == node_searched {
return true;
}
let adja = &graph.adjacency_list();
let mut found = false;
for (node_to, _link) in adja.get(&node_from).unwrap() {
if visited.contains(node_to) {
continue;
}
graph.color_link(node_from, *node_to, (0, 255, 0));
found = deep_first_search(graph, *node_to, node_searched, visited);
if found {
break;
}
}
if !found {
graph.color_node(node_from, (255, 0, 0));
}
found
}§Example: viewing algorithms in action
use dynalgo::graph::Graph;
use dynalgo::algo::coloration::Coloration;
use dynalgo::algo::connectivity::Connectivity;
use dynalgo::algo::eulerian::Eulerian;
use dynalgo::algo::tree::Tree;
let mut g = Graph::new();
g.from_str(
"A 0 0, B 100 -100, C 200 -100, D 300 -100, E 300 100, F 200 150,
G 200 50, H 100 100, I 100 0, A > I, I > B, B > C, C > D, D > E, E < F, E > G, F > G, F > H,
G < H, H < I",
);
let (_c_g, _components) = Connectivity::components(&g);
assert!(_components.len() == 1);
let mut g = Graph::new();
g.from_str(
"F 0 0, E 100 0, A 250 50, H 300 80, C 0 100, J 100 100, K 0 150, B 200 150,
D 100 250, I 200 250, G 300 250, F > J, C > F, J > C, C > E, E > J, C - K, K > D, J > B,
E > A, A - H,
H > G, G > I, I > D, I > B, B > D, B > G",
);
let (scc_g, sc_components) = Connectivity::strongly_connected_components(&g);
assert!(sc_components.len() == 4);
let mut g = Graph::new();
g.from_str(
"A 0 0, B 200 0, C 0 200, D 160 160, E 250 200, F 100 300,
G 100 100, A - B 2, A - G 5,
B - G 15, B - D 10, B - E 3, C - G 5, C - D 7, C - E 10, C - F 12,
D - G 3, D - E 1, E - F 11",
);
let mst_tree = Tree::minimal_spanning_tree(&g);
let mut g = Graph::new();
g.from_str(
"A 0 0, B 100 -100, C 200 -100, D 300 -100, E 300 100, F 200 150,
G 200 50, H 100 100, I 100 0, J 100 -200, A > I, I > B, B > C, C > D, D > E, E < F,
E > G, F > G, F > H,
G < H, H < I, J - B",
);
let bfs_tree = Tree::bfs_tree(&g, 'A');
let mut g = Graph::new();
g.from_str(
"A 0 0, B 200 0, C 0 200, D 160 160, E 250 200, F 100 300,
G 100 100, A - B, A - G, B - G, B - D, B - E, C - G, C - E, C - F,
D - G, D - E, E - F",
);
let (e_g, _cycle) = Eulerian::hierholzer(&g);
let mut g = Graph::new();
g.from_str(
"A 0 0, B -80 200, C 100 100, D -100 100, E 80 200
F 0 60, G -40 160, H 40 100, I 40 160, J -40 100,
L 0 -60, M 160 100, N 120 240, O -120 240, P -160 100,
Q -160 40, R -190 20, S -130 20,
T 160 180, U 160 20, V 160 -60, W 240 180, X 240 20, Y 240 -60, Z 240 100
A - F, A - D, A - C, C - H, C - E, E - I, E - B, B - G, B - D, D - J,
J - H, J - I, F - I, F - G, H - G,
A - L, C - M, E - N, B - O, D - P,
P - Q, Q - R, Q - S,
V - X, V - Z, V - W, U - Y, U - Z, U - W, M - X, M - Y, M - W, T - X, T - Y, T - Z",
);
let (p_g, partitions) = Coloration::quick_partition(&g);
assert!(partitions.len() == 3);
Graph::to_html(vec![
("Strongly connected components (Kosaraju)", vec![&scc_g]),
("Minimal spanning tree (Prim)", vec![&mst_tree]),
("BFS tree", vec![&bfs_tree]),
("Eulerian path (Hierholzer)", vec![&e_g]),
("Color - Quick partition", vec![&p_g]),
])
.unwrap();