checkpoint 2025-08-27

README.md

@@ -7,36 +7,36 @@
 - Create a custom to_graph method which displays a maxflow graph
 
 TODOs
-- [ ] Implementation of Algos:
+- [x] Implementation of Algos:
     - [x] Ford-Fulkersson (DFS zur Berechnung des flusserhöhenden/augmentierenden Pfads)
     - [x] Edmonds-Karp (BFS zur Berechnung des flusserhöhenden/augmnetierenden Pfads)
     - [x] Dinic
-    - [ ] Goldberg-Tarjan/Preflow-Push
-- [ ] Step-by-step implementation for all algos
+    - [x] Goldberg-Tarjan/Preflow-Push
+- [x] Step-by-step implementation for all algos
     - [x] Ford-Fulkerson
     - [x] Edmonds-Karp
     - [x] Dinic
-    - [ ] Goldberg-Tarjan/Preflow-Push
+    - [x] Goldberg-Tarjan/Preflow-Push
 - [x] Mark edges which have active flows with a color
 - [x] Move GUI Graph conversion to a trait of StableGraph
-- [ ] Add graph positioning strategy which looks "nicer"#
+- [ ] Add graph positioning strategy which looks "nicer"
     - [x] Only insert nodes which are at least a distance of 40 away (default)
     - [ ] Pseudo-random node positioning strategy
-- [ ] Handle residual edges properly
+- [x] Handle residual edges properly
     - [x] Add display option for residual edges
 - [x] Only show active flows (filter all edges with f=0)
-- [ ] Show normal vs residual graph
+- [x] Show normal vs residual graph -> not needed, residual graph is shown by default
 - [x] When increasing flows, handle residual path
-- [ ] Add unit tests
-    - [ ] With small problems to prove correctness
-    - [ ] For Benchmarking the algos
-    - [ ] Check validity of the generated flows (incoming flows = outgoing flows; flow <= capacity)
-- [ ] Add info display pane
+- [x] Add unit tests
+    - [x] With small problems to prove correctness
+    - [x] For Benchmarking the algos
+    - [x] Check validity of the generated flows (incoming flows = outgoing flows; flow <= capacity)
+- [x] Add info display pane
     - [x] is valid flow? (add trait to graph)
     - [x] current total flow (add trait to calculate)
-    - [ ] number of steps
-- [ ] implement PartialEq for StableGraph (not really possible -> how do you compare graphs?)
-- [ ] Step-by-step vizualisation with choosable time delay
+    - [x] number of steps (is implemented for stepwise)
+- [x] implement PartialEq for StableGraph (not really possible -> how do you compare graphs?) -> implemented a prune_zero trait & compare node/edge weights for same index
+- [x] Step-by-step vizualisation with choosable time delay
 - [ ] Dinic: add GUI options to show Layer Graph and Blocking flow
 - [ ] Goldberg-Tarjan: show distance labels at nodes
 - [x] change GUI colors to accomodate color-blindness (blue-yellow rather than red-green)
@@ -92,3 +92,10 @@ note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
 thread '<unnamed>' panicked at src/algorithms/goldberg_tarjan.rs:109:238:
 No distance label found
 note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
+
+# Code erklären
+
+- Graph generieren (random_generator.rs)
+- GUI, Custom Layout (main.rs, layout.rs)
+- Graph Hilfsfunktionen (graph.rs)
+- Algorithmen (ford_fulkerson.rs, edmonds_karp.rs, dinic.rs, goldberg_tarjan.rs)

src/algorithms/dinic.rs

@@ -82,7 +82,6 @@ impl Dinic {
                     visited.visit(neighbor);
                     let mut new_path = path.clone();
                     new_path.push(neighbor);
-                    // TODO: is this right?
                     if neighbor == self.sink {
                         return Some(new_path);
                     } else {
@@ -113,15 +112,7 @@ impl MaxflowAlgorithm for Dinic {
     
             // increase flow with bottleneck capacity along the augmenting path
             for edge in edges {
-                // get source and target of edge
-                let (source, target) = self.residual_graph.edge_endpoints(edge).expect("edge not connected");
-                // increase flow of the forward edge with the calculated bottleneck value
-                let weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(edge).expect("edge not found");
-                (*weight).0 += bottleneck_capacity;
-                // increase capacity of the residual edge of the with the calculated bottleneck value
-                let residual_edge = self.residual_graph.find_edge(target, source).expect("residual edge not found");
-                let residual_weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(residual_edge).expect("edge not found");
-                (*residual_weight).1 += bottleneck_capacity;
+                self.residual_graph.add_flow(edge, bottleneck_capacity);
             }
             false
         } else {

src/algorithms/edmonds_karp.rs

@@ -65,15 +65,7 @@ impl MaxflowAlgorithm for EdmondsKarp {
 
             // increase flow with bottleneck capacity along the augmenting path
             for edge in edges {
-                // get source and target of edge
-                let (source, target) = self.residual_graph.edge_endpoints(edge).expect("edge not connected");
-                // increase flow of the forward edge with the calculated bottleneck value
-                let weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(edge).expect("edge not found");
-                (*weight).0 += bottleneck_capacity;
-                // increase capacity of the residual edge of the with the calculated bottleneck value
-                let residual_edge = self.residual_graph.find_edge(target, source).expect("residual edge not found");
-                let residual_weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(residual_edge).expect("edge not found");
-                (*residual_weight).1 += bottleneck_capacity;
+                self.residual_graph.add_flow(edge, bottleneck_capacity);
             }
             false
         } else {

src/algorithms/ford_fulkerson.rs

@@ -37,7 +37,6 @@ impl FordFulkerson {
                     visited.visit(neighbor);
                     let mut new_path = path.clone();
                     new_path.push(neighbor);
-                    // TODO: is this right?
                     if neighbor == self.sink {
                         return Some(new_path);
                     } else {
@@ -65,15 +64,7 @@ impl MaxflowAlgorithm for FordFulkerson {
 
             // increase flow with bottleneck capacity along the augmenting path
             for edge in edges {
-                // get source and target of edge
-                let (source, target) = self.residual_graph.edge_endpoints(edge).expect("edge not connected");
-                // increase flow of the forward edge with the calculated bottleneck value
-                let weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(edge).expect("edge not found");
-                (*weight).0 += bottleneck_capacity;
-                // increase capacity of the residual edge of the with the calculated bottleneck value
-                let residual_edge = self.residual_graph.find_edge(target, source).expect("residual edge not found");
-                let residual_weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(residual_edge).expect("edge not found");
-                (*residual_weight).1 += bottleneck_capacity;
+                self.residual_graph.add_flow(edge, bottleneck_capacity);
             }
             false
         } else {

src/algorithms/goldberg_tarjan.rs

@@ -97,13 +97,11 @@ impl MaxflowAlgorithm for GoldbergTarjan {
         // if the distance labels were not already computed, compute them now
         if self.distance_label == None {
             self.compute_distances();
-            //println!("distance labeling: {:?}", self.distance_label);
         }
         
         // Main loop: while there is an active node, continue
         if let Some((node, excess)) = self.active_node() {
             // find all outgoing edges with available capacity
-            //println!("active node {:?} source {:?} sink {:?}", node, self.source, self.sink);
             let valid_edges: Vec<petgraph::prelude::EdgeIndex> = self.residual_graph
                 .edges_directed(node, Direction::Outgoing)
                 .filter(|e| (e.weight().1 - e.weight().0) > 0 )
@@ -112,20 +110,11 @@ impl MaxflowAlgorithm for GoldbergTarjan {
                 .collect::<Vec<_>>();
             if valid_edges.len() > 0 {
                 // node has valid edges -> push (move min[excess, capacity] to first valid edge)
-                //println!("push");
                 let edge = valid_edges[0];
-                // let (source, target) = self.residual_graph.edge_endpoints(edge).expect("edge not connected");
                 let available_capacity = self.residual_graph.edge_weight(edge).expect("Invalid edge index").1 - self.residual_graph.edge_weight(edge).expect("Invalid edge index").0;
                 let additional_flow = min(excess, available_capacity);
                 self.residual_graph.add_flow(edge, additional_flow);
                 
-                // // increase flow of the forward edge with the calculated bottleneck value
-                // let weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(edge).expect("edge not found");
-                // (*weight).0 += additional_flow;
-                // // increase capacity of the residual edge of the with the calculated bottleneck value
-                // let residual_edge = self.residual_graph.find_edge(target, source).expect("residual edge not found");
-                // let residual_weight: &mut (u64, u64) = self.residual_graph.edge_weight_mut(residual_edge).expect("edge not found");
-                // (*residual_weight).1 += additional_flow;
             } else {
                 // node has no valid edges -> relabel (increase node distance label to min[neighbors] + 1)
                 let neighbors = self.residual_graph
@@ -134,8 +123,8 @@ impl MaxflowAlgorithm for GoldbergTarjan {
                     .sorted_by_key(|e| self.distance_label.as_ref().expect("distance labelling not present").get(&e.target()))
                     .map(|e| e.target())
                     .collect::<Vec<_>>();
+                assert!(neighbors.len() > 0);
                 let lowest_distance = self.distance_label.as_ref().expect("distance labelling not present").get(&neighbors[0]).expect("No distance label found").clone();
-                //println!("relabel {} + 1 (index: {:?})", lowest_distance, node);
                 self.distance_label.as_mut().expect("distance labelling not present").insert(node, lowest_distance + 1);
             }
             false

src/graph.rs

@@ -76,9 +76,9 @@ pub trait FlowGraph {
 
     fn reset_flow(&mut self);
 
-    fn valid_flow(&self, source: NodeIndex, sink: NodeIndex) -> bool;
+    fn prune_zero(&self) -> StableGraph<(f32, f32), (u64, u64)>;
 
-    fn saturated_cut(&self, source: NodeIndex, sink: NodeIndex) -> bool;
+    fn valid_flow(&self, source: NodeIndex, sink: NodeIndex) -> bool;
 
     fn total_flow(&self, source: NodeIndex, sink: NodeIndex) -> u64;
 
@@ -153,6 +153,19 @@ impl FlowGraph for StableGraph<(f32, f32), (u64, u64)> {
         }
     }
 
+    // removes all edges where the current flow is zero & returns a pruned graph
+    fn prune_zero(&self) -> StableGraph<(f32, f32), (u64, u64)> {
+        let mut zero_graph = self.clone();
+        for edge in zero_graph.edge_indices().collect::<Vec<_>>() {
+            let weight = zero_graph.edge_weight(edge).expect("edge not found");
+            if weight.0 == 0 {
+                zero_graph.remove_edge(edge);
+            }
+        }
+
+        zero_graph
+    }
+
     // check if flow is valid:
     // - for every edge, the flow doesn't exceed the capacity
     // - for every node, the amount of incoming flows is equal to the amount of outgoing flows
@@ -183,23 +196,6 @@ impl FlowGraph for StableGraph<(f32, f32), (u64, u64)> {
         true
     }
 
-    // checks if there exists a saturated cut in the graph (a bip)
-    fn saturated_cut(&self, source: NodeIndex, sink: NodeIndex) -> bool {
-        let mut s = HashSet::new();
-        let mut t = HashSet::new();
-
-        for node in self.node_indices().into_iter().collect::<Vec<_>>() {
-            if has_path_connecting(self, source, node, None) {
-                s.insert(node);
-            } else {
-                t.insert(node);
-            }
-        }
-
-        return true;
-    }
-
-    // TODO: assert that incoming flows at sink are equal to outgoing flows at source (otherwise return 0)
     fn total_flow(&self, source: NodeIndex, sink: NodeIndex) -> u64 {
         let outgoing_flows_source: u64 = self.edges_directed(source, Direction::Outgoing).map(|e| e.weight().0).sum();
         let incoming_flows_source: u64 = self.edges_directed(source, Direction::Incoming).map(|e| e.weight().0).sum();
@@ -207,7 +203,9 @@ impl FlowGraph for StableGraph<(f32, f32), (u64, u64)> {
         let incoming_flows_sink: u64 = self.edges_directed(sink, Direction::Incoming).map(|e| e.weight().0).sum();
         let total_flow_source = outgoing_flows_source - incoming_flows_source;
         let total_flow_sink = incoming_flows_sink - outgoing_flows_sink;
-        assert!(total_flow_sink == total_flow_source);
+        if total_flow_sink != total_flow_source {
+            return 0;
+        }
         return total_flow_source;
     }
 
@@ -233,22 +231,38 @@ impl FlowGraph for StableGraph<(f32, f32), (u64, u64)> {
         self.edge_weight(edge).expect("edge not found").1 - self.edge_weight(edge).expect("edge not found").0
     }
     
-    fn add_flow(&mut self, edge: EdgeIndex, flow: u64) {
-        // search for reverse edge and subtract existing flow if possible
-        let (source, target) = self.edge_endpoints(edge).expect("edge not connected");
-        let residual_edge = self.find_edge(target, source).expect("residual edge not found");
-        let residual_weight: &mut (u64, u64) = self.edge_weight_mut(residual_edge).expect("residual edge not found");
-        let forward_flow = i128::from(flow) - i128::from((*residual_weight).0);
-        // subtract minimum of additional_flow and residual_weight
-        if residual_weight.0 > 0 {
-            (*residual_weight).0 -= min(residual_weight.0, flow);
+    // adds the specified flow to the edge of a residual graph
+    fn add_flow(&mut self, forward_edge: EdgeIndex, flow: u64) {
+        // search for reverse edge
+        let (source, target) = self.edge_endpoints(forward_edge).expect("edge not connected");
+        let reverse_edge = self.find_edge(target, source).expect("reverse edge not found");
+        
+        // calculate how much flow needs to be added on the reverse edge
+        let current_reverse_flow = self.edge_weight(reverse_edge).expect("reverse erge not found").0;
+        // maximum flow we can subtract from reverse edge
+        let reverse_flow = min(current_reverse_flow, flow);
+        let forward_flow = flow - reverse_flow;
+        if reverse_flow > 0 {
+            // decrease reverse flow
+            let reverse_weight: &mut (u64, u64) = self.edge_weight_mut(reverse_edge).expect("reverse edge not found");
+            (*reverse_weight).0 -= reverse_flow;
+            assert!(reverse_weight.0 <= reverse_weight.1);
+            // decrease forward capacity 
+            let forward_weight: &mut (u64, u64) = self.edge_weight_mut(forward_edge).expect("edge not found");
+            (*forward_weight).1 -= reverse_flow;
+            assert!(forward_weight.0 <= forward_weight.1);
         }
-        assert!((*residual_weight).0 <= (*residual_weight).1);
+
         // add remaining flow to forward edge
-        let forward_weight: &mut (u64, u64) = self.edge_weight_mut(edge).expect("edge not found");
         if forward_flow > 0 {
-            (*forward_weight).0 += u64::try_from(forward_flow).expect("error casting flow to u64");
+            // increase forward flow
+            let forward_weight: &mut (u64, u64) = self.edge_weight_mut(forward_edge).expect("edge not found");
+            (*forward_weight).0 += forward_flow;
+            assert!(forward_weight.0 <= forward_weight.1);
+            // increase reverse capacity
+            let reverse_weight: &mut (u64, u64) = self.edge_weight_mut(reverse_edge).expect("reverse edge not found");
+            (*reverse_weight).1 += forward_flow;
+            assert!(reverse_weight.0 <= reverse_weight.1);
         }
-        assert!((*forward_weight).0 <= (*forward_weight).1);
     }
 }

src/layout.rs

@@ -30,9 +30,9 @@ impl<E: Clone> From<EdgeProps<E>> for CustomEdgeShape {
             label_text: props.label,
 
             width: 1.,
-            tip_size: 10.,
-            tip_angle: std::f32::consts::TAU / 30.,
-            curve_size: 15.,
+            tip_size: 6.,
+            tip_angle: std::f32::consts::TAU / 20.,
+            curve_size: 10.,
             loop_size: 3.,
         }
     }

src/main.rs

@@ -27,6 +27,7 @@ pub struct MaxflowApp {
     display_active_flows: bool,
     display_layer_graph: bool,
     algorithm_finished: bool,
+    num_steps: u64,
     test_thread: Option<JoinHandle<String>>,
     test_results: String,
     test_results_open: bool,
@@ -48,6 +49,7 @@ impl MaxflowApp {
             display_active_flows: false,
             display_layer_graph: false,
             algorithm_finished: false,
+            num_steps: 0,
             test_thread: None,
             test_results: String::default(),
             test_results_open: false,
@@ -61,6 +63,8 @@ impl MaxflowApp {
     fn reset_state(&mut self) {
         // undo finished run
         self.algorithm_finished = false;
+        // set steps to zero
+        self.num_steps = 0;
         // reinitialize the current graph from the problem
         self.current_graph = self.problem.g.clone();
         // assign new maxflow problem to the graph
@@ -120,21 +124,25 @@ impl MaxflowApp {
         match &mut self.algorithm {
             MaxflowAlgorithmEnum::FordFulkerson(x) => {
                 let finished = x.step();
+                self.num_steps += 1;
                 self.current_graph = x.graph();
                 finished
             },
             MaxflowAlgorithmEnum::EdmondsKarp(x) => {
                 let finished = x.step();
+                self.num_steps += 1;
                 self.current_graph = x.graph();
                 finished
             },
             MaxflowAlgorithmEnum::Dinic(x) => {
                 let finished = x.step();
+                self.num_steps += 1;
                 self.current_graph = x.graph();
                 finished
             },
             MaxflowAlgorithmEnum::GoldbergTarjan(x) => {
                 let finished = x.step();
+                self.num_steps += 1;
                 self.current_graph = x.graph();
                 finished
             }
@@ -159,7 +167,6 @@ impl App for MaxflowApp {
                             ui.add(egui::DragValue::new(&mut self.node_count).range(2..=50));
                             ui.label("maximum capacity");
                             ui.add(egui::DragValue::new(&mut self.max_capacity).range(1..=100));
-                            // TODO: add generation strategy (random, pseudo-random)
                             if ui.button("generate graph").clicked() {
                                 self.problem = random_generator::MaxflowProblem::new_planar_graph(self.node_count, self.max_capacity);
                                 self.reset_state();
@@ -234,6 +241,8 @@ impl App for MaxflowApp {
                             ui.label(format!("is valid flow: {}", self.current_graph.valid_flow(self.problem.s, self.problem.t)));
 
                             ui.label(format!("total flow: {}", self.current_graph.total_flow(self.problem.s, self.problem.t)));
+
+                            ui.label(format!("number of steps: {}", self.num_steps))
                         });
 
                     CollapsingHeader::new("Tests")

src/random_generator.rs

@@ -26,7 +26,7 @@ impl MaxflowProblem {
             // check if node is too close to another node (distance < 40)
             let mut too_close = true;
             let (mut x, mut y) = (0.0, 0.0);
-            // this is a poor attempt at modeling a do..while look in Rust
+            // this is a poor attempt at modeling a do..while loop in Rust
             while too_close {
                 too_close = false;
                 x = rng.gen_range(0.0..=400.0);
@@ -44,7 +44,6 @@ impl MaxflowProblem {
         // select source (s) and sink (t)
         let (s,t) = nodes.choose_multiple(&mut rng, 2).copied().collect_tuple::<(NodeIndex, NodeIndex)>().expect("not enough nodes");
 
-        // TODO: this probably takes forever...
         // iterate over all possible edges
         let mut possible_edges: Vec<(NodeIndex, NodeIndex, f32)> = Vec::new();
         for pair in nodes.clone().into_iter().combinations(2) {

src/testing.rs

@@ -12,13 +12,7 @@ fn solve_problem_all_algos(problem: &MaxflowProblem) -> (f64, f64, f64, f64) {
     let mut durations = vec![0.0; 4];
     for (i,a) in instances.iter_mut().enumerate() {
         let now = Instant::now();
-        match a {
-            MaxflowAlgorithmEnum::GoldbergTarjan(_) => { a.run(); },
-            _ => {
         a.run();
-            }
-        }
-        //a.run();
         durations[i] = now.elapsed().as_secs_f64();
 
         // check if the flow is valid
@@ -27,7 +21,6 @@ fn solve_problem_all_algos(problem: &MaxflowProblem) -> (f64, f64, f64, f64) {
 
     // check if all algorithms return the same total flow
     let total_flows: Vec<u64> = instances.iter_mut().map(|x| x.graph().total_flow(problem.s, problem.t)).collect();
-    println!("total flows: {:?}", total_flows);
     assert!(total_flows.iter().all(|&x| x == total_flows[0]), "algorithms return different total flows");
 
     return durations.into_iter().collect_tuple().unwrap();
@@ -37,6 +30,7 @@ fn run_tests(test_tuples: Vec<(u64, u64, u64)>) -> String {
     let mut response = String::new();
     
     for (problem_count, nodes, capacity) in test_tuples {
+        println!("Running test: {} times, {} nodes, {} capacity", problem_count, nodes, capacity);
         response += format!("=== Testing with problem_count={}, nodes={}, capacity={}\n", problem_count, nodes, capacity).as_str();
         let mut problems: Vec<_> = Vec::new();
         for _ in 0..problem_count {
@@ -61,10 +55,11 @@ pub fn run_small_tests() -> String {
     let test_tuples = [
         // (number of problems, number of nodes, max. capacity)
         (10, 10, 10),
+        (10, 10, 100),
+        (10, 50, 10),
+        (10, 50, 100),
         (10, 100, 10),
-        (10, 100, 100),
-        (10, 200, 10),
-        (10, 200, 100)
+        (10, 100, 100)
     ];
     return run_tests(test_tuples.into());
 }
@@ -75,13 +70,12 @@ pub fn run_large_tests() -> String {
         (10, 100, 10),
         (10, 100, 100),
         (10, 100, 1000),
-        (10, 500, 10),
-        (10, 500, 100),
-        (10, 500, 1000),
-        (10, 1000, 10),
-        (10, 1000, 100),
-        (10, 1000, 1000),
-        (10, 10000, 10)
+        (10, 200, 10),
+        (10, 200, 100),
+        (10, 200, 1000),
+        (10, 300, 10),
+        (10, 300, 100),
+        (10, 300, 1000)
     ];
     return run_tests(test_tuples.into());
 }

tests.txt

@@ -0,0 +1,54 @@
+=== Testing with problem_count=10, nodes=100, capacity=10
+Ford-Fulkerson:	    0.00019723s
+Edmonds-Karp:	    0.00017104s
+Dinic:				0.00114540s
+Goldberg-Tarjan:	0.11118784s
+
+=== Testing with problem_count=10, nodes=100, capacity=100
+Ford-Fulkerson:	    0.00044646s
+Edmonds-Karp:	    0.00030087s
+Dinic:				0.00212037s
+Goldberg-Tarjan:	0.15394399s
+
+=== Testing with problem_count=10, nodes=100, capacity=1000
+Ford-Fulkerson:	    0.00028169s
+Edmonds-Karp:	    0.00017956s
+Dinic:				0.00128019s
+Goldberg-Tarjan:	0.11455003s
+
+=== Testing with problem_count=10, nodes=200, capacity=10
+Ford-Fulkerson:	    0.00057035s
+Edmonds-Karp:	    0.00042638s
+Dinic:				0.00270890s
+Goldberg-Tarjan:	1.70483265s
+
+=== Testing with problem_count=10, nodes=200, capacity=100
+Ford-Fulkerson:	    0.00121046s
+Edmonds-Karp:	    0.00045426s
+Dinic:				0.00301752s
+Goldberg-Tarjan:	1.48397911s
+
+=== Testing with problem_count=10, nodes=200, capacity=1000
+Ford-Fulkerson:	    0.00183244s
+Edmonds-Karp:	    0.00062984s
+Dinic:				0.00411386s
+Goldberg-Tarjan:	1.49089764s
+
+=== Testing with problem_count=10, nodes=300, capacity=10
+Ford-Fulkerson:	    0.00086230s
+Edmonds-Karp:	    0.00071712s
+Dinic:				0.00423448s
+Goldberg-Tarjan:	5.84010118s
+
+=== Testing with problem_count=10, nodes=300, capacity=100
+Ford-Fulkerson:	    0.00164213s
+Edmonds-Karp:	    0.00040957s
+Dinic:				0.00322493s
+Goldberg-Tarjan:	1.97116912s
+
+=== Testing with problem_count=10, nodes=300, capacity=1000
+Ford-Fulkerson:	    0.00362413s
+Edmonds-Karp:	    0.00094858s
+Dinic:				0.00600265s
+Goldberg-Tarjan:	5.16341617s
+

tests/example_flows.rs

@@ -20,27 +20,9 @@ fn generate_small_maxflow_example() -> (StableGraph<(f32, f32), (u64, u64)>, Sta
     g.add_edge(one, two, (0,2));
     g.add_edge(two, four, (0,9));
     g.add_edge(three, t, (0,10));
-    g.add_edge(four, three, (0,6));
+    g.add_edge(four, three, (0,5)); // changed capacity to 5 to enforce a single optimal solution
     g.add_edge(four, t, (0,10));
 
-    // TODO:
-    // let mut m: StableGraph<(f32, f32), (u64, u64)> = StableGraph::new();
-    // let s = m.add_node((0., 5.));
-    // let one = m.add_node((10., 0.));
-    // let two = m.add_node((10., 10.));
-    // let three = m.add_node((20., 0.));
-    // let four = m.add_node((20., 10.));
-    // let t = m.add_node((30., 5.));
-    // m.add_edge(s, one, (10, 10));
-    // m.add_edge(s, two, (9, 10));
-    // m.add_edge(one, three, (4, 4));
-    // m.add_edge(one, four, (6, 8));
-    // m.add_edge(one, two, (0,2));
-    // m.add_edge(two, four, (9,9));
-    // m.add_edge(three, t, (9,10));
-    // m.add_edge(four, three, (5,6));
-    // m.add_edge(four, t, (10,10));
-
     let mut m = g.clone();
     m.update_edge(s, one, (10, 10));
     m.update_edge(s, two, (9, 10));
@@ -49,7 +31,7 @@ fn generate_small_maxflow_example() -> (StableGraph<(f32, f32), (u64, u64)>, Sta
     m.update_edge(one, two, (0,2));
     m.update_edge(two, four, (9,9));
     m.update_edge(three, t, (9,10));
-    m.update_edge(four, three, (5,6));
+    m.update_edge(four, three, (5,5)); // changed capacity to 5 to enforce a single optimal solution
     m.update_edge(four, t, (10,10));
 
     return (g, m, s, t);
@@ -57,11 +39,12 @@ fn generate_small_maxflow_example() -> (StableGraph<(f32, f32), (u64, u64)>, Sta
 
 fn graph_equal(one: StableGraph<(f32, f32), (u64, u64)>, other: StableGraph<(f32, f32), (u64, u64)>) -> bool {
     // ensure all edges have the same weights
-    println!("Graph 1: {:?}", one);
-    println!("Graph 2: {:?}", other);
     let edges = one.edge_indices().map(|e| e).collect::<Vec<_>>();
     for edge in edges {
         if one.edge_weight(edge).expect("edge index not found") != other.edge_weight(edge).expect("edge index not found") {
+            println!("Edge weights don't match");
+            println!("Graph 1: {:?}", one);
+            println!("Graph 2: {:?}", other);
             return false;
         }
     }
@@ -70,6 +53,9 @@ fn graph_equal(one: StableGraph<(f32, f32), (u64, u64)>, other: StableGraph<(f32
     let nodes = one.node_indices().map(|n| n).collect::<Vec<_>>();
     for node in nodes {
         if one.node_weight(node).expect("node index not found") != other.node_weight(node).expect("node index not found") {
+            println!("Node weights don't match");
+            println!("Graph 1: {:?}", one);
+            println!("Graph 2: {:?}", other);
             return false;
         }
     }
@@ -85,5 +71,38 @@ fn test_ford_fulkerson() {
     let mut  algo = FordFulkerson::from_problem(&problem);
     let solution = algo.run();
 
-    assert!(graph_equal(solution, m.residual()));
+    assert!(graph_equal(solution.prune_zero(), m.residual().prune_zero()));
+}
+
+#[test]
+fn test_edmonds_karp() {
+    let (g, m, s, t) = generate_small_maxflow_example();
+
+    let problem = MaxflowProblem::from(g, s, t);
+    let mut  algo = EdmondsKarp::from_problem(&problem);
+    let solution = algo.run();
+
+    assert!(graph_equal(solution.prune_zero(), m.residual().prune_zero()));
+}
+
+#[test]
+fn test_dinic() {
+    let (g, m, s, t) = generate_small_maxflow_example();
+
+    let problem = MaxflowProblem::from(g, s, t);
+    let mut  algo = Dinic::from_problem(&problem);
+    let solution = algo.run();
+
+    assert!(graph_equal(solution.prune_zero(), m.residual().prune_zero()));
+}
+
+#[test]
+fn test_goldberg_tarjan() {
+    let (g, m, s, t) = generate_small_maxflow_example();
+
+    let problem = MaxflowProblem::from(g, s, t);
+    let mut  algo = GoldbergTarjan::from_problem(&problem);
+    let solution = algo.run();
+
+    assert!(graph_equal(solution.prune_zero(), m.residual().prune_zero()));
 }