Style improvements

1 files changed, 132 insertions, 141 deletions

diff --git a/src/rpc/graph_algo.rs b/src/rpc/graph_algo.rs
index 5bd6cc51..1e4a819b 100644
--- a/src/rpc/graph_algo.rs
+++ b/src/rpc/graph_algo.rs
@@ -6,33 +6,33 @@ use std::cmp::{max, min};
 use std::collections::HashMap;
 use std::collections::VecDeque;
 
-///Vertex data structures used in all the graphs used in layout.rs.
-///usize parameters correspond to node/zone/partitions ids.
-///To understand the vertex roles below, please refer to the formal description
-///of the layout computation algorithm.
+/// Vertex data structures used in all the graphs used in layout.rs.
+/// usize parameters correspond to node/zone/partitions ids.
+/// To understand the vertex roles below, please refer to the formal description
+/// of the layout computation algorithm.
 #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash)]
 pub enum Vertex {
 	Source,
-	Pup(usize),       //The vertex p+ of partition p
-	Pdown(usize),     //The vertex p- of partition p
-	PZ(usize, usize), //The vertex corresponding to x_(partition p, zone z)
-	N(usize),         //The vertex corresponding to node n
+	Pup(usize),       // The vertex p+ of partition p
+	Pdown(usize),     // The vertex p- of partition p
+	PZ(usize, usize), // The vertex corresponding to x_(partition p, zone z)
+	N(usize),         // The vertex corresponding to node n
 	Sink,
 }
 
-///Edge data structure for the flow algorithm.
+/// Edge data structure for the flow algorithm.
 #[derive(Clone, Copy, Debug)]
 pub struct FlowEdge {
-	cap: u32,    //flow maximal capacity of the edge
-	flow: i32,   //flow value on the edge
-	dest: usize, //destination vertex id
-	rev: usize,  //index of the reversed edge (v, self) in the edge list of vertex v
+	cap: u32,    // flow maximal capacity of the edge
+	flow: i32,   // flow value on the edge
+	dest: usize, // destination vertex id
+	rev: usize,  // index of the reversed edge (v, self) in the edge list of vertex v
 }
 
-///Edge data structure for the detection of negative cycles.
+/// Edge data structure for the detection of negative cycles.
 #[derive(Clone, Copy, Debug)]
 pub struct WeightedEdge {
-	w: i32, //weight of the edge
+	w: i32, // weight of the edge
 	dest: usize,
 }
 
@@ -40,14 +40,14 @@ pub trait Edge: Clone + Copy {}
 impl Edge for FlowEdge {}
 impl Edge for WeightedEdge {}
 
-///Struct for the graph structure. We do encapsulation here to be able to both
-///provide user friendly Vertex enum to address vertices, and to use internally usize
-///indices and Vec instead of HashMap in the graph algorithm to optimize execution speed.
+/// Struct for the graph structure. We do encapsulation here to be able to both
+/// provide user friendly Vertex enum to address vertices, and to use internally usize
+/// indices and Vec instead of HashMap in the graph algorithm to optimize execution speed.
 pub struct Graph<E: Edge> {
-	vertextoid: HashMap<Vertex, usize>,
-	idtovertex: Vec<Vertex>,
+	vertex_to_id: HashMap<Vertex, usize>,
+	id_to_vertex: Vec<Vertex>,
 
-	//The graph is stored as an adjacency list
+	// The graph is stored as an adjacency list
 	graph: Vec<Vec<E>>,
 }
 
@@ -60,22 +60,30 @@ impl<E: Edge> Graph<E> {
 			map.insert(*vert, i);
 		}
 		Graph::<E> {
-			vertextoid: map,
-			idtovertex: vertices.to_vec(),
+			vertex_to_id: map,
+			id_to_vertex: vertices.to_vec(),
 			graph: vec![Vec::<E>::new(); vertices.len()],
 		}
 	}
+
+	fn get_vertex_id(&self, v: &Vertex) -> Result<usize, String> {
+		self.vertex_to_id
+			.get(v)
+			.cloned()
+			.ok_or_else(|| format!("The graph does not contain vertex {:?}", v))
+	}
 }
 
 impl Graph<FlowEdge> {
-	///This function adds a directed edge to the graph with capacity c, and the
-	///corresponding reversed edge with capacity 0.
+	/// This function adds a directed edge to the graph with capacity c, and the
+	/// corresponding reversed edge with capacity 0.
 	pub fn add_edge(&mut self, u: Vertex, v: Vertex, c: u32) -> Result<(), String> {
-		if !self.vertextoid.contains_key(&u) || !self.vertextoid.contains_key(&v) {
-			return Err("The graph does not contain the provided vertex.".to_string());
+		let idu = self.get_vertex_id(&u)?;
+		let idv = self.get_vertex_id(&v)?;
+		if idu == idv {
+			return Err("Cannot add edge from vertex to itself in flow graph".into());
 		}
-		let idu = self.vertextoid[&u];
-		let idv = self.vertextoid[&v];
+
 		let rev_u = self.graph[idu].len();
 		let rev_v = self.graph[idv].len();
 		self.graph[idu].push(FlowEdge {
@@ -93,28 +101,22 @@ impl Graph<FlowEdge> {
 		Ok(())
 	}
 
-	///This function returns the list of vertices that receive a positive flow from
-	///vertex v.
+	/// This function returns the list of vertices that receive a positive flow from
+	/// vertex v.
 	pub fn get_positive_flow_from(&self, v: Vertex) -> Result<Vec<Vertex>, String> {
-		if !self.vertextoid.contains_key(&v) {
-			return Err("The graph does not contain the provided vertex.".to_string());
-		}
-		let idv = self.vertextoid[&v];
+		let idv = self.get_vertex_id(&v)?;
 		let mut result = Vec::<Vertex>::new();
 		for edge in self.graph[idv].iter() {
 			if edge.flow > 0 {
-				result.push(self.idtovertex[edge.dest]);
+				result.push(self.id_to_vertex[edge.dest]);
 			}
 		}
 		Ok(result)
 	}
 
-	///This function returns the value of the flow incoming to v.
+	/// This function returns the value of the flow incoming to v.
 	pub fn get_inflow(&self, v: Vertex) -> Result<i32, String> {
-		if !self.vertextoid.contains_key(&v) {
-			return Err("The graph does not contain the provided vertex.".to_string());
-		}
-		let idv = self.vertextoid[&v];
+		let idv = self.get_vertex_id(&v)?;
 		let mut result = 0;
 		for edge in self.graph[idv].iter() {
 			result += max(0, self.graph[edge.dest][edge.rev].flow);
@@ -122,12 +124,9 @@ impl Graph<FlowEdge> {
 		Ok(result)
 	}
 
-	///This function returns the value of the flow outgoing from v.
+	/// This function returns the value of the flow outgoing from v.
 	pub fn get_outflow(&self, v: Vertex) -> Result<i32, String> {
-		if !self.vertextoid.contains_key(&v) {
-			return Err("The graph does not contain the provided vertex.".to_string());
-		}
-		let idv = self.vertextoid[&v];
+		let idv = self.get_vertex_id(&v)?;
 		let mut result = 0;
 		for edge in self.graph[idv].iter() {
 			result += max(0, edge.flow);
@@ -135,19 +134,19 @@ impl Graph<FlowEdge> {
 		Ok(result)
 	}
 
-	///This function computes the flow total value by computing the outgoing flow
-	///from the source.
+	/// This function computes the flow total value by computing the outgoing flow
+	/// from the source.
 	pub fn get_flow_value(&mut self) -> Result<i32, String> {
 		self.get_outflow(Vertex::Source)
 	}
 
-	///This function shuffles the order of the edge lists. It keeps the ids of the
-	///reversed edges consistent.
+	/// This function shuffles the order of the edge lists. It keeps the ids of the
+	/// reversed edges consistent.
 	fn shuffle_edges(&mut self) {
 		let mut rng = rand::thread_rng();
 		for i in 0..self.graph.len() {
 			self.graph[i].shuffle(&mut rng);
-			//We need to update the ids of the reverse edges.
+			// We need to update the ids of the reverse edges.
 			for j in 0..self.graph[i].len() {
 				let target_v = self.graph[i][j].dest;
 				let target_rev = self.graph[i][j].rev;
@@ -156,97 +155,86 @@ impl Graph<FlowEdge> {
 		}
 	}
 
-	///Computes an upper bound of the flow on the graph
-	pub fn flow_upper_bound(&self) -> u32 {
-		let idsource = self.vertextoid[&Vertex::Source];
+	/// Computes an upper bound of the flow on the graph
+	pub fn flow_upper_bound(&self) -> Result<u32, String> {
+		let idsource = self.get_vertex_id(&Vertex::Source)?;
 		let mut flow_upper_bound = 0;
 		for edge in self.graph[idsource].iter() {
 			flow_upper_bound += edge.cap;
 		}
-		flow_upper_bound
+		Ok(flow_upper_bound)
 	}
 
-	///This function computes the maximal flow using Dinic's algorithm. It starts with
-	///the flow values already present in the graph. So it is possible to add some edge to
-	///the graph, compute a flow, add other edges, update the flow.
+	/// This function computes the maximal flow using Dinic's algorithm. It starts with
+	/// the flow values already present in the graph. So it is possible to add some edge to
+	/// the graph, compute a flow, add other edges, update the flow.
 	pub fn compute_maximal_flow(&mut self) -> Result<(), String> {
-		if !self.vertextoid.contains_key(&Vertex::Source) {
-			return Err("The graph does not contain a source.".to_string());
-		}
-		if !self.vertextoid.contains_key(&Vertex::Sink) {
-			return Err("The graph does not contain a sink.".to_string());
-		}
-
-		let idsource = self.vertextoid[&Vertex::Source];
-		let idsink = self.vertextoid[&Vertex::Sink];
+		let idsource = self.get_vertex_id(&Vertex::Source)?;
+		let idsink = self.get_vertex_id(&Vertex::Sink)?;
 
 		let nb_vertices = self.graph.len();
 
-		let flow_upper_bound = self.flow_upper_bound();
+		let flow_upper_bound = self.flow_upper_bound()?;
 
-		//To ensure the dispersion of the associations generated by the
-		//assignation, we shuffle the neighbours of the nodes. Hence,
-		//the vertices do not consider their neighbours in the same order.
+		// To ensure the dispersion of the associations generated by the
+		// assignation, we shuffle the neighbours of the nodes. Hence,
+		// the vertices do not consider their neighbours in the same order.
 		self.shuffle_edges();
 
-		//We run Dinic's max flow algorithm
+		// We run Dinic's max flow algorithm
 		loop {
-			//We build the level array from Dinic's algorithm.
+			// We build the level array from Dinic's algorithm.
 			let mut level = vec![None; nb_vertices];
 
 			let mut fifo = VecDeque::new();
 			fifo.push_back((idsource, 0));
-			while !fifo.is_empty() {
-				if let Some((id, lvl)) = fifo.pop_front() {
-					if level[id] == None {
-						//it means id has not yet been reached
-						level[id] = Some(lvl);
-						for edge in self.graph[id].iter() {
-							if edge.cap as i32 - edge.flow > 0 {
-								fifo.push_back((edge.dest, lvl + 1));
-							}
+			while let Some((id, lvl)) = fifo.pop_front() {
+				if level[id] == None {
+					// it means id has not yet been reached
+					level[id] = Some(lvl);
+					for edge in self.graph[id].iter() {
+						if edge.cap as i32 - edge.flow > 0 {
+							fifo.push_back((edge.dest, lvl + 1));
 						}
 					}
 				}
 			}
 			if level[idsink] == None {
-				//There is no residual flow
+				// There is no residual flow
 				break;
 			}
-			//Now we run DFS respecting the level array
+			// Now we run DFS respecting the level array
 			let mut next_nbd = vec![0; nb_vertices];
-			let mut lifo = VecDeque::new();
+			let mut lifo = Vec::new();
 
-			lifo.push_back((idsource, flow_upper_bound));
+			lifo.push((idsource, flow_upper_bound));
 
-			while let Some((id_tmp, f_tmp)) = lifo.back() {
-				let id = *id_tmp;
-				let f = *f_tmp;
+			while let Some((id, f)) = lifo.last().cloned() {
 				if id == idsink {
-					//The DFS reached the sink, we can add a
-					//residual flow.
-					lifo.pop_back();
-					while let Some((id, _)) = lifo.pop_back() {
+					// The DFS reached the sink, we can add a
+					// residual flow.
+					lifo.pop();
+					while let Some((id, _)) = lifo.pop() {
 						let nbd = next_nbd[id];
 						self.graph[id][nbd].flow += f as i32;
 						let id_rev = self.graph[id][nbd].dest;
 						let nbd_rev = self.graph[id][nbd].rev;
 						self.graph[id_rev][nbd_rev].flow -= f as i32;
 					}
-					lifo.push_back((idsource, flow_upper_bound));
+					lifo.push((idsource, flow_upper_bound));
 					continue;
 				}
-				//else we did not reach the sink
+				// else we did not reach the sink
 				let nbd = next_nbd[id];
 				if nbd >= self.graph[id].len() {
-					//There is nothing to explore from id anymore
-					lifo.pop_back();
-					if let Some((parent, _)) = lifo.back() {
+					// There is nothing to explore from id anymore
+					lifo.pop();
+					if let Some((parent, _)) = lifo.last() {
 						next_nbd[*parent] += 1;
 					}
 					continue;
 				}
-				//else we can try to send flow from id to its nbd
+				// else we can try to send flow from id to its nbd
 				let new_flow = min(
 					f as i32,
 					self.graph[id][nbd].cap as i32 - self.graph[id][nbd].flow,
@@ -257,19 +245,19 @@ impl Graph<FlowEdge> {
 				}
 				if let (Some(lvldest), Some(lvlid)) = (level[self.graph[id][nbd].dest], level[id]) {
 					if lvldest <= lvlid {
-						//We cannot send flow to nbd.
+						// We cannot send flow to nbd.
 						next_nbd[id] += 1;
 						continue;
 					}
 				}
-				//otherwise, we send flow to nbd.
-				lifo.push_back((self.graph[id][nbd].dest, new_flow));
+				// otherwise, we send flow to nbd.
+				lifo.push((self.graph[id][nbd].dest, new_flow));
 			}
 		}
 		Ok(())
 	}
 
-	///This function takes a flow, and a cost function on the edges, and tries to find an
+	/// This function takes a flow, and a cost function on the edges, and tries to find an
 	/// equivalent flow with a better cost, by finding improving overflow cycles. It uses
 	/// as subroutine the Bellman Ford algorithm run up to path_length.
 	/// We assume that the cost of edge (u,v) is the opposite of the cost of (v,u), and
@@ -279,19 +267,19 @@ impl Graph<FlowEdge> {
 		cost: &CostFunction,
 		path_length: usize,
 	) -> Result<(), String> {
-		//We build the weighted graph g where we will look for negative cycle
+		// We build the weighted graph g where we will look for negative cycle
 		let mut gf = self.build_cost_graph(cost)?;
 		let mut cycles = gf.list_negative_cycles(path_length);
 		while !cycles.is_empty() {
-			//we enumerate negative cycles
+			// we enumerate negative cycles
 			for c in cycles.iter() {
 				for i in 0..c.len() {
-					//We add one flow unit to the edge (u,v) of cycle c
-					let idu = self.vertextoid[&c[i]];
-					let idv = self.vertextoid[&c[(i + 1) % c.len()]];
+					// We add one flow unit to the edge (u,v) of cycle c
+					let idu = self.vertex_to_id[&c[i]];
+					let idv = self.vertex_to_id[&c[(i + 1) % c.len()]];
 					for j in 0..self.graph[idu].len() {
-						//since idu appears at most once in the cycles, we enumerate every
-						//edge at most once.
+						// since idu appears at most once in the cycles, we enumerate every
+						// edge at most once.
 						let edge = self.graph[idu][j];
 						if edge.dest == idv {
 							self.graph[idu][j].flow += 1;
@@ -308,16 +296,16 @@ impl Graph<FlowEdge> {
 		Ok(())
 	}
 
-	///Construct the weighted graph G_f from the flow and the cost function
+	/// Construct the weighted graph G_f from the flow and the cost function
 	fn build_cost_graph(&self, cost: &CostFunction) -> Result<Graph<WeightedEdge>, String> {
-		let mut g = Graph::<WeightedEdge>::new(&self.idtovertex);
-		let nb_vertices = self.idtovertex.len();
+		let mut g = Graph::<WeightedEdge>::new(&self.id_to_vertex);
+		let nb_vertices = self.id_to_vertex.len();
 		for i in 0..nb_vertices {
 			for edge in self.graph[i].iter() {
 				if edge.cap as i32 - edge.flow > 0 {
-					//It is possible to send overflow through this edge
-					let u = self.idtovertex[i];
-					let v = self.idtovertex[edge.dest];
+					// It is possible to send overflow through this edge
+					let u = self.id_to_vertex[i];
+					let v = self.id_to_vertex[edge.dest];
 					if cost.contains_key(&(u, v)) {
 						g.add_edge(u, v, cost[&(u, v)])?;
 					} else if cost.contains_key(&(v, u)) {
@@ -333,29 +321,26 @@ impl Graph<FlowEdge> {
 }
 
 impl Graph<WeightedEdge> {
-	///This function adds a single directed weighted edge to the graph.
+	/// This function adds a single directed weighted edge to the graph.
 	pub fn add_edge(&mut self, u: Vertex, v: Vertex, w: i32) -> Result<(), String> {
-		if !self.vertextoid.contains_key(&u) || !self.vertextoid.contains_key(&v) {
-			return Err("The graph does not contain the provided vertex.".to_string());
-		}
-		let idu = self.vertextoid[&u];
-		let idv = self.vertextoid[&v];
+		let idu = self.get_vertex_id(&u)?;
+		let idv = self.get_vertex_id(&v)?;
 		self.graph[idu].push(WeightedEdge { w, dest: idv });
 		Ok(())
 	}
 
-	///This function lists the negative cycles it manages to find after path_length
-	///iterations of the main loop of the Bellman-Ford algorithm. For the classical
-	///algorithm, path_length needs to be equal to the number of vertices. However,
-	///for particular graph structures like in our case, the algorithm is still correct
-	///when path_length is the length of the longest possible simple path.
-	///See the formal description of the algorithm for more details.
+	/// This function lists the negative cycles it manages to find after path_length
+	/// iterations of the main loop of the Bellman-Ford algorithm. For the classical
+	/// algorithm, path_length needs to be equal to the number of vertices. However,
+	/// for particular graph structures like in our case, the algorithm is still correct
+	/// when path_length is the length of the longest possible simple path.
+	/// See the formal description of the algorithm for more details.
 	fn list_negative_cycles(&self, path_length: usize) -> Vec<Vec<Vertex>> {
 		let nb_vertices = self.graph.len();
 
-		//We start with every vertex at distance 0 of some imaginary extra -1 vertex.
+		// We start with every vertex at distance 0 of some imaginary extra -1 vertex.
 		let mut distance = vec![0; nb_vertices];
-		//The prev vector collects for every vertex from where does the shortest path come
+		// The prev vector collects for every vertex from where does the shortest path come
 		let mut prev = vec![None; nb_vertices];
 
 		for _ in 0..path_length + 1 {
@@ -369,29 +354,35 @@ impl Graph<WeightedEdge> {
 			}
 		}
 
-		//If self.graph contains a negative cycle, then at this point the graph described
-		//by prev (which is a directed 1-forest/functional graph)
-		//must contain a cycle. We list the cycles of prev.
+		// If self.graph contains a negative cycle, then at this point the graph described
+		// by prev (which is a directed 1-forest/functional graph)
+		// must contain a cycle. We list the cycles of prev.
 		let cycles_prev = cycles_of_1_forest(&prev);
 
-		//Remark that the cycle in prev is in the reverse order compared to the cycle
-		//in the graph. Thus the .rev().
+		// Remark that the cycle in prev is in the reverse order compared to the cycle
+		// in the graph. Thus the .rev().
 		return cycles_prev
 			.iter()
-			.map(|cycle| cycle.iter().rev().map(|id| self.idtovertex[*id]).collect())
+			.map(|cycle| {
+				cycle
+					.iter()
+					.rev()
+					.map(|id| self.id_to_vertex[*id])
+					.collect()
+			})
 			.collect();
 	}
 }
 
-///This function returns the list of cycles of a directed 1 forest. It does not
-///check for the consistency of the input.
+/// This function returns the list of cycles of a directed 1 forest. It does not
+/// check for the consistency of the input.
 fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
 	let mut cycles = Vec::<Vec<usize>>::new();
 	let mut time_of_discovery = vec![None; forest.len()];
 
 	for t in 0..forest.len() {
 		let mut id = t;
-		//while we are on a valid undiscovered node
+		// while we are on a valid undiscovered node
 		while time_of_discovery[id] == None {
 			time_of_discovery[id] = Some(t);
 			if let Some(i) = forest[id] {
@@ -401,8 +392,8 @@ fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
 			}
 		}
 		if forest[id] != None && time_of_discovery[id] == Some(t) {
-			//We discovered an id that we explored at this iteration t.
-			//It means we are on a cycle
+			// We discovered an id that we explored at this iteration t.
+			// It means we are on a cycle
 			let mut cy = vec![id; 1];
 			let mut id2 = id;
 			while let Some(id_next) = forest[id2] {