Corrected the warnings and errors issued by cargo clippy
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3ba2c5b424
commit
948ff93cf1
2 changed files with 64 additions and 81 deletions
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@ -195,8 +195,8 @@ impl ClusterLayout {
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.collect::<Vec<(String, usize)>>();
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.collect::<Vec<(String, usize)>>();
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//We create an indexing of the zones
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//We create an indexing of the zones
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let mut zone_id = HashMap::<String, usize>::new();
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let mut zone_id = HashMap::<String, usize>::new();
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for i in 0..part_per_zone_vec.len() {
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for (i, ppz) in part_per_zone_vec.iter().enumerate() {
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zone_id.insert(part_per_zone_vec[i].0.clone(), i);
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zone_id.insert(ppz.0.clone(), i);
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}
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}
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//We compute a candidate for the new partition to zone
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//We compute a candidate for the new partition to zone
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@ -212,7 +212,7 @@ impl ClusterLayout {
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let mut node_assignation = vec![vec![None; self.replication_factor]; nb_partitions];
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let mut node_assignation = vec![vec![None; self.replication_factor]; nb_partitions];
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//We will decrement part_per_nod to keep track of the number
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//We will decrement part_per_nod to keep track of the number
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//of partitions that we still have to associate.
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//of partitions that we still have to associate.
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let mut part_per_nod = part_per_nod.clone();
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let mut part_per_nod = part_per_nod;
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//We minimize the distance to the former assignation(if any)
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//We minimize the distance to the former assignation(if any)
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@ -265,7 +265,7 @@ impl ClusterLayout {
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&& part_per_nod[*id] > 0
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&& part_per_nod[*id] > 0
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})
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})
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.collect();
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.collect();
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assert!(possible_nodes.len() > 0);
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assert!(!possible_nodes.is_empty());
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//We randomly pick a node
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//We randomly pick a node
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if let Some(nod) = possible_nodes.choose(&mut rng) {
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if let Some(nod) = possible_nodes.choose(&mut rng) {
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node_assignation[i][j] = Some(*nod);
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node_assignation[i][j] = Some(*nod);
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@ -277,12 +277,12 @@ impl ClusterLayout {
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//We write the assignation in the 1D table
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//We write the assignation in the 1D table
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self.ring_assignation_data = Vec::<CompactNodeType>::new();
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self.ring_assignation_data = Vec::<CompactNodeType>::new();
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for i in 0..nb_partitions {
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for ass in node_assignation {
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for j in 0..self.replication_factor {
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for nod in ass {
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if let Some(id) = node_assignation[i][j] {
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if let Some(id) = nod {
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self.ring_assignation_data.push(id as CompactNodeType);
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self.ring_assignation_data.push(id as CompactNodeType);
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} else {
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} else {
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assert!(false)
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panic!()
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}
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}
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}
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}
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}
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}
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@ -318,7 +318,7 @@ impl ClusterLayout {
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self.node_id_vec = new_node_id_vec;
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self.node_id_vec = new_node_id_vec;
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self.ring_assignation_data = vec![];
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self.ring_assignation_data = vec![];
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return node_assignation;
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node_assignation
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}
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}
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///This function compute the number of partition to assign to
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///This function compute the number of partition to assign to
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@ -345,7 +345,7 @@ impl ClusterLayout {
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//Compute the optimal number of partitions per zone
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//Compute the optimal number of partitions per zone
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let sum_capacities: u32 = zone_capacity.values().sum();
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let sum_capacities: u32 = zone_capacity.values().sum();
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if sum_capacities <= 0 {
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if sum_capacities == 0 {
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println!("No storage capacity in the network.");
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println!("No storage capacity in the network.");
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return None;
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return None;
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}
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}
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@ -493,14 +493,10 @@ impl ClusterLayout {
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.map(|id_nod| match self.node_role(id_nod) {
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.map(|id_nod| match self.node_role(id_nod) {
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Some(NodeRole {
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Some(NodeRole {
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zone: _,
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zone: _,
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capacity,
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capacity: Some(c),
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tags: _,
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tags: _,
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}) => {
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}) => {
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if let Some(c) = capacity {
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*c
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*c
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} else {
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0
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}
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}
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}
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_ => 0,
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_ => 0,
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})
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})
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@ -31,8 +31,8 @@ struct WeightedEdge {
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* as possible to old_match.
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* as possible to old_match.
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* */
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* */
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pub fn optimize_matching(
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pub fn optimize_matching(
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old_match: &Vec<Vec<usize>>,
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old_match: &[Vec<usize>],
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new_match: &Vec<Vec<usize>>,
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new_match: &[Vec<usize>],
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nb_right: usize,
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nb_right: usize,
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) -> Vec<Vec<usize>> {
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) -> Vec<Vec<usize>> {
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let nb_left = old_match.len();
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let nb_left = old_match.len();
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@ -72,17 +72,12 @@ pub fn optimize_matching(
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//Discovering and flipping a cycle with positive weight in this
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//Discovering and flipping a cycle with positive weight in this
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//graph will make the matching closer to old_match.
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//graph will make the matching closer to old_match.
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//We use Bellman Ford algorithm to discover positive cycles
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//We use Bellman Ford algorithm to discover positive cycles
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loop {
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while let Some(cycle) = positive_cycle(&edge_vec, nb_left, nb_right) {
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if let Some(cycle) = positive_cycle(&edge_vec, nb_left, nb_right) {
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for i in cycle {
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for i in cycle {
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//We flip the edges of the cycle.
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//We flip the edges of the cycle.
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(edge_vec[i].u, edge_vec[i].v) = (edge_vec[i].v, edge_vec[i].u);
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(edge_vec[i].u, edge_vec[i].v) = (edge_vec[i].v, edge_vec[i].u);
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edge_vec[i].w *= -1;
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edge_vec[i].w *= -1;
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}
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}
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} else {
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//If there is no cycle, we return the optimal matching.
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break;
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}
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}
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}
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//The optimal matching is build from the graph structure.
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//The optimal matching is build from the graph structure.
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@ -97,7 +92,7 @@ pub fn optimize_matching(
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//This function finds a positive cycle in a bipartite wieghted graph.
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//This function finds a positive cycle in a bipartite wieghted graph.
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fn positive_cycle(
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fn positive_cycle(
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edge_vec: &Vec<WeightedEdge>,
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edge_vec: &[WeightedEdge],
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nb_left: usize,
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nb_left: usize,
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nb_right: usize,
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nb_right: usize,
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) -> Option<Vec<usize>> {
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) -> Option<Vec<usize>> {
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@ -122,8 +117,7 @@ fn positive_cycle(
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//the number of partitions can be much larger than the
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//the number of partitions can be much larger than the
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//number of nodes, we optimize that.
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//number of nodes, we optimize that.
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for _ in 0..(2 * nb_side_min) {
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for _ in 0..(2 * nb_side_min) {
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for j in 0..edge_vec.len() {
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for (j, e) in edge_vec.iter().enumerate() {
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let e = edge_vec[j];
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if weight[e.v] < weight[e.u] + e.w {
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if weight[e.v] < weight[e.u] + e.w {
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weight[e.v] = weight[e.u] + e.w;
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weight[e.v] = weight[e.u] + e.w;
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prev[e.v] = j;
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prev[e.v] = j;
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@ -148,8 +142,7 @@ fn positive_cycle(
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curr = edge_vec[prev[curr]].u;
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curr = edge_vec[prev[curr]].u;
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}
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}
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//Now curr is on the cycle. We collect the edges ids.
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//Now curr is on the cycle. We collect the edges ids.
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let mut cycle = Vec::<usize>::new();
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let mut cycle = vec![prev[curr]];
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cycle.push(prev[curr]);
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let mut cycle_vert = edge_vec[prev[curr]].u;
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let mut cycle_vert = edge_vec[prev[curr]].u;
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while cycle_vert != curr {
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while cycle_vert != curr {
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cycle.push(prev[cycle_vert]);
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cycle.push(prev[cycle_vert]);
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@ -180,16 +173,16 @@ pub fn dinic_compute_matching(left_cap_vec: Vec<u32>, right_cap_vec: Vec<u32>) -
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// 0 will be the source
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// 0 will be the source
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graph.push(vec![ed; left_cap_vec.len()]);
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graph.push(vec![ed; left_cap_vec.len()]);
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for i in 0..left_cap_vec.len() {
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for (i, c) in left_cap_vec.iter().enumerate() {
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graph[0][i].c = left_cap_vec[i] as i32;
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graph[0][i].c = *c as i32;
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graph[0][i].v = i + 2;
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graph[0][i].v = i + 2;
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graph[0][i].rev = 0;
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graph[0][i].rev = 0;
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}
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}
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//1 will be the sink
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//1 will be the sink
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graph.push(vec![ed; right_cap_vec.len()]);
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graph.push(vec![ed; right_cap_vec.len()]);
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for i in 0..right_cap_vec.len() {
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for (i, c) in right_cap_vec.iter().enumerate() {
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graph[1][i].c = right_cap_vec[i] as i32;
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graph[1][i].c = *c as i32;
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graph[1][i].v = i + 2 + left_cap_vec.len();
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graph[1][i].v = i + 2 + left_cap_vec.len();
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graph[1][i].rev = 0;
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graph[1][i].rev = 0;
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}
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}
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@ -267,18 +260,15 @@ pub fn dinic_compute_matching(left_cap_vec: Vec<u32>, right_cap_vec: Vec<u32>) -
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let mut next_nbd = vec![0; nb_vertices];
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let mut next_nbd = vec![0; nb_vertices];
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let mut lifo = VecDeque::new();
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let mut lifo = VecDeque::new();
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let flow_upper_bound;
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let flow_upper_bound = if let Some(x) = left_cap_vec.iter().max() {
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if let Some(x) = left_cap_vec.iter().max() {
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*x as i32
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flow_upper_bound = *x as i32;
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} else {
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} else {
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flow_upper_bound = 0;
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panic!();
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assert!(false);
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};
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}
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lifo.push_back((0, flow_upper_bound));
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lifo.push_back((0, flow_upper_bound));
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loop {
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while let Some((id_tmp, f_tmp)) = lifo.back() {
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if let Some((id_tmp, f_tmp)) = lifo.back() {
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let id = *id_tmp;
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let id = *id_tmp;
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let f = *f_tmp;
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let f = *f_tmp;
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if id == 1 {
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if id == 1 {
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@ -316,9 +306,6 @@ pub fn dinic_compute_matching(left_cap_vec: Vec<u32>, right_cap_vec: Vec<u32>) -
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}
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}
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//otherwise, we send flow to nbd.
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//otherwise, we send flow to nbd.
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lifo.push_back((graph[id][nbd].v, new_flow));
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lifo.push_back((graph[id][nbd].v, new_flow));
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} else {
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break;
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}
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}
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}
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}
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}
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