Dijkstra's algorithm using C++ STL












0












$begingroup$


I'm implementing Dijkstra's algorithm using C++ STL.



Input



n e (number of vertices and the number of edges)
followed by e lines of edges and their weights w
followed by u and v the shortest path between which is to be found out



Output



A single integer representing the shortest path between u and v



My Approach



adj : adjacency list representation of the graph



cost : weights associated with each vertex



I'm implementing my own priority queue, which prioritizes the vertices based on their dist values



following are the functions I have implemented:




  1. distance (vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) main logic for the algorithm is implemented here


  2. vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) returns an initial min-heap data structure of the vertices (prioritized according to the dist values)


  3. int extract_min (vector<int> &H, vector<int> dist) returns and deletes the minimum element from the min-heap


  4. void decrease_key (vector <int> &H, int i, int key, vector<int> dist) takes arguments as: the heap, index of the element for which key is to be changed (i), the key value, and the dist array


  5. void min_heapify (vector<int> &H, int i, vector<int> dist)



Code



#include <iostream>
#include <vector>
#include <limits>
#include <algorithm>

using std::vector;
using std::cout;

int heapsize;

int parent (int i) {
if (i%2 == 0) return (i/2) - 1;
return i/2;
}

void min_heapify (vector<int> &H, int i, vector<int> dist) {
int l = (2*i) + 1;
int r = (2*i) + 2;
int smallest = i;
if (l < heapsize && dist[H[l]] < dist[H[i]]) smallest = l;
if (r < heapsize && dist[H[r]] < dist[H[i]]) smallest = r;
if (smallest != i) {
std::swap(H[i], H[smallest]);
min_heapify(H, smallest, dist);
}
}

void decrease_key (vector <int> &H, int i, int key, vector<int> dist) {
while (i < heapsize && i > 0 && dist[H[parent(i)]] > dist[H[i]]){
std::swap (H[i], H[parent(i)]);
i = parent(i);
}
}

int extract_min (vector<int> &H, vector<int> dist) {
if (heapsize >= 1) {
int min = H[0];
H[0] = H[heapsize - 1];
H[heapsize - 1] = -1;
heapsize -- ;
min_heapify (H, 0, dist);
return min;
}
}

vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) {
vector<int> H;
heapsize = adj.size();
for (int i = 0; i < adj.size(); i ++) H.push_back(i);
for (int i = H.size() / 2; i >= 0; i --) {
min_heapify (H, i, dist);
}
return H;
}

int distance(vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) {
vector <int> dist (adj.size(), std::numeric_limits<int>::max());
dist [s] = 0;
vector<int> H = makequeue (adj, dist);
int u;
while (heapsize != 0) {
u = extract_min (H, dist);
for (int i = 0; i < adj[u].size(); i ++) {
if ( (dist[u] != std::numeric_limits<int>::max()) && (dist[adj[u][i]] > dist[u] + cost[u][i])) {
dist[adj[u][i]] = dist[u] + cost[u][i];
vector<int>::iterator it = find(H.begin(), H.begin() + heapsize, adj[u][i]);
decrease_key (H, std::distance(H.begin(), it) , dist[adj[u][i]], dist);
}
}
}

if (dist[t] == std::numeric_limits<int>::max()) return -1;
else return dist[t];
}

int main() {
int n, m;
std::cin >> n >> m;
vector<vector<int> > adj(n, vector<int>());
vector<vector<int> > cost(n, vector<int>());
for (int i = 0; i < m; i++) {
int x, y, w;
std::cin >> x >> y >> w;
adj[x - 1].push_back(y - 1);
cost[x - 1].push_back(w);
}
int s, t;
std::cin >> s >> t;
s--, t--;
std::cout << distance(adj, cost, s, t);
}


Example



Input



10 9



1 2 1



2 3 1



3 4 1



4 5 1



5 6 1



6 7 1



7 8 1



8 9 1



9 10 1



1 10



Output



9



Concern



the platform where I wish to submit the code gives wrong answer for a particular test case, I haven't been able to figure out where the problem might lie



My best guess is in the decrease_key function since I'm using a workaround here - by first performing a find to determine the index of the vertex. (Something similar to what was asked here: https://stackoverflow.com/questions/17009056/how-to-implement-ologn-decrease-key-operation-for-min-heap-based-priority-queu)



I'm not very sure how to use the priority_queue container in C++ STL, therefore I went with my own implementation. I'd prefer if someone could guide me as to what is wrong with the code I've written.









share









$endgroup$

















    0












    $begingroup$


    I'm implementing Dijkstra's algorithm using C++ STL.



    Input



    n e (number of vertices and the number of edges)
    followed by e lines of edges and their weights w
    followed by u and v the shortest path between which is to be found out



    Output



    A single integer representing the shortest path between u and v



    My Approach



    adj : adjacency list representation of the graph



    cost : weights associated with each vertex



    I'm implementing my own priority queue, which prioritizes the vertices based on their dist values



    following are the functions I have implemented:




    1. distance (vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) main logic for the algorithm is implemented here


    2. vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) returns an initial min-heap data structure of the vertices (prioritized according to the dist values)


    3. int extract_min (vector<int> &H, vector<int> dist) returns and deletes the minimum element from the min-heap


    4. void decrease_key (vector <int> &H, int i, int key, vector<int> dist) takes arguments as: the heap, index of the element for which key is to be changed (i), the key value, and the dist array


    5. void min_heapify (vector<int> &H, int i, vector<int> dist)



    Code



    #include <iostream>
    #include <vector>
    #include <limits>
    #include <algorithm>

    using std::vector;
    using std::cout;

    int heapsize;

    int parent (int i) {
    if (i%2 == 0) return (i/2) - 1;
    return i/2;
    }

    void min_heapify (vector<int> &H, int i, vector<int> dist) {
    int l = (2*i) + 1;
    int r = (2*i) + 2;
    int smallest = i;
    if (l < heapsize && dist[H[l]] < dist[H[i]]) smallest = l;
    if (r < heapsize && dist[H[r]] < dist[H[i]]) smallest = r;
    if (smallest != i) {
    std::swap(H[i], H[smallest]);
    min_heapify(H, smallest, dist);
    }
    }

    void decrease_key (vector <int> &H, int i, int key, vector<int> dist) {
    while (i < heapsize && i > 0 && dist[H[parent(i)]] > dist[H[i]]){
    std::swap (H[i], H[parent(i)]);
    i = parent(i);
    }
    }

    int extract_min (vector<int> &H, vector<int> dist) {
    if (heapsize >= 1) {
    int min = H[0];
    H[0] = H[heapsize - 1];
    H[heapsize - 1] = -1;
    heapsize -- ;
    min_heapify (H, 0, dist);
    return min;
    }
    }

    vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) {
    vector<int> H;
    heapsize = adj.size();
    for (int i = 0; i < adj.size(); i ++) H.push_back(i);
    for (int i = H.size() / 2; i >= 0; i --) {
    min_heapify (H, i, dist);
    }
    return H;
    }

    int distance(vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) {
    vector <int> dist (adj.size(), std::numeric_limits<int>::max());
    dist [s] = 0;
    vector<int> H = makequeue (adj, dist);
    int u;
    while (heapsize != 0) {
    u = extract_min (H, dist);
    for (int i = 0; i < adj[u].size(); i ++) {
    if ( (dist[u] != std::numeric_limits<int>::max()) && (dist[adj[u][i]] > dist[u] + cost[u][i])) {
    dist[adj[u][i]] = dist[u] + cost[u][i];
    vector<int>::iterator it = find(H.begin(), H.begin() + heapsize, adj[u][i]);
    decrease_key (H, std::distance(H.begin(), it) , dist[adj[u][i]], dist);
    }
    }
    }

    if (dist[t] == std::numeric_limits<int>::max()) return -1;
    else return dist[t];
    }

    int main() {
    int n, m;
    std::cin >> n >> m;
    vector<vector<int> > adj(n, vector<int>());
    vector<vector<int> > cost(n, vector<int>());
    for (int i = 0; i < m; i++) {
    int x, y, w;
    std::cin >> x >> y >> w;
    adj[x - 1].push_back(y - 1);
    cost[x - 1].push_back(w);
    }
    int s, t;
    std::cin >> s >> t;
    s--, t--;
    std::cout << distance(adj, cost, s, t);
    }


    Example



    Input



    10 9



    1 2 1



    2 3 1



    3 4 1



    4 5 1



    5 6 1



    6 7 1



    7 8 1



    8 9 1



    9 10 1



    1 10



    Output



    9



    Concern



    the platform where I wish to submit the code gives wrong answer for a particular test case, I haven't been able to figure out where the problem might lie



    My best guess is in the decrease_key function since I'm using a workaround here - by first performing a find to determine the index of the vertex. (Something similar to what was asked here: https://stackoverflow.com/questions/17009056/how-to-implement-ologn-decrease-key-operation-for-min-heap-based-priority-queu)



    I'm not very sure how to use the priority_queue container in C++ STL, therefore I went with my own implementation. I'd prefer if someone could guide me as to what is wrong with the code I've written.









    share









    $endgroup$















      0












      0








      0





      $begingroup$


      I'm implementing Dijkstra's algorithm using C++ STL.



      Input



      n e (number of vertices and the number of edges)
      followed by e lines of edges and their weights w
      followed by u and v the shortest path between which is to be found out



      Output



      A single integer representing the shortest path between u and v



      My Approach



      adj : adjacency list representation of the graph



      cost : weights associated with each vertex



      I'm implementing my own priority queue, which prioritizes the vertices based on their dist values



      following are the functions I have implemented:




      1. distance (vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) main logic for the algorithm is implemented here


      2. vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) returns an initial min-heap data structure of the vertices (prioritized according to the dist values)


      3. int extract_min (vector<int> &H, vector<int> dist) returns and deletes the minimum element from the min-heap


      4. void decrease_key (vector <int> &H, int i, int key, vector<int> dist) takes arguments as: the heap, index of the element for which key is to be changed (i), the key value, and the dist array


      5. void min_heapify (vector<int> &H, int i, vector<int> dist)



      Code



      #include <iostream>
      #include <vector>
      #include <limits>
      #include <algorithm>

      using std::vector;
      using std::cout;

      int heapsize;

      int parent (int i) {
      if (i%2 == 0) return (i/2) - 1;
      return i/2;
      }

      void min_heapify (vector<int> &H, int i, vector<int> dist) {
      int l = (2*i) + 1;
      int r = (2*i) + 2;
      int smallest = i;
      if (l < heapsize && dist[H[l]] < dist[H[i]]) smallest = l;
      if (r < heapsize && dist[H[r]] < dist[H[i]]) smallest = r;
      if (smallest != i) {
      std::swap(H[i], H[smallest]);
      min_heapify(H, smallest, dist);
      }
      }

      void decrease_key (vector <int> &H, int i, int key, vector<int> dist) {
      while (i < heapsize && i > 0 && dist[H[parent(i)]] > dist[H[i]]){
      std::swap (H[i], H[parent(i)]);
      i = parent(i);
      }
      }

      int extract_min (vector<int> &H, vector<int> dist) {
      if (heapsize >= 1) {
      int min = H[0];
      H[0] = H[heapsize - 1];
      H[heapsize - 1] = -1;
      heapsize -- ;
      min_heapify (H, 0, dist);
      return min;
      }
      }

      vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) {
      vector<int> H;
      heapsize = adj.size();
      for (int i = 0; i < adj.size(); i ++) H.push_back(i);
      for (int i = H.size() / 2; i >= 0; i --) {
      min_heapify (H, i, dist);
      }
      return H;
      }

      int distance(vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) {
      vector <int> dist (adj.size(), std::numeric_limits<int>::max());
      dist [s] = 0;
      vector<int> H = makequeue (adj, dist);
      int u;
      while (heapsize != 0) {
      u = extract_min (H, dist);
      for (int i = 0; i < adj[u].size(); i ++) {
      if ( (dist[u] != std::numeric_limits<int>::max()) && (dist[adj[u][i]] > dist[u] + cost[u][i])) {
      dist[adj[u][i]] = dist[u] + cost[u][i];
      vector<int>::iterator it = find(H.begin(), H.begin() + heapsize, adj[u][i]);
      decrease_key (H, std::distance(H.begin(), it) , dist[adj[u][i]], dist);
      }
      }
      }

      if (dist[t] == std::numeric_limits<int>::max()) return -1;
      else return dist[t];
      }

      int main() {
      int n, m;
      std::cin >> n >> m;
      vector<vector<int> > adj(n, vector<int>());
      vector<vector<int> > cost(n, vector<int>());
      for (int i = 0; i < m; i++) {
      int x, y, w;
      std::cin >> x >> y >> w;
      adj[x - 1].push_back(y - 1);
      cost[x - 1].push_back(w);
      }
      int s, t;
      std::cin >> s >> t;
      s--, t--;
      std::cout << distance(adj, cost, s, t);
      }


      Example



      Input



      10 9



      1 2 1



      2 3 1



      3 4 1



      4 5 1



      5 6 1



      6 7 1



      7 8 1



      8 9 1



      9 10 1



      1 10



      Output



      9



      Concern



      the platform where I wish to submit the code gives wrong answer for a particular test case, I haven't been able to figure out where the problem might lie



      My best guess is in the decrease_key function since I'm using a workaround here - by first performing a find to determine the index of the vertex. (Something similar to what was asked here: https://stackoverflow.com/questions/17009056/how-to-implement-ologn-decrease-key-operation-for-min-heap-based-priority-queu)



      I'm not very sure how to use the priority_queue container in C++ STL, therefore I went with my own implementation. I'd prefer if someone could guide me as to what is wrong with the code I've written.









      share









      $endgroup$




      I'm implementing Dijkstra's algorithm using C++ STL.



      Input



      n e (number of vertices and the number of edges)
      followed by e lines of edges and their weights w
      followed by u and v the shortest path between which is to be found out



      Output



      A single integer representing the shortest path between u and v



      My Approach



      adj : adjacency list representation of the graph



      cost : weights associated with each vertex



      I'm implementing my own priority queue, which prioritizes the vertices based on their dist values



      following are the functions I have implemented:




      1. distance (vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) main logic for the algorithm is implemented here


      2. vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) returns an initial min-heap data structure of the vertices (prioritized according to the dist values)


      3. int extract_min (vector<int> &H, vector<int> dist) returns and deletes the minimum element from the min-heap


      4. void decrease_key (vector <int> &H, int i, int key, vector<int> dist) takes arguments as: the heap, index of the element for which key is to be changed (i), the key value, and the dist array


      5. void min_heapify (vector<int> &H, int i, vector<int> dist)



      Code



      #include <iostream>
      #include <vector>
      #include <limits>
      #include <algorithm>

      using std::vector;
      using std::cout;

      int heapsize;

      int parent (int i) {
      if (i%2 == 0) return (i/2) - 1;
      return i/2;
      }

      void min_heapify (vector<int> &H, int i, vector<int> dist) {
      int l = (2*i) + 1;
      int r = (2*i) + 2;
      int smallest = i;
      if (l < heapsize && dist[H[l]] < dist[H[i]]) smallest = l;
      if (r < heapsize && dist[H[r]] < dist[H[i]]) smallest = r;
      if (smallest != i) {
      std::swap(H[i], H[smallest]);
      min_heapify(H, smallest, dist);
      }
      }

      void decrease_key (vector <int> &H, int i, int key, vector<int> dist) {
      while (i < heapsize && i > 0 && dist[H[parent(i)]] > dist[H[i]]){
      std::swap (H[i], H[parent(i)]);
      i = parent(i);
      }
      }

      int extract_min (vector<int> &H, vector<int> dist) {
      if (heapsize >= 1) {
      int min = H[0];
      H[0] = H[heapsize - 1];
      H[heapsize - 1] = -1;
      heapsize -- ;
      min_heapify (H, 0, dist);
      return min;
      }
      }

      vector<int> makequeue (vector<vector<int>> adj, vector<int> dist) {
      vector<int> H;
      heapsize = adj.size();
      for (int i = 0; i < adj.size(); i ++) H.push_back(i);
      for (int i = H.size() / 2; i >= 0; i --) {
      min_heapify (H, i, dist);
      }
      return H;
      }

      int distance(vector<vector<int> > &adj, vector<vector<int> > &cost, int s, int t) {
      vector <int> dist (adj.size(), std::numeric_limits<int>::max());
      dist [s] = 0;
      vector<int> H = makequeue (adj, dist);
      int u;
      while (heapsize != 0) {
      u = extract_min (H, dist);
      for (int i = 0; i < adj[u].size(); i ++) {
      if ( (dist[u] != std::numeric_limits<int>::max()) && (dist[adj[u][i]] > dist[u] + cost[u][i])) {
      dist[adj[u][i]] = dist[u] + cost[u][i];
      vector<int>::iterator it = find(H.begin(), H.begin() + heapsize, adj[u][i]);
      decrease_key (H, std::distance(H.begin(), it) , dist[adj[u][i]], dist);
      }
      }
      }

      if (dist[t] == std::numeric_limits<int>::max()) return -1;
      else return dist[t];
      }

      int main() {
      int n, m;
      std::cin >> n >> m;
      vector<vector<int> > adj(n, vector<int>());
      vector<vector<int> > cost(n, vector<int>());
      for (int i = 0; i < m; i++) {
      int x, y, w;
      std::cin >> x >> y >> w;
      adj[x - 1].push_back(y - 1);
      cost[x - 1].push_back(w);
      }
      int s, t;
      std::cin >> s >> t;
      s--, t--;
      std::cout << distance(adj, cost, s, t);
      }


      Example



      Input



      10 9



      1 2 1



      2 3 1



      3 4 1



      4 5 1



      5 6 1



      6 7 1



      7 8 1



      8 9 1



      9 10 1



      1 10



      Output



      9



      Concern



      the platform where I wish to submit the code gives wrong answer for a particular test case, I haven't been able to figure out where the problem might lie



      My best guess is in the decrease_key function since I'm using a workaround here - by first performing a find to determine the index of the vertex. (Something similar to what was asked here: https://stackoverflow.com/questions/17009056/how-to-implement-ologn-decrease-key-operation-for-min-heap-based-priority-queu)



      I'm not very sure how to use the priority_queue container in C++ STL, therefore I went with my own implementation. I'd prefer if someone could guide me as to what is wrong with the code I've written.







      c++ algorithm





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