Issue #135 is started

Author: Hamid Gasmi

3-graph-algorithms/2_paths_in_graphs/dijkstra_priorityQueue.py

@@ -26,7 +26,7 @@ def dijkstra(self, s, t):
         parents = [None] * len(self.adjacency_list)
         parents[s] = -1
 
-        q = queue.PriorityQueue()
+        q = queue.PriorityQueue(n)
         for v in range(0, len(self.adjacency_list)):
             if v == s:
                 continue

3-graph-algorithms/2_paths_in_graphs/shortest_paths.py

@@ -1,13 +1,81 @@
 #Uses python3
-
 import sys
 import queue
+from collections import namedtuple
+
+Edge = namedtuple('Edge', ['vertex', 'weight'])
+
+class Graph:
+    def __init__(self, n, edges):
+        self.adjacency_list = [[] for _ in range(n)]
+        self.build_adjacency_list(edges)
+
+    def v_size(self):
+        return len(self.adjacency_list)
+
+    def build_adjacency_list(self, edges):
+        for ((s, d), w) in edges:
+            self.adjacency_list[s - 1].append(Edge(d - 1, w))
+
+    # Implementation: Bellman-Ford algorithm
+    def shortest_paths(self, s, distances):
+        n = self.v_size()
+        parents = [-1] * n
+        distances[s] = 0
+        negative_cycle_reachable_nodes = []
 
+        # Find shortest paths
+        for i in range(n):
+            for v in range(n):
+                for a_tuple in self.adjacency_list[v]:
+                    a_candidate_distance = distances[v] + a_tuple.weight
+                    if distances[a_tuple.vertex] > a_candidate_distance:
+                        distances[a_tuple.vertex] = a_candidate_distance
+                        parents[a_tuple.vertex] = v
+                        
+                        if i == n - 1:
+                            negative_cycle_reachable_nodes.append(a_tuple.vertex)
+                            distances[s] = - 10**19
+                            
+        # Find all negative cycles
+        visited = [False] * n
+        for v in negative_cycle_reachable_nodes:
+            cycle_v = self.get_cycle(v, parents)
+            # Visit all nodes reachable from a negative cycle
+            self.dfs(cycle_v, distances, visited)
+    
+    def get_cycle(self, v, parents):
+        # Find a node in a cycle where v is reachable from
+        cycle_v = v
+        for _ in range(self.v_size()):
+            cycle_v = parents[cycle_v]
 
-def shortet_paths(adj, cost, s, distance, reachable, shortest):
-    #write your code here
-    pass
+        return cycle_v
 
+        # Find all nodes of the cycle
+        #cycle = []
+        #cycle.append(cycle_v)
+        #p = parents[cycle_v]
+        #while p != cycle_v:
+        #    cycle.append(p)
+        #    p = parents[p]
+        # return cycle
+
+    def dfs(self, s, distances, visited):
+        if visited[s]:
+            return
+        
+        visited[s] = True
+        distances[s] = - 10**19
+
+        for a_tuple in self.adjacency_list[s]:
+            self.dfs(a_tuple.vertex, distances, visited)
+
+def shortet_paths(n, edges, s, distance):
+
+    aGraph = Graph(n, edges)
+
+    aGraph.shortest_paths(s, distances)
 
 if __name__ == '__main__':
     input = sys.stdin.read()
@@ -16,22 +84,15 @@ def shortet_paths(adj, cost, s, distance, reachable, shortest):
     data = data[2:]
     edges = list(zip(zip(data[0:(3 * m):3], data[1:(3 * m):3]), data[2:(3 * m):3]))
     data = data[3 * m:]
-    adj = [[] for _ in range(n)]
-    cost = [[] for _ in range(n)]
-    for ((a, b), w) in edges:
-        adj[a - 1].append(b - 1)
-        cost[a - 1].append(w)
+    
     s = data[0]
     s -= 1
-    distance = [10**19] * n
-    reachable = [0] * n
-    shortest = [1] * n
-    shortet_paths(adj, cost, s, distance, reachable, shortest)
+    distances = [10**19] * n
+    shortet_paths(n, edges, s, distances)
     for x in range(n):
-        if reachable[x] == 0:
+        if distances[x] == 10**19:
             print('*')
-        elif shortest[x] == 0:
+        elif distances[x] == - 10**19:
             print('-')
         else:
-            print(distance[x])
-
+            print(distances[x])

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/01

@@ -0,0 +1,9 @@
+6 7
+1 2 10
+2 3 5
+1 3 100
+3 5 7
+5 4 10
+4 3 -18
+6 1 -1
+1

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/01a

@@ -0,0 +1,6 @@
+0
+10
+-
+-
+-
+*

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/01e

@@ -0,0 +1,6 @@
+0
+10
+-
+-
+-
+*

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/02

@@ -0,0 +1,6 @@
+5 4
+1 2 1
+4 1 2
+2 3 2
+3 1 -5
+4

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/02a

@@ -0,0 +1,5 @@
+-
+-
+-
+0
+*

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/02e

@@ -0,0 +1,5 @@
+-
+-
+-
+0
+*

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/03

@@ -0,0 +1,19 @@
+15 17
+1 2 10
+2 3 5
+1 3 100
+1 15 2
+3 5 7
+4 3 -18
+5 4 10
+5 7 2
+5 8 1
+7 9 1
+9 10 1
+6 1 -1
+2 11 1
+11 12 7
+12 13 10
+13 11 -18
+12 14 1
+1

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/03a

@@ -0,0 +1,15 @@
+0
+10
+-
+-
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+*
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+-
+-
+-
+-
+-
+-
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+2

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/03e

@@ -0,0 +1,15 @@
+0
+10
+-
+-
+-
+*
+-
+-
+-
+-
+-
+-
+-
+-
+2

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/04

@@ -0,0 +1,19 @@
+15 17
+1 2 10
+2 3 5
+1 3 100
+1 15 2
+3 5 7
+4 3 -18
+5 4 10
+5 7 2
+5 8 1
+7 9 1
+9 10 1
+6 1 -1
+2 11 1
+11 12 7
+12 13 10
+13 11 -18
+12 14 1
+6

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/04a

@@ -0,0 +1,15 @@
+-1
+9
+-
+-
+-
+0
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+-
+-
+-
+-
+-
+-
+-
+1

3-graph-algorithms/2_paths_in_graphs/shortest_paths_tests/04e

@@ -0,0 +1,15 @@
+-1
+9
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+-
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+0
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+-
+-
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+-
+-
+-
+-
+1