Create bellman_ford.py

Author: arnab132

bellman_ford.py

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+# Python3 program for Bellman-Ford's single source
+# shortest path algorithm.
+
+# Class to represent a graph
+class Graph:
+
+	def __init__(self, vertices):
+		self.V = vertices # No. of vertices
+		self.graph = []
+
+	# function to add an edge to graph
+	def addEdge(self, u, v, w):
+		self.graph.append([u, v, w])
+		
+	# utility function used to print the solution
+	def printArr(self, dist):
+		print("Vertex Distance from Source")
+		for i in range(self.V):
+			print("{0}\t\t{1}".format(i, dist[i]))
+	
+	# The main function that finds shortest distances from src to
+	# all other vertices using Bellman-Ford algorithm. The function
+	# also detects negative weight cycle
+	def BellmanFord(self, src):
+
+		# Step 1: Initialize distances from src to all other vertices
+		# as INFINITE
+		dist = [float("Inf")] * self.V
+		dist[src] = 0
+
+
+		# Step 2: Relax all edges |V| - 1 times. A simple shortest
+		# path from src to any other vertex can have at-most |V| - 1
+		# edges
+		for _ in range(self.V - 1):
+			# Update dist value and parent index of the adjacent vertices of
+			# the picked vertex. Consider only those vertices which are still in
+			# queue
+			for u, v, w in self.graph:
+				if dist[u] != float("Inf") and dist[u] + w < dist[v]:
+						dist[v] = dist[u] + w
+
+		# Step 3: check for negative-weight cycles. The above step
+		# guarantees shortest distances if graph doesn't contain
+		# negative weight cycle. If we get a shorter path, then there
+		# is a cycle.
+
+		for u, v, w in self.graph:
+				if dist[u] != float("Inf") and dist[u] + w < dist[v]:
+						print("Graph contains negative weight cycle")
+						return
+						
+		# print all distance
+		self.printArr(dist)
+
+g = Graph(5)
+g.addEdge(0, 1, -1)
+g.addEdge(0, 2, 4)
+g.addEdge(1, 2, 3)
+g.addEdge(1, 3, 2)
+g.addEdge(1, 4, 2)
+g.addEdge(3, 2, 5)
+g.addEdge(3, 1, 1)
+g.addEdge(4, 3, -3)
+
+# Print the solution
+g.BellmanFord(0)