play with dijkstra

trees_and_graphs/dijkstra-adj-matrix.py

@@ -0,0 +1,66 @@
+# dijkstra's single source shortest path algorithm
+# with adjacency matrix representation
+
+import sys
+
+
+class Graph():
+
+	def __init__(self, vertices):
+
+		self.V = vertices
+		self.graph = [[0 for col in range(vertices)] for row in range(vertices)]
+
+	def print_solution(self, dist):
+
+		print("Vertex \tDistance from Source")
+		for node in range(self.V):
+			print(node, "\t", dist[node])
+
+	def min_distance(self, dist, sset):
+
+		# minimum distance for next node
+		min_ = sys.maxsize
+
+		# search not nearest vertex not in the shortest path tree
+		for u in range(self.V):
+			if dist[u] < min_ and sset[u] == False:
+				min_ = dist[u]
+				min_index = u
+
+		return min_index
+
+
+	def dijkstra(self, src):
+
+		dist = [sys.maxsize] * self.V
+		dist[src] = 0
+		sset = [False] * self.V
+
+		for c in range(self.V):
+			x = self.min_distance(dist, sset)
+			sset[x] = True
+
+			for y in range(self.V):
+				if self.graph[x][y] > 0 and \
+                   sset[y] == False and \
+                   dist[y] > dist[x] + self.graph[x][y]:
+					    dist[y] = dist[x] + self.graph[x][y]
+
+		self.print_solution(dist)
+
+
+if __name__ == "__main__":
+	g = Graph(9)
+	g.graph = [     [0, 4, 0, 0, 0, 0, 0, 8, 0],
+			        [4, 0, 8, 0, 0, 0, 0, 11, 0],
+			        [0, 8, 0, 7, 0, 4, 0, 0, 2],
+			        [0, 0, 7, 0, 9, 14, 0, 0, 0],
+			        [0, 0, 0, 9, 0, 10, 0, 0, 0],
+			        [0, 0, 4, 14, 10, 0, 2, 0, 0],
+			        [0, 0, 0, 0, 0, 2, 0, 1, 6],
+			        [8, 11, 0, 0, 0, 0, 1, 0, 7],
+			        [0, 0, 2, 0, 0, 0, 6, 7, 0]
+			]
+
+	g.dijkstra(0)