104 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			V
		
	
	
			
		
		
	
	
			104 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			V
		
	
	
// Author: ccs
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// I follow literally code in C, done many years ago
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fn main() {
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	// Adjacency matrix as a map	
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	// Example 01
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	graph_01 := {
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		'A': ['B', 'C']
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		'B': ['A', 'D', 'E']
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		'C': ['A', 'F']
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		'D': ['B']
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		'E': ['F', 'B', 'F']
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		'F': ['C', 'E']
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	}
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	// Example 02
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	graph_02 := {
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		'A': ['B', 'C', 'D']
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		'B': ['E']
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		'C': ['F']
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		'D': ['E']
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		'E': ['H']
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		'F': ['H']
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		'G': ['H']
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		'H': ['E', 'F', 'G']
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	}
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	// println('Graph: $graph')
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	path_01 := depth_first_search_path(graph_01, 'A', 'F')
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	println('\n Graph_01: a first path from node A to node F is: $path_01.reverse()')
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	path_02 := depth_first_search_path(graph_02, 'A', 'H')
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	println('\n Graph_02: a first path from node A to node F is: $path_02.reverse()')
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}
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// Depth-First Search (BFS) allows you to find a path between two nodes in the graph.
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fn depth_first_search_path(graph map[string][]string, start string, target string) []string {
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	mut path := []string{} // ONE PATH with SUCCESS = array
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	mut stack := []string{} // a stack ... many nodes
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	// all_nodes := graph.keys() // get a key of this map
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	n_nodes := graph.len // numbers of nodes of this graph
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	mut visited := a_map_nodes_bool(n_nodes) // a map fully
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	// false ... not visited yet: {'A': false, 'B': false, 'C': false, 'D': false, 'E': false}
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	stack << start // first push on the stack
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	for stack.len > 0 {
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		mut node := stack.pop() // get the top node and remove it from the stack
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		// check if this node is already visited
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		if visited[node] == false {
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			// if no ... test it searchin for a final node
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			visited[node] = true // means: node visited
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			if node == target {
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				path = build_path_reverse(graph, start, node, visited)
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				return path
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			}
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			//  Exploring of node removed from  stack and add its relatives
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			print('\n Exploring of node $node (true/false): ${graph[node]}')
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			// graph[node].reverse() take a classical choice for DFS
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			// at most os left in this case.
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			// use vertex in graph[node] the choice is right
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			// take  all nodes from the node
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			for vertex in graph[node].reverse() {
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				// println("\n ...${vertex}")
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				// not explored yet
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				if visited[vertex] == false {
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					stack << vertex
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				}
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			}
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			print('\n Stack: $stack (only not visited) \n Visited: $visited')
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		}
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	}
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	path = ['Path not found, problem in the Graph, start or end nodes! ']
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	return path
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}
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// Creating a map for nodes not VISITED visited ...
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// starting by false ===> means this node was not visited yet
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fn a_map_nodes_bool(size int) map[string]bool {
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	mut my_map := map[string]bool{} // look this map ...
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	for i in 0 .. size {
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		my_map[u8(65 + i).ascii_str()] = false
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	}
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	return my_map
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}
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// Based in the current node that is final, search for his parent, that is already visited, up to the root or start node
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fn build_path_reverse(graph map[string][]string, start string, final string, visited map[string]bool) []string {
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	print('\n\n Nodes visited (true) or no (false): $visited')
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	array_of_nodes := graph.keys()
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	mut current := final
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	mut path := []string{}
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	path << current
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	for current != start {
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		for i in array_of_nodes {
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			if (current in graph[i]) && (visited[i] == true) {
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				current = i
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				break // the first ocurrence is enough
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			}
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		}
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		path << current // updating the path tracked
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	}
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	return path
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}
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