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105 lines
3.2 KiB
V
105 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 H 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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mut visited := visited_init(graph) // a map fully with false in all vertex
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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 aa map to initialize with of visited nodes .... all with false in the init
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// so these nodes are NOT VISITED YET
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fn visited_init(a_graph map[string][]string) map[string]bool {
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mut temp := map[string]bool{} // attention in these initializations with maps
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for i, _ in a_graph {
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temp[i] = false
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}
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return temp
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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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//*****************************************************
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