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v/examples/graphs/dfs.v

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