examples: add 2 more graph search examples (DFS and BFS), move them into `examples/graphs` (#14131)
Claudio Cesar de Sá
GitHub
parent
5dce091379
commit
a2db44bc38
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@ -1,3 +1,18 @@
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fn main() {
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graph := {
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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': ['B', 'F']
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'F': ['C', 'E']
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}
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println('Graph: $graph')
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path := breadth_first_search_path(graph, 'A', 'F')
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println('The shortest path from node A to node F is: $path')
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assert path == ['A', 'C', 'F']
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}
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// Breadth-First Search (BFS) allows you to find the shortest distance between two nodes in the graph.
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fn breadth_first_search_path(graph map[string][]string, vertex string, target string) []string {
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mut path := []string{}
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@ -24,18 +39,3 @@ fn breadth_first_search_path(graph map[string][]string, vertex string, target st
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}
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return path
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}
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fn main() {
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graph := {
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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': ['B', 'F']
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'F': ['C', 'E']
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}
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println('Graph: $graph')
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path := breadth_first_search_path(graph, 'A', 'F')
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println('The shortest path from node A to node F is: $path')
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assert path == ['A', 'C', 'F']
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}
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@ -0,0 +1,92 @@
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// 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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graph := {
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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': ['B', 'F']
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'F': ['C', 'E']
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}
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println('Graph: $graph')
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path := breadth_first_search_path(graph, 'A', 'F')
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println('\n The shortest path from node A to node F is: $path.reverse()')
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}
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// Breadth-First Search (BFS) allows you to find the shortest distance between two nodes in the graph.
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fn breadth_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 queue := []string{} // a queue ... many paths
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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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// a map to store all the nodes visited to avoid cycles
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// start all them with False, not visited yet
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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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queue << start // first arrival
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for queue.len != 0 {
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mut node := departure(mut queue) // get the front node and remove it
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if visited[node] == false { // check if this node is already visited
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// if no ... test it searchinf for a final node
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visited[node] = true // means: visit this node
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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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// Expansion of node removed from queue
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print('\n Expansion of node $node (true/false): ${graph[node]}')
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// take all nodes from the node
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for vertex in graph[node] { // println("\n ...${vertex}")
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// not explored yet
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if visited[vertex] == false {
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queue << vertex
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}
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}
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print('\n QUEUE: $queue (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 VISITED nodes ...
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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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base := u8(65)
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mut key := base.ascii_str()
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for i in 0 .. size {
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key = u8(base + i).ascii_str()
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my_map[key] = false
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}
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return my_map
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}
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// classical removing of a node from the start of a queue
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fn departure(mut queue []string) string {
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mut x := queue[0]
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queue.delete(0)
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return x
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}
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// Based in the current node that is final, search for its parent, 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 // update the path tracked
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}
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return path
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}
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@ -0,0 +1,103 @@
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// 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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