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v/examples/graphs/dfs2.v

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// Author: CCS & KeitoTobi1
// Backtracking Supported.
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: all path pattern from node A to node F is:')
print_pattern(path_01)
path_02 := depth_first_search_path(graph_02, 'A', 'H')
println('\n Graph_02: all path pattern from node A to node F is:')
print_pattern(path_02)
}
fn depth_first_search_path(adj map[string][]string, start string, target string) [][]string {
mut sol := Solution{}
mut path := []string{}
mut visited := visited_init(adj)
// false ... not visited yet: {'A': false, 'B': false, 'C': false, 'D': false, 'E': false}
sol.find_pattern(adj, mut visited, start, target, mut path)
return sol.pattern
}
struct Solution {
pub mut:
pattern [][]string
}
fn (mut s Solution) find_pattern(adj map[string][]string, mut visited map[string]bool, node string, target string, mut path []string) {
path << node
visited[node] = true
if node == target {
print('\n Founded pattern: ${path}')
s.pattern << [path]
}
print('\n Exploring of node ${node} (true/false): ${adj[node]}')
for i, _ in adj[node] {
if !visited[adj[node][i]] {
mut temp := path.clone()
s.find_pattern(adj, mut visited, adj[node][i], target, mut temp)
}
}
visited[node] = false
print('\n Current: ${node} (only not visited) \n Visited: ${visited}')
}
fn print_pattern(pat [][]string) {
for p in pat {
println(p)
}
}
// 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(adj map[string][]string) map[string]bool {
mut temp := map[string]bool{}
for i, _ in adj {
temp[i] = false
}
return temp
}