4.1. route between nodes in graph

This commit is contained in:
anebz 2019-10-15 09:52:04 +02:00
parent 2a40eebc1c
commit 0b23f63b46
4 changed files with 188 additions and 0 deletions

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import java.util.LinkedList;
public class Question {
public enum State {
Unvisited, Visited, Visiting;
}
public static void main(String a[])
{
Graph g = createNewGraph();
Node[] n = g.getNodes();
Node start = n[3];
Node end = n[5];
System.out.println(search(g, start, end));
}
public static Graph createNewGraph()
{
Graph g = new Graph();
Node[] temp = new Node[6];
temp[0] = new Node("a", 3);
temp[1] = new Node("b", 0);
temp[2] = new Node("c", 0);
temp[3] = new Node("d", 1);
temp[4] = new Node("e", 1);
temp[5] = new Node("f", 0);
temp[0].addAdjacent(temp[1]);
temp[0].addAdjacent(temp[2]);
temp[0].addAdjacent(temp[3]);
temp[3].addAdjacent(temp[4]);
temp[4].addAdjacent(temp[5]);
for (int i = 0; i < 6; i++) {
g.addNode(temp[i]);
}
return g;
}
public static boolean search(Graph g, Node start, Node end) {
LinkedList<Node> q = new LinkedList<Node>();
for (Node u : g.getNodes()) {
u.state = State.Unvisited;
}
start.state = State.Visiting;
q.add(start);
Node u;
while(!q.isEmpty()) {
u = q.removeFirst();
if (u != null) {
for (Node v : u.getAdjacent()) {
if (v.state == State.Unvisited) {
if (v == end) {
return true;
} else {
v.state = State.Visiting;
q.add(v);
}
}
}
u.state = State.Visited;
}
}
return false;
}
}

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# 4.1. Route between nodes
> Given a directed graph and two nodes (S and E), is there a route from S to E?
A graph can be written like this:
```java
class Graph {
public Node[] nodes;
}
class Node {
public String name;
public Node[] children;
}
```
The function to find a route from S to E:
```java
bool findRoute(Node S, Node E) {
Node[] children = S.children;
for (int i = 0; i < children.size(); i++){
if (children[i] == E) {
return True;
}
if (children[i].children == Null) {
continue;
}
else if (findRoute(Node children[i].children, E)){
return True;
}
}
return False;
}
```
Example, Route from 5 to 11:
* 5
* 2
* 3
* 4
* 1
* 9
* 11
* 6
1. children = [2, 1, 6]
1. Recursive of 2, children = [3, 4]
2. None of them have children, continue, return False
2. Back to main loop, continue with children
1. recursive of 1, children = [9, 11]
2. found in children[1] == E, return True
3. Back to main loop, return True
Looks good, O(N) where N = all elements in graph, well if the graph isn't balanced at all we might have to iterate through it all.
## Hints
Two well known algorithms can do this, what are the tradeoffs between them?
1. Depth-first search (mine)
1. Check each node until the end
2. Breadth-first search
1. Cheack each main children first, then go deep
## Solution
Remember to **mark the found nodes as visited to avoid cycles and repetitions of nodes**.
For an iterative solution of breadh-first search, see Java files.
Depth-first search is a bit simpler to implement since it can be done with simple recursion. Breadth-first search can also be useful to find the shortest path, whereas depth-first search might traverse one adjacent node very deeply before ever going onto the immediate neighbors.

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public class Graph {
public static int MAX_VERTICES = 6;
private Node vertices[];
public int count;
public Graph() {
vertices = new Node[MAX_VERTICES];
count = 0;
}
public void addNode(Node x) {
if (count < vertices.length) {
vertices[count] = x;
count++;
} else {
System.out.print("Graph full");
}
}
public Node[] getNodes() {
return vertices;
}
}

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class Node {
private Node adjacent[];
public int adjacentCount;
private String vertex;
public Question.State state;
public Node(String vertex, int adjacentLength) {
this.vertex = vertex;
adjacentCount = 0;
adjacent = new Node[adjacentLength];
}
public void addAdjacent(Node x) {
if (adjacentCount < adjacent.length) {
this.adjacent[adjacentCount] = x;
adjacentCount++;
} else {
System.out.print("No more adjacent can be added");
}
}
public Node[] getAdjacent() {
return adjacent;
}
public String getVertex() {
return vertex;
}
}