Graph & Topology Sort
Graph
- Definition
- Graph is very similar to trees
- Directed v.s. Undirected
- Interview Questions
- DFS, BFS
- DAG (Directed Acyclic Graph)
- Topological sort
Graph Representation
- Graph node
- Adjacent matrices
- |V| vertices, then |V|*|V| matrix of 0s and 1s for the graph.
- Adjacent lists
- |V| vertices, then |V| arraylist, each containing the adjacent vertices.
- 2|E| space for undirected, and |E| space for directed.
GraphNode {
int val;
List<GraphNode> neighbors;
}
Topological Sort
A topological sort (sometimes abbreviated toposort) or topological ordering of a directed graph is a linear ordering of its vertices such that for every directed edge uv from vertex u to vertex v, u comes before v in the ordering.
- Maintain a set of vertices with 0-incoming vertices.
- Keep selecting 0-incoming vertex, remove all its outcoming edges, add it into the set.
- If all vertices are merged into 0-incoming vertices set, then topological sort result is found.
Course Schedule
There are a total of n courses you have to take, labeled from 0 to n - 1.
Some courses may have prerequisites, for example to take course 0 you have to first take course 1, which is expressed as a pair: [0,1]
Given the total number of courses and a list of prerequisite pairs, is it possible for you to finish all courses?
Example:
[1, 0], possible; [[1,0], [0,1]], impossible.
Course Schedule
How would we solve it in real life?
- Draw a directed graph, with prerequisite order.
- Select a course which has no prerequisite, and remove all its prerequisite relationships.
- Repeat the above operation until all courses are scheduled or 0-prerequisite course doesn't exist.
- If there are courses not selected, then the courses cannot be scheduled.
Course Schedule
public boolean canFinish(int numCourses, int[][] prerequisites) {
ArrayList<ArrayList<Integer>> graph = new ArrayList<>();
for (int i = 0; i < numCourses; i++) {
graph.add(new ArrayList<Integer>());
}
int[] preNum = new int[numCourses];
for (int i = 0; i < prerequisites.length; i++) {
graph.get(prerequisites[i][1]).add(prerequisites[i][0]);
preNum[prerequisites[i][0]]++;
}
for (int i = 0; i < numCourses; i++) {
boolean availableCourse = false;
for (int j = 0; j < numCourses; j++) {
if (preNum[j] == 0) {
for (int k : graph.get(j)) {
preNum[k]--;
}
availableCourse = true;
preNum[j] = -1;
break;
}
}
if (!availableCourse) {
return false;
}
}
return true;
}Course Schedule
def canFinish(numCourses, prerequisites):
graph = [[] for _ in range(numCourses)]
preNum = [0] * numCourses
for i in range(len(prerequisites)):
graph[prerequisites[i][1]].append(prerequisites[i][0])
preNum[prerequisites[i][0]] += 1
for i in range(numCourses):
availableCourse = False
for j in range(numCourses):
if preNum[j] == 0:
for k in graph[j]:
preNum[k] -= 1
availableCourse = True
preNum[j] = -1
break
if not availableCourse:
return False
return TrueClone Graph
clone an undirected graph. Each node in the graph contains a label and a list of its neighbors.
class Node:
def __init__(self, val = 0, neighbors = None):
self.val = val
self.neighbors = neighbors if neighbors is not None else []Clone Graph
Use BFS/DFS to go through all the nodes
Use Hashmap to remember which nodes has been visited
Clone each node with its label and is neighbors
Clone Graph
public Node cloneGraph(Node node) {
if (node == null) {
return null;
}
Map<Node, Node> map = new HashMap<>();
return dfs(node, map);
}
private Node dfs(Node node, Map<Node, Node> map) {
if (node == null) {
return null;
}
if (map.containsKey(node)) {
return map.get(node);
}
Node copy = new Node(node.val);
map.put(node, copy);
for (Node neighbor : node.neighbors) {
copy.neighbors.add(dfs(neighbor, map));
}
return copy;
}Clone Graph
def cloneGraph(self, node: 'Node') -> 'Node':
if not node:
return None
node_map = {}
def dfs(node):
if node in node_map:
return node_map[node]
clone = Node(node.val)
node_map[node] = clone
for neighbor in node.neighbors:
clone.neighbors.append(dfs(neighbor))
return clone
return dfs(node)
Alien Dictionary
There is a new alien language which uses the latin alphabet. However, the order among letters are unknown to you. You receive a list of words from the dictionary, where words are sorted lexicographically by the rules of this new language. Derive the order of letters in this language.
For example,
Given the following words in dictionary,
[ "wrt", "wrf", "er", "ett", "rftt"]
The correct order is: "wertf".
Alien Dictionary
What do we need to do?
Use the words to get the priority between two letters
Use topology sort to get the information of the order of these letters
Note:
You may assume all letters are in lowercase.
If the order is invalid, return an empty string.
There may be multiple valid order of letters, return any one of them is fine.
Alien Dictionary
public String alienOrder(String[] words) {
Map<Character, Set<Character>> hm = new HashMap<>();
Set<Character> set = new HashSet<>();
Queue<Character> queue = new LinkedList<>();
StringBuilder result = new StringBuilder();
for (String word: words) {
char[] wordArray = word.toCharArray();
for (char c: wordArray) {
set.add(c);
}
}
for (Character c: set) {
hm.put(c, new HashSet<Character>());
}
for (int i = 0; i < words.length-1; i ++) {
int minLen = Math.min(words[i].length(), words[i+1].length());
int j = 0;
for(j = 0; j < minLen; j ++) {
if (words[i].charAt(j) != words[i+1].charAt(j)) {
hm.get(words[i+1].charAt(j)).add(words[i].charAt(j));
break;
}
}
if (j == minLen && words[i].length() > words[i+1].length()) return "";
}
Alien Dictionary
for(Map.Entry<Character, Set<Character>> entry: hm.entrySet()) {
if (entry.getValue().isEmpty()) {
queue.add(entry.getKey());
result.append(entry.getKey());
}
}
while(!queue.isEmpty()) {
Character c = queue.poll();
for(Map.Entry<Character, Set<Character>> entry: hm.entrySet()) {
if (entry.getValue().contains(c)) {
entry.getValue().remove(c);
if (entry.getValue().isEmpty()) {
queue.add(entry.getKey());
result.append(entry.getKey());
}
}
}
}
String finalResult = result.toString();
if (finalResult.length() == set.size()) {
return finalResult;
} else {
return "";
}
}Alien Dictionary
def alienOrder(words):
hm = {}
set = set()
queue = []
result = ""
for word in words:
wordArray = list(word)
for c in wordArray:
set.add(c)
for c in set:
hm[c] = set()
for i in range(len(words)-1):
minLen = min(len(words[i]), len(words[i+1]))
j = 0
for j in range(minLen):
if words[i][j] != words[i+1][j]:
hm[words[i+1][j]].add(words[i][j])
break
if j == minLen and len(words[i]) > len(words[i+1]):
return ""
Alien Dictionary
for c, values in hm.items():
if len(values) == 0:
queue.append(c)
result += c
while len(queue) > 0:
c = queue.pop(0)
for key, values in hm.items():
if c in values:
values.remove(c)
if len(values) == 0:
queue.append(key)
result += key
if len(result) == len(set):
return result
else:
return ""
Minimum Height Trees
For a undirected graph with tree characteristics, we can choose any node as the root. The result graph is then a rooted tree. Among all possible rooted trees, those with minimum height are called minimum height trees (MHTs). Given such a graph, write a function to find all the MHTs and return a list of their root labels.
Examples
Given n = 4, edges = [[1, 0], [1, 2], [1, 3]], return [1].
Given n = 6, edges = [[0, 3], [1, 3], [2, 3], [4, 3], [5, 4]], return [3, 4]
0
|
1
/ \
2 3
0 1 2
\ | /
3
|
4
|
5
Minimum Height Trees
- Calculate the height of trees for every node
- O(|V| * |V|)
Minimum Height Trees
How many Minimum Height Trees can a tree have at most?
0
|
1
/ \
2 3
0
|
1
0
|
1
|
2
At most 2!
Minimum Height Trees
How many Minimum Height Trees can a tree have at most?
We can use a proof by Contradiction
If there are more than 2 nodes that are the roots.
We just choose 3 of them. Then these 3 must become a circle somehow. It contradicts with the definition of tree
Minimum Height Trees
How many Minimum Height Trees can a tree have at most?
We can use a proof by Contradiction
m
h-m
h-m
n
Minimum Height Trees
- Remove all the leaves
- Update the graph
- Keep the process until at most two leaves are left.
public List<Integer> findMinHeightTrees(int n, int[][] edges) {
List<Integer> result = new ArrayList<>();
if (n < 1) return result;
ArrayList<HashSet<Integer>> graph = new ArrayList<>(n);
for (int i = 0; i < n; i++) {
graph.add(new HashSet<>());
}
for (int i = 0; i < edges.length; i++) {
graph.get(edges[i][0]).add(edges[i][1]);
graph.get(edges[i][1]).add(edges[i][0]);
}
Queue<Integer> leaves = new LinkedList<>();
for (int i = 0; i < n; i++) {
if (graph.get(i).size() <= 1) {
leaves.add(i);
}
}
while (n > 2) {
n -= leaves.size();
Queue<Integer> newLeaves = new LinkedList<>();
while (!leaves.isEmpty()) {
Integer leaf = leaves.poll();
Integer neighbor = graph.get(leaf).iterator().next();
graph.get(neighbor).remove(leaf);
if (graph.get(neighbor).size() == 1) {
newLeaves.add(neighbor);
}
}
leaves = newLeaves;
}
return new ArrayList<>(leaves);
}def findMinHeightTrees(n, edges):
if n < 1:
return []
graph = [[] for _ in range(n)]
for edge in edges:
graph[edge[0]].append(edge[1])
graph[edge[1]].append(edge[0])
leaves = []
for i in range(n):
if len(graph[i]) <= 1:
leaves.append(i)
while n > 2:
n -= len(leaves)
newLeaves = []
for leaf in leaves:
neighbor = graph[leaf][0]
graph[neighbor].remove(leaf)
if len(graph[neighbor]) == 1:
newLeaves.append(neighbor)
leaves = newLeaves
return leaves
Homework
Copy of 9 Graph & Topology Sort
By ZhiTongGuiGu
