Posts tagged as “graph”

花花酱 LeetCode 2192. All Ancestors of a Node in a Directed Acyclic Graph

By zxi on March 11, 2022

You are given a positive integer n representing the number of nodes of a Directed Acyclic Graph (DAG). The nodes are numbered from 0 to n - 1 (inclusive).

You are also given a 2D integer array edges, where edges[i] = [from_i, to_i] denotes that there is a unidirectional edge from from_i to to_i in the graph.

Return a list answer, where answer[i] is the list of ancestors of the i^th node, sorted in ascending order.

A node u is an ancestor of another node v if u can reach v via a set of edges.

Example 1:

Input: n = 8, edgeList = [[0,3],[0,4],[1,3],[2,4],[2,7],[3,5],[3,6],[3,7],[4,6]]
Output: [[],[],[],[0,1],[0,2],[0,1,3],[0,1,2,3,4],[0,1,2,3]]
Explanation:
The above diagram represents the input graph.
- Nodes 0, 1, and 2 do not have any ancestors.
- Node 3 has two ancestors 0 and 1.
- Node 4 has two ancestors 0 and 2.
- Node 5 has three ancestors 0, 1, and 3.
- Node 6 has five ancestors 0, 1, 2, 3, and 4.
- Node 7 has four ancestors 0, 1, 2, and 3.

Example 2:

Input: n = 5, edgeList = [[0,1],[0,2],[0,3],[0,4],[1,2],[1,3],[1,4],[2,3],[2,4],[3,4]]
Output: [[],[0],[0,1],[0,1,2],[0,1,2,3]]
Explanation:
The above diagram represents the input graph.
- Node 0 does not have any ancestor.
- Node 1 has one ancestor 0.
- Node 2 has two ancestors 0 and 1.
- Node 3 has three ancestors 0, 1, and 2.
- Node 4 has four ancestors 0, 1, 2, and 3.

Constraints:

1 <= n <= 1000
0 <= edges.length <= min(2000, n * (n - 1) / 2)
edges[i].length == 2
0 <= from_i, to_i <= n - 1
from_i != to_i
There are no duplicate edges.
The graph is directed and acyclic.

Solution: DFS

For each source node S, add it to all its reachable nodes by traversing the entire graph.
In one pass, only traverse each child node at most once.

Time complexity: O(VE)
Space complexity: (V+E)

C++

// Author: Huahua

class Solution {

public:

vector<vector<int>> getAncestors(int n, vector<vector<int>>& edges) {

vector<vector<int>> ans(n);

vector<vector<int>> g(n);

for (const auto& e : edges)

g[e[0]].push_back(e[1]);

function<void(int, int)> dfs = [&](int s, int u) -> void {

for (int v : g[u]) {

if (ans[v].empty() || ans[v].back() != s) {

ans[v].push_back(s);

dfs(s, v);

}

};

for (int i = 0; i < n; ++i)

dfs(i, i);

return ans;

}

};

花花酱 LeetCode 2157. Groups of Strings

By zxi on February 6, 2022

You are given a 0-indexed array of strings words. Each string consists of lowercase English letters only. No letter occurs more than once in any string of words.

Two strings s1 and s2 are said to be connected if the set of letters of s2 can be obtained from the set of letters of s1 by any one of the following operations:

Adding exactly one letter to the set of the letters of s1.
Deleting exactly one letter from the set of the letters of s1.
Replacing exactly one letter from the set of the letters of s1 with any letter, including itself.

The array words can be divided into one or more non-intersecting groups. A string belongs to a group if any one of the following is true:

It is connected to at least one other string of the group.
It is the only string present in the group.

Note that the strings in words should be grouped in such a manner that a string belonging to a group cannot be connected to a string present in any other group. It can be proved that such an arrangement is always unique.

Return an array ans of size 2 where:

ans[0] is the total number of groups words can be divided into, and
ans[1] is the size of the largest group.

Example 1:

Input: words = ["a","b","ab","cde"]
Output: [2,3]
Explanation:
- words[0] can be used to obtain words[1] (by replacing 'a' with 'b'), and words[2] (by adding 'b'). So words[0] is connected to words[1] and words[2].
- words[1] can be used to obtain words[0] (by replacing 'b' with 'a'), and words[2] (by adding 'a'). So words[1] is connected to words[0] and words[2].
- words[2] can be used to obtain words[0] (by deleting 'b'), and words[1] (by deleting 'a'). So words[2] is connected to words[0] and words[1].
- words[3] is not connected to any string in words.
Thus, words can be divided into 2 groups ["a","b","ab"] and ["cde"]. The size of the largest group is 3.

Example 2:

Input: words = ["a","ab","abc"]
Output: [1,3]
Explanation:
- words[0] is connected to words[1].
- words[1] is connected to words[0] and words[2].
- words[2] is connected to words[1].
Since all strings are connected to each other, they should be grouped together.
Thus, the size of the largest group is 3.

Constraints:

1 <= words.length <= 2 * 10⁴
1 <= words[i].length <= 26
words[i] consists of lowercase English letters only.
No letter occurs more than once in words[i].

Solution: Bitmask + DFS

Use a bitmask to represent a string. Use dfs to find connected components.

Time complexity: O(n*26²)
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

vector<int> groupStrings(vector<string>& words) {

unordered_map<int, int> m;

for (const string& w : words)

++m[accumulate(begin(w), end(w), 0, [](int k, char c){ return k | (1 << (c - 'a')); })];

function<int(int)> dfs = [&](int mask) {

auto it = m.find(mask);

if (it == end(m)) return 0;

int ans = it->second;

m.erase(it);

for (int i = 0; i < 26; ++i) {

ans += dfs(mask ^ (1 << i));

for (int j = i + 1; j < 26; ++j)

if ((mask >> i & 1) != (mask >> j & 1))

ans += dfs(mask ^ (1 << i) ^ (1 << j));

}

return ans;

};

int size = 0;

int groups = 0;

while (!m.empty()) {

size = max(size, dfs(begin(m)->first));

++groups;

}

return {groups, size};

}

};

花花酱 LeetCode 1998. GCD Sort of an Array

By zxi on December 31, 2021

You are given an integer array nums, and you can perform the following operation any number of times on nums:

Swap the positions of two elements nums[i] and nums[j] if gcd(nums[i], nums[j]) > 1 where gcd(nums[i], nums[j]) is the greatest common divisor of nums[i] and nums[j].

Return true if it is possible to sort nums in non-decreasing order using the above swap method, or false otherwise.

Example 1:

Input: nums = [7,21,3]
Output: true
Explanation: We can sort [7,21,3] by performing the following operations:
- Swap 7 and 21 because gcd(7,21) = 7. nums = [21,7,3]
- Swap 21 and 3 because gcd(21,3) = 3. nums = [3,7,21]

Example 2:

Input: nums = [5,2,6,2]
Output: false
Explanation: It is impossible to sort the array because 5 cannot be swapped with any other element.

Example 3:

Input: nums = [10,5,9,3,15]
Output: true
We can sort [10,5,9,3,15] by performing the following operations:
- Swap 10 and 15 because gcd(10,15) = 5. nums = [15,5,9,3,10]
- Swap 15 and 3 because gcd(15,3) = 3. nums = [3,5,9,15,10]
- Swap 10 and 15 because gcd(10,15) = 5. nums = [3,5,9,10,15]

Constraints:

1 <= nums.length <= 3 * 10⁴
2 <= nums[i] <= 10⁵

Solution: Union-Find

Let nums[j]’s target position be i. In order to put nums[j] to pos i by swapping. nums[i] and nums[j] must be in the same connected component. There is an edge between two numbers if they have gcd > 1.

We union two numbers if their have gcd > 1. However, it will be TLE if we do all pairs . Thus, for each number, we union it with its divisors instead.

Time complexity: O(n²) TLE -> O(sum(sqrt(nums[i]))) <= O(n*sqrt(m))
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

bool gcdSort(vector<int>& nums) {

const int m = *max_element(begin(nums), end(nums));

const int n = nums.size();

vector<int> p(m + 1);

iota(begin(p), end(p), 0);

function<int(int)> find = [&](int x) {

return p[x] == x ? x : (p[x] = find(p[x]));

};

for (int x : nums)

for (int d = 2; d <= sqrt(x); ++d)

if (x % d == 0)

p[find(x)] = p[find(x / d)] = find(d);

vector<int> sorted(nums);

sort(begin(sorted), end(sorted));

for (int i = 0; i < n; ++i)

if (find(sorted[i]) != find(nums[i]))

return false;

return true;

}

};

花花酱 LeetCode 2115. Find All Possible Recipes from Given Supplies

By zxi on December 26, 2021

You have information about n different recipes. You are given a string array recipes and a 2D string array ingredients. The i^th recipe has the name recipes[i], and you can create it if you have all the needed ingredients from ingredients[i]. Ingredients to a recipe may need to be created from other recipes, i.e., ingredients[i] may contain a string that is in recipes.

You are also given a string array supplies containing all the ingredients that you initially have, and you have an infinite supply of all of them.

Return a list of all the recipes that you can create. You may return the answer in any order.

Note that two recipes may contain each other in their ingredients.

Example 1:

Input: recipes = ["bread"], ingredients = [["yeast","flour"]], supplies = ["yeast","flour","corn"]
Output: ["bread"]
Explanation:
We can create "bread" since we have the ingredients "yeast" and "flour".

Example 2:

Input: recipes = ["bread","sandwich"], ingredients = [["yeast","flour"],["bread","meat"]], supplies = ["yeast","flour","meat"]
Output: ["bread","sandwich"]
Explanation:
We can create "bread" since we have the ingredients "yeast" and "flour".
We can create "sandwich" since we have the ingredient "meat" and can create the ingredient "bread".

Example 3:

Input: recipes = ["bread","sandwich","burger"], ingredients = [["yeast","flour"],["bread","meat"],["sandwich","meat","bread"]], supplies = ["yeast","flour","meat"]
Output: ["bread","sandwich","burger"]
Explanation:
We can create "bread" since we have the ingredients "yeast" and "flour".
We can create "sandwich" since we have the ingredient "meat" and can create the ingredient "bread".
We can create "burger" since we have the ingredient "meat" and can create the ingredients "bread" and "sandwich".

Constraints:

n == recipes.length == ingredients.length
1 <= n <= 100
1 <= ingredients[i].length, supplies.length <= 100
1 <= recipes[i].length, ingredients[i][j].length, supplies[k].length <= 10
recipes[i], ingredients[i][j], and supplies[k] consist only of lowercase English letters.
All the values of recipes and supplies combined are unique.
Each ingredients[i] does not contain any duplicate values.

Solution: Brute Force

C++

// Author: Huahua

class Solution {

public:

vector<string> findAllRecipes(vector<string>& recipes, vector<vector<string>>& ingredients, vector<string>& supplies) {

const int n = recipes.size();

unordered_set<string> s(begin(supplies), end(supplies));

vector<string> ans;

vector<int> seen(n);

while (true) {

bool newSupply = false;

for (int i = 0; i < n; ++i) {

if (seen[i]) continue;

bool hasAll = true;

for (const string& ingredient : ingredients[i])

if (!s.count(ingredient)) {

hasAll = false;

break;

}

if (!hasAll) continue;

ans.push_back(recipes[i]);

seen[i] = 1;

s.insert(recipes[i]);

newSupply = true;

}

if (!newSupply) break;

}

return ans;

}

};

花花酱 LeetCode 2097. Valid Arrangement of Pairs

By zxi on December 5, 2021

You are given a 0-indexed 2D integer array pairs where pairs[i] = [start_i, end_i]. An arrangement of pairs is valid if for every index i where 1 <= i < pairs.length, we have end_i-1 == start_i.

Return any valid arrangement of pairs.

Note: The inputs will be generated such that there exists a valid arrangement of pairs.

Example 1:

Input: pairs = [[5,1],[4,5],[11,9],[9,4]]
Output: [[11,9],[9,4],[4,5],[5,1]]
Explanation:
This is a valid arrangement since end_i-1 always equals start_i.
end₀ = 9 == 9 = start₁ 
end₁ = 4 == 4 = start₂
end₂ = 5 == 5 = start₃

Example 2:

Input: pairs = [[1,3],[3,2],[2,1]]
Output: [[1,3],[3,2],[2,1]]
Explanation:
This is a valid arrangement since end_i-1 always equals start_i.
end₀ = 3 == 3 = start₁
end₁ = 2 == 2 = start₂
The arrangements [[2,1],[1,3],[3,2]] and [[3,2],[2,1],[1,3]] are also valid.

Example 3:

Input: pairs = [[1,2],[1,3],[2,1]]
Output: [[1,2],[2,1],[1,3]]
Explanation:
This is a valid arrangement since end_i-1 always equals start_i.
end₀ = 2 == 2 = start₁
end₁ = 1 == 1 = start₂

Constraints:

1 <= pairs.length <= 10⁵
pairs[i].length == 2
0 <= start_i, end_i <= 10⁹
start_i != end_i
No two pairs are exactly the same.
There exists a valid arrangement of pairs.

Solution: Eulerian trail

The goal of the problem is to find a Eulerian trail in the graph.

If there is a vertex whose out degree – in degree == 1 which means it’s the starting vertex. Otherwise wise, the graph must have a Eulerian circuit thus we can start from any vertex.

We can use Hierholzer’s algorithm to find it.

Time complexity: O(|V| + |E|)
Space complexity: O(|V| + |E|)

C++

// Author: Huahua

class Solution {

public:

vector<vector<int>> validArrangement(vector<vector<int>>& pairs) {

unordered_map<int, queue<int>> g;

unordered_map<int, int> degree; // out - in

for (const auto& p : pairs) {

g[p[0]].push(p[1]);

++degree[p[0]];

--degree[p[1]];

}

int s = pairs[0][0];

for (const auto& [u, d] : degree)

if (d == 1) s = u;

vector<vector<int>> ans;

function<void(int)> dfs = [&](int u) {

while (!g[u].empty()) {

int v = g[u].front(); g[u].pop();

dfs(v);

ans.push_back({u, v});

}

};

dfs(s);

return {rbegin(ans), rend(ans)};

}

};

Python3

# Author: Huahua

class Solution:

def validArrangement(self, pairs: List[List[int]]) -> List[List[int]]:

g = defaultdict(list)

d = defaultdict(int)

for u, v in pairs:

g[u].append(v)

d[u] += 1

d[v] -= 1

s = pairs[0][0]

for u in d:

if d[u] == 1: s = u

ans = []

def dfs(u: int) -> None:

while g[u]:

v = g[u].pop()

dfs(v)

ans.append([u, v])

dfs(s)

return ans[::-1]