# Posts tagged as “DFS”

Given a 2D grid consisting of 1s (land) and 0s (water).  An island is a maximal 4-directionally (horizontal or vertical) connected group of 1s.

The grid is said to be connected if we have exactly one island, otherwise is said disconnected.

In one day, we are allowed to change any single land cell (1) into a water cell (0).

Return the minimum number of days to disconnect the grid.

Example 1:

Input: grid = [[0,1,1,0],[0,1,1,0],[0,0,0,0]]
Output: 2
Explanation: We need at least 2 days to get a disconnected grid.
Change land grid and grid to water and get 2 disconnected island.


Example 2:

Input: grid = [[1,1]]
Output: 2
Explanation: Grid of full water is also disconnected ([[1,1]] -> [[0,0]]), 0 islands.


Example 3:

Input: grid = [[1,0,1,0]]
Output: 0


Example 4:

Input: grid = [[1,1,0,1,1],
[1,1,1,1,1],
[1,1,0,1,1],
[1,1,0,1,1]]
Output: 1


Example 5:

Input: grid = [[1,1,0,1,1],
[1,1,1,1,1],
[1,1,0,1,1],
[1,1,1,1,1]]
Output: 2


Constraints:

• 1 <= grid.length, grid[i].length <= 30
• grid[i][j] is 0 or 1.

## Solution: Brute Force

We need at most two days to disconnect an island.
1. check if we have more than one islands. (0 days)
2. For each 1 cell, change it to 0 and check how many islands do we have. (1 days)
3. Otherwise, 2 days

Time complexity: O(m^2*n^2)
Space complexity: O(m*n)

## C++

Given a 2D array of characters grid of size m x n, you need to find if there exists any cycle consisting of the same value in grid.

A cycle is a path of length 4 or more in the grid that starts and ends at the same cell. From a given cell, you can move to one of the cells adjacent to it – in one of the four directions (up, down, left, or right), if it has the same value of the current cell.

Also, you cannot move to the cell that you visited in your last move. For example, the cycle (1, 1) -> (1, 2) -> (1, 1) is invalid because from (1, 2) we visited (1, 1) which was the last visited cell.

Return true if any cycle of the same value exists in grid, otherwise, return false.

Example 1:

Input: grid = [["a","a","a","a"],["a","b","b","a"],["a","b","b","a"],["a","a","a","a"]]
Output: true
Explanation: There are two valid cycles shown in different colors in the image below:



Example 2:

Input: grid = [["c","c","c","a"],["c","d","c","c"],["c","c","e","c"],["f","c","c","c"]]
Output: true
Explanation: There is only one valid cycle highlighted in the image below:



Example 3:

Input: grid = [["a","b","b"],["b","z","b"],["b","b","a"]]
Output: false


Constraints:

• m == grid.length
• n == grid[i].length
• 1 <= m <= 500
• 1 <= n <= 500
• grid consists only of lowercase English letters.

## Solution: DFS

Finding a cycle in an undirected graph => visiting a node that has already been visited and it’s not the parent node of the current node.
b b
b b
null -> (0, 0) -> (0, 1) -> (1, 1) -> (1, 0) -> (0, 0)
The second time we visit (0, 0) which has already been visited before and it’s not the parent of the current node (1, 0) ( (1, 0)’s parent is (1, 1) ) which means we found a cycle.

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

## C++

Given a binary tree, write a function to get the maximum width of the given tree. The width of a tree is the maximum width among all levels. The binary tree has the same structure as a full binary tree, but some nodes are null.

The width of one level is defined as the length between the end-nodes (the leftmost and right most non-null nodes in the level, where the null nodes between the end-nodes are also counted into the length calculation.

Example 1:

Input:

1
/   \
3     2
/ \     \
5   3     9

Output: 4
Explanation: The maximum width existing in the third level with the length 4 (5,3,null,9).


Example 2:

Input:

1
/
3
/ \
5   3

Output: 2
Explanation: The maximum width existing in the third level with the length 2 (5,3).


Example 3:

Input:

1
/ \
3   2
/
5

Output: 2
Explanation: The maximum width existing in the second level with the length 2 (3,2).


Example 4:

Input:

1
/ \
3   2
/     \
5       9
/         \
6           7
Output: 8
Explanation:The maximum width existing in the fourth level with the length 8 (6,null,null,null,null,null,null,7).

## Solution: DFS

Let us assign an id to each node, similar to the index of a heap. root is 1, left child = parent * 2, right child = parent * 2 + 1. Width = id(right most child) – id(left most child) + 1, so far so good.
However, this kind of id system grows exponentially, it overflows even with long type with just 64 levels. To avoid that, we can remap the id with id – id(left most child of each level).

Time complexity: O(n)
Space complexity: O(h)

## Python3

Given 2n balls of k distinct colors. You will be given an integer array balls of size k where balls[i] is the number of balls of color i

All the balls will be shuffled uniformly at random, then we will distribute the first n balls to the first box and the remaining n balls to the other box (Please read the explanation of the second example carefully).

Please note that the two boxes are considered different. For example, if we have two balls of colors a and b, and two boxes [] and (), then the distribution [a] (b) is considered different than the distribution [b] (a) (Please read the explanation of the first example carefully).

We want to calculate the probability that the two boxes have the same number of distinct balls.

Example 1:

Input: balls = [1,1]
Output: 1.00000
Explanation: Only 2 ways to divide the balls equally:
- A ball of color 1 to box 1 and a ball of color 2 to box 2
- A ball of color 2 to box 1 and a ball of color 1 to box 2
In both ways, the number of distinct colors in each box is equal. The probability is 2/2 = 1


Example 2:

Input: balls = [2,1,1]
Output: 0.66667
Explanation: We have the set of balls [1, 1, 2, 3]
This set of balls will be shuffled randomly and we may have one of the 12 distinct shuffles with equale probability (i.e. 1/12):
[1,1 / 2,3], [1,1 / 3,2], [1,2 / 1,3], [1,2 / 3,1], [1,3 / 1,2], [1,3 / 2,1], [2,1 / 1,3], [2,1 / 3,1], [2,3 / 1,1], [3,1 / 1,2], [3,1 / 2,1], [3,2 / 1,1]
After that we add the first two balls to the first box and the second two balls to the second box.
We can see that 8 of these 12 possible random distributions have the same number of distinct colors of balls in each box.
Probability is 8/12 = 0.66667


Example 3:

Input: balls = [1,2,1,2]
Output: 0.60000
Explanation: The set of balls is [1, 2, 2, 3, 4, 4]. It is hard to display all the 180 possible random shuffles of this set but it is easy to check that 108 of them will have the same number of distinct colors in each box.
Probability = 108 / 180 = 0.6


Example 4:

Input: balls = [3,2,1]
Output: 0.30000
Explanation: The set of balls is [1, 1, 1, 2, 2, 3]. It is hard to display all the 60 possible random shuffles of this set but it is easy to check that 18 of them will have the same number of distinct colors in each box.
Probability = 18 / 60 = 0.3


Example 5:

Input: balls = [6,6,6,6,6,6]
Output: 0.90327


Constraints:

• 1 <= balls.length <= 8
• 1 <= balls[i] <= 6
• sum(balls) is even.
• Answers within 10^-5 of the actual value will be accepted as correct.

## Solution 0: Permutation (TLE)

Enumerate all permutations of the balls, count valid ones and divide that by the total.

Time complexity: O((8*6)!) = O(48!)
After deduplication: O(48!/(6!)^8) ~ 1.7e38
Space complexity: O(8*6)

## Solution 1: Combination

For each color, put n_i balls into box1, the left t_i – n_i balls go to box2.
permutations = fact(n//2) / PROD(fact(n_i)) * fact(n//2) * PROD(fact(t_i – n_i))
E.g
balls = [1×2, 2×6, 3×4]
One possible combination:
box1: 1 22 333
box2: 1 2222 3
permutations = 6! / (1! * 2! * 3!) * 6! / (1! * 4! * 1!) = 1800

Time complexity: O((t+1)^k) = O(7^8)
Space complexity: O(k + (t*k)) = O(8 + 48)

vector version

## C++

happy string is a string that:

• consists only of letters of the set ['a', 'b', 'c'].
• s[i] != s[i + 1] for all values of i from 1 to s.length - 1 (string is 1-indexed).

For example, strings “abc”, “ac”, “b” and “abcbabcbcb” are all happy strings and strings “aa”, “baa” and “ababbc” are not happy strings.

Given two integers n and k, consider a list of all happy strings of length n sorted in lexicographical order.

Return the kth string of this list or return an empty string if there are less than k happy strings of length n.

Example 1:

Input: n = 1, k = 3
Output: "c"
Explanation: The list ["a", "b", "c"] contains all happy strings of length 1. The third string is "c".


Example 2:

Input: n = 1, k = 4
Output: ""
Explanation: There are only 3 happy strings of length 1.


Example 3:

Input: n = 3, k = 9
Output: "cab"
Explanation: There are 12 different happy string of length 3 ["aba", "abc", "aca", "acb", "bab", "bac", "bca", "bcb", "cab", "cac", "cba", "cbc"]. You will find the 9th string = "cab"


Example 4:

Input: n = 2, k = 7
Output: ""


Example 5:

Input: n = 10, k = 100
Output: "abacbabacb"


Constraints:

• 1 <= n <= 10
• 1 <= k <= 100

## Solution: DFS

Generate the happy strings in lexical order, store the k-th one.
Time complexity: O(n + k)
Space complexity: O(n)

## C++

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