Posts published in July 2018

花花酱 LeetCode 881. Random Flip Matrix

By zxi on July 31, 2018

Problem

You are given the number of rows n_rows and number of columns n_cols of a 2D binary matrix where all values are initially 0. Write a function flip which chooses a 0 value uniformly at random, changes it to 1, and then returns the position [row.id, col.id] of that value. Also, write a function reset which sets all values back to 0. Try to minimize the number of calls to system’s Math.random() and optimize the time and space complexity.

Note:

1 <= n_rows, n_cols <= 10000
0 <= row.id < n_rows and 0 <= col.id < n_cols
flip will not be called when the matrix has no 0 values left.
the total number of calls to flip and reset will not exceed 1000.

Example 1:

Input: 
["Solution","flip","flip","flip","flip"]
[[2,3],[],[],[],[]]
Output: [null,[0,1],[1,2],[1,0],[1,1]]

Example 2:

Input: 
["Solution","flip","flip","reset","flip"]
[[1,2],[],[],[],[]]
Output: [null,[0,0],[0,1],null,[0,0]]

Explanation of Input Syntax:

The input is two lists: the subroutines called and their arguments. Solution‘s constructor has two arguments, n_rows and n_cols. flip and reset have no arguments. Arguments are always wrapped with a list, even if there aren’t any.

Solution 1: Hashtable + Resample

Time complexity: O(|flip|) = O(1000) = O(1)

Space complexity: O(|flip|) = O(1000) = O(1)

// Author: Huahua

// Running time: 12 ms

class Solution {

public:

Solution(int n_rows, int n_cols):

rows_(n_rows), cols_(n_cols), n_(rows_ * cols_) {}

vector<int> flip() {

int index = rand() % n_;

while (m_.count(index))

index = rand() % n_;

m_.insert(index);

return {index / cols_, index % cols_};

}

void reset() {

m_.clear();

n_ = rows_ * cols_;

}

private:

const int rows_;

const int cols_;

int n_;

unordered_set<int> m_;

};

Solution 2: Fisher–Yates shuffle

Generate a random shuffle of 0 to n – 1, one number at a time.

Time complexity: flip: O(1)

Space complexity: O(|flip|) = O(1000) = O(1)

C++

// Author: Huahua

// Running time: 12 ms

class Solution {

public:

Solution(int n_rows, int n_cols):

rows_(n_rows), cols_(n_cols), n_(rows_ * cols_) {}

vector<int> flip() {

int s = rand() % (n_--);

int index = s;

if (m_.count(s))

index = m_[s];

m_[s] = m_.count(n_) ? m_[n_] : n_;

return {index / cols_, index % cols_};

}

void reset() {

m_.clear();

n_ = rows_ * cols_;

}

private:

const int rows_;

const int cols_;

int n_;

unordered_map<int, int> m_;

};

Upgraded to HTTPS

By zxi on July 31, 2018

Purchased a SSL certificate and upgraded the blog to full https.

Please visit https://zxi.mytechroad.com/blog

Let me know if you encounter any problems.

花花酱 LeetCode 855. Exam Room

By zxi on July 29, 2018

Problem

In an exam room, there are N seats in a single row, numbered 0, 1, 2, ..., N-1.

When a student enters the room, they must sit in the seat that maximizes the distance to the closest person. If there are multiple such seats, they sit in the seat with the lowest number. (Also, if no one is in the room, then the student sits at seat number 0.)

Return a class ExamRoom(int N) that exposes two functions: ExamRoom.seat() returning an int representing what seat the student sat in, and ExamRoom.leave(int p) representing that the student in seat number p now leaves the room. It is guaranteed that any calls to ExamRoom.leave(p) have a student sitting in seat p.

Example 1:

Input: ["ExamRoom","seat","seat","seat","seat","leave","seat"], [[10],[],[],[],[],[4],[]]
Output: [null,0,9,4,2,null,5]
Explanation:
ExamRoom(10) -> null
seat() -> 0, no one is in the room, then the student sits at seat number 0.
seat() -> 9, the student sits at the last seat number 9.
seat() -> 4, the student sits at the last seat number 4.
seat() -> 2, the student sits at the last seat number 2.
leave(4) -> null
seat() -> 5, the student sits at the last seat number 5.

Note:

1 <= N <= 10^9
ExamRoom.seat() and ExamRoom.leave() will be called at most 10^4 times across all test cases.
Calls to ExamRoom.leave(p) are guaranteed to have a student currently sitting in seat number p.

Solution: BST

Use a BST (ordered set) to track the current seatings.

Time Complexity:

init: O(1)

seat: O(P)

leave: O(logP)

Space complexity: O(P)

// Author: Huahua

// Running time: 24 ms

class ExamRoom {

public:

ExamRoom(int N): N_(N) {}

int seat() {

int p = 0;

int max_dist = s_.empty() ? 0 : *s_.begin();

auto left = s_.begin();

auto right = left;

while (left != s_.end()) {

++right;

int l = *left;

int r = right != s_.end() ? *right : (2 * (N_ - 1) - *left);

int d = (r - l) / 2;

if (d > max_dist) {

max_dist = d;

p = l + d;

}

left = right;

}

s_.insert(p);

return p;

}

void leave(int p) {

s_.erase(p);

}

private:

const int N_;

set<int> s_;

};

花花酱 LeetCode 879. Profitable Schemes

By zxi on July 28, 2018

Problem

There are G people in a gang, and a list of various crimes they could commit.

The i-th crime generates a profit[i] and requires group[i] gang members to participate.

If a gang member participates in one crime, that member can’t participate in another crime.

Let’s call a profitable scheme any subset of these crimes that generates at least P profit, and the total number of gang members participating in that subset of crimes is at most G.

How many schemes can be chosen? Since the answer may be very large, return it modulo 10^9 + 7.

Example 1:

Input: G = 5, P = 3, group = [2,2], profit = [2,3]
Output: 2
Explanation: 
To make a profit of at least 3, the gang could either commit crimes 0 and 1, or just crime 1.
In total, there are 2 schemes.

Example 2:

Input: G = 10, P = 5, group = [2,3,5], profit = [6,7,8]
Output: 7
Explanation: 
To make a profit of at least 5, the gang could commit any crimes, as long as they commit one.
There are 7 possible schemes: (0), (1), (2), (0,1), (0,2), (1,2), and (0,1,2).

Note:

1 <= G <= 100
0 <= P <= 100
1 <= group[i] <= 100
0 <= profit[i] <= 100
1 <= group.length = profit.length <= 100

Solution: DP

Time complexity: O(KPG)

Space complexity: O(KPG)

C++

// Author: Huahua

// Running time: 64 ms

class Solution {

public:

int profitableSchemes(int G, int P, vector<int>& group, vector<int>& profit) {

const int kMod = 1000000007;

const int K = group.size();

// dp[k][i][j]:= # of schemes of making profit i with j people by commiting first k crimes.

vector<vector<vector<int>>> dp(K + 1, vector<vector<int>>(P + 1, vector<int>(G + 1, 0)));

dp[0][0][0] = 1;

for (int k = 1; k <= K; ++k) {

const int p = profit[k - 1];

const int g = group[k - 1];

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

for (int j = 0; j <= G; ++j)

dp[k][i][j] = (dp[k - 1][i][j] + (j < g ? 0 : dp[k - 1][max(0, i - p)][j - g])) % kMod;

}

return accumulate(begin(dp[K][P]), end(dp[K][P]), 0LL) % kMod;

}

};

Space complexity: O(PG)

v1: Dimension reduction by copying.

// Author: Huahua

// Running time: 24 ms

class Solution {

public:

int profitableSchemes(int G, int P, vector<int>& group, vector<int>& profit) {

const int kMod = 1000000007;

const int K = group.size();

// dp[i][j]:= # of schemes of making profit i with j people.

vector<vector<int>> dp(P + 1, vector<int>(G + 1, 0));

dp[0][0] = 1;

for (int k = 1; k <= K; ++k) {

auto tmp = dp;

const int p = profit[k - 1];

const int g = group[k - 1];

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

for (int j = 0; j <= G; ++j)

tmp[i][j] = (tmp[i][j] + (j < g ? 0 : dp[max(0, i - p)][j - g])) % kMod;

dp.swap(tmp);

}

return accumulate(begin(dp[P]), end(dp[P]), 0LL) % kMod;

}

};

v2: Dimension reduction by using rolling array.

// Author: Huahua

// Running time: 16 ms

class Solution {

public:

int profitableSchemes(int G, int P, vector<int>& group, vector<int>& profit) {

const int kMod = 1000000007;

// dp[i][j]:= # of schemes of making profit i with j people.

vector<vector<int>> dp(P + 1, vector<int>(G + 1, 0));

dp[0][0] = 1;

const int K = group.size();

for (int k = 0; k < K; ++k) {

const int p = profit[k];

const int g = group[k];

for (int i = P; i >= 0; --i) {

const int ip = min(P, i + p);

for (int j = G - g; j >= 0; --j)

dp[ip][j + g] = (dp[ip][j + g] + dp[i][j]) % kMod;

}

return accumulate(begin(dp[P]), end(dp[P]), 0LL) % kMod;

}

};

花花酱 LeetCode 878. Nth Magical Number

By zxi on July 28, 2018

Problem

A positive integer is magical if it is divisible by either A or B.

Return the N-th magical number. Since the answer may be very large, return it modulo 10^9 + 7.

Example 1:

Input: N = 1, A = 2, B = 3
Output: 2

Example 2:

Input: N = 4, A = 2, B = 3
Output: 6

Example 3:

Input: N = 5, A = 2, B = 4
Output: 10

Example 4:

Input: N = 3, A = 6, B = 4
Output: 8

Note:

1 <= N <= 10^9
2 <= A <= 40000
2 <= B <= 40000

Solution: Math + Binary Search

Let n denote the number of numbers <= X that are divisible by either A or B.

n = X / A + X / B – X / lcm(A, B) = X / A + X / B – X / (A * B / gcd(A, B))

Binary search for the smallest X such that n >= N

Time complexity: O(log(1e9*4e5)

Space complexity: O(1)

// Author: Huahua

// Running time: 0 ms

class Solution {

public:

int nthMagicalNumber(int N, int A, int B) {

const int kMod = 1000000007;

long l = 2;

long r = static_cast<long>(1e9 * 4e5);

int d = gcd(A, B);

while (l < r) {

long m = (r - l) / 2 + l;

if (m / A + m / B - m / (A * B / d) < N)

l = m + 1;

else

r = m;

}

return l % kMod;

}

private:

int gcd(int a, int b) {

if (a % b == 0) return b;

return gcd(b, a % b);

}

};