Posts tagged as “prefix sum”

花花酱 LeetCode 1513. Number of Substrings With Only 1s

By zxi on July 29, 2020

Given a binary string s (a string consisting only of ‘0’ and ‘1’s).

Return the number of substrings with all characters 1’s.

Since the answer may be too large, return it modulo 10^9 + 7.

Example 1:

Input: s = "0110111"
Output: 9
Explanation: There are 9 substring in total with only 1's characters.
"1" -> 5 times.
"11" -> 3 times.
"111" -> 1 time.

Example 2:

Input: s = "101"
Output: 2
Explanation: Substring "1" is shown 2 times in s.

Example 3:

Input: s = "111111"
Output: 21
Explanation: Each substring contains only 1's characters.

Example 4:

Input: s = "000"
Output: 0

Constraints:

s[i] == '0' or s[i] == '1'
1 <= s.length <= 10^5

Solution: DP / Prefix Sum

dp[i] := # of all 1 subarrays end with s[i].
dp[i] = dp[i-1] if s[i] == ‘1‘ else 0
ans = sum(dp)
s=1101
dp[0] = 1 // 1
dp[1] = 2 // 11, *1
dp[2] = 0 // None
dp[3] = 1 // ***1
ans = 1 + 2 + 1 = 5

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

C++

class Solution {

public:

int numSub(string s) {

constexpr int kMod = 1e9 + 7;

long ans = 0;

vector<int> dp(s.length() + 1);

for (int i = 1; i <= s.length(); ++i) {

dp[i] = s[i - 1] == '1' ? dp[i - 1] + 1 : 0;

ans += dp[i];

}

return ans % kMod;

}

};

dp[i] only depends on dp[i-1], we can reduce the space complexity to O(1)

C++

class Solution {

public:

int numSub(string s) {

constexpr int kMod = 1e9 + 7;

long ans = 0;

int cur = 0;

for (char c : s) {

cur = c == '1' ? cur + 1 : 0;

ans += cur;

}

return ans % kMod;

}

};

Java

class Solution {

public int numSub(String s) {

final int kMod = 1_000_000_000 + 7;

int ans = 0;

int cur = 0;

for (int i = 0; i < s.length(); ++i) {

cur = s.charAt(i) == '1' ? cur + 1 : 0;

ans = (ans + cur) % kMod;

}

return ans;

}

Python3

class Solution:

def numSub(self, s: str) -> int:

kMod = 10**9 + 7

ans = 0

cur = 0

for c in s:

cur = cur + 1 if c == '1' else 0

ans += cur

return ans % kMod

花花酱 LeetCode 1524. Number of Sub-arrays With Odd Sum

By zxi on July 25, 2020

Given an array of integers arr. Return the number of sub-arrays with odd sum.

As the answer may grow large, the answer must be computed modulo 10^9 + 7.

Example 1:

Input: arr = [1,3,5]
Output: 4
Explanation: All sub-arrays are [[1],[1,3],[1,3,5],[3],[3,5],[5]]
All sub-arrays sum are [1,4,9,3,8,5].
Odd sums are [1,9,3,5] so the answer is 4.

Example 2:

Input: arr = [2,4,6]
Output: 0
Explanation: All sub-arrays are [[2],[2,4],[2,4,6],[4],[4,6],[6]]
All sub-arrays sum are [2,6,12,4,10,6].
All sub-arrays have even sum and the answer is 0.

Example 3:

Input: arr = [1,2,3,4,5,6,7]
Output: 16

Example 4:

Input: arr = [100,100,99,99]
Output: 4

Example 5:

Input: arr = [7]
Output: 1

Constraints:

1 <= arr.length <= 10^5
1 <= arr[i] <= 100

Solution: DP

We would like to know how many subarrays end with arr[i] have odd or even sums.

dp[i][0] := # end with arr[i] has even sum
dp[i][1] := # end with arr[i] has even sum

if arr[i] is even:

dp[i][0]=dp[i-1][0] + 1, dp[i][1]=dp[i-1][1]

else:

dp[i][1]=dp[i-1][0], dp[i][0]=dp[i-1][0] + 1

ans = sum(dp[i][1])

Time complexity: O(n)
Space complexity: O(n) -> O(1)

C++

class Solution {

public:

int numOfSubarrays(vector<int>& arr) {

const int n = arr.size();

constexpr int kMod = 1e9 + 7;

// dp[i][0] # of subarrays ends with a[i-1] have even sums.

// dp[i][1] # of subarrays ends with a[i-1] have odd sums.

vector<vector<int>> dp(n + 1, vector<int>(2));

long ans = 0;

for (int i = 1; i <= n; ++i) {

if (arr[i - 1] & 1) {

dp[i][0] = dp[i - 1][1];

dp[i][1] = dp[i - 1][0] + 1;

} else {

dp[i][0] = dp[i - 1][0] + 1;

dp[i][1] = dp[i - 1][1];

}

ans += dp[i][1];

}

return ans % kMod;

}

};

Java

// Author: Huahua

class Solution {

public int numOfSubarrays(int[] arr) {

long ans = 0, odd = 0, even = 0;

for (int x : arr) {

even += 1;

if (x % 2 == 1) {

long t = even; even = odd; odd = t;

}

ans += odd;

}

return (int)(ans % (int)(1e9 + 7));

}

Python3

# Author: Huahua

class Solution:

def numOfSubarrays(self, arr: List[int]) -> int:

ans, odd, even = 0, 0, 0

for x in arr:

if x & 1:

odd, even = even + 1, odd

else:

odd, even = odd, even + 1

ans += odd

return ans % int(1e9 + 7)

花花酱 LeetCode 1508. Range Sum of Sorted Subarray Sums

By zxi on July 11, 2020

Given the array nums consisting of n positive integers. You computed the sum of all non-empty continous subarrays from the array and then sort them in non-decreasing order, creating a new array of n * (n + 1) / 2 numbers.

Return the sum of the numbers from index left to index right (indexed from 1), inclusive, in the new array. Since the answer can be a huge number return it modulo 10^9 + 7.

Example 1:

Input: nums = [1,2,3,4], n = 4, left = 1, right = 5
Output: 13 
Explanation: All subarray sums are 1, 3, 6, 10, 2, 5, 9, 3, 7, 4. After sorting them in non-decreasing order we have the new array [1, 2, 3, 3, 4, 5, 6, 7, 9, 10]. The sum of the numbers from index le = 1 to ri = 5 is 1 + 2 + 3 + 3 + 4 = 13.

Example 2:

Input: nums = [1,2,3,4], n = 4, left = 3, right = 4
Output: 6
Explanation: The given array is the same as example 1. We have the new array [1, 2, 3, 3, 4, 5, 6, 7, 9, 10]. The sum of the numbers from index le = 3 to ri = 4 is 3 + 3 = 6.

Example 3:

Input: nums = [1,2,3,4], n = 4, left = 1, right = 10
Output: 50

Constraints:

1 <= nums.length <= 10^3
nums.length == n
1 <= nums[i] <= 100
1 <= left <= right <= n * (n + 1) / 2

Solution 1: Brute Force

Find sums of all the subarrays and sort the values.

Time complexity: O(n^2logn)
Space complexity: O(n^2)

C++

// Author: Huahua

class Solution {

public:

int rangeSum(vector<int>& nums, int n, int left, int right) {

constexpr int kMod = 1e9 + 7;

vector<int> sums;

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

for (int j = i, sum = 0; j < n; ++j)

sums.push_back(sum += nums[j]);

sort(begin(sums), end(sums));

return accumulate(begin(sums) + left - 1, begin(sums) + right, 0LL) % kMod;

}

};

Java

// Author: Huahua

class Solution {

public int rangeSum(int[] nums, int n, int left, int right) {

final int kMod = (int)(1e9 + 7);

int[] sums = new int[n * (n + 1) / 2];

int idx = 0;

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

for (int j = i, sum = 0; j < n; ++j, ++idx)

sums[idx] = sum += nums[j];

Arrays.sort(sums);

int ans = 0;

for (int i = left; i <= right; ++i)

ans = (ans + sums[i - 1]) % kMod;

return ans;

}

Python3

# Author: Huahua

class Solution:

def rangeSum(self, nums: List[int], n: int, left: int, right: int) -> int:

sums = []

for i in range(n):

s = 0

for j in range(i, n):

s += nums[j]

sums.append(s)

sums.sort()

return sum(sums[left - 1:right])

Solution 2: Priority Queue / Min Heap

For each subarray, start with one element e.g nums[i], put them into a priority queue (min heap). Each time, we have the smallest subarray sum, and extend that subarray and put the new sum back into priority queue. Thought it has the same time complexity as the brute force one in worst case, but space complexity can be reduce to O(n).

Time complexity: O(n^2logn)
Space complexity: O(n)

C++

struct Entry {

int sum;

int i;

bool operator<(const Entry& e) const { return sum > e.sum; }

};

class Solution {

public:

int rangeSum(vector<int>& nums, int n, int left, int right) {

constexpr int kMod = 1e9 + 7;

priority_queue<Entry> q; // Sort by e.sum in descending order.

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

q.push({nums[i], i});

long ans = 0;

for (int j = 1; j <= right; ++j) {

const auto e = std::move(q.top()); q.pop();

if (j >= left) ans += e.sum;

if (e.i + 1 < n) q.push({e.sum + nums[e.i + 1], e.i + 1});

}

return ans % kMod;

}

};

Java

import java.util.AbstractMap;

class Solution {

public int rangeSum(int[] nums, int n, int left, int right) {

final int kMod = (int)(1e9 + 7);

var q = new PriorityQueue<Map.Entry<Integer, Integer>>((a, b) -> a.getKey() - b.getKey());

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

q.offer(new AbstractMap.SimpleEntry<>(nums[i], i));

int ans = 0;

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

var e = q.poll();

int sum = e.getKey();

int i = e.getValue();

if (k >= left)

ans = (ans + sum) % kMod;

if (i + 1 < n)

q.offer(new AbstractMap.SimpleEntry<>(sum + nums[i + 1], i + 1));

}

return ans;

}

Python3

# Author: Huahua

class Solution:

def rangeSum(self, nums: List[int], n: int, left: int, right: int) -> int:

q = [(num, i) for i, num in enumerate(nums)]

heapq.heapify(q)

ans = 0

for k in range(1, right + 1):

s, i = heapq.heappop(q)

if k >= left:

ans += s

if i + 1 < n:

heapq.heappush(q, (s + nums[i + 1], i + 1))

return ans % int(1e9 + 7)

Solution 3: Binary Search + Sliding Window

Use binary search to find S s.t. that there are at least k subarrys have sum <= S.

Given S, we can use sliding window to count how many subarrays have sum <= S and their total sum.

ans = sums_of_first(right) – sums_of_first(left – 1).

Time complexity: O(n * log(sum(nums))
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

int rangeSum(vector<int>& nums, int n, int left, int right) {

constexpr int kMod = 1e9 + 7;

// Returns number of subarrays that have

// sum <= target and their total sum.

auto countAndSum = [&](int target) -> pair<int, long> {

int count = 0;

long cur = 0;

long sum = 0;

long total_sum = 0;

for (long j = 0, i = 0; j < n; ++j) {

cur += nums[j];

sum += nums[j] * (j - i + 1);

while (cur > target) {

sum -= cur;

cur -= nums[i++];

}

count += j - i + 1;

total_sum += sum;

}

return {count, total_sum};

};

// Returns the total sums of smallest k subarrays.

// Use binary search to find the smallest sum l s.t.

// there are at least k of subarrays have sums <= l.

const int min_sum = *min_element(begin(nums), end(nums));

const int max_sum = accumulate(begin(nums), end(nums), 0) + 1;

auto sumOfFirstK = [&](int k) -> long {

int l = min_sum;

int r = max_sum;

while (l < r) {

int mid = l + (r - l) / 2;

if (countAndSum(mid).first >= k)

r = mid;

else

l = mid + 1;

}

const auto [count, sum] = countAndSum(l);

// There can be more subarrays have the same sum of l.

return sum - l * (count - k);

};

return (sumOfFirstK(right) - sumOfFirstK(left - 1)) % kMod;

}

};

花花酱 LeetCode 1480. Running Sum of 1d Array

By zxi on June 14, 2020

Given an array nums. We define a running sum of an array as runningSum[i] = sum(nums[0]…nums[i]).

Return the running sum of nums.

Example 1:

Input: nums = [1,2,3,4]
Output: [1,3,6,10]
Explanation: Running sum is obtained as follows: [1, 1+2, 1+2+3, 1+2+3+4].

Example 2:

Input: nums = [1,1,1,1,1]
Output: [1,2,3,4,5]
Explanation: Running sum is obtained as follows: [1, 1+1, 1+1+1, 1+1+1+1, 1+1+1+1+1].

Example 3:

Input: nums = [3,1,2,10,1]
Output: [3,4,6,16,17]

Constraints:

1 <= nums.length <= 1000
-10^6 <= nums[i] <= 10^6

Solution

Time complexity: O(n)
Space complexity: O(1)

C++

// Author: Huahua

class Solution {

public:

vector<int> runningSum(vector<int>& nums) {

vector<int> ans(nums);

for (int i = 1; i < ans.size(); ++i)

ans[i] += ans[i - 1];

return ans;

}

};

花花酱 LeetCode 1413. Minimum Value to Get Positive Step by Step Sum

By zxi on April 18, 2020

Given an array of integers nums, you start with an initial positive value startValue.

In each iteration, you calculate the step by step sum of startValue plus elements in nums (from left to right).

Return the minimum positive value of startValue such that the step by step sum is never less than 1.

Example 1:

Input: nums = [-3,2,-3,4,2]
Output: 5
Explanation: If you choose startValue = 4, in the third iteration your step by step sum is less than 1.
                step by step sum
                startValue = 4 | startValue = 5 | nums
                  (4 -3 ) = 1  | (5 -3 ) = 2    |  -3
                  (1 +2 ) = 3  | (2 +2 ) = 4    |   2
                  (3 -3 ) = 0  | (4 -3 ) = 1    |  -3
                  (0 +4 ) = 4  | (1 +4 ) = 5    |   4
                  (4 +2 ) = 6  | (5 +2 ) = 7    |   2

Example 2:

Input: nums = [1,2]
Output: 1
Explanation: Minimum start value should be positive.

Example 3:

Input: nums = [1,-2,-3]
Output: 5

Constraints:

1 <= nums.length <= 100
-100 <= nums[i] <= 100

Solution: Prefix sum

Find the minimum prefix sum, ans = – min(prefix_sum, 0) + 1

Time complexity: O(n)
Space complexity: O(1)

C++

// Author: Huahua

class Solution {

public:

int minStartValue(vector<int>& nums) {

int min_sum = 0;

int sum = 0;

for (int num : nums) {

sum += num;

min_sum = min(min_sum, sum);

}

return -min_sum + 1;

}

};