[NeetCode 150] Longest Increasing Subsequence

Longest Increasing Subsequence

Given an integer array nums, return the length of the longest strictly increasing subsequence.

A subsequence is a sequence that can be derived from the given sequence by deleting some or no elements without changing the relative order of the remaining characters.

For example, “cat” is a subsequence of “crabt”.

Example 1:

Input: nums = [9,1,4,2,3,3,7]

Output: 4

Explanation: The longest increasing subsequence is [1,2,3,7], which has a length of 4.

Example 2:

Input: nums = [0,3,1,3,2,3]

Output: 4

Constraints:

1 <= nums.length <= 1000
-1000 <= nums[i] <= 1000

Solution

Let dp[i]dp[i]dp[i] denotes the minimum last number of increasing subsequence of length iii. Obviously, dpdpdp will be an ascending array. To maintain dpdpdp, we need to find the index of last number that less than current number lll, and add current number at the end to update dp[l+1]dp[l+1]dp[l+1].

Because dpdpdp is an ascending array, we can apply binary search to accelerate the search, which makes the whole solution O(nlog⁡n)O(n\log n)O(nlogn) time complexity.

Code

class Solution:
    def bs(self, nums, target, ri):
        le = 0
        pos = 0
        while le <= ri:
            mid = (le+ri)//2
            if nums[mid] < target:
                pos = mid
                le = mid+1
            else:
                ri = mid-1
        return pos

    def lengthOfLIS(self, nums: List[int]) -> int:
        dp = [1001]*(len(nums)+1)
        dp[0] = -1001
        ans = 0
        for num in nums:
            pos = self.bs(dp, num, ans)
            dp[pos+1] = min(dp[pos+1], num)
            ans = max(ans, pos+1)
        return ans
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