900. RLE Iterator RLE 迭代器
作者: 负雪明烛 id: fuxuemingzhu 个人博客: https://fuxuemingzhu.cn/
题目地址:https://leetcode.com/problems/rle-iterator/description/
Write an iterator that iterates through a run-length encoded sequence.
The iterator is initialized by RLEIterator(int[] A), where A is a run-length encoding of some sequence. More specifically, for all even i, A[i] tells us the number of times that the non-negative integer value A[i+1] is repeated in the sequence.
The iterator supports one function: next(int n), which exhausts the next n elements (n >= 1) and returns the last element exhausted in this way. If there is no element left to exhaust, next returns -1 instead.
For example, we start with A = [3,8,0,9,2,5], which is a run-length encoding of the sequence [8,8,8,5,5]. This is because the sequence can be read as “three eights, zero nines, two fives”.
Example 1:
Input: ["RLEIterator","next","next","next","next"], [[[3,8,0,9,2,5]],[2],[1],[1],[2]]Output: [null,8,8,5,-1]
Explanation:
RLEIterator is initialized with RLEIterator([3,8,0,9,2,5]).This maps to the sequence [8,8,8,5,5].RLEIterator.next is then called 4 times:
.next(2) exhausts 2 terms of the sequence, returning 8. The remaining sequence is now [8, 5, 5].
.next(1) exhausts 1 term of the sequence, returning 8. The remaining sequence is now [5, 5].
.next(1) exhausts 1 term of the sequence, returning 5. The remaining sequence is now [5].
.next(2) exhausts 2 terms, returning -1. This is because the first term exhausted was 5,but the second term did not exist. Since the last term exhausted does not exist, we return -1.Note:
- 0 <= A.length <= 1000 A.length is an even integer. 0 <= A[i] <= 10^9 There are at most 1000 calls to RLEIterator.next(int n) per test case. Each call to RLEIterator.next(int n) will have 1 <= n <= 10^9.
给出了一个数组,这个数组第偶数个位置表示的是其后面的那个数字出现的次数。让我们设计一个函数,能找出后面的第n个数字,如果后面没有数字就返回-1.这个运算的过程中要把偶数位置出现的次数给统计进去。
这个设计确实类似于python的next()函数,估计next()是这个题的原型吧。
看了下A的规模是1000,那么对时间复杂度的要求并没有那么严格。其实这个题可以直接使用O(N)的时间复杂度求解。
使用index指向我们现在统计到的数组A的位置,这个位置只指向偶数位置。然后每次next()调用同时维护数组A和index。直接遍历就好,如果A[index]的个数>n,就往后去找,直至找到对应的位置,这个时候的位置就代表我们的找到了要弹出的数字。遍历的过程中一定要更新n,也要更新每个位置出现次数。这样就相当于n把原来位置的数字给消耗掉了。
平均时间复杂度是O(n),空间复杂度是O(1)。
代码如下:
class RLEIterator(object):
def __init__(self, A): """ :type A: List[int] """ self.A = A self.index = 0
def next(self, n): """ :type n: int :rtype: int """ while self.index < len(self.A) and self.A[self.index] < n: n -= self.A[self.index] self.index += 2 if self.index >= len(self.A): return -1 self.A[self.index] -= n return self.A[self.index + 1]
# Your RLEIterator object will be instantiated and called as such:# obj = RLEIterator(A)# param_1 = obj.next(n)二刷的时候使用C++,思路和上面大致相同。如果当前位置的数字大于等于剩余的n,那么把当前数字-n;如果当前位置的数字小于n,那么必须向后寻找了,需要更新n并且向后走,每次走两步。
如果上面的循环结束的时候,pos已经走到了数组外边,直接返回-1,否则返回pos位置对应的下一个位置。
C++代码如下:
class RLEIterator {public: RLEIterator(vector<int> A) : A_(A), pos(0){ }
int next(int n) { while (pos < A_.size() && n > 0) { if (A_[pos] >= n) { A_[pos] -= n; n = 0; } else { n -= A_[pos]; A_[pos] = 0; pos += 2; } } if (pos >= A_.size() - 1) return -1; return A_[pos + 1]; }private: vector<int> A_; int pos;};
/** * Your RLEIterator object will be instantiated and called as such: * RLEIterator obj = new RLEIterator(A); * int param_1 = obj.next(n); */参考资料:
2018 年 9 月 18 日 —— 铭记这一天 2019 年 2 月 26 日 —— 二月就要完了

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