{ "data": { "question": { "questionId": "3941", "questionFrontendId": "3624", "categoryTitle": "Algorithms", "boundTopicId": 3727791, "title": "Number of Integers With Popcount-Depth Equal to K II", "titleSlug": "number-of-integers-with-popcount-depth-equal-to-k-ii", "content": "
You are given an integer array nums.
For any positive integer x, define the following sequence:
p0 = xpi+1 = popcount(pi) for all i >= 0, where popcount(y) is the number of set bits (1's) in the binary representation of y.This sequence will eventually reach the value 1.
\n\nThe popcount-depth of x is defined as the smallest integer d >= 0 such that pd = 1.
For example, if x = 7 (binary representation "111"). Then, the sequence is: 7 → 3 → 2 → 1, so the popcount-depth of 7 is 3.
You are also given a 2D integer array queries, where each queries[i] is either:
[1, l, r, k] - Determine the number of indices j such that l <= j <= r and the popcount-depth of nums[j] is equal to k.[2, idx, val] - Update nums[idx] to val.Return an integer array answer, where answer[i] is the number of indices for the ith query of type [1, l, r, k].
\n
Example 1:
\n\nInput: nums = [2,4], queries = [[1,0,1,1],[2,1,1],[1,0,1,0]]
\n\nOutput: [2,1]
\n\nExplanation:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\tValid \n\t\t\t nums[j] | \n\t\t\tupdated \n\t\t\t nums | \n\t\t\tAnswer | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,1,1] | \n\t\t\t[2,4] | \n\t\t\t[10, 100] | \n\t\t\t[1, 1] | \n\t\t\t[0, 1] | \n\t\t\t1 | \n\t\t\t[0, 1] | \n\t\t\t— | \n\t\t\t2 | \n\t\t
| 1 | \n\t\t\t[2,1,1] | \n\t\t\t[2,4] | \n\t\t\t[10, 100] | \n\t\t\t[1, 1] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[2,1] | \n\t\t\t— | \n\t\t
| 2 | \n\t\t\t[1,0,1,0] | \n\t\t\t[2,1] | \n\t\t\t[10, 1] | \n\t\t\t[1, 0] | \n\t\t\t[0, 1] | \n\t\t\t0 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
Thus, the final answer is [2, 1].
Example 2:
\n\nInput: nums = [3,5,6], queries = [[1,0,2,2],[2,1,4],[1,1,2,1],[1,0,1,0]]
\n\nOutput: [3,1,0]
\n\nExplanation:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\tValid \n\t\t\t nums[j] | \n\t\t\tupdated \n\t\t\t nums | \n\t\t\tAnswer | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,2,2] | \n\t\t\t[3, 5, 6] | \n\t\t\t[11, 101, 110] | \n\t\t\t[2, 2, 2] | \n\t\t\t[0, 2] | \n\t\t\t2 | \n\t\t\t[0, 1, 2] | \n\t\t\t— | \n\t\t\t3 | \n\t\t
| 1 | \n\t\t\t[2,1,4] | \n\t\t\t[3, 5, 6] | \n\t\t\t[11, 101, 110] | \n\t\t\t[2, 2, 2] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[3, 4, 6] | \n\t\t\t— | \n\t\t
| 2 | \n\t\t\t[1,1,2,1] | \n\t\t\t[3, 4, 6] | \n\t\t\t[11, 100, 110] | \n\t\t\t[2, 1, 2] | \n\t\t\t[1, 2] | \n\t\t\t1 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
| 3 | \n\t\t\t[1,0,1,0] | \n\t\t\t[3, 4, 6] | \n\t\t\t[11, 100, 110] | \n\t\t\t[2, 1, 2] | \n\t\t\t[0, 1] | \n\t\t\t0 | \n\t\t\t[] | \n\t\t\t— | \n\t\t\t0 | \n\t\t
Thus, the final answer is [3, 1, 0].
Example 3:
\n\nInput: nums = [1,2], queries = [[1,0,1,1],[2,0,3],[1,0,0,1],[1,0,0,2]]
\n\nOutput: [1,0,1]
\n\nExplanation:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\tValid \n\t\t\t nums[j] | \n\t\t\tupdated \n\t\t\t nums | \n\t\t\tAnswer | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,1,1] | \n\t\t\t[1, 2] | \n\t\t\t[1, 10] | \n\t\t\t[0, 1] | \n\t\t\t[0, 1] | \n\t\t\t1 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
| 1 | \n\t\t\t[2,0,3] | \n\t\t\t[1, 2] | \n\t\t\t[1, 10] | \n\t\t\t[0, 1] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[3, 2] | \n\t\t\t\n\t\t |
| 2 | \n\t\t\t[1,0,0,1] | \n\t\t\t[3, 2] | \n\t\t\t[11, 10] | \n\t\t\t[2, 1] | \n\t\t\t[0, 0] | \n\t\t\t1 | \n\t\t\t[] | \n\t\t\t— | \n\t\t\t0 | \n\t\t
| 3 | \n\t\t\t[1,0,0,2] | \n\t\t\t[3, 2] | \n\t\t\t[11, 10] | \n\t\t\t[2, 1] | \n\t\t\t[0, 0] | \n\t\t\t2 | \n\t\t\t[0] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
Thus, the final answer is [1, 0, 1].
\n
Constraints:
\n\n1 <= n == nums.length <= 1051 <= nums[i] <= 10151 <= queries.length <= 105queries[i].length == 3 or 4\n\tqueries[i] == [1, l, r, k] or,queries[i] == [2, idx, val]0 <= l <= r <= n - 10 <= k <= 50 <= idx <= n - 11 <= val <= 1015给你一个整数数组 nums。
对于任意正整数 x,定义以下序列:
p0 = xpi+1 = popcount(pi),对于所有 i >= 0,其中 popcount(y) 表示整数 y 的二进制表示中 1 的个数。这个序列最终会收敛到值 1。
\n\npopcount-depth(位计数深度)定义为满足 pd = 1 的最小整数 d >= 0。
例如,当 x = 7(二进制表示为 \"111\")时,该序列为:7 → 3 → 2 → 1,因此 7 的 popcount-depth 为 3。
此外,给定一个二维整数数组 queries,其中每个 queries[i] 可以是以下两种类型之一:
[1, l, r, k] - 计算在区间 [l, r] 中,满足 nums[j] 的 popcount-depth 等于 k 的索引 j 的数量。[2, idx, val] - 将 nums[idx] 更新为 val。返回一个整数数组 answer,其中 answer[i] 表示第 i 个类型为 [1, l, r, k] 的查询的结果。
\n\n
示例 1:
\n\n输入: nums = [2,4], queries = [[1,0,1,1],[2,1,1],[1,0,1,0]]
\n\n输出: [2,1]
\n\n解释:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\t有效 \n\t\t\t nums[j] | \n\t\t\t更新后的 \n\t\t\t nums | \n\t\t\t答案 | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,1,1] | \n\t\t\t[2,4] | \n\t\t\t[10, 100] | \n\t\t\t[1, 1] | \n\t\t\t[0, 1] | \n\t\t\t1 | \n\t\t\t[0, 1] | \n\t\t\t— | \n\t\t\t2 | \n\t\t
| 1 | \n\t\t\t[2,1,1] | \n\t\t\t[2,4] | \n\t\t\t[10, 100] | \n\t\t\t[1, 1] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[2,1] | \n\t\t\t— | \n\t\t
| 2 | \n\t\t\t[1,0,1,0] | \n\t\t\t[2,1] | \n\t\t\t[10, 1] | \n\t\t\t[1, 0] | \n\t\t\t[0, 1] | \n\t\t\t0 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
因此,最终 answer 为 [2, 1]。
示例 2:
\n\n输入:nums = [3,5,6], queries = [[1,0,2,2],[2,1,4],[1,1,2,1],[1,0,1,0]]
\n\n输出:[3,1,0]
\n\n解释:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\t有效 \n\t\t\t nums[j] | \n\t\t\t更新后的 \n\t\t\t nums | \n\t\t\t答案 | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,2,2] | \n\t\t\t[3, 5, 6] | \n\t\t\t[11, 101, 110] | \n\t\t\t[2, 2, 2] | \n\t\t\t[0, 2] | \n\t\t\t2 | \n\t\t\t[0, 1, 2] | \n\t\t\t— | \n\t\t\t3 | \n\t\t
| 1 | \n\t\t\t[2,1,4] | \n\t\t\t[3, 5, 6] | \n\t\t\t[11, 101, 110] | \n\t\t\t[2, 2, 2] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[3, 4, 6] | \n\t\t\t— | \n\t\t
| 2 | \n\t\t\t[1,1,2,1] | \n\t\t\t[3, 4, 6] | \n\t\t\t[11, 100, 110] | \n\t\t\t[2, 1, 2] | \n\t\t\t[1, 2] | \n\t\t\t1 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
| 3 | \n\t\t\t[1,0,1,0] | \n\t\t\t[3, 4, 6] | \n\t\t\t[11, 100, 110] | \n\t\t\t[2, 1, 2] | \n\t\t\t[0, 1] | \n\t\t\t0 | \n\t\t\t[] | \n\t\t\t— | \n\t\t\t0 | \n\t\t
因此,最终 answer 为 [3, 1, 0] 。
示例 3:
\n\n输入:nums = [1,2], queries = [[1,0,1,1],[2,0,3],[1,0,0,1],[1,0,0,2]]
\n\n输出:[1,0,1]
\n\n解释:
\n\ni | \n\t\t\tqueries[i] | \n\t\t\tnums | \n\t\t\tbinary(nums) | \n\t\t\tpopcount- \n\t\t\tdepth | \n\t\t\t[l, r] | \n\t\t\tk | \n\t\t\t有效 \n\t\t\t nums[j] | \n\t\t\t更新后的 \n\t\t\t nums | \n\t\t\t答案 | \n\t\t
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n\t\t\t[1,0,1,1] | \n\t\t\t[1, 2] | \n\t\t\t[1, 10] | \n\t\t\t[0, 1] | \n\t\t\t[0, 1] | \n\t\t\t1 | \n\t\t\t[1] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
| 1 | \n\t\t\t[2,0,3] | \n\t\t\t[1, 2] | \n\t\t\t[1, 10] | \n\t\t\t[0, 1] | \n\t\t\t— | \n\t\t\t— | \n\t\t\t— | \n\t\t\t[3, 2] | \n\t\t\t\n\t\t |
| 2 | \n\t\t\t[1,0,0,1] | \n\t\t\t[3, 2] | \n\t\t\t[11, 10] | \n\t\t\t[2, 1] | \n\t\t\t[0, 0] | \n\t\t\t1 | \n\t\t\t[] | \n\t\t\t— | \n\t\t\t0 | \n\t\t
| 3 | \n\t\t\t[1,0,0,2] | \n\t\t\t[3, 2] | \n\t\t\t[11, 10] | \n\t\t\t[2, 1] | \n\t\t\t[0, 0] | \n\t\t\t2 | \n\t\t\t[0] | \n\t\t\t— | \n\t\t\t1 | \n\t\t
因此,最终 answer 为 [1, 0, 1] 。
\n\n
提示:
\n\n1 <= n == nums.length <= 1051 <= nums[i] <= 10151 <= queries.length <= 105queries[i].length == 3 或 4\n\tqueries[i] == [1, l, r, k] 或queries[i] == [2, idx, val]0 <= l <= r <= n - 10 <= k <= 50 <= idx <= n - 11 <= val <= 1015depth[i] for each nums[i] by applying popcount until you reach 1.",
"Maintain six Fenwick trees fenw[0] through fenw[5], where fenw[d] stores a 1 at index i iff depth[i] == d.",
"For an update [2, idx, val], remove index idx from its old fenw[old_depth] and insert into fenw[new_depth]; for a query [1, l, r, k], return fenw[k].query(r) - fenw[k].query(l-1)."
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