comments | difficulty | edit_url | rating | source | tags | ||||||
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true |
Hard |
2735 |
Weekly Contest 393 Q4 |
|
You are given two arrays nums
and andValues
of length n
and m
respectively.
The value of an array is equal to the last element of that array.
You have to divide nums
into m
disjoint contiguous subarrays such that for the ith
subarray [li, ri]
, the bitwise AND
of the subarray elements is equal to andValues[i]
, in other words, nums[li] & nums[li + 1] & ... & nums[ri] == andValues[i]
for all 1 <= i <= m
, where &
represents the bitwise AND
operator.
Return the minimum possible sum of the values of the m
subarrays nums
is divided into. If it is not possible to divide nums
into m
subarrays satisfying these conditions, return -1
.
Example 1:
Input: nums = [1,4,3,3,2], andValues = [0,3,3,2]
Output: 12
Explanation:
The only possible way to divide nums
is:
[1,4]
as1 & 4 == 0
.[3]
as the bitwiseAND
of a single element subarray is that element itself.[3]
as the bitwiseAND
of a single element subarray is that element itself.[2]
as the bitwiseAND
of a single element subarray is that element itself.
The sum of the values for these subarrays is 4 + 3 + 3 + 2 = 12
.
Example 2:
Input: nums = [2,3,5,7,7,7,5], andValues = [0,7,5]
Output: 17
Explanation:
There are three ways to divide nums
:
[[2,3,5],[7,7,7],[5]]
with the sum of the values5 + 7 + 5 == 17
.[[2,3,5,7],[7,7],[5]]
with the sum of the values7 + 7 + 5 == 19
.[[2,3,5,7,7],[7],[5]]
with the sum of the values7 + 7 + 5 == 19
.
The minimum possible sum of the values is 17
.
Example 3:
Input: nums = [1,2,3,4], andValues = [2]
Output: -1
Explanation:
The bitwise AND
of the entire array nums
is 0
. As there is no possible way to divide nums
into a single subarray to have the bitwise AND
of elements 2
, return -1
.
Constraints:
1 <= n == nums.length <= 104
1 <= m == andValues.length <= min(n, 10)
1 <= nums[i] < 105
0 <= andValues[j] < 105
We design a function
The execution process of the function
- If
$n - i < m - j$ , it means that the remaining elements are not enough to divide into$m - j$ subarrays, return$+\infty$ . - If
$j = m$ , it means that$m$ subarrays have been divided. At this time, check whether$i = n$ holds. If it holds, return$0$ , otherwise return$+\infty$ . - Otherwise, we perform a bitwise AND operation on
$a$ and$nums[i]$ to get a new$a$ . If$a < andValues[j]$ , it means that the bitwise AND result of the current subarray to be divided does not meet the requirements, return$+\infty$ . Otherwise, we have two choices:- Do not divide the current element, i.e.,
$dfs(i + 1, j, a)$ . - Divide the current element, i.e.,
$dfs(i + 1, j + 1, -1) + nums[i]$ .
- Do not divide the current element, i.e.,
- Return the minimum of the above two choices.
To avoid repeated calculations, we use the method of memoization search and store the result of
The time complexity is
class Solution:
def minimumValueSum(self, nums: List[int], andValues: List[int]) -> int:
@cache
def dfs(i: int, j: int, a: int) -> int:
if n - i < m - j:
return inf
if j == m:
return 0 if i == n else inf
a &= nums[i]
if a < andValues[j]:
return inf
ans = dfs(i + 1, j, a)
if a == andValues[j]:
ans = min(ans, dfs(i + 1, j + 1, -1) + nums[i])
return ans
n, m = len(nums), len(andValues)
ans = dfs(0, 0, -1)
return ans if ans < inf else -1
class Solution {
private int[] nums;
private int[] andValues;
private final int inf = 1 << 29;
private Map<Long, Integer> f = new HashMap<>();
public int minimumValueSum(int[] nums, int[] andValues) {
this.nums = nums;
this.andValues = andValues;
int ans = dfs(0, 0, -1);
return ans >= inf ? -1 : ans;
}
private int dfs(int i, int j, int a) {
if (nums.length - i < andValues.length - j) {
return inf;
}
if (j == andValues.length) {
return i == nums.length ? 0 : inf;
}
a &= nums[i];
if (a < andValues[j]) {
return inf;
}
long key = (long) i << 36 | (long) j << 32 | a;
if (f.containsKey(key)) {
return f.get(key);
}
int ans = dfs(i + 1, j, a);
if (a == andValues[j]) {
ans = Math.min(ans, dfs(i + 1, j + 1, -1) + nums[i]);
}
f.put(key, ans);
return ans;
}
}
class Solution {
public:
int minimumValueSum(vector<int>& nums, vector<int>& andValues) {
this->nums = nums;
this->andValues = andValues;
n = nums.size();
m = andValues.size();
int ans = dfs(0, 0, -1);
return ans >= inf ? -1 : ans;
}
private:
vector<int> nums;
vector<int> andValues;
int n;
int m;
const int inf = 1 << 29;
unordered_map<long long, int> f;
int dfs(int i, int j, int a) {
if (n - i < m - j) {
return inf;
}
if (j == m) {
return i == n ? 0 : inf;
}
a &= nums[i];
if (a < andValues[j]) {
return inf;
}
long long key = (long long) i << 36 | (long long) j << 32 | a;
if (f.contains(key)) {
return f[key];
}
int ans = dfs(i + 1, j, a);
if (a == andValues[j]) {
ans = min(ans, dfs(i + 1, j + 1, -1) + nums[i]);
}
return f[key] = ans;
}
};
func minimumValueSum(nums []int, andValues []int) int {
n, m := len(nums), len(andValues)
f := map[int]int{}
const inf int = 1 << 29
var dfs func(i, j, a int) int
dfs = func(i, j, a int) int {
if n-i < m-j {
return inf
}
if j == m {
if i == n {
return 0
}
return inf
}
a &= nums[i]
if a < andValues[j] {
return inf
}
key := i<<36 | j<<32 | a
if v, ok := f[key]; ok {
return v
}
ans := dfs(i+1, j, a)
if a == andValues[j] {
ans = min(ans, dfs(i+1, j+1, -1)+nums[i])
}
f[key] = ans
return ans
}
if ans := dfs(0, 0, -1); ans < inf {
return ans
}
return -1
}
function minimumValueSum(nums: number[], andValues: number[]): number {
const [n, m] = [nums.length, andValues.length];
const f: Map<bigint, number> = new Map();
const dfs = (i: number, j: number, a: number): number => {
if (n - i < m - j) {
return Infinity;
}
if (j === m) {
return i === n ? 0 : Infinity;
}
a &= nums[i];
if (a < andValues[j]) {
return Infinity;
}
const key = (BigInt(i) << 36n) | (BigInt(j) << 32n) | BigInt(a);
if (f.has(key)) {
return f.get(key)!;
}
let ans = dfs(i + 1, j, a);
if (a === andValues[j]) {
ans = Math.min(ans, dfs(i + 1, j + 1, -1) + nums[i]);
}
f.set(key, ans);
return ans;
};
const ans = dfs(0, 0, -1);
return ans >= Infinity ? -1 : ans;
}