MAP must be a m x 3 array.

This error message usually occurs when you try to pass an array with an incorrect number of dimensions or an incorrect shape to a function or method that expects a specific shape or dimensionality of an input array.

In this case, the error message suggests that you are trying to pass a variable named "MAP" to a function that expects an array with three columns (i.e., three dimensions) and an unspecified number of rows (i.e., m). Double-check the shape of your input array and make sure it matches the expected shape. Also, make sure that the data type of the array elements is compatible with the function you are using.

相关问题

"TypeError: Invalid attempt to spread non-iterable instance. In order to be iterable, non-array objects must have a [Symbol.iterator]() method."

这个错误通常发生在你尝试将一个非可迭代对象展开（spread）的时候。JavaScript 中的可迭代对象包括数组和一些内置对象（例如字符串、Map、Set 等），它们都有一个 [Symbol.iterator]() 方法来定义它们的迭代行为。

如果你尝试展开一个不可迭代的对象，就会出现这个错误。解决方法是确保你的对象是可迭代的，或者使用其他方法来处理它。可以检查一下你在哪里使用了展开操作符（...），然后确认该对象是否是可迭代的。

You are given an array containing � n positive integers. Your task is to divide the array into � k subarrays so that the maximum sum in a subarray is as small as possible. Input The first input line contains two integers � n and � k: the size of the array and the number of subarrays in the division. The next line contains � n integers � 1 , � 2 , … , � � x 1 ​ ,x 2 ​ ,…,x n ​ : the contents of the array. Output Print one integer: the maximum sum in a subarray in the optimal division. Constraints 1 ≤ � ≤ 2 ⋅ 1 0 5 1≤n≤2⋅10 5 1 ≤ � ≤ � 1≤k≤n 1 ≤ � � ≤ 1 0 9 1≤x i ​ ≤10 9 Explanation: An optimal division is [ 2 , 4 ] , [ 7 ] , [ 3 , 5 ] [2,4],[7],[3,5] where the sums of the subarrays are 6 , 7 , 8 6,7,8. The largest sum is the last sum 8 8.

This problem can be solved using binary search. We can try to find the minimum possible maximum sum in a subarray by binary searching over the range of possible values. The upper bound of this range is the sum of all elements in the array, since each subarray must have at least one element. The lower bound of this range is the maximum element in the array, since each subarray must have at least one element and the maximum element must be in its own subarray.

For each guess of the maximum sum, we can try to divide the array into subarrays such that no subarray has a sum greater than the guess. This can be done by iterating through the array and greedily assigning each element to the current subarray until the sum of the subarray is greater than the guess. Then, we start a new subarray with the current element.

If we can divide the array into k subarrays with a maximum sum no greater than our guess, we can try a smaller guess. If we cannot divide the array into k subarrays with a maximum sum no greater than our guess, we need to try a larger guess.

Here's some sample code in Python:

n, k = map(int, input().split())
arr = list(map(int, input().split()))

low = max(arr)
high = sum(arr)

while low < high:
    mid = (low + high) // 2
    count = 1
    total = 0
    for x in arr:
        if total + x > mid:
            count += 1
            total = x
        else:
            total += x

    if count > k:
        low = mid + 1
    else:
        high = mid

print(low)

This code reads in the input and initializes the range of possible values for the maximum sum in a subarray. Then, it performs binary search to find the minimum possible maximum sum. For each guess of the maximum sum, it tries to divide the array into k subarrays such that no subarray has a sum greater than the guess. If it can do this, it tries a smaller guess. If not, it tries a larger guess. Finally, it prints out the minimum possible maximum sum.