【LeetCode】566. Reshape the Matrix 解题报告（Python）-CFANZ编程社区

id： fuxuemingzhu

个人博客： http://fuxuemingzhu.cn/

题目描述

In MATLAB, there is a very useful function called ‘reshape’, which can reshape a matrix into a new one with different size but keep its original data.

You’re given a matrix represented by a two-dimensional array, and two positive integers r and c representing the row number and column number of the wanted reshaped matrix, respectively.

The reshaped matrix need to be filled with all the elements of the original matrix in the same row-traversing order as they were.

If the ‘reshape’ operation with given parameters is possible and legal, output the new reshaped matrix; Otherwise, output the original matrix.

Example 1:

Input: 
nums = 
[[1,2],
 [3,4]]
r = 1, c = 4
Output: 
[[1,2,3,4]]
Explanation:
The row-traversing of nums is [1,2,3,4]. The new reshaped matrix is a 1 * 4 matrix, fill it row by row by using the previous list.

Example 2:

Input: 
nums = 
[[1,2],
 [3,4]]
r = 2, c = 4
Output: 
[[1,2],
 [3,4]]
Explanation:
There is no way to reshape a 2 * 2 matrix to a 2 * 4 matrix. So output the original matrix.

Note:

The height and width of the given matrix is in range [1, 100].
The given r and c are all positive.

题目大意

实现Matlab的reshape函数，就是把原来的数组逐行遍历重新改成r行，c列，如果不能实现的话就是返回原来的数组。

解题方法

变长数组

Python的list是可变的，那么一个简单的想法就是使用可变的List作为新的一行，如果新的一行的元素个数等于题目要求的列数，那么就新建一行。把每行的结果放到返回的列表中即可。

时间复杂度是O(mn)，空间复杂度是O(1).没有额外空间

class Solution(object):
    def matrixReshape(self, nums, r, c):
        """
        :type nums: List[List[int]]
        :type r: int
        :type c: int
        :rtype: List[List[int]]
        """
        M, N = len(nums), len(nums[0])
        if M * N != r * c:
            return nums
        res = []
        row = []
        for i in range(M):
            for j in range(N):
                row.append(nums[i][j])
                if len(row) == c:
                    res.append(row)
                    row = []
        return res

求余法

这个做法是由位图法激发出来的，使用一个变量count保存现在已经有了的元素数量，那么直接可以使用res[count / c][count % c]确定轮到了的元素的位置。这个方法需要把数组提前构造好。

时间复杂度是O(mn)，空间复杂度是O(1).没有额外空间

class Solution(object):
    def matrixReshape(self, nums, r, c):
        """
        :type nums: List[List[int]]
        :type r: int
        :type c: int
        :rtype: List[List[int]]
        """
        M, N = len(nums), len(nums[0])
        if M * N != r * c:
            return nums
        res = [[0] * c for _ in range(r)]
        count = 0
        for i in range(M):
            for j in range(N):
                res[count / c][count % c] = nums[i][j]
                count +=1
        return res

维护行列

上面的方法每次需要通过除法和求余来确定新的位置，事实上是比较耗时的。更快的方法就是维护行和列的变量，在遍历的过程中更新行和列，这样就可以对应放入的位置了。

时间复杂度是O(mn)，空间复杂度是O(1).没有额外空间

class Solution(object):
    def matrixReshape(self, nums, r, c):
        """
        :type nums: List[List[int]]
        :type r: int
        :type c: int
        :rtype: List[List[int]]
        """
        M, N = len(nums), len(nums[0])
        if M * N != r * c:
            return nums
        res = [[0] * c for _ in range(r)]
        row, col = 0, 0
        for i in range(M):
            for j in range(N):
                if col == c:
                    row += 1
                    col = 0
                res[row][col] = nums[i][j]
                col += 1
        return res