【leetcode】801. Minimum Swaps To Make Sequences Increasing
题目如下:
We have two integer sequences
AandBof the same non-zero length.We are allowed to swap elements
A[i]andB[i]. Note that both elements are in the same index position in their respective sequences.At the end of some number of swaps,
AandBare both strictly increasing. (A sequence is strictly increasing if and only ifA[0] < A[1] < A[2] < ... < A[A.length - 1].)Given A and B, return the minimum number of swaps to make both sequences strictly increasing. It is guaranteed that the given input always makes it possible.
Example: Input: A = [1,3,5,4], B = [1,2,3,7] Output: 1 Explanation: Swap A[3] and B[3]. Then the sequences are: A = [1, 3, 5, 7] and B = [1, 2, 3, 4] which are both strictly increasing.Note:
A, Bare arrays with the same length, and that length will be in the range[1, 1000].A[i], B[i]are integer values in the range[0, 2000].
解题思路:每个下标对应的元素只有交换和不交换两种选择,记dp[i][0]为在[0~i]这个区间内,在第i个元素不交换时使得[0~i]区间子数组严格递增时总的交换次数,而dp[i][0]为在[0~i]这个区间内,在第i个元素交换时使得[0~i]区间子数组严格递增时总的交换次数。要使得数组严格递增,第i个元素是否需要交换取决于与(i-1)元素的值的大小情况,总得来说分为可能性如下,
1. A[i] > A[i - 1] and B[i] > B[i - 1] and A[i] > B[i - 1] and B[i] > A[i - 1] ,这种情况下,第i个元素可以交换或者不交换,并且和i-1是否交换没有任何关系,那么可以得出: 在第i个元素不交换的情况下,dp[i][0] 应该等于第i-1个元素交换与不交换两种情况下的较小值,有 dp[i][0] = min(dp[i][0], dp[i - 1][0], dp[i - 1][1]) ,如果第i个元素非要任性的交换,那么结果就是第i-1个元素交换与不交换两种情况下的较小值加上1,有dp[i][1] = min(dp[i][1], dp[i - 1][0] + 1, dp[i - 1][1] + 1) 。
2. A[i] > A[i - 1] and B[i] > B[i - 1] ,这种情况是i和i-1之间要么都交换,要么都不交换。有 dp[i][0] = min(dp[i][0], dp[i - 1][0]) ,dp[i][1] = min(dp[i][1], dp[i - 1][1] + 1)
3. A[i] > B[i - 1] and B[i] > A[i - 1] and (A[i] <= A[i - 1] or B[i] <= B[i - 1]),这种情况是要么i交换,要么i-1交换。有 dp[i][1] = min(dp[i][1], dp[i - 1][0] + 1),dp[i][0] = min(dp[i][0], dp[i - 1][1])
4.其他情况则表示无论i交换或者不交换都无法保证严格递增。
代码如下:
class Solution(object): def minSwap(self, A, B): """ :type A: List[int] :type B: List[int] :rtype: int """ dp = [[float('inf')] * 2 for _ in A] dp[0][0] = 0 dp[0][1] = 1 for i in range(1, len(A)): if (A[i] > A[i - 1] and B[i] > B[i - 1]) and (A[i] > B[i - 1] and B[i] > A[i - 1]): dp[i][0] = min(dp[i][0], dp[i - 1][0], dp[i - 1][1]) dp[i][1] = min(dp[i][1], dp[i - 1][0] + 1, dp[i - 1][1] + 1) elif A[i] > A[i - 1] and B[i] > B[i - 1]: dp[i][0] = min(dp[i][0], dp[i - 1][0]) dp[i][1] = min(dp[i][1], dp[i - 1][1] + 1) elif A[i] > B[i - 1] and B[i] > A[i - 1] and (A[i] <= A[i - 1] or B[i] <= B[i - 1]): dp[i][1] = min(dp[i][1], dp[i - 1][0] + 1) dp[i][0] = min(dp[i][0], dp[i - 1][1]) #print dp return min(dp[-1]) if min(dp[-1]) != float('inf') else -1
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