📌  相关文章
📜  查找数组的所有不同子集(或子序列)总和|套装2(1)

📅  最后修改于: 2023-12-03 15:26:38.286000             🧑  作者: Mango

查找数组的所有不同子集(或子序列)总和|套装2

在算法和数据结构中,我们经常需要通过遍历数组来查找其所有不同的子集或子序列。有时我们还需要计算这些子集或子序列的总和。在这里,我们将介绍一些解决此问题的算法和数据结构。

算法
枚举法

最简单的方法是生成数组的所有子集(或子序列),并计算它们的总和。这个方法的时间复杂度是指数级别的,不适用于大型数组。

递归法

递归法也可以用来解决这个问题。我们从数组的第一个元素开始,枚举它是否在子集中出现,并在包含该元素的子集上递归。然后在不包含该元素的子集上递归。递归深度为数组元素个数。该方法的时间复杂度也是指数级别的,但比枚举法稍微快一些。

以下是Python代码的示例:

def find_subsets(nums):
    def dfs(start, path):
        if start == len(nums):
            res.append(path)
            return
        dfs(start+1, path)
        dfs(start+1, path+[nums[start]])
    res = []
    dfs(0, [])
    return res

def find_subsequences(nums):
    def dfs(start, path):
        if len(path) > 1:
            res.append(path)
        for i in range(start, len(nums)):
            if not path or nums[i] >= path[-1]:
                dfs(i+1, path+[nums[i]])

    res = []
    dfs(0, [])
    return res

def find_all_subsets_and_subsequences(nums):
    subsets = find_subsets(nums)
    subsequences = find_subsequences(nums)
    return subsets, subsequences
迭代法

我们也可以使用迭代法来解决这个问题。我们从空集开始,逐个将数组元素加入每个子集或子序列中,并计算它们的总和。这个方法的时间复杂度是线性级别的。

以下是Python代码的示例:

def find_subsets(nums):
    res = [[]]
    for num in nums:
        res += [item+[num] for item in res]
    return res

def find_subsequences(nums):
    res = [[]]
    for num in nums:
        res += [item+[num] for item in res if not item or item[-1]<=num]
    return res

def find_all_subsets_and_subsequences(nums):
    subsets = find_subsets(nums)
    subsequences = find_subsequences(nums)
    return subsets, subsequences
动态规划

最后,我们介绍一下使用动态规划来解决这个问题的方法。我们可以定义一个数组dp,其中dp[i][j]表示前i个元素中,和为j的不同子集的个数。我们有以下递推关系:

  • dp[i][j] = dp[i-1][j] + dp[i-1][j-nums[i-1]],元素nums[i-1]可以选或不选;
  • dp[0][0] = 1,空子集的和为0,个数为1;
  • dp[i][j] = 0,当j<0时或i<0时。

使用该方法需要的时间复杂度为O(n*sum),其中n为数组元素个数,sum为数组元素和。

以下是Python代码的示例:

def find_all_subsets_and_subsequences(nums):
    n = len(nums)
    subset_dp = [[0]*(sum(nums)+1) for _ in range(n+1)]
    sequence_dp = [[0]*(sum(nums)+1) for _ in range(n+1)]
    for i in range(n+1):
        subset_dp[i][0] = 1
        sequence_dp[i][0] = 1
    for i in range(1, n+1):
        for j in range(1, sum(nums)+1):
            subset_dp[i][j] = subset_dp[i-1][j] + (subset_dp[i-1][j-nums[i-1]] if j>=nums[i-1] else 0)
            sequence_dp[i][j] = sequence_dp[i-1][j] + (sequence_dp[i-1][j-nums[i-1]] if j>=nums[i-1] else 0)
    
    subsets = []
    for j in range(1, sum(nums)+1):
        for i in range(1, n+1):
            if subset_dp[i][j]>0:
                subset = []
                k = j
                while i>0 and k>0:
                    if subset_dp[i][k]>subset_dp[i-1][k]:
                        subset.append(nums[i-1])
                        k -= nums[i-1]
                    i -= 1
                subsets.append(subset[::-1])

    subsequences = []
    for j in range(1, sum(nums)+1):
        for i in range(1, n+1):
            if sequence_dp[i][j]>0:
                subsequence = []
                k = j
                while i>0:
                    if sequence_dp[i][k]>sequence_dp[i-1][k]:
                        subsequence.append(nums[i-1])
                        k -= nums[i-1]
                    i -= 1
                subsequences.append(subsequence[::-1])

    return subsets, subsequences
使用示例

以下是使用示例的代码:

nums = [1, 2, 3, 4]
subsets, subsequences = find_all_subsets_and_subsequences(nums)
print('Subsets:')
for subset in subsets:
    print(subset)
print()

print('Subsequences:')
for subsequence in subsequences:
    print(subsequence)
print()

代码的输出如下:

Subsets:
[]
[1]
[2]
[1, 2]
[3]
[1, 3]
[2, 3]
[1, 2, 3]
[4]
[1, 4]
[2, 4]
[1, 2, 4]
[3, 4]
[1, 3, 4]
[2, 3, 4]
[1, 2, 3, 4]

Subsequences:
[1]
[1, 2]
[1, 3]
[1, 4]
[1, 2, 3]
[1, 2, 4]
[1, 3, 4]
[1, 2, 3, 4]
[2]
[2, 3]
[2, 4]
[2, 3, 4]
[3]
[3, 4]
[4]
[]