📅  最后修改于: 2023-12-03 15:39:16.288000             🧑  作者: Mango
这个问题可以通过哈希表和动态规划来解决。
我们可以使用一个哈希表来计算字符串中每个字符出现的次数。然后,我们可以按照字符出现的次数进行排序,并将其分成k个组。最后,我们可以计算未分组的字符数并返回其值。
def get_count_of_unassigned_characters(string: str, group_count: int) -> int:
if group_count == 1:
return 0
freq = {}
for c in string:
if c in freq:
freq[c] += 1
else:
freq[c] = 1
freq_list = list(freq.items())
freq_list.sort(key=lambda x: x[1], reverse=True)
group_size = len(string) // group_count
groups = [freq_list[i * group_size:(i + 1) * group_size] for i in range(group_count)]
unassigned_characters = 0
for i in range(group_count):
group_freq = {}
for c, f in groups[i]:
if f in group_freq:
group_freq[f].append(c)
else:
group_freq[f] = [c]
unassigned_characters += len(groups[i]) - len(group_freq)
return unassigned_characters
我们可以使用动态规划来解决这个问题。我们可以定义一个二维数组dp,其中dp[i][j]表示将字符串前i个字符分成j个不同字符组的最小未分组字符数。
我们可以使用以下公式计算dp[i][j]:
dp[i][j] = min(dp[k][j-1] + unassigned_characters(k+1, i))
其中,unassigned_characters(k+1, i)表示将字符串的第k+1个字符到第i个字符分成一个组的未分组字符数。
def get_count_of_unassigned_characters(string: str, group_count: int) -> int:
if group_count == 1:
return 0
n = len(string)
dp = [[float('inf')] * (group_count + 1) for _ in range(n + 1)]
dp[0][0] = 0
for i in range(1, n + 1):
for j in range(1, group_count + 1):
for k in range(j - 1, i):
unassigned = get_unassigned_characters(string, k + 1, i)
dp[i][j] = min(dp[i][j], dp[k][j - 1] + unassigned)
return dp[n][group_count]
def get_unassigned_characters(string: str, start: int, end: int) -> int:
freq = {}
for i in range(start, end):
if string[i] in freq:
freq[string[i]] += 1
else:
freq[string[i]] = 1
assigned = sum([1 for f in freq.values() if f > 0])
unassigned = end - start - assigned
return unassigned
这样,我们就解决了这个问题,时间复杂度为𝑂(𝑁^2𝐾)。