(Python) 查找受分区大小限制限制的列表列表的所有可能分区
(Python) Finding all possible partitions of a list of lists subject to a size limit for a partition
假设我有一个列表 k = [[1,1,1],[2,2],[3],[4]]
,大小限制为 c = 4
。
然后我想找到 k
主题 ot c
所有可能的分区。理想情况下,结果应该是:
[ {[[1,1,1],[3]], [[2,2], [4]]}, {[[1,1,1],[4]], [[2,2], [3]]}, {[[1,1,1]], [[2,2], [3], [4]]}, ..., {[[1,1,1]], [[2,2]], [[3]], [[4]]} ]
我在上面的示例中使用了集合符号 { }
(实际情况是 [ ]
),以便更清楚地了解什么是分区,其中每个分区包含组合在一起的列表组。
我实现了以下算法,但我的结果不符合:
def num_item(l):
flat_l = [item for sublist in l for item in sublist]
return len(flat_l)
def get_all_possible_partitions(lst, c):
p_opt = []
for l in lst:
p_temp = [l]
lst_copy = lst.copy()
lst_copy.remove(l)
iterations = 0
while num_item(p_temp) <= c and iterations <= len(lst_copy):
for l_ in lst_copy:
iterations += 1
if num_item(p_temp + [l_]) <= c:
p_temp += [l_]
p_opt += [p_temp]
return p_opt
运行get_all_possible_partitions(k, 4)
,我得到:
[[[1, 1, 1], [3]], [[2, 2], [3], [4]], [[3], [1, 1, 1]], [[4], [1, 1, 1]]]
我知道它不会删除重复项并耗尽可能的组合,我一直坚持下去。
有些见解会很棒! P.S。我没能找到类似的问题:/
如果列表中的所有元素都是唯一的,那么你可以使用位。
设k = [a,b,c],长度为3,则有2^3 - 1 = 7个分区:
如果用bit来组合a,b,c,就会有
001 -> [c]
010 -> [b]
011 -> [b, c]
100 -> [a]
101 -> [a,c]
110 -> [a,b]
111 -> [a,b,c]
所以,现在解决这个问题的关键是显而易见的。
我想这就是你想要的(评论中的解释):
# Main function
def get_all_possible_partitions(lst, c):
yield from _get_all_possible_partitions_rec(lst, c, [False] * len(lst), [])
# Produces partitions recursively
def _get_all_possible_partitions_rec(lst, c, picked, partition):
# If all elements have been picked it is a complete partition
if all(picked):
yield tuple(partition)
else:
# Get all possible subsets of unpicked elements
for subset in _get_all_possible_subsets_rec(lst, c, picked, [], 0):
# Add the subset to the partition
partition.append(subset)
# Generate all partitions that complete the current one
yield from _get_all_possible_partitions_rec(lst, c, picked, partition)
# Remove the subset from the partition
partition.pop()
# Produces all possible subsets of unpicked elements
def _get_all_possible_subsets_rec(lst, c, picked, current, idx):
# If we have gone over all elements finish
if idx >= len(lst): return
# If the current element is available and fits in the subset
if not picked[idx] and len(lst[idx]) <= c:
# Mark it as picked
picked[idx] = True
# Add it to the subset
current.append(lst[idx])
# Generate the subset
yield tuple(current)
# Generate all possible subsets extending this one
yield from _get_all_possible_subsets_rec(lst, c - len(lst[idx]), picked, current, idx + 1)
# Remove current element
current.pop()
# Unmark as picked
picked[idx] = False
# Only allow skip if it is not the first available element
if len(current) > 0 or picked[idx]:
# Get all subsets resulting from skipping current element
yield from _get_all_possible_subsets_rec(lst, c, picked, current, idx + 1)
# Test
k = [[1, 1, 1], [2, 2], [3], [4]]
c = 4
partitions = list(get_all_possible_partitions(k, c))
print(*partitions, sep='\n')
输出:
(([1, 1, 1],), ([2, 2],), ([3],), ([4],))
(([1, 1, 1],), ([2, 2],), ([3], [4]))
(([1, 1, 1],), ([2, 2], [3]), ([4],))
(([1, 1, 1],), ([2, 2], [3], [4]))
(([1, 1, 1],), ([2, 2], [4]), ([3],))
(([1, 1, 1], [3]), ([2, 2],), ([4],))
(([1, 1, 1], [3]), ([2, 2], [4]))
(([1, 1, 1], [4]), ([2, 2],), ([3],))
(([1, 1, 1], [4]), ([2, 2], [3]))
注意:这个答案实际上是针对closed linked question.
如果你只想 return 列表的二分,你可以使用 more_iterools.set_partions:
>>> from more_itertools import set_partitions
>>>
>>> def get_bipartions(lst):
... half_list_len = len(lst) // 2
... if len(lst) % 2 == 0:
... return list(
... map(tuple, [
... p
... for p in set_partitions(lst, k=2)
... if half_list_len == len(p[0])
... ]))
... else:
... return list(
... map(tuple, [
... p
... for p in set_partitions(lst, k=2)
... if abs(half_list_len - len(p[0])) < 1
... ]))
...
>>> get_bipartions(['A', 'B', 'C'])
[(['A'], ['B', 'C']), (['B'], ['A', 'C'])]
>>> get_bipartions(['A', 'B', 'C', 'D'])
[(['A', 'B'], ['C', 'D']), (['B', 'C'], ['A', 'D']), (['A', 'C'], ['B', 'D'])]
>>> get_bipartions(['A', 'B', 'C', 'D', 'E'])
[(['A', 'B'], ['C', 'D', 'E']), (['B', 'C'], ['A', 'D', 'E']), (['A', 'C'], ['B', 'D', 'E']), (['C', 'D'], ['A', 'B', 'E']), (['B', 'D'], ['A', 'C', 'E']), (['A', 'D'], ['B', 'C', 'E'])]
假设我有一个列表 k = [[1,1,1],[2,2],[3],[4]]
,大小限制为 c = 4
。
然后我想找到 k
主题 ot c
所有可能的分区。理想情况下,结果应该是:
[ {[[1,1,1],[3]], [[2,2], [4]]}, {[[1,1,1],[4]], [[2,2], [3]]}, {[[1,1,1]], [[2,2], [3], [4]]}, ..., {[[1,1,1]], [[2,2]], [[3]], [[4]]} ]
我在上面的示例中使用了集合符号 { }
(实际情况是 [ ]
),以便更清楚地了解什么是分区,其中每个分区包含组合在一起的列表组。
我实现了以下算法,但我的结果不符合:
def num_item(l):
flat_l = [item for sublist in l for item in sublist]
return len(flat_l)
def get_all_possible_partitions(lst, c):
p_opt = []
for l in lst:
p_temp = [l]
lst_copy = lst.copy()
lst_copy.remove(l)
iterations = 0
while num_item(p_temp) <= c and iterations <= len(lst_copy):
for l_ in lst_copy:
iterations += 1
if num_item(p_temp + [l_]) <= c:
p_temp += [l_]
p_opt += [p_temp]
return p_opt
运行get_all_possible_partitions(k, 4)
,我得到:
[[[1, 1, 1], [3]], [[2, 2], [3], [4]], [[3], [1, 1, 1]], [[4], [1, 1, 1]]]
我知道它不会删除重复项并耗尽可能的组合,我一直坚持下去。
有些见解会很棒! P.S。我没能找到类似的问题:/
如果列表中的所有元素都是唯一的,那么你可以使用位。
设k = [a,b,c],长度为3,则有2^3 - 1 = 7个分区:
如果用bit来组合a,b,c,就会有
001 -> [c]
010 -> [b]
011 -> [b, c]
100 -> [a]
101 -> [a,c]
110 -> [a,b]
111 -> [a,b,c]
所以,现在解决这个问题的关键是显而易见的。
我想这就是你想要的(评论中的解释):
# Main function
def get_all_possible_partitions(lst, c):
yield from _get_all_possible_partitions_rec(lst, c, [False] * len(lst), [])
# Produces partitions recursively
def _get_all_possible_partitions_rec(lst, c, picked, partition):
# If all elements have been picked it is a complete partition
if all(picked):
yield tuple(partition)
else:
# Get all possible subsets of unpicked elements
for subset in _get_all_possible_subsets_rec(lst, c, picked, [], 0):
# Add the subset to the partition
partition.append(subset)
# Generate all partitions that complete the current one
yield from _get_all_possible_partitions_rec(lst, c, picked, partition)
# Remove the subset from the partition
partition.pop()
# Produces all possible subsets of unpicked elements
def _get_all_possible_subsets_rec(lst, c, picked, current, idx):
# If we have gone over all elements finish
if idx >= len(lst): return
# If the current element is available and fits in the subset
if not picked[idx] and len(lst[idx]) <= c:
# Mark it as picked
picked[idx] = True
# Add it to the subset
current.append(lst[idx])
# Generate the subset
yield tuple(current)
# Generate all possible subsets extending this one
yield from _get_all_possible_subsets_rec(lst, c - len(lst[idx]), picked, current, idx + 1)
# Remove current element
current.pop()
# Unmark as picked
picked[idx] = False
# Only allow skip if it is not the first available element
if len(current) > 0 or picked[idx]:
# Get all subsets resulting from skipping current element
yield from _get_all_possible_subsets_rec(lst, c, picked, current, idx + 1)
# Test
k = [[1, 1, 1], [2, 2], [3], [4]]
c = 4
partitions = list(get_all_possible_partitions(k, c))
print(*partitions, sep='\n')
输出:
(([1, 1, 1],), ([2, 2],), ([3],), ([4],))
(([1, 1, 1],), ([2, 2],), ([3], [4]))
(([1, 1, 1],), ([2, 2], [3]), ([4],))
(([1, 1, 1],), ([2, 2], [3], [4]))
(([1, 1, 1],), ([2, 2], [4]), ([3],))
(([1, 1, 1], [3]), ([2, 2],), ([4],))
(([1, 1, 1], [3]), ([2, 2], [4]))
(([1, 1, 1], [4]), ([2, 2],), ([3],))
(([1, 1, 1], [4]), ([2, 2], [3]))
注意:这个答案实际上是针对closed linked question.
如果你只想 return 列表的二分,你可以使用 more_iterools.set_partions:
>>> from more_itertools import set_partitions
>>>
>>> def get_bipartions(lst):
... half_list_len = len(lst) // 2
... if len(lst) % 2 == 0:
... return list(
... map(tuple, [
... p
... for p in set_partitions(lst, k=2)
... if half_list_len == len(p[0])
... ]))
... else:
... return list(
... map(tuple, [
... p
... for p in set_partitions(lst, k=2)
... if abs(half_list_len - len(p[0])) < 1
... ]))
...
>>> get_bipartions(['A', 'B', 'C'])
[(['A'], ['B', 'C']), (['B'], ['A', 'C'])]
>>> get_bipartions(['A', 'B', 'C', 'D'])
[(['A', 'B'], ['C', 'D']), (['B', 'C'], ['A', 'D']), (['A', 'C'], ['B', 'D'])]
>>> get_bipartions(['A', 'B', 'C', 'D', 'E'])
[(['A', 'B'], ['C', 'D', 'E']), (['B', 'C'], ['A', 'D', 'E']), (['A', 'C'], ['B', 'D', 'E']), (['C', 'D'], ['A', 'B', 'E']), (['B', 'D'], ['A', 'C', 'E']), (['A', 'D'], ['B', 'C', 'E'])]