[英]python itertools permutations with tied values
I want to find efficiently permutations of a vector which has tied values. 我想找到一个有绑定值的向量的有效排列。
Eg, if perm_vector = [0,0,1,2]
I would want to obtain as output all combinations of [0,0,1,2], [0,0,2,1], [0,1,2,0]
and so on, but I don't want to obtain [0,0,1,2]
twice which is what the standard itertools.permutations(perm_vector)
would give. 例如,如果
perm_vector = [0,0,1,2]
我想获得[0,0,1,2], [0,0,2,1], [0,1,2,0]
所有组合作为输出[0,0,1,2], [0,0,2,1], [0,1,2,0]
等等,但我不想获得[0,0,1,2]
两次,这是标准的itertools.permutations(perm_vector)
所给出的。
I tried the following but it works really SLOW when perm_vector grows
in len: 我试过以下但是当
perm_vector grows
在len中perm_vector grows
时它确实很慢:
vectors_list = []
for it in itertools.permutations(perm_vector):
vectors_list.append(list(it))
df_vectors_list = pd.DataFrame( vectors_list)
df_gb = df_vectors_list.groupby(list(df_vectors_list.columns))
vectors_list = pd.DataFrame(df_gb.groups.keys()).T
The question is of more general "speed-up" nature, actually. 实际上,问题是更加普遍的“加速”性质。 The main time is spent on creating the permutations of long vectors - even without the duplicity, creation of permutations of a vector of 12 unique values takes a "infinity".
主要时间用于创建长向量的排列 - 即使没有两面性,创建12个唯一值的向量的排列也需要“无穷大”。 Is there a possibility to call the itertools iteratively without accessing the entire permutations data but working on bunches of it?
是否有可能迭代地调用itertools而不访问整个排列数据但是处理它的串?
Try this if perm_vector is small: 如果perm_vector很小,请尝试这样做:
import itertools as iter
{x for x in iter.permutations(perm_vector)}
This should give you unique values, because now it becomes a set, which by default delete duplications. 这应该为您提供唯一值,因为它现在变成一个集合,默认情况下删除重复。
If perm_vector is large, you might want to try backtracking: 如果perm_vector很大,您可能想尝试回溯:
def permu(L, left, right, cache):
for i in range(left, right):
L[left], L[i] = L[i], L[left]
L_tuple = tuple(L)
if L_tuple not in cache:
permu(L, left + 1, right, cache)
L[left], L[i] = L[i], L[left]
cache[L_tuple] = 0
cache = {}
permu(perm_vector, 0, len(perm_vector), cache)
cache.keys()
How about this: 这个怎么样:
from collections import Counter
def starter(l):
cnt = Counter(l)
res = [None] * len(l)
return worker(cnt, res, len(l) - 1)
def worker(cnt, res, n):
if n < 0:
yield tuple(res)
else:
for k in cnt.keys():
if cnt[k] != 0:
cnt[k] = cnt[k] - 1
res[n] = k
for r in worker(cnt, res, n - 1):
yield r
cnt[k] = cnt[k] + 1
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