I do have a piece of code that compute partitions of a set of (potentialy duplicated) integers. But i am interested in the set of possible partition and there multiplicity.
You can for exemple launch the follwoing code :
import numpy as np
from collections import Counter
import pandas as pd
def _B(i):
# for a given multiindex i, we defined _B(i) as the set of integers containg i_j times the number j:
if len(i) != 1:
B = []
for j in range(len(i)):
B.extend(i[j]*[j])
else:
B = i*[0]
return B
def _partition(collection):
# from here: https://stackoverflow.com/a/62532969/8425270
if len(collection) == 1:
yield (collection,)
return
first = collection[0]
for smaller in _partition(collection[1:]):
# insert `first` in each of the subpartition's subsets
for n, subset in enumerate(smaller):
yield smaller[:n] + ((first,) + subset,) + smaller[n + 1 :]
# put `first` in its own subset
yield ((first,),) + smaller
def to_list(tpl):
# the final hierarchy is
return list(list(i) if isinstance(i, tuple) else i for i in tpl)
def _Pi(inst_B):
# inst_B must be a tuple
if type(inst_B) != tuple :
inst_B = tuple(inst_B)
pp = [tuple(sorted(p)) for p in _partition(inst_B)]
c = Counter(pp)
Pi = c.keys()
N = list()
for pi in Pi:
N.append(c[pi])
Pi = [to_list(pi) for pi in Pi]
return Pi, N
if __name__ == "__main__":
import cProfile
pr = cProfile.Profile()
pr.enable()
sh = (3, 3, 3)
rez = list()
rez_sorted= list()
rez_ref = list()
for idx in np.ndindex(sh):
if sum(idx) > 0:
print(idx)
Pi, N = _Pi(_B(idx))
print(pd.DataFrame({'Pi': Pi, 'N': N * np.array([np.math.factorial(len(pi) - 1) for pi in Pi])}))
pr.disable()
# after your program ends
pr.print_stats(sort="tottime")
This code computes, for several examples of tuples of integer numbers (generated by np.ndindex
) the partitions and counts i need. Everything happens in the _partition
and the _Pi
functions, this is were you should look at.
If you look closely at how these two functions are working, you'll see that they comput eevery potential partition and THEN count up how many times they appeared. For small problems, this is fine, but if the size of the prolbme increase, this starts to take a looooot of time. Try setting sh = (5,5,5)
, you'll see what i mean;
So the problem is the following :
Is there a way to compute directly the partitions and there number of occurences instead ?
Edit: I cross-posted on mathoverflow there, and they propose a solution in this article, in corrolary 2.10 (page 10 of the pdf). The problem could be solved by implmenting the sets p(v,r) in this corrolary.
I was hoping, as in the univariate case, that those sets would have a nice recursive expression but i ould not find one yet.
More Edit : This problem is equivalent to finding all (multiset)-partitions of a multiset. If the solution for finding (set)-partitions of a set is given by Bell partial polynomials, here we need multivariate version of these polynomials.