I\'m trying to find or develop Integer Partitioning code for Python.
FYI, Integer Partitioning is representing a given integer n as a sum of integers smaller than n.
def part(n, k):
def _part(n, k, pre):
if n <= 0:
return []
if k == 1:
if n <= pre:
return [[n]]
return []
ret = []
for i in range(min(pre, n), 0, -1):
ret += [[i] + sub for sub in _part(n-i, k-1, i)]
return ret
return _part(n, k, n)
Example:
>>> part(5, 1)
[[5]]
>>> part(5, 2)
[[4, 1], [3, 2]]
>>> part(5, 3)
[[3, 1, 1], [2, 2, 1]]
>>> part(5, 4)
[[2, 1, 1, 1]]
>>> part(5, 5)
[[1, 1, 1, 1, 1]]
>>> part(6, 3)
[[4, 1, 1], [3, 2, 1], [2, 2, 2]]
UPDATE
Using memoization:
def part(n, k):
def memoize(f):
cache = [[[None] * n for j in xrange(k)] for i in xrange(n)]
def wrapper(n, k, pre):
if cache[n-1][k-1][pre-1] is None:
cache[n-1][k-1][pre-1] = f(n, k, pre)
return cache[n-1][k-1][pre-1]
return wrapper
@memoize
def _part(n, k, pre):
if n <= 0:
return []
if k == 1:
if n <= pre:
return [(n,)]
return []
ret = []
for i in xrange(min(pre, n), 0, -1):
ret += [(i,) + sub for sub in _part(n-i, k-1, i)]
return ret
return _part(n, k, n)
First I want to thanks everyone for their contribution. I arrived here needing an algorithm for generating integer partitions with the following details :
Generate partitions of a number into EXACTLY k parts but also having MINIMUM and MAXIMUM constraints.
Therefore, I modified the code of "Snakes and Coffee" to accommodate these new requirements:
def partition_min_max(n,k,l, m):
'''n is the integer to partition, k is the length of partitions,
l is the min partition element size, m is the max partition element size '''
if k < 1:
raise StopIteration
if k == 1:
if n <= m and n>=l :
yield (n,)
raise StopIteration
for i in range(l,m+1):
for result in partition_min_max(n-i,k-1,i,m):
yield result+(i,)
>>> x = list(partition_min_max(20 ,3, 3, 10 ))
>>> print(x)
>>> [(10, 7, 3), (9, 8, 3), (10, 6, 4), (9, 7, 4), (8, 8, 4), (10, 5, 5), (9, 6, 5), (8, 7, 5), (8, 6, 6), (7, 7, 6)]
I've written a generator solution
def partitionfunc(n,k,l=1):
'''n is the integer to partition, k is the length of partitions, l is the min partition element size'''
if k < 1:
raise StopIteration
if k == 1:
if n >= l:
yield (n,)
raise StopIteration
for i in range(l,n+1):
for result in partitionfunc(n-i,k-1,i):
yield (i,)+result
This generates all the partitions of n
with length k
with each one being in order of least to greatest.
Just a quick note: Via cProfile
, it appears that using the generator method is much faster than using falsetru's direct method, using the test function lambda x,y: list(partitionfunc(x,y))
. On a test run of n=50,k-5
, my code ran in .019 seconds vs the 2.612 seconds of the direct method.