Python Integer Partitioning with given k partitions

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. For example, an integer 5 can be expressed as 4 + 1 = 3 + 2 = 3 + 1 + 1 = 2 + 2 + 1 = 2 + 1 + 1 + 1 = 1 + 1 + 1 + 1 + 1

I’ve found a number of solutions for this. http://homepages.ed.ac.uk/jkellehe/partitions.php and http://code.activestate.com/recipes/218332-generator-for-integer-partitions/

However, what I really want is to restrict the number of partitions.

Say, # of partition k = 2, a program only need to show 5 = 4 + 1 = 3 + 2,

if k = 3, 5 = 3 + 1 + 1 = 2 + 2 + 1

Answers:

Thank you for visiting the Q&A section on Magenaut. Please note that all the answers may not help you solve the issue immediately. So please treat them as advisements. If you found the post helpful (or not), leave a comment & I’ll get back to you as soon as possible.

Method 1

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.

Method 2

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)

Method 3

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)]

Method 4

Building upon previous answer with maximum and minimum constraints, we can optimize it be a little better . For eg with k = 16 , n = 2048 and m = 128 , there is only one such partition which satisfy the constraints(128+128+…+128). But the code searches unnecessary branches for an answer which can be pruned.

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:
        return
    if k == 1:
        if n <= m and n>=l :
            yield (n,)
        return
    if (k*128) < n: #If the current sum is too small to reach n
        return
    if k*1 > n:#If current sum is too big to reach n
        return
    for i in range(l,m+1):
        for result in partition_min_max(n-i,k-1,i,m):                
            yield result+(i,)


All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0

0 0 votes
Article Rating
Subscribe
Notify of
guest

0 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x