This module includes functions and classes for enumerating and counting multiset partitions.
Enumerates partions of a multiset.
Parameters :  multiplicities


Yields :  state

See also
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import multiset_partitions_taocp
>>> # variables components and multiplicities represent the multiset 'abb'
>>> components = 'ab'
>>> multiplicities = [1, 2]
>>> states = multiset_partitions_taocp(multiplicities)
>>> list(list_visitor(state, components) for state in states)
[[['a', 'b', 'b']],
[['a', 'b'], ['b']],
[['a'], ['b', 'b']],
[['a'], ['b'], ['b']]]
Use with multiset_partitions_taocp to enumerate the ways a number can be expressed as a product of factors. For this usage, the exponents of the prime factors of a number are arguments to the partition enumerator, while the corresponding prime factors are input here.
Examples
To enumerate the factorings of a number we can think of the elements of the partition as being the prime factors and the multiplicities as being their exponents.
>>> from sympy.utilities.enumerative import factoring_visitor
>>> from sympy.utilities.enumerative import multiset_partitions_taocp
>>> from sympy import factorint
>>> primes, multiplicities = zip(*factorint(24).items())
>>> primes
(2, 3)
>>> multiplicities
(3, 1)
>>> states = multiset_partitions_taocp(multiplicities)
>>> list(factoring_visitor(state, primes) for state in states)
[[24], [8, 3], [12, 2], [4, 6], [4, 2, 3], [6, 2, 2], [2, 2, 2, 3]]
Return a list of lists to represent the partition.
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import multiset_partitions_taocp
>>> states = multiset_partitions_taocp([1, 2, 1])
>>> s = next(states)
>>> list_visitor(s, 'abc') # for multiset 'a b b c'
[['a', 'b', 'b', 'c']]
>>> s = next(states)
>>> list_visitor(s, [1, 2, 3]) # for multiset '1 2 2 3
[[1, 2, 2], [3]]
The approach of the function multiset_partitions_taocp is extended and generalized by the class MultisetPartitionTraverser.
Has methods to enumerate and count the partitions of a multiset.
This implements a refactored and extended version of Knuth’s algorithm 7.1.2.5M [AOCP].”
The enumeration methods of this class are generators and return data structures which can be interpreted by the same visitor functions used for the output of multiset_partitions_taocp.
See also
multiset_partitions_taocp, sympy.utilities.iterables.multiset_partititions
References
[AOCP]  (1, 2, 3, 4) Algorithm 7.1.2.5M in Volume 4A, Combinatoral Algorithms, Part 1, of The Art of Computer Programming, by Donald Knuth. 
[Factorisatio]  On a Problem of Oppenheim concerning “Factorisatio Numerorum” E. R. Canfield, Paul Erdos, Carl Pomerance, JOURNAL OF NUMBER THEORY, Vol. 17, No. 1. August 1983. See section 7 for a description of an algorithm similar to Knuth’s. 
[Yorgey]  Generating Multiset Partitions, Brent Yorgey, The Monad.Reader, Issue 8, September 2007. 
Examples
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> m.count_partitions([4,4,4,2])
127750
>>> m.count_partitions([3,3,3])
686
Returns the number of partitions of a multiset whose components have the multiplicities given in multiplicities.
For larger counts, this method is much faster than calling one of the enumerators and counting the result. Uses dynamic programming to cut down on the number of nodes actually explored. The dictionary used in order to accelerate the counting process is stored in the MultisetPartitionTraverser object and persists across calls. If the the user does not expect to call count_partitions for any additional multisets, the object should be cleared to save memory. On the other hand, the cache built up from one count run can significantly speed up subsequent calls to count_partitions, so it may be advantageous not to clear the object.
Notes
If one looks at the workings of Knuth’s algorithm M [AOCP], it can be viewed as a traversal of a binary tree of parts. A part has (up to) two children, the left child resulting from the spread operation, and the right child from the decrement operation. The ordinary enumeration of multiset partitions is an inorder traversal of this tree, and with the partitions corresponding to paths from the root to the leaves. The mapping from paths to partitions is a little complicated, since the partition would contain only those parts which are leaves or the parents of a spread link, not those which are parents of a decrement link.
For counting purposes, it is sufficient to count leaves, and this can be done with a recursive inorder traversal. The number of leaves of a subtree rooted at a particular part is a function only of that part itself, so memoizing has the potential to speed up the counting dramatically.
This method follows a computational approach which is similar to the hypothetical memoized recursive function, but with two differences:
Unlike the enumeration functions, there is currently no _range version of count_partitions. If someone wants to stretch their brain, it should be possible to construct one by memoizing with a histogram of counts rather than a single count, and combining the histograms.
Examples
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> m.count_partitions([9,8,2])
288716
>>> m.count_partitions([2,2])
9
>>> del m
Enumerate the partitions of a multiset.
See also
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> states = m.enum_all([2,2])
>>> list(list_visitor(state, 'ab') for state in states)
[[['a', 'a', 'b', 'b']],
[['a', 'a', 'b'], ['b']],
[['a', 'a'], ['b', 'b']],
[['a', 'a'], ['b'], ['b']],
[['a', 'b', 'b'], ['a']],
[['a', 'b'], ['a', 'b']],
[['a', 'b'], ['a'], ['b']],
[['a'], ['a'], ['b', 'b']],
[['a'], ['a'], ['b'], ['b']]]
Enumerate the partitions of a multiset with lb < num(parts)
Equivalent to enum_range(multiplicities, lb, sum(multiplicities))
Parameters :  multiplicities
lb


See also
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> states = m.enum_large([2,2], 2)
>>> list(list_visitor(state, 'ab') for state in states)
[[['a', 'a'], ['b'], ['b']],
[['a', 'b'], ['a'], ['b']],
[['a'], ['a'], ['b', 'b']],
[['a'], ['a'], ['b'], ['b']]]
Enumerate the partitions of a multiset with lb < num(parts) <= ub.
In particular, if partitions with exactly k parts are desired, call with (multiplicities, k  1, k). This method generalizes enum_all, enum_small, and enum_large.
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> states = m.enum_range([2,2], 1, 2)
>>> list(list_visitor(state, 'ab') for state in states)
[[['a', 'a', 'b'], ['b']],
[['a', 'a'], ['b', 'b']],
[['a', 'b', 'b'], ['a']],
[['a', 'b'], ['a', 'b']]]
Enumerate multiset partitions with no more than ub parts.
Equivalent to enum_range(multiplicities, 0, ub)
Parameters :  multiplicities
ub


See also
Examples
>>> from sympy.utilities.enumerative import list_visitor
>>> from sympy.utilities.enumerative import MultisetPartitionTraverser
>>> m = MultisetPartitionTraverser()
>>> states = m.enum_small([2,2], 2)
>>> list(list_visitor(state, 'ab') for state in states)
[[['a', 'a', 'b', 'b']],
[['a', 'a', 'b'], ['b']],
[['a', 'a'], ['b', 'b']],
[['a', 'b', 'b'], ['a']],
[['a', 'b'], ['a', 'b']]]
The implementation is based, in part, on the answer given to exercise 69, in Knuth [AOCP].