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746 lines
20 KiB
746 lines
20 KiB
from sympy.core import Basic, Dict, sympify, Tuple
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from sympy.core.numbers import Integer
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from sympy.core.sorting import default_sort_key
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from sympy.core.sympify import _sympify
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from sympy.functions.combinatorial.numbers import bell
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from sympy.matrices import zeros
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from sympy.sets.sets import FiniteSet, Union
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from sympy.utilities.iterables import flatten, group
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from sympy.utilities.misc import as_int
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from collections import defaultdict
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class Partition(FiniteSet):
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"""
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This class represents an abstract partition.
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A partition is a set of disjoint sets whose union equals a given set.
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See Also
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========
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sympy.utilities.iterables.partitions,
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sympy.utilities.iterables.multiset_partitions
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"""
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_rank = None
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_partition = None
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def __new__(cls, *partition):
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"""
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Generates a new partition object.
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This method also verifies if the arguments passed are
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valid and raises a ValueError if they are not.
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Examples
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========
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Creating Partition from Python lists:
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3])
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>>> a
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Partition({3}, {1, 2})
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>>> a.partition
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[[1, 2], [3]]
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>>> len(a)
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2
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>>> a.members
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(1, 2, 3)
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Creating Partition from Python sets:
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>>> Partition({1, 2, 3}, {4, 5})
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Partition({4, 5}, {1, 2, 3})
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Creating Partition from SymPy finite sets:
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>>> from sympy import FiniteSet
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>>> a = FiniteSet(1, 2, 3)
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>>> b = FiniteSet(4, 5)
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>>> Partition(a, b)
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Partition({4, 5}, {1, 2, 3})
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"""
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args = []
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dups = False
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for arg in partition:
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if isinstance(arg, list):
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as_set = set(arg)
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if len(as_set) < len(arg):
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dups = True
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break # error below
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arg = as_set
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args.append(_sympify(arg))
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if not all(isinstance(part, FiniteSet) for part in args):
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raise ValueError(
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"Each argument to Partition should be " \
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"a list, set, or a FiniteSet")
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# sort so we have a canonical reference for RGS
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U = Union(*args)
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if dups or len(U) < sum(len(arg) for arg in args):
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raise ValueError("Partition contained duplicate elements.")
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obj = FiniteSet.__new__(cls, *args)
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obj.members = tuple(U)
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obj.size = len(U)
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return obj
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def sort_key(self, order=None):
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"""Return a canonical key that can be used for sorting.
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Ordering is based on the size and sorted elements of the partition
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and ties are broken with the rank.
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Examples
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========
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>>> from sympy import default_sort_key
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>>> from sympy.combinatorics import Partition
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>>> from sympy.abc import x
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>>> a = Partition([1, 2])
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>>> b = Partition([3, 4])
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>>> c = Partition([1, x])
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>>> d = Partition(list(range(4)))
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>>> l = [d, b, a + 1, a, c]
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>>> l.sort(key=default_sort_key); l
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[Partition({1, 2}), Partition({1}, {2}), Partition({1, x}), Partition({3, 4}), Partition({0, 1, 2, 3})]
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"""
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if order is None:
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members = self.members
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else:
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members = tuple(sorted(self.members,
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key=lambda w: default_sort_key(w, order)))
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return tuple(map(default_sort_key, (self.size, members, self.rank)))
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@property
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def partition(self):
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"""Return partition as a sorted list of lists.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> Partition([1], [2, 3]).partition
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[[1], [2, 3]]
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"""
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if self._partition is None:
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self._partition = sorted([sorted(p, key=default_sort_key)
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for p in self.args])
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return self._partition
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def __add__(self, other):
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"""
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Return permutation whose rank is ``other`` greater than current rank,
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(mod the maximum rank for the set).
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3])
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>>> a.rank
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1
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>>> (a + 1).rank
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2
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>>> (a + 100).rank
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1
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"""
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other = as_int(other)
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offset = self.rank + other
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result = RGS_unrank((offset) %
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RGS_enum(self.size),
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self.size)
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return Partition.from_rgs(result, self.members)
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def __sub__(self, other):
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"""
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Return permutation whose rank is ``other`` less than current rank,
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(mod the maximum rank for the set).
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3])
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>>> a.rank
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1
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>>> (a - 1).rank
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0
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>>> (a - 100).rank
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1
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"""
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return self.__add__(-other)
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def __le__(self, other):
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"""
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Checks if a partition is less than or equal to
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the other based on rank.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3, 4, 5])
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>>> b = Partition([1], [2, 3], [4], [5])
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>>> a.rank, b.rank
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(9, 34)
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>>> a <= a
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True
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>>> a <= b
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True
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"""
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return self.sort_key() <= sympify(other).sort_key()
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def __lt__(self, other):
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"""
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Checks if a partition is less than the other.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3, 4, 5])
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>>> b = Partition([1], [2, 3], [4], [5])
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>>> a.rank, b.rank
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(9, 34)
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>>> a < b
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True
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"""
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return self.sort_key() < sympify(other).sort_key()
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@property
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def rank(self):
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"""
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Gets the rank of a partition.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3], [4, 5])
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>>> a.rank
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13
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"""
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if self._rank is not None:
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return self._rank
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self._rank = RGS_rank(self.RGS)
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return self._rank
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@property
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def RGS(self):
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"""
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Returns the "restricted growth string" of the partition.
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Explanation
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===========
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The RGS is returned as a list of indices, L, where L[i] indicates
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the block in which element i appears. For example, in a partition
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of 3 elements (a, b, c) into 2 blocks ([c], [a, b]) the RGS is
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[1, 1, 0]: "a" is in block 1, "b" is in block 1 and "c" is in block 0.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> a = Partition([1, 2], [3], [4, 5])
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>>> a.members
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(1, 2, 3, 4, 5)
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>>> a.RGS
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(0, 0, 1, 2, 2)
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>>> a + 1
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Partition({3}, {4}, {5}, {1, 2})
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>>> _.RGS
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(0, 0, 1, 2, 3)
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"""
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rgs = {}
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partition = self.partition
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for i, part in enumerate(partition):
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for j in part:
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rgs[j] = i
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return tuple([rgs[i] for i in sorted(
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[i for p in partition for i in p], key=default_sort_key)])
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@classmethod
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def from_rgs(self, rgs, elements):
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"""
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Creates a set partition from a restricted growth string.
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Explanation
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===========
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The indices given in rgs are assumed to be the index
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of the element as given in elements *as provided* (the
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elements are not sorted by this routine). Block numbering
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starts from 0. If any block was not referenced in ``rgs``
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an error will be raised.
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Examples
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========
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>>> from sympy.combinatorics import Partition
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>>> Partition.from_rgs([0, 1, 2, 0, 1], list('abcde'))
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Partition({c}, {a, d}, {b, e})
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>>> Partition.from_rgs([0, 1, 2, 0, 1], list('cbead'))
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Partition({e}, {a, c}, {b, d})
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>>> a = Partition([1, 4], [2], [3, 5])
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>>> Partition.from_rgs(a.RGS, a.members)
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Partition({2}, {1, 4}, {3, 5})
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"""
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if len(rgs) != len(elements):
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raise ValueError('mismatch in rgs and element lengths')
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max_elem = max(rgs) + 1
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partition = [[] for i in range(max_elem)]
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j = 0
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for i in rgs:
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partition[i].append(elements[j])
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j += 1
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if not all(p for p in partition):
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raise ValueError('some blocks of the partition were empty.')
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return Partition(*partition)
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class IntegerPartition(Basic):
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"""
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This class represents an integer partition.
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Explanation
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===========
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In number theory and combinatorics, a partition of a positive integer,
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``n``, also called an integer partition, is a way of writing ``n`` as a
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list of positive integers that sum to n. Two partitions that differ only
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in the order of summands are considered to be the same partition; if order
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matters then the partitions are referred to as compositions. For example,
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4 has five partitions: [4], [3, 1], [2, 2], [2, 1, 1], and [1, 1, 1, 1];
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the compositions [1, 2, 1] and [1, 1, 2] are the same as partition
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[2, 1, 1].
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See Also
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========
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sympy.utilities.iterables.partitions,
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sympy.utilities.iterables.multiset_partitions
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References
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==========
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.. [1] https://en.wikipedia.org/wiki/Partition_%28number_theory%29
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"""
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_dict = None
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_keys = None
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def __new__(cls, partition, integer=None):
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"""
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Generates a new IntegerPartition object from a list or dictionary.
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Explanation
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===========
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The partition can be given as a list of positive integers or a
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dictionary of (integer, multiplicity) items. If the partition is
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preceded by an integer an error will be raised if the partition
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does not sum to that given integer.
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Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> a = IntegerPartition([5, 4, 3, 1, 1])
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>>> a
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IntegerPartition(14, (5, 4, 3, 1, 1))
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>>> print(a)
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[5, 4, 3, 1, 1]
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>>> IntegerPartition({1:3, 2:1})
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IntegerPartition(5, (2, 1, 1, 1))
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If the value that the partition should sum to is given first, a check
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will be made to see n error will be raised if there is a discrepancy:
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>>> IntegerPartition(10, [5, 4, 3, 1])
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Traceback (most recent call last):
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...
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ValueError: The partition is not valid
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"""
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if integer is not None:
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integer, partition = partition, integer
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if isinstance(partition, (dict, Dict)):
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_ = []
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for k, v in sorted(partition.items(), reverse=True):
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if not v:
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continue
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k, v = as_int(k), as_int(v)
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_.extend([k]*v)
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partition = tuple(_)
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else:
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partition = tuple(sorted(map(as_int, partition), reverse=True))
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sum_ok = False
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if integer is None:
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integer = sum(partition)
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sum_ok = True
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else:
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integer = as_int(integer)
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if not sum_ok and sum(partition) != integer:
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raise ValueError("Partition did not add to %s" % integer)
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if any(i < 1 for i in partition):
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raise ValueError("All integer summands must be greater than one")
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obj = Basic.__new__(cls, Integer(integer), Tuple(*partition))
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obj.partition = list(partition)
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obj.integer = integer
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return obj
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def prev_lex(self):
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"""Return the previous partition of the integer, n, in lexical order,
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wrapping around to [1, ..., 1] if the partition is [n].
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Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> p = IntegerPartition([4])
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>>> print(p.prev_lex())
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[3, 1]
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>>> p.partition > p.prev_lex().partition
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True
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"""
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d = defaultdict(int)
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d.update(self.as_dict())
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keys = self._keys
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if keys == [1]:
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return IntegerPartition({self.integer: 1})
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if keys[-1] != 1:
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d[keys[-1]] -= 1
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if keys[-1] == 2:
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d[1] = 2
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else:
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d[keys[-1] - 1] = d[1] = 1
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else:
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d[keys[-2]] -= 1
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left = d[1] + keys[-2]
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new = keys[-2]
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d[1] = 0
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while left:
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new -= 1
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if left - new >= 0:
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d[new] += left//new
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left -= d[new]*new
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return IntegerPartition(self.integer, d)
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def next_lex(self):
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"""Return the next partition of the integer, n, in lexical order,
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wrapping around to [n] if the partition is [1, ..., 1].
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Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> p = IntegerPartition([3, 1])
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>>> print(p.next_lex())
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[4]
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>>> p.partition < p.next_lex().partition
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True
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"""
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d = defaultdict(int)
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d.update(self.as_dict())
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key = self._keys
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a = key[-1]
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if a == self.integer:
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d.clear()
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d[1] = self.integer
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elif a == 1:
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if d[a] > 1:
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d[a + 1] += 1
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d[a] -= 2
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else:
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b = key[-2]
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d[b + 1] += 1
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d[1] = (d[b] - 1)*b
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d[b] = 0
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else:
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if d[a] > 1:
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if len(key) == 1:
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d.clear()
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d[a + 1] = 1
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d[1] = self.integer - a - 1
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else:
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a1 = a + 1
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d[a1] += 1
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d[1] = d[a]*a - a1
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d[a] = 0
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else:
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b = key[-2]
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b1 = b + 1
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d[b1] += 1
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need = d[b]*b + d[a]*a - b1
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d[a] = d[b] = 0
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d[1] = need
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return IntegerPartition(self.integer, d)
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def as_dict(self):
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"""Return the partition as a dictionary whose keys are the
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partition integers and the values are the multiplicity of that
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integer.
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Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> IntegerPartition([1]*3 + [2] + [3]*4).as_dict()
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{1: 3, 2: 1, 3: 4}
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"""
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if self._dict is None:
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groups = group(self.partition, multiple=False)
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self._keys = [g[0] for g in groups]
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self._dict = dict(groups)
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return self._dict
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@property
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def conjugate(self):
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"""
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Computes the conjugate partition of itself.
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Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> a = IntegerPartition([6, 3, 3, 2, 1])
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>>> a.conjugate
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[5, 4, 3, 1, 1, 1]
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"""
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j = 1
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temp_arr = list(self.partition) + [0]
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k = temp_arr[0]
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b = [0]*k
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while k > 0:
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while k > temp_arr[j]:
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b[k - 1] = j
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k -= 1
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j += 1
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return b
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def __lt__(self, other):
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"""Return True if self is less than other when the partition
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is listed from smallest to biggest.
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|
|
Examples
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========
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> a = IntegerPartition([3, 1])
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>>> a < a
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False
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>>> b = a.next_lex()
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>>> a < b
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True
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>>> a == b
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False
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"""
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return list(reversed(self.partition)) < list(reversed(other.partition))
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|
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def __le__(self, other):
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"""Return True if self is less than other when the partition
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is listed from smallest to biggest.
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|
|
Examples
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|
========
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|
|
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> a = IntegerPartition([4])
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>>> a <= a
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True
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"""
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return list(reversed(self.partition)) <= list(reversed(other.partition))
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|
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def as_ferrers(self, char='#'):
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"""
|
|
Prints the ferrer diagram of a partition.
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|
|
Examples
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|
========
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|
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>>> from sympy.combinatorics.partitions import IntegerPartition
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>>> print(IntegerPartition([1, 1, 5]).as_ferrers())
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|
#####
|
|
#
|
|
#
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|
"""
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|
return "\n".join([char*i for i in self.partition])
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|
|
|
def __str__(self):
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return str(list(self.partition))
|
|
|
|
|
|
def random_integer_partition(n, seed=None):
|
|
"""
|
|
Generates a random integer partition summing to ``n`` as a list
|
|
of reverse-sorted integers.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.combinatorics.partitions import random_integer_partition
|
|
|
|
For the following, a seed is given so a known value can be shown; in
|
|
practice, the seed would not be given.
|
|
|
|
>>> random_integer_partition(100, seed=[1, 1, 12, 1, 2, 1, 85, 1])
|
|
[85, 12, 2, 1]
|
|
>>> random_integer_partition(10, seed=[1, 2, 3, 1, 5, 1])
|
|
[5, 3, 1, 1]
|
|
>>> random_integer_partition(1)
|
|
[1]
|
|
"""
|
|
from sympy.core.random import _randint
|
|
|
|
n = as_int(n)
|
|
if n < 1:
|
|
raise ValueError('n must be a positive integer')
|
|
|
|
randint = _randint(seed)
|
|
|
|
partition = []
|
|
while (n > 0):
|
|
k = randint(1, n)
|
|
mult = randint(1, n//k)
|
|
partition.append((k, mult))
|
|
n -= k*mult
|
|
partition.sort(reverse=True)
|
|
partition = flatten([[k]*m for k, m in partition])
|
|
return partition
|
|
|
|
|
|
def RGS_generalized(m):
|
|
"""
|
|
Computes the m + 1 generalized unrestricted growth strings
|
|
and returns them as rows in matrix.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.combinatorics.partitions import RGS_generalized
|
|
>>> RGS_generalized(6)
|
|
Matrix([
|
|
[ 1, 1, 1, 1, 1, 1, 1],
|
|
[ 1, 2, 3, 4, 5, 6, 0],
|
|
[ 2, 5, 10, 17, 26, 0, 0],
|
|
[ 5, 15, 37, 77, 0, 0, 0],
|
|
[ 15, 52, 151, 0, 0, 0, 0],
|
|
[ 52, 203, 0, 0, 0, 0, 0],
|
|
[203, 0, 0, 0, 0, 0, 0]])
|
|
"""
|
|
d = zeros(m + 1)
|
|
for i in range(m + 1):
|
|
d[0, i] = 1
|
|
|
|
for i in range(1, m + 1):
|
|
for j in range(m):
|
|
if j <= m - i:
|
|
d[i, j] = j * d[i - 1, j] + d[i - 1, j + 1]
|
|
else:
|
|
d[i, j] = 0
|
|
return d
|
|
|
|
|
|
def RGS_enum(m):
|
|
"""
|
|
RGS_enum computes the total number of restricted growth strings
|
|
possible for a superset of size m.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.combinatorics.partitions import RGS_enum
|
|
>>> from sympy.combinatorics import Partition
|
|
>>> RGS_enum(4)
|
|
15
|
|
>>> RGS_enum(5)
|
|
52
|
|
>>> RGS_enum(6)
|
|
203
|
|
|
|
We can check that the enumeration is correct by actually generating
|
|
the partitions. Here, the 15 partitions of 4 items are generated:
|
|
|
|
>>> a = Partition(list(range(4)))
|
|
>>> s = set()
|
|
>>> for i in range(20):
|
|
... s.add(a)
|
|
... a += 1
|
|
...
|
|
>>> assert len(s) == 15
|
|
|
|
"""
|
|
if (m < 1):
|
|
return 0
|
|
elif (m == 1):
|
|
return 1
|
|
else:
|
|
return bell(m)
|
|
|
|
|
|
def RGS_unrank(rank, m):
|
|
"""
|
|
Gives the unranked restricted growth string for a given
|
|
superset size.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.combinatorics.partitions import RGS_unrank
|
|
>>> RGS_unrank(14, 4)
|
|
[0, 1, 2, 3]
|
|
>>> RGS_unrank(0, 4)
|
|
[0, 0, 0, 0]
|
|
"""
|
|
if m < 1:
|
|
raise ValueError("The superset size must be >= 1")
|
|
if rank < 0 or RGS_enum(m) <= rank:
|
|
raise ValueError("Invalid arguments")
|
|
|
|
L = [1] * (m + 1)
|
|
j = 1
|
|
D = RGS_generalized(m)
|
|
for i in range(2, m + 1):
|
|
v = D[m - i, j]
|
|
cr = j*v
|
|
if cr <= rank:
|
|
L[i] = j + 1
|
|
rank -= cr
|
|
j += 1
|
|
else:
|
|
L[i] = int(rank / v + 1)
|
|
rank %= v
|
|
return [x - 1 for x in L[1:]]
|
|
|
|
|
|
def RGS_rank(rgs):
|
|
"""
|
|
Computes the rank of a restricted growth string.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.combinatorics.partitions import RGS_rank, RGS_unrank
|
|
>>> RGS_rank([0, 1, 2, 1, 3])
|
|
42
|
|
>>> RGS_rank(RGS_unrank(4, 7))
|
|
4
|
|
"""
|
|
rgs_size = len(rgs)
|
|
rank = 0
|
|
D = RGS_generalized(rgs_size)
|
|
for i in range(1, rgs_size):
|
|
n = len(rgs[(i + 1):])
|
|
m = max(rgs[0:i])
|
|
rank += D[n, m + 1] * rgs[i]
|
|
return rank
|