Set Partitions#
AUTHORS:
Mike Hansen
MuPAD-Combinat developers (for algorithms and design inspiration).
Travis Scrimshaw (2013-02-28): Removed
CombinatorialClass
and added entry point throughSetPartition
.Martin Rubey (2017-10-10): Cleanup, add crossings and nestings, add random generation.
This module defines a class for immutable partitioning of a set. For
mutable version see DisjointSet()
.
- class sage.combinat.set_partition.AbstractSetPartition#
Bases:
ClonableArray
Methods of set partitions which are independent of the base set
- base_set()#
Return the base set of
self
, which is the union of all parts ofself
.EXAMPLES:
sage: SetPartition([[1], [2,3], [4]]).base_set() {1, 2, 3, 4} sage: SetPartition([[1,2,3,4]]).base_set() {1, 2, 3, 4} sage: SetPartition([]).base_set() {}
- base_set_cardinality()#
Return the cardinality of the base set of
self
, which is the sum of the sizes of the parts ofself
.This is also known as the size (sometimes the weight) of a set partition.
EXAMPLES:
sage: SetPartition([[1], [2,3], [4]]).base_set_cardinality() 4 sage: SetPartition([[1,2,3,4]]).base_set_cardinality() 4
- coarsenings()#
Return a list of coarsenings of
self
.See also
refinements()
EXAMPLES:
sage: SetPartition([[1,3],[2,4]]).coarsenings() [{{1, 2, 3, 4}}, {{1, 3}, {2, 4}}] sage: SetPartition([[1],[2,4],[3]]).coarsenings() [{{1, 2, 3, 4}}, {{1, 2, 4}, {3}}, {{1, 3}, {2, 4}}, {{1}, {2, 3, 4}}, {{1}, {2, 4}, {3}}] sage: SetPartition([]).coarsenings() [{}]
- conjugate()#
An involution exchanging singletons and circular adjacencies.
This method implements the definition of the conjugate of a set partition defined in [Cal2005].
INPUT:
self
– a set partition of an ordered set
OUTPUT:
a set partition
EXAMPLES:
sage: SetPartition([[1,6,7],[2,8],[3,4,5]]).conjugate() {{1, 4, 7}, {2, 8}, {3}, {5}, {6}} sage: all(sp.conjugate().conjugate()==sp for sp in SetPartitions([1,3,5,7])) True sage: SetPartition([]).conjugate() {}
- inf(other)#
The product of the set partitions
self
andother
.The product of two set partitions \(B\) and \(C\) is defined as the set partition whose parts are the nonempty intersections between each part of \(B\) and each part of \(C\). This product is also the infimum of \(B\) and \(C\) in the classical set partition lattice (that is, the coarsest set partition which is finer than each of \(B\) and \(C\)). Consequently,
inf
acts as an alias for this method.See also
EXAMPLES:
sage: x = SetPartition([ [1,2], [3,5,4] ]) sage: y = SetPartition(( (3,1,2), (5,4) )) sage: x * y {{1, 2}, {3}, {4, 5}} sage: S = SetPartitions(4) sage: sp1 = S([[2,3,4], [1]]) sage: sp2 = S([[1,3], [2,4]]) sage: s = S([[2,4], [3], [1]]) sage: sp1.inf(sp2) == s True
- max_block_size()#
The maximum block size of the diagram.
EXAMPLES:
sage: # needs sage.modules sage: from sage.combinat.diagram_algebras import PartitionDiagram, PartitionDiagrams sage: pd = PartitionDiagram([[1,-3,-5],[2,4],[3,-1,-2],[5],[-4]]) sage: pd.max_block_size() 3 sage: sorted(d.max_block_size() for d in PartitionDiagrams(2)) [1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4] sage: sorted(sp.max_block_size() for sp in SetPartitions(3)) [1, 2, 2, 2, 3]
- standard_form()#
Return
self
as a list of lists.When the ground set is totally ordered, the elements of each block are listed in increasing order.
This is not related to standard set partitions (which simply means set partitions of \([n] = \{ 1, 2, \ldots , n \}\) for some integer \(n\)) or standardization (
standardization()
).EXAMPLES:
sage: [x.standard_form() for x in SetPartitions(4, [2,2])] # needs sage.graphs sage.rings.finite_rings [[[1, 2], [3, 4]], [[1, 4], [2, 3]], [[1, 3], [2, 4]]]
- sup(t)#
Return the supremum of
self
andt
in the classical set partition lattice.The supremum of two set partitions \(B\) and \(C\) is obtained as the transitive closure of the relation which relates \(i\) to \(j\) if and only if \(i\) and \(j\) are in the same part in at least one of the set partitions \(B\) and \(C\).
See also
__mul__()
EXAMPLES:
sage: S = SetPartitions(4) sage: sp1 = S([[2,3,4], [1]]) sage: sp2 = S([[1,3], [2,4]]) sage: s = S([[1,2,3,4]]) sage: sp1.sup(sp2) == s True
- class sage.combinat.set_partition.SetPartition(parent, s, check=True)#
Bases:
AbstractSetPartition
A partition of a set.
A set partition \(p\) of a set \(S\) is a partition of \(S\) into subsets called parts and represented as a set of sets. By extension, a set partition of a nonnegative integer \(n\) is the set partition of the integers from 1 to \(n\). The number of set partitions of \(n\) is called the \(n\)-th Bell number.
There is a natural integer partition associated with a set partition, namely the nonincreasing sequence of sizes of all its parts.
There is a classical lattice associated with all set partitions of \(n\). The infimum of two set partitions is the set partition obtained by intersecting all the parts of both set partitions. The supremum is obtained by transitive closure of the relation \(i\) related to \(j\) if and only if they are in the same part in at least one of the set partitions.
We will use terminology from partitions, in particular the length of a set partition \(A = \{A_1, \ldots, A_k\}\) is the number of parts of \(A\) and is denoted by \(|A| := k\). The size of \(A\) is the cardinality of \(S\). We will also sometimes use the notation \([n] := \{1, 2, \ldots, n\}\).
EXAMPLES:
There are 5 set partitions of the set \(\{1,2,3\}\):
sage: SetPartitions(3).cardinality() # needs sage.libs.flint 5
Here is the list of them:
sage: SetPartitions(3).list() # needs sage.graphs [{{1, 2, 3}}, {{1, 2}, {3}}, {{1, 3}, {2}}, {{1}, {2, 3}}, {{1}, {2}, {3}}]
There are 6 set partitions of \(\{1,2,3,4\}\) whose underlying partition is \([2, 1, 1]\):
sage: SetPartitions(4, [2,1,1]).list() # needs sage.graphs sage.rings.finite_rings [{{1}, {2, 4}, {3}}, {{1}, {2}, {3, 4}}, {{1, 4}, {2}, {3}}, {{1, 3}, {2}, {4}}, {{1, 2}, {3}, {4}}, {{1}, {2, 3}, {4}}]
Since github issue #14140, we can create a set partition directly by
SetPartition
, which creates the base set by taking the union of the parts passed in:sage: s = SetPartition([[1,3],[2,4]]); s {{1, 3}, {2, 4}} sage: s.parent() Set partitions
- apply_permutation(p)#
Apply
p
to the underlying set ofself
.INPUT:
p
– a permutation
EXAMPLES:
sage: x = SetPartition([[1,2], [3,5,4]]) sage: p = Permutation([2,1,4,5,3]) sage: x.apply_permutation(p) {{1, 2}, {3, 4, 5}} sage: q = Permutation([3,2,1,5,4]) sage: x.apply_permutation(q) {{1, 4, 5}, {2, 3}} sage: m = PerfectMatching([(1,4),(2,6),(3,5)]) sage: m.apply_permutation(Permutation([4,1,5,6,3,2])) [(1, 2), (3, 5), (4, 6)]
- arcs()#
Return
self
as a list of arcs.Assuming that the blocks are sorted, the arcs are the pairs of consecutive elements in the blocks.
EXAMPLES:
sage: A = SetPartition([[1],[2,3],[4]]) sage: A.arcs() [(2, 3)] sage: B = SetPartition([[1,3,6,7],[2,5],[4]]) sage: B.arcs() [(1, 3), (3, 6), (6, 7), (2, 5)]
- cardinality()#
Return the len of
self
EXAMPLES:
sage: from sage.structure.list_clone_demo import IncreasingArrays sage: len(IncreasingArrays()([1,2,3])) 3
- check()#
Check that we are a valid set partition.
EXAMPLES:
sage: S = SetPartitions(4) sage: s = S([[1, 3], [2, 4]]) sage: s.check()
- closers()#
Return the maximal elements of the blocks.
EXAMPLES:
sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: P.closers() [7, 8, 9, 12, 13]
- crossings()#
Return the crossing arcs of a set partition on a totally ordered set.
OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns a list of the pairs of crossing lines (as a line correspond to a pair, it returns a list of pairs of pairs).
EXAMPLES:
sage: p = SetPartition([[1,4],[2,5,7],[3,6]]) sage: p.crossings() [((1, 4), (2, 5)), ((1, 4), (3, 6)), ((2, 5), (3, 6)), ((3, 6), (5, 7))]
- crossings_iterator()#
Return the crossing arcs of a set partition on a totally ordered set.
OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns an iterator over the pairs of crossing lines (as a line correspond to a pair, the iterator produces pairs of pairs).
EXAMPLES:
sage: p = SetPartition([[1,4],[2,5,7],[3,6]]) sage: next(p.crossings_iterator()) ((1, 4), (2, 5))
- is_atomic()#
Return if
self
is an atomic set partition.A (standard) set partition \(A\) can be split if there exist \(j < i\) such that \(\max(A_j) < \min(A_i)\) where \(A\) is ordered by minimal elements. This means we can write \(A = B | C\) for some nonempty set partitions \(B\) and \(C\). We call a set partition atomic if it cannot be split and is nonempty. Here, the pipe symbol \(|\) is as defined in method
pipe()
.EXAMPLES:
sage: SetPartition([[1,3], [2]]).is_atomic() True sage: SetPartition([[1,3], [2], [4]]).is_atomic() False sage: SetPartition([[1], [2,4], [3]]).is_atomic() False sage: SetPartition([[1,2,3,4]]).is_atomic() True sage: SetPartition([[1, 4], [2], [3]]).is_atomic() True sage: SetPartition([]).is_atomic() False
- is_noncrossing()#
Check if
self
is noncrossing.OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns
True
if the picture obtained this way has no crossings.EXAMPLES:
sage: p = SetPartition([[1,4],[2,5,7],[3,6]]) sage: p.is_noncrossing() False sage: n = PerfectMatching([3,8,1,7,6,5,4,2]); n [(1, 3), (2, 8), (4, 7), (5, 6)] sage: n.is_noncrossing() False sage: PerfectMatching([(1, 4), (2, 3), (5, 6)]).is_noncrossing() True
- is_nonnesting()#
Return if
self
is nonnesting or not.OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns
True
if the picture obtained this way has no nestings.EXAMPLES:
sage: n = PerfectMatching([3,8,1,7,6,5,4,2]); n [(1, 3), (2, 8), (4, 7), (5, 6)] sage: n.is_nonnesting() False sage: PerfectMatching([(1, 3), (2, 5), (4, 6)]).is_nonnesting() True
- latex_options()#
Return the latex options for use in the
_latex_
function as a dictionary. The default values are set using the global options.Options can be found in
set_latex_options()
EXAMPLES:
sage: SP = SetPartition([[1,6], [3,5,4]]); SP.latex_options() {'angle': 0, 'color': 'black', 'fill': False, 'plot': None, 'radius': '1cm', 'show_labels': True, 'tikz_scale': 1}
- nestings()#
Return the nestings of
self
.OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns the list of the pairs of nesting lines (as a line correspond to a pair, it returns a list of pairs of pairs).
EXAMPLES:
sage: m = PerfectMatching([(1, 6), (2, 7), (3, 5), (4, 8)]) sage: m.nestings() [((1, 6), (3, 5)), ((2, 7), (3, 5))] sage: n = PerfectMatching([3,8,1,7,6,5,4,2]); n [(1, 3), (2, 8), (4, 7), (5, 6)] sage: n.nestings() [((2, 8), (4, 7)), ((2, 8), (5, 6)), ((4, 7), (5, 6))]
- nestings_iterator()#
Iterate over the nestings of
self
.OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns an iterator over the pairs of nesting lines (as a line correspond to a pair, the iterator produces pairs of pairs).
EXAMPLES:
sage: n = PerfectMatching([(1, 6), (2, 7), (3, 5), (4, 8)]) sage: it = n.nestings_iterator() sage: next(it) ((1, 6), (3, 5)) sage: next(it) ((2, 7), (3, 5)) sage: next(it) Traceback (most recent call last): ... StopIteration
- number_of_crossings()#
Return the number of crossings.
OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns the number the pairs of crossing lines.
EXAMPLES:
sage: p = SetPartition([[1,4],[2,5,7],[3,6]]) sage: p.number_of_crossings() 4 sage: n = PerfectMatching([3,8,1,7,6,5,4,2]); n [(1, 3), (2, 8), (4, 7), (5, 6)] sage: n.number_of_crossings() 1
- number_of_nestings()#
Return the number of nestings of
self
.OUTPUT:
We place the elements of the ground set in order on a line and draw the set partition by linking consecutive elements of each block in the upper half-plane. This function returns the number the pairs of nesting lines.
EXAMPLES:
sage: n = PerfectMatching([3,8,1,7,6,5,4,2]); n [(1, 3), (2, 8), (4, 7), (5, 6)] sage: n.number_of_nestings() 3
- openers()#
Return the minimal elements of the blocks.
EXAMPLES:
sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: P.openers() [1, 3, 5, 8, 12]
- ordered_set_partition_action(s)#
Return the action of an ordered set partition
s
onself
.Let \(A = \{A_1, A_2, \ldots, A_k\}\) be a set partition of some set \(S\) and \(s\) be an ordered set partition (i.e., set composition) of a subset of \([k]\). Let \(A^{\downarrow}\) denote the standardization of \(A\), and \(A_{\{ i_1, i_2, \ldots, i_m \}}\) denote the sub-partition \(\{A_{i_1}, A_{i_2}, \ldots, A_{i_m}\}\) for any subset \(\{i_1, \ldots, i_m\}\) of \(\{1, \ldots, k\}\). We define the set partition \(s(A)\) by
\[s(A) = A_{s_1}^{\downarrow} | A_{s_2}^{\downarrow} | \cdots | A_{s_q}^{\downarrow}.\]where \(s = (s_1, s_2, \ldots, s_q)\). Here, the pipe symbol \(|\) is as defined in method
pipe()
.This is \(s[A]\) in section 2.3 in [LM2011].
INPUT:
s
– an ordered set partition with base set a subset of \(\{1, \ldots, k\}\)
EXAMPLES:
sage: A = SetPartition([[1], [2,4], [3]]) sage: s = OrderedSetPartition([[1,3], [2]]) sage: A.ordered_set_partition_action(s) {{1}, {2}, {3, 4}} sage: s = OrderedSetPartition([[2,3], [1]]) sage: A.ordered_set_partition_action(s) {{1, 3}, {2}, {4}}
We create Figure 1 in [LM2011] (we note that there is a typo in the lower-left corner of the table in the published version of the paper, whereas the arXiv version gives the correct partition):
sage: A = SetPartition([[1,3], [2,9], [4,5,8], [7]]) sage: B = SetPartition([[1,3], [2,8], [4,5,6], [7]]) sage: C = SetPartition([[1,5], [2,8], [3,4,6], [7]]) sage: s = OrderedSetPartition([[1,3], [2]]) sage: t = OrderedSetPartition([[2], [3,4]]) sage: u = OrderedSetPartition([[1], [2,3,4]]) sage: A.ordered_set_partition_action(s) {{1, 2}, {3, 4, 5}, {6, 7}} sage: A.ordered_set_partition_action(t) {{1, 2}, {3, 4, 6}, {5}} sage: A.ordered_set_partition_action(u) {{1, 2}, {3, 8}, {4, 5, 7}, {6}} sage: B.ordered_set_partition_action(s) {{1, 2}, {3, 4, 5}, {6, 7}} sage: B.ordered_set_partition_action(t) {{1, 2}, {3, 4, 5}, {6}} sage: B.ordered_set_partition_action(u) {{1, 2}, {3, 8}, {4, 5, 6}, {7}} sage: C.ordered_set_partition_action(s) {{1, 4}, {2, 3, 5}, {6, 7}} sage: C.ordered_set_partition_action(t) {{1, 2}, {3, 4, 5}, {6}} sage: C.ordered_set_partition_action(u) {{1, 2}, {3, 8}, {4, 5, 6}, {7}}
REFERENCES:
- pipe(other)#
Return the pipe of the set partitions
self
andother
.The pipe of two set partitions is defined as follows:
For any integer \(k\) and any subset \(I\) of \(\ZZ\), let \(I + k\) denote the subset of \(\ZZ\) obtained by adding \(k\) to every element of \(k\).
If \(B\) and \(C\) are set partitions of \([n]\) and \([m]\), respectively, then the pipe of \(B\) and \(C\) is defined as the set partition
\[\{ B_1, B_2, \ldots, B_b, C_1 + n, C_2 + n, \ldots, C_c + n \}\]of \([n+m]\), where \(B = \{ B_1, B_2, \ldots, B_b \}\) and \(C = \{ C_1, C_2, \ldots, C_c \}\). This pipe is denoted by \(B | C\).
EXAMPLES:
sage: SetPartition([[1,3],[2,4]]).pipe(SetPartition([[1,3],[2]])) {{1, 3}, {2, 4}, {5, 7}, {6}} sage: SetPartition([]).pipe(SetPartition([[1,2],[3,5],[4]])) {{1, 2}, {3, 5}, {4}} sage: SetPartition([[1,2],[3,5],[4]]).pipe(SetPartition([])) {{1, 2}, {3, 5}, {4}} sage: SetPartition([[1,2],[3]]).pipe(SetPartition([[1]])) {{1, 2}, {3}, {4}}
- plot(angle=None, color='black', base_set_dict=None)#
Return a plot of
self
.INPUT:
angle
– (default: \(\pi/4\)) the angle at which the arcs take off (if angle is negative, the arcs are drawn below the horizontal line)color
– (default:'black'
) color of the arcsbase_set_dict
– (optional) dictionary with keys elements ofbase_set()
and values as integer or float
EXAMPLES:
sage: p = SetPartition([[1,10,11],[2,3,7],[4,5,6],[8,9]]) sage: p.plot() # needs sage.plot sage.symbolic Graphics object consisting of 29 graphics primitives
sage: p = SetPartition([[1,3,4],[2,5]]) sage: print(p.plot().description()) # needs sage.plot sage.symbolic Point set defined by 1 point(s): [(0.0, 0.0)] Point set defined by 1 point(s): [(1.0, 0.0)] Point set defined by 1 point(s): [(2.0, 0.0)] Point set defined by 1 point(s): [(3.0, 0.0)] Point set defined by 1 point(s): [(4.0, 0.0)] Text '1' at the point (0.0,-0.1) Text '2' at the point (1.0,-0.1) Text '3' at the point (2.0,-0.1) Text '4' at the point (3.0,-0.1) Text '5' at the point (4.0,-0.1) Arc with center (1.0,-1.0) radii (1.41421356237...,1.41421356237...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) Arc with center (2.5,-0.5) radii (0.70710678118...,0.70710678118...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) Arc with center (2.5,-1.5) radii (2.1213203435...,2.1213203435...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) sage: p = SetPartition([['a','c'],['b','d'],['e']]) sage: print(p.plot().description()) # needs sage.plot sage.symbolic Point set defined by 1 point(s): [(0.0, 0.0)] Point set defined by 1 point(s): [(1.0, 0.0)] Point set defined by 1 point(s): [(2.0, 0.0)] Point set defined by 1 point(s): [(3.0, 0.0)] Point set defined by 1 point(s): [(4.0, 0.0)] Text 'a' at the point (0.0,-0.1) Text 'b' at the point (1.0,-0.1) Text 'c' at the point (2.0,-0.1) Text 'd' at the point (3.0,-0.1) Text 'e' at the point (4.0,-0.1) Arc with center (1.0,-1.0) radii (1.41421356237...,1.41421356237...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) Arc with center (2.0,-1.0) radii (1.41421356237...,1.41421356237...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) sage: p = SetPartition([['a','c'],['b','d'],['e']]) sage: print(p.plot(base_set_dict={'a':0,'b':1,'c':2, # needs sage.plot sage.symbolic ....: 'd':-2.3,'e':5.4}).description()) Point set defined by 1 point(s): [(-2.3, 0.0)] Point set defined by 1 point(s): [(0.0, 0.0)] Point set defined by 1 point(s): [(1.0, 0.0)] Point set defined by 1 point(s): [(2.0, 0.0)] Point set defined by 1 point(s): [(5.4, 0.0)] Text 'a' at the point (0.0,-0.1) Text 'b' at the point (1.0,-0.1) Text 'c' at the point (2.0,-0.1) Text 'd' at the point (-2.3,-0.1) Text 'e' at the point (5.4,-0.1) Arc with center (-0.6...,-1.65) radii (2.3334523779...,2.3334523779...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...) Arc with center (1.0,-1.0) radii (1.4142135623...,1.4142135623...) angle 0.0 inside the sector (0.785398163397...,2.35619449019...)
- refinements()#
Return a list of refinements of
self
.See also
coarsenings()
EXAMPLES:
sage: SetPartition([[1,3],[2,4]]).refinements() # needs sage.graphs sage.libs.flint [{{1, 3}, {2, 4}}, {{1, 3}, {2}, {4}}, {{1}, {2, 4}, {3}}, {{1}, {2}, {3}, {4}}] sage: SetPartition([[1],[2,4],[3]]).refinements() # needs sage.graphs sage.libs.flint [{{1}, {2, 4}, {3}}, {{1}, {2}, {3}, {4}}] sage: SetPartition([]).refinements() # needs sage.graphs sage.libs.flint [{}]
- restriction(I)#
Return the restriction of
self
to a subsetI
(which is given as a set or list or any other iterable).EXAMPLES:
sage: A = SetPartition([[1], [2,3]]) sage: A.restriction([1,2]) {{1}, {2}} sage: A.restriction([2,3]) {{2, 3}} sage: A.restriction([]) {} sage: A.restriction([4]) {}
- set_latex_options(**kwargs)#
Set the latex options for use in the
_latex_
functiontikz_scale
– (default: 1) scale for use with tikz packageplot
– (default:None
)None
returns the set notation,linear
returns a linear plot,cyclic
returns a cyclic plotcolor
– (default:'black'
) the arc colorsfill
– (default:False
) ifTrue
then fillscolor
, else you can pass in a color to alter the fill color - only works with cyclic plotshow_labels
– (default:True
) ifTrue
shows labels - only works with plotsradius
– (default:"1cm"
) radius of circle for cyclic plot - only works with cyclic plotangle
– (default: 0) angle for linear plot
EXAMPLES:
sage: SP = SetPartition([[1,6], [3,5,4]]) sage: SP.set_latex_options(tikz_scale=2,plot='linear',fill=True,color='blue',angle=45) sage: SP.set_latex_options(plot='cyclic') sage: SP.latex_options() {'angle': 45, 'color': 'blue', 'fill': True, 'plot': 'cyclic', 'radius': '1cm', 'show_labels': True, 'tikz_scale': 2}
- shape()#
Return the integer partition whose parts are the sizes of the sets in
self
.EXAMPLES:
sage: S = SetPartitions(5) sage: x = S([[1,2], [3,5,4]]) sage: x.shape() [3, 2] sage: y = S([[2], [3,1], [5,4]]) sage: y.shape() [2, 2, 1]
- shape_partition()#
Return the integer partition whose parts are the sizes of the sets in
self
.EXAMPLES:
sage: S = SetPartitions(5) sage: x = S([[1,2], [3,5,4]]) sage: x.shape() [3, 2] sage: y = S([[2], [3,1], [5,4]]) sage: y.shape() [2, 2, 1]
- size()#
Return the cardinality of the base set of
self
, which is the sum of the sizes of the parts ofself
.This is also known as the size (sometimes the weight) of a set partition.
EXAMPLES:
sage: SetPartition([[1], [2,3], [4]]).base_set_cardinality() 4 sage: SetPartition([[1,2,3,4]]).base_set_cardinality() 4
- standardization()#
Return the standardization of
self
.Given a set partition \(A = \{A_1, \ldots, A_n\}\) of an ordered set \(S\), the standardization of \(A\) is the set partition of \(\{1, 2, \ldots, |S|\}\) obtained by replacing the elements of the parts of \(A\) by the integers \(1, 2, \ldots, |S|\) in such a way that their relative order is preserved (i. e., the smallest element in the whole set partition is replaced by \(1\), the next-smallest by \(2\), and so on).
EXAMPLES:
sage: SetPartition([[4], [1, 3]]).standardization() {{1, 2}, {3}} sage: SetPartition([[4], [6, 3]]).standardization() {{1, 3}, {2}} sage: SetPartition([]).standardization() {} sage: SetPartition([('c','b'),('d','f'),('e','a')]).standardization() {{1, 5}, {2, 3}, {4, 6}}
- strict_coarsenings()#
Return all strict coarsenings of
self
.Strict coarsening is the binary relation on set partitions defined as the transitive-and-reflexive closure of the relation \(\prec\) defined as follows: For two set partitions \(A\) and \(B\), we have \(A \prec B\) if there exist parts \(A_i, A_j\) of \(A\) such that \(\max(A_i) < \min(A_j)\) and \(B = A \setminus \{A_i, A_j\} \cup \{ A_i \cup A_j \}\).
EXAMPLES:
sage: A = SetPartition([[1],[2,3],[4]]) sage: A.strict_coarsenings() [{{1}, {2, 3}, {4}}, {{1, 2, 3}, {4}}, {{1, 4}, {2, 3}}, {{1}, {2, 3, 4}}, {{1, 2, 3, 4}}] sage: SetPartition([[1],[2,4],[3]]).strict_coarsenings() [{{1}, {2, 4}, {3}}, {{1, 2, 4}, {3}}, {{1, 3}, {2, 4}}] sage: SetPartition([]).strict_coarsenings() [{}]
- to_partition()#
Return the integer partition whose parts are the sizes of the sets in
self
.EXAMPLES:
sage: S = SetPartitions(5) sage: x = S([[1,2], [3,5,4]]) sage: x.shape() [3, 2] sage: y = S([[2], [3,1], [5,4]]) sage: y.shape() [2, 2, 1]
- to_permutation()#
Convert a set partition of \(\{1,...,n\}\) to a permutation by considering the blocks of the partition as cycles.
The cycles are such that the number of excedences is maximised, that is, each cycle is of the form \((a_1,a_2, ...,a_k)\) with \(a_1<a_2<...<a_k\).
EXAMPLES:
sage: s = SetPartition([[1,3],[2,4]]) sage: s.to_permutation() [3, 4, 1, 2]
- to_restricted_growth_word(bijection='blocks')#
Convert a set partition of \(\{1,...,n\}\) to a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before.
INPUT:
bijection
(default:blocks
) – defines the map from set partitions to restricted growth functions. These are currently:blocks
:to_restricted_growth_word_blocks()
.intertwining
:to_restricted_growth_word_intertwining()
.
OUTPUT:
A restricted growth word.
EXAMPLES:
sage: P = SetPartition([[1,4],[2,8],[3,5,6,9],[7]]) sage: P.to_restricted_growth_word() [0, 1, 2, 0, 2, 2, 3, 1, 2] sage: P.to_restricted_growth_word("intertwining") [0, 1, 2, 2, 1, 0, 3, 3, 2] sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: P.to_restricted_growth_word() [0, 0, 1, 0, 2, 2, 0, 3, 1, 2, 2, 4, 2] sage: P.to_restricted_growth_word("intertwining") [0, 0, 1, 1, 2, 0, 1, 3, 3, 3, 0, 4, 1]
- to_restricted_growth_word_blocks()#
Convert a set partition of \(\{1,...,n\}\) to a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before.
The word is obtained by sorting the blocks by their minimal element and setting the letters at the positions of the elements in the \(i\)-th block to \(i\).
OUTPUT:
a restricted growth word.
EXAMPLES:
sage: P = SetPartition([[1,4],[2,8],[3,5,6,9],[7]]) sage: P.to_restricted_growth_word_blocks() [0, 1, 2, 0, 2, 2, 3, 1, 2]
- to_restricted_growth_word_intertwining()#
Convert a set partition of \(\{1,...,n\}\) to a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before.
The \(i\)-th letter of the word is the numbers of crossings of the arc (or half-arc) in the extended arc diagram ending at \(i\), with arcs (or half-arcs) beginning at a smaller element and ending at a larger element.
OUTPUT:
a restricted growth word.
EXAMPLES:
sage: P = SetPartition([[1,4],[2,8],[3,5,6,9],[7]]) sage: P.to_restricted_growth_word_intertwining() [0, 1, 2, 2, 1, 0, 3, 3, 2]
- to_rook_placement(bijection='arcs')#
Return a set of pairs defining a placement of non-attacking rooks on a triangular board.
The cells of the board corresponding to a set partition of \(\{1,...,n\}\) are the pairs \((i,j)\) with \(0 < i < j < n+1\).
INPUT:
bijection
(default:arcs
) – defines the bijection from set partitions to rook placements. These are currently:arcs
:arcs()
gamma
:to_rook_placement_gamma()
See also
EXAMPLES:
sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: P.to_rook_placement() [(1, 2), (2, 4), (4, 7), (3, 9), (5, 6), (6, 10), (10, 11), (11, 13)] sage: P.to_rook_placement("gamma") [(1, 4), (3, 5), (4, 6), (5, 8), (7, 11), (8, 9), (10, 12), (12, 13)] sage: P.to_rook_placement("rho") [(1, 2), (2, 6), (3, 4), (4, 10), (5, 9), (6, 7), (10, 11), (11, 13)] sage: P.to_rook_placement("psi") [(1, 2), (2, 6), (3, 4), (5, 9), (6, 7), (7, 10), (9, 11), (11, 13)]
- to_rook_placement_gamma()#
Return the rook diagram obtained by placing rooks according to Wachs and White’s bijection gamma.
Note that our index convention differs from the convention in [WW1991]: regarding the rook board as a lower-right triangular grid, we refer with \((i,j)\) to the cell in the \(i\)-th column from the right and the \(j\)-th row from the top.
The algorithm proceeds as follows: non-attacking rooks are placed beginning at the left column. If \(n+1-i\) is an opener, column \(i\) remains empty. Otherwise, we place a rook into column \(i\), such that the number of cells below the rook, which are not yet attacked by another rook, equals the index of the block to which \(n+1-i\) belongs.
OUTPUT:
A list of coordinates.
See also
EXAMPLES:
sage: P = SetPartition([[1,4],[2,8],[3,5,6,9],[7]]) sage: P.to_rook_placement_gamma() [(1, 3), (2, 7), (4, 5), (5, 6), (6, 9)]
Figure 5 in [WW1991]:
sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: r = P.to_rook_placement_gamma(); r [(1, 4), (3, 5), (4, 6), (5, 8), (7, 11), (8, 9), (10, 12), (12, 13)]
- to_rook_placement_psi()#
Return the rook diagram obtained by placing rooks according to Yip’s bijection psi.
OUTPUT:
A list of coordinates.
See also
EXAMPLES:
Example 36 (arXiv version: Example 4.5) in [Yip2018]:
sage: P = SetPartition([[1, 5], [2], [3, 8, 9], [4], [6, 7]]) sage: P.to_rook_placement_psi() [(1, 7), (3, 8), (4, 5), (7, 9)]
Note that the columns corresponding to the minimal elements of the blocks remain empty.
- to_rook_placement_rho()#
Return the rook diagram obtained by placing rooks according to Wachs and White’s bijection rho.
Note that our index convention differs from the convention in [WW1991]: regarding the rook board as a lower-right triangular grid, we refer with \((i,j)\) to the cell in the \(i\)-th column from the right and the \(j\)-th row from the top.
The algorithm proceeds as follows: non-attacking rooks are placed beginning at the top row. The columns corresponding to the closers of the set partition remain empty. Let \(rs_j\) be the number of closers which are larger than \(j\) and whose block is before the block of \(j\).
We then place a rook into row \(j\), such that the number of cells to the left of the rook, which are not yet attacked by another rook and are not in a column corresponding to a closer, equals \(rs_j\), unless there are not enough cells in this row available, in which case the row remains empty.
One can show that the precisely those rows which correspond to openers of the set partition remain empty.
OUTPUT:
A list of coordinates.
See also
EXAMPLES:
sage: P = SetPartition([[1,4],[2,8],[3,5,6,9],[7]]) sage: P.to_rook_placement_rho() [(1, 5), (2, 6), (3, 4), (5, 9), (6, 8)]
Figure 6 in [WW1991]:
sage: P = SetPartition([[1,2,4,7],[3,9],[5,6,10,11,13],[8],[12]]) sage: r = P.to_rook_placement_rho(); r [(1, 2), (2, 6), (3, 4), (4, 10), (5, 9), (6, 7), (10, 11), (11, 13)] sage: sorted(P.closers() + [i for i, _ in r]) == list(range(1,14)) True sage: sorted(P.openers() + [j for _, j in r]) == list(range(1,14)) True
- class sage.combinat.set_partition.SetPartitions#
Bases:
UniqueRepresentation
,Parent
An (unordered) partition of a set \(S\) is a set of pairwise disjoint nonempty subsets with union \(S\), and is represented by a sorted list of such subsets.
SetPartitions(s)
returns the class of all set partitions of the sets
, which can be given as a set or a string; if a string, each character is considered an element.SetPartitions(n)
, wheren
is an integer, returns the class of all set partitions of the set \(\{1, 2, \ldots, n\}\).You may specify a second argument \(k\). If \(k\) is an integer,
SetPartitions
returns the class of set partitions into \(k\) parts; if it is an integer partition,SetPartitions
returns the class of set partitions whose block sizes correspond to that integer partition.The Bell number \(B_n\), named in honor of Eric Temple Bell, is the number of different partitions of a set with \(n\) elements.
EXAMPLES:
sage: S = [1,2,3,4] sage: SetPartitions(S, 2) Set partitions of {1, 2, 3, 4} with 2 parts sage: SetPartitions([1,2,3,4], [3,1]).list() # needs sage.graphs sage.rings.finite_rings [{{1}, {2, 3, 4}}, {{1, 2, 3}, {4}}, {{1, 2, 4}, {3}}, {{1, 3, 4}, {2}}] sage: SetPartitions(7, [3,3,1]).cardinality() # needs sage.libs.flint 70
In strings, repeated letters are not considered distinct as of github issue #14140:
sage: SetPartitions('abcde').cardinality() # needs sage.libs.flint 52 sage: SetPartitions('aabcd').cardinality() # needs sage.libs.flint 15
REFERENCES:
- Element#
alias of
SetPartition
- from_arcs(arcs, n)#
Return the coarsest set partition of \(\{1,...,n\}\) such that any two elements connected by an arc are in the same block.
INPUT:
n
– an integer specifying the size of the set partition to be produced.arcs
– a list of pairs specifying which elements are in the same block.
EXAMPLES:
sage: SetPartitions().from_arcs([(2,3)], 5) {{1}, {2, 3}, {4}, {5}}
- from_restricted_growth_word(w, bijection='blocks')#
Convert a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before to a set partition of \(\{1,...,n\}\).
INPUT:
w
– a restricted growth word.bijection
(default:blocks
) – defines the map from restricted growth functions to set partitions. These are currently:blocks
: .intertwining
:from_restricted_growth_word_intertwining()
.
OUTPUT:
A set partition.
EXAMPLES:
sage: SetPartitions().from_restricted_growth_word([0, 1, 2, 0, 2, 2, 3, 1, 2]) {{1, 4}, {2, 8}, {3, 5, 6, 9}, {7}} sage: SetPartitions().from_restricted_growth_word([0, 0, 1, 0, 2, 2, 0, 3, 1, 2, 2, 4, 2]) {{1, 2, 4, 7}, {3, 9}, {5, 6, 10, 11, 13}, {8}, {12}} sage: SetPartitions().from_restricted_growth_word([0, 0, 1, 0, 2, 2, 0, 3, 1, 2, 2, 4, 2], "intertwining") {{1, 2, 6, 7, 9}, {3, 4}, {5, 10, 13}, {8, 11}, {12}}
- from_restricted_growth_word_blocks(w)#
Convert a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before to a set partition of \(\{1,...,n\}\).
w[i]
is the index of the block containingi+1
when sorting the blocks by their minimal element.INPUT:
w
– a restricted growth word.
OUTPUT:
A set partition.
EXAMPLES:
sage: SetPartitions().from_restricted_growth_word_blocks([0, 0, 1, 0, 2, 2, 0, 3, 1, 2, 2, 4, 2]) {{1, 2, 4, 7}, {3, 9}, {5, 6, 10, 11, 13}, {8}, {12}}
- from_restricted_growth_word_intertwining(w)#
Convert a word of length \(n\) with letters in the non-negative integers such that each letter is at most 1 larger than all the letters before to a set partition of \(\{1,...,n\}\).
The \(i\)-th letter of the word is the numbers of crossings of the arc (or half-arc) in the extended arc diagram ending at \(i\), with arcs (or half-arcs) beginning at a smaller element and ending at a larger element.
INPUT:
w
– a restricted growth word.
OUTPUT:
A set partition.
EXAMPLES:
sage: SetPartitions().from_restricted_growth_word_intertwining([0, 0, 1, 0, 2, 2, 0, 3, 1, 2, 2, 4, 2]) {{1, 2, 6, 7, 9}, {3, 4}, {5, 10, 13}, {8, 11}, {12}}
- from_rook_placement(rooks, bijection='arcs', n=None)#
Convert a rook placement of the triangular grid to a set partition of \(\{1,...,n\}\).
If
n
is not given, it is first checked whether it can be determined from the parent, otherwise it is the maximal occurring integer in the set of rooks.INPUT:
rooks
– a list of pairs \((i,j)\) satisfying \(0 < i < j < n+1\).bijection
(default:arcs
) – defines the map from rook placements to set partitions. These are currently:arcs
:from_arcs()
.gamma
:from_rook_placement_gamma()
.
n
– (optional) the size of the ground set.
See also
EXAMPLES:
sage: SetPartitions(9).from_rook_placement([[1,4],[2,8],[3,5],[5,6],[6,9]]) {{1, 4}, {2, 8}, {3, 5, 6, 9}, {7}} sage: SetPartitions(13).from_rook_placement([[12,13],[10,12],[8,9],[7,11],[5,8],[4,6],[3,5],[1,4]], "gamma") {{1, 2, 4, 7}, {3, 9}, {5, 6, 10, 11, 13}, {8}, {12}}
- from_rook_placement_gamma(rooks, n)#
Return the set partition of \(\{1,...,n\}\) corresponding to the given rook placement by applying Wachs and White’s bijection gamma.
Note that our index convention differs from the convention in [WW1991]: regarding the rook board as a lower-right triangular grid, we refer with \((i,j)\) to the cell in the \(i\)-th column from the right and the \(j\)-th row from the top.
INPUT:
n
– an integer specifying the size of the set partition to be produced.rooks
– a list of pairs \((i,j)\) such that \(0 < i < j < n+1\).
OUTPUT:
A set partition.
See also
EXAMPLES:
Figure 5 in [WW1991] concerns the following rook placement:
sage: r = [(1, 4), (3, 5), (4, 6), (5, 8), (7, 11), (8, 9), (10, 12), (12, 13)]
Note that the rook \((1, 4)\), translated into Wachs and White’s convention, is a rook in row 4 from the top and column 13 from the left. The corresponding set partition is:
sage: SetPartitions().from_rook_placement_gamma(r, 13) {{1, 2, 4, 7}, {3, 9}, {5, 6, 10, 11, 13}, {8}, {12}}
- from_rook_placement_psi(rooks, n)#
Return the set partition of \(\{1,...,n\}\) corresponding to the given rook placement by applying Yip’s bijection psi.
INPUT:
n
– an integer specifying the size of the set partition to be produced.rooks
– a list of pairs \((i,j)\) such that \(0 < i < j < n+1\).
OUTPUT:
A set partition.
See also
EXAMPLES:
Example 36 (arXiv version: Example 4.5) in [Yip2018] concerns the following rook placement:
sage: r = [(4,5), (1,7), (3, 8), (7,9)] sage: SetPartitions().from_rook_placement_psi(r, 9) {{1, 5}, {2}, {3, 8, 9}, {4}, {6, 7}}
- from_rook_placement_rho(rooks, n)#
Return the set partition of \(\{1,...,n\}\) corresponding to the given rook placement by applying Wachs and White’s bijection rho.
Note that our index convention differs from the convention in [WW1991]: regarding the rook board as a lower-right triangular grid, we refer with \((i,j)\) to the cell in the \(i\)-th column from the right and the \(j\)-th row from the top.
INPUT:
n
– an integer specifying the size of the set partition to be produced.rooks
– a list of pairs \((i,j)\) such that \(0 < i < j < n+1\).
OUTPUT:
A set partition.
See also
EXAMPLES:
Figure 5 in [WW1991] concerns the following rook placement:
sage: r = [(1, 2), (2, 6), (3, 4), (4, 10), (5, 9), (6, 7), (10, 11), (11, 13)]
Note that the rook \((1, 2)\), translated into Wachs and White’s convention, is a rook in row 2 from the top and column 13 from the left. The corresponding set partition is:
sage: SetPartitions().from_rook_placement_rho(r, 13) {{1, 2, 4, 7}, {3, 9}, {5, 6, 10, 11, 13}, {8}, {12}}
- is_less_than(s, t)#
Check if \(s < t\) in the refinement ordering on set partitions.
This means that \(s\) is a refinement of \(t\) and satisfies \(s \neq t\).
A set partition \(s\) is said to be a refinement of a set partition \(t\) of the same set if and only if each part of \(s\) is a subset of a part of \(t\).
EXAMPLES:
sage: S = SetPartitions(4) sage: s = S([[1,3],[2,4]]) sage: t = S([[1],[2],[3],[4]]) sage: S.is_less_than(t, s) True sage: S.is_less_than(s, t) False sage: S.is_less_than(s, s) False
- is_strict_refinement(s, t)#
Return
True
ifs
is a strict refinement oft
and satisfies \(s \neq t\).A set partition \(s\) is said to be a strict refinement of a set partition \(t\) of the same set if and only if one can obtain \(t\) from \(s\) by repeatedly combining pairs of parts whose convex hulls don’t intersect (i. e., whenever we are combining two parts, the maximum of each of them should be smaller than the minimum of the other).
EXAMPLES:
sage: S = SetPartitions(4) sage: s = S([[1],[2],[3],[4]]) sage: t = S([[1,3],[2,4]]) sage: u = S([[1,2,3,4]]) sage: S.is_strict_refinement(s, t) True sage: S.is_strict_refinement(t, u) False sage: A = SetPartition([[1,3],[2,4]]) sage: B = SetPartition([[1,2,3,4]]) sage: S.is_strict_refinement(s, A) True sage: S.is_strict_refinement(t, B) False
- lt(s, t)#
Check if \(s < t\) in the refinement ordering on set partitions.
This means that \(s\) is a refinement of \(t\) and satisfies \(s \neq t\).
A set partition \(s\) is said to be a refinement of a set partition \(t\) of the same set if and only if each part of \(s\) is a subset of a part of \(t\).
EXAMPLES:
sage: S = SetPartitions(4) sage: s = S([[1,3],[2,4]]) sage: t = S([[1],[2],[3],[4]]) sage: S.is_less_than(t, s) True sage: S.is_less_than(s, t) False sage: S.is_less_than(s, s) False
- class sage.combinat.set_partition.SetPartitions_all#
Bases:
SetPartitions
All set partitions.
- subset(size=None, **kwargs)#
Return the subset of set partitions of a given size and additional keyword arguments.
EXAMPLES:
sage: P = SetPartitions() sage: P.subset(4) Set partitions of {1, 2, 3, 4}
- class sage.combinat.set_partition.SetPartitions_set(s)#
Bases:
SetPartitions
Set partitions of a fixed set \(S\).
- base_set()#
Return the base set of
self
.EXAMPLES:
sage: SetPartitions(3).base_set() {1, 2, 3} sage: sorted(SetPartitions(["a", "b", "c"]).base_set()) ['a', 'b', 'c']
- base_set_cardinality()#
Return the cardinality of the base set of
self
.EXAMPLES:
sage: SetPartitions(3).base_set_cardinality() 3
- cardinality()#
Return the number of set partitions of the set \(S\).
The cardinality is given by the \(n\)-th Bell number where \(n\) is the number of elements in the set \(S\).
EXAMPLES:
sage: # needs sage.libs.flint sage: SetPartitions([1,2,3,4]).cardinality() 15 sage: SetPartitions(3).cardinality() 5 sage: SetPartitions(3,2).cardinality() 3 sage: SetPartitions([]).cardinality() 1
- random_element()#
Return a random set partition.
This is a very naive implementation of Knuths outline in F3B, 7.2.1.5.
EXAMPLES:
sage: S = SetPartitions(10) sage: s = S.random_element() # needs sage.symbolic sage: s.parent() is S # needs sage.symbolic True sage: assert s in S, s # needs sage.symbolic sage: S = SetPartitions(["a", "b", "c"]) sage: s = S.random_element() # needs sage.symbolic sage: s.parent() is S # needs sage.symbolic True sage: assert s in S, s # needs sage.symbolic
- class sage.combinat.set_partition.SetPartitions_setn(s, k)#
Bases:
SetPartitions_set
Set partitions with a given number of blocks.
- cardinality()#
The Stirling number of the second kind is the number of partitions of a set of size \(n\) into \(k\) blocks.
EXAMPLES:
sage: SetPartitions(5, 3).cardinality() 25 sage: stirling_number2(5,3) 25
- number_of_blocks()#
Return the number of blocks of the set partitions in
self
.EXAMPLES:
sage: SetPartitions(5, 3).number_of_blocks() 3
- random_element()#
Return a random set partition of
self
.See https://mathoverflow.net/questions/141999.
EXAMPLES:
sage: S = SetPartitions(10, 4) sage: s = S.random_element() sage: s.parent() is S True sage: assert s in S, s sage: S = SetPartitions(["a", "b", "c"], 2) sage: s = S.random_element() sage: s.parent() is S True sage: assert s in S, s
- class sage.combinat.set_partition.SetPartitions_setparts(s, parts)#
Bases:
SetPartitions_set
Set partitions with fixed partition sizes corresponding to an integer partition \(\lambda\).
- cardinality()#
Return the cardinality of
self
.This algorithm counts for each block of the partition the number of ways to fill it using values from the set. Then, for each distinct value \(v\) of block size, we divide the result by the number of ways to arrange the blocks of size \(v\) in the set partition.
For example, if we want to count the number of set partitions of size 13 having [3,3,3,2,2] as underlying partition we compute the number of ways to fill each block of the partition, which is \(\binom{13}{3} \binom{10}{3} \binom{7}{3} \binom{4}{2}\binom{2}{2}\) and as we have three blocks of size \(3\) and two blocks of size \(2\), we divide the result by \(3!2!\) which gives us \(600600\).
EXAMPLES:
sage: SetPartitions(3, [2,1]).cardinality() 3 sage: SetPartitions(13, Partition([3,3,3,2,2])).cardinality() 600600
- random_element()#
Return a random set partition of
self
.ALGORITHM:
Based on the cardinality method. For each block size \(k_i\), we choose a uniformly random subset \(X_i \subseteq S_i\) of size \(k_i\) of the elements \(S_i\) that have not yet been selected. Thus, we define \(S_{i+1} = S_i \setminus X_i\) with \(S_i = S\) being the defining set. This is not yet proven to be uniformly distributed, but numerical tests show this is likely uniform.
EXAMPLES:
sage: S = SetPartitions(10, [4,3,2,1]) sage: s = S.random_element() sage: s.parent() is S True sage: assert s in S, s sage: S = SetPartitions(["a", "b", "c", "d"], [2,2]) sage: s = S.random_element() sage: s.parent() is S True sage: assert s in S, s
- shape()#
Return the partition of block sizes of the set partitions in
self
.EXAMPLES:
sage: SetPartitions(5, [2,2,1]).shape() [2, 2, 1]
- sage.combinat.set_partition.cyclic_permutations_of_set_partition(set_part)#
Return all combinations of cyclic permutations of each cell of the set partition.
AUTHORS:
Robert L. Miller
EXAMPLES:
sage: from sage.combinat.set_partition import cyclic_permutations_of_set_partition sage: cyclic_permutations_of_set_partition([[1,2,3,4],[5,6,7]]) [[[1, 2, 3, 4], [5, 6, 7]], [[1, 2, 4, 3], [5, 6, 7]], [[1, 3, 2, 4], [5, 6, 7]], [[1, 3, 4, 2], [5, 6, 7]], [[1, 4, 2, 3], [5, 6, 7]], [[1, 4, 3, 2], [5, 6, 7]], [[1, 2, 3, 4], [5, 7, 6]], [[1, 2, 4, 3], [5, 7, 6]], [[1, 3, 2, 4], [5, 7, 6]], [[1, 3, 4, 2], [5, 7, 6]], [[1, 4, 2, 3], [5, 7, 6]], [[1, 4, 3, 2], [5, 7, 6]]]
- sage.combinat.set_partition.cyclic_permutations_of_set_partition_iterator(set_part)#
Iterates over all combinations of cyclic permutations of each cell of the set partition.
AUTHORS:
Robert L. Miller
EXAMPLES:
sage: from sage.combinat.set_partition import cyclic_permutations_of_set_partition_iterator sage: list(cyclic_permutations_of_set_partition_iterator([[1,2,3,4],[5,6,7]])) [[[1, 2, 3, 4], [5, 6, 7]], [[1, 2, 4, 3], [5, 6, 7]], [[1, 3, 2, 4], [5, 6, 7]], [[1, 3, 4, 2], [5, 6, 7]], [[1, 4, 2, 3], [5, 6, 7]], [[1, 4, 3, 2], [5, 6, 7]], [[1, 2, 3, 4], [5, 7, 6]], [[1, 2, 4, 3], [5, 7, 6]], [[1, 3, 2, 4], [5, 7, 6]], [[1, 3, 4, 2], [5, 7, 6]], [[1, 4, 2, 3], [5, 7, 6]], [[1, 4, 3, 2], [5, 7, 6]]]