# Finite posets¶

Here is some terminology used in this file:

• An order filter (or upper set) of a poset $$P$$ is a subset $$S$$ of $$P$$ such that if $$x \leq y$$ and $$x\in S$$ then $$y\in S$$.

• An order ideal (or lower set) of a poset $$P$$ is a subset $$S$$ of $$P$$ such that if $$x \leq y$$ and $$y\in S$$ then $$x\in S$$.

class sage.categories.finite_posets.FinitePosets(base_category)

The category of finite posets i.e. finite sets with a partial order structure.

EXAMPLES:

sage: FinitePosets()
Category of finite posets
sage: FinitePosets().super_categories()
[Category of posets, Category of finite sets]
sage: FinitePosets().example()
NotImplemented


class ParentMethods

Bases: object

antichains()

Return all antichains of self.

EXAMPLES:

sage: A = posets.PentagonPoset().antichains(); A
Set of antichains of Finite lattice containing 5 elements
sage: list(A)
[[], [0], [1], [1, 2], [1, 3], [2], [3], [4]]

birational_free_labelling(linear_extension=None, prefix='x', base_field=None, reduced=False, addvars=None, labels=None, min_label=None, max_label=None)

Return the birational free labelling of self.

Let us hold back defining this, and introduce birational toggles and birational rowmotion first. These notions have been introduced in [EP2013] as generalizations of the notions of toggles (order_ideal_toggle()) and rowmotion on order ideals of a finite poset. They have been studied further in [GR2013].

Let $$\mathbf{K}$$ be a field, and $$P$$ be a finite poset. Let $$\widehat{P}$$ denote the poset obtained from $$P$$ by adding a new element $$1$$ which is greater than all existing elements of $$P$$, and a new element $$0$$ which is smaller than all existing elements of $$P$$ and $$1$$. Now, a $$\mathbf{K}$$-labelling of $$P$$ will mean any function from $$\widehat{P}$$ to $$\mathbf{K}$$. The image of an element $$v$$ of $$\widehat{P}$$ under this labelling will be called the label of this labelling at $$v$$. The set of all $$\mathbf{K}$$-labellings of $$P$$ is clearly $$\mathbf{K}^{\widehat{P}}$$.

For any $$v \in P$$, we now define a rational map $$T_v : \mathbf{K}^{\widehat{P}} \dashrightarrow \mathbf{K}^{\widehat{P}}$$ as follows: For every $$f \in \mathbf{K}^{\widehat{P}}$$, the image $$T_v f$$ should send every element $$u \in \widehat{P}$$ distinct from $$v$$ to $$f(u)$$ (so the labels at all $$u \neq v$$ don’t change), while $$v$$ is sent to

$\frac{1}{f(v)} \cdot \frac{\sum_{u \lessdot v} f(u)} {\sum_{u \gtrdot v} \frac{1}{f(u)}}$

(both sums are over all $$u \in \widehat{P}$$ satisfying the respectively given conditions). Here, $$\lessdot$$ and $$\gtrdot$$ mean (respectively) “covered by” and “covers”, interpreted with respect to the poset $$\widehat{P}$$. This rational map $$T_v$$ is an involution and is called the (birational) $$v$$-toggle; see birational_toggle() for its implementation.

Now, birational rowmotion is defined as the composition $$T_{v_1} \circ T_{v_2} \circ \cdots \circ T_{v_n}$$, where $$(v_1, v_2, \ldots, v_n)$$ is a linear extension of $$P$$ (written as a linear ordering of the elements of $$P$$). This is a rational map $$\mathbf{K}^{\widehat{P}} \dashrightarrow \mathbf{K}^{\widehat{P}}$$ which does not depend on the choice of the linear extension; it is denoted by $$R$$. See birational_rowmotion() for its implementation.

The definitions of birational toggles and birational rowmotion extend to the case of $$\mathbf{K}$$ being any semifield rather than necessarily a field (although it becomes less clear what constitutes a rational map in this generality). The most useful case is that of the tropical semiring, in which case birational rowmotion relates to classical constructions such as promotion of rectangular semistandard Young tableaux (page 5 of [EP2013b] and future work, via the related notion of birational promotion) and rowmotion on order ideals of the poset ([EP2013]).

The birational free labelling is a special labelling defined for every finite poset $$P$$ and every linear extension $$(v_1, v_2, \ldots, v_n)$$ of $$P$$. It is given by sending every element $$v_i$$ in $$P$$ to $$x_i$$, sending the element $$0$$ of $$\widehat{P}$$ to $$a$$, and sending the element $$1$$ of $$\widehat{P}$$ to $$b$$, where the ground field $$\mathbf{K}$$ is the field of rational functions in $$n+2$$ indeterminates $$a, x_1, x_2, \ldots, x_n, b$$ over $$\mathbb Q$$.

In Sage, a labelling $$f$$ of a poset $$P$$ is encoded as a $$4$$-tuple $$(\mathbf{K}, d, u, v)$$, where $$\mathbf{K}$$ is the ground field of the labelling (i. e., its target), $$d$$ is the dictionary containing the values of $$f$$ at the elements of $$P$$ (the keys being the respective elements of $$P$$), $$u$$ is the label of $$f$$ at $$0$$, and $$v$$ is the label of $$f$$ at $$1$$.

Warning

The dictionary $$d$$ is labelled by the elements of $$P$$. If $$P$$ is a poset with facade option set to False, these might not be what they seem to be! (For instance, if P == Poset({1: [2, 3]}, facade=False), then the value of $$d$$ at $$1$$ has to be accessed by d[P(1)], not by d[1].)

Warning

Dictionaries are mutable. They do compare correctly, but are not hashable and need to be cloned to avoid spooky action at a distance. Be careful!

INPUT:

• linear_extension – (default: the default linear extension of self) a linear extension of self (as a linear extension or as a list), or more generally a list of all elements of all elements of self each occurring exactly once

• prefix – (default: 'x') the prefix to name the indeterminates corresponding to the elements of self in the labelling (so, setting it to 'frog' will result in these indeterminates being called frog1, frog2, ..., frogn rather than x1, x2, ..., xn).

• base_field – (default: QQ) the base field to be used instead of $$\QQ$$ to define the rational function field over; this is not going to be the base field of the labelling, because the latter will have indeterminates adjoined!

• reduced – (default: False) if set to True, the result will be the reduced birational free labelling, which differs from the regular one by having $$0$$ and $$1$$ both sent to $$1$$ instead of $$a$$ and $$b$$ (the indeterminates $$a$$ and $$b$$ then also won’t appear in the ground field)

• addvars – (default: '') a string containing names of extra variables to be adjoined to the ground field (these don’t have an effect on the labels)

• labels – (default: 'x') Either a function that takes an element of the poset and returns a name for the indeterminate corresponding to that element, or a string containing a comma-separated list of indeterminates that will be assigned to elements in the order of linear_extension. If the list contains more indeterminates than needed, the excess will be ignored. If it contains too few, then the needed indeterminates will be constructed from prefix.

• min_label – (default: 'a') a string to be used as the label for the element $$0$$ of $$\widehat{P}$$

• max_label – (default: 'b') a string to be used as the label for the element $$1$$ of $$\widehat{P}$$

OUTPUT:

The birational free labelling of the poset self and the linear extension linear_extension. Or, if reduced is set to True, the reduced birational free labelling.

EXAMPLES:

We construct the birational free labelling on a simple poset:

sage: P = Poset({1: [2, 3]})
sage: l = P.birational_free_labelling(); l
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(l[1].items())
[(1, x1), (2, x2), (3, x3)]

sage: l = P.birational_free_labelling(linear_extension=[1, 3, 2]); l
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(l[1].items())
[(1, x1), (2, x3), (3, x2)]

sage: l = P.birational_free_labelling(linear_extension=[1, 3, 2], reduced=True, addvars="spam, eggs"); l
(Fraction Field of Multivariate Polynomial Ring in x1, x2, x3, spam, eggs over Rational Field,
{...},
1,
1)
sage: sorted(l[1].items())
[(1, x1), (2, x3), (3, x2)]

sage: l = P.birational_free_labelling(linear_extension=[1, 3, 2], prefix="wut", reduced=True, addvars="spam, eggs"); l
(Fraction Field of Multivariate Polynomial Ring in wut1, wut2, wut3, spam, eggs over Rational Field,
{...},
1,
1)
sage: sorted(l[1].items())
[(1, wut1), (2, wut3), (3, wut2)]

sage: l = P.birational_free_labelling(linear_extension=[1, 3, 2], reduced=False, addvars="spam, eggs"); l
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b, spam, eggs over Rational Field,
{...},
a,
b)
sage: sorted(l[1].items())
[(1, x1), (2, x3), (3, x2)]
sage: l[1][2]
x3


Illustrating labelling with a function:

sage: P = posets.ChainPoset(2).product(posets.ChainPoset(2))
sage: l = P.birational_free_labelling(labels=lambda e : 'x_' + str(e[0]) + str(e[1]))
sage: sorted(l[1].items())
[((0, 0), x_00), ((0, 1), x_01), ((1, 0), x_10), ((1, 1), x_11)]
sage: l[2]
a


The same, but with min_label and max_label provided:

sage: P = posets.ChainPoset(2).product(posets.ChainPoset(2))
sage: l = P.birational_free_labelling(labels=lambda e : 'x_' + str(e[0]) + str(e[1]), min_label="lambda", max_label="mu")
sage: sorted(l[1].items())
[((0, 0), x_00), ((0, 1), x_01), ((1, 0), x_10), ((1, 1), x_11)]
sage: l[2]
lambda
sage: l[3]
mu


Illustrating labelling with a comma separated list of labels:

sage: l = P.birational_free_labelling(labels='w,x,y,z')
sage: sorted(l[1].items())
[((0, 0), w), ((0, 1), x), ((1, 0), y), ((1, 1), z)]
sage: l = P.birational_free_labelling(labels='w,x,y,z,m')
sage: sorted(l[1].items())
[((0, 0), w), ((0, 1), x), ((1, 0), y), ((1, 1), z)]
sage: l = P.birational_free_labelling(labels='w')
sage: sorted(l[1].items())
[((0, 0), w), ((0, 1), x1), ((1, 0), x2), ((1, 1), x3)]


sage: P = Poset({1: [2, 3]}, facade=False)
sage: l = P.birational_free_labelling(linear_extension=[1, 3, 2], reduced=False, addvars="spam, eggs"); l
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b, spam, eggs over Rational Field,
{...},
a,
b)
sage: l[1][2]
Traceback (most recent call last):
...
KeyError: 2
sage: l[1][P(2)]
x3


Another poset:

sage: P = posets.SSTPoset([2,1])
sage: lext = sorted(P)
sage: l
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, x4, x5, x6, x7, x8, b, ohai over Rational Field,
{...},
a,
b)
sage: sorted(l[1].items())
[([[1, 1], [2]], x1), ([[1, 1], [3]], x2), ([[1, 2], [2]], x3), ([[1, 2], [3]], x4),
([[1, 3], [2]], x5), ([[1, 3], [3]], x6), ([[2, 2], [3]], x7), ([[2, 3], [3]], x8)]


See birational_rowmotion(), birational_toggle() and birational_toggles() for more substantial examples of what one can do with the birational free labelling.

birational_rowmotion(labelling)

Return the result of applying birational rowmotion to the $$\mathbf{K}$$-labelling labelling of the poset self.

See the documentation of birational_free_labelling() for a definition of birational rowmotion and $$\mathbf{K}$$-labellings and for an explanation of how $$\mathbf{K}$$-labellings are to be encoded to be understood by Sage. This implementation allows $$\mathbf{K}$$ to be a semifield, not just a field. Birational rowmotion is only a rational map, so an exception (most likely, ZeroDivisionError) will be thrown if the denominator is zero.

INPUT:

OUTPUT:

The image of the $$\mathbf{K}$$-labelling $$f$$ under birational rowmotion.

EXAMPLES:

sage: P = Poset({1: [2, 3], 2: [4], 3: [4]})
sage: lex = [1, 2, 3, 4]
sage: t = P.birational_free_labelling(linear_extension=lex); t
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, x4, b over Rational Field,
{...},
a,
b)
sage: sorted(t[1].items())
[(1, x1), (2, x2), (3, x3), (4, x4)]
sage: t = P.birational_rowmotion(t); t
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, x4, b over Rational Field,
{...},
a,
b)
sage: sorted(t[1].items())
[(1, a*b/x4), (2, (x1*x2*b + x1*x3*b)/(x2*x4)),
(3, (x1*x2*b + x1*x3*b)/(x3*x4)), (4, (x2*b + x3*b)/x4)]


A result of [GR2013] states that applying birational rowmotion $$n+m$$ times to a $$\mathbf{K}$$-labelling $$f$$ of the poset $$[n] \times [m]$$ gives back $$f$$. Let us check this:

sage: def test_rectangle_periodicity(n, m, k):
....:     P = posets.ChainPoset(n).product(posets.ChainPoset(m))
....:     t0 = P.birational_free_labelling(P)
....:     t = t0
....:     for i in range(k):
....:         t = P.birational_rowmotion(t)
....:     return t == t0
sage: test_rectangle_periodicity(2, 2, 4)
True
sage: test_rectangle_periodicity(2, 2, 2)
False
sage: test_rectangle_periodicity(2, 3, 5)  # long time
True


While computations with the birational free labelling quickly run out of memory due to the complexity of the rational functions involved, it is computationally cheap to check properties of birational rowmotion on examples in the tropical semiring:

sage: def test_rectangle_periodicity_tropical(n, m, k):
....:     P = posets.ChainPoset(n).product(posets.ChainPoset(m))
....:     TT = TropicalSemiring(ZZ)
....:     t0 = (TT, {v: TT(floor(random()*100)) for v in P}, TT(0), TT(124))
....:     t = t0
....:     for i in range(k):
....:         t = P.birational_rowmotion(t)
....:     return t == t0
sage: test_rectangle_periodicity_tropical(7, 6, 13)
True


Tropicalization is also what relates birational rowmotion to classical rowmotion on order ideals. In fact, if $$T$$ denotes the tropical semiring of $$\ZZ$$ and $$P$$ is a finite poset, then we can define an embedding $$\phi$$ from the set $$J(P)$$ of all order ideals of $$P$$ into the set $$T^{\widehat{P}}$$ of all $$T$$-labellings of $$P$$ by sending every $$I \in J(P)$$ to the indicator function of $$I$$ extended by the value $$1$$ at the element $$0$$ and the value $$0$$ at the element $$1$$. This map $$\phi$$ has the property that $$R \circ \phi = \phi \circ r$$, where $$R$$ denotes birational rowmotion, and $$r$$ denotes classical rowmotion on $$J(P)$$. An example:

sage: P = posets.IntegerPartitions(5)
sage: TT = TropicalSemiring(ZZ)
sage: def indicator_labelling(I):
....:     # send order ideal I to a T-labelling of P.
....:     dct = {v: TT(v in I) for v in P}
....:     return (TT, dct, TT(1), TT(0))
sage: all(indicator_labelling(P.rowmotion(I))
....:     == P.birational_rowmotion(indicator_labelling(I))
True

birational_toggle(v, labelling)

Return the result of applying the birational $$v$$-toggle $$T_v$$ to the $$\mathbf{K}$$-labelling labelling of the poset self.

See the documentation of birational_free_labelling() for a definition of this toggle and of $$\mathbf{K}$$-labellings as well as an explanation of how $$\mathbf{K}$$-labellings are to be encoded to be understood by Sage. This implementation allows $$\mathbf{K}$$ to be a semifield, not just a field. The birational $$v$$-toggle is only a rational map, so an exception (most likely, ZeroDivisionError) will be thrown if the denominator is zero.

INPUT:

• v – an element of self (must have self as parent if self is a facade=False poset)

• labelling – a $$\mathbf{K}$$-labelling of self in the sense as defined in the documentation of birational_free_labelling()

OUTPUT:

The $$\mathbf{K}$$-labelling $$T_v f$$ of self, where $$f$$ is labelling.

EXAMPLES:

Let us start with the birational free labelling of the “V”-poset (the three-element poset with Hasse diagram looking like a “V”):

sage: V = Poset({1: [2, 3]})
sage: s = V.birational_free_labelling(); s
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(s[1].items())
[(1, x1), (2, x2), (3, x3)]


The image of $$s$$ under the $$1$$-toggle $$T_1$$ is:

sage: s1 = V.birational_toggle(1, s); s1
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(s1[1].items())
[(1, a*x2*x3/(x1*x2 + x1*x3)), (2, x2), (3, x3)]


Now let us apply the $$2$$-toggle $$T_2$$ (to the old s):

sage: s2 = V.birational_toggle(2, s); s2
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(s2[1].items())
[(1, x1), (2, x1*b/x2), (3, x3)]


On the other hand, we can also apply $$T_2$$ to the image of $$s$$ under $$T_1$$:

sage: s12 = V.birational_toggle(2, s1); s12
(Fraction Field of Multivariate Polynomial Ring in a, x1, x2, x3, b over Rational Field,
{...},
a,
b)
sage: sorted(s12[1].items())
[(1, a*x2*x3/(x1*x2 + x1*x3)), (2, a*x3*b/(x1*x2 + x1*x3)), (3, x3)]


Each toggle is an involution:

sage: all( V.birational_toggle(i, V.birational_toggle(i, s)) == s
....:      for i in V )
True


sage: t = (QQ, {1: 3, 2: 6, 3: 7}, 2, 10)
sage: t1 = V.birational_toggle(1, t); t1
(Rational Field, {...}, 2, 10)
sage: sorted(t1[1].items())
[(1, 28/13), (2, 6), (3, 7)]
sage: t13 = V.birational_toggle(3, t1); t13
(Rational Field, {...}, 2, 10)
sage: sorted(t13[1].items())
[(1, 28/13), (2, 6), (3, 40/13)]


However, labellings have to be sufficiently generic, lest denominators vanish:

sage: t = (QQ, {1: 3, 2: 5, 3: -5}, 1, 15)
sage: t1 = V.birational_toggle(1, t)
Traceback (most recent call last):
...
ZeroDivisionError: rational division by zero


We don’t get into zero-division issues in the tropical semiring (unless the zero of the tropical semiring appears in the labelling):

sage: TT = TropicalSemiring(QQ)
sage: t = (TT, {1: TT(2), 2: TT(4), 3: TT(1)}, TT(6), TT(0))
sage: t1 = V.birational_toggle(1, t); t1
(Tropical semiring over Rational Field, {...}, 6, 0)
sage: sorted(t1[1].items())
[(1, 8), (2, 4), (3, 1)]
sage: t12 = V.birational_toggle(2, t1); t12
(Tropical semiring over Rational Field, {...}, 6, 0)
sage: sorted(t12[1].items())
[(1, 8), (2, 4), (3, 1)]
sage: t123 = V.birational_toggle(3, t12); t123
(Tropical semiring over Rational Field, {...}, 6, 0)
sage: sorted(t123[1].items())
[(1, 8), (2, 4), (3, 7)]


We turn to more interesting posets. Here is the $$6$$-element poset arising from the weak order on $$S_3$$:

sage: P = posets.SymmetricGroupWeakOrderPoset(3)
sage: sorted(list(P))
['123', '132', '213', '231', '312', '321']
sage: t = (TT, {'123': TT(4), '132': TT(2), '213': TT(3), '231': TT(1), '321': TT(1), '312': TT(2)}, TT(7), TT(1))
sage: t1 = P.birational_toggle('123', t); t1
(Tropical semiring over Rational Field, {...}, 7, 1)
sage: sorted(t1[1].items())
[('123', 6), ('132', 2), ('213', 3), ('231', 1), ('312', 2), ('321', 1)]
sage: t13 = P.birational_toggle('213', t1); t13
(Tropical semiring over Rational Field, {...}, 7, 1)
sage: sorted(t13[1].items())
[('123', 6), ('132', 2), ('213', 4), ('231', 1), ('312', 2), ('321', 1)]


Let us verify on this example some basic properties of toggles. First of all, again let us check that $$T_v$$ is an involution for every $$v$$:

sage: all( P.birational_toggle(v, P.birational_toggle(v, t)) == t
....:      for v in P )
True


Furthermore, two toggles $$T_v$$ and $$T_w$$ commute unless one of $$v$$ or $$w$$ covers the other:

sage: all( P.covers(v, w) or P.covers(w, v)
....:      or P.birational_toggle(v, P.birational_toggle(w, t))
....:         == P.birational_toggle(w, P.birational_toggle(v, t))
....:      for v in P for w in P )
True

birational_toggles(vs, labelling)

Return the result of applying a sequence of birational toggles (specified by vs) to the $$\mathbf{K}$$-labelling labelling of the poset self.

See the documentation of birational_free_labelling() for a definition of birational toggles and $$\mathbf{K}$$-labellings and for an explanation of how $$\mathbf{K}$$-labellings are to be encoded to be understood by Sage. This implementation allows $$\mathbf{K}$$ to be a semifield, not just a field. The birational $$v$$-toggle is only a rational map, so an exception (most likely, ZeroDivisionError) will be thrown if the denominator is zero.

INPUT:

• vs – an iterable comprising elements of self (which must have self as parent if self is a facade=False poset)

• labelling – a $$\mathbf{K}$$-labelling of self in the sense as defined in the documentation of birational_free_labelling()

OUTPUT:

The $$\mathbf{K}$$-labelling $$T_{v_n} T_{v_{n-1}} \cdots T_{v_1} f$$ of self, where $$f$$ is labelling and $$(v_1, v_2, \ldots, v_n)$$ is vs (written as list).

EXAMPLES:

sage: P = posets.SymmetricGroupBruhatOrderPoset(3)
sage: sorted(list(P))
['123', '132', '213', '231', '312', '321']
sage: TT = TropicalSemiring(ZZ)
sage: t = (TT, {'123': TT(4), '132': TT(2), '213': TT(3), '231': TT(1), '321': TT(1), '312': TT(2)}, TT(7), TT(1))
sage: tA = P.birational_toggles(['123', '231', '312'], t); tA
(Tropical semiring over Integer Ring, {...}, 7, 1)
sage: sorted(tA[1].items())
[('123', 6), ('132', 2), ('213', 3), ('231', 2), ('312', 1), ('321', 1)]
sage: tAB = P.birational_toggles(['132', '213', '321'], tA); tAB
(Tropical semiring over Integer Ring, {...}, 7, 1)
sage: sorted(tAB[1].items())
[('123', 6), ('132', 6), ('213', 5), ('231', 2), ('312', 1), ('321', 1)]

sage: P = Poset({1: [2, 3], 2: [4], 3: [4]})
sage: Qx = PolynomialRing(QQ, 'x').fraction_field()
sage: x = Qx.gen()
sage: t = (Qx, {1: 1, 2: x, 3: (x+1)/x, 4: x^2}, 1, 1)
sage: t1 = P.birational_toggles((i for i in range(1, 5)), t); t1
(Fraction Field of Univariate Polynomial Ring in x over Rational Field,
{...},
1,
1)
sage: sorted(t1[1].items())
[(1, (x^2 + x)/(x^2 + x + 1)), (2, (x^3 + x^2)/(x^2 + x + 1)), (3, x^4/(x^2 + x + 1)), (4, 1)]
sage: t2 = P.birational_toggles(reversed(range(1, 5)), t)
sage: sorted(t2[1].items())
[(1, 1/x^2), (2, (x^2 + x + 1)/x^4), (3, (x^2 + x + 1)/(x^3 + x^2)), (4, (x^2 + x + 1)/x^3)]


Facade set to False works:

sage: P = Poset({'x': ['y', 'w'], 'y': ['z'], 'w': ['z']}, facade=False)
sage: lex = ['x', 'y', 'w', 'z']
sage: t = P.birational_free_labelling(linear_extension=lex)
sage: sorted(P.birational_toggles([P('x'), P('y')], t)[1].items())
[(x, a*x2*x3/(x1*x2 + x1*x3)), (y, a*x3*x4/(x1*x2 + x1*x3)), (w, x3), (z, x4)]

directed_subsets(direction)

Return the order filters (resp. order ideals) of self, as lists.

If direction is ‘up’, returns the order filters (upper sets).

If direction is ‘down’, returns the order ideals (lower sets).

INPUT:

• direction – ‘up’ or ‘down’

EXAMPLES:

sage: P = Poset((divisors(12), attrcall("divides")), facade=True)
sage: A = P.directed_subsets('up')
sage: sorted(list(A))
[[], [1, 2, 4, 3, 6, 12], [2, 4, 3, 6, 12], [2, 4, 6, 12], [3, 6, 12], [4, 3, 6, 12], [4, 6, 12], [4, 12], [6, 12], [12]]

is_lattice()

Return whether the poset is a lattice.

A poset is a lattice if all pairs of elements have both a least upper bound (“join”) and a greatest lower bound (“meet”) in the poset.

EXAMPLES:

sage: P = Poset([[1, 3, 2], [4], [4, 5, 6], [6], [7], [7], [7], []])
sage: P.is_lattice()
True

sage: P = Poset([[1, 2], [3], [3], []])
sage: P.is_lattice()
True

sage: P = Poset({0: [2, 3], 1: [2, 3]})
sage: P.is_lattice()
False

sage: P = Poset({1: [2, 3, 4], 2: [5, 6], 3: [5, 7], 4: [6, 7], 5: [8, 9],
....:            6: [8, 10], 7: [9, 10], 8: [11], 9: [11], 10: [11]})
sage: P.is_lattice()
False

is_poset_isomorphism(f, codomain)

Return whether $$f$$ is an isomorphism of posets from self to codomain.

INPUT:

• f – a function from self to codomain

• codomain – a poset

EXAMPLES:

We build the poset $$D$$ of divisors of 30, and check that it is isomorphic to the boolean lattice $$B$$ of the subsets of $$\{2,3,5\}$$ ordered by inclusion, via the reverse function $$f: B \to D, b \mapsto \prod_{x\in b} x$$:

sage: D = Poset((divisors(30), attrcall("divides")))
sage: B = Poset(([frozenset(s) for s in Subsets([2,3,5])], attrcall("issubset")))
sage: def f(b): return D(prod(b))
sage: B.is_poset_isomorphism(f, D)
True


On the other hand, $$f$$ is not an isomorphism to the chain of divisors of 30, ordered by usual comparison:

sage: P = Poset((divisors(30), operator.le))
sage: def f(b): return P(prod(b))
sage: B.is_poset_isomorphism(f, P)
False


A non surjective case:

sage: B = Poset(([frozenset(s) for s in Subsets([2,3])], attrcall("issubset")))
sage: def f(b): return D(prod(b))
sage: B.is_poset_isomorphism(f, D)
False


A non injective case:

sage: B = Poset(([frozenset(s) for s in Subsets([2,3,5,6])], attrcall("issubset")))
sage: def f(b): return D(gcd(prod(b), 30))
sage: B.is_poset_isomorphism(f, D)
False


Note

since D and B are not facade posets, f is responsible for the conversions between integers and subsets to elements of D and B and back.

is_poset_morphism(f, codomain)

Return whether $$f$$ is a morphism of posets from self to codomain, that is

$x\leq y \Longrightarrow f(x) \leq f(y)$

for all $$x$$ and $$y$$ in self.

INPUT:

• f – a function from self to codomain

• codomain – a poset

EXAMPLES:

We build the boolean lattice of the subsets of $$\{2,3,5,6\}$$ and the lattice of divisors of $$30$$, and check that the map $$b \mapsto \gcd(\prod_{x\in b} x, 30)$$ is a morphism of posets:

sage: D = Poset((divisors(30), attrcall("divides")))
sage: B = Poset(([frozenset(s) for s in Subsets([2,3,5,6])], attrcall("issubset")))
sage: def f(b): return D(gcd(prod(b), 30))
sage: B.is_poset_morphism(f, D)
True


Note

since D and B are not facade posets, f is responsible for the conversions between integers and subsets to elements of D and B and back.

$$f$$ is also a morphism of posets to the chain of divisors of 30, ordered by usual comparison:

sage: P = Poset((divisors(30), operator.le))
sage: def f(b): return P(gcd(prod(b), 30))
sage: B.is_poset_morphism(f, P)
True


FIXME: should this be is_order_preserving_morphism?

is_self_dual()

Return whether the poset is self-dual.

A poset is self-dual if it is isomorphic to its dual poset.

EXAMPLES:

sage: P = Poset({1: [3, 4], 2: [3, 4]})
sage: P.is_self_dual()
True

sage: P = Poset({1: [2, 3]})
sage: P.is_self_dual()
False


order_filter_generators(filter)

Generators for an order filter

INPUT:

• filter – an order filter of self, as a list (or iterable)

EXAMPLES:

sage: P = Poset((Subsets([1,2,3]), attrcall("issubset")))
sage: I = P.order_filter([Set([1,2]), Set([2,3]), Set([1])])
sage: sorted(sorted(p) for p in I)
[[1], [1, 2], [1, 2, 3], [1, 3], [2, 3]]
sage: gen = P.order_filter_generators(I)
sage: sorted(sorted(p) for p in gen)
[[1], [2, 3]]

order_ideal_complement_generators(antichain, direction='up')

Return the Panyushev complement of the antichain antichain.

Given an antichain $$A$$ of a poset $$P$$, the Panyushev complement of $$A$$ is defined to be the antichain consisting of the minimal elements of the order filter $$B$$, where $$B$$ is the (set-theoretic) complement of the order ideal of $$P$$ generated by $$A$$.

Setting the optional keyword variable direction to 'down' leads to the inverse Panyushev complement being computed instead of the Panyushev complement. The inverse Panyushev complement of an antichain $$A$$ is the antichain whose Panyushev complement is $$A$$. It can be found as the antichain consisting of the maximal elements of the order ideal $$C$$, where $$C$$ is the (set-theoretic) complement of the order filter of $$P$$ generated by $$A$$.

panyushev_complement() is an alias for this method.

Panyushev complementation is related (actually, isomorphic) to rowmotion (rowmotion()).

INPUT:

• antichain – an antichain of self, as a list (or iterable), or, more generally, generators of an order ideal (resp. order filter)

• direction – ‘up’ or ‘down’ (default: ‘up’)

OUTPUT:

• the generating antichain of the complement order filter (resp. order ideal) of the order ideal (resp. order filter) generated by the antichain antichain

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: P.order_ideal_complement_generators([1])
{2}
sage: P.order_ideal_complement_generators([3])
set()
sage: P.order_ideal_complement_generators([1,2])
{3}
sage: P.order_ideal_complement_generators([1,2,3])
set()

sage: P.order_ideal_complement_generators([1], direction="down")
{2}
sage: P.order_ideal_complement_generators([3], direction="down")
{1, 2}
sage: P.order_ideal_complement_generators([1,2], direction="down")
set()
sage: P.order_ideal_complement_generators([1,2,3], direction="down")
set()


Warning

This is a brute force implementation, building the order ideal generated by the antichain, and searching for order filter generators of its complement

order_ideal_generators(ideal, direction='down')

Return the antichain of (minimal) generators of the order ideal (resp. order filter) ideal.

INPUT:

• ideal – an order ideal $$I$$ (resp. order filter) of self, as a list (or iterable); this should be an order ideal if direction is set to 'down', and an order filter if direction is set to 'up'.

• direction'up' or 'down' (default: 'down').

The antichain of (minimal) generators of an order ideal $$I$$ in a poset $$P$$ is the set of all minimal elements of $$P$$. In the case of an order filter, the definition is similar, but with “maximal” used instead of “minimal”.

EXAMPLES:

We build the boolean lattice of all subsets of $$\{1,2,3\}$$ ordered by inclusion, and compute an order ideal there:

sage: P = Poset((Subsets([1,2,3]), attrcall("issubset")))
sage: I = P.order_ideal([Set([1,2]), Set([2,3]), Set([1])])
sage: sorted(sorted(p) for p in I)
[[], [1], [1, 2], [2], [2, 3], [3]]


Then, we retrieve the generators of this ideal:

sage: gen = P.order_ideal_generators(I)
sage: sorted(sorted(p) for p in gen)
[[1, 2], [2, 3]]


If direction is ‘up’, then this instead computes the minimal generators for an order filter:

sage: I = P.order_filter([Set([1,2]), Set([2,3]), Set([1])])
sage: sorted(sorted(p) for p in I)
[[1], [1, 2], [1, 2, 3], [1, 3], [2, 3]]
sage: gen = P.order_ideal_generators(I, direction='up')
sage: sorted(sorted(p) for p in gen)
[[1], [2, 3]]


Complexity: $$O(n+m)$$ where $$n$$ is the cardinality of $$I$$, and $$m$$ the number of upper covers of elements of $$I$$.

Return the lattice of order ideals of a poset self, ordered by inclusion.

The lattice of order ideals of a poset $$P$$ is usually denoted by $$J(P)$$. Its underlying set is the set of order ideals of $$P$$, and its partial order is given by inclusion.

The order ideals of $$P$$ are in a canonical bijection with the antichains of $$P$$. The bijection maps every order ideal to the antichain formed by its maximal elements. By setting the as_ideals keyword variable to False, one can make this method apply this bijection before returning the lattice.

INPUT:

• as_ideals – Boolean, if True (default) returns a poset on the set of order ideals, otherwise on the set of antichains

• facade – Boolean or None (default). Whether to return a facade lattice or not. By default return facade lattice if the poset is a facade poset.

EXAMPLES:

sage: P = posets.PentagonPoset()
sage: P.cover_relations()
[[0, 1], [0, 2], [1, 4], [2, 3], [3, 4]]
sage: J = P.order_ideals_lattice(); J
Finite lattice containing 8 elements
sage: sorted(sorted(e) for e in J)
[[], [0], [0, 1], [0, 1, 2], [0, 1, 2, 3], [0, 1, 2, 3, 4], [0, 2], [0, 2, 3]]


As a lattice on antichains:

sage: J2 = P.order_ideals_lattice(False); J2
Finite lattice containing 8 elements
sage: sorted(J2)
[(), (0,), (1,), (1, 2), (1, 3), (2,), (3,), (4,)]

panyushev_complement(antichain, direction='up')

Return the Panyushev complement of the antichain antichain.

Given an antichain $$A$$ of a poset $$P$$, the Panyushev complement of $$A$$ is defined to be the antichain consisting of the minimal elements of the order filter $$B$$, where $$B$$ is the (set-theoretic) complement of the order ideal of $$P$$ generated by $$A$$.

Setting the optional keyword variable direction to 'down' leads to the inverse Panyushev complement being computed instead of the Panyushev complement. The inverse Panyushev complement of an antichain $$A$$ is the antichain whose Panyushev complement is $$A$$. It can be found as the antichain consisting of the maximal elements of the order ideal $$C$$, where $$C$$ is the (set-theoretic) complement of the order filter of $$P$$ generated by $$A$$.

panyushev_complement() is an alias for this method.

Panyushev complementation is related (actually, isomorphic) to rowmotion (rowmotion()).

INPUT:

• antichain – an antichain of self, as a list (or iterable), or, more generally, generators of an order ideal (resp. order filter)

• direction – ‘up’ or ‘down’ (default: ‘up’)

OUTPUT:

• the generating antichain of the complement order filter (resp. order ideal) of the order ideal (resp. order filter) generated by the antichain antichain

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: P.order_ideal_complement_generators([1])
{2}
sage: P.order_ideal_complement_generators([3])
set()
sage: P.order_ideal_complement_generators([1,2])
{3}
sage: P.order_ideal_complement_generators([1,2,3])
set()

sage: P.order_ideal_complement_generators([1], direction="down")
{2}
sage: P.order_ideal_complement_generators([3], direction="down")
{1, 2}
sage: P.order_ideal_complement_generators([1,2], direction="down")
set()
sage: P.order_ideal_complement_generators([1,2,3], direction="down")
set()


Warning

This is a brute force implementation, building the order ideal generated by the antichain, and searching for order filter generators of its complement

panyushev_orbit_iter(antichain, element_constructor=<class 'set'>, stop=True, check=True)

Iterate over the Panyushev orbit of an antichain antichain of self.

The Panyushev orbit of an antichain is its orbit under Panyushev complementation (see panyushev_complement()).

INPUT:

• antichain – an antichain of self, given as an iterable.

• element_constructor (defaults to set) – a type constructor (set, tuple, list, frozenset, iter, etc.) which is to be applied to the antichains before they are yielded.

• stop – a Boolean (default: True) determining whether the iterator should stop once it completes its cycle (this happens when it is set to True) or go on forever (this happens when it is set to False).

• check – a Boolean (default: True) determining whether antichain should be checked for being an antichain.

OUTPUT:

• an iterator over the orbit of the antichain antichain under Panyushev complementation. This iterator $$I$$ has the property that I[0] == antichain and each $$i$$ satisfies self.order_ideal_complement_generators(I[i]) == I[i+1], where I[i+1] has to be understood as I[0] if it is undefined. The entries I[i] are sets by default, but depending on the optional keyword variable element_constructors they can also be tuples, lists etc.

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: list(P.panyushev_orbit_iter(set([1, 2])))
[{1, 2}, {3}, set()]
sage: list(P.panyushev_orbit_iter([1, 2]))
[{1, 2}, {3}, set()]
sage: list(P.panyushev_orbit_iter([2, 1]))
[{1, 2}, {3}, set()]
sage: list(P.panyushev_orbit_iter(set([1, 2]), element_constructor=list))
[[1, 2], [3], []]
sage: list(P.panyushev_orbit_iter(set([1, 2]), element_constructor=frozenset))
[frozenset({1, 2}), frozenset({3}), frozenset()]
sage: list(P.panyushev_orbit_iter(set([1, 2]), element_constructor=tuple))
[(1, 2), (3,), ()]

sage: P = Poset( {} )
sage: list(P.panyushev_orbit_iter([]))
[set()]

sage: P = Poset({ 1: [2, 3], 2: [4], 3: [4], 4: [] })
sage: Piter = P.panyushev_orbit_iter([2], stop=False)
sage: next(Piter)
{2}
sage: next(Piter)
{3}
sage: next(Piter)
{2}
sage: next(Piter)
{3}

panyushev_orbits(element_constructor=<class 'set'>)

Return the Panyushev orbits of antichains in self.

The Panyushev orbit of an antichain is its orbit under Panyushev complementation (see panyushev_complement()).

INPUT:

• element_constructor (defaults to set) – a type constructor (set, tuple, list, frozenset, iter, etc.) which is to be applied to the antichains before they are returned.

OUTPUT:

• the partition of the set of all antichains of self into orbits under Panyushev complementation. This is returned as a list of lists L such that for each L and i, cyclically: self.order_ideal_complement_generators(L[i]) == L[i+1]. The entries L[i] are sets by default, but depending on the optional keyword variable element_constructors they can also be tuples, lists etc.

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: orb = P.panyushev_orbits()
sage: sorted(sorted(o) for o in orb)
[[set(), {1, 2}, {3}], [{2}, {1}]]
sage: orb = P.panyushev_orbits(element_constructor=list)
sage: sorted(sorted(o) for o in orb)
[[[], [1, 2], [3]], [[1], [2]]]
sage: orb = P.panyushev_orbits(element_constructor=frozenset)
sage: sorted(sorted(o) for o in orb)
[[frozenset(), frozenset({1, 2}), frozenset({3})],
[frozenset({2}), frozenset({1})]]
sage: orb = P.panyushev_orbits(element_constructor=tuple)
sage: sorted(sorted(o) for o in orb)
[[(), (1, 2), (3,)], [(1,), (2,)]]
sage: P = Poset( {} )
sage: P.panyushev_orbits()
[[set()]]

rowmotion(order_ideal)

The image of the order ideal order_ideal under rowmotion in self.

Rowmotion on a finite poset $$P$$ is an automorphism of the set $$J(P)$$ of all order ideals of $$P$$. One way to define it is as follows: Given an order ideal $$I \in J(P)$$, we let $$F$$ be the set-theoretic complement of $$I$$ in $$P$$. Furthermore we let $$A$$ be the antichain consisting of all minimal elements of $$F$$. Then, the rowmotion of $$I$$ is defined to be the order ideal of $$P$$ generated by the antichain $$A$$ (that is, the order ideal consisting of each element of $$P$$ which has some element of $$A$$ above it).

Rowmotion is related (actually, isomorphic) to Panyushev complementation (panyushev_complement()).

INPUT:

• order_ideal – an order ideal of self, as a set

OUTPUT:

• the image of order_ideal under rowmotion, as a set again

EXAMPLES:

sage: P = Poset( {1: [2, 3], 2: [], 3: [], 4: [8], 5: [], 6: [5], 7: [1, 4], 8: []} )
sage: I = Set({2, 6, 1, 7})
sage: P.rowmotion(I)
{1, 3, 4, 5, 6, 7}

sage: P = Poset( {} )
sage: I = Set({})
sage: P.rowmotion(I)
{}

rowmotion_orbit_iter(oideal, element_constructor=<class 'set'>, stop=True, check=True)

Iterate over the rowmotion orbit of an order ideal oideal of self.

The rowmotion orbit of an order ideal is its orbit under rowmotion (see rowmotion()).

INPUT:

• oideal – an order ideal of self, given as an iterable.

• element_constructor (defaults to set) – a type constructor (set, tuple, list, frozenset, iter, etc.) which is to be applied to the order ideals before they are yielded.

• stop – a Boolean (default: True) determining whether the iterator should stop once it completes its cycle (this happens when it is set to True) or go on forever (this happens when it is set to False).

• check – a Boolean (default: True) determining whether oideal should be checked for being an order ideal.

OUTPUT:

• an iterator over the orbit of the order ideal oideal under rowmotion. This iterator $$I$$ has the property that I[0] == oideal and that every $$i$$ satisfies self.rowmotion(I[i]) == I[i+1], where I[i+1] has to be understood as I[0] if it is undefined. The entries I[i] are sets by default, but depending on the optional keyword variable element_constructors they can also be tuples, lists etc.

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: list(P.rowmotion_orbit_iter(set([1, 2])))
[{1, 2}, {1, 2, 3}, set()]
sage: list(P.rowmotion_orbit_iter([1, 2]))
[{1, 2}, {1, 2, 3}, set()]
sage: list(P.rowmotion_orbit_iter([2, 1]))
[{1, 2}, {1, 2, 3}, set()]
sage: list(P.rowmotion_orbit_iter(set([1, 2]), element_constructor=list))
[[1, 2], [1, 2, 3], []]
sage: list(P.rowmotion_orbit_iter(set([1, 2]), element_constructor=frozenset))
[frozenset({1, 2}), frozenset({1, 2, 3}), frozenset()]
sage: list(P.rowmotion_orbit_iter(set([1, 2]), element_constructor=tuple))
[(1, 2), (1, 2, 3), ()]

sage: P = Poset( {} )
sage: list(P.rowmotion_orbit_iter([]))
[set()]

sage: P = Poset({ 1: [2, 3], 2: [4], 3: [4], 4: [] })
sage: Piter = P.rowmotion_orbit_iter([1, 2, 3], stop=False)
sage: next(Piter)
{1, 2, 3}
sage: next(Piter)
{1, 2, 3, 4}
sage: next(Piter)
set()
sage: next(Piter)
{1}
sage: next(Piter)
{1, 2, 3}

sage: P = Poset({ 1: [4], 2: [4, 5], 3: [5] })
sage: list(P.rowmotion_orbit_iter([1, 2], element_constructor=list))
[[1, 2], [1, 2, 3, 4], [2, 3, 5], [1], [2, 3], [1, 2, 3, 5], [1, 2, 4], [3]]

rowmotion_orbits(element_constructor=<class 'set'>)

Return the rowmotion orbits of order ideals in self.

The rowmotion orbit of an order ideal is its orbit under rowmotion (see rowmotion()).

INPUT:

• element_constructor (defaults to set) – a type constructor (set, tuple, list, frozenset, iter, etc.) which is to be applied to the antichains before they are returned.

OUTPUT:

• the partition of the set of all order ideals of self into orbits under rowmotion. This is returned as a list of lists L such that for each L and i, cyclically: self.rowmotion(L[i]) == L[i+1]. The entries L[i] are sets by default, but depending on the optional keyword variable element_constructors they can also be tuples, lists etc.

EXAMPLES:

sage: P = Poset( {1: [2, 3], 2: [], 3: [], 4: [2]} )
sage: sorted(len(o) for o in P.rowmotion_orbits())
[3, 5]
sage: orb = P.rowmotion_orbits(element_constructor=list)
sage: sorted(sorted(e) for e in orb)
[[[], [4, 1], [4, 1, 2, 3]], [[1], [1, 3], [4], [4, 1, 2], [4, 1, 3]]]
sage: orb = P.rowmotion_orbits(element_constructor=tuple)
sage: sorted(sorted(e) for e in orb)
[[(), (4, 1), (4, 1, 2, 3)], [(1,), (1, 3), (4,), (4, 1, 2), (4, 1, 3)]]
sage: P = Poset({})
sage: P.rowmotion_orbits(element_constructor=tuple)
[[()]]

rowmotion_orbits_plots()

Return plots of the rowmotion orbits of order ideals in self.

The rowmotion orbit of an order ideal is its orbit under rowmotion (see rowmotion()).

EXAMPLES:

sage: P = Poset( {1: [2, 3], 2: [], 3: [], 4: [2]} )
sage: P.rowmotion_orbits_plots()
Graphics Array of size 2 x 5
sage: P = Poset({})
sage: P.rowmotion_orbits_plots()
Graphics Array of size 1 x 1

toggling_orbit_iter(vs, oideal, element_constructor=<class 'set'>, stop=True, check=True)

Iterate over the orbit of an order ideal oideal of self under the operation of toggling the vertices vs[0], vs[1], ... in this order.

See order_ideal_toggle() for a definition of toggling.

Warning

The orbit is that under the composition of toggles, not under the single toggles themselves. Thus, for example, if vs == [1,2], then the orbit has the form $$(I, T_2 T_1 I, T_2 T_1 T_2 T_1 I, \ldots)$$ (where $$I$$ denotes oideal and $$T_i$$ means toggling at $$i$$) rather than $$(I, T_1 I, T_2 T_1 I, T_1 T_2 T_1 I, \ldots)$$.

INPUT:

• vs: a list (or other iterable) of elements of self (but since the output depends on the order, sets should not be used as vs).

• oideal – an order ideal of self, given as an iterable.

• element_constructor (defaults to set) – a type constructor (set, tuple, list, frozenset, iter, etc.) which is to be applied to the order ideals before they are yielded.

• stop – a Boolean (default: True) determining whether the iterator should stop once it completes its cycle (this happens when it is set to True) or go on forever (this happens when it is set to False).

• check – a Boolean (default: True) determining whether oideal should be checked for being an order ideal.

OUTPUT:

• an iterator over the orbit of the order ideal oideal under toggling the vertices in the list vs in this order. This iterator $$I$$ has the property that I[0] == oideal and that every $$i$$ satisfies self.order_ideal_toggles(I[i], vs) == I[i+1], where I[i+1] has to be understood as I[0] if it is undefined. The entries I[i] are sets by default, but depending on the optional keyword variable element_constructors they can also be tuples, lists etc.

EXAMPLES:

sage: P = Poset( ( [1,2,3], [ [1,3], [2,3] ] ) )
sage: list(P.toggling_orbit_iter([1, 3, 1], set([1, 2])))
[{1, 2}]
sage: list(P.toggling_orbit_iter([1, 2, 3], set([1, 2])))
[{1, 2}, set(), {1, 2, 3}]
sage: list(P.toggling_orbit_iter([3, 2, 1], set([1, 2])))
[{1, 2}, {1, 2, 3}, set()]
sage: list(P.toggling_orbit_iter([3, 2, 1], set([1, 2]), element_constructor=list))
[[1, 2], [1, 2, 3], []]
sage: list(P.toggling_orbit_iter([3, 2, 1], set([1, 2]), element_constructor=frozenset))
[frozenset({1, 2}), frozenset({1, 2, 3}), frozenset()]
sage: list(P.toggling_orbit_iter([3, 2, 1], set([1, 2]), element_constructor=tuple))
[(1, 2), (1, 2, 3), ()]
sage: list(P.toggling_orbit_iter([3, 2, 1], [2, 1], element_constructor=tuple))
[(1, 2), (1, 2, 3), ()]

sage: P = Poset( {} )
sage: list(P.toggling_orbit_iter([], []))
[set()]

sage: P = Poset({ 1: [2, 3], 2: [4], 3: [4], 4: [] })
sage: Piter = P.toggling_orbit_iter([1, 2, 4, 3], [1, 2, 3], stop=False)
sage: next(Piter)
{1, 2, 3}
sage: next(Piter)
{1}
sage: next(Piter)
set()
sage: next(Piter)
{1, 2, 3}
sage: next(Piter)
{1}

toggling_orbits(vs, element_constructor=<class 'set'>)

Return the orbits of order ideals in self under the operation of toggling the vertices vs[0], vs[1], ... in this order.

See order_ideal_toggle() for a definition of toggling.

Warning

The orbits are those under the composition of toggles, not under the single toggles themselves. Thus, for example, if vs == [1,2], then the orbits have the form $$(I, T_2 T_1 I, T_2 T_1 T_2 T_1 I, \ldots)$$ (where $$I$$ denotes an order ideal and $$T_i$$ means toggling at $$i$$) rather than $$(I, T_1 I, T_2 T_1 I, T_1 T_2 T_1 I, \ldots)$$.

INPUT:

• vs: a list (or other iterable) of elements of self (but since the output depends on the order, sets should not be used as vs).

OUTPUT:

• a partition of the order ideals of self, as a list of sets L such that for each L and i, cyclically: self.order_ideal_toggles(L[i], vs) == L[i+1].

EXAMPLES:

sage: P = Poset( {1: [2, 4], 2: [], 3: [4], 4: []} )
sage: sorted(len(o) for o in P.toggling_orbits([1, 2]))
[2, 3, 3]
sage: P = Poset( {1: [3], 2: [1, 4], 3: [], 4: [3]} )
sage: sorted(len(o) for o in P.toggling_orbits((1, 2, 4, 3)))
[3, 3]

toggling_orbits_plots(vs)

Return plots of the orbits of order ideals in self under the operation of toggling the vertices vs[0], vs[1], ... in this order.

See toggling_orbits() for more information.

EXAMPLES:

sage: P = Poset( {1: [2, 3], 2: [], 3: [], 4: [2]} )
sage: P.toggling_orbits_plots([1,2,3,4])
Graphics Array of size 2 x 5
sage: P = Poset({})
sage: P.toggling_orbits_plots([])
Graphics Array of size 1 x 1