# Generating Series#

This file makes a number of extensions to lazy power series by endowing them with some semantic content for how they’re to be interpreted.

This code is based on the work of Ralf Hemmecke and Martin Rubey’s Aldor-Combinat, which can be found at http://www.risc.uni-linz.ac.at/people/hemmecke/aldor/combinat/index.html. In particular, the relevant section for this file can be found at http://www.risc.uni-linz.ac.at/people/hemmecke/AldorCombinat/combinatse10.html. One notable difference is that we use power-sum symmetric functions as the coefficients of our cycle index series.

REFERENCES:

[BLL] (1,2)

F. Bergeron, G. Labelle, and P. Leroux. “Combinatorial species and tree-like structures”. Encyclopedia of Mathematics and its Applications, vol. 67, Cambridge Univ. Press. 1998.

[BLL-Intro]

François Bergeron, Gilbert Labelle, and Pierre Leroux. “Introduction to the Theory of Species of Structures”, March 14, 2008.

class sage.combinat.species.generating_series.CycleIndexSeries(parent, coeff_stream)#
coefficient_cycle_type(t)#

Return the coefficient of a cycle type t in self.

EXAMPLES:

sage: from sage.combinat.species.generating_series import CycleIndexSeriesRing
sage: p = SymmetricFunctions(QQ).power()                                    # optional - sage.modules
sage: CIS = CycleIndexSeriesRing(QQ)
sage: f = CIS([0, p(), 2*p([1,1]),3*p([2,1])])                           # optional - sage.modules
sage: f.coefficient_cycle_type()                                         # optional - sage.modules
1
sage: f.coefficient_cycle_type([1,1])                                       # optional - sage.modules
2
sage: f.coefficient_cycle_type([2,1])                                       # optional - sage.modules
3

count(t)#

Return the number of structures corresponding to a certain cycle type t.

EXAMPLES:

sage: from sage.combinat.species.generating_series import CycleIndexSeriesRing
sage: p = SymmetricFunctions(QQ).power()                                    # optional - sage.modules
sage: CIS = CycleIndexSeriesRing(QQ)
sage: f = CIS([0, p(), 2*p([1,1]), 3*p([2,1])])                          # optional - sage.modules
sage: f.count()                                                          # optional - sage.modules
1
sage: f.count([1,1])                                                        # optional - sage.modules
4
sage: f.count([2,1])                                                        # optional - sage.modules
6

derivative(n=1)#

Return the species-theoretic $$n$$-th derivative of self.

For a cycle index series $$F (p_{1}, p_{2}, p_{3}, \ldots)$$, its derivative is the cycle index series $$F' = D_{p_{1}} F$$ (that is, the formal derivative of $$F$$ with respect to the variable $$p_{1}$$).

If $$F$$ is the cycle index series of a species $$S$$ then $$F'$$ is the cycle index series of an associated species $$S'$$ of $$S$$-structures with a “hole”.

EXAMPLES:

The species $$E$$ of sets satisfies the relationship $$E' = E$$:

sage: E = species.SetSpecies().cycle_index_series()
sage: E[:8] == E.derivative()[:8]
True


The species $$C$$ of cyclic orderings and the species $$L$$ of linear orderings satisfy the relationship $$C' = L$$:

sage: C = species.CycleSpecies().cycle_index_series()
sage: L = species.LinearOrderSpecies().cycle_index_series()
sage: L[:8] == C.derivative()[:8]
True

exponential()#

Return the species-theoretic exponential of self.

For a cycle index $$Z_{F}$$ of a species $$F$$, its exponential is the cycle index series $$Z_{E} \circ Z_{F}$$, where $$Z_{E}$$ is the ExponentialCycleIndexSeries().

The exponential $$Z_{E} \circ Z_{F}$$ is then the cycle index series of the species $$E \circ F$$ of “sets of $$F$$-structures”.

EXAMPLES:

Let $$BT$$ be the species of binary trees, $$BF$$ the species of binary forests, and $$E$$ the species of sets. Then we have $$BF = E \circ BT$$:

sage: BT = species.BinaryTreeSpecies().cycle_index_series()
sage: BF = species.BinaryForestSpecies().cycle_index_series()
sage: BT.exponential().isotype_generating_series()[:8] == BF.isotype_generating_series()[:8]
True

generating_series()#

Return the generating series of self.

EXAMPLES:

sage: P = species.PartitionSpecies()
sage: cis = P.cycle_index_series()
sage: f = cis.generating_series()
sage: f[:5]
[1, 1, 1, 5/6, 5/8]

isotype_generating_series()#

Return the isotype generating series of self.

EXAMPLES:

sage: P = species.PermutationSpecies()
sage: cis = P.cycle_index_series()
sage: f = cis.isotype_generating_series()
sage: f[:10]
[1, 1, 2, 3, 5, 7, 11, 15, 22, 30]

logarithm()#

Return the combinatorial logarithm of self.

For a cycle index $$Z_{F}$$ of a species $$F$$, its logarithm is the cycle index series $$Z_{\Omega} \circ Z_{F}$$, where $$Z_{\Omega}$$ is the LogarithmCycleIndexSeries().

The logarithm $$Z_{\Omega} \circ Z_{F}$$ is then the cycle index series of the (virtual) species $$\Omega \circ F$$ of “connected $$F$$-structures”. In particular, if $$F = E^{+} \circ G$$ for $$E^{+}$$ the species of nonempty sets and $$G$$ some other species, then $$\Omega \circ F = G$$.

EXAMPLES:

Let $$G$$ be the species of nonempty graphs and $$CG$$ be the species of nonempty connected graphs. Then $$G = E^{+} \circ CG$$, so $$CG = \Omega \circ G$$:

sage: G = species.SimpleGraphSpecies().cycle_index_series() - 1
sage: from sage.combinat.species.generating_series import LogarithmCycleIndexSeries
sage: CG = LogarithmCycleIndexSeries()(G)
sage: CG.isotype_generating_series()[0:8]
[0, 1, 1, 2, 6, 21, 112, 853]

pointing()#

Return the species-theoretic pointing of self.

For a cycle index $$F$$, its pointing is the cycle index series $$F^{\bullet} = p_{1} \cdot F'$$.

If $$F$$ is the cycle index series of a species $$S$$ then $$F^{\bullet}$$ is the cycle index series of an associated species $$S^{\bullet}$$ of $$S$$-structures with a marked “root”.

EXAMPLES:

The species $$E^{\bullet}$$ of “pointed sets” satisfies $$E^{\bullet} = X \cdot E$$:

sage: E = species.SetSpecies().cycle_index_series()
sage: X = species.SingletonSpecies().cycle_index_series()
sage: E.pointing()[:8] == (X*E)[:8]
True

class sage.combinat.species.generating_series.CycleIndexSeriesRing(base_ring, sparse=True)#

Return the ring of cycle index series over R.

This is the ring of formal power series $$\Lambda[x]$$, where $$\Lambda$$ is the ring of symmetric functions over R in the $$p$$-basis. Its purpose is to house the cycle index series of species (in a somewhat nonstandard notation tailored to Sage): If $$F$$ is a species, then the cycle index series of $$F$$ is defined to be the formal power series

$\sum_{n \geq 0} \frac{1}{n!} (\sum_{\sigma \in S_n} \operatorname{fix} F[\sigma] \prod_{z \text{ is a cycle of } \sigma} p_{\text{length of } z}) x^n \in \Lambda_\QQ [x],$

where $$\operatorname{fix} F[\sigma]$$ denotes the number of fixed points of the permutation $$F[\sigma]$$ of $$F[n]$$. We notice that this power series is “equigraded” (meaning that its $$x^n$$-coefficient is homogeneous of degree $$n$$). A more standard convention in combinatorics would be to use $$x_i$$ instead of $$p_i$$, and drop the $$x$$ (that is, evaluate the above power series at $$x = 1$$); but this would be more difficult to implement in Sage, as it would be an element of a power series ring in infinitely many variables.

Note that it is just a LazyPowerSeriesRing (whose base ring is $$\Lambda$$) whose elements have some extra methods.

EXAMPLES:

sage: from sage.combinat.species.generating_series import CycleIndexSeriesRing
sage: R = CycleIndexSeriesRing(QQ); R                                           # optional - sage.modules
Cycle Index Series Ring over Rational Field
sage: p = SymmetricFunctions(QQ).p()                                            # optional - sage.modules
sage: R(lambda n: p[n])                                                         # optional - sage.modules
p[] + p + p + p + p + p + p + O^7

Element#

alias of CycleIndexSeries

sage.combinat.species.generating_series.ExponentialCycleIndexSeries()#

Return the cycle index series of the species $$E$$ of sets.

This cycle index satisfies

$Z_{E} = \sum_{n \geq 0} \sum_{\lambda \vdash n} \frac{p_{\lambda}}{z_{\lambda}}.$

EXAMPLES:

sage: from sage.combinat.species.generating_series import ExponentialCycleIndexSeries
sage: ExponentialCycleIndexSeries()[:5]                                         # optional - sage.modules
[p[], p, 1/2*p[1, 1] + 1/2*p, 1/6*p[1, 1, 1] + 1/2*p[2, 1]
+ 1/3*p, 1/24*p[1, 1, 1, 1] + 1/4*p[2, 1, 1] + 1/8*p[2, 2]
+ 1/3*p[3, 1] + 1/4*p]

class sage.combinat.species.generating_series.ExponentialGeneratingSeries(parent, coeff_stream)#

A class for ordinary generating series.

Note that it is just a LazyPowerSeries whose elements have some extra methods.

EXAMPLES:

sage: from sage.combinat.species.generating_series import OrdinaryGeneratingSeriesRing
sage: R = OrdinaryGeneratingSeriesRing(QQ)
sage: f = R(lambda n: n)
sage: f
z + 2*z^2 + 3*z^3 + 4*z^4 + 5*z^5 + 6*z^6 + O(z^7)

count(n)#

Return the number of structures of size n.

EXAMPLES:

sage: from sage.combinat.species.generating_series import ExponentialGeneratingSeriesRing
sage: R = ExponentialGeneratingSeriesRing(QQ)
sage: f = R(lambda n: 1)
sage: [f.count(i) for i in range(7)]
[1, 1, 2, 6, 24, 120, 720]

counts(n)#

Return the number of structures on a set for size i for each i in range(n).

EXAMPLES:

sage: from sage.combinat.species.generating_series import ExponentialGeneratingSeriesRing
sage: R = ExponentialGeneratingSeriesRing(QQ)
sage: f = R(range(20))
sage: f.counts(5)
[0, 1, 4, 18, 96]

functorial_composition(y)#

Return the exponential generating series which is the functorial composition of self with y.

If $$f = \sum_{n=0}^{\infty} f_n \frac{x^n}{n!}$$ and $$g = \sum_{n=0}^{\infty} g_n \frac{x^n}{n!}$$, then functorial composition $$f \Box g$$ is defined as

$f \Box g = \sum_{n=0}^{\infty} f_{g_n} \frac{x^n}{n!}.$

REFERENCES:

EXAMPLES:

sage: G = species.SimpleGraphSpecies()
sage: g = G.generating_series()
sage: [g.coefficient(i) for i in range(10)]
[1, 1, 1, 4/3, 8/3, 128/15, 2048/45, 131072/315, 2097152/315, 536870912/2835]

sage: E = species.SetSpecies()
sage: E2 = E.restricted(min=2, max=3)
sage: WP = species.SubsetSpecies()
sage: P2 = E2*E
sage: g1 = WP.generating_series()
sage: g2 = P2.generating_series()
sage: g1.functorial_composition(g2)[:10]
[1, 1, 1, 4/3, 8/3, 128/15, 2048/45, 131072/315, 2097152/315, 536870912/2835]

class sage.combinat.species.generating_series.ExponentialGeneratingSeriesRing(base_ring)#

Return the ring of exponential generating series over R.

Note that it is just a LazyPowerSeriesRing whose elements have some extra methods.

EXAMPLES:

sage: from sage.combinat.species.generating_series import ExponentialGeneratingSeriesRing
sage: R = ExponentialGeneratingSeriesRing(QQ); R
Lazy Taylor Series Ring in z over Rational Field
sage: [R(lambda n: 1).coefficient(i) for i in range(4)]
[1, 1, 1, 1]
sage: R(lambda n: 1).counts(4)
[1, 1, 2, 6]

Element#
sage.combinat.species.generating_series.LogarithmCycleIndexSeries()#

Return the cycle index series of the virtual species $$\Omega$$, the compositional inverse of the species $$E^{+}$$ of nonempty sets.

The notion of virtual species is treated thoroughly in [BLL]. The specific algorithm used here to compute the cycle index of $$\Omega$$ is found in [Labelle2008].

EXAMPLES:

The virtual species $$\Omega$$ is ‘properly virtual’, in the sense that its cycle index has negative coefficients:

sage: from sage.combinat.species.generating_series import LogarithmCycleIndexSeries
sage: LogarithmCycleIndexSeries()[0:4]                                          # optional - sage.modules
[0, p, -1/2*p[1, 1] - 1/2*p, 1/3*p[1, 1, 1] - 1/3*p]


Its defining property is that $$\Omega \circ E^{+} = E^{+} \circ \Omega = X$$ (that is, that composition with $$E^{+}$$ in both directions yields the multiplicative identity $$X$$):

sage: Eplus = sage.combinat.species.set_species.SetSpecies(min=1).cycle_index_series()
sage: LogarithmCycleIndexSeries()(Eplus)[0:4]                                   # optional - sage.modules
[0, p, 0, 0]

class sage.combinat.species.generating_series.OrdinaryGeneratingSeries(parent, coeff_stream)#

A class for ordinary generating series.

Note that it is just a LazyPowerSeries whose elements have some extra methods.

EXAMPLES:

sage: from sage.combinat.species.generating_series import OrdinaryGeneratingSeriesRing
sage: R = OrdinaryGeneratingSeriesRing(QQ)
sage: f = R(lambda n: n)
sage: f
z + 2*z^2 + 3*z^3 + 4*z^4 + 5*z^5 + 6*z^6 + O(z^7)

count(n)#

Return the number of structures on a set of size n.

INPUT:

• n – the size of the set

EXAMPLES:

sage: from sage.combinat.species.generating_series import OrdinaryGeneratingSeriesRing
sage: R = OrdinaryGeneratingSeriesRing(QQ)
sage: f = R(range(20))
sage: f.count(10)
10

counts(n)#

Return the number of structures on a set for size i for each i in range(n).

EXAMPLES:

sage: from sage.combinat.species.generating_series import OrdinaryGeneratingSeriesRing
sage: R = OrdinaryGeneratingSeriesRing(QQ)
sage: f = R(range(20))
sage: f.counts(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

class sage.combinat.species.generating_series.OrdinaryGeneratingSeriesRing(base_ring)#

Return the ring of ordinary generating series over R.

Note that it is just a LazyPowerSeriesRing whose elements have some extra methods.

EXAMPLES:

sage: from sage.combinat.species.generating_series import OrdinaryGeneratingSeriesRing
sage: R = OrdinaryGeneratingSeriesRing(QQ); R
Lazy Taylor Series Ring in z over Rational Field
sage: [R(lambda n: 1).coefficient(i) for i in range(4)]
[1, 1, 1, 1]
sage: R(lambda n: 1).counts(4)
[1, 1, 1, 1]