File: matroid_properties.rules

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#  Copyright (c) 1997-2024
#  Ewgenij Gawrilow, Michael Joswig, and the polymake team
#  Technische Universität Berlin, Germany
#  https://polymake.org
#
#  This program is free software; you can redistribute it and/or modify it
#  under the terms of the GNU General Public License as published by the
#  Free Software Foundation; either version 2, or (at your option) any
#  later version: http://www.gnu.org/licenses/gpl.txt.
#
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#  GNU General Public License for more details.
#-------------------------------------------------------------------------------


object Matroid {


## ENUMERATIVE PROPERTIES ###

# @category Enumerative properties
# Size of the ground set.  The ground set itself always consists of the first integers starting with zero.
# @example The elements of the Fano matroid correspond to the seven points of the projective plane over GF2.
# > print fano_matroid()->N_ELEMENTS;
# | 7
property N_ELEMENTS : Int;

# @category Enumerative properties
# Rank of the matroid, i.e., number of elements in each basis.
# @example The non-Fano matroid is realizable over any field, unless the chracteristic is 2.
# > print non_fano_matroid()->RANK;
# | 3
property RANK : Int;

# @category Enumerative properties
# The number of [[BASES]].
# @example The bases of the Fano matroid correspond to the 28 nonlinear triples of points in the projective plane over GF2.
# > print fano_matroid()->N_BASES;
# | 28
property N_BASES : Int;

# @category Enumerative properties
# The number of [[CIRCUITS]].
# @example The circuits of the Fano matroid correspond to the seven lines in the the projective plane over GF2 and their complements.
# > print fano_matroid()->N_CIRCUITS;
# | 14
property N_CIRCUITS : Int;

# @category Enumerative properties
# The number of [[MATROID_HYPERPLANES]]
# @example Every one of the four elements of the uniform matroid U(2,4) yields a hyperplane.
# > print uniform_matroid(2,4)->N_MATROID_HYPERPLANES;
# | 4
property N_MATROID_HYPERPLANES : Int;

# @category Enumerative properties
# The number of [[LOOPS]].
# @example The uniform matroids do not have any loops.
# > print uniform_matroid(2,4)->N_LOOPS;
# | 0
property N_LOOPS : Int;

# @category Enumerative properties
# The number of flats, i.e. the number of nodes in [[LATTICE_OF_FLATS]].
# @example The uniform matroid U(2,4) has six flats.
# > print uniform_matroid(2,4)->N_FLATS;
# | 6
property N_FLATS : Int;

# @category Enumerative properties
# The number of cyclic flats, i.e. the number of nodes in [[LATTICE_OF_CYCLIC_FLATS]].
# @example In the uniform matroid U(2,4) only the empty set and the entire set of all elements form cyclic flats.
# > print uniform_matroid(2,4)->N_CYCLIC_FLATS;
# | 2
property N_CYCLIC_FLATS : Int;

# @category Enumerative properties
# The order of the [[AUTOMORPHISM_GROUP]] of the matroid.
# @example The automorphism group of the Fano matroid is SL(3,2) of order 168.
# > print fano_matroid()->N_AUTOMORPHISMS;
# | 168
property N_AUTOMORPHISMS : Int;


## AXIOM SYSTEMS ###

# @category Axiom systems
# Subsets of the ground set which form the bases of the matroid.
# Note that if you want to define a matroid via its bases, you should also specify [[N_ELEMENTS]], because
# we allow matroids with loops.
# @example polymake does not automatically check if the sets given actually form the bases of a matroid.
# > $B = new Array<Set>([[0,1],[0,2],[1,2]]);
# > print check_basis_exchange_axiom($B);
# | true
# > $M = new Matroid(BASES=>$B, N_ELEMENTS=>3);
# > print $M->RANK;
# | 2
property BASES : Array<Set>;

# permuting the [[BASES]]
permutation BasesPerm : PermBase;

rule BasesPerm.PERMUTATION : BasesPerm.BASES, BASES {
   $this->BasesPerm->PERMUTATION = find_permutation($this->BasesPerm->BASES, $this->BASES)
      // die "no permutation";
}

rule BASES : BasesPerm.BASES, BasesPerm.PERMUTATION {
   $this->BASES = permuted($this->BasesPerm->BASES, $this->BasesPerm->PERMUTATION);
}
weight 1.10;

# @category Axiom systems
# All subsets of the ground sets with cardinality [[RANK]] that are not [[BASES]].
# @example Some matroids are more efficiently characterized by listing the non-bases.
# > $M = new Matroid(RANK=>2, N_ELEMENTS=>4, NON_BASES=>[]);
property NON_BASES : Array<Set>;

# @category Axiom systems
# Circuits, i.e., minimally dependent sets.
# @example The four circuits of the matroid U(2,4).
# > print uniform_matroid(2,4)->CIRCUITS;
# | {0 1 2}
# | {0 1 3}
# | {0 2 3}
# | {1 2 3}
# @example Matroids can be defined in terms of their circuits.
# > $M = new Matroid(CIRCUITS=>[[0,1,2,3]], N_ELEMENTS=>4);
# > print $M->BASES;
# | {0 1 2}
# | {0 1 3}
# | {0 2 3}
# | {1 2 3}
property CIRCUITS : Array<Set>;

# @category Axiom systems
# Hyperplanes, i.e., flats of rank [[RANK]]-1.
# @example The fano matroid's hyperplanes correspond to the lines of the fano plane.
# > print fano_matroid()->MATROID_HYPERPLANES;
# | {3 5 6}
# | {2 4 6}
# | {1 4 5}
# | {1 2 3}
# | {0 3 4}
# | {0 2 5}
# | {0 1 6}
# @example Matroids can be defined in terms of their hyperplanes.
# > $M = new Matroid(MATROID_HYPERPLANES=>[[0],[1],[2],[3]], N_ELEMENTS=>4);
# > print $M->BASES;
# | {0 1}
# | {0 2}
# | {0 3}
# | {1 2}
# | {1 3}
# | {2 3}
property MATROID_HYPERPLANES : Array<Set>;

permutation HyperplanePerm : PermBase;

rule HyperplanePerm.PERMUTATION : HyperplanePerm.MATROID_HYPERPLANES, MATROID_HYPERPLANES {
   $this->HyperplanePerm->PERMUTATION = find_permutation($this->HyperplanePerm->MATROID_HYPERPLANES, $this->MATROID_HYPERPLANES)
      // die "no permutation";
}
weight 2.10;

rule MATROID_HYPERPLANES : HyperplanePerm.MATROID_HYPERPLANES, HyperplanePerm.PERMUTATION {
   $this->MATROID_HYPERPLANES = permuted($this->HyperplanePerm->MATROID_HYPERPLANES, $this->HyperplanePerm->PERMUTATION);
}
weight 1.10;

# @category Axiom systems
# The lattice of flats.
# This is a graph with all closed sets as nodes and inclusion relations as edges.
# @example The fano matroid's lattice of flats corresponds to the point-line incidence graph of the fano plane plus a top and bottom node.
# > $l = fano_matroid()->LATTICE_OF_FLATS;
# > $l->VISUAL;
property LATTICE_OF_FLATS : Lattice<BasicDecoration, Sequential>;

# @category Axiom systems
# The lattice of cyclic flats of the matroid.
# A flat is a cyclic flat, if and only if it is a union of circuits.
# Their ranks can also be read off of this property using nodes_of_dim(..)
# @example The nontrivial cyclic flats of the complete graph K5 correspond to complete subgraphs on three or four vertices.
# > $g = graph::complete(5);
# > $m = matroid_from_graph($g);
# > $m->LATTICE_OF_CYCLIC_FLATS->VISUAL;
property LATTICE_OF_CYCLIC_FLATS : Lattice<BasicDecoration, Sequential>;


## REALIZABILITY ###

# @category Realizability
# If the matroid is realizable over the rationals, this property contains
# coordinates for some realization. Specifying (rational) coordinates is one way
# to define a matroid.  See also [[BINARY_VECTORS]] and [[TERNARY_VECTORS]] for
# realization over GF(2) and GF(3).
# @example Every graphic matroid is realizable.
# > $g = graph::complete(4);
# > $m = matroid_from_graph($g);
# > print $m->VECTORS;
# | 1 0 0
# | 0 1 0
# | 1 1 0
# | 0 0 1
# | 1 0 1
# | 0 1 -1
property VECTORS : Matrix;

# @category Realizability
# Whether or not the matroid is representable over GF(2).
# @example The uniform matroid of rank 2 on 4 elements is not binary.
# > print uniform_matroid(2,4)->BINARY;
# | false
property BINARY : Bool;

# @category Realizability
# If the matroid is realizable over the field GF(2) with two elements, this property may contain
# coordinates for some realization.
# @example The fano matroid is representable over GF(2). Its cannonical representation are the 7 nonzero vectors in the 3 dimensional vector space over GF(2).
# > print fano_matroid()->BINARY_VECTORS();
# | 1 1 1
# | 0 0 1
# | 0 1 0
# | 0 1 1
# | 1 0 0
# | 1 0 1
# | 1 1 0
property BINARY_VECTORS : Matrix<Int>;

# @category Realizability
# Whether the matroid is representable over GF(3).
# NOTE: the property my be 'undef' when polymake is unable to decide whether the matroid is ternary.
# @example The Vámos matroid is not representable over any field, so it is not ternary.
# > print vamos_matroid()->TERNARY;
# | false
property TERNARY : Bool;

# @category Realizability
# If the matroid is realizable over the field GF(3) with three elements, this property may contain
# coordinates for some realization.
# @example The matroid obtained from PG(2,3) is ternary. Its cannonical representation are the 13 points in PG(2,3).
# > print pg23_matroid()->TERNARY_VECTORS;
# | 1 0 0
# | 0 1 0
# | 1 1 0
# | 0 0 1
# | 1 -1 1
# | 1 -1 -1
# | 1 0 -1
# | 1 1 1
# | 0 1 -1
# | 1 0 1
# | 1 1 -1
# | 0 1 1
# | 1 -1 0
property TERNARY_VECTORS : Matrix<Int>;

# @category Realizability
# Whether the matroid is representable over every field, that is the repesentation is unimodular.
# NOTE: the property my be 'undef' when polymake is unable to decide whether the matroid is regular.
# @example The fano matroid is not representable over GF(3), hence it is not regular.
# > print fano_matroid()->REGULAR;
# | false
property REGULAR : Bool;


## ADVANCED PROPERTIES ###

# @category Advanced properties
# Loops are one element dependent sets, i.e. they correspond to elements which are not included in any basis.
# @example All elements in the uniform matroid of rank 0 are loops.
# > print uniform_matroid(0,4)->LOOPS;
# | {0 1 2 3}
property LOOPS : Set;

# @category Advanced properties
# Polytope whose vertices are the characteristic vectors of the bases.
# @example The polytope of the uniform matroid of rank 1 on 4 elements is the standard 3-simplex.
# > print uniform_matroid(1,4)->POLYTOPE->VERTICES;
# | 1 1 0 0 0
# | 1 0 1 0 0
# | 1 0 0 1 0
# | 1 0 0 0 1
property POLYTOPE : polytope::Polytope;

# @category Advanced properties
# If the matroid is transversal,
# this is the unique maximal presentation. I.e. the set system consists of [[RANK]] many sets and none of the
# sets can be increased without changing the matroid.
# @example The uniform matroid of rank 2 on 4 elements has a transversal representation.
# > print uniform_matroid(2,4)->MAXIMAL_TRANSVERSAL_PRESENTATION;
# | {0 1 2 3}
# | {0 1 2 3}
property MAXIMAL_TRANSVERSAL_PRESENTATION : IncidenceMatrix;

# @category Advanced properties
# Whether the m atroid is transversal, i.e., has a transversal presentation.
# @example The uniform matroid of rank 2 on 4 elements is transversal.
# > print uniform_matroid(2,4)->TRANSVERSAL;
# | true
property TRANSVERSAL : Bool;

# @category Advanced properties
# Whether the matroid is nested, i.e., its [[LATTICE_OF_CYCLIC_FLATS]] forms a chain.
# @example All uniform matroids are nested.
# > print uniform_matroid(2,4)->NESTED;
# | true
property NESTED : Bool;

# @category Advanced properties
# Whether the matroid is paving, i.e. every circuit is at least as large as the matroid's rank.
# @example All uniform matroids are paving.
# > print uniform_matroid(2,4)->PAVING;
# | true
property PAVING : Bool;

# @category Advanced properties
# Whether the matroid is a uniform matroid.
# @example
# > print uniform_matroid(2,4)->UNIFORM;
# | true
property UNIFORM : Bool;

# @category Advanced properties
# Whether the matroid is isomorphic to its dual
# If you want to check whether it is actually equal (not just isomorphic), ask for
# [[IDENTICALLY_SELF_DUAL]].
# @example The Vámos matroid is self dual.
# > print vamos_matroid()->SELF_DUAL;
# | true
property SELF_DUAL : Bool;

# @category Advanced properties
# Whether the matroid is equal to its dual. Note that this does not check for isomorphy,
# if you want to check whether the matroid is isomorphic to its dual, ask for
# [[SELF_DUAL]].
# @example The Vámos matroid is not identically self dual.
# > print vamos_matroid()->IDENTICALLY_SELF_DUAL;
# | false
property IDENTICALLY_SELF_DUAL : Bool;

# @category Advanced properties
# The Tutte polynomial of a matroid.
# It is a polynomial in the two variables x and y, which are chosen such that the tutte polynomial
# of a single coloop is x and the tutte polynomial of a single loop is y.
# @example The following computes the tutte polynomial of the fano matroid.
# > print fano_matroid()->TUTTE_POLYNOMIAL;
# | x_0^3 + 4*x_0^2 + 7*x_0*x_1 + 3*x_0 + x_1^4 + 3*x_1^3 + 6*x_1^2 + 3*x_1
property TUTTE_POLYNOMIAL : common::Polynomial;

# @category Advanced properties
# The G-invariant of the matroid (see [Derksen: Symmetric and quasi-symmetric functions associated to polymatroids, J. Algebr. Comb. 30 (2009), 43-86])
# We use the formulation by Bonin and Kung in [Bonin, Kung: The G-invariant and catenary data of a matroid (2015)]:
# The G-invariant is an element of the free abelian group over all (n,r)-sequences (where n = [[N_ELEMENTS]] and r = [[RANK]]), i.e. 0/1-sequences (r_1,...,r_n), where exactly r entries are 1. We identify each such sequence with its support, i.e. the set of entries equal to 1, so the G-invariant can be represented as a map which takes
# an r-set to the coefficient of the corresponding (n,r)-sequence.
# The formal definition goes as follows: For each permutation p on n, we define a sequence r(p) = (r_1,...,r_n)
# by r_1 = rank({p(1)}) and r_j = rank( {p(1),...,p(j)}) - rank( {p(1),...,p(j-1)}). Then
# G(M) := sum_p r(p), where the sum runs over all permutations p.
# @example The folowing computes the G-invariant of the fano matroid.
# > print fano_matroid()->G_INVARIANT;
# | {({0 1 2} 4032) ({0 1 3} 1008)}
property G_INVARIANT : Map< Set<Int>, Integer>;

# @category Advanced properties
# This is an equivalent characterization of the [[G_INVARIANT]] given by Bonin and Kung ([Bonin, Kung: The G-invariant and catenary data of a matroid (2015)]).
# It lives in the free abelian group over all (n,r)-compositions (where n = [[N_ELEMENTS]] and r = [[RANK]]).
# Those are sequences (a0,...,ar) with a0 >= 0, a_j > 0 for j > 0 and sum a_i = n
# For each maximal chain of flats F0,...,Fr = E of M, the corresponding composition is a0 = |F0| and a_i = |Fi \ Fi-1| for i > 0.
# For a composition a, let v(M,a) be the number of maximal chains of flats with composition a. Then
# G(M) := sum_a v(M,a) * a, where the sum runs over all compositions a.
# @example The folowing computes the catenary g invariant of the fano matroid.
# > print fano_matroid()->CATENARY_G_INVARIANT;
# | {(<0 1 2 4> 21)}
property CATENARY_G_INVARIANT : Map< Vector<Int>, Integer>;

# @category Advanced properties
# The coefficient of x of the [[TUTTE_POLYNOMIAL]].
# @example The following computes the beta invariant of the fano matroid.
# > print fano_matroid()->BETA_INVARIANT;
# | 3
property BETA_INVARIANT : Integer;

# @category Advanced properties
# Whether the matroid is connected
# @example The fano matroid is connected.
# > print fano_matroid()->CONNECTED;
# | true
property CONNECTED : Bool;

# @category Advanced properties
# The connected components
# @example Every edge of a star graph is a connected component in the sense of matroids (<-> 2-connected component in graphs).
# > print matroid_from_graph(graph::complete_bipartite(1,5))->CONNECTED_COMPONENTS;
# | {0}
# | {1}
# | {2}
# | {3}
# | {4}
property CONNECTED_COMPONENTS : Array<Set> {
   sub equal {
      defined(find_permutation(@_))
   }
}

# @category Advanced properties
# The number of [[CONNECTED_COMPONENTS]]
# @example Every edge of a star graph is a connected component in the sense of matroids (<-> 2-connected component in graphs).
# > print matroid_from_graph(graph::complete_bipartite(1,5))->N_CONNECTED_COMPONENTS;
# | 5
property N_CONNECTED_COMPONENTS : Int;

# @category Advanced properties
# Whether the matroid is series-parallel
# @example Every cycle graph is series parallel.
# > print matroid_from_graph(graph::cycle_graph(5))->SERIES_PARALLEL;
# | true
property SERIES_PARALLEL : Bool;

# @category Advanced properties
# Whether the matroid is simple.
# @example The Fano Matroid is simple.
# > print fano_matroid()->SIMPLE;
# | true
property SIMPLE : Bool;

# @category Advanced properties
# Whether the matroid is sparse paving, i.e., both the matroid and its dual are paving.
# @example The Fano Matroid is sparse paving.
# > print fano_matroid()->SPARSE_PAVING;
# | true
property SPARSE_PAVING : Bool;

# @category Advanced properties
# Whether the matroid is laminar. This is the case if and only if for any two circuits C1,C2 with
# non-empty intersection, their closures are comparable (i.e. one contains the other)
# see also [Fife, Oxley: Laminar matroids. arXiv: 1606.08354]
# @example The fano matroid is not laminar. Any two lines in the fano plane correspond to circuits which are also flats. Neither line is a subset of the other.
# > print fano_matroid()->LAMINAR;
# | false
property LAMINAR : Bool;

# @category Advanced properties
# The flats that correspond to split facets of the matroid [[POLYTOPE]].
# The facets are either hypersimplex facets or splits
property SPLIT_FLACETS : Array<Array<Set>>;

# @category Advanced properties
# Whether all SPLIT_FLACETS in the matroid are compatible.
property SPLIT : Bool;

# @category Advanced properties
# Whether the matroid is a positroid.
# Warning: This property is not preserved under matroid isomorphisms.
property POSITROID : Bool;

# @category Advanced properties
# The h-vector of a matroid
# @example The following computes the h-vector of the Fano Matroid.
# > print fano_matroid()->H_VECTOR;
# | 1 4 10 13
property H_VECTOR : Vector<Integer>;

# @category Advanced properties
# The f-vector of a matroid
# @example The following computes the f-vector of the Fano Matroid.
# > print fano_matroid()->F_VECTOR;
# | 7 21 28
property F_VECTOR : Vector<Integer>;

# @category Advanced properties
# A string listing the bases in revlex order. A '*' means the basis is present, a '0' that it is absent
# @example The uniform matroid contains all bases of the same order. The Fano Matroid only contains some of the bases.
# > print uniform_matroid(2,4)->REVLEX_BASIS_ENCODING;
# | ******
# > print fano_matroid()->REVLEX_BASIS_ENCODING;
# | ***0***0***0*****0**0*******0****0*
property REVLEX_BASIS_ENCODING : String;

# @category Advanced properties
# The automorphism group of the matroid, operating on the ground set.
# @example Any two points in the fano plane may be exchanged, i.e. the group action on the groundset is transitive.
# > print fano_matroid()->AUTOMORPHISM_GROUP->PERMUTATION_ACTION->ORBITS;
# | {0 1 2 3 4 5 6}
property AUTOMORPHISM_GROUP : group::Group;


## INPUT PROPERTIES AND OTHER STUFF ###

# @category Other
# Unique names assigned to the elements of the matroid.
#
# For a matroid built from scratch, you should create this property by yourself.
# the labels may be assigned for you in a meaningful way.
# If you build the matroid with a construction client, (e.g. [[matroid_from_graph]])
# the labels may be assigned for you in a meaningful way.
# @example The labels of a graphic matroid are the edges.
# > print matroid_from_graph(graph::cycle_graph(4))->LABELS;
# | {1 0} {2 1} {3 0} {3 2}
property LABELS : Array<String> : mutable;

# @category Input properties
# A transversal matroid can be defined via a multiset of subsets of the ground set (0,...,n-1)
# (i.e., [[N_ELEMENTS]] needs to be specified). The nodes of one parititon correspond to the
# subsets in the multiset. These nodes are adjacent to the elements specified inside their
# corresponding sets.
# Its bases are the maximal matchings of the bipartite incidence graph.
# @example A transveral presentation of the uniform matroid of rank 2 on 4 elements corresponds to a complete bipartite graph with partitions of size 2 and 4.
# > $m = new Matroid(N_ELEMENTS=>4, TRANSVERSAL_PRESENTATION=>[[0,1,2,3],[0,1,2,3]]);
# > print $m->RANK;
# | 2
# > print $m->UNIFORM;
# | true
property TRANSVERSAL_PRESENTATION : Array<Set<Int>>;

}

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