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r""" Similarity class types of matrices with entries in a finite field
The notion of a matrix conjugacy class type was introduced by J. A. Green in [Green55]_, in the context of computing the irreducible characters of finite general linear groups. The class types are equivalence classes of similarity classes of square matrices with entries in a finite field which, roughly speaking, have the same qualitative properties.
For example, all similarity classes of the same class type have centralizers of the same cardinality and the same degrees of elementary divisors. Qualitative properties of similarity classes such as semisimplicity and regularity descend to class types.
The most important feature of similarity class types is that, for any `n`, the number of similarity class types of `n\times n` matrices is independent of `q`. This makes it possible to perform many combinatorial calculations treating `q` as a formal variable.
In order to define similarity class types, recall that similarity classes of `n\times n` matrices with entries in `\GF{q}` correspond to functions
.. MATH::
c: \mathrm{Irr}\GF{q[t]} \to \Lambda
such that
.. MATH::
\sum_{f\in \mathrm{Irr}\GF{q[t]}} |c(f)|\deg f = n,
where we denote the set of irreducible monic polynomials in `\GF{q[t]}` by `\mathrm{Irr}\GF{q[t]}`, the set of all partitions by `\Lambda`, and the size of `\lambda \in \Lambda` by `|\lambda|`.
Similarity classes indexed by functions `c_1` and `c_2` as above are said to be of the same type if there exists a degree-preserving self-bijection `\sigma` of `\mathrm{Irr}\GF{q[t]}` such that `c_2 = c_1\circ \sigma`. Thus, the type of `c` remembers only the degrees of the polynomials (and not the polynomials themselves) for which `c` takes a certain value `\lambda`. Replacing each irreducible polynomial of degree `d` for which `c` takes a non-trivial value `\lambda` by the pair `(d, \lambda)`, we obtain a multiset of such pairs. Clearly, `c_1` and `c_2` have the same type if and only if these multisets are equal. Thus a similarity class type may be viewed as a multiset of pairs of the form `(d, \lambda)`.
For `2 \times 2` matrices there are four types::
sage: for tau in SimilarityClassTypes(2): ....: print(tau) [[1, [1]], [1, [1]]] [[1, [2]]] [[1, [1, 1]]] [[2, [1]]]
These four types correspond to the regular split semisimple matrices, the non-semisimple matrices, the central matrices and the irreducble matrices respectively.
For any matrix `A` in a given similarity class type, it is possible to calculate the number elements in the similarity class of `A`, the dimension of the algebra of matrices in `M_n(A)` that commite with `A`, and the cardinality of the subgroup of `GL_n(\GF{q})` that commute with `A`. For each similarity class type, it is also possible to compute the number of classes of that type (and hence, the total number of matrices of that type). All these calculations treat the cardinality `q` of the finite field as a formal variable::
sage: M = SimilarityClassType([[1, [1]], [1, [1]]]) sage: M.class_card() q^2 + q sage: M.centralizer_algebra_dim() 2 sage: M.centralizer_group_card() q^2 - 2*q + 1 sage: M.number_of_classes() 1/2*q^2 - 1/2*q sage: M.number_of_matrices() 1/2*q^4 - 1/2*q^2
We now describe two applications of similarity class types.
We say that an `n \times n` matrix has rational canonical form type `\lambda` for some partition `\lambda` of `n` if the diagonal blocks in the rational canonical form have sizes given by the parts of `\lambda`. Thus the matrices with rational canonical type `(n)` are the regular ones, while the matrices with rational canonical type `(1^n)` are the central ones.
Using similarity class types, it becomes easy to get a formula for the number of matrices with a given rational canonical type::
sage: def matrices_with_rcf(la): ....: return sum([tau.number_of_matrices() for tau in filter(lambda tau:tau.rcf()==la, SimilarityClassTypes(la.size()))]) sage: matrices_with_rcf(Partition([2,1])) q^6 + q^5 + q^4 - q^3 - q^2 - q
Similarity class types can also be used to calculate the number of simultaneous similarity classes of `k`-tuples of `n\times n` matrices with entries in `\GF{q}` by using Burnside's lemma::
sage: from sage.combinat.similarity_class_type import order_of_general_linear_group, centralizer_algebra_dim sage: q = ZZ['q'].gen() sage: def simultaneous_similarity_classes(n,k): ....: return SimilarityClassTypes(n).sum(lambda la: q**(k*centralizer_algebra_dim(la)), invertible = True)/order_of_general_linear_group(n) sage: simultaneous_similarity_classes(3, 2) q^10 + q^8 + 2*q^7 + 2*q^6 + 2*q^5 + q^4
Similarity class types can be used to calculate the coefficients of generating functions coming from the cycle index type techniques of Kung and Stong (see Morrison [Morrison06]_).
Along with the results of [PSS13]_, similarity class types can be used to calculate the number of similarity classes of matrices of order `n` with entries in a principal ideal local ring of length two with residue field of cardinality `q` with centralizer of any given cardinality up to `n = 4`. Among these, the classes which are selftranspose can also be counted::
sage: from sage.combinat.similarity_class_type import matrix_centralizer_cardinalities_length_two sage: list(matrix_centralizer_cardinalities_length_two(3)) [(q^6 - 3*q^5 + 3*q^4 - q^3, 1/6*q^6 - 1/2*q^5 + 1/3*q^4), (q^6 - 2*q^5 + q^4, q^5 - q^4), (q^8 - 3*q^7 + 3*q^6 - q^5, 1/2*q^5 - q^4 + 1/2*q^3), (q^8 - 2*q^7 + q^6, q^4 - q^3), (q^10 - 2*q^9 + 2*q^7 - q^6, q^4 - q^3), (q^8 - q^7 - q^6 + q^5, 1/2*q^5 - q^4 + 1/2*q^3), (q^6 - q^5 - q^4 + q^3, 1/2*q^6 - 1/2*q^5), (q^6 - q^5, q^4), (q^10 - 2*q^9 + q^8, q^3), (q^8 - 2*q^7 + q^6, q^4 - q^3), (q^8 - q^7, q^3 + q^2), (q^12 - 3*q^11 + 3*q^10 - q^9, 1/6*q^4 - 1/2*q^3 + 1/3*q^2), (q^12 - 2*q^11 + q^10, q^3 - q^2), (q^14 - 2*q^13 + 2*q^11 - q^10, q^3 - q^2), (q^12 - q^11 - q^10 + q^9, 1/2*q^4 - 1/2*q^3), (q^12 - q^11, q^2), (q^14 - 2*q^13 + q^12, q^2), (q^18 - q^17 - q^16 + q^14 + q^13 - q^12, q^2), (q^12 - q^9, 1/3*q^4 - 1/3*q^2), (q^6 - q^3, 1/3*q^6 - 1/3*q^4)]
REFERENCES:
.. [Green55] Green, J. A. *The characters of the finite general linear groups*. Trans. Amer. Math. Soc. 80 (1955), 402--447. :doi:`10.1090/S0002-9947-1955-0072878-2`
.. [Morrison06] Morrison, Kent E. *Integer sequences and matrices over finite fields*. J. Integer Seq. 9 (2006), no. 2, Article 06.2.1, 28 pp. https://cs.uwaterloo.ca/journals/JIS/VOL9/Morrison/morrison37.html
.. [PSS13] Prasad, A., Singla, P., and Spallone, S., *Similarity of matrices over local rings of length two*. :arxiv:`1212.6157`
AUTHOR:
- Amritanshu Prasad (2013-07-18): initial implementation
- Amritanshu Prasad (2013-09-09): added functions for similarity classes over rings of length two
""" #***************************************************************************** # Copyright (C) 2013 Amritanshu Prasad <amri@imsc.res.in> # # Distributed under the terms of the GNU General Public License (GPL) # # This code 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. # # The full text of the GPL is available at: # # http://www.gnu.org/licenses/ #***************************************************************************** from __future__ import print_function from six.moves import range from six import add_metaclass
from operator import mul from itertools import chain, product from sage.misc.all import prod from sage.functions.all import factorial from sage.arith.all import moebius, divisors from sage.misc.inherit_comparison import InheritComparisonClasscallMetaclass from sage.structure.element import Element from sage.structure.parent import Parent from sage.structure.unique_representation import UniqueRepresentation from sage.categories.finite_enumerated_sets import FiniteEnumeratedSets from sage.combinat.combinat import CombinatorialElement from sage.combinat.partition import Partitions, Partition from sage.rings.all import ZZ, QQ, FractionField from sage.misc.cachefunc import cached_in_parent_method, cached_function from sage.combinat.misc import IterableFunctionCall from functools import reduce
@cached_function def fq(n, q = None): """ Return `(1-q^{-1}) (1-q^{-2}) \cdots (1-q^{-n})`.
INPUT:
- ``n`` -- A non-negative integer
- ``q`` -- an integer or an indeterminate
OUTPUT:
A rational function in ``q``.
EXAMPLES::
sage: from sage.combinat.similarity_class_type import fq sage: fq(0) 1 sage: fq(3) (q^6 - q^5 - q^4 + q^2 + q - 1)/q^6 """
@cached_function def primitives(n, invertible = False, q = None): """ Return the number of similarity classes of simple matrices of order ``n`` with entries in a finite field of order ``q``. This is the same as the number of irreducible polynomials of degree `d`.
If ``invertible`` is ``True``, then only the number of similarity classes of invertible matrices is returned.
.. NOTE::
All primitive classes are invertible unless ``n`` is `1`.
INPUT:
- ``n`` -- a positive integer
- ``invertible`` -- boolean; if set, only number of non-zero classes is returned
- ``q`` -- an integer or an indeterminate
OUTPUT:
- a rational function of the variable ``q``
EXAMPLES::
sage: from sage.combinat.similarity_class_type import primitives sage: primitives(1) q sage: primitives(1, invertible = True) q - 1 sage: primitives(4) 1/4*q^4 - 1/4*q^2 sage: primitives(4, invertible = True) 1/4*q^4 - 1/4*q^2 """ else:
@cached_function def order_of_general_linear_group(n, q = None): r""" Return the cardinality of the group of `n \times n` invertible matrices with entries in a field of order ``q``.
INPUT:
- ``n`` -- a non-negative integer
- ``q`` -- an integer or an indeterminate
EXAMPLES::
sage: from sage.combinat.similarity_class_type import order_of_general_linear_group sage: order_of_general_linear_group(0) 1 sage: order_of_general_linear_group(2) q^4 - q^3 - q^2 + q """
@cached_function def centralizer_algebra_dim(la): r""" Return the dimension of the centralizer algebra in `M_n(\GF{q})` of a nilpotent matrix whose Jordan blocks are given by ``la``.
EXAMPLES::
sage: from sage.combinat.similarity_class_type import centralizer_algebra_dim sage: centralizer_algebra_dim(Partition([2, 1])) 5
.. NOTE::
If it is a list, ``la`` is expected to be sorted in decreasing order. """
@cached_function def centralizer_group_cardinality(la, q = None): r""" Return the cardinality of the centralizer group in `GL_n(\GF{q})` of a nilpotent matrix whose Jordan blocks are given by ``la``.
INPUT:
- ``lambda`` -- a partition
- ``q`` -- an integer or an indeterminate
OUTPUT:
A polynomial function of ``q``.
EXAMPLES::
sage: from sage.combinat.similarity_class_type import centralizer_group_cardinality sage: q = ZZ['q'].gen() sage: centralizer_group_cardinality(Partition([2, 1])) q^5 - 2*q^4 + q^3 """
@add_metaclass(InheritComparisonClasscallMetaclass) class PrimarySimilarityClassType(Element): r""" A primary similarity class type is a pair consisting of a partition and a positive integer.
For a partition `\lambda` and a positive integer `d`, the primary similarity class type `(d, \lambda)` represents similarity classes of square matrices of order `|\lambda| \cdot d` with entries in a finite field of order `q` which correspond to the `\GF{q[t]}`-module
.. MATH::
\frac{\GF{q[t]}}{p(t)^{\lambda_1} } \oplus \frac{\GF{q[t]}}{p(t)^{\lambda_2}} \oplus \dotsb
for some irreducible polynomial `p(t)` of degree `d`. """ @staticmethod def __classcall_private__(cls, deg, par): r""" Create a primary similarity class type.
EXAMPLES::
sage: PrimarySimilarityClassType(2, [3, 2, 1]) [2, [3, 2, 1]]
The parent class is the class of primary similarity class types of order `d |\lambda|`::
sage: PT = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT.parent().size() 12 """
def __init__(self, parent, deg, par): """ Initialize ``self``.
EXAMPLES::
sage: elt = PrimarySimilarityClassType(2, [3, 2, 1]) sage: TestSuite(elt).run() """
def __repr__(self): """ Return string representation of ``self``.
EXAMPLES::
sage: PrimarySimilarityClassType(2, [3, 2, 1]) [2, [3, 2, 1]] """
def __hash__(self): r""" TESTS::
sage: PT1 = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT2 = PrimarySimilarityClassType(3, [3, 2, 1]) sage: PT3 = PrimarySimilarityClassType(2, [4, 2, 1]) sage: hash(PT1) 5050909583595644741 # 64-bit 1658169157 # 32-bit sage: hash(PT2) 5050909583595644740 # 64-bit 1658169156 # 32-bit sage: hash(PT3) 6312110366011971308 # 64-bit 1429493484 # 32-bit """
def __eq__(self, other): """ Check equality.
EXAMPLES::
sage: PT1 = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT2 = PrimarySimilarityClassType(2, Partition([3, 2, 1])) sage: PT1 == PT2 True sage: PT3 = PrimarySimilarityClassType(3, [3, 2, 1]) sage: PT1 == PT3 False sage: PT4 = PrimarySimilarityClassType(2, [3, 2, 1, 0]) sage: PT1 == PT4 True sage: PT5 = PrimarySimilarityClassType(2, [4, 2, 1]) sage: PT1 == PT5 False """ self.degree() == other.degree() and \ self.partition() == other.partition()
def __ne__(self, other): r""" TESTS::
sage: PT1 = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT2 = PrimarySimilarityClassType(2, Partition([3, 2, 1])) sage: PT1 != PT2 False sage: PT3 = PrimarySimilarityClassType(3, [3, 2, 1]) sage: PT1 != PT3 True """ self.degree() != other.degree() or \ self.partition() != other.partition()
def size(self): """ Return the size of ``self``.
EXAMPLES::
sage: PT = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT.size() 12 """
def degree(self): """ Return degree of ``self``.
EXAMPLES::
sage: PT = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT.degree() 2 """
def partition(self): """ Return partition corresponding to ``self``.
EXAMPLES::
sage: PT = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT.partition() [3, 2, 1] """
def centralizer_algebra_dim(self): r""" Return the dimension of the algebra of matrices which commute with a matrix of type ``self``.
For a partition `(d, \lambda)` this dimension is given by `d(\lambda_1 + 3\lambda_2 + 5\lambda_3 + \cdots)`.
EXAMPLES::
sage: PT = PrimarySimilarityClassType(2, [3, 2, 1]) sage: PT.centralizer_algebra_dim() 28 """
@cached_in_parent_method def statistic(self, func, q = None): r""" Return `n_{\lambda}(q^d)` where `n_{\lambda}` is the value returned by ``func`` upon input `\lambda`, if ``self`` is `(d, \lambda)`.
EXAMPLES::
sage: PT = PrimarySimilarityClassType(2, [3, 1]) sage: q = ZZ['q'].gen() sage: PT.statistic(lambda la:q**la.size(), q = q) q^8 """ q = ZZ['q'].gen()
@cached_in_parent_method def centralizer_group_card(self, q = None): """ Return the cardinality of the centralizer group of a matrix of type ``self`` in a field of order ``q``.
INPUT:
- ``q`` -- an integer or an indeterminate
EXAMPLES::
sage: PT = PrimarySimilarityClassType(1, []) sage: PT.centralizer_group_card() 1 sage: PT = PrimarySimilarityClassType(2, [1, 1]) sage: PT.centralizer_group_card() q^8 - q^6 - q^4 + q^2 """
class PrimarySimilarityClassTypes(UniqueRepresentation, Parent): r""" All primary similarity class types of size ``n`` whose degree is greater than that of ``min`` or whose degree is that of ``min`` and whose partition is less than of ``min`` in lexicographic order.
A primary similarity class type of size `n` is a pair `(\lambda, d)` consisting of a partition `\lambda` and a positive integer `d` such that `|\lambda| d = n`.
INPUT:
- ``n`` -- a positive integer - ``min`` -- a primary matrix type of size ``n``
EXAMPLES:
If ``min`` is not specified, then the class of all primary similarity class types of size ``n`` is created::
sage: PTC = PrimarySimilarityClassTypes(2) sage: for PT in PTC: ....: print(PT) [1, [2]] [1, [1, 1]] [2, [1]]
If ``min`` is specified, then the class consists of only those primary similarity class types whose degree is greater than that of ``min`` or whose degree is that of ``min`` and whose partition is less than of ``min`` in lexicographic order::
sage: PTC = PrimarySimilarityClassTypes(2, min = PrimarySimilarityClassType(1, [1, 1])) sage: for PT in PTC: ....: print(PT) [1, [1, 1]] [2, [1]] """ @staticmethod def __classcall_private__(cls, n, min = None): r""" Create the class of vector partitions of ``vec`` where all parts are greater than or equal to the vector ``min``.
EXAMPLES::
sage: PTC1 = PrimarySimilarityClassTypes(2) sage: PTC2 = PrimarySimilarityClassTypes(2, min = PrimarySimilarityClassType(1, [2])) sage: PTC1 is PTC2 True """ else: raise ValueError("min must be a PrimarySimilarityClassType")
def __init__(self, n, min): r""" Initialize ``self``.
TESTS::
sage: PTC = PrimarySimilarityClassTypes(2) sage: TestSuite(PTC).run() """
def _element_constructor_(self, deg, par): """ Construct an element of ``self``.
INPUT:
- ``deg`` -- positive integer
- ``par`` -- a partition
EXAMPLES::
sage: PTC = PrimarySimilarityClassTypes(2) sage: elt = PTC(1, [1, 1]); elt [1, [1, 1]] sage: elt.parent() is PTC True """
Element = PrimarySimilarityClassType
def __iter__(self): r""" Iterate over ``self``.
EXAMPLES::
sage: PTC = PrimarySimilarityClassTypes(2) sage: PTC.cardinality() 3 """
def size(self): """ Return size of elements of ``self``.
The size of a primary similarity class type `(d, \lambda)` is `d |\lambda|`.
EXAMPLES::
sage: PTC = PrimarySimilarityClassTypes(2) sage: PTC.size() 2 """
###############################################################################
###############################################################################
class SimilarityClassType(CombinatorialElement): r""" A similarity class type.
A matrix type is a multiset of primary similarity class types.
INPUT:
- ``tau`` -- A list of primary similarity class types
EXAMPLES::
sage: tau1 = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]); tau1 [[2, [2, 1]], [3, [3, 2, 1]]] """ @staticmethod def __classcall_private__(cls, tau): """ Create a similarity class type.
EXAMPLES:
The input can be a list of lists or a list of primary similarity class types, and the order in which this list is given does not matter::
sage: tau1 = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]); tau1 [[2, [2, 1]], [3, [3, 2, 1]]] sage: types = [PrimarySimilarityClassType(2, [2, 1]), PrimarySimilarityClassType(3, [3, 2, 1])] sage: tau2 = SimilarityClassType(types) sage: tau1 == tau2 True
The parent class is the class of similarity class types of the sum of the sizes of the primary matrix types in ``tau``::
sage: tau = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]) sage: tau.parent().size() 24 """ else:
def __init__(self, parent, tau): """ Initialize ``self``.
EXAMPLES::
sage: elt = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]) sage: TestSuite(elt).run() """
def size(self): """ Return the sum of the sizes of the primary parts of ``self``.
EXAMPLES::
sage: tau = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]) sage: tau.size() 24 """
def centralizer_algebra_dim(self): """ Return the dimension of the algebra of matrices which commute with a matrix of type ``self``.
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.centralizer_algebra_dim() 2 """
def centralizer_group_card(self, q = None): """ Return the cardinality of the group of matrices in `GL_n(\GF{q})` which commute with a matrix of type ``self``.
INPUT:
- ``q`` -- an integer or an indeterminate
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.centralizer_group_card() q^2 - 2*q + 1 """
def as_partition_dictionary(self): r""" Return a dictionary whose keys are the partitions of types occuring in ``self`` and the value at the key `\lambda` is the partition formed by sorting the degrees of primary types with partition `\lambda`.
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.as_partition_dictionary() {[1]: [1, 1]} """ else:
def number_of_classes(self, invertible = False, q = None): """ Return the number of similarity classes of matrices of type ``self``.
INPUT:
- ``invertible`` -- Boolean; return number of invertible classes if set to ``True``
- ``q`` -- An integer or an indeterminate
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.number_of_classes() 1/2*q^2 - 1/2*q """
def is_semisimple(self): """ Return ``True`` if every primary similarity class type in ``self`` has all parts equal to ``1``.
EXAMPLES::
sage: tau = SimilarityClassType([[2, [1, 1]], [1, [1]]]) sage: tau.is_semisimple() True sage: tau = SimilarityClassType([[2, [1, 1]], [1, [2]]]) sage: tau.is_semisimple() False """
def is_regular(self): """ Return ``True`` if every primary type in ``self`` has partition with one part.
EXAMPLES::
sage: tau = SimilarityClassType([[2, [1]], [1, [3]]]) sage: tau.is_regular() True sage: tau = SimilarityClassType([[2, [1, 1]], [1, [3]]]) sage: tau.is_regular() False """
def rcf(self): """ Return the partition corresponding to the rational canonical form of a matrix of type ``self``.
EXAMPLES::
sage: tau = SimilarityClassType([[2, [1, 1, 1]], [1, [3, 2]]]) sage: tau.rcf() [5, 4, 2] """ else:
def class_card(self, q = None): """ Return the number of matrices in each similarity class of type ``self``.
INPUT:
- ``q`` -- an integer or an indeterminate
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1, 1, 1, 1]]]) sage: tau.class_card() 1 sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.class_card() q^2 + q """
def number_of_matrices(self, invertible = False, q = None): """ Return the number of matrices of type ``self``.
INPUT:
- ``invertible`` -- A boolean; return the number of invertible matrices if set
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]]]) sage: tau.number_of_matrices() q sage: tau.number_of_matrices(invertible = True) q - 1 sage: tau = SimilarityClassType([[1, [1]], [1, [1]]]) sage: tau.number_of_matrices() 1/2*q^4 - 1/2*q^2 """
def statistic(self, func, q = None): r""" Return
.. MATH::
\prod_{(d, \lambda)\in \tau} n_{\lambda}(q^d)
where `n_{\lambda}(q)` is the value returned by ``func`` on the input `\lambda`.
INPUT:
- ``func`` -- a function that takes a partition to a polynomial in ``q``
- ``q`` -- an integer or an indeterminate
EXAMPLES::
sage: tau = SimilarityClassType([[1, [1]], [1, [2, 1]], [2, [1, 1]]]) sage: from sage.combinat.similarity_class_type import fq sage: tau.statistic(lambda la: prod([fq(m) for m in la.to_exp()])) (q^9 - 3*q^8 + 2*q^7 + 2*q^6 - 4*q^5 + 4*q^4 - 2*q^3 - 2*q^2 + 3*q - 1)/q^9 sage: q = ZZ['q'].gen() sage: tau.statistic(lambda la: q**la.size(), q = q) q^8 """
class SimilarityClassTypes(UniqueRepresentation, Parent): r""" Class of all similarity class types of size ``n`` with all primary matrix types greater than or equal to the primary matrix type ``min``.
A similarity class type is a multiset of primary matrix types.
INPUT:
- ``n`` -- a non-negative integer - ``min`` -- a primary similarity class type
EXAMPLES:
If ``min`` is not specified, then the class of all matrix types of size ``n`` is constructed::
sage: M = SimilarityClassTypes(2) sage: for tau in M: ....: print(tau) [[1, [1]], [1, [1]]] [[1, [2]]] [[1, [1, 1]]] [[2, [1]]]
If ``min`` is specified, then the class consists of only those similarity class types which are multisets of primary matrix types which either have size greater than that of ``min``, or if they have size equal to that of ``min``, then they occur after ``min`` in the iterator for ``PrimarySimilarityClassTypes(n)``, where ``n`` is the size of ``min``::
sage: M = SimilarityClassTypes(2, min = [1, [1, 1]]) sage: for tau in M: ....: print(tau) [[1, [1, 1]]] [[2, [1]]] """ @staticmethod def __classcall_private__(cls, n, min = None): r""" Create the class of similarity class types of size ``n`` consisting of primary similarity class types greater than or equal to ``min``.
EXAMPLES::
sage: M1 = SimilarityClassTypes(2, min = [1, [1]]) sage: M2 = SimilarityClassTypes(2) sage: M1 is M2 True """ raise ValueError("min must be a PrimarySimilarityClassType")
def __init__(self, n, min): r""" Initialize ``self``.
TESTS::
sage: M = SimilarityClassTypes(2) sage: TestSuite(M).run() """
def _element_constructor_(self, tau): """ Construct an element of ``self``.
INPUT:
- ``tau`` -- a list of primary similarity class types
EXAMPLES::
sage: M = SimilarityClassTypes(2) sage: elt = M([[1, [1]], [1, [1]]]); elt [[1, [1]], [1, [1]]] sage: elt.parent() is M True """ else:
Element = SimilarityClassType
def __iter__(self): r""" Iterator for vector partitions.
EXAMPLES::
sage: SimilarityClassTypes(3).cardinality() 8
A good test of the iterator is to see that all elements of `M_n(\GF{q})` or `GL_n(\GF{q})` are enumerated through types::
sage: from sage.combinat.similarity_class_type import order_of_general_linear_group sage: q = QQ['q'].gen() sage: def test(n): ....: M = SimilarityClassTypes(n) ....: return M.sum(lambda la:1) == q**(n**2) and M.sum(lambda la:1, invertible = True)== order_of_general_linear_group(n) sage: all(test(n) for n in range(5)) True sage: all(test(n) for n in range(5, 15)) # long time True """ else: else:# recursively find all possibilties for what remains of n
def size(self): """ Return size of ``self``.
EXAMPLES::
sage: tau = SimilarityClassType([[3, [3, 2, 1]], [2, [2, 1]]]) sage: tau.parent().size() 24 """
def sum(self, stat, sumover = "matrices", invertible = False, q = None): r""" Return the sum of a local statistic over all types.
Given a set of functions `n_{\lambda}(q)` (these could be polynomials or rational functions in `q`, for each similarity class type `\tau` define
.. MATH::
n_\tau(q) = \prod_{(d,\lambda)\in \tau} n_{\lambda}(q^d).
This function returns
.. MATH::
\sum n_{\tau(g)}(q)
where `\tau(g)` denotes the type of a matrix `g`, and the sum is over all `n \times n` matrices if ``sumover`` is set to ``"matrices"``, is over all `n \times n` similarity classes if ``sumover`` is set to ``"classes"``, and over all `n \times n` types if ``sumover`` is set to ``"types"``. If ``invertible`` is set to ``True``, then the sum is only over invertible matrices or classes.
INPUT:
- ``stat`` -- a function which takes partitions and returns a function of ``q`` - ``sumover`` -- can be one of the following:
* ``"matrices"`` * ``"classes"`` * ``"types"``
- ``q`` -- an integer or an indeterminate
OUTPUT:
A function of ``q``.
EXAMPLES::
sage: M = SimilarityClassTypes(2) sage: M.sum(lambda la:1) q^4 sage: M.sum(lambda la:1, invertible = True) q^4 - q^3 - q^2 + q sage: M.sum(lambda la:1, sumover = "classes") q^2 + q sage: M.sum(lambda la:1, sumover = "classes", invertible = True) q^2 - 1
Burside's lemma can be used to calculate the number of similarity classes of matrices::
sage: from sage.combinat.similarity_class_type import centralizer_algebra_dim, order_of_general_linear_group sage: q = ZZ['q'].gen() sage: M.sum(lambda la:q**centralizer_algebra_dim(la), invertible = True)/order_of_general_linear_group(2) q^2 + q """ elif sumover == "types": return sum([tau.statistic(stat, invertible = invertible, q = q) for tau in self]) else: raise ValueError("invalid parameter %s"%(sumover))
################################################################################ # Similarity over rings of length two # ################################################################################
def dictionary_from_generator(gen): r""" Given a generator for a list of pairs `(c,f)`, construct a dictionary whose keys are the distinct values for `c` and whose value at `c` is the sum of `f` over all pairs of the form `(c',f)` such that `c=c'`.
EXAMPLES::
sage: from sage.combinat.similarity_class_type import dictionary_from_generator sage: dictionary_from_generator(((floor(x/2), x) for x in range(10))) {0: 1, 1: 5, 2: 9, 3: 13, 4: 17}
It also works with lists::
sage: dictionary_from_generator([(floor(x/2),x) for x in range(10)]) {0: 1, 1: 5, 2: 9, 3: 13, 4: 17}
.. NOTE::
Since the generator is first converted to a list, memory usage could be high. """
def matrix_similarity_classes(n, q=None, invertible=False): r""" Return the number of matrix similarity classes over a finite field of order ``q``.
TESTS::
sage: from sage.combinat.similarity_class_type import matrix_similarity_classes sage: matrix_similarity_classes(2) q^2 + q sage: matrix_similarity_classes(2, invertible = True) q^2 - 1 sage: matrix_similarity_classes(2, invertible = True, q = 4) 15 """ return basering.one() tilde ** len([x for x in la.to_exp() if x > 0]) for la in Partitions(n))
def matrix_centralizer_cardinalities(n, q = None, invertible = False): """ Generate pairs consisting of centralizer cardinalities of matrices over a finite field and their frequencies.
TESTS::
sage: from sage.combinat.similarity_class_type import matrix_centralizer_cardinalities sage: list(matrix_centralizer_cardinalities(1)) [(q - 1, q)] sage: list(matrix_centralizer_cardinalities(2)) [(q^2 - 2*q + 1, 1/2*q^2 - 1/2*q), (q^2 - q, q), (q^4 - q^3 - q^2 + q, q), (q^2 - 1, 1/2*q^2 - 1/2*q)] sage: list(matrix_centralizer_cardinalities(2, invertible = True)) [(q^2 - 2*q + 1, 1/2*q^2 - 3/2*q + 1), (q^2 - q, q - 1), (q^4 - q^3 - q^2 + q, q - 1), (q^2 - 1, 1/2*q^2 - 1/2*q)] """
def input_parsing(data): """ Recognize and return the intended type of ``input``.
TESTS::
sage: from sage.combinat.similarity_class_type import input_parsing sage: input_parsing(Partition([2, 1])) ('par', [2, 1]) sage: input_parsing(PrimarySimilarityClassType(2, [2, 1])) ('pri', [2, [2, 1]]) sage: input_parsing(SimilarityClassType([[2, [2, 1]]])) ('sim', [[2, [2, 1]]]) sage: input_parsing([2, 1]) ('par', [2, 1]) sage: input_parsing([2, [2, 1]]) ('pri', [2, [2, 1]]) sage: input_parsing([[2, [2, 1]]]) ('sim', [[2, [2, 1]]]) """ else: except(TypeError, ValueError): raise ValueError("Expected a Partition, a SimilarityClassType or a PrimarySimilarityClassType, got a %s" % type(data))
def ext_orbits(input_data, q = None, selftranspose = False): r""" Return the number of orbits in `\mathrm{Ext}^1(M, M)` for the action of `\mathrm{Aut}(M, M)`, where `M` is the `\GF{q[t]}`-module constructed from ``input_data``.
INPUT:
- ``input_data`` -- input for :func:`input_parsing()` - ``q`` -- (default: `q`) an integer or an indeterminate - ``selftranspose`` -- (default: ``False``) boolean stating if we only want selftranspose type
TESTS::
sage: from sage.combinat.similarity_class_type import ext_orbits sage: ext_orbits([6, 1]) q^7 + q^6 + q^5 sage: ext_orbits([6, 1], selftranspose = True) q^7 + q^6 - q^5 sage: ext_orbits([6, 1, 1]) q^8 + 2*q^7 + 2*q^6 + 2*q^5 sage: ext_orbits ([6, 1, 1], selftranspose = True) q^8 + 2*q^7 sage: ext_orbits([2, 2]) q^4 + q^3 + q^2 sage: ext_orbits([2, 2], selftranspose = True) q^4 + q^3 + q^2 sage: ext_orbits([2, 2, 2]) q^6 + q^5 + 2*q^4 + q^3 + 2*q^2 sage: ext_orbits([2, 2, 2], selftranspose = True) q^6 + q^5 + 2*q^4 + q^3 sage: ext_orbits([2, 2, 2, 2]) q^8 + q^7 + 3*q^6 + 3*q^5 + 5*q^4 + 3*q^3 + 3*q^2 sage: ext_orbits([2, 2, 2, 2], selftranspose = True) q^8 + q^7 + 3*q^6 + 3*q^5 + 3*q^4 + q^3 + q^2 sage: ext_orbits([2, [6, 1]]) q^14 + q^12 + q^10 sage: ext_orbits([[2, [6, 1]]]) q^14 + q^12 + q^10 """ # Comments cite items in the paper "Similarity over rings of length two" by # Prasad, Singla, and Spallone. return q.parent()(1) else: else: else: raise ValueError('partition %s not implemented for ExtOrbitClasses.orbits'%(la))
def matrix_similarity_classes_length_two(n, q = None, selftranspose = False, invertible = False): """ Return the number of similarity classes of matrices of order ``n`` with entries in a principal ideal local ring of length two.
INPUT:
- ``n`` -- the order - ``q`` -- (default: `q`) an integer or an indeterminate - ``selftranspose`` -- (default: ``False``) boolean stating if we only want selftranspose type - ``invertible`` -- (default: ``False``) boolean stating if we only want invertible type
EXAMPLES:
We can generate Table 6 of [PSS13]_::
sage: from sage.combinat.similarity_class_type import matrix_similarity_classes_length_two sage: matrix_similarity_classes_length_two(2) q^4 + q^3 + q^2 sage: matrix_similarity_classes_length_two(2, invertible = True) q^4 - q sage: matrix_similarity_classes_length_two(3) q^6 + q^5 + 2*q^4 + q^3 + 2*q^2 sage: matrix_similarity_classes_length_two(3, invertible = true) q^6 - q^3 + 2*q^2 - 2*q sage: matrix_similarity_classes_length_two(4) q^8 + q^7 + 3*q^6 + 3*q^5 + 5*q^4 + 3*q^3 + 3*q^2 sage: matrix_similarity_classes_length_two(4, invertible = True) q^8 + q^6 - q^5 + 2*q^4 - 2*q^3 + 2*q^2 - 3*q
And also Table 7::
sage: matrix_similarity_classes_length_two(2, selftranspose = True) q^4 + q^3 + q^2 sage: matrix_similarity_classes_length_two(2, selftranspose = True, invertible = True) q^4 - q sage: matrix_similarity_classes_length_two(3, selftranspose = True) q^6 + q^5 + 2*q^4 + q^3 sage: matrix_similarity_classes_length_two(3, selftranspose = True, invertible = True) q^6 - q^3 sage: matrix_similarity_classes_length_two(4, selftranspose = True) q^8 + q^7 + 3*q^6 + 3*q^5 + 3*q^4 + q^3 + q^2 sage: matrix_similarity_classes_length_two(4, selftranspose = True, invertible = True) q^8 + q^6 - q^5 - q """
def ext_orbit_centralizers(input_data, q = None, selftranspose = False): r""" Generate pairs consisting of centralizer cardinalities of orbits in `\mathrm{Ext}^1(M, M)` for the action of `\mathrm{Aut}(M, M)`, where `M` is the `\GF{q[t]}`-module constructed from ``input`` and their frequencies.
INPUT:
- ``input_data`` -- input for :func:`input_parsing()` - ``q`` -- (default: `q`) an integer or an indeterminate - ``selftranspose`` -- (default: ``False``) boolean stating if we only want selftranspose type
TESTS::
sage: from sage.combinat.similarity_class_type import ext_orbit_centralizers sage: list(ext_orbit_centralizers([6, 1])) [(q^9 - 2*q^8 + q^7, q^6), (q^7 - 2*q^6 + q^5, q^7 - q^6), (q^7 - q^6, q^6 + q^5)] sage: list(ext_orbit_centralizers([6, 1], selftranspose = True)) [(q^9 - 2*q^8 + q^7, q^6), (q^7 - 2*q^6 + q^5, q^7 - q^6), (q^7 - q^6, q^6 - q^5)] sage: list(ext_orbit_centralizers([6, 1, 1])) [(q^12 - 3*q^11 + 3*q^10 - q^9, 1/2*q^7 - 1/2*q^6), (q^8 - 3*q^7 + 3*q^6 - q^5, 1/2*q^8 - q^7 + 1/2*q^6), (q^12 - 2*q^11 + q^10, q^6), (q^8 - 2*q^7 + q^6, q^7 - q^6), (q^14 - 2*q^13 + 2*q^11 - q^10, q^6), (q^10 - 2*q^9 + 2*q^7 - q^6, q^7 - q^6), (q^12 - q^11 - q^10 + q^9, 1/2*q^7 - 1/2*q^6), (q^8 - q^7 - q^6 + q^5, 1/2*q^8 - q^7 + 1/2*q^6), (q^8 - 2*q^7 + q^6, q^7 - q^6), (q^8 - q^7, q^6 + 2*q^5), (q^10 - 2*q^9 + q^8, 2*q^6)] sage: list(ext_orbit_centralizers([6, 1, 1], selftranspose = True)) [(q^12 - 3*q^11 + 3*q^10 - q^9, 1/2*q^7 - 1/2*q^6), (q^8 - 3*q^7 + 3*q^6 - q^5, 1/2*q^8 - q^7 + 1/2*q^6), (q^12 - 2*q^11 + q^10, q^6), (q^8 - 2*q^7 + q^6, q^7 - q^6), (q^14 - 2*q^13 + 2*q^11 - q^10, q^6), (q^10 - 2*q^9 + 2*q^7 - q^6, q^7 - q^6), (q^12 - q^11 - q^10 + q^9, 1/2*q^7 - 1/2*q^6), (q^8 - q^7 - q^6 + q^5, 1/2*q^8 - q^7 + 1/2*q^6), (q^8 - 2*q^7 + q^6, q^7 - q^6), (q^8 - q^7, q^6)] sage: list(ext_orbit_centralizers([2, [6, 1, 1]], selftranspose = True)) [(q^24 - 3*q^22 + 3*q^20 - q^18, 1/2*q^14 - 1/2*q^12), (q^16 - 3*q^14 + 3*q^12 - q^10, 1/2*q^16 - q^14 + 1/2*q^12), (q^24 - 2*q^22 + q^20, q^12), (q^16 - 2*q^14 + q^12, q^14 - q^12), (q^28 - 2*q^26 + 2*q^22 - q^20, q^12), (q^20 - 2*q^18 + 2*q^14 - q^12, q^14 - q^12), (q^24 - q^22 - q^20 + q^18, 1/2*q^14 - 1/2*q^12), (q^16 - q^14 - q^12 + q^10, 1/2*q^16 - q^14 + 1/2*q^12), (q^16 - 2*q^14 + q^12, q^14 - q^12), (q^16 - q^14, q^12)] sage: list(ext_orbit_centralizers([[2, [6, 1, 1]]], selftranspose = True)) [(q^24 - 3*q^22 + 3*q^20 - q^18, 1/2*q^14 - 1/2*q^12), (q^16 - 3*q^14 + 3*q^12 - q^10, 1/2*q^16 - q^14 + 1/2*q^12), (q^24 - 2*q^22 + q^20, q^12), (q^16 - 2*q^14 + q^12, q^14 - q^12), (q^28 - 2*q^26 + 2*q^22 - q^20, q^12), (q^20 - 2*q^18 + 2*q^14 - q^12, q^14 - q^12), (q^24 - q^22 - q^20 + q^18, 1/2*q^14 - 1/2*q^12), (q^16 - q^14 - q^12 + q^10, 1/2*q^16 - q^14 + 1/2*q^12), (q^16 - 2*q^14 + q^12, q^14 - q^12), (q^16 - q^14, q^12)] """ # Comments cite items in the paper "Similarity over rings of length two" by # Prasad, Singla, and Spallone. yield (1, 1) return else: else: elif max(la) == 2 and min(la) == 2: for item in matrix_centralizer_cardinalities_length_two(len(la), q = q, selftranspose = selftranspose): yield item else: raise ValueError('partition %s not implemented for ExtOrbitClasses.orbit_centralizers'%(la))
def matrix_centralizer_cardinalities_length_two(n, q = None, selftranspose = False, invertible = False): r""" Generate pairs consisting of centralizer cardinalities of matrices over a principal ideal local ring of length two with residue field of order ``q`` and their frequencies.
INPUT:
- ``n`` -- the order - ``q`` -- (default: `q`) an integer or an indeterminate - ``selftranspose`` -- (default: ``False``) boolean stating if we only want selftranspose type - ``invertible`` -- (default: ``False``) boolean stating if we only want invertible type
TESTS::
sage: from sage.combinat.similarity_class_type import matrix_centralizer_cardinalities_length_two sage: list(matrix_centralizer_cardinalities_length_two(1)) [(q^2 - q, q^2)] sage: list(matrix_centralizer_cardinalities_length_two(2)) [(q^4 - 2*q^3 + q^2, 1/2*q^4 - 1/2*q^3), (q^4 - q^3, q^3), (q^6 - 2*q^5 + q^4, 1/2*q^3 - 1/2*q^2), (q^6 - q^5, q^2), (q^8 - q^7 - q^6 + q^5, q^2), (q^6 - q^4, 1/2*q^3 - 1/2*q^2), (q^4 - q^2, 1/2*q^4 - 1/2*q^3)] sage: from sage.combinat.similarity_class_type import dictionary_from_generator sage: dictionary_from_generator(matrix_centralizer_cardinalities_length_two(2, q = 2)) {4: 4, 8: 8, 12: 4, 16: 2, 32: 4, 48: 2, 96: 4} """
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