Utilities¶

sympy.combinatorics.util.
_base_ordering
(base, degree)[source]¶ Order \(\{0, 1, ..., n1\}\) so that base points come first and in order.
Parameters: ``base``  the base
``degree``  the degree of the associated permutation group
Returns: A list
base_ordering
such thatbase_ordering[point]
is thenumber of
point
in the ordering.Notes
This is used in backtrack searches, when we define a relation \(<<\) on the underlying set for a permutation group of degree \(n\), \(\{0, 1, ..., n1\}\), so that if \((b_1, b_2, ..., b_k)\) is a base we have \(b_i << b_j\) whenever \(i<j\) and \(b_i << a\) for all \(i\in\{1,2, ..., k\}\) and \(a\) is not in the base. The idea is developed and applied to backtracking algorithms in [1], pp.108132. The points that are not in the base are taken in increasing order.
References
[1] Holt, D., Eick, B., O’Brien, E. “Handbook of computational group theory”
Examples
>>> from sympy.combinatorics.named_groups import SymmetricGroup >>> from sympy.combinatorics.util import _base_ordering >>> S = SymmetricGroup(4) >>> S.schreier_sims() >>> _base_ordering(S.base, S.degree) [0, 1, 2, 3]

sympy.combinatorics.util.
_check_cycles_alt_sym
(perm)[source]¶ Checks for cycles of prime length p with n/2 < p < n2.
Here \(n\) is the degree of the permutation. This is a helper function for the function is_alt_sym from sympy.combinatorics.perm_groups.
Examples
>>> from sympy.combinatorics.util import _check_cycles_alt_sym >>> from sympy.combinatorics.permutations import Permutation >>> a = Permutation([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12]]) >>> _check_cycles_alt_sym(a) False >>> b = Permutation([[0, 1, 2, 3, 4, 5, 6], [7, 8, 9, 10]]) >>> _check_cycles_alt_sym(b) True

sympy.combinatorics.util.
_distribute_gens_by_base
(base, gens)[source]¶ Distribute the group elements
gens
by membership in basic stabilizers.Notice that for a base \((b_1, b_2, ..., b_k)\), the basic stabilizers are defined as \(G^{(i)} = G_{b_1, ..., b_{i1}}\) for \(i \in\{1, 2, ..., k\}\).
Parameters: ``base``  a sequence of points in `{0, 1, …, n1}`
``gens``  a list of elements of a permutation group of degree `n`.
Returns: List of length \(k\), where \(k\) is
the length of
base
. The \(i\)th entry contains those elements ingens
which fix the first \(i\) elements ofbase
(so that the\(0\)th entry is equal to
gens
itself). If no element fixes the first\(i\) elements of
base
, the \(i\)th element is set to a list containingthe identity element.
Examples
>>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> from sympy.combinatorics.named_groups import DihedralGroup >>> from sympy.combinatorics.util import _distribute_gens_by_base >>> D = DihedralGroup(3) >>> D.schreier_sims() >>> D.strong_gens [(0 1 2), (0 2), (1 2)] >>> D.base [0, 1] >>> _distribute_gens_by_base(D.base, D.strong_gens) [[(0 1 2), (0 2), (1 2)], [(1 2)]]

sympy.combinatorics.util.
_handle_precomputed_bsgs
(base, strong_gens, transversals=None, basic_orbits=None, strong_gens_distr=None)[source]¶ Calculate BSGSrelated structures from those present.
The base and strong generating set must be provided; if any of the transversals, basic orbits or distributed strong generators are not provided, they will be calculated from the base and strong generating set.
Parameters: ``base``  the base
``strong_gens``  the strong generators
``transversals``  basic transversals
``basic_orbits``  basic orbits
``strong_gens_distr``  strong generators distributed by membership in basic
stabilizers
Returns: (transversals, basic_orbits, strong_gens_distr)
wheretransversals
are the basic transversals,
basic_orbits
are the basic orbits, andstrong_gens_distr
are the strong generators distributed by membershipin basic stabilizers.
See also
_orbits_transversals_from_bsgs
,distribute_gens_by_base
Examples
>>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> from sympy.combinatorics.named_groups import DihedralGroup >>> from sympy.combinatorics.util import _handle_precomputed_bsgs >>> D = DihedralGroup(3) >>> D.schreier_sims() >>> _handle_precomputed_bsgs(D.base, D.strong_gens, ... basic_orbits=D.basic_orbits) ([{0: (2), 1: (0 1 2), 2: (0 2)}, {1: (2), 2: (1 2)}], [[0, 1, 2], [1, 2]], [[(0 1 2), (0 2), (1 2)], [(1 2)]])

sympy.combinatorics.util.
_orbits_transversals_from_bsgs
(base, strong_gens_distr, transversals_only=False, slp=False)[source]¶ Compute basic orbits and transversals from a base and strong generating set.
The generators are provided as distributed across the basic stabilizers. If the optional argument
transversals_only
is set to True, only the transversals are returned.Parameters: ``base``  the base
``strong_gens_distr``  strong generators distributed by membership in basic
stabilizers
``transversals_only``  a flag switching between returning only the
transversals/ both orbits and transversals
``slp``  if ``True``, return a list of dictionaries containing the
generator presentations of the elements of the transversals, i.e. the list of indices of generators from \(strong_gens_distr[i]\) such that their product is the relevant transversal element
Examples
>>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> from sympy.combinatorics.named_groups import SymmetricGroup >>> from sympy.combinatorics.util import _orbits_transversals_from_bsgs >>> from sympy.combinatorics.util import (_orbits_transversals_from_bsgs, ... _distribute_gens_by_base) >>> S = SymmetricGroup(3) >>> S.schreier_sims() >>> strong_gens_distr = _distribute_gens_by_base(S.base, S.strong_gens) >>> _orbits_transversals_from_bsgs(S.base, strong_gens_distr) ([[0, 1, 2], [1, 2]], [{0: (2), 1: (0 1 2), 2: (0 2 1)}, {1: (2), 2: (1 2)}])

sympy.combinatorics.util.
_remove_gens
(base, strong_gens, basic_orbits=None, strong_gens_distr=None)[source]¶ Remove redundant generators from a strong generating set.
Parameters: ``base``  a base
``strong_gens``  a strong generating set relative to ``base``
``basic_orbits``  basic orbits
``strong_gens_distr``  strong generators distributed by membership in basic
stabilizers
Returns: A strong generating set with respect to
base
which is a subset ofstrong_gens
.Notes
This procedure is outlined in [1],p.95.
References
[1] Holt, D., Eick, B., O’Brien, E. “Handbook of computational group theory”
Examples
>>> from sympy.combinatorics.named_groups import SymmetricGroup >>> from sympy.combinatorics.perm_groups import PermutationGroup >>> from sympy.combinatorics.util import _remove_gens >>> from sympy.combinatorics.testutil import _verify_bsgs >>> S = SymmetricGroup(15) >>> base, strong_gens = S.schreier_sims_incremental() >>> new_gens = _remove_gens(base, strong_gens) >>> len(new_gens) 14 >>> _verify_bsgs(S, base, new_gens) True

sympy.combinatorics.util.
_strip
(g, base, orbits, transversals)[source]¶ Attempt to decompose a permutation using a (possibly partial) BSGS structure.
This is done by treating the sequence
base
as an actual base, and the orbitsorbits
and transversalstransversals
as basic orbits and transversals relative to it.This process is called “sifting”. A sift is unsuccessful when a certain orbit element is not found or when after the sift the decomposition doesn’t end with the identity element.
The argument
transversals
is a list of dictionaries that provides transversal elements for the orbitsorbits
.Parameters: ``g``  permutation to be decomposed
``base``  sequence of points
``orbits``  a list in which the ``i``th entry is an orbit of ``base[i]``
under some subgroup of the pointwise stabilizer of `
`base[0], base[1], …, base[i  1]``. The groups themselves are implicit
in this function since the only information we need is encoded in the orbits
and transversals
``transversals``  a list of orbit transversals associated with the orbits
``orbits``.
See also
sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims
,sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims_random
Notes
The algorithm is described in [1],pp.8990. The reason for returning both the current state of the element being decomposed and the level at which the sifting ends is that they provide important information for the randomized version of the SchreierSims algorithm.
References
[1] Holt, D., Eick, B., O’Brien, E. “Handbook of computational group theory”
Examples
>>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> from sympy.combinatorics.named_groups import SymmetricGroup >>> from sympy.combinatorics.permutations import Permutation >>> from sympy.combinatorics.util import _strip >>> S = SymmetricGroup(5) >>> S.schreier_sims() >>> g = Permutation([0, 2, 3, 1, 4]) >>> _strip(g, S.base, S.basic_orbits, S.basic_transversals) ((4), 5)

sympy.combinatorics.util.
_strong_gens_from_distr
(strong_gens_distr)[source]¶ Retrieve strong generating set from generators of basic stabilizers.
This is just the union of the generators of the first and second basic stabilizers.
Parameters: ``strong_gens_distr``  strong generators distributed by membership in basic
stabilizers
See also
Examples
>>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> from sympy.combinatorics.named_groups import SymmetricGroup >>> from sympy.combinatorics.util import (_strong_gens_from_distr, ... _distribute_gens_by_base) >>> S = SymmetricGroup(3) >>> S.schreier_sims() >>> S.strong_gens [(0 1 2), (2)(0 1), (1 2)] >>> strong_gens_distr = _distribute_gens_by_base(S.base, S.strong_gens) >>> _strong_gens_from_distr(strong_gens_distr) [(0 1 2), (2)(0 1), (1 2)]