wg?ddlmZmZmZddlmZej ZejZdZdZ dZ d dZ ddZ dd Z d Zgifd Zd Zy)) Permutation _af_invert_af_rmul)isprimect|}dg|z}t|D] }||||< |}t|D]}||vs|||<|dz }|S)a Order `\{0, 1, \dots, n-1\}` 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 that ``base_ordering[point]`` is the number of ``point`` in the ordering. Examples ======== >>> from sympy.combinatorics 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] Notes ===== This is used in backtrack searches, when we define a relation `\ll` on the underlying set for a permutation group of degree `n`, `\{0, 1, \dots, n-1\}`, so that if `(b_1, b_2, \dots, b_k)` is a base we have `b_i \ll b_j` whenever `i>> from sympy.combinatorics.util import _check_cycles_alt_sym >>> from sympy.combinatorics 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 See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.is_alt_sym rrTF)size array_formsetr addr)permnaf current_len total_lenusedrjs r_check_cycles_alt_symr!Fs8 A BKI 5D 1a4[  D=QA !11K HHQKAQ%1*q qE Q%1*  $IQT!kAE&9gk>R  rc t|}|dj}t|Dcgc]}g}}d}|D]x}d}||dz kr>|j||||k(r&|dz }||dz kr|j||||k(r&||kDr|}t|dzD]} || j |zt|dz|D]1} || j t t t|3|Scc}w)aL Distribute the group elements ``gens`` by membership in basic stabilizers. Explanation =========== Notice that for a base `(b_1, b_2, \dots, b_k)`, the basic stabilizers are defined as `G^{(i)} = G_{b_1, \dots, b_{i-1}}` for `i \in\{1, 2, \dots, k\}`. Parameters ========== base : a sequence of points in `\{0, 1, \dots, n-1\}` gens : a list of elements of a permutation group of degree `n`. Returns ======= list List of length `k`, where `k` is the length of *base*. The `i`-th entry contains those elements in *gens* which fix the first `i` elements of *base* (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 containing the identity element. Examples ======== >>> 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)]] See Also ======== _strong_gens_from_distr, _orbits_transversals_from_bsgs, _handle_precomputed_bsgs rr)r rr _array_formappend_af_newlist) r gensr r _stabsmax_stab_indexgenr krs r_distribute_gens_by_baser-vs`4yH !W\\Fx )AR )E )N! (Q,3??47#;tAw#F FA(Q,3??47#;tAw#F ~ Nq1u !A !HOOC  ! !>A%x 06 aU6] 3456 L *s C7Nc| t||}|!|t||\}}nQt||d}nB|@t|}dg|z}t|D]!}t ||j ||<#|||fS)a_ Calculate BSGS-related structures from those present. Explanation =========== 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) where *transversals* are the basic transversals, *basic_orbits* are the basic orbits, and *strong_gens_distr* are the strong generators distributed by membership in basic stabilizers. Examples ======== >>> 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)]]) See Also ======== _orbits_transversals_from_bsgs, _distribute_gens_by_base NT)transversals_only)r-_orbits_transversals_from_bsgsr r r&keys)r strong_gens transversals basic_orbitsstrong_gens_distrr rs r_handle_precomputed_bsgsr6s\ 4T;G  .t5FG 'L,/t5F=AC   4yH 6(?L8_ ?"&|A';';'="> Q ? '8 88rcTddlm}t|}|ddj}dg|z}dg|z}|durdg|z} t |D]S} |||| || dd\|| <|| <t || || <|dus5t || j | <U|r|S|s |fS ||fS)aX Compute basic orbits and transversals from a base and strong generating set. Explanation =========== 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 : bool, default: False A flag switching between returning only the transversals and both orbits and transversals. slp : bool, default: False 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 SymmetricGroup >>> from sympy.combinatorics.util import _distribute_gens_by_base >>> S = SymmetricGroup(3) >>> S.schreier_sims() >>> strong_gens_distr = _distribute_gens_by_base(S.base, S.strong_gens) >>> (S.base, strong_gens_distr) ([0, 1], [[(0 1 2), (2)(0 1), (1 2)], [(1 2)]]) See Also ======== _distribute_gens_by_base, _handle_precomputed_bsgs r)_orbit_transversalNFT)pairsslp)sympy.combinatorics.perm_groupsr8r rr dictr&r1) r r5r/r:r8r r r3slpsr4rs rr0r0sVC4yH q !! $ ) )F6(?L 6(?DE!vh 8_;#5f>OPQ>R!%a$$@ Qa|A/ Q  %"<?#7#7#9:LO ; - -\4//rcddlm}t|}|dj}| t ||}|3g}t |D]#}||||||}|j |%|j g|dd} t |dz ddD]s}||dd} ||D]a} | ||dzvs| dd} | j| | gk(r*||| ||} | ||k(s@| j| | j| cu| S)a  Remove redundant generators from a strong generating set. Parameters ========== base : a base strong_gens : a strong generating set relative to *base* basic_orbits : basic orbits strong_gens_distr : strong generators distributed by membership in basic stabilizers Returns ======= A strong generating set with respect to ``base`` which is a subset of ``strong_gens``. Examples ======== >>> from sympy.combinatorics import SymmetricGroup >>> from sympy.combinatorics.util import _remove_gens >>> from sympy.combinatorics.testutil import _verify_bsgs >>> S = SymmetricGroup(15) >>> base, strong_gens = S.schreier_sims_incremental() >>> new_gens = _remove_gens(base, strong_gens) >>> len(new_gens) 14 >>> _verify_bsgs(S, base, new_gens) True Notes ===== This procedure is outlined in [1],p.95. References ========== .. [1] Holt, D., Eick, B., O'Brien, E. "Handbook of computational group theory" r)_orbitNr)r;r?r rr-r r$remove)r r2r4r5r?r r r basic_orbitres gens_copyr+ temp_gens temp_orbits r _remove_gensrG8s@X74yH ^ F 4T;G x -A ):1)=tAwGK    , -R a.C 8a<R ( $%a(+ $Q' $C+AE22%aL   %?#FItAw? a0$$S)JJsO $ $ Jrc|j}t|}t|D]S}|||}|||k(r|||vrt||dzfcS|||j}t t ||}Ut||dzfS)a! Attempt to decompose a permutation using a (possibly partial) BSGS structure. Explanation =========== This is done by treating the sequence ``base`` as an actual base, and the orbits ``orbits`` and transversals ``transversals`` 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 does not end with the identity element. The argument ``transversals`` is a list of dictionaries that provides transversal elements for the orbits ``orbits``. Parameters ========== g : permutation to be decomposed base : sequence of points orbits : list 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 : list A list of orbit transversals associated with the orbits *orbits*. Examples ======== >>> from sympy.combinatorics import Permutation, SymmetricGroup >>> 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) Notes ===== The algorithm is described in [1],pp.89-90. 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 Schreier-Sims algorithm. References ========== .. [1] Holt, D., Eick, B., O'Brien, E."Handbook of computational group theory" See Also ======== sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims_random r)r#r r r%rr) gr orbitsr3hr rbetaus r_striprNs@ A4yH 8_'az 47?  vay 1:q1u$ $ OD ! - - Z]A &' 1:x!| ##rct|}t|dz|D]}|||} | ||k(r| ||vr|s ||dzfcS||dz|fcS||| } || k(r|s d|dzfcSd|dz|fcStt| |}|sj||| dd} | j | D cgc]} || ff } } | |z}|s||dzfS||dz|fScc} w)z optimized _strip, with h, transversals and result in array form if the stripped elements is the identity, it returns False, base_len + 1 j h[base[i]] == base[i] for i <= j rFN)r r rrreverse) rKr rJr3r r:r=r rrLrMu_slprIs r _strip_afrRs4yH 1Q3 !az 47?  vay !a%xa!eS= OD ! 6hl**(Q,+ + Z]A & GDM!$E MMO(-.1a!Y.E.#+C%& (Q, hlC  /s$ C c|t|dk(r|dddS|d}|dD]}||vs|j||S)a% 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 Examples ======== >>> from sympy.combinatorics 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)] See Also ======== _distribute_gens_by_base rrN)r r$)r5resultr+s r_strong_gens_from_distrrUs\@ " #A&&"1%$Q' #C&  c" # r)NNN)FF)NN) sympy.combinatorics.permutationsrrr sympy.ntheoryrrmulr%rr!r-r6r0rGrNrRrUrrrZsrNN!   5p-`>B>BBF>9DAF=0@DNJ$Z57R B'r