switching to high quality piper tts and added label translations
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Matthias Hinrichs
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from sympy.combinatorics import Permutation
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from sympy.combinatorics.util import _distribute_gens_by_base
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rmul = Permutation.rmul
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def _cmp_perm_lists(first, second):
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"""
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Compare two lists of permutations as sets.
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Explanation
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===========
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This is used for testing purposes. Since the array form of a
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permutation is currently a list, Permutation is not hashable
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and cannot be put into a set.
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Examples
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========
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>>> from sympy.combinatorics.permutations import Permutation
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>>> from sympy.combinatorics.testutil import _cmp_perm_lists
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>>> a = Permutation([0, 2, 3, 4, 1])
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>>> b = Permutation([1, 2, 0, 4, 3])
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>>> c = Permutation([3, 4, 0, 1, 2])
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>>> ls1 = [a, b, c]
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>>> ls2 = [b, c, a]
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>>> _cmp_perm_lists(ls1, ls2)
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True
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"""
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return {tuple(a) for a in first} == \
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{tuple(a) for a in second}
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def _naive_list_centralizer(self, other, af=False):
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from sympy.combinatorics.perm_groups import PermutationGroup
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"""
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Return a list of elements for the centralizer of a subgroup/set/element.
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Explanation
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===========
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This is a brute force implementation that goes over all elements of the
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group and checks for membership in the centralizer. It is used to
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test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``.
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Examples
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========
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>>> from sympy.combinatorics.testutil import _naive_list_centralizer
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>>> from sympy.combinatorics.named_groups import DihedralGroup
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>>> D = DihedralGroup(4)
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>>> _naive_list_centralizer(D, D)
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[Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])]
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See Also
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========
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sympy.combinatorics.perm_groups.centralizer
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"""
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from sympy.combinatorics.permutations import _af_commutes_with
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if hasattr(other, 'generators'):
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elements = list(self.generate_dimino(af=True))
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gens = [x._array_form for x in other.generators]
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commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens)
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centralizer_list = []
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if not af:
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for element in elements:
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if commutes_with_gens(element):
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centralizer_list.append(Permutation._af_new(element))
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else:
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for element in elements:
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if commutes_with_gens(element):
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centralizer_list.append(element)
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return centralizer_list
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elif hasattr(other, 'getitem'):
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return _naive_list_centralizer(self, PermutationGroup(other), af)
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elif hasattr(other, 'array_form'):
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return _naive_list_centralizer(self, PermutationGroup([other]), af)
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def _verify_bsgs(group, base, gens):
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"""
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Verify the correctness of a base and strong generating set.
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Explanation
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===========
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This is a naive implementation using the definition of a base and a strong
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generating set relative to it. There are other procedures for
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verifying a base and strong generating set, but this one will
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serve for more robust testing.
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Examples
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========
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>>> from sympy.combinatorics.named_groups import AlternatingGroup
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>>> from sympy.combinatorics.testutil import _verify_bsgs
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>>> A = AlternatingGroup(4)
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>>> A.schreier_sims()
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>>> _verify_bsgs(A, A.base, A.strong_gens)
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True
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See Also
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========
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sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims
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"""
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from sympy.combinatorics.perm_groups import PermutationGroup
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strong_gens_distr = _distribute_gens_by_base(base, gens)
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current_stabilizer = group
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for i in range(len(base)):
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candidate = PermutationGroup(strong_gens_distr[i])
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if current_stabilizer.order() != candidate.order():
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return False
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current_stabilizer = current_stabilizer.stabilizer(base[i])
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if current_stabilizer.order() != 1:
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return False
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return True
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def _verify_centralizer(group, arg, centr=None):
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"""
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Verify the centralizer of a group/set/element inside another group.
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This is used for testing ``.centralizer()`` from
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``sympy.combinatorics.perm_groups``
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Examples
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========
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>>> from sympy.combinatorics.named_groups import (SymmetricGroup,
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... AlternatingGroup)
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>>> from sympy.combinatorics.perm_groups import PermutationGroup
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>>> from sympy.combinatorics.permutations import Permutation
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>>> from sympy.combinatorics.testutil import _verify_centralizer
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>>> S = SymmetricGroup(5)
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>>> A = AlternatingGroup(5)
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>>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])])
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>>> _verify_centralizer(S, A, centr)
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True
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See Also
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========
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_naive_list_centralizer,
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sympy.combinatorics.perm_groups.PermutationGroup.centralizer,
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_cmp_perm_lists
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"""
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if centr is None:
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centr = group.centralizer(arg)
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centr_list = list(centr.generate_dimino(af=True))
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centr_list_naive = _naive_list_centralizer(group, arg, af=True)
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return _cmp_perm_lists(centr_list, centr_list_naive)
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def _verify_normal_closure(group, arg, closure=None):
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from sympy.combinatorics.perm_groups import PermutationGroup
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"""
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Verify the normal closure of a subgroup/subset/element in a group.
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This is used to test
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sympy.combinatorics.perm_groups.PermutationGroup.normal_closure
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Examples
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========
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>>> from sympy.combinatorics.named_groups import (SymmetricGroup,
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... AlternatingGroup)
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>>> from sympy.combinatorics.testutil import _verify_normal_closure
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>>> S = SymmetricGroup(3)
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>>> A = AlternatingGroup(3)
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>>> _verify_normal_closure(S, A, closure=A)
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True
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See Also
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========
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sympy.combinatorics.perm_groups.PermutationGroup.normal_closure
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"""
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if closure is None:
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closure = group.normal_closure(arg)
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conjugates = set()
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if hasattr(arg, 'generators'):
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subgr_gens = arg.generators
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elif hasattr(arg, '__getitem__'):
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subgr_gens = arg
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elif hasattr(arg, 'array_form'):
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subgr_gens = [arg]
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for el in group.generate_dimino():
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conjugates.update(gen ^ el for gen in subgr_gens)
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naive_closure = PermutationGroup(list(conjugates))
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return closure.is_subgroup(naive_closure)
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def canonicalize_naive(g, dummies, sym, *v):
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"""
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Canonicalize tensor formed by tensors of the different types.
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Explanation
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===========
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sym_i symmetry under exchange of two component tensors of type `i`
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None no symmetry
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0 commuting
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1 anticommuting
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Parameters
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==========
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g : Permutation representing the tensor.
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dummies : List of dummy indices.
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msym : Symmetry of the metric.
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v : A list of (base_i, gens_i, n_i, sym_i) for tensors of type `i`.
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base_i, gens_i BSGS for tensors of this type
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n_i number of tensors of type `i`
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Returns
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=======
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Returns 0 if the tensor is zero, else returns the array form of
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the permutation representing the canonical form of the tensor.
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Examples
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========
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>>> from sympy.combinatorics.testutil import canonicalize_naive
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>>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs
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>>> from sympy.combinatorics import Permutation
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>>> g = Permutation([1, 3, 2, 0, 4, 5])
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>>> base2, gens2 = get_symmetric_group_sgs(2)
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>>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0))
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[0, 2, 1, 3, 4, 5]
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"""
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from sympy.combinatorics.perm_groups import PermutationGroup
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from sympy.combinatorics.tensor_can import gens_products, dummy_sgs
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from sympy.combinatorics.permutations import _af_rmul
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v1 = []
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for i in range(len(v)):
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base_i, gens_i, n_i, sym_i = v[i]
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v1.append((base_i, gens_i, [[]]*n_i, sym_i))
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size, sbase, sgens = gens_products(*v1)
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dgens = dummy_sgs(dummies, sym, size-2)
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if isinstance(sym, int):
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num_types = 1
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dummies = [dummies]
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sym = [sym]
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else:
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num_types = len(sym)
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dgens = []
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for i in range(num_types):
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dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2))
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S = PermutationGroup(sgens)
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D = PermutationGroup([Permutation(x) for x in dgens])
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dlist = list(D.generate(af=True))
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g = g.array_form
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st = set()
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for s in S.generate(af=True):
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h = _af_rmul(g, s)
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for d in dlist:
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q = tuple(_af_rmul(d, h))
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st.add(q)
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a = list(st)
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a.sort()
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prev = (0,)*size
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for h in a:
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if h[:-2] == prev[:-2]:
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if h[-1] != prev[-1]:
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return 0
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prev = h
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return list(a[0])
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def graph_certificate(gr):
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"""
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Return a certificate for the graph
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Parameters
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==========
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gr : adjacency list
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Explanation
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===========
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The graph is assumed to be unoriented and without
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external lines.
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Associate to each vertex of the graph a symmetric tensor with
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number of indices equal to the degree of the vertex; indices
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are contracted when they correspond to the same line of the graph.
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The canonical form of the tensor gives a certificate for the graph.
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This is not an efficient algorithm to get the certificate of a graph.
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Examples
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========
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>>> from sympy.combinatorics.testutil import graph_certificate
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>>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]}
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>>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]}
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>>> c1 = graph_certificate(gr1)
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>>> c2 = graph_certificate(gr2)
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>>> c1
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[0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21]
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>>> c1 == c2
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True
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"""
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from sympy.combinatorics.permutations import _af_invert
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from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize
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items = list(gr.items())
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items.sort(key=lambda x: len(x[1]), reverse=True)
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pvert = [x[0] for x in items]
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pvert = _af_invert(pvert)
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# the indices of the tensor are twice the number of lines of the graph
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num_indices = 0
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for v, neigh in items:
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num_indices += len(neigh)
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# associate to each vertex its indices; for each line
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# between two vertices assign the
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# even index to the vertex which comes first in items,
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# the odd index to the other vertex
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vertices = [[] for i in items]
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i = 0
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for v, neigh in items:
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for v2 in neigh:
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if pvert[v] < pvert[v2]:
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vertices[pvert[v]].append(i)
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vertices[pvert[v2]].append(i+1)
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i += 2
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g = []
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for v in vertices:
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g.extend(v)
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assert len(g) == num_indices
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g += [num_indices, num_indices + 1]
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size = num_indices + 2
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assert sorted(g) == list(range(size))
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g = Permutation(g)
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vlen = [0]*(len(vertices[0])+1)
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for neigh in vertices:
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vlen[len(neigh)] += 1
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v = []
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for i in range(len(vlen)):
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n = vlen[i]
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if n:
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base, gens = get_symmetric_group_sgs(i)
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v.append((base, gens, n, 0))
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v.reverse()
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dummies = list(range(num_indices))
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can = canonicalize(g, dummies, 0, *v)
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return can
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