X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feuclidean_jordan_algebra.py;h=ce6f6e55e18b28aabea82c9118758c1dab061c28;hb=3cee3d24af1c7606b4c2f30c16a7f6f3e51fd1bd;hp=624806fddac93c9292b229d6afd7954224827e87;hpb=7c384faefd026dd4010e30399646e2e4cb5b4b27;p=sage.d.git diff --git a/mjo/eja/euclidean_jordan_algebra.py b/mjo/eja/euclidean_jordan_algebra.py index 624806f..ce6f6e5 100644 --- a/mjo/eja/euclidean_jordan_algebra.py +++ b/mjo/eja/euclidean_jordan_algebra.py @@ -5,8 +5,8 @@ are used in optimization, and have some additional nice methods beyond what can be supported in a general Jordan Algebra. """ -from sage.structure.unique_representation import UniqueRepresentation from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra import FiniteDimensionalAlgebra +from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra_element import FiniteDimensionalAlgebraElement class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): @staticmethod @@ -29,6 +29,71 @@ class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra): """ return "Euclidean Jordan algebra of degree {} over {}".format(self.degree(), self.base_ring()) + def rank(self): + """ + Return the rank of this EJA. + """ + raise NotImplementedError + + + class Element(FiniteDimensionalAlgebraElement): + """ + An element of a Euclidean Jordan algebra. + """ + + def __pow__(self, n): + """ + Return ``self`` raised to the power ``n``. + + Jordan algebras are always power-associative; see for + example Faraut and Koranyi, Proposition II.1.2 (ii). + """ + A = self.parent() + if n == 0: + return A.one() + elif n == 1: + return self + else: + return A.element_class(A, self.vector()*(self.matrix()**(n-1))) + + + def span_of_powers(self): + """ + Return the vector space spanned by successive powers of + this element. + """ + # The dimension of the subalgebra can't be greater than + # the big algebra, so just put everything into a list + # and let span() get rid of the excess. + V = self.vector().parent() + return V.span( (self**d).vector() for d in xrange(V.dimension()) ) + + + def degree(self): + """ + Compute the degree of this element the straightforward way + according to the definition; by appending powers to a list + and figuring out its dimension (that is, whether or not + they're linearly dependent). + + EXAMPLES:: + + sage: J = eja_ln(4) + sage: J.one().degree() + 1 + sage: e0,e1,e2,e3 = J.gens() + sage: (e0 - e1).degree() + 2 + + """ + return self.span_of_powers().dimension() + + + def minimal_polynomial(self): + return self.matrix().minimal_polynomial() + + def characteristic_polynomial(self): + return self.matrix().characteristic_polynomial() def eja_rn(dimension, field=QQ): @@ -64,9 +129,6 @@ def eja_rn(dimension, field=QQ): Qs = [ matrix(field, dimension, dimension, lambda k,j: 1*(k == j == i)) for i in xrange(dimension) ] - # Assuming associativity is wrong here, but it works to - # temporarily trick the Jordan algebra constructor into using the - # multiplication table. return FiniteDimensionalEuclideanJordanAlgebra(field,Qs)