X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_algebra.py;h=907f40d72135df42d211cdd9bb8923df6bf462e6;hb=7c21799d680433b62d48ca79cc2ea8f27e1cd8da;hp=af4080b0807d6ac6848849f23edd237657896413;hpb=6d6af7c2560b2886cd47a2c8f3c0b9d1b843f649;p=sage.d.git diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py index af4080b..907f40d 100644 --- a/mjo/eja/eja_algebra.py +++ b/mjo/eja/eja_algebra.py @@ -168,7 +168,7 @@ from sage.rings.all import (ZZ, QQ, AA, QQbar, RR, RLF, CLF, QuadraticField) from mjo.eja.eja_element import FiniteDimensionalEJAElement from mjo.eja.eja_operator import FiniteDimensionalEJAOperator -from mjo.eja.eja_utils import _all2list, _mat2vec +from mjo.eja.eja_utils import _all2list def EuclideanJordanAlgebras(field): r""" @@ -1281,7 +1281,9 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): # # Of course, matrices aren't vectors in sage, so we have to # appeal to the "long vectors" isometry. - oper_vecs = [ _mat2vec(g.operator().matrix()) for g in self.gens() ] + + V = VectorSpace(self.base_ring(), self.dimension()**2) + oper_vecs = [ V(g.operator().matrix().list()) for g in self.gens() ] # Now we use basic linear algebra to find the coefficients, # of the matrices-as-vectors-linear-combination, which should @@ -1291,7 +1293,7 @@ class FiniteDimensionalEJA(CombinatorialFreeModule): # We used the isometry on the left-hand side already, but we # still need to do it for the right-hand side. Recall that we # wanted something that summed to the identity matrix. - b = _mat2vec( matrix.identity(self.base_ring(), self.dimension()) ) + b = V( matrix.identity(self.base_ring(), self.dimension()).list() ) # Now if there's an identity element in the algebra, this # should work. We solve on the left to avoid having to @@ -2045,7 +2047,6 @@ class MatrixEJA(FiniteDimensionalEJA): # if the user passes check_axioms=True. if "check_axioms" not in kwargs: kwargs["check_axioms"] = False - super().__init__(self._denormalized_basis(matrix_space), self.jordan_product, self.trace_inner_product, @@ -2140,10 +2141,6 @@ class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): return cls(n, **kwargs) def __init__(self, n, field=AA, **kwargs): - # We know this is a valid EJA, but will double-check - # if the user passes check_axioms=True. - if "check_axioms" not in kwargs: kwargs["check_axioms"] = False - A = MatrixSpace(field, n) super().__init__(A, **kwargs) @@ -2227,10 +2224,6 @@ class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): """ def __init__(self, n, field=AA, **kwargs): - # We know this is a valid EJA, but will double-check - # if the user passes check_axioms=True. - if "check_axioms" not in kwargs: kwargs["check_axioms"] = False - from mjo.hurwitz import ComplexMatrixAlgebra A = ComplexMatrixAlgebra(n, scalars=field) super().__init__(A, **kwargs) @@ -2317,10 +2310,6 @@ class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA): """ def __init__(self, n, field=AA, **kwargs): - # We know this is a valid EJA, but will double-check - # if the user passes check_axioms=True. - if "check_axioms" not in kwargs: kwargs["check_axioms"] = False - from mjo.hurwitz import QuaternionMatrixAlgebra A = QuaternionMatrixAlgebra(n, scalars=field) super().__init__(A, **kwargs) @@ -3203,6 +3192,34 @@ class CartesianProductEJA(FiniteDimensionalEJA): ones = tuple(J.one().to_matrix() for J in factors) self.one.set_cache(self(ones)) + def _sets_keys(self): + r""" + + SETUP:: + + sage: from mjo.eja.eja_algebra import (ComplexHermitianEJA, + ....: RealSymmetricEJA) + + TESTS: + + The superclass uses ``_sets_keys()`` to implement its + ``cartesian_factors()`` method:: + + sage: J1 = RealSymmetricEJA(2, + ....: field=QQ, + ....: orthonormalize=False, + ....: prefix="a") + sage: J2 = ComplexHermitianEJA(2,field=QQ,orthonormalize=False) + sage: J = cartesian_product([J1,J2]) + sage: x = sum(i*J.gens()[i] for i in range(len(J.gens()))) + sage: x.cartesian_factors() + (a1 + 2*a2, 3*b0 + 4*b1 + 5*b2 + 6*b3) + + """ + # Copy/pasted from CombinatorialFreeModule_CartesianProduct, + # but returning a tuple instead of a list. + return tuple(range(len(self.cartesian_factors()))) + def cartesian_factors(self): # Copy/pasted from CombinatorialFreeModule_CartesianProduct. return self._sets