product. This will be applied to ``basis`` to compute an
inner-product table (basically a matrix) for this algebra.
+ - ``matrix_space`` -- the space that your matrix basis lives in,
+ or ``None`` (the default). So long as your basis does not have
+ length zero you can omit this. But in trivial algebras, it is
+ required.
+
- ``field`` -- a subfield of the reals (default: ``AA``); the scalar
field for the algebra.
sage: basis = tuple(b.superalgebra_element() for b in A.basis())
sage: J.subalgebra(basis, orthonormalize=False).is_associative()
True
-
"""
Element = FiniteDimensionalEJAElement
jordan_product,
inner_product,
field=AA,
+ matrix_space=None,
orthonormalize=True,
associative=None,
cartesian_product=False,
category = MagmaticAlgebras(field).FiniteDimensional()
category = category.WithBasis().Unital().Commutative()
+ if n <= 1:
+ # All zero- and one-dimensional algebras are just the real
+ # numbers with (some positive multiples of) the usual
+ # multiplication as its Jordan and inner-product.
+ associative = True
if associative is None:
# We should figure it out. As with check_axioms, we have to do
# this without the help of the _jordan_product_is_associative()
basis = tuple(gram_schmidt(basis, inner_product))
# Save the (possibly orthonormalized) matrix basis for
- # later...
+ # later, as well as the space that its elements live in.
+ # In most cases we can deduce the matrix space, but when
+ # n == 0 (that is, there are no basis elements) we cannot.
self._matrix_basis = basis
+ if matrix_space is None:
+ self._matrix_space = self._matrix_basis[0].parent()
+ else:
+ self._matrix_space = matrix_space
# Now create the vector space for the algebra, which will have
# its own set of non-ambient coordinates (in terms of the
sage: J = ComplexHermitianEJA(2,field=QQ,orthonormalize=False)
sage: J.matrix_space()
- Full MatrixSpace of 4 by 4 dense matrices over Rational Field
+ Module of 2 by 2 matrices with entries in Algebraic Field over
+ the scalar ring Rational Field
sage: J = QuaternionHermitianEJA(1,field=QQ,orthonormalize=False)
sage: J.matrix_space()
Module of 1 by 1 matrices with entries in Quaternion
the scalar ring Rational Field
"""
- if self.is_trivial():
- return MatrixSpace(self.base_ring(), 0)
- else:
- return self.matrix_basis()[0].parent()
+ return self._matrix_space
@cached_method
jordan_product,
inner_product,
field=QQ,
+ matrix_space=self.matrix_space(),
associative=self.is_associative(),
orthonormalize=False,
check_field=False,
return eja_class.random_instance(*args, **kwargs)
-class MatrixEJA:
+class MatrixEJA(FiniteDimensionalEJA):
+ @staticmethod
+ def _denormalized_basis(A):
+ """
+ Returns a basis for the space of complex Hermitian n-by-n matrices.
+
+ Why do we embed these? Basically, because all of numerical linear
+ algebra assumes that you're working with vectors consisting of `n`
+ entries from a field and scalars from the same field. There's no way
+ to tell SageMath that (for example) the vectors contain complex
+ numbers, while the scalar field is real.
+
+ SETUP::
+
+ sage: from mjo.hurwitz import (ComplexMatrixAlgebra,
+ ....: QuaternionMatrixAlgebra,
+ ....: OctonionMatrixAlgebra)
+ sage: from mjo.eja.eja_algebra import MatrixEJA
+
+ TESTS::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: A = MatrixSpace(QQ, n)
+ sage: B = MatrixEJA._denormalized_basis(A)
+ sage: all( M.is_hermitian() for M in B)
+ True
+
+ ::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: A = ComplexMatrixAlgebra(n, scalars=QQ)
+ sage: B = MatrixEJA._denormalized_basis(A)
+ sage: all( M.is_hermitian() for M in B)
+ True
+
+ ::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: A = QuaternionMatrixAlgebra(n, scalars=QQ)
+ sage: B = MatrixEJA._denormalized_basis(A)
+ sage: all( M.is_hermitian() for M in B )
+ True
+
+ ::
+
+ sage: set_random_seed()
+ sage: n = ZZ.random_element(1,5)
+ sage: A = OctonionMatrixAlgebra(n, scalars=QQ)
+ sage: B = MatrixEJA._denormalized_basis(A)
+ sage: all( M.is_hermitian() for M in B )
+ True
+
+ """
+ # These work for real MatrixSpace, whose monomials only have
+ # two coordinates (because the last one would always be "1").
+ es = A.base_ring().gens()
+ gen = lambda A,m: A.monomial(m[:2])
+
+ if hasattr(A, 'entry_algebra_gens'):
+ # We've got a MatrixAlgebra, and its monomials will have
+ # three coordinates.
+ es = A.entry_algebra_gens()
+ gen = lambda A,m: A.monomial(m)
+
+ basis = []
+ for i in range(A.nrows()):
+ for j in range(i+1):
+ if i == j:
+ E_ii = gen(A, (i,j,es[0]))
+ basis.append(E_ii)
+ else:
+ for e in es:
+ E_ij = gen(A, (i,j,e))
+ E_ij += E_ij.conjugate_transpose()
+ basis.append(E_ij)
+
+ return tuple( basis )
+
@staticmethod
def jordan_product(X,Y):
return (X*Y + Y*X)/2
r"""
A trace inner-product for matrices that aren't embedded in the
reals. It takes MATRICES as arguments, not EJA elements.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import (RealSymmetricEJA,
+ ....: ComplexHermitianEJA,
+ ....: QuaternionHermitianEJA,
+ ....: OctonionHermitianEJA)
+
+ EXAMPLES::
+
+ sage: J = RealSymmetricEJA(2,field=QQ,orthonormalize=False)
+ sage: I = J.one().to_matrix()
+ sage: J.trace_inner_product(I, -I)
+ -2
+
+ ::
+
+ sage: J = ComplexHermitianEJA(2,field=QQ,orthonormalize=False)
+ sage: I = J.one().to_matrix()
+ sage: J.trace_inner_product(I, -I)
+ -2
+
+ ::
+
+ sage: J = QuaternionHermitianEJA(2,field=QQ,orthonormalize=False)
+ sage: I = J.one().to_matrix()
+ sage: J.trace_inner_product(I, -I)
+ -2
+
+ ::
+
+ sage: J = OctonionHermitianEJA(2,field=QQ,orthonormalize=False)
+ sage: I = J.one().to_matrix()
+ sage: J.trace_inner_product(I, -I)
+ -2
+
"""
- return (X*Y).trace().real()
+ tr = (X*Y).trace()
+ if hasattr(tr, 'coefficient'):
+ # Works for octonions, and has to come first because they
+ # also have a "real()" method that doesn't return an
+ # element of the scalar ring.
+ return tr.coefficient(0)
+ elif hasattr(tr, 'coefficient_tuple'):
+ # Works for quaternions.
+ return tr.coefficient_tuple()[0]
+ # Works for real and complex numbers.
+ return tr.real()
-class RealSymmetricEJA(RationalBasisEJA, ConcreteEJA, MatrixEJA):
+
+ def __init__(self, matrix_space, **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
+
+
+ super().__init__(self._denormalized_basis(matrix_space),
+ self.jordan_product,
+ self.trace_inner_product,
+ field=matrix_space.base_ring(),
+ matrix_space=matrix_space,
+ **kwargs)
+
+ self.rank.set_cache(matrix_space.nrows())
+ self.one.set_cache( self(matrix_space.one()) )
+
+class RealSymmetricEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA):
"""
The rank-n simple EJA consisting of real symmetric n-by-n
matrices, the usual symmetric Jordan product, and the trace inner
Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
"""
- @classmethod
- def _denormalized_basis(cls, n, field):
- """
- Return a basis for the space of real symmetric n-by-n matrices.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import RealSymmetricEJA
-
- TESTS::
-
- sage: set_random_seed()
- sage: n = ZZ.random_element(1,5)
- sage: B = RealSymmetricEJA._denormalized_basis(n,ZZ)
- sage: all( M.is_symmetric() for M in B)
- True
-
- """
- # The basis of symmetric matrices, as matrices, in their R^(n-by-n)
- # coordinates.
- S = []
- for i in range(n):
- for j in range(i+1):
- Eij = matrix(field, n, lambda k,l: k==i and l==j)
- if i == j:
- Sij = Eij
- else:
- Sij = Eij + Eij.transpose()
- S.append(Sij)
- return tuple(S)
-
-
@staticmethod
def _max_random_instance_size():
return 4 # Dimension 10
# if the user passes check_axioms=True.
if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
- associative = False
- if n <= 1:
- associative = True
-
- super().__init__(self._denormalized_basis(n,field),
- self.jordan_product,
- self.trace_inner_product,
- field=field,
- associative=associative,
- **kwargs)
-
- # TODO: this could be factored out somehow, but is left here
- # because the MatrixEJA is not presently a subclass of the
- # FDEJA class that defines rank() and one().
- self.rank.set_cache(n)
- idV = self.matrix_space().one()
- self.one.set_cache(self(idV))
+ A = MatrixSpace(field, n)
+ super().__init__(A, **kwargs)
-class ComplexHermitianEJA(RationalBasisEJA, ConcreteEJA, MatrixEJA):
+class ComplexHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA):
"""
The rank-n simple EJA consisting of complex Hermitian n-by-n
matrices over the real numbers, the usual symmetric Jordan product,
EXAMPLES:
- In theory, our "field" can be any subfield of the reals::
+ In theory, our "field" can be any subfield of the reals, but we
+ can't use inexact real fields at the moment because SageMath
+ doesn't know how to convert their elements into complex numbers,
+ or even into algebraic reals::
- sage: ComplexHermitianEJA(2, field=RDF, check_axioms=True)
- Euclidean Jordan algebra of dimension 4 over Real Double Field
- sage: ComplexHermitianEJA(2, field=RR, check_axioms=True)
- Euclidean Jordan algebra of dimension 4 over Real Field with
- 53 bits of precision
+ sage: QQbar(RDF(1))
+ Traceback (most recent call last):
+ ...
+ TypeError: Illegal initializer for algebraic number
+ sage: AA(RR(1))
+ Traceback (most recent call last):
+ ...
+ TypeError: Illegal initializer for algebraic number
+
+ This causes the following error when we try to scale a matrix of
+ complex numbers by an inexact real number::
+
+ sage: ComplexHermitianEJA(2,field=RR)
+ Traceback (most recent call last):
+ ...
+ TypeError: Unable to coerce entries (=(1.00000000000000,
+ -0.000000000000000)) to coefficients in Algebraic Real Field
TESTS:
sage: ComplexHermitianEJA(0)
Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
-
"""
-
- @classmethod
- def _denormalized_basis(cls, n, field):
- """
- Returns a basis for the space of complex Hermitian n-by-n matrices.
-
- Why do we embed these? Basically, because all of numerical linear
- algebra assumes that you're working with vectors consisting of `n`
- entries from a field and scalars from the same field. There's no way
- to tell SageMath that (for example) the vectors contain complex
- numbers, while the scalar field is real.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import ComplexHermitianEJA
-
- TESTS::
-
- sage: set_random_seed()
- sage: n = ZZ.random_element(1,5)
- sage: B = ComplexHermitianEJA._denormalized_basis(n,QQ)
- sage: all( M.is_hermitian() for M in B)
- True
-
- """
- from mjo.hurwitz import ComplexMatrixAlgebra
- A = ComplexMatrixAlgebra(n, scalars=field)
- es = A.entry_algebra_gens()
-
- basis = []
- for i in range(n):
- for j in range(i+1):
- if i == j:
- E_ii = A.monomial( (i,j,es[0]) )
- basis.append(E_ii)
- else:
- for e in es:
- E_ij = A.monomial( (i,j,e) )
- ec = e.conjugate()
- # If the conjugate has a negative sign in front
- # of it, (j,i,ec) won't be a monomial!
- if (j,i,ec) in A.indices():
- E_ij += A.monomial( (j,i,ec) )
- else:
- E_ij -= A.monomial( (j,i,-ec) )
- basis.append(E_ij)
-
- return tuple( basis )
-
- @staticmethod
- def trace_inner_product(X,Y):
- r"""
- SETUP::
-
- sage: from mjo.eja.eja_algebra import ComplexHermitianEJA
-
- TESTS::
-
- sage: J = ComplexHermitianEJA(2,field=QQ,orthonormalize=False)
- sage: I = J.one().to_matrix()
- sage: J.trace_inner_product(I, -I)
- -2
-
- """
- return (X*Y).trace().real()
-
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
- associative = False
- if n <= 1:
- associative = True
+ from mjo.hurwitz import ComplexMatrixAlgebra
+ A = ComplexMatrixAlgebra(n, scalars=field)
+ super().__init__(A, **kwargs)
- super().__init__(self._denormalized_basis(n,field),
- self.jordan_product,
- self.trace_inner_product,
- field=field,
- associative=associative,
- **kwargs)
- # TODO: this could be factored out somehow, but is left here
- # because the MatrixEJA is not presently a subclass of the
- # FDEJA class that defines rank() and one().
- self.rank.set_cache(n)
- idV = self.matrix_space().one()
- self.one.set_cache(self(idV))
@staticmethod
def _max_random_instance_size():
return cls(n, **kwargs)
-class QuaternionHermitianEJA(RationalBasisEJA, ConcreteEJA, MatrixEJA):
+class QuaternionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA):
r"""
The rank-n simple EJA consisting of self-adjoint n-by-n quaternion
matrices, the usual symmetric Jordan product, and the
Euclidean Jordan algebra of dimension 0 over Algebraic Real Field
"""
- @classmethod
- def _denormalized_basis(cls, n, field):
- """
- Returns a basis for the space of quaternion Hermitian n-by-n matrices.
-
- Why do we embed these? Basically, because all of numerical
- linear algebra assumes that you're working with vectors consisting
- of `n` entries from a field and scalars from the same field. There's
- no way to tell SageMath that (for example) the vectors contain
- complex numbers, while the scalar field is real.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import QuaternionHermitianEJA
-
- TESTS::
-
- sage: set_random_seed()
- sage: n = ZZ.random_element(1,5)
- sage: B = QuaternionHermitianEJA._denormalized_basis(n,QQ)
- sage: all( M.is_hermitian() for M in B )
- True
-
- """
- from mjo.hurwitz import QuaternionMatrixAlgebra
- A = QuaternionMatrixAlgebra(n, scalars=field)
- es = A.entry_algebra_gens()
-
- basis = []
- for i in range(n):
- for j in range(i+1):
- if i == j:
- E_ii = A.monomial( (i,j,es[0]) )
- basis.append(E_ii)
- else:
- for e in es:
- E_ij = A.monomial( (i,j,e) )
- ec = e.conjugate()
- # If the conjugate has a negative sign in front
- # of it, (j,i,ec) won't be a monomial!
- if (j,i,ec) in A.indices():
- E_ij += A.monomial( (j,i,ec) )
- else:
- E_ij -= A.monomial( (j,i,-ec) )
- basis.append(E_ij)
-
- return tuple( basis )
-
-
- @staticmethod
- def trace_inner_product(X,Y):
- r"""
- Overload the superclass method because the quaternions are weird
- and we need to use ``coefficient_tuple()`` to get the realpart.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import QuaternionHermitianEJA
-
- TESTS::
-
- sage: J = QuaternionHermitianEJA(2,field=QQ,orthonormalize=False)
- sage: I = J.one().to_matrix()
- sage: J.trace_inner_product(I, -I)
- -2
-
- """
- return (X*Y).trace().coefficient_tuple()[0]
-
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
- associative = False
- if n <= 1:
- associative = True
-
- super().__init__(self._denormalized_basis(n,field),
- self.jordan_product,
- self.trace_inner_product,
- field=field,
- associative=associative,
- **kwargs)
-
- # TODO: this could be factored out somehow, but is left here
- # because the MatrixEJA is not presently a subclass of the
- # FDEJA class that defines rank() and one().
- self.rank.set_cache(n)
- idV = self.matrix_space().one()
- self.one.set_cache(self(idV))
+ from mjo.hurwitz import QuaternionMatrixAlgebra
+ A = QuaternionMatrixAlgebra(n, scalars=field)
+ super().__init__(A, **kwargs)
@staticmethod
n = ZZ.random_element(cls._max_random_instance_size() + 1)
return cls(n, **kwargs)
-class OctonionHermitianEJA(RationalBasisEJA, ConcreteEJA, MatrixEJA):
+class OctonionHermitianEJA(MatrixEJA, RationalBasisEJA, ConcreteEJA):
r"""
SETUP::
sage: from mjo.eja.eja_algebra import (FiniteDimensionalEJA,
....: OctonionHermitianEJA)
+ sage: from mjo.hurwitz import Octonions, OctonionMatrixAlgebra
EXAMPLES:
After a change-of-basis, the 2-by-2 algebra has the same
multiplication table as the ten-dimensional Jordan spin algebra::
- sage: b = OctonionHermitianEJA._denormalized_basis(2,QQ)
+ sage: A = OctonionMatrixAlgebra(2,Octonions(QQ),QQ)
+ sage: b = OctonionHermitianEJA._denormalized_basis(A)
sage: basis = (b[0] + b[9],) + b[1:9] + (b[0] - b[9],)
sage: jp = OctonionHermitianEJA.jordan_product
sage: ip = OctonionHermitianEJA.trace_inner_product
# if the user passes check_axioms=True.
if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
- super().__init__(self._denormalized_basis(n,field),
- self.jordan_product,
- self.trace_inner_product,
- field=field,
- **kwargs)
-
- # TODO: this could be factored out somehow, but is left here
- # because the MatrixEJA is not presently a subclass of the
- # FDEJA class that defines rank() and one().
- self.rank.set_cache(n)
- idV = self.matrix_space().one()
- self.one.set_cache(self(idV))
-
-
- @classmethod
- def _denormalized_basis(cls, n, field):
- """
- Returns a basis for the space of octonion Hermitian n-by-n
- matrices.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import OctonionHermitianEJA
-
- EXAMPLES::
-
- sage: B = OctonionHermitianEJA._denormalized_basis(3,QQ)
- sage: all( M.is_hermitian() for M in B )
- True
- sage: len(B)
- 27
-
- """
from mjo.hurwitz import OctonionMatrixAlgebra
A = OctonionMatrixAlgebra(n, scalars=field)
- es = A.entry_algebra_gens()
-
- basis = []
- for i in range(n):
- for j in range(i+1):
- if i == j:
- E_ii = A.monomial( (i,j,es[0]) )
- basis.append(E_ii)
- else:
- for e in es:
- E_ij = A.monomial( (i,j,e) )
- ec = e.conjugate()
- # If the conjugate has a negative sign in front
- # of it, (j,i,ec) won't be a monomial!
- if (j,i,ec) in A.indices():
- E_ij += A.monomial( (j,i,ec) )
- else:
- E_ij -= A.monomial( (j,i,-ec) )
- basis.append(E_ij)
-
- return tuple( basis )
+ super().__init__(A, **kwargs)
- @staticmethod
- def trace_inner_product(X,Y):
- r"""
- The octonions don't know that the reals are embedded in them,
- so we have to take the e0 component ourselves.
-
- SETUP::
-
- sage: from mjo.eja.eja_algebra import OctonionHermitianEJA
-
- TESTS::
-
- sage: J = OctonionHermitianEJA(2,field=QQ,orthonormalize=False)
- sage: I = J.one().to_matrix()
- sage: J.trace_inner_product(I, -I)
- -2
-
- """
- return (X*Y).trace().coefficient(0)
+ if n == 3:
+ from mjo.eja.eja_cache import albert_eja_coeffs
+ a = albert_eja_coeffs(self.coordinate_polynomial_ring())
+ if self._rational_algebra is None:
+ self._charpoly_coefficients.set_cache(a)
+ else:
+ self._rational_algebra._charpoly_coefficients.set_cache(a)
class AlbertEJA(OctonionHermitianEJA):
(r0, r1, r2)
"""
def __init__(self, n, field=AA, **kwargs):
+ MS = MatrixSpace(field, n, 1)
+
if n == 0:
jordan_product = lambda x,y: x
inner_product = lambda x,y: x
else:
def jordan_product(x,y):
- P = x.parent()
- return P( xi*yi for (xi,yi) in zip(x,y) )
+ return MS( xi*yi for (xi,yi) in zip(x,y) )
def inner_product(x,y):
return (x.T*y)[0,0]
if "orthonormalize" not in kwargs: kwargs["orthonormalize"] = False
if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
- column_basis = tuple( b.column()
- for b in FreeModule(field, n).basis() )
+ column_basis = tuple( MS(b) for b in FreeModule(field, n).basis() )
super().__init__(column_basis,
jordan_product,
inner_product,
field=field,
+ matrix_space=MS,
associative=True,
**kwargs)
self.rank.set_cache(n)
- if n == 0:
- self.one.set_cache( self.zero() )
- else:
- self.one.set_cache( sum(self.gens()) )
+ self.one.set_cache( self.sum(self.gens()) )
@staticmethod
def _max_random_instance_size():
# verify things, we'll skip the rest of the checks.
if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
+ n = B.nrows()
+ MS = MatrixSpace(field, n, 1)
+
def inner_product(x,y):
return (y.T*B*x)[0,0]
def jordan_product(x,y):
- P = x.parent()
x0 = x[0,0]
xbar = x[1:,0]
y0 = y[0,0]
ybar = y[1:,0]
z0 = inner_product(y,x)
zbar = y0*xbar + x0*ybar
- return P([z0] + zbar.list())
+ return MS([z0] + zbar.list())
- n = B.nrows()
- column_basis = tuple( b.column()
- for b in FreeModule(field, n).basis() )
+ column_basis = tuple( MS(b) for b in FreeModule(field, n).basis() )
# TODO: I haven't actually checked this, but it seems legit.
associative = False
jordan_product,
inner_product,
field=field,
+ matrix_space=MS,
associative=associative,
**kwargs)
# one-dimensional ambient space (because the rank is bounded
# by the ambient dimension).
self.rank.set_cache(min(n,2))
-
if n == 0:
self.one.set_cache( self.zero() )
else:
0
"""
- def __init__(self, **kwargs):
+ def __init__(self, field=AA, **kwargs):
jordan_product = lambda x,y: x
- inner_product = lambda x,y: 0
+ inner_product = lambda x,y: field.zero()
basis = ()
+ MS = MatrixSpace(field,0)
# New defaults for keyword arguments
if "orthonormalize" not in kwargs: kwargs["orthonormalize"] = False
jordan_product,
inner_product,
associative=True,
+ field=field,
+ matrix_space=MS,
**kwargs)
# The rank is zero using my definition, namely the dimension of the
associative = all( f.is_associative() for f in factors )
- MS = self.matrix_space()
+ # Compute my matrix space. This category isn't perfect, but
+ # is good enough for what we need to do.
+ MS_cat = MagmaticAlgebras(field).FiniteDimensional().WithBasis()
+ MS_cat = MS_cat.Unital().CartesianProducts()
+ MS_factors = tuple( J.matrix_space() for J in factors )
+ from sage.sets.cartesian_product import CartesianProduct
+ MS = CartesianProduct(MS_factors, MS_cat)
+
basis = []
zero = MS.zero()
for i in range(m):
jordan_product,
inner_product,
field=field,
+ matrix_space=MS,
orthonormalize=False,
associative=associative,
cartesian_product=True,
check_field=False,
check_axioms=False)
+ self.rank.set_cache(sum(J.rank() for J in factors))
ones = tuple(J.one().to_matrix() for J in factors)
self.one.set_cache(self(ones))
- self.rank.set_cache(sum(J.rank() for J in factors))
def cartesian_factors(self):
# Copy/pasted from CombinatorialFreeModule_CartesianProduct.
sage: J2 = ComplexHermitianEJA(1)
sage: J = cartesian_product([J1,J2])
sage: J.one().to_matrix()[0]
- [1 0]
- [0 1]
+ +---+
+ | 1 |
+ +---+
sage: J.one().to_matrix()[1]
- [1 0]
- [0 1]
+ +---+
+ | 1 |
+ +---+
::
+----+
"""
- scalars = self.cartesian_factor(0).base_ring()
-
- # This category isn't perfect, but is good enough for what we
- # need to do.
- cat = MagmaticAlgebras(scalars).FiniteDimensional().WithBasis()
- cat = cat.Unital().CartesianProducts()
- factors = tuple( J.matrix_space() for J in self.cartesian_factors() )
-
- from sage.sets.cartesian_product import CartesianProduct
- return CartesianProduct(factors, cat)
+ return super().matrix_space()
@cached_method
projects / sage.d.git / blobdiff