prefix='e',
category=None,
natural_basis=None,
- check=True):
+ check_field=True,
+ check_axioms=True):
"""
SETUP::
- sage: from mjo.eja.eja_algebra import (JordanSpinEJA, random_eja)
+ sage: from mjo.eja.eja_algebra import (
+ ....: FiniteDimensionalEuclideanJordanAlgebra,
+ ....: JordanSpinEJA,
+ ....: random_eja)
EXAMPLES:
TESTS:
- The ``field`` we're given must be real::
+ The ``field`` we're given must be real with ``check_field=True``::
sage: JordanSpinEJA(2,QQbar)
Traceback (most recent call last):
...
- ValueError: field is not real
+ ValueError: scalar field is not real
+
+ The multiplication table must be square with ``check_axioms=True``::
+
+ sage: FiniteDimensionalEuclideanJordanAlgebra(QQ,((),()))
+ Traceback (most recent call last):
+ ...
+ ValueError: multiplication table is not square
"""
- if check:
+ if check_field:
if not field.is_subring(RR):
# Note: this does return true for the real algebraic
- # field, and any quadratic field where we've specified
- # a real embedding.
- raise ValueError('field is not real')
+ # field, the rationals, and any quadratic field where
+ # we've specified a real embedding.
+ raise ValueError("scalar field is not real")
+
+ # The multiplication table had better be square
+ n = len(mult_table)
+ if check_axioms:
+ if not all( len(l) == n for l in mult_table ):
+ raise ValueError("multiplication table is not square")
self._natural_basis = natural_basis
fda = super(FiniteDimensionalEuclideanJordanAlgebra, self)
fda.__init__(field,
- range(len(mult_table)),
+ range(n),
prefix=prefix,
category=category)
self.print_options(bracket='')
for ls in mult_table
]
+ if check_axioms:
+ if not self._is_commutative():
+ raise ValueError("algebra is not commutative")
+ if not self._is_jordanian():
+ raise ValueError("Jordan identity does not hold")
+ if not self._inner_product_is_associative():
+ raise ValueError("inner product is not associative")
def _element_constructor_(self, elt):
"""
def product_on_basis(self, i, j):
return self._multiplication_table[i][j]
+ def _is_commutative(self):
+ r"""
+ Whether or not this algebra's multiplication table is commutative.
+
+ This method should of course always return ``True``, unless
+ this algebra was constructed with ``check_axioms=False`` and
+ passed an invalid multiplication table.
+ """
+ return all( self.product_on_basis(i,j) == self.product_on_basis(i,j)
+ for i in range(self.dimension())
+ for j in range(self.dimension()) )
+
+ def _is_jordanian(self):
+ r"""
+ Whether or not this algebra's multiplication table respects the
+ Jordan identity `(x^{2})(xy) = x(x^{2}y)`.
+
+ We only check one arrangement of `x` and `y`, so for a
+ ``True`` result to be truly true, you should also check
+ :meth:`_is_commutative`. This method should of course always
+ return ``True``, unless this algebra was constructed with
+ ``check_axioms=False`` and passed an invalid multiplication table.
+ """
+ return all( (self.monomial(i)**2)*(self.monomial(i)*self.monomial(j))
+ ==
+ (self.monomial(i))*((self.monomial(i)**2)*self.monomial(j))
+ for i in range(self.dimension())
+ for j in range(self.dimension()) )
+
+ def _inner_product_is_associative(self):
+ r"""
+ Return whether or not this algebra's inner product `B` is
+ associative; that is, whether or not `B(xy,z) = B(x,yz)`.
+
+ This method should of course always return ``True``, unless
+ this algebra was constructed with ``check_axioms=False`` and
+ passed an invalid multiplication table.
+ """
+
+ # Used to check whether or not something is zero in an inexact
+ # ring. This number is sufficient to allow the construction of
+ # QuaternionHermitianEJA(2, RDF) with check_axioms=True.
+ epsilon = 1e-16
+
+ for i in range(self.dimension()):
+ for j in range(self.dimension()):
+ for k in range(self.dimension()):
+ x = self.monomial(i)
+ y = self.monomial(j)
+ z = self.monomial(k)
+ diff = (x*y).inner_product(z) - x.inner_product(y*z)
+
+ if self.base_ring().is_exact():
+ if diff != 0:
+ return False
+ else:
+ if diff.abs() > epsilon:
+ return False
+
+ return True
+
@cached_method
def characteristic_polynomial_of(self):
"""
J5 = eigspace
else:
gens = tuple( self.from_vector(b) for b in eigspace.basis() )
- subalg = FiniteDimensionalEuclideanJordanSubalgebra(self, gens)
+ subalg = FiniteDimensionalEuclideanJordanSubalgebra(self,
+ gens,
+ check_axioms=False)
if eigval == 0:
J0 = subalg
elif eigval == 1:
return (J0, J5, J1)
- def random_elements(self, count):
+ def random_element(self, thorough=False):
+ r"""
+ Return a random element of this algebra.
+
+ Our algebra superclass method only returns a linear
+ combination of at most two basis elements. We instead
+ want the vector space "random element" method that
+ returns a more diverse selection.
+
+ INPUT:
+
+ - ``thorough`` -- (boolean; default False) whether or not we
+ should generate irrational coefficients for the random
+ element when our base ring is irrational; this slows the
+ algebra operations to a crawl, but any truly random method
+ should include them
+
+ """
+ # For a general base ring... maybe we can trust this to do the
+ # right thing? Unlikely, but.
+ V = self.vector_space()
+ v = V.random_element()
+
+ if self.base_ring() is AA:
+ # The "random element" method of the algebraic reals is
+ # stupid at the moment, and only returns integers between
+ # -2 and 2, inclusive:
+ #
+ # https://trac.sagemath.org/ticket/30875
+ #
+ # Instead, we implement our own "random vector" method,
+ # and then coerce that into the algebra. We use the vector
+ # space degree here instead of the dimension because a
+ # subalgebra could (for example) be spanned by only two
+ # vectors, each with five coordinates. We need to
+ # generate all five coordinates.
+ if thorough:
+ v *= QQbar.random_element().real()
+ else:
+ v *= QQ.random_element()
+
+ return self.from_vector(V.coordinate_vector(v))
+
+ def random_elements(self, count, thorough=False):
"""
Return ``count`` random elements as a tuple.
+ INPUT:
+
+ - ``thorough`` -- (boolean; default False) whether or not we
+ should generate irrational coefficients for the random
+ elements when our base ring is irrational; this slows the
+ algebra operations to a crawl, but any truly random method
+ should include them
+
SETUP::
sage: from mjo.eja.eja_algebra import JordanSpinEJA
True
"""
- return tuple( self.random_element() for idx in range(count) )
+ return tuple( self.random_element(thorough)
+ for idx in range(count) )
@classmethod
def random_instance(cls, field=AA, **kwargs):
mult_table = [ [ V.gen(i)*(i == j) for j in range(n) ]
for i in range(n) ]
- fdeja = super(HadamardEJA, self)
- fdeja.__init__(field, mult_table, **kwargs)
+ super(HadamardEJA, self).__init__(field,
+ mult_table,
+ check_axioms=False,
+ **kwargs)
self.rank.set_cache(n)
def inner_product(self, x, y):
Qs = self.multiplication_table_from_matrix_basis(basis)
- fdeja = super(MatrixEuclideanJordanAlgebra, self)
- fdeja.__init__(field, Qs, natural_basis=basis, **kwargs)
- return
+ super(MatrixEuclideanJordanAlgebra, self).__init__(field,
+ Qs,
+ natural_basis=basis,
+ **kwargs)
@cached_method
# Do this over the rationals and convert back at the end.
# Only works because we know the entries of the basis are
- # integers.
+ # integers. The argument ``check_axioms=False`` is required
+ # because the trace inner-product method for this
+ # class is a stub and can't actually be checked.
J = MatrixEuclideanJordanAlgebra(QQ,
basis,
- normalize_basis=False)
+ normalize_basis=False,
+ check_field=False,
+ check_axioms=False)
a = J._charpoly_coefficients()
# Unfortunately, changing the basis does change the
Yu = cls.real_unembed(Y)
tr = (Xu*Yu).trace()
- if tr in RLF:
- # It's real already.
- return tr
-
- # Otherwise, try the thing that works for complex numbers; and
- # if that doesn't work, the thing that works for quaternions.
try:
- return tr.vector()[0] # real part, imag part is index 1
+ # Works in QQ, AA, RDF, et cetera.
+ return tr.real()
except AttributeError:
- # A quaternions doesn't have a vector() method, but does
+ # A quaternion doesn't have a real() method, but does
# have coefficient_tuple() method that returns the
# coefficients of 1, i, j, and k -- in that order.
return tr.coefficient_tuple()[0]
def __init__(self, n, field=AA, **kwargs):
basis = self._denormalized_basis(n, field)
- super(RealSymmetricEJA, self).__init__(field, basis, **kwargs)
+ super(RealSymmetricEJA, self).__init__(field,
+ basis,
+ check_axioms=False,
+ **kwargs)
self.rank.set_cache(n)
def __init__(self, n, field=AA, **kwargs):
basis = self._denormalized_basis(n,field)
- super(ComplexHermitianEJA,self).__init__(field, basis, **kwargs)
+ super(ComplexHermitianEJA,self).__init__(field,
+ basis,
+ check_axioms=False,
+ **kwargs)
self.rank.set_cache(n)
def __init__(self, n, field=AA, **kwargs):
basis = self._denormalized_basis(n,field)
- super(QuaternionHermitianEJA,self).__init__(field, basis, **kwargs)
+ super(QuaternionHermitianEJA,self).__init__(field,
+ basis,
+ check_axioms=False,
+ **kwargs)
self.rank.set_cache(n)
# The rank of this algebra is two, unless we're in a
# one-dimensional ambient space (because the rank is bounded
# by the ambient dimension).
- fdeja = super(BilinearFormEJA, self)
- fdeja.__init__(field, mult_table, **kwargs)
+ super(BilinearFormEJA, self).__init__(field,
+ mult_table,
+ check_axioms=False,
+ **kwargs)
self.rank.set_cache(min(n,2))
def inner_product(self, x, y):
def __init__(self, n, field=AA, **kwargs):
# This is a special case of the BilinearFormEJA with the identity
# matrix as its bilinear form.
- return super(JordanSpinEJA, self).__init__(n, field, **kwargs)
+ super(JordanSpinEJA, self).__init__(n, field, **kwargs)
class TrivialEJA(FiniteDimensionalEuclideanJordanAlgebra):
"""
def __init__(self, field=AA, **kwargs):
mult_table = []
- fdeja = super(TrivialEJA, self)
+ super(TrivialEJA, self).__init__(field,
+ mult_table,
+ check_axioms=False,
+ **kwargs)
# The rank is zero using my definition, namely the dimension of the
# largest subalgebra generated by any element.
- fdeja.__init__(field, mult_table, **kwargs)
self.rank.set_cache(0)
+
+
+class DirectSumEJA(FiniteDimensionalEuclideanJordanAlgebra):
+ r"""
+ The external (orthogonal) direct sum of two other Euclidean Jordan
+ algebras. Essentially the Cartesian product of its two factors.
+ Every Euclidean Jordan algebra decomposes into an orthogonal
+ direct sum of simple Euclidean Jordan algebras, so no generality
+ is lost by providing only this construction.
+
+ SETUP::
+
+ sage: from mjo.eja.eja_algebra import (HadamardEJA,
+ ....: RealSymmetricEJA,
+ ....: DirectSumEJA)
+
+ EXAMPLES::
+
+ sage: J1 = HadamardEJA(2)
+ sage: J2 = RealSymmetricEJA(3)
+ sage: J = DirectSumEJA(J1,J2)
+ sage: J.dimension()
+ 8
+ sage: J.rank()
+ 5
+
+ """
+ def __init__(self, J1, J2, field=AA, **kwargs):
+ n1 = J1.dimension()
+ n2 = J2.dimension()
+ n = n1+n2
+ V = VectorSpace(field, n)
+ mult_table = [ [ V.zero() for j in range(n) ]
+ for i in range(n) ]
+ for i in range(n1):
+ for j in range(n1):
+ p = (J1.monomial(i)*J1.monomial(j)).to_vector()
+ mult_table[i][j] = V(p.list() + [field.zero()]*n2)
+
+ for i in range(n2):
+ for j in range(n2):
+ p = (J2.monomial(i)*J2.monomial(j)).to_vector()
+ mult_table[n1+i][n1+j] = V([field.zero()]*n1 + p.list())
+
+ super(DirectSumEJA, self).__init__(field,
+ mult_table,
+ check_axioms=False,
+ **kwargs)
+ self.rank.set_cache(J1.rank() + J2.rank())
projects / sage.d.git / blobdiff