deortho_vector_basis = tuple( V(b.list()) for b in basis )
from mjo.eja.eja_utils import gram_schmidt
- basis = gram_schmidt(basis, inner_product)
+ basis = tuple(gram_schmidt(basis, inner_product))
# Save the (possibly orthonormalized) matrix basis for
# later...
# Now we actually compute the multiplication and inner-product
# tables/matrices using the possibly-orthonormalized basis.
- self._inner_product_matrix = matrix.zero(field, n)
+ self._inner_product_matrix = matrix.identity(field, n)
self._multiplication_table = [ [0 for j in range(i+1)]
for i in range(n) ]
q_i = basis[i]
q_j = basis[j]
- elt = jordan_product(q_i, q_j)
- ip = inner_product(q_i, q_j)
-
# The jordan product returns a matrixy answer, so we
# have to convert it to the algebra coordinates.
+ elt = jordan_product(q_i, q_j)
elt = W.coordinate_vector(V(elt.list()))
self._multiplication_table[i][j] = self.from_vector(elt)
- self._inner_product_matrix[i,j] = ip
- self._inner_product_matrix[j,i] = ip
+
+ if not orthonormalize:
+ # If we're orthonormalizing the basis with respect
+ # to an inner-product, then the inner-product
+ # matrix with respect to the resulting basis is
+ # just going to be the identity.
+ ip = inner_product(q_i, q_j)
+ self._inner_product_matrix[i,j] = ip
+ self._inner_product_matrix[j,i] = ip
self._inner_product_matrix._cache = {'hermitian': True}
self._inner_product_matrix.set_immutable()
This method should of course always return ``True``, unless
this algebra was constructed with ``check_axioms=False`` and
- passed an invalid multiplication table.
+ passed an invalid Jordan or inner-product.
"""
# Used to check whether or not something is zero in an inexact
jordan_product,
inner_product,
field=AA,
- orthonormalize=True,
check_field=True,
- check_axioms=True,
**kwargs):
if check_field:
field=QQ,
orthonormalize=False,
check_field=False,
- check_axioms=False,
- **kwargs)
+ check_axioms=False)
super().__init__(basis,
jordan_product,
inner_product,
field=field,
check_field=check_field,
- check_axioms=check_axioms,
**kwargs)
@cached_method
a = ( a_i.change_ring(self.base_ring())
for a_i in self._rational_algebra._charpoly_coefficients() )
- # Now convert the coordinate variables back to the
+ if self._deortho_matrix is None:
+ # This can happen if our base ring was, say, AA and we
+ # chose not to (or didn't need to) orthonormalize. It's
+ # still faster to do the computations over QQ even if
+ # the numbers in the boxes stay the same.
+ return tuple(a)
+
+ # Otherwise, convert the coordinate variables back to the
# deorthonormalized ones.
R = self.coordinate_polynomial_ring()
from sage.modules.free_module_element import vector
....: for j in range(n-1) ]
sage: actual == expected
True
+
"""
def __init__(self, B, **kwargs):
- if not B.is_positive_definite():
- raise ValueError("bilinear form is not positive-definite")
+ # The matrix "B" is supplied by the user in most cases,
+ # so it makes sense to check whether or not its positive-
+ # definite unless we are specifically asked not to...
+ if ("check_axioms" not in kwargs) or kwargs["check_axioms"]:
+ if not B.is_positive_definite():
+ raise ValueError("bilinear form is not positive-definite")
+
+ # However, all of the other data for this EJA is computed
+ # by us in manner that guarantees the axioms are
+ # satisfied. So, again, unless we are specifically asked to
+ # verify things, we'll skip the rest of the checks.
+ if "check_axioms" not in kwargs: kwargs["check_axioms"] = False
def inner_product(x,y):
return (y.T*B*x)[0,0]
xbar = x[1:,0]
y0 = y[0,0]
ybar = y[1:,0]
- z0 = (y.T*x)[0,0]
+ z0 = inner_product(y,x)
zbar = y0*xbar + x0*ybar
- return P([0] + zbar.list())
-
- # 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
+ return P([z0] + zbar.list())
n = B.nrows()
column_basis = tuple( b.column() for b in FreeModule(ZZ, n).basis() )
projects / sage.d.git / blobdiff