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()
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