from sage.modules.with_basis.indexed_element import IndexedFreeModuleElement
from mjo.eja.eja_operator import FiniteDimensionalEJAOperator
-from mjo.eja.eja_utils import _mat2vec
+from mjo.eja.eja_utils import _mat2vec, _scale
class FiniteDimensionalEJAElement(IndexedFreeModuleElement):
"""
M = matrix([(self.parent().one()).to_vector()])
old_rank = 1
- # Specifying the row-reduction algorithm can e.g. help over
+ # Specifying the row-reduction algorithm can e.g. help over
# AA because it avoids the RecursionError that gets thrown
# when we have to look too hard for a root.
#
if self.parent()._matrix_basis_is_cartesian:
# Aaaaand linear combinations don't work in Cartesian
# product spaces, even though they provide a method
- # with that name.
+ # with that name. This is special-cased because the
+ # _scale() function is slow.
pairs = zip(B, self.to_vector())
- return sum( ( W(tuple(alpha*b_i for b_i in b))
- for (b,alpha) in pairs ),
+ return sum( ( _scale(b, alpha) for (b,alpha) in pairs ),
W.zero())
else:
# This is just a manual "from_vector()", but of course
"""
powers = tuple( self**k for k in range(self.degree()) )
- A = self.parent().subalgebra(powers, associative=True, **kwargs)
+ A = self.parent().subalgebra(powers,
+ associative=True,
+ check_field=False,
+ check_axioms=False,
+ **kwargs)
A.one.set_cache(A(self.parent().one()))
return A