-from sage.functions.other import sqrt
-from sage.matrix.constructor import matrix
-from sage.modules.free_module_element import vector
+from sage.structure.element import is_Matrix
def _scale(x, alpha):
r"""
[3, 4, 1, 0, 0, 0, 0, 0, 0, 0]
"""
- if hasattr(x, 'list') and hasattr(x, 'to_vector'):
- # This avoids calling to_vector() on a matrix algebra with
- # e.g. quaternions where the returned vector is of the wrong
- # length (three instead of four) because the quaternions don't
- # know how many generators they have.
- return _all2list(x.list())
-
if hasattr(x, 'to_vector'):
# This works on matrices of e.g. octonions directly, without
# first needing to convert them to a list of octonions and
# then recursing down into the list. It also avoids the wonky
# list(x) when x is an element of a CFM. I don't know what it
- # returns but it aint the coordinates. This will fall through
- # to the iterable case the next time around.
- return _all2list(x.to_vector())
+ # returns but it aint the coordinates. We don't recurse
+ # because vectors can only contain ring elements as entries.
+ return x.to_vector().list()
+
+ if is_Matrix(x):
+ # This sucks, but for performance reasons we don't want to
+ # call _all2list recursively on the contents of a matrix
+ # when we don't have to (they only contain ring elements
+ # as entries)
+ return x.list()
try:
xl = list(x)
# Avoid the retardation of list(QQ(1)) == [1].
return [x]
- return sum(list( map(_all2list, xl) ), [])
-
+ return sum( map(_all2list, xl) , [])
-def _mat2vec(m):
- return vector(m.base_ring(), m.list())
-
-def _vec2mat(v):
- return matrix(v.base_ring(), sqrt(v.degree()), v.list())
-
def gram_schmidt(v, inner_product=None):
"""
Perform Gram-Schmidt on the list ``v`` which are assumed to be
# cool
return v
- R = v[0].base_ring()
-
# Our "zero" needs to belong to the right space for sum() to work.
zero = v[0].parent().zero()