-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 _charpoly_sage_input(s):
r"""
SETUP::
+ sage: from mjo.eja.eja_algebra import JordanSpinEJA
sage: from mjo.eja.eja_utils import _charpoly_sage_input
EXAMPLES::
sage: J = JordanSpinEJA(4,QQ)
- sage: J._charpoly_coefficients()[0]
+ sage: a = J._charpoly_coefficients()
+ sage: a[0]
X1^2 - X2^2 - X3^2 - X4^2
- sage: _charpoly_sage_input("X1^2 - X2^2 - X3^2 - X4^2")
+ sage: _charpoly_sage_input(str(a[0]))
'X[0]**2 - X[1]**2 - X[2]**2 - X[3]**2'
"""
# 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) ), [])
-
-
-
-def _mat2vec(m):
- return vector(m.base_ring(), m.list())
+ return sum( map(_all2list, xl) , [])
-def _vec2mat(v):
- return matrix(v.base_ring(), sqrt(v.degree()), v.list())
def gram_schmidt(v, inner_product=None):
"""