eja: update a comment.

diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py
index 55b8207ddc3f881e8d98f245bf0275bc4b947334..a77bb871def9264ac0a82dfea4737b6c2b4411fc 100644 (file)
--- a/mjo/eja/eja_algebra.py
+++ b/mjo/eja/eja_algebra.py
@@ -2765,15 +2765,10 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
         # Use whatever category the superclass came up with. Usually
         # some join of the EJA and Cartesian product
         # categories. There's no need to check the field since it
-        # already came from an EJA. Likewise the axioms are guaranteed
-        # to be satisfied. We can't orthonormalize by default because
-        # there's no way to pass "orthonormalize=False" to
-        # cartesian_product(...) when the base ring is QQ and
-        # orthonormalizing would give us irrational entries.
+        # already came from an EJA.
         #
-        # TODO: create a separate constructor that is capable of
-        # orthonormalizing and is only used by the cartesian_product()
-        # thingy.
+        # If you want the basis to be orthonormalized, orthonormalize
+        # the factors.
         FiniteDimensionalEJA.__init__(self,
                                       basis,
                                       jordan_product,
@@ -2783,16 +2778,6 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
                                       check_field=False,
                                       check_axioms=False,
                                       category=self.category())
-        # TODO:
-        #
-        # Initialize the FDEJA class, too. Does this override the
-        # initialization that we did for the
-        # CombinatorialFreeModule_CartesianProduct class? If not, we
-        # will probably have to duplicate some of the work (i.e. one
-        # of the constructors).  Since the CartesianProduct one is
-        # smaller, that makes the most sense to copy/paste if it comes
-        # down to that.
-        #
 
         self.rank.set_cache(sum(J.rank() for J in modules))