2. Profile (and fix?) any remaining slow operations.
-3. Every once in a long while, the test
-
- sage: set_random_seed()
- sage: x = random_eja().random_element()
- sage: x.is_invertible() == (x.det() != 0)
-
- in eja_element.py returns False. Example:
-
- sage: J1 = ComplexHermitianEJA(2)
- sage: J2 = TrivialEJA()
- sage: J = cartesian_product([J1,J2])
- sage: x = J.from_vector(vector(QQ, [-1, -1/2, -1/2, -1/2]))
- sage: x.is_invertible()
- True
- sage: x.det()
- 0
-
-4. When we take a Cartesian product involving a trivial algebra, we
+3. When we take a Cartesian product involving a trivial algebra, we
could easily cache the identity and charpoly coefficients using
the nontrivial factor. On the other hand, it's nice that we can
test out some alternate code paths...
+
+4. Can we hit "x" with the deortho matrix and delegate to the
+ _rational_algebra to speed up minimal_polynomial?
+
+5. In CartesianProductEJA we already know the multiplication table and
+ inner product matrix. Refactor things until it's no longer
+ necessary to duplicate that work.