-1. Add CartesianProductEJA.
+1. Add references and start citing them.
-2. Add references and start citing them.
+2. Pre-cache charpoly for some more algebras.
-3. Implement the octonion simple EJA.
+3. Profile the construction of "large" matrix algebras (like the
+ 15-dimensional QuaternionHermitianAlgebra(3)) to find out why
+ they're so slow.
-4. Factor out the unit-norm basis (and operator symmetry) tests once
- all of the algebras pass.
+4. What the ever-loving fuck is this shit?
-5. Override random_instance(), one(), et cetera in DirectSumEJA.
+ sage: O = Octonions(QQ)
+ sage: e0 = O.monomial(0)
+ sage: e0*[[[[]]]]
+ [[[[]]]]*e0
-6. Switch to QQ in *all* algebras for _charpoly_coefficients().
- This only works when we know that the basis can be rationalized...
- which is the case at least for the concrete EJAs we provide,
- but not in general.
+5. Every once in a long while, the test
-7. Pass already_echelonized (default: False) and echelon_basis
- (default: None) into the subalgebra constructor. The value of
- already_echelonized can be passed to V.span_of_basis() to save
- some time, and usinf e.g. FreeModule_submodule_with_basis_field
- we may somehow be able to pass the echelon basis straight in to
- save time.
+ sage: set_random_seed()
+ sage: x = random_eja().random_element()
+ sage: x.is_invertible() == (x.det() != 0)
- This may require supporting "basis" as a list of basis vectors
- (as opposed to superalgebra elements) in the subalgebra constructor.
-
-8. Implement random_instance() for general algebras as random_eja().
- Copy/paste the "general" construction into the other classes that
- can use it. The general construction can be something like "call
- random_instance() on something that inherits me and return the
- result."
+ in eja_element.py returns False.