X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2FTODO;h=70e945ed4bbe499bd6dde2a92c0153e30f1dede0;hb=5b1f16399286eba471884a1cfe45247b3a0a7693;hp=93aa9fb42e6ec6cdba6963db8dacfddd116ba762;hpb=21fa036e86711c6c28b6d89af2b1bfe4ceb24b29;p=sage.d.git

diff --git a/mjo/eja/TODO b/mjo/eja/TODO
index 93aa9fb..70e945e 100644
--- a/mjo/eja/TODO
+++ b/mjo/eja/TODO
@@ -1,7 +1,4 @@
-1. Finish CartesianProductEJA: add to_matrix(), random_instance(),...
-   methods. I guess we should create a separate class hierarchy for
-   Cartesian products of RationalBasisEJA? That way we get fast
-   charpoly and random_instance() defined...
+1. Add cartesian products to random_eja().
 
 2. Add references and start citing them.
 
@@ -14,9 +11,16 @@ RealSymmetricEJA(4):
 sage: F = J.base_ring()
 sage: a0 = (1/4)*X[4]**2*X[6]**2 - (1/2)*X[2]*X[5]*X[6]**2 - (1/2)*X[3]*X[4]*X[6]*X[7] + (F(2).sqrt()/2)*X[1]*X[5]*X[6]*X[7] + (1/4)*X[3]**2*X[7]**2 - (1/2)*X[0]*X[5]*X[7]**2 + (F(2).sqrt()/2)*X[2]*X[3]*X[6]*X[8] - (1/2)*X[1]*X[4]*X[6*X[8] - (1/2)*X[1]*X[3]*X[7]*X[8] + (F(2).sqrt()/2)*X[0]*X[4]*X[7]*X[8] + (1/4)*X[1]**2*X[8]**2 - (1/2)*X[0]*X[2]*X[8]**2 - (1/2)*X[2]*X[3]**2*X[9] + (F(2).sqrt()/2)*X[1]*X[3]*X[4]*X[9] - (1/2)*X[0]*X[4]**2*X[9] - (1/2)*X[1]**2*X[5]*X[9] + X[0]*X[2]*X[5]*X[9]
 
-5. The main EJA element constructor is happy to convert between
-   e.g. HadamardEJA(3) and JordanSpinEJA(3).
-
-6. Profile the construction of "large" matrix algebras (like the
+5. Profile the construction of "large" matrix algebras (like the
    15-dimensional QuaternionHermitianAlgebra(3)) to find out why
    they're so slow.
+
+6. We should compute whether or not the algebra is associative if it
+   is unknown. I guess the "associative" argument should be ternary
+   (True, False, None)? We should also figure out the correct
+   True/False values for the example classes, and of course add an
+   _is_associative() method.
+
+7. When field=RDF, subalgebra construction is failing because the
+   inner product isn't associative? Actually, it's the combination
+   of field=RDF and orthonormalize=True.