X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2FTODO;h=529f70fd633bf36275c63282a05614f1109a7df0;hb=d9b0659df5d8ad61f457674e009180618dffef67;hp=13b00ac6a3056eaf623ac5c2905be6c7d049706c;hpb=db1f7761ebf564221669137ae07476ea45d82a2c;p=sage.d.git diff --git a/mjo/eja/TODO b/mjo/eja/TODO index 13b00ac..529f70f 100644 --- a/mjo/eja/TODO +++ b/mjo/eja/TODO @@ -1,37 +1,25 @@ -1. Add cartesian products to random_eja(). +1. Add references and start citing them. -2. Add references and start citing them. +2. Profile (and fix?) any remaining slow operations. -3. Implement the octonion simple EJA. We don't actually need octonions - for this to work, only their real embedding (some 8x8 monstrosity). +3. Every once in a long while, the test -4. Pre-cache charpoly for some small algebras? + sage: set_random_seed() + sage: x = random_eja().random_element() + sage: x.is_invertible() == (x.det() != 0) -RealSymmetricEJA(4): + in eja_element.py returns False. Example: -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] + 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 -5. Profile the construction of "large" matrix algebras (like the - 15-dimensional QuaternionHermitianAlgebra(3)) to find out why - they're so slow. - -6. Instead of storing a basis multiplication matrix, just make - product_on_basis() a cached method and manually cache its - entries. The cython cached method lookup should be faster than a - python-based matrix lookup anyway. - -7. What the ever-loving fuck is this shit? - - sage: O = Octonions(QQ) - sage: e0 = O.monomial(0) - sage: e0*[[[[]]]] - [[[[]]]]*e0 - -8. In fact, could my octonion matrix algebra be generalized for any - algebra of matrices over the reals whose entries are not real? Then - we wouldn't need real embeddings at all. They might even be fricking - vector spaces if I did that... - -9. Add HurwitzMatrixAlgebra subclass between MatrixAlgebra and - OctonionMatrixAlgebra. +4. 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...