X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2FTODO;h=45a9ac06bf2c86020dee102143393e486fa408c5;hb=86bf0d59519eef1259fa9fb82457148b28c2fa2e;hp=f27df9cdc14c6e94cabd6a067285bc354ecd3cbe;hpb=7bb608efc474092b1c26286924c8d91a1bf51aaa;p=sage.d.git diff --git a/mjo/eja/TODO b/mjo/eja/TODO index f27df9c..45a9ac0 100644 --- a/mjo/eja/TODO +++ b/mjo/eja/TODO @@ -1,22 +1,22 @@ -1. Add cartesian products to random_eja(). +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. We don't actually need octonions - for this to work, only their real embedding (some 8x8 monstrosity). +3. Profile the construction of "large" matrix algebras (like the + 15-dimensional QuaternionHermitianAlgebra(3)) to find out why + they're so slow. -4. Pre-cache charpoly for some small algebras? +4. What the ever-loving fuck is this shit? -RealSymmetricEJA(4): + sage: O = Octonions(QQ) + sage: e0 = O.monomial(0) + sage: e0*[[[[]]]] + [[[[]]]]*e0 -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. Every once in a long while, the test -5. Profile the construction of "large" matrix algebras (like the - 15-dimensional QuaternionHermitianAlgebra(3)) to find out why - they're so slow. + sage: set_random_seed() + sage: x = random_eja().random_element() + sage: x.is_invertible() == (x.det() != 0) -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. + in eja_element.py returns False.