X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_element_subalgebra.py;h=3936ac1fe5c7709165b91114b9e52bd8f47ab683;hb=fe2af66b109e9487a59f21d5b67bb5c4aafdc98d;hp=a26381b12dbe649d5dad9bc0cd056adbb1606f62;hpb=8b85fd74f79fe1eb23e9f04bfd73b7d3cbf9b554;p=sage.d.git diff --git a/mjo/eja/eja_element_subalgebra.py b/mjo/eja/eja_element_subalgebra.py index a26381b..3936ac1 100644 --- a/mjo/eja/eja_element_subalgebra.py +++ b/mjo/eja/eja_element_subalgebra.py @@ -1,4 +1,5 @@ from sage.matrix.constructor import matrix +from sage.rings.all import QQ from mjo.eja.eja_subalgebra import FiniteDimensionalEuclideanJordanSubalgebra @@ -18,6 +19,19 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide P = matrix(field, power_vectors) if orthonormalize_basis == False: + # Echelonize the matrix ourselves, because otherwise the + # call to P.pivot_rows() below can choose a non-optimal + # row-reduction algorithm. In particular, scaling can + # help over AA because it avoids the RecursionError that + # gets thrown when we have to look too hard for a root. + # + # Beware: QQ supports an entirely different set of "algorithm" + # keywords than do AA and RR. + algo = None + if field is not QQ: + algo = "scaled_partial_pivoting" + P.echelonize(algorithm=algo) + # In this case, we just need to figure out which elements # of the "powers" list are redundant... First compute the # vector subspace spanned by the powers of the given @@ -28,7 +42,6 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide # Pick those out of the list of all powers. superalgebra_basis = tuple(map(powers.__getitem__, ind_rows)) - basis_vectors = map(power_vectors.__getitem__, ind_rows) else: # If we're going to orthonormalize the basis anyway, we # might as well just do Gram-Schmidt on the whole list of