X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_element_subalgebra.py;h=3936ac1fe5c7709165b91114b9e52bd8f47ab683;hb=8adc54235f68f871cdbb66e8854a5a50ce4ad751;hp=73e1cbd9ab34ce1078c6ebaeaade3cc87d3d9448;hpb=ca00d13ae0f578f5debd52eb0986a91c73f3f93d;p=sage.d.git

diff --git a/mjo/eja/eja_element_subalgebra.py b/mjo/eja/eja_element_subalgebra.py
index 73e1cbd..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
@@ -28,11 +42,6 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide
 
             # Pick those out of the list of all powers.
             superalgebra_basis = tuple(map(powers.__getitem__, ind_rows))
-
-            # If our superalgebra is a subalgebra of something else, then
-            # these vectors won't have the right coordinates for
-            # V.span_of_basis() unless we use V.from_vector() on them.
-            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
@@ -47,8 +56,6 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide
             superalgebra_basis = [ self._superalgebra.from_vector(b)
                                    for b in basis_vectors ]
 
-        W = V.span_of_basis( V.from_vector(v) for v in basis_vectors )
-
         fdeja = super(FiniteDimensionalEuclideanJordanElementSubalgebra, self)
         fdeja.__init__(self._superalgebra,
                        superalgebra_basis,
@@ -61,7 +68,7 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide
         # polynomial has the same degree as the space's dimension
         # (remember how we constructed the space?), so that must be
         # its rank too.
-        self.rank.set_cache(W.dimension())
+        self.rank.set_cache(self.dimension())
 
 
     def one(self):