From: Michael Orlitzky <michael@orlitzky.com>
Date: Sat, 21 Nov 2020 18:57:32 +0000 (-0500)
Subject: eja: minor improvement to the algebra one() method.
X-Git-Url: https://gitweb.michael.orlitzky.com/?a=commitdiff_plain;h=8adc54235f68f871cdbb66e8854a5a50ce4ad751;p=sage.d.git

eja: minor improvement to the algebra one() method.
---

diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py
index 7089c50..222b12c 100644
--- a/mjo/eja/eja_algebra.py
+++ b/mjo/eja/eja_algebra.py
@@ -599,19 +599,20 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule):
         # appeal to the "long vectors" isometry.
         oper_vecs = [ _mat2vec(g.operator().matrix()) for g in self.gens() ]
 
-        # Now we use basis linear algebra to find the coefficients,
+        # Now we use basic linear algebra to find the coefficients,
         # of the matrices-as-vectors-linear-combination, which should
         # work for the original algebra basis too.
-        A = matrix.column(self.base_ring(), oper_vecs)
+        A = matrix(self.base_ring(), oper_vecs)
 
         # We used the isometry on the left-hand side already, but we
         # still need to do it for the right-hand side. Recall that we
         # wanted something that summed to the identity matrix.
         b = _mat2vec( matrix.identity(self.base_ring(), self.dimension()) )
 
-        # Now if there's an identity element in the algebra, this should work.
-        coeffs = A.solve_right(b)
-        return self.linear_combination(zip(self.gens(), coeffs))
+        # Now if there's an identity element in the algebra, this
+        # should work. We solve on the left to avoid having to
+        # transpose the matrix "A".
+        return self.from_vector(A.solve_left(b))
 
 
     def peirce_decomposition(self, c):