From 8adc54235f68f871cdbb66e8854a5a50ce4ad751 Mon Sep 17 00:00:00 2001 From: Michael Orlitzky Date: Sat, 21 Nov 2020 13:57:32 -0500 Subject: [PATCH] eja: minor improvement to the algebra one() method. --- mjo/eja/eja_algebra.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) 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): -- 2.43.2