eja: fix a deorthonormalization bug.

[sage.d.git] / mjo / eja / eja_algebra.py

diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py
index 8b37a83602ef9b00b5a14c55785c2163b44df32b..615b0d494af83a132e1d6343fe05917e4ed2eaf7 100644 (file)
--- a/mjo/eja/eja_algebra.py
+++ b/mjo/eja/eja_algebra.py
@@ -319,9 +319,11 @@ class FiniteDimensionalEJA(CombinatorialFreeModule):
         # written out as "long vectors."
         V = VectorSpace(field, degree)
 
-        # The matrix that will hole the orthonormal -> unorthonormal
-        # coordinate transformation.
-        self._deortho_matrix = None
+        # The matrix that will hold the orthonormal -> unorthonormal
+        # coordinate transformation. Default to an identity matrix of
+        # the appropriate size to avoid special cases for None
+        # everywhere.
+        self._deortho_matrix = matrix.identity(field,n)
 
         if orthonormalize:
             # Save a copy of the un-orthonormalized basis for later.
@@ -1753,13 +1755,6 @@ class RationalBasisEJA(FiniteDimensionalEJA):
         a = ( a_i.change_ring(self.base_ring())
               for a_i in self._rational_algebra._charpoly_coefficients() )
 
-        if self._deortho_matrix is None:
-            # This can happen if our base ring was, say, AA and we
-            # chose not to (or didn't need to) orthonormalize. It's
-            # still faster to do the computations over QQ even if
-            # the numbers in the boxes stay the same.
-            return tuple(a)
-
         # Otherwise, convert the coordinate variables back to the
         # deorthonormalized ones.
         R = self.coordinate_polynomial_ring()
@@ -3086,6 +3081,13 @@ class CartesianProductEJA(FiniteDimensionalEJA):
                                       check_field=False,
                                       check_axioms=False)
 
+        # Since we don't (re)orthonormalize the basis, the FDEJA
+        # constructor is going to set self._deortho_matrix to the
+        # identity matrix. Here we set it to the correct value using
+        # the deortho matrices from our factors.
+        self._deortho_matrix = matrix.block_diagonal( [J._deortho_matrix
+                                                       for J in factors] )
+
         self.rank.set_cache(sum(J.rank() for J in factors))
         ones = tuple(J.one().to_matrix() for J in factors)
         self.one.set_cache(self(ones))