diff --git a/galgebra/lt.py b/galgebra/lt.py
index b2e4babb..6a7d3b7d 100644
--- a/galgebra/lt.py
+++ b/galgebra/lt.py
@@ -752,25 +752,17 @@ def __init__(self, f, Ga, nargs=None, fct=False):
             self.f = None
             self.nargs = nargs
             Mlt.increment_slots(nargs, Ga)
-            if nargs > 1:  # General tensor of raank > 1
-                t_indexes = nargs * [Mlt.extact_basis_indexes(self.Ga)]
-                self.fvalue = 0
-                for t_index, a_prod in zip(itertools.product(*t_indexes),
-                                           itertools.product(*self.Ga._mlt_pdiffs)):
-                    if fct:  # Tensor field
-                        coef = Function(f+'_'+''.join(map(str, t_index)), real=True)(*self.Ga.coords)
-                    else:  # Constant Tensor
-                        coef = symbols(f+'_'+''.join(map(str, t_index)), real=True)
-                    coef *= reduce(lambda x, y: x*y, a_prod)
-                    self.fvalue += coef
-            else:  # General tensor of rank = 1
-                self.fvalue = 0
-                for t_index, a_prod in zip(Mlt.extact_basis_indexes(self.Ga), self.Ga._mlt_pdiffs[0]):
-                    if fct:  # Tensor field
-                        coef = Function(f+'_'+''.join(map(str, t_index)), real=True)(*self.Ga.coords)
-                    else:  # Constant Tensor
-                        coef = symbols(f+'_'+''.join(map(str, t_index)), real=True)
-                    self.fvalue += coef * a_prod
+            t_indexes = Mlt.extact_basis_indexes(self.Ga)
+            self.fvalue = S(0)
+            for t_index, a_prod in zip(itertools.product(t_indexes, repeat=self.nargs),
+                                       itertools.product(*self.Ga._mlt_pdiffs)):
+                name = '{}_{}'.format(f, ''.join(map(str, t_index)))
+                if fct:  # Tensor field
+                    coef = Function(name, real=True)(*self.Ga.coords)
+                else:  # Constant Tensor
+                    coef = symbols(name, real=True)
+                self.fvalue += reduce(lambda x, y: x*y, a_prod, coef)
+
         else:
             if isinstance(f, types.FunctionType):  # Tensor defined by general multi-linear function
                 args, _varargs, _kwargs, _defaults = inspect.getargspec(f)