IndexSum: Factor out common factors if possible

test/test_apply_function_pullbacks.py

@@ -151,8 +151,8 @@ def test_apply_single_function_pullbacks_triangle3d():
         vc: as_vector(Jinv[j, i] * rvc[j], i),
         t: rt,
         s: as_tensor([[rs[0], rs[1], rs[2]], [rs[1], rs[3], rs[4]], [rs[2], rs[4], rs[5]]]),
-        cov2t: as_tensor(Jinv[k, i] * rcov2t[k, l] * Jinv[l, j], (i, j)),
-        contra2t: as_tensor((1.0 / detJ) ** 2 * J[i, k] * rcontra2t[k, l] * J[j, l], (i, j)),
+        cov2t: as_tensor(Jinv[k, i] * (rcov2t[k, l] * Jinv[l, j]), (i, j)),
+        contra2t: (1.0 / detJ) ** 2 * as_tensor(J[i, k] * (rcontra2t[k, l] * J[j, l]), (i, j)),
         # Mixed elements become a bit more complicated
         uml2: as_vector([ruml2[0] / detJ, ruml2[1] / detJ]),
         um: rum,

ufl/indexsum.py

@@ -6,6 +6,7 @@
 #
 # SPDX-License-Identifier:    LGPL-3.0-or-later
 
+from ufl.algebra import Product
 from ufl.constantvalue import Zero
 from ufl.core.expr import Expr, ufl_err_str
 from ufl.core.multiindex import MultiIndex
@@ -21,7 +22,7 @@
 class IndexSum(Operator):
     """Index sum."""
 
-    __slots__ = ("_dimension", "ufl_free_indices", "ufl_index_dimensions")
+    __slots__ = ("_dimension", "_initialised", "ufl_free_indices", "ufl_index_dimensions")
 
     def __new__(cls, summand, index):
         """Create a new IndexSum."""
@@ -33,21 +34,33 @@ def __new__(cls, summand, index):
         if len(index) != 1:
             raise ValueError(f"Expecting a single Index but got {len(index)}.")
 
+        (j,) = index
         # Simplification to zero
         if isinstance(summand, Zero):
             sh = summand.ufl_shape
-            (j,) = index
             fi = summand.ufl_free_indices
             fid = summand.ufl_index_dimensions
             pos = fi.index(j.count())
             fi = fi[:pos] + fi[pos + 1 :]
             fid = fid[:pos] + fid[pos + 1 :]
             return Zero(sh, fi, fid)
 
-        return Operator.__new__(cls)
+        # Factor out common factors
+        if isinstance(summand, Product):
+            a, b = summand.ufl_operands
+            if j.count() not in a.ufl_free_indices:
+                return Product(a, IndexSum(b, index))
+            elif j.count() not in b.ufl_free_indices:
+                return Product(b, IndexSum(a, index))
+
+        self = Operator.__new__(cls)
+        self._initialised = False
+        return self
 
     def __init__(self, summand, index):
         """Initialise."""
+        if self._initialised:
+            return
         (j,) = index
         fi = summand.ufl_free_indices
         fid = summand.ufl_index_dimensions
@@ -56,6 +69,7 @@ def __init__(self, summand, index):
         self.ufl_free_indices = fi[:pos] + fi[pos + 1 :]
         self.ufl_index_dimensions = fid[:pos] + fid[pos + 1 :]
         Operator.__init__(self, (summand, index))
+        self._initialised = True
 
     def index(self):
         """Get index."""

ufl/pullback.py

@@ -270,7 +270,7 @@ def apply(self, expr):
         # Apply transform "row-wise" to TensorElement(PiolaMapped, ...)
         *k, i, j, m, n = indices(len(expr.ufl_shape) + 2)
         kmn = (*k, m, n)
-        return as_tensor((1.0 / detJ) ** 2 * J[i, m] * expr[kmn] * J[j, n], (*k, i, j))
+        return (1.0 / detJ) ** 2 * as_tensor(J[i, m] * (expr[kmn] * J[j, n]), (*k, i, j))
 
     def physical_value_shape(self, element, domain) -> typing.Tuple[int, ...]:
         """Get the physical value shape when this pull back is applied to an element on a domain.
@@ -313,7 +313,7 @@ def apply(self, expr):
         # Apply transform "row-wise" to TensorElement(PiolaMapped, ...)
         *k, i, j, m, n = indices(len(expr.ufl_shape) + 2)
         kmn = (*k, m, n)
-        return as_tensor(K[m, i] * expr[kmn] * K[n, j], (*k, i, j))
+        return as_tensor(K[m, i] * (expr[kmn] * K[n, j]), (*k, i, j))
 
     def physical_value_shape(self, element, domain) -> typing.Tuple[int, ...]:
         """Get the physical value shape when this pull back is applied to an element on a domain.
@@ -358,7 +358,7 @@ def apply(self, expr):
         # Apply transform "row-wise" to TensorElement(PiolaMapped, ...)
         *k, i, j, m, n = indices(len(expr.ufl_shape) + 2)
         kmn = (*k, m, n)
-        return as_tensor((1.0 / detJ) * K[m, i] * expr[kmn] * J[j, n], (*k, i, j))
+        return (1.0 / detJ) * as_tensor(K[m, i] * (expr[kmn] * J[j, n]), (*k, i, j))
 
     def physical_value_shape(self, element, domain) -> typing.Tuple[int, ...]:
         """Get the physical value shape when this pull back is applied to an element.