api: fix derivative kwargs at call

.github/workflows/examples-mpi.yml

@@ -48,6 +48,11 @@ jobs:
     - name: Checkout devito
       uses: actions/checkout@v4
 
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: 3.11
+
     - name: Setup MPI
       uses: mpi4py/setup-mpi@v1
       with:

.github/workflows/examples.yml

@@ -46,7 +46,7 @@ jobs:
 
     - name: Install dependencies
       run: |
-        pip install -e .[tests,extras]
+        pip install -e .
 
     - name: Tests in examples
       run: |

devito/finite_differences/derivative.py

@@ -219,35 +219,44 @@ def _process_weights(cls, **kwargs):
             return as_tuple(weights)
 
     def __call__(self, x0=None, fd_order=None, side=None, method=None, weights=None):
-        side = side or self._side
-        method = method or self._method
-        weights = weights if weights is not None else self._weights
-
-        x0 = self._process_x0(self.dims, x0=x0)
-        _x0 = frozendict({**self.x0, **x0})
-
-        _fd_order = dict(self.fd_order.getters)
-        try:
-            _fd_order.update(fd_order or {})
-        except TypeError:
-            assert self.ndims == 1
-            _fd_order.update({self.dims[0]: fd_order or self.fd_order[0]})
-        except AttributeError:
-            raise TypeError("fd_order incompatible with dimensions")
+        rkw = {}
+        if side is not None:
+            rkw['side'] = side
+        if method is not None:
+            rkw['method'] = method
+        if weights is not None:
+            rkw['weights'] = weights
+
+        if x0 is not None:
+            x0 = self._process_x0(self.dims, x0=x0)
+            rkw['x0'] = frozendict({**self.x0, **x0})
+
+        if fd_order is not None:
+            try:
+                _fd_order = dict(fd_order)
+            except TypeError:
+                assert self.ndims == 1
+                _fd_order = {self.dims[0]: fd_order}
+            except AttributeError:
+                raise TypeError("fd_order incompatible with dimensions")
 
         if isinstance(self.expr, Derivative):
             # In case this was called on a perfect cross-derivative `u.dxdy`
             # we need to propagate the call to the nested derivative
-            x0s = self._filter_dims(self.expr._filter_dims(_x0), neg=True)
-            expr = self.expr(x0=x0s, fd_order=self.expr._filter_dims(_fd_order),
-                             side=side, method=method)
-        else:
-            expr = self.expr
-
-        _fd_order = self._filter_dims(_fd_order, as_tuple=True)
-
-        return self._rebuild(fd_order=_fd_order, x0=_x0, side=side, method=method,
-                             weights=weights, expr=expr)
+            rkwe = dict(rkw)
+            if 'x0' in rkwe:
+                rkwe['x0'] = self._filter_dims(self.expr._filter_dims(rkw['x0']),
+                                               neg=True)
+            if fd_order is not None:
+                fdo = self.expr._filter_dims(_fd_order)
+                if fdo:
+                    rkwe['fd_order'] = fdo
+            rkw['expr'] = self.expr(**rkwe)
+
+        if fd_order is not None:
+            rkw['fd_order'] = self._filter_dims(_fd_order, as_tuple=True)
+
+        return self._rebuild(**rkw)
 
     def _rebuild(self, *args, **kwargs):
         kwargs['preprocessed'] = True

environment-dev.yml

@@ -6,3 +6,5 @@ dependencies:
   - pip>=21.1.2
   - pip:
     - -r requirements.txt
+    - -r requirements-optional.txt
+    - -r requirements-testing.txt

tests/test_derivatives.py

@@ -743,6 +743,24 @@ def test_cross_newnest(self):
 
         assert f.dxdy == f.dx.dy
 
+    def test_nested_call(self):
+        grid = Grid((11, 11))
+        x, y = grid.dimensions
+        f = Function(name="f", grid=grid, space_order=8)
+
+        deriv = Derivative(f, x, y, deriv_order=(0, 0), fd_order=(2, 2),
+                           x0={x: x-x.spacing/2, y: y+y.spacing/2}).dy(x0=y-y.spacing/2)
+
+        derivc = Derivative(f.dy(x0=y-y.spacing/2), x, y, deriv_order=(0, 0),
+                            fd_order=(2, 2), x0={x: x-x.spacing/2, y: y+y.spacing/2})
+
+        assert deriv.expr.fd_order == (2, 2)
+        assert deriv.expr.deriv_order == (0, 0)
+        assert deriv.expr.x0 == {x: x-x.spacing/2, y: y+y.spacing/2}
+
+        # Should be commutative
+        assert simplify(deriv.evaluate - derivc.evaluate) == 0
+
 
 class TestTwoStageEvaluation: