examples: add rotated fd section to userapi notebook

devito/finite_differences/derivative.py

@@ -188,12 +188,12 @@ def _process_kwargs(cls, expr, *dims, **kwargs):
 
     def __call__(self, x0=None, fd_order=None, side=None, method=None):
         if self.ndims == 1:
-            _fd_order = fd_order or self._fd_order
-            _side = side or self._side
-            _method = method or self._method
-            new_x0 = {self.dims[0]: x0} if x0 is not None else self.x0
-            return self._new_from_self(fd_order=_fd_order, side=_side, x0=new_x0,
-                                       method=_method)
+            fd_order = fd_order or self._fd_order
+            side = side or self._side
+            method = method or self._method
+            x0 = {self.dims[0]: x0} if x0 is not None else self.x0
+            return self._new_from_self(fd_order=fd_order, side=side, x0=x0,
+                                       method=method)
 
         if side is not None:
             raise TypeError("Side only supported for first order single"

devito/finite_differences/finite_difference.py

@@ -36,7 +36,7 @@ def first_derivative(expr, dim, fd_order=None, side=centered, matvec=direct, x0=
         finite difference. Defaults to `direct`.
     x0 : dict, optional
         Origin of the finite-difference scheme as a map dim: origin_dim.
-    coefficients : strong, optional
+    coefficients : string, optional
         Use taylor or custom coefficients (weights). Defaults to taylor.
     expand : bool, optional
         If True, the derivative is fully expanded as a sum of products,
@@ -220,7 +220,8 @@ def make_derivative(expr, dim, fd_order, deriv_order, side, matvec, x0, coeffici
     indices, x0 = generate_indices(expr, dim, fd_order, side=side, matvec=matvec,
                                    x0=x0)
 
-    # Finite difference weights from Taylor approximation given these positions
+    # Finite difference weights corresponding to the indices. Computed via the
+    # `coefficients` method (`taylor` or `symbolic`)
     weights = fd_weights_registry[coefficients](expr, deriv_order, indices, x0)
 
     # Enforce fixed precision FD coefficients to avoid variations in results