Fixed a bug in vector field conversion (#532)

pde/fields/vectorial.py

@@ -147,10 +147,14 @@ def from_expression(
 
     def __getitem__(self, key: int | str) -> ScalarField:
         """extract a component of the VectorField"""
+        axis = self.grid.get_axis_index(key)
+        comp_name = self.grid.c.axes[axis]
+        if self.label:
+            label = self.label + f"_{comp_name}"
+        else:
+            label = f"{comp_name} component"
         return ScalarField(
-            self.grid,
-            data=self._data_full[self.grid.get_axis_index(key)],
-            with_ghost_cells=True,
+            self.grid, data=self._data_full[axis], label=label, with_ghost_cells=True
         )
 
     def __setitem__(self, key: int | str, value: NumberOrArray | ScalarField):
@@ -590,14 +594,12 @@ def interpolate_to_grid(
         # determine the points at which data needs to be calculated
         if isinstance(grid, CartesianGrid):
             # convert Cartesian coordinates to coordinates in current grid
-            points = self.grid.transform(
-                grid.cell_coords, "cartesian", "grid", full=True
-            )
-            # interpolate the data to the grid; this gives the vector in the grid basis
+            points = self.grid.c.pos_from_cart(grid.cell_coords)
             points_grid_sym = self.grid._coords_symmetric(points)
+            # interpolate the data to the grid; this gives the vector in the grid basis
             data_grid = self.interpolate(points_grid_sym, bc=bc, fill=fill)
             # convert the vector to the cartesian basis
-            data = self.grid._vector_to_cartesian(points, data_grid, coords="grid")
+            data = self.grid._vector_to_cartesian(points, data_grid)
 
         elif (
             self.grid.__class__ is grid.__class__

pde/grids/base.py

@@ -722,18 +722,16 @@ def point_from_cartesian(
             return self._coords_symmetric(points_sph)
 
     def _vector_to_cartesian(
-        self, points: ArrayLike, components: ArrayLike, *, coords: CoordsType = "grid"
+        self, points: ArrayLike, components: ArrayLike
     ) -> np.ndarray:
         """convert the vectors at given points into a Cartesian basis
 
         Args:
             points (:class:`~numpy.ndarray`):
-                The coordinates of the point(s) where the vectors are specified.
+                The coordinates of the point(s) where the vectors are specified. These
+                need to be given in grid coordinates.
             components (:class:`~numpy.ndarray`):
                 The components of the vectors at the given points
-            coords (str):
-                The coordinate system in which the point is specified. Valid values are
-                `cartesian`, `cell`, and `grid`; see :meth:`~pde.grids.base.GridBase.transform`.
 
         Returns:
             The vectors specified at the same position but with components given in
@@ -1118,12 +1116,13 @@ def get_vector_data(self, data: np.ndarray, **kwargs) -> dict[str, Any]:
         img_coord0 = self.get_image_data(data[0], **kwargs)
         img_coord1 = self.get_image_data(data[1], **kwargs)
 
+        points_cart = np.stack((img_coord0["xs"], img_coord0["ys"]), axis=-1)
+        points = self.c._pos_from_cart(points_cart)
+
         # convert vectors to cartesian coordinates
         img_data = img_coord0
         img_data["data_x"], img_data["data_y"] = self._vector_to_cartesian(
-            np.stack((img_coord0["xs"], img_coord0["ys"]), axis=-1),
-            [img_coord0["data"], img_coord1["data"]],
-            coords="cartesian",
+            points, [img_coord0["data"], img_coord1["data"]]
         )
         img_data.pop("data")
         return img_data