Revert "fix: restore Grid1D support in decorators — used by workspace scripts"

This reverts commit 8f22034.

Author: Jammy2211

autoarray/structures/decorators/abstract.py

@@ -1,10 +1,6 @@
-from typing import Union
-
 import numpy as np
 
-from autoarray.mask.mask_1d import Mask1D
 from autoarray.mask.mask_2d import Mask2D
-from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.uniform_2d import Grid2D
 
@@ -62,7 +58,7 @@ def _xp(self):
         return np
 
     @property
-    def mask(self) -> Union[Mask1D, Mask2D]:
+    def mask(self) -> Mask2D:
         return self.grid.mask
 
     @property
@@ -75,14 +71,8 @@ def via_grid_2d(self, result):
     def via_grid_2d_irr(self, result):
         raise NotImplementedError
 
-    def via_grid_1d(self, result):
-        raise NotImplementedError
-
     @property
     def evaluate_func(self):
-        if isinstance(self.grid, Grid1D):
-            grid = self.grid.grid_2d_radial_projected_from()
-            return self.func(self.obj, grid, self._xp, *self.args, **self.kwargs)
         return self.func(self.obj, self.grid, self._xp, *self.args, **self.kwargs)
 
     @property
@@ -103,7 +93,5 @@ def result(self):
             return self.via_grid_2d(self.evaluate_func)
         elif isinstance(self.grid, Grid2DIrregular):
             return self.via_grid_2d_irr(self.evaluate_func)
-        elif isinstance(self.grid, Grid1D):
-            return self.via_grid_1d(self.evaluate_func)
 
         return self.evaluate_func

autoarray/structures/decorators/to_array.py

@@ -3,10 +3,8 @@
 from typing import List, Union
 
 from autoarray.structures.arrays.irregular import ArrayIrregular
-from autoarray.structures.arrays.uniform_1d import Array1D
 from autoarray.structures.arrays.uniform_2d import Array2D
 from autoarray.structures.decorators.abstract import AbstractMaker
-from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.uniform_2d import Grid2D
 
@@ -22,11 +20,6 @@ def via_grid_2d_irr(self, result) -> Union[ArrayIrregular, List[ArrayIrregular]]
             return ArrayIrregular(values=result)
         return [ArrayIrregular(values=res) for res in result]
 
-    def via_grid_1d(self, result) -> Union[Array1D, List[Array1D]]:
-        if not isinstance(result, list):
-            return Array1D(values=result, mask=self.mask)
-        return [Array1D(values=res, mask=self.mask) for res in result]
-
 
 def to_array(func):
     """
@@ -46,11 +39,11 @@ def to_array(func):
     @wraps(func)
     def wrapper(
         obj: object,
-        grid: Union[np.ndarray, Grid2D, Grid2DIrregular, Grid1D],
+        grid: Union[np.ndarray, Grid2D, Grid2DIrregular],
         xp=np,
         *args,
         **kwargs,
-    ) -> Union[np.ndarray, Array1D, Array2D, ArrayIrregular, List]:
+    ) -> Union[np.ndarray, Array2D, ArrayIrregular, List]:
         return ArrayMaker(func=func, obj=obj, grid=grid, xp=xp, *args, **kwargs).result
 
     return wrapper

autoarray/structures/decorators/to_grid.py

@@ -3,7 +3,6 @@
 from typing import List, Union
 
 from autoarray.structures.decorators.abstract import AbstractMaker
-from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.uniform_2d import Grid2D
 
@@ -35,13 +34,6 @@ def via_grid_2d_irr(self, result) -> Union[Grid2DIrregular, List[Grid2DIrregular
             return Grid2DIrregular(values=result)
         return [Grid2DIrregular(values=res) for res in result]
 
-    def via_grid_1d(self, result) -> Union[Grid2D, List[Grid2D]]:
-        if not isinstance(result, list):
-            return Grid2D(values=result, mask=self.mask.derive_mask.to_mask_2d)
-        return [
-            Grid2D(values=res, mask=self.mask.derive_mask.to_mask_2d) for res in result
-        ]
-
 
 def to_grid(func):
     """
@@ -61,7 +53,7 @@ def to_grid(func):
     @wraps(func)
     def wrapper(
         obj: object,
-        grid: Union[np.ndarray, Grid2D, Grid2DIrregular, Grid1D],
+        grid: Union[np.ndarray, Grid2D, Grid2DIrregular],
         xp=np,
         *args,
         **kwargs,

autoarray/structures/decorators/to_vector_yx.py

@@ -3,7 +3,6 @@
 from typing import List, Union
 
 from autoarray.structures.decorators.abstract import AbstractMaker
-from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.uniform_2d import Grid2D
 from autoarray.structures.vectors.irregular import VectorYX2DIrregular

autoarray/structures/decorators/transform.py

@@ -2,7 +2,6 @@
 import numpy as np
 from typing import Union
 
-from autoarray.structures.grids.uniform_1d import Grid1D
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 from autoarray.structures.grids.uniform_2d import Grid2D
 

test_autoarray/structures/decorators/test_to_array.py

@@ -3,22 +3,6 @@
 import autoarray as aa
 
 
-def test__in_grid_1d__out_ndarray_1d_list():
-    mask = aa.Mask1D(mask=[True, False, False, True], pixel_scales=(1.0,))
-
-    grid_1d = aa.Grid1D.from_mask(mask=mask)
-
-    obj = aa.m.MockGrid2DLikeObj()
-
-    ndarray_1d_list = obj.ndarray_1d_list_from(grid=grid_1d)
-
-    assert isinstance(ndarray_1d_list[0], aa.Array1D)
-    assert (ndarray_1d_list[0].native == np.array([[0.0, 1.0, 1.0, 0.0]])).all()
-
-    assert isinstance(ndarray_1d_list[1], aa.Array1D)
-    assert (ndarray_1d_list[1].native == np.array([[0.0, 2.0, 2.0, 0.0]])).all()
-
-
 def test__in_grid_2d__out_ndarray_1d_list():
     mask = aa.Mask2D(
         mask=[

test_autoarray/structures/decorators/test_to_grid.py

@@ -4,41 +4,6 @@
 import autoarray as aa
 
 
-def test__in_grid_1d__out_ndarray_2d():
-    mask_1d = aa.Mask1D(mask=[True, False, False, True], pixel_scales=(1.0,))
-
-    grid_1d = aa.Grid1D.from_mask(mask=mask_1d)
-
-    obj = aa.m.MockGrid2DLikeObj()
-
-    ndarray_2d = obj.ndarray_2d_from(grid=grid_1d)
-
-    assert isinstance(ndarray_2d, aa.Grid2D)
-    assert ndarray_2d.native == pytest.approx(
-        np.array([[[0.0, 0.0], [0.0, -1.0], [0.0, 1.0], [0.0, 0.0]]]), abs=1.0e-4
-    )
-
-
-def test__in_dgrid_1d__out_ndarray_2d_list():
-    mask = aa.Mask1D(mask=[True, False, False, True], pixel_scales=(1.0,))
-
-    grid_1d = aa.Grid1D.from_mask(mask=mask)
-
-    obj = aa.m.MockGrid2DLikeObj()
-
-    ndarray_2d_list = obj.ndarray_2d_list_from(grid=grid_1d)
-
-    assert isinstance(ndarray_2d_list[0], aa.Grid2D)
-    assert ndarray_2d_list[0].native == pytest.approx(
-        np.array([[[0.0, 0.0], [0.0, -0.5], [0.0, 0.5], [0.0, 0.0]]]), abs=1.0e-4
-    )
-
-    assert isinstance(ndarray_2d_list[1], aa.Grid2D)
-    assert ndarray_2d_list[1].native == pytest.approx(
-        np.array([[[0.0, 0.0], [0.0, -1.0], [0.0, 1.0], [0.0, 0.0]]]), abs=1.0e-4
-    )
-
-
 def test__in_grid_2d__out_ndarray_2d():
     mask = aa.Mask2D(
         mask=[