diff --git a/autoarray/dataset/grids.py b/autoarray/dataset/grids.py index 9b66d302..95231b70 100644 --- a/autoarray/dataset/grids.py +++ b/autoarray/dataset/grids.py @@ -66,7 +66,7 @@ def lp(self) -> Union[Grid1D, Grid2D]: """ return Grid2D.from_mask( mask=self.mask, - over_sampling_size=self.over_sampling.lp, + over_sample_size=self.over_sampling.lp, ) @cached_property @@ -87,7 +87,7 @@ def pixelization(self) -> Grid2D: """ return Grid2D.from_mask( mask=self.mask, - over_sampling_size=self.over_sampling.pixelization, + over_sample_size=self.over_sampling.pixelization, ) @cached_property @@ -117,7 +117,7 @@ def blurring(self) -> Optional[Grid2D]: @cached_property def border_relocator(self) -> BorderRelocator: return BorderRelocator( - mask=self.mask, sub_size=self.pixelization.over_sampling_size + mask=self.mask, sub_size=self.pixelization.over_sample_size ) diff --git a/autoarray/dataset/over_sampling.py b/autoarray/dataset/over_sampling.py index 10c3187a..b50481b8 100644 --- a/autoarray/dataset/over_sampling.py +++ b/autoarray/dataset/over_sampling.py @@ -29,7 +29,7 @@ def __init__( This class controls how over sampling is performed for 3 different types of grids: - `grid`: A grids of (y,x) coordinates which aligns with the centre of every image pixel of the image data. + - `grid`: A grids of (y,x) coordinates which aligns with the centre of every image pixel of the image data. - `grids.pixelization`: A grid of (y,x) coordinates which again align with the centre of every image pixel of the image data. This grid is used specifically for pixelizations computed via the `inversion` module, which diff --git a/autoarray/dataset/plot/imaging_plotters.py b/autoarray/dataset/plot/imaging_plotters.py index a10a2cfc..3f8bac92 100644 --- a/autoarray/dataset/plot/imaging_plotters.py +++ b/autoarray/dataset/plot/imaging_plotters.py @@ -126,7 +126,7 @@ def figures_2d( if over_sampling: self.mat_plot_2d.plot_array( - array=self.dataset.grids.lp.over_sampling_size, + array=self.dataset.grids.lp.over_sample_size, visuals_2d=self.get_visuals_2d(), auto_labels=AutoLabels( title=title_str or f"Over Sampling (Uniform)", @@ -137,7 +137,7 @@ def figures_2d( if over_sampling_pixelization: self.mat_plot_2d.plot_array( - array=self.dataset.grids.pixelization.over_sampling_size, + array=self.dataset.grids.pixelization.over_sample_size, visuals_2d=self.get_visuals_2d(), auto_labels=AutoLabels( title=title_str or f"Over Sampling (Pixelization)", diff --git a/autoarray/fixtures.py b/autoarray/fixtures.py index ff684ec4..73d150d4 100644 --- a/autoarray/fixtures.py +++ b/autoarray/fixtures.py @@ -90,11 +90,11 @@ def make_grid_2d_7x7(): def make_grid_2d_sub_1_7x7(): - return aa.Grid2D.from_mask(mask=make_mask_2d_7x7(), over_sampling_size=1) + return aa.Grid2D.from_mask(mask=make_mask_2d_7x7(), over_sample_size=1) def make_grid_2d_sub_2_7x7(): - return aa.Grid2D.from_mask(mask=make_mask_2d_7x7(), over_sampling_size=2) + return aa.Grid2D.from_mask(mask=make_mask_2d_7x7(), over_sample_size=2) def make_grid_2d_7x7_simple(): diff --git a/autoarray/inversion/linear_obj/func_list.py b/autoarray/inversion/linear_obj/func_list.py index 9ec30e9b..ce72bdcb 100644 --- a/autoarray/inversion/linear_obj/func_list.py +++ b/autoarray/inversion/linear_obj/func_list.py @@ -96,7 +96,7 @@ def unique_mappings(self) -> UniqueMappings: For a `LinearObjFuncList` every data pixel's group of sub-pixels maps directly to the linear function. """ - sub_size = np.max(self.grid.over_sampling_size) + sub_size = np.max(self.grid.over_sample_size) # TODO : This shape slim is prob unreliable and needs to be divided by sub_size**2 diff --git a/autoarray/inversion/pixelization/border_relocator.py b/autoarray/inversion/pixelization/border_relocator.py index 6870f9a3..28f7a3ff 100644 --- a/autoarray/inversion/pixelization/border_relocator.py +++ b/autoarray/inversion/pixelization/border_relocator.py @@ -284,7 +284,7 @@ def relocated_grid_from(self, grid: Grid2D) -> Grid2D: return Grid2D( values=values, mask=grid.mask, - over_sampling_size=self.sub_size, + over_sample_size=self.sub_size, over_sampled=over_sampled, ) diff --git a/autoarray/structures/decorators/abstract.py b/autoarray/structures/decorators/abstract.py index 2d6e7f23..5c61c643 100644 --- a/autoarray/structures/decorators/abstract.py +++ b/autoarray/structures/decorators/abstract.py @@ -60,8 +60,8 @@ def mask(self) -> Union[Mask1D, Mask2D]: return self.grid.mask @property - def over_sampling_size(self) -> np.ndarray: - return self.grid.over_sampling_size + def over_sample_size(self) -> np.ndarray: + return self.grid.over_sample_size def via_grid_2d(self, result): raise NotImplementedError diff --git a/autoarray/structures/decorators/to_grid.py b/autoarray/structures/decorators/to_grid.py index 62d7b870..57b13602 100644 --- a/autoarray/structures/decorators/to_grid.py +++ b/autoarray/structures/decorators/to_grid.py @@ -30,7 +30,7 @@ def via_grid_2d(self, result) -> Union[Grid2D, List[Grid2D]]: return Grid2D( values=result, mask=self.mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, over_sampled=over_sampled, ) @@ -43,7 +43,7 @@ def via_grid_2d(self, result) -> Union[Grid2D, List[Grid2D]]: Grid2D( values=res, mask=self.mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, over_sampled=over_sampled, ) for res, over_sampled in zip(result, grid_over_sampled_list) diff --git a/autoarray/structures/grids/uniform_2d.py b/autoarray/structures/grids/uniform_2d.py index 523a9645..226e98e3 100644 --- a/autoarray/structures/grids/uniform_2d.py +++ b/autoarray/structures/grids/uniform_2d.py @@ -26,7 +26,7 @@ def __init__( values: Union[np.ndarray, List], mask: Mask2D, store_native: bool = False, - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, over_sampled: Optional[Grid2D] = None, *args, **kwargs, @@ -149,7 +149,7 @@ def __init__( store_native If True, the ndarray is stored in its native format [total_y_pixels, total_x_pixels, 2]. This avoids mapping large data arrays to and from the slim / native formats, which can be a computational bottleneck. - over_sampling_size + over_sample_size The over sampling scheme, which divides the grid into a sub grid of smaller pixels when computing values (e.g. images) from the grid so as to approximate the 2D line integral of the amount of light that falls into each pixel. @@ -166,16 +166,16 @@ def __init__( grid_2d_util.check_grid_2d(grid_2d=values) - if isinstance(over_sampling_size, int): - over_sampling_size = np.full( - fill_value=over_sampling_size, shape=mask.shape_slim + if isinstance(over_sample_size, int): + over_sample_size = np.full( + fill_value=over_sample_size, shape=mask.shape_slim ).astype("int") - over_sampling_size = Array2D(values=over_sampling_size, mask=mask) + over_sample_size = Array2D(values=over_sample_size, mask=mask) from autoarray.operators.over_sampling.over_sampler import OverSampler - self.over_sampler = OverSampler(sub_size=over_sampling_size, mask=mask) + self.over_sampler = OverSampler(sub_size=over_sample_size, mask=mask) if over_sampled is None: self.over_sampled = ( @@ -197,7 +197,7 @@ def no_mask( pixel_scales: ty.PixelScales, shape_native: Tuple[int, int] = None, origin: Tuple[float, float] = (0.0, 0.0), - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) by inputting the grid coordinates in 1D or 2D, automatically @@ -244,7 +244,7 @@ def no_mask( return Grid2D( values=values, mask=mask, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -255,7 +255,7 @@ def from_yx_1d( shape_native: Tuple[int, int], pixel_scales: ty.PixelScales, origin: Tuple[float, float] = (0.0, 0.0), - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) by inputting the grid coordinates as 1D y and x values. @@ -319,7 +319,7 @@ def from_yx_1d( shape_native=shape_native, pixel_scales=pixel_scales, origin=origin, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -329,7 +329,7 @@ def from_yx_2d( x: Union[np.ndarray, List], pixel_scales: ty.PixelScales, origin: Tuple[float, float] = (0.0, 0.0), - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) by inputting the grid coordinates as 2D y and x values. @@ -374,7 +374,7 @@ def from_yx_2d( values=np.stack((y, x), axis=-1), pixel_scales=pixel_scales, origin=origin, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -382,7 +382,7 @@ def from_extent( cls, extent: Tuple[float, float, float, float], shape_native: Tuple[int, int], - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) by inputting the extent of the (y,x) grid coordinates as an input @@ -431,7 +431,7 @@ def from_extent( return Grid2D.no_mask( values=grid_2d, pixel_scales=pixel_scales, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -440,7 +440,7 @@ def uniform( shape_native: Tuple[int, int], pixel_scales: ty.PixelScales, origin: Tuple[float, float] = (0.0, 0.0), - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a `Grid2D` (see *Grid2D.__new__*) as a uniform grid of (y,x) values given an input `shape_native` and @@ -469,7 +469,7 @@ def uniform( shape_native=shape_native, pixel_scales=pixel_scales, origin=origin, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -478,7 +478,7 @@ def bounding_box( bounding_box: np.ndarray, shape_native: Tuple[int, int], buffer_around_corners: bool = False, - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) from an input bounding box with coordinates [y_min, y_max, x_min, x_max], @@ -521,14 +521,14 @@ def bounding_box( shape_native=shape_native, pixel_scales=pixel_scales, origin=origin, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod def from_mask( cls, mask: Mask2D, - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) from a mask, where only unmasked pixels are included in the grid (if the @@ -551,7 +551,7 @@ def from_mask( return Grid2D( values=grid_1d, mask=mask, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -560,7 +560,7 @@ def from_fits( file_path: Union[Path, str], pixel_scales: ty.PixelScales, origin: Tuple[float, float] = (0.0, 0.0), - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Create a Grid2D (see *Grid2D.__new__*) from a mask, where only unmasked pixels are included in the grid (if the @@ -580,7 +580,7 @@ def from_fits( values=grid_2d, pixel_scales=pixel_scales, origin=origin, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) @classmethod @@ -588,7 +588,7 @@ def blurring_grid_from( cls, mask: Mask2D, kernel_shape_native: Tuple[int, int], - over_sampling_size: Union[int, Array2D] = 4, + over_sample_size: Union[int, Array2D] = 4, ) -> "Grid2D": """ Setup a blurring-grid from a mask, where a blurring grid consists of all pixels that are masked (and @@ -676,7 +676,7 @@ def blurring_grid_from( return cls.from_mask( mask=blurring_mask, - over_sampling_size=over_sampling_size, + over_sample_size=over_sample_size, ) def subtracted_from(self, offset: Tuple[(float, float), np.ndarray]) -> "Grid2D": @@ -692,11 +692,11 @@ def subtracted_from(self, offset: Tuple[(float, float), np.ndarray]) -> "Grid2D" return Grid2D( values=self - np.array(offset), mask=mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, ) @property - def over_sampling_size(self): + def over_sample_size(self): return self.over_sampler.sub_size @property @@ -711,7 +711,7 @@ def slim(self) -> "Grid2D": return Grid2D( values=self, mask=self.mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, ) @property @@ -728,7 +728,7 @@ def native(self) -> "Grid2D": return Grid2D( values=self, mask=self.mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, store_native=True, ) @@ -766,7 +766,7 @@ def grid_2d_via_deflection_grid_from(self, deflection_grid: "Grid2D") -> "Grid2D return Grid2D( values=self - deflection_grid, mask=self.mask, - over_sampling_size=self.over_sampling_size, + over_sample_size=self.over_sample_size, ) def blurring_grid_via_kernel_shape_from( @@ -786,7 +786,7 @@ def blurring_grid_via_kernel_shape_from( return Grid2D.blurring_grid_from( mask=self.mask, kernel_shape_native=kernel_shape_native, - over_sampling_size=1, + over_sample_size=1, ) def grid_with_coordinates_within_distance_removed_from( @@ -823,7 +823,7 @@ def grid_with_coordinates_within_distance_removed_from( return Grid2D.from_mask( mask=mask, - over_sampling_size=self.over_sampling_size.apply_mask(mask=mask), + over_sample_size=self.over_sample_size.apply_mask(mask=mask), ) def squared_distances_to_coordinate_from( @@ -1080,16 +1080,16 @@ def padded_grid_from(self, kernel_shape_native: Tuple[int, int]) -> "Grid2D": (padded_shape[1] - shape[1]) // 2, ) - over_sampling_size = np.pad( - self.over_sampling_size.native, + over_sample_size = np.pad( + self.over_sample_size.native, pad_width, mode="constant", constant_values=1, ) - over_sampling_size[over_sampling_size == 0] = 1 + over_sample_size[over_sample_size == 0] = 1 - return Grid2D.from_mask(mask=padded_mask, over_sampling_size=over_sampling_size) + return Grid2D.from_mask(mask=padded_mask, over_sample_size=over_sample_size) @cached_property def is_uniform(self) -> bool: diff --git a/test_autoarray/dataset/abstract/test_dataset.py b/test_autoarray/dataset/abstract/test_dataset.py index b72af8ab..a1dc7573 100644 --- a/test_autoarray/dataset/abstract/test_dataset.py +++ b/test_autoarray/dataset/abstract/test_dataset.py @@ -101,7 +101,7 @@ def test__grids_pixelization__uses_mask_and_settings( ) assert isinstance(masked_imaging_7x7.grids.pixelization, aa.Grid2D) - assert masked_imaging_7x7.grids.pixelization.over_sampling_size[0] == 4 + assert masked_imaging_7x7.grids.pixelization.over_sample_size[0] == 4 def test__grid_settings__sub_size(image_7x7, noise_map_7x7): @@ -114,8 +114,8 @@ def test__grid_settings__sub_size(image_7x7, noise_map_7x7): ), ) - assert dataset_7x7.grids.lp.over_sampling_size[0] == 2 - assert dataset_7x7.grids.pixelization.over_sampling_size[0] == 4 + assert dataset_7x7.grids.lp.over_sample_size[0] == 2 + assert dataset_7x7.grids.pixelization.over_sample_size[0] == 4 def test__new_imaging_with_arrays_trimmed_via_kernel_shape(): diff --git a/test_autoarray/inversion/inversion/imaging/test_inversion_imaging_util.py b/test_autoarray/inversion/inversion/imaging/test_inversion_imaging_util.py index 957c68c3..711135eb 100644 --- a/test_autoarray/inversion/inversion/imaging/test_inversion_imaging_util.py +++ b/test_autoarray/inversion/inversion/imaging/test_inversion_imaging_util.py @@ -188,7 +188,7 @@ def test__data_vector_via_w_tilde_data_two_methods_agree(): # TODO : Use pytest.parameterize for sub_size in range(1, 3): - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=sub_size) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=sub_size) mapper_grids = pixelization.mapper_grids_from( mask=mask, @@ -232,7 +232,7 @@ def test__data_vector_via_w_tilde_data_two_methods_agree(): pix_sizes_for_sub_slim_index=mapper.pix_sizes_for_sub_slim_index, pix_weights_for_sub_slim_index=mapper.pix_weights_for_sub_slim_index, pix_pixels=mapper.params, - sub_size=np.array(grid.over_sampling_size), + sub_size=np.array(grid.over_sample_size), ) data_vector_via_w_tilde = ( @@ -308,7 +308,7 @@ def test__curvature_matrix_via_w_tilde_preload_two_methods_agree(): pixelization = aa.mesh.Rectangular(shape=(20, 20)) for sub_size in range(1, 2, 3): - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=sub_size) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=sub_size) mapper_grids = pixelization.mapper_grids_from( mask=mask, @@ -343,7 +343,7 @@ def test__curvature_matrix_via_w_tilde_preload_two_methods_agree(): pix_sizes_for_sub_slim_index=mapper.pix_sizes_for_sub_slim_index, pix_weights_for_sub_slim_index=mapper.pix_weights_for_sub_slim_index, pix_pixels=mapper.params, - sub_size=np.array(grid.over_sampling_size), + sub_size=np.array(grid.over_sample_size), ) curvature_matrix_via_w_tilde = aa.util.inversion_imaging.curvature_matrix_via_w_tilde_curvature_preload_imaging_from( diff --git a/test_autoarray/inversion/inversion/test_abstract.py b/test_autoarray/inversion/inversion/test_abstract.py index 4bb153b7..735b3cda 100644 --- a/test_autoarray/inversion/inversion/test_abstract.py +++ b/test_autoarray/inversion/inversion/test_abstract.py @@ -114,7 +114,7 @@ def test__curvature_matrix__via_w_tilde__identical_to_mapping(): pixel_scales=2.0, ) - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=1) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=1) mesh_0 = aa.mesh.Rectangular(shape=(3, 3)) mesh_1 = aa.mesh.Rectangular(shape=(4, 4)) @@ -178,7 +178,7 @@ def test__curvature_matrix_via_w_tilde__includes_source_interpolation__identical pixel_scales=2.0, ) - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=1) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=1) mesh_0 = aa.mesh.Delaunay() mesh_1 = aa.mesh.Delaunay() diff --git a/test_autoarray/inversion/pixelization/mappers/test_abstract.py b/test_autoarray/inversion/pixelization/mappers/test_abstract.py index 8e154b21..7217dc79 100644 --- a/test_autoarray/inversion/pixelization/mappers/test_abstract.py +++ b/test_autoarray/inversion/pixelization/mappers/test_abstract.py @@ -202,7 +202,7 @@ def test__mapped_to_source_from(grid_2d_7x7): values=[[0.1, 0.1], [1.1, 0.6], [2.1, 0.1], [0.4, 1.1], [1.1, 7.1], [2.1, 1.1]], shape_native=(3, 2), pixel_scales=1.0, - over_sampling_size=1, + over_sample_size=1, ) mesh_grid = aa.Mesh2DDelaunay(values=mesh_grid) diff --git a/test_autoarray/inversion/pixelization/mappers/test_delaunay.py b/test_autoarray/inversion/pixelization/mappers/test_delaunay.py index dd8a654f..33b03fbb 100644 --- a/test_autoarray/inversion/pixelization/mappers/test_delaunay.py +++ b/test_autoarray/inversion/pixelization/mappers/test_delaunay.py @@ -7,7 +7,7 @@ def test__pix_indexes_for_sub_slim_index__matches_util(grid_2d_sub_1_7x7): values=[[0.1, 0.1], [1.1, 0.6], [2.1, 0.1], [0.4, 1.1], [1.1, 7.1], [2.1, 1.1]], shape_native=(3, 2), pixel_scales=1.0, - over_sampling_size=1, + over_sample_size=1, ) mesh_grid = aa.Mesh2DDelaunay(values=mesh_grid) diff --git a/test_autoarray/inversion/pixelization/mappers/test_factory.py b/test_autoarray/inversion/pixelization/mappers/test_factory.py index 83fc4940..c08bca93 100644 --- a/test_autoarray/inversion/pixelization/mappers/test_factory.py +++ b/test_autoarray/inversion/pixelization/mappers/test_factory.py @@ -20,7 +20,7 @@ def test__rectangular_mapper(): ) # Slightly manipulate input grid so sub gridding is evidence in first source pixel. - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=2) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=2) grid.over_sampled[0, 0] = -2.0 grid.over_sampled[0, 1] = 2.0 @@ -70,7 +70,7 @@ def test__delaunay_mapper(): ) # Slightly manipulate input grid so sub gridding is evidence in first source pixel. - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=2) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=2) grid.over_sampled[0, 0] = -2.0 grid.over_sampled[0, 1] = 2.0 @@ -126,7 +126,7 @@ def test__voronoi_mapper(): ) # Slightly manipulate input grid so sub gridding is evidence in first source pixel. - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=2) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=2) grid.over_sampled[0, 0] = -2.0 grid.over_sampled[0, 1] = 2.0 diff --git a/test_autoarray/inversion/pixelization/mappers/test_rectangular.py b/test_autoarray/inversion/pixelization/mappers/test_rectangular.py index aee46356..026e230d 100644 --- a/test_autoarray/inversion/pixelization/mappers/test_rectangular.py +++ b/test_autoarray/inversion/pixelization/mappers/test_rectangular.py @@ -18,7 +18,7 @@ def test__pix_indexes_for_sub_slim_index__matches_util(): ], pixel_scales=1.0, shape_native=(3, 3), - over_sampling_size=1, + over_sample_size=1, ) mesh_grid = aa.Mesh2DRectangular.overlay_grid( diff --git a/test_autoarray/inversion/pixelization/mappers/test_voronoi.py b/test_autoarray/inversion/pixelization/mappers/test_voronoi.py index 8b54842e..57e971aa 100644 --- a/test_autoarray/inversion/pixelization/mappers/test_voronoi.py +++ b/test_autoarray/inversion/pixelization/mappers/test_voronoi.py @@ -8,7 +8,7 @@ def test__pix_indexes_for_sub_slim_index__matches_util(grid_2d_sub_1_7x7): values=[[0.1, 0.1], [1.1, 0.6], [2.1, 0.1], [0.4, 1.1], [1.1, 7.1], [2.1, 1.1]], shape_native=(3, 2), pixel_scales=1.0, - over_sampling_size=1, + over_sample_size=1, ) source_plane_mesh_grid = aa.Mesh2DVoronoi( diff --git a/test_autoarray/inversion/pixelization/test_border_relocator.py b/test_autoarray/inversion/pixelization/test_border_relocator.py index 6eccee10..db190269 100644 --- a/test_autoarray/inversion/pixelization/test_border_relocator.py +++ b/test_autoarray/inversion/pixelization/test_border_relocator.py @@ -326,7 +326,7 @@ def test__relocated_grid_from__inside_border_no_relocations(): ) grid = aa.Grid2D.from_mask( - mask=mask, over_sampling_size=np.array(mask.pixels_in_mask * [2]) + mask=mask, over_sample_size=np.array(mask.pixels_in_mask * [2]) ) grid.over_sampled[1, :] = [0.1, 0.1] @@ -345,7 +345,7 @@ def test__relocated_grid_from__outside_border_includes_relocations(): ) grid = aa.Grid2D.from_mask( - mask=mask, over_sampling_size=np.array(mask.pixels_in_mask * [2]) + mask=mask, over_sample_size=np.array(mask.pixels_in_mask * [2]) ) grid.over_sampled[1, :] = [10.1, 0.1] @@ -368,10 +368,10 @@ def test__relocated_grid_from__positive_origin_included_in_relocate(): centre=(1.0, 1.0), ) - grid = aa.Grid2D.from_mask(mask=mask, over_sampling_size=2) + grid = aa.Grid2D.from_mask(mask=mask, over_sample_size=2) grid.over_sampled[1, :] = [11.1, 1.0] - border_relocator = aa.BorderRelocator(mask=mask, sub_size=grid.over_sampling_size) + border_relocator = aa.BorderRelocator(mask=mask, sub_size=grid.over_sample_size) relocated_grid = border_relocator.relocated_grid_from(grid=grid) diff --git a/test_autoarray/inversion/test_linear_obj.py b/test_autoarray/inversion/test_linear_obj.py index 1319742a..5267cd46 100644 --- a/test_autoarray/inversion/test_linear_obj.py +++ b/test_autoarray/inversion/test_linear_obj.py @@ -45,7 +45,7 @@ def test__data_to_pix_unique_from(): mask = aa.Mask2D.all_false(shape_native=(1, 2), pixel_scales=0.1) grid = aa.Grid2D.uniform( - shape_native=(1, 2), pixel_scales=0.1, over_sampling_size=2 + shape_native=(1, 2), pixel_scales=0.1, over_sample_size=2 ) linear_obj = aa.AbstractLinearObjFuncList(grid=grid, regularization=None) diff --git a/test_autoarray/operators/over_sample/test_decorator.py b/test_autoarray/operators/over_sample/test_decorator.py index c98de7db..47dae1e8 100644 --- a/test_autoarray/operators/over_sample/test_decorator.py +++ b/test_autoarray/operators/over_sample/test_decorator.py @@ -20,7 +20,7 @@ def test__in_grid_2d__over_sample_uniform__out_ndarray_1d(): pixel_scales=(1.0, 1.0), ) - grid_2d = aa.Grid2D.from_mask(mask=mask, over_sampling_size=2) + grid_2d = aa.Grid2D.from_mask(mask=mask, over_sample_size=2) obj = aa.m.MockGrid2DLikeObj()