remove interpolated reconstruction plot and some unit tests

Author: Jammy2211

autoarray/inversion/mock/mock_mapper.py

@@ -20,7 +20,6 @@ def __init__(
         mapping_matrix=None,
         pixel_signals=None,
         parameters=None,
-        interpolated_array=None,
     ):
         mapper_grids = MapperGrids(
             mask=mask,
@@ -41,7 +40,6 @@ def __init__(
         self._mapping_matrix = mapping_matrix
         self._parameters = parameters
         self._pixel_signals = pixel_signals
-        self._interpolated_array = interpolated_array
 
     def pixel_signals_from(self, signal_scale, xp=np):
         if self._pixel_signals is None:
@@ -71,11 +69,3 @@ def pix_sub_weights_split_points(self):
     @property
     def mapping_matrix(self):
         return self._mapping_matrix
-
-    def interpolated_array_from(
-        self,
-        values: np.ndarray,
-        shape_native: Tuple[int, int] = (401, 401),
-        extent: Optional[Tuple[float, float, float, float]] = None,
-    ):
-        return self._interpolated_array

autoarray/plot/__init__.py

@@ -28,9 +28,6 @@
 from autoarray.plot.wrap.two_d.grid_errorbar import GridErrorbar
 from autoarray.plot.wrap.two_d.vector_yx_quiver import VectorYXQuiver
 from autoarray.plot.wrap.two_d.patch_overlay import PatchOverlay
-from autoarray.plot.wrap.two_d.interpolated_reconstruction import (
-    InterpolatedReconstruction,
-)
 from autoarray.plot.wrap.two_d.delaunay_drawer import DelaunayDrawer
 from autoarray.plot.wrap.two_d.origin_scatter import OriginScatter
 from autoarray.plot.wrap.two_d.mask_scatter import MaskScatter

autoarray/plot/mat_plot/two_d.py

@@ -49,7 +49,6 @@ def __init__(
         grid_errorbar: Optional[w2d.GridErrorbar] = None,
         vector_yx_quiver: Optional[w2d.VectorYXQuiver] = None,
         patch_overlay: Optional[w2d.PatchOverlay] = None,
-        interpolated_reconstruction: Optional[w2d.InterpolatedReconstruction] = None,
         delaunay_drawer: Optional[w2d.DelaunayDrawer] = None,
         origin_scatter: Optional[w2d.OriginScatter] = None,
         mask_scatter: Optional[w2d.MaskScatter] = None,
@@ -135,8 +134,6 @@ def __init__(
             Overlays matplotlib `patches.Patch` objects over the figure, such as an `Ellipse`.
         delaunay_drawer
             Draws a colored Delaunay mesh of pixels using `plt.tripcolor`.
-        interpolated_reconstruction
-            Draws a colored Delaunay mesh of pixels using `plt.fill`.
         origin_scatter
             Scatters the (y,x) origin of the data structure on the figure.
         mask_scatter
@@ -190,10 +187,6 @@ def __init__(
         self.vector_yx_quiver = vector_yx_quiver or w2d.VectorYXQuiver(is_default=True)
         self.patch_overlay = patch_overlay or w2d.PatchOverlay(is_default=True)
 
-        self.interpolated_reconstruction = (
-            interpolated_reconstruction
-            or w2d.InterpolatedReconstruction(is_default=True)
-        )
         self.delaunay_drawer = delaunay_drawer or w2d.DelaunayDrawer(is_default=True)
 
         self.origin_scatter = origin_scatter or w2d.OriginScatter(is_default=True)
@@ -694,36 +687,19 @@ def _plot_delaunay_mapper(
 
         interpolation_array = None
 
-        if interpolate_to_uniform:
-            interpolation_array = (
-                self.interpolated_reconstruction.imshow_reconstruction(
-                    mapper=mapper,
-                    pixel_values=pixel_values,
-                    units=self.units,
-                    cmap=self.cmap,
-                    colorbar=self.colorbar,
-                    colorbar_tickparams=self.colorbar_tickparams,
-                    aspect=aspect_inv,
-                    ax=ax,
-                    use_log10=self.use_log10,
-                )
-            )
-
-        else:
-
-            if hasattr(pixel_values, "array"):
-                pixel_values = pixel_values.array
+        if hasattr(pixel_values, "array"):
+            pixel_values = pixel_values.array
 
-            self.delaunay_drawer.draw_delaunay_pixels(
-                mapper=mapper,
-                pixel_values=pixel_values,
-                units=self.units,
-                cmap=self.cmap,
-                colorbar=self.colorbar,
-                colorbar_tickparams=self.colorbar_tickparams,
-                ax=ax,
-                use_log10=self.use_log10,
-            )
+        self.delaunay_drawer.draw_delaunay_pixels(
+            mapper=mapper,
+            pixel_values=pixel_values,
+            units=self.units,
+            cmap=self.cmap,
+            colorbar=self.colorbar,
+            colorbar_tickparams=self.colorbar_tickparams,
+            ax=ax,
+            use_log10=self.use_log10,
+        )
 
         self.title.set(auto_title=auto_labels.title)
         self.ylabel.set()

autoarray/plot/wrap/__init__.py

@@ -25,9 +25,6 @@
 from autoarray.plot.wrap.two_d.grid_errorbar import GridErrorbar
 from autoarray.plot.wrap.two_d.vector_yx_quiver import VectorYXQuiver
 from autoarray.plot.wrap.two_d.patch_overlay import PatchOverlay
-from autoarray.plot.wrap.two_d.interpolated_reconstruction import (
-    InterpolatedReconstruction,
-)
 from autoarray.plot.wrap.two_d.origin_scatter import OriginScatter
 from autoarray.plot.wrap.two_d.mask_scatter import MaskScatter
 from autoarray.plot.wrap.two_d.border_scatter import BorderScatter

autoarray/plot/wrap/two_d/__init__.py

@@ -6,9 +6,6 @@
 from .grid_errorbar import GridErrorbar
 from .vector_yx_quiver import VectorYXQuiver
 from .patch_overlay import PatchOverlay
-from .interpolated_reconstruction import (
-    InterpolatedReconstruction,
-)
 from .delaunay_drawer import DelaunayDrawer
 from .origin_scatter import OriginScatter
 from .mask_scatter import MaskScatter

autoarray/plot/wrap/two_d/interpolated_reconstruction.py

@@ -54,36 +54,8 @@ def test__max_pixel_list_from__filter_neighbors():
     ]
 
 
-def test__interpolated_array_from():
-    values = np.array([0.0, 1.0, 1.0, 1.0])
 
-    mapper = aa.m.MockMapper(parameters=4, interpolated_array=values)
 
-    mapper_valued = aa.MapperValued(values=values, mapper=mapper)
-
-    values = mapper_valued.interpolated_array_from(
-        shape_native=(3, 3), extent=(-0.2, 0.2, -0.3, 0.3)
-    )
-
-    assert (values == np.array([0.0, 1.0, 1.0, 1.0])).all()
-
-
-def test__interpolated_array_from__with_pixel_mask():
-    values = np.array([0.0, 1.0, 1.0, 1.0])
-
-    mapper = aa.m.MockMapper(parameters=4, interpolated_array=values)
-
-    mesh_pixel_mask = np.array([True, False, False, True])
-
-    mapper_valued = aa.MapperValued(
-        values=values, mapper=mapper, mesh_pixel_mask=mesh_pixel_mask
-    )
-
-    values = mapper_valued.interpolated_array_from(
-        shape_native=(3, 3), extent=(-0.2, 0.2, -0.3, 0.3)
-    )
-
-    assert values == pytest.approx(np.array([0.0, 1.0, 1.0, 1.0]), 1.0e-4)
 
 
 def test__magnification_via_mesh_from():

test_autoarray/inversion/inversion/test_mapper_valued.py

@@ -133,38 +133,6 @@ def test__adaptive_pixel_signals_from___matches_util(grid_2d_7x7, image_7x7):
     assert (pixel_signals == pixel_signals_util).all()
 
 
-def test__interpolated_array_from(grid_2d_7x7):
-    mesh_grid_ndarray = aa.Grid2D.no_mask(
-        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,
-    )
-
-    mesh_grid = aa.Mesh2DDelaunay(values=mesh_grid_ndarray)
-
-    mapper_grids = aa.MapperGrids(
-        mask=grid_2d_7x7.mask,
-        source_plane_data_grid=grid_2d_7x7,
-        source_plane_mesh_grid=mesh_grid,
-    )
-
-    mapper = aa.Mapper(mapper_grids=mapper_grids, regularization=None)
-
-    interpolated_array_via_mapper = mapper.interpolated_array_from(
-        values=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]),
-        shape_native=(3, 3),
-        extent=(-0.2, 0.2, -0.2, 0.2),
-    )
-
-    interpolated_array_via_grid = mesh_grid.interpolated_array_from(
-        values=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]),
-        shape_native=(3, 3),
-        extent=(-0.2, 0.2, -0.2, 0.2),
-    )
-
-    assert (interpolated_array_via_mapper == interpolated_array_via_grid).all()
-
-
 def test__mapped_to_source_from(grid_2d_7x7):
     mesh_grid = aa.Grid2D.no_mask(
         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]],

test_autoarray/inversion/pixelization/mappers/test_abstract.py

@@ -104,30 +104,3 @@ def test__rectangular_neighbors_from():
     assert (
         neighbors_sizes == np.array([2, 3, 3, 2, 3, 4, 4, 3, 3, 4, 4, 3, 2, 3, 3, 2])
     ).all()
-
-
-def test__delaunay_interpolated_grid_from():
-    shape_native = (3, 3)
-
-    grid_interpolate_slim = aa.Grid2D.uniform(
-        shape_native=shape_native, pixel_scales=1.0
-    ).slim
-
-    delaunay_grid = np.array(
-        [[1.0, -1.0], [1.0, 1.0], [0.0, 0.0], [-1.0, -1.0], [-1.0, 1.0]]
-    )
-
-    delaunay = scipy.spatial.Delaunay(delaunay_grid)
-
-    values = np.array([1.0, 2.0, 3.0, 4.0, 5.0])
-
-    interpolated_grid = aa.util.mesh_numba.delaunay_interpolated_array_from(
-        shape_native=shape_native,
-        interpolation_grid_slim=grid_interpolate_slim,
-        pixel_values=values,
-        delaunay=delaunay,
-    )
-
-    assert interpolated_grid == pytest.approx(
-        np.array([[1.0, 1.5, 2.0], [2.5, 3.0, 3.5], [4.0, 4.5, 5.0]]), 1.0e-4
-    )

test_autoarray/inversion/pixelization/mesh/test_mesh_util.py

@@ -3,43 +3,6 @@
 
 import autoarray as aa
 
-
-def test__interpolated_array_from():
-    grid = aa.Grid2D.no_mask(
-        values=[[0.0, 0.0], [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,
-    )
-
-    mesh = aa.Mesh2DDelaunay(values=grid)
-
-    interpolated_array = mesh.interpolated_array_from(
-        values=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]), shape_native=(3, 2)
-    )
-
-    assert interpolated_array.native == pytest.approx(
-        np.array([[3.0, 5.0], [2.0, 5.0], [1.0, 5.0]]), 1.0e-4
-    )
-
-    interpolated_array = mesh.interpolated_array_from(
-        values=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]), shape_native=(2, 3)
-    )
-
-    assert interpolated_array.native == pytest.approx(
-        np.array([[3.0, 6.0, 5.0], [1.0, 4.0, 5.0]]), 1.0e-4
-    )
-
-    interpolated_array = mesh.interpolated_array_from(
-        values=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0]),
-        shape_native=(3, 2),
-        extent=(-0.4, 0.4, -0.4, 0.4),
-    )
-
-    assert interpolated_array.native == pytest.approx(
-        np.array([[1.0, 1.907216], [1.0, 1.0], [1.0, 1.0]]), 1.0e-4
-    )
-
-
 def test__neighbors(grid_2d_sub_1_7x7):
 
     mesh_grid = aa.Grid2D.no_mask(