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Jammy2211Jammy2211
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interpolate works but now need to remove convolver
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3 files changed

+5
-12
lines changed

3 files changed

+5
-12
lines changed

autoarray/inversion/pixelization/mappers/mapper_util.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -146,9 +146,9 @@ def data_slim_to_pixelization_unique_from(
146146

147147

148148
def rectangular_mappings_weights_via_interpolation_from(
149-
shape_native : Tuple[int, int],
150-
source_plane_data_grid: jnp.ndarray,
151-
source_plane_mesh_grid: jnp.ndarray
149+
shape_native: Tuple[int, int],
150+
source_plane_data_grid: jnp.ndarray,
151+
source_plane_mesh_grid: jnp.ndarray,
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):
153153
"""
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Compute bilinear interpolation weights and corresponding rectangular mesh indices for an irregular grid.

test_autoarray/inversion/inversion/test_factory.py

Lines changed: 2 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -487,14 +487,8 @@ def test__inversion_matrices__x2_mappers(
487487
settings=aa.SettingsInversion(use_positive_only_solver=True),
488488
)
489489

490-
assert (
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inversion.operated_mapping_matrix[0:9, 0:9]
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== rectangular_mapper_7x7_3x3.mapping_matrix
493-
).all()
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assert (
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inversion.operated_mapping_matrix[0:9, 9:18]
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== delaunay_mapper_9_3x3.mapping_matrix
497-
).all()
490+
assert inversion.operated_mapping_matrix[0:9, 0:9] == pytest.approx(rectangular_mapper_7x7_3x3.mapping_matrix, abs=1.0e-4)
491+
assert inversion.operated_mapping_matrix[0:9, 9:18] == pytest.approx(delaunay_mapper_9_3x3.mapping_matrix, abs=1.0e-4)
498492

499493
operated_mapping_matrix = np.hstack(
500494
[

test_autoarray/inversion/pixelization/mappers/test_factory.py

Lines changed: 0 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -42,7 +42,6 @@ def test__rectangular_mapper():
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(5.0, 5.0), 1.0e-4
4343
)
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assert mapper.source_plane_mesh_grid.origin == pytest.approx((0.5, 0.5), 1.0e-4)
45-
print(mapper.mapping_matrix)
4645
assert mapper.mapping_matrix == pytest.approx(
4746
np.array(
4847
[

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