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Jammy2211Jammy2211
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remove anti annular
1 parent ed60fda commit 1460984

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‎autoarray/mask/mask_2d.py‎

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Original file line numberDiff line numberDiff line change
@@ -380,65 +380,6 @@ def circular_annular(
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invert=invert,
381381
)
382382

383-
@classmethod
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def circular_anti_annular(
385-
cls,
386-
shape_native: Tuple[int, int],
387-
inner_radius: float,
388-
outer_radius: float,
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outer_radius_2: float,
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pixel_scales: ty.PixelScales,
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origin: Tuple[float, float] = (0.0, 0.0),
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centre: Tuple[float, float] = (0.0, 0.0),
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invert: bool = False,
394-
) -> "Mask2D":
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"""
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Returns a Mask2D (see *Mask2D.__new__*) where all `False` entries are within an inner circle and second
397-
outer circle, forming an inverse annulus.
398-
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The `inner_radius`, `outer_radius`, `outer_radius_2` and `centre` are all input in scaled units.
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Parameters
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----------
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shape_native
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The (y,x) shape of the mask in units of pixels.
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inner_radius
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The inner radius in scaled units of the annulus within which pixels are `False` and unmasked.
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outer_radius
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The first outer radius in scaled units of the annulus within which pixels are `True` and masked.
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outer_radius_2
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The second outer radius in scaled units of the annulus within which pixels are `False` and unmasked and
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outside of which all entries are `True` and masked.
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pixel_scales
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The (y,x) scaled units to pixel units conversion factors of every pixel. If this is input as a `float`,
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it is converted to a (float, float) structure.
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origin
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The (y,x) scaled units origin of the mask's coordinate system.
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centre
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The (y,x) scaled units centre of the anti-annulus used to mask pixels.
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invert
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If `True`, the `bool`'s of the input `mask` are inverted, for example `False`'s become `True`
421-
and visa versa.
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"""
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pixel_scales = geometry_util.convert_pixel_scales_2d(pixel_scales=pixel_scales)
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mask = mask_2d_util.mask_2d_circular_anti_annular_from(
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shape_native=shape_native,
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pixel_scales=pixel_scales,
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inner_radius=inner_radius,
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outer_radius=outer_radius,
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outer_radius_2_scaled=outer_radius_2,
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centre=centre,
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)
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return cls(
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mask=mask,
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pixel_scales=pixel_scales,
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origin=origin,
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invert=invert,
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)
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442383
@classmethod
443384
def elliptical(
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cls,

‎autoarray/mask/mask_2d_util.py‎

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Original file line numberDiff line numberDiff line change
@@ -128,71 +128,6 @@ def mask_2d_circular_annular_from(
128128
return ~((distances_squared >= inner_radius**2) & (distances_squared <= outer_radius**2))
129129

130130

131-
@numba_util.jit()
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def mask_2d_circular_anti_annular_from(
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shape_native: Tuple[int, int],
134-
pixel_scales: ty.PixelScales,
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inner_radius: float,
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outer_radius: float,
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outer_radius_2_scaled: float,
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centre: Tuple[float, float] = (0.0, 0.0),
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) -> np.ndarray:
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"""
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Returns an anti-annular mask from an input inner and outer mask radius and shape. The anti-annular is analogous to
142-
the annular mask but inverted, whereby its unmasked values are those inside the annulus.
143-
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This creates a 2D array where all values outside the inner and outer radii are unmasked and therefore `False`.
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Parameters
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----------
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shape_native
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The (y,x) shape of the mask in units of pixels.
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pixel_scales
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The scaled units to pixel units conversion factor of each pixel.
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inner_radius
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The inner radius in scaled units of the annulus within which pixels are `False` and unmasked.
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outer_radius
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The first outer radius in scaled units of the annulus within which pixels are `True` and masked.
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outer_radius_2
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The second outer radius in scaled units of the annulus within which pixels are `False` and unmasked and
158-
outside of which all entries are `True` and masked.
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centre
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The centre of the annulus used to mask pixels.
161-
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Returns
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-------
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ndarray
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The 2D mask array whose central pixels are masked as a annulus.
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Examples
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--------
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mask = mask_annnular_from(
170-
shape=(10, 10), pixel_scales=0.1, inner_radius=0.5, outer_radius=1.5, centre=(0.0, 0.0))
171-
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"""
173-
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mask_2d = np.full(shape_native, True)
175-
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centres_scaled = mask_2d_centres_from(
177-
shape_native=mask_2d.shape, pixel_scales=pixel_scales, centre=centre
178-
)
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for y in range(mask_2d.shape[0]):
181-
for x in range(mask_2d.shape[1]):
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y_scaled = (y - centres_scaled[0]) * pixel_scales[0]
183-
x_scaled = (x - centres_scaled[1]) * pixel_scales[1]
184-
185-
r_scaled = np.sqrt(x_scaled**2 + y_scaled**2)
186-
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if (
188-
inner_radius >= r_scaled
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or outer_radius_2_scaled >= r_scaled >= outer_radius
190-
):
191-
mask_2d[y, x] = False
192-
193-
return mask_2d
194-
195-
196131
def mask_2d_via_pixel_coordinates_from(
197132
shape_native: Tuple[int, int], pixel_coordinates: [list], buffer: int = 0
198133
) -> np.ndarray:

‎test_autoarray/mask/test_mask_2d.py‎

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Original file line numberDiff line numberDiff line change
@@ -141,45 +141,6 @@ def test__circular_annular():
141141
assert mask.origin == (0.0, 0.0)
142142
assert mask.mask_centre == (0.0, 0.0)
143143

144-
145-
def test__circular_anti_annular():
146-
mask_via_util = aa.util.mask_2d.mask_2d_circular_anti_annular_from(
147-
shape_native=(9, 9),
148-
pixel_scales=(1.2, 1.2),
149-
inner_radius=0.8,
150-
outer_radius=2.2,
151-
outer_radius_2_scaled=3.0,
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centre=(0.0, 0.0),
153-
)
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mask = aa.Mask2D.circular_anti_annular(
156-
shape_native=(9, 9),
157-
pixel_scales=(1.2, 1.2),
158-
inner_radius=0.8,
159-
outer_radius=2.2,
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outer_radius_2=3.0,
161-
centre=(0.0, 0.0),
162-
)
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164-
assert (mask == mask_via_util).all()
165-
assert mask.origin == (0.0, 0.0)
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assert mask.mask_centre == (0.0, 0.0)
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168-
mask = aa.Mask2D.circular_anti_annular(
169-
shape_native=(9, 9),
170-
pixel_scales=(1.2, 1.2),
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inner_radius=0.8,
172-
outer_radius=2.2,
173-
outer_radius_2=3.0,
174-
centre=(0.0, 0.0),
175-
invert=True,
176-
)
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178-
assert (mask == np.invert(mask_via_util)).all()
179-
assert mask.origin == (0.0, 0.0)
180-
assert mask.mask_centre == (0.0, 0.0)
181-
182-
183144
def test__elliptical():
184145
mask_via_util = aa.util.mask_2d.mask_2d_elliptical_from(
185146
shape_native=(8, 5),

‎test_autoarray/mask/test_mask_2d_util.py‎

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Original file line numberDiff line numberDiff line change
@@ -234,97 +234,6 @@ def test__mask_2d_circular_annular_from__input_centre():
234234
).all()
235235

236236

237-
def test__mask_2d_circular_anti_annular_from():
238-
mask = util.mask_2d.mask_2d_circular_anti_annular_from(
239-
shape_native=(5, 5),
240-
pixel_scales=(1.0, 1.0),
241-
inner_radius=0.5,
242-
outer_radius=10.0,
243-
outer_radius_2_scaled=20.0,
244-
)
245-
246-
assert (
247-
mask
248-
== np.array(
249-
[
250-
[True, True, True, True, True],
251-
[True, True, True, True, True],
252-
[True, True, False, True, True],
253-
[True, True, True, True, True],
254-
[True, True, True, True, True],
255-
]
256-
)
257-
).all()
258-
259-
mask = util.mask_2d.mask_2d_circular_anti_annular_from(
260-
shape_native=(5, 5),
261-
pixel_scales=(0.1, 1.0),
262-
inner_radius=1.5,
263-
outer_radius=10.0,
264-
outer_radius_2_scaled=20.0,
265-
)
266-
267-
assert (
268-
mask
269-
== np.array(
270-
[
271-
[True, False, False, False, True],
272-
[True, False, False, False, True],
273-
[True, False, False, False, True],
274-
[True, False, False, False, True],
275-
[True, False, False, False, True],
276-
]
277-
)
278-
).all()
279-
280-
mask = util.mask_2d.mask_2d_circular_anti_annular_from(
281-
shape_native=(5, 5),
282-
pixel_scales=(1.0, 1.0),
283-
inner_radius=0.5,
284-
outer_radius=1.5,
285-
outer_radius_2_scaled=20.0,
286-
)
287-
288-
assert (
289-
mask
290-
== np.array(
291-
[
292-
[False, False, False, False, False],
293-
[False, True, True, True, False],
294-
[False, True, False, True, False],
295-
[False, True, True, True, False],
296-
[False, False, False, False, False],
297-
]
298-
)
299-
).all()
300-
301-
302-
def test__mask_2d_circular_anti_annular_from__include_centre():
303-
mask = util.mask_2d.mask_2d_circular_anti_annular_from(
304-
shape_native=(7, 7),
305-
pixel_scales=(3.0, 3.0),
306-
inner_radius=1.5,
307-
outer_radius=4.5,
308-
outer_radius_2_scaled=8.7,
309-
centre=(-3.0, 3.0),
310-
)
311-
312-
assert (
313-
mask
314-
== np.array(
315-
[
316-
[True, True, True, True, True, True, True],
317-
[True, True, True, True, True, True, True],
318-
[True, True, False, False, False, False, False],
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[True, True, False, True, True, True, False],
320-
[True, True, False, True, False, True, False],
321-
[True, True, False, True, True, True, False],
322-
[True, True, False, False, False, False, False],
323-
]
324-
)
325-
).all()
326-
327-
328237
def test__mask_2d_elliptical_from():
329238
mask = util.mask_2d.mask_2d_elliptical_from(
330239
shape_native=(3, 3),

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