Got test in phase passing, now going to make decorator for pixel scale conversion

Author: Jammy2211

autoarray/data/imaging.py

@@ -31,6 +31,10 @@ def pixel_scale(self):
     def shape(self):
         return self.image.shape_2d
 
+    @property
+    def shape_2d(self):
+        return self.image.shape_2d
+
     def binned_from_bin_up_factor(self, bin_up_factor):
 
         image = self.image.binned_from_bin_up_factor(

autoarray/mask/mask.py

@@ -91,6 +91,11 @@ def circular(cls, shape_2d, radius_arcsec, pixel_scales, sub_size=1, origin=(0.0
         centre: (float, float)
             The centre of the circle used to mask pixels.
         """
+
+        if type(pixel_scales) is not tuple:
+            if type(pixel_scales) is float or int:
+                pixel_scales = (float(pixel_scales), float(pixel_scales))
+
         mask_2d = mask_util.mask_2d_circular_from_shape_2d_pixel_scales_and_radius(
             shape_2d=shape_2d,
             pixel_scales=pixel_scales,
@@ -121,6 +126,10 @@ def circular_annular(cls, shape_2d, inner_radius_arcsec, outer_radius_arcsec, pi
         centre: (float, float)
             The centre of the annulus used to mask pixels.
         """
+
+        if type(pixel_scales) is float:
+            pixel_scales = (pixel_scales, pixel_scales)
+
         mask_2d = mask_util.mask_2d_circular_annular_from_shape_2d_pixel_scales_and_radii(
             shape_2d=shape_2d,
             pixel_scales=pixel_scales,
@@ -160,6 +169,10 @@ def circular_anti_annular(cls, shape_2d, inner_radius_arcsec, outer_radius_arcse
         centre: (float, float)
             The centre of the anti-annulus used to mask pixels.
         """
+
+        if type(pixel_scales) is float:
+            pixel_scales = (pixel_scales, pixel_scales)
+
         mask_2d = mask_util.mask_2d_circular_anti_annular_from_shape_2d_pixel_scales_and_radii(
             shape_2d=shape_2d,
             pixel_scales=pixel_scales,
@@ -196,6 +209,10 @@ def elliptical(cls, shape_2d,
         centre: (float, float)
             The centre of the ellipse used to mask pixels.
         """
+
+        if type(pixel_scales) is float:
+            pixel_scales = (pixel_scales, pixel_scales)
+
         mask_2d = mask_util.mask_2d_elliptical_from_shape_2d_pixel_scales_and_radius(
             shape_2d=shape_2d,
             pixel_scales=pixel_scales,
@@ -243,6 +260,10 @@ def elliptical_annular(cls, shape_2d,
         centre: (float, float)
             The centre of the elliptical annuli used to mask pixels.
         """
+
+        if type(pixel_scales) is float:
+            pixel_scales = (pixel_scales, pixel_scales)
+
         mask_2d = mask_util.mask_2d_elliptical_annular_from_shape_2d_pixel_scales_and_radius(
             shape_2d=shape_2d,
             pixel_scales=pixel_scales,
@@ -273,6 +294,10 @@ def from_fits(cls, file_path, hdu, pixel_scales, sub_size, origin=(0.0, 0.0)):
         pixel_scales : (float, float)
             The arc-second to pixel conversion factor of each pixel.
         """
+
+        if type(pixel_scales) is float:
+            pixel_scales = (pixel_scales, pixel_scales)
+
         return cls(
             array_util.numpy_array_2d_from_fits(file_path=file_path, hdu=hdu),
             pixel_scales=pixel_scales,

test_autoarray/mock/mock_data.py

@@ -6,44 +6,44 @@
 
 
 class MockImage(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 
 class MockNoiseMap(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 
 class MockBackgroundNoiseMap(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 
 class MockPoissonNoiseMap(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 
 class MockExposureTimeMap(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 
 class MockBackgrondSkyMap(object):
-    def __new__(cls, shape, value, pixel_scales=1.0):
-        return aa.array.manual_2d(
-            array=value * np.ones(shape=shape), pixel_scales=pixel_scales
+    def __new__(cls, shape_2d, value, pixel_scales=1.0):
+        return aa.array.full(
+            fill_value=value, shape_2d=shape_2d, pixel_scales=pixel_scales
         )
 
 

test_autoarray/unit/conftest.py

@@ -145,7 +145,7 @@ def make_convolver_7x7(mask_7x7, blurring_mask_7x7, psf_3x3):
 
 @pytest.fixture(name="image_7x7")
 def make_image_7x7():
-    return mock_data.MockImage(shape=(7, 7), value=1.0)
+    return mock_data.MockImage(shape_2d=(7, 7), value=1.0)
 
 
 @pytest.fixture(name="psf_3x3")
@@ -155,27 +155,27 @@ def make_psf_3x3():
 
 @pytest.fixture(name="noise_map_7x7")
 def make_noise_map_7x7():
-    return mock_data.MockNoiseMap(shape=(7, 7), value=2.0)
+    return mock_data.MockNoiseMap(shape_2d=(7, 7), value=2.0)
 
 
 @pytest.fixture(name="background_noise_map_7x7")
 def make_background_noise_map_7x7():
-    return mock_data.MockBackgroundNoiseMap(shape=(7, 7), value=3.0)
+    return mock_data.MockBackgroundNoiseMap(shape_2d=(7, 7), value=3.0)
 
 
 @pytest.fixture(name="poisson_noise_map_7x7")
 def make_poisson_noise_map_7x7():
-    return mock_data.MockPoissonNoiseMap(shape=(7, 7), value=4.0)
+    return mock_data.MockPoissonNoiseMap(shape_2d=(7, 7), value=4.0)
 
 
 @pytest.fixture(name="exposure_time_map_7x7")
 def make_exposure_time_map_7x7():
-    return mock_data.MockExposureTimeMap(shape=(7, 7), value=5.0)
+    return mock_data.MockExposureTimeMap(shape_2d=(7, 7), value=5.0)
 
 
 @pytest.fixture(name="background_sky_map_7x7")
 def make_background_sky_map_7x7():
-    return mock_data.MockBackgrondSkyMap(shape=(7, 7), value=6.0)
+    return mock_data.MockBackgrondSkyMap(shape_2d=(7, 7), value=6.0)
 
 
 @pytest.fixture(name="positions_7x7")
@@ -209,13 +209,13 @@ def make_imaging_7x7(
 
 @pytest.fixture(name="imaging_6x6")
 def make_imaging_6x6():
-    image = mock_data.MockImage(shape=(6, 6), value=1.0)
+    image = mock_data.MockImage(shape_2d=(6, 6), value=1.0)
     psf = mock_data.MockPSF(shape_2d=(3, 3), value=1.0)
-    noise_map = mock_data.MockNoiseMap(shape=(6, 6), value=2.0)
-    background_noise_map = mock_data.MockBackgroundNoiseMap(shape=(6, 6), value=3.0)
-    poisson_noise_map = mock_data.MockPoissonNoiseMap(shape=(6, 6), value=4.0)
-    exposure_time_map = mock_data.MockExposureTimeMap(shape=(6, 6), value=5.0)
-    background_sky_map = mock_data.MockBackgrondSkyMap(shape=(6, 6), value=6.0)
+    noise_map = mock_data.MockNoiseMap(shape_2d=(6, 6), value=2.0)
+    background_noise_map = mock_data.MockBackgroundNoiseMap(shape_2d=(6, 6), value=3.0)
+    poisson_noise_map = mock_data.MockPoissonNoiseMap(shape_2d=(6, 6), value=4.0)
+    exposure_time_map = mock_data.MockExposureTimeMap(shape_2d=(6, 6), value=5.0)
+    background_sky_map = mock_data.MockBackgrondSkyMap(shape_2d=(6, 6), value=6.0)
 
     return mock_data.MockImaging(
         image=image,