finish

Author: Jammy2211

autogalaxy/abstract_fit.py

@@ -110,7 +110,9 @@ def linear_light_profile_intensity_dict(
             reconstruction = self.inversion.reconstruction_dict[linear_obj_func]
 
             for i, light_profile in enumerate(linear_obj_func.light_profile_list):
-                linear_light_profile_intensity_dict[light_profile] = float(reconstruction[i])
+                linear_light_profile_intensity_dict[light_profile] = float(
+                    reconstruction[i]
+                )
 
         return linear_light_profile_intensity_dict
 

autogalaxy/analysis/chaining_util.py

@@ -500,7 +500,6 @@ def mass_light_dark_basis_from(
         lmp_model.centre = light_profile.centre
         lmp_model.ell_comps = light_profile.ell_comps
 
-
         print(light_profile.intensity)
         print(type(light_profile.intensity))
 

autogalaxy/profiles/basis.py

@@ -215,7 +215,10 @@ def deflections_yx_2d_from(
         """
         if len(self.mass_profile_list) > 0:
             return sum(
-                [mass.deflections_yx_2d_from(grid=grid, xp=xp) for mass in self.profile_list]
+                [
+                    mass.deflections_yx_2d_from(grid=grid, xp=xp)
+                    for mass in self.profile_list
+                ]
             )
         return xp.zeros((grid.shape[0], 2))
 

autogalaxy/profiles/light/linear/abstract.py

@@ -203,7 +203,9 @@ def __init__(
                     """
                 )
 
-        super().__init__(grid=grid, regularization=regularization, settings=settings, xp=xp)
+        super().__init__(
+            grid=grid, regularization=regularization, settings=settings, xp=xp
+        )
 
         self.blurring_grid = blurring_grid
         self.psf = psf
@@ -307,7 +309,7 @@ def operated_mapping_matrix_override(self) -> Optional[np.ndarray]:
                 image=image_2d,
                 blurring_image=blurring_image_2d,
                 use_mixed_precision=self.settings.use_mixed_precision,
-                xp=self._xp
+                xp=self._xp,
             )
 
             blurred_image_2d_list.append(blurred_image_2d.array)

autogalaxy/profiles/mass/stellar/gaussian.py

@@ -197,19 +197,18 @@ def zeta_from(self, grid: aa.type.Grid2DLike, xp=np):
 
         ind_pos_y = y >= 0
 
-        scale = q / (xp.asarray(self.sigma, dtype=xp.float64)
-                     * xp.sqrt(xp.asarray(2.0, dtype=xp.float64) * (1.0 - q2)))
+        scale = q / (
+            xp.asarray(self.sigma, dtype=xp.float64)
+            * xp.sqrt(xp.asarray(2.0, dtype=xp.float64) * (1.0 - q2))
+        )
 
         xs = x * scale
         ys = xp.abs(y) * scale
 
         z1 = xs + 1j * ys
         z2 = q * xs + 1j * ys / q
 
-        exp_term = xp.exp(
-            -(xs * xs) * (1.0 - q2)
-            - (ys * ys) * (1.0 / q2 - 1.0)
-        )
+        exp_term = xp.exp(-(xs * xs) * (1.0 - q2) - (ys * ys) * (1.0 / q2 - 1.0))
 
         core = -1j * (self.wofz(z1, xp=xp) - exp_term * self.wofz(z2, xp=xp))
 
@@ -243,10 +242,13 @@ def wofz(self, z, xp=np):
         w_large = 1j * inv_sqrt_pi / t
 
         # ---------- Region 5 ----------
-        U5 = xp.asarray([1.320522, 35.7668, 219.031,
-                         1540.787, 3321.990, 36183.31], dtype=xp.float64)
-        V5 = xp.asarray([1.841439, 61.57037, 364.2191,
-                         2186.181, 9022.228, 24322.84, 32066.6], dtype=xp.float64)
+        U5 = xp.asarray(
+            [1.320522, 35.7668, 219.031, 1540.787, 3321.990, 36183.31], dtype=xp.float64
+        )
+        V5 = xp.asarray(
+            [1.841439, 61.57037, 364.2191, 2186.181, 9022.228, 24322.84, 32066.6],
+            dtype=xp.float64,
+        )
 
         t = inv_sqrt_pi
         for u in U5:
@@ -259,10 +261,22 @@ def wofz(self, z, xp=np):
         w5 = xp.exp(-z2) + 1j * z * t / s
 
         # ---------- Region 6 ----------
-        U6 = xp.asarray([5.9126262, 30.180142, 93.15558,
-                         181.92853, 214.38239, 122.60793], dtype=xp.float64)
-        V6 = xp.asarray([10.479857, 53.992907, 170.35400,
-                         348.70392, 457.33448, 352.73063, 122.60793], dtype=xp.float64)
+        U6 = xp.asarray(
+            [5.9126262, 30.180142, 93.15558, 181.92853, 214.38239, 122.60793],
+            dtype=xp.float64,
+        )
+        V6 = xp.asarray(
+            [
+                10.479857,
+                53.992907,
+                170.35400,
+                348.70392,
+                457.33448,
+                352.73063,
+                122.60793,
+            ],
+            dtype=xp.float64,
+        )
 
         t = inv_sqrt_pi
         for u in U6: