Merge remote-tracking branch 'origin/main'

sibirrer · Jun 11, 2024 · 6b21dd4 · 6b21dd4
2 parents 78cda97 + e84214a
commit 6b21dd4
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Showing 2 changed files with 12 additions and 5 deletions.
diff --git a/lenstronomy/Analysis/lens_profile.py b/lenstronomy/Analysis/lens_profile.py
@@ -152,7 +152,7 @@ def profile_slope(
         center_y=None,
         model_list_bool=None,
         num_points=10,
-        alpha_differentials=True
+        alpha_differentials=True,
     ):
         """Computes the logarithmic power-law slope of a profile. ATTENTION: this is not
         an observable!
@@ -164,7 +164,8 @@ def profile_slope(
         :param center_y: center of profile from where to compute the slope
         :param model_list_bool: bool list, indicate which part of the model to consider
         :param num_points: number of estimates around the Einstein radius
-        :param alpha_differentials: if True, uses the deflection angle differentials, else the convergence differentials
+        :param alpha_differentials: if True, uses the deflection angle differentials,
+            else the convergence differentials
         :type alpha_differentials: bool
         :return: logarithmic power-law slope
         """
@@ -184,7 +185,9 @@ def profile_slope(
                 center_x + x_dr, center_y + y_dr, kwargs_lens, k=model_list_bool
             )
             alpha_E_dr = np.sqrt(alpha_E_dr_x_i**2 + alpha_E_dr_y_i**2)
-            slope = np.mean(np.log(alpha_E_dr / alpha_E_r) / np.log((radius + dr) / radius))
+            slope = np.mean(
+                np.log(alpha_E_dr / alpha_E_r) / np.log((radius + dr) / radius)
+            )
             gamma = -slope + 2
         else:
             kappa = self._lens_model.kappa(

diff --git a/test/test_Analysis/test_lens_profile.py b/test/test_Analysis/test_lens_profile.py
@@ -49,9 +49,13 @@ def test_profile_slope(self):
                 "gamma": gamma_in,
             }
         ]
-        gamma_out = lens_model.profile_slope(kwargs_lens, radius=1.45, alpha_differentials=True)
+        gamma_out = lens_model.profile_slope(
+            kwargs_lens, radius=1.45, alpha_differentials=True
+        )
         npt.assert_array_almost_equal(gamma_out, gamma_in, decimal=3)
-        gamma_out = lens_model.profile_slope(kwargs_lens, radius=1.45, alpha_differentials=False)
+        gamma_out = lens_model.profile_slope(
+            kwargs_lens, radius=1.45, alpha_differentials=False
+        )
         npt.assert_array_almost_equal(gamma_out, gamma_in, decimal=3)
 
     def test_effective_einstein_radius(self):