Merge branch 'feature/composite' of https://github.com/ajshajib/hierArc…

… into feature/composite
sibirrer · Dec 4, 2023 · ff4b614 · ff4b614
2 parents d2648e3 + eaae1a2
commit ff4b614
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Showing 2 changed files with 11 additions and 7 deletions.
diff --git a/hierarc/Likelihood/hierarchy_likelihood.py b/hierarc/Likelihood/hierarchy_likelihood.py
@@ -324,7 +324,7 @@ def draw_lens_scaling_params(
                 gamma_in + alpha_gamma_in * self._lambda_scaling_property,
                 gamma_in_sigma,
                 m2l + alpha_m2l * self._lambda_scaling_property,
-                m2l_sigma
+                m2l_sigma,
             )
             return gamma_in_draw, m2l_draw
         else:

diff --git a/hierarc/Likelihood/parameter_scaling.py b/hierarc/Likelihood/parameter_scaling.py
@@ -177,10 +177,10 @@ def draw_anisotropy(
             return np.array([a_ani_draw, beta_inf_draw])
         return None
 
-    def draw_lens_parameters(self, gamma_in=None, gamma_in_sigma=0, m2l=None,
-                             m2l_sigma=0):
-        """
-        Draw Gaussian distribution and re-sample if outside bounds.
+    def draw_lens_parameters(
+        self, gamma_in=None, gamma_in_sigma=0, m2l=None, m2l_sigma=0
+    ):
+        """Draw Gaussian distribution and re-sample if outside bounds.
 
         :param gamma_in: mean of the distribution
         :param gamma_in_sigma: std of the distribution
@@ -200,8 +200,12 @@ def draw_lens_parameters(self, gamma_in=None, gamma_in_sigma=0, m2l=None,
         gamma_in_draw = np.random.normal(gamma_in, gamma_in_sigma)
         m2l_draw = np.random.normal(m2l, m2l_sigma)
 
-        if (gamma_in_draw < self._gamma_in_min or gamma_in_draw > self._gamma_in_max
-            or m2l_draw < self._m2l_min or m2l_draw > self._m2l_max):
+        if (
+            gamma_in_draw < self._gamma_in_min
+            or gamma_in_draw > self._gamma_in_max
+            or m2l_draw < self._m2l_min
+            or m2l_draw > self._m2l_max
+        ):
             return self.draw_lens_parameters(gamma_in, gamma_in_sigma, m2l, m2l_sigma)
 
         return gamma_in_draw, m2l_draw