diff --git a/mbtrack2/utilities/misc.py b/mbtrack2/utilities/misc.py
index a8cb9704b569edc1f2a8d0469012592668696547..87cb942cef012e5e156a2245d5c5ac9a802c20ef 100644
--- a/mbtrack2/utilities/misc.py
+++ b/mbtrack2/utilities/misc.py
@@ -221,7 +221,8 @@ def yokoya_elliptic(x_radius, y_radius):
             small_semiaxis = x_radius
             large_semiaxis = y_radius
 
-        # Our equations are approximately valid only for qr (ratio) values less than or equal to 0.8.
+        # Our equations are approximately valid only for qr (ratio) values
+        # less than or equal to 0.8.
         qr_th = 0.8
         F = np.sqrt(large_semiaxis**2 - small_semiaxis**2)
         mu_b = np.arccosh(large_semiaxis/F)
@@ -305,14 +306,15 @@ def yokoya_elliptic(x_radius, y_radius):
             ff_values = np.array(function_ff(small_semiaxis_th, F_th, mu_b_th, ip, il))
             L_values = np.array(function_L(mu_b_th, ip, il))
 
-            coeff_long = np.where((ip == 0) & (il == 0), 0.25, np.where((ip == 0) | (il == 0), 0.5, 1.0))
+            coeff_long = np.where( (ip == 0) & (il == 0), 0.25,
+                                    np.where((ip == 0) | (il == 0), 0.5, 1.0) )
             coeff_quad = np.where(il == 0, 0.5, 1.0)
 
-            yoklong = np.sum(coeff_long * ff_values[0] * L_values[0])
-            yokxdip = np.sum(ff_values[1] * L_values[1])
-            yokydip = np.sum(ff_values[2] * L_values[2])
-            yokxquad = -np.sum(coeff_quad * ff_values[3] * L_values[0])
-            yokyquad = -yokxquad
+            yoklong_th = np.sum(coeff_long * ff_values[0] * L_values[0])
+            yokxdip_th = np.sum(ff_values[1] * L_values[1])
+            yokydip_th = np.sum(ff_values[2] * L_values[2])
+            yokxquad_th = -np.sum(coeff_quad * ff_values[3] * L_values[0])
+            yokyquad_th = -yokxquad_th
             
             if y_radius > x_radius:
                 yokxdip_th, yokydip_th = yokydip_th, yokxdip_th
@@ -344,7 +346,8 @@ def yokoya_elliptic(x_radius, y_radius):
             ff_values = np.array(function_ff(small_semiaxis, F, mu_b, ip, il))
             L_values = np.array(function_L(mu_b, ip, il))
 
-            coeff_long = np.where((ip == 0) & (il == 0), 0.25, np.where((ip == 0) | (il == 0), 0.5, 1.0))
+            coeff_long = np.where( (ip == 0) & (il == 0), 0.25,
+                                    np.where((ip == 0) | (il == 0), 0.5, 1.0) )
             coeff_quad = np.where(il == 0, 0.5, 1.0)
 
             yoklong = np.sum(coeff_long * ff_values[0] * L_values[0])