diff --git a/zernipy/grid.py b/zernipy/grid.py
index 9b4131e..a6c2a57 100644
--- a/zernipy/grid.py
+++ b/zernipy/grid.py
@@ -1,7 +1,8 @@
 """Classes for representing flux coordinates."""
 
 from abc import ABC, abstractmethod
-from zernipy.backend import np, jnp, put
+
+from zernipy.backend import jnp, np, put
 
 
 class _Indexable:
diff --git a/zernipy/zernike.py b/zernipy/zernike.py
index 9f69a32..9ee989d 100644
--- a/zernipy/zernike.py
+++ b/zernipy/zernike.py
@@ -1,7 +1,8 @@
 """Functions for evaluating Zernike polynomials and their derivatives."""
 
 import functools
-from zernipy.backend import cond, custom_jvp, fori_loop, gammaln, jit, jnp, select, switch
+
+from zernipy.backend import cond, custom_jvp, fori_loop, gammaln, jit, jnp, switch
 
 
 def jacobi_poly_single(x, n, alpha, beta=0, P_n1=0, P_n2=0):
@@ -1197,7 +1198,7 @@ def find_init_jacobi(dx, args):
 
 
 @custom_jvp
-@functools.partial(jit, static_argnums=[3,4])
+@functools.partial(jit, static_argnums=[3, 4])
 def zernike_radial_jvp_gpu(r, l, m, dr=0, repeat=1):
     """Radial part of zernike polynomials.
 
@@ -1229,12 +1230,13 @@ def zernike_radial_jvp_gpu(r, l, m, dr=0, repeat=1):
             "Analytic radial derivatives of Zernike polynomials for order>4 "
             + "have not been implemented."
         )
+
     def update(x, args):
         index, result, out = args
         idx = index[x]
         out = out.at[:, idx].set(result[:, None])
         return (index, result, out)
-    
+
     def body_inner(N, args):
         alpha, out, P_past = args
         P_n2 = P_past[0]
@@ -1299,9 +1301,9 @@ def find_inter_jacobi(dx, args):
                 - coef[3] * 128 * (2 * alpha + 3) * r ** (alpha + 2) * P_n[3]
                 + coef[4] * 256 * r ** (alpha + 4) * P_n[4]
             )
-        index = jnp.argwhere(jnp.logical_and(m == alpha, n == N),  size=repeat)
+        index = jnp.argwhere(jnp.logical_and(m == alpha, n == N), size=repeat)
         _, _, out = fori_loop(0, repeat, update, (index, result, out))
-        
+
         # Shift past values if needed
         mask = N >= 2 + dxs
         P_n2 = jnp.where(mask[:, None], P_n1, P_n2)