diff --git a/python/damask/grid_filters.py b/python/damask/grid_filters.py
index cbd4b35e5..38039ac14 100644
--- a/python/damask/grid_filters.py
+++ b/python/damask/grid_filters.py
@@ -103,8 +103,8 @@ def divergence(size: _FloatSequence,
     k_s = _ks(size,f.shape[:3],True)
 
     f_fourier = _np.fft.rfftn(f,axes=(0,1,2))
-    divergence_ = (_np.einsum('ijkl,ijkl ->ijk', k_s,f_fourier)*2.0j*_np.pi if n == 3 else          # vector, 3   -> 1
-                   _np.einsum('ijkm,ijklm->ijkl',k_s,f_fourier)*2.0j*_np.pi)                        # tensor, 3x3 -> 3
+    divergence_ = (_np.einsum('ijkl,ijkl ->ijk' if n==3 else
+                              'ijkm,ijklm->ijkl', k_s,f_fourier)*2.0j*_np.pi)                       # vector 3 -> 1, tensor 3x3 -> 3
 
     return _np.fft.irfftn(divergence_,axes=(0,1,2),s=f.shape[:3])
 
@@ -131,8 +131,8 @@ def gradient(size: _FloatSequence,
     k_s = _ks(size,f.shape[:3],True)
 
     f_fourier = _np.fft.rfftn(f,axes=(0,1,2))
-    gradient_ = (_np.einsum('ijkl,ijkm->ijkm', f_fourier,k_s)*2.0j*_np.pi if n == 1 else            # scalar, 1 -> 3
-                 _np.einsum('ijkl,ijkm->ijklm',f_fourier,k_s)*2.0j*_np.pi)                          # vector, 3 -> 3x3
+    gradient_ = (_np.einsum('ijkl,ijkm->ijkm' if n==1 else
+                            'ijkl,ijkm->ijklm',f_fourier,k_s)*2.0j*_np.pi)                          # scalar 1 -> 3, vector 3 -> 3x3
 
     return _np.fft.irfftn(gradient_,axes=(0,1,2),s=f.shape[:3])