diff --git a/nifty5/library/smooth_linear_amplitude.py b/nifty5/library/smooth_linear_amplitude.py
index 34b6ca54834af1da112bd7a030743f1710462479..5f19efb4544df88a74de14d43f3eeb7986732e1b 100644
--- a/nifty5/library/smooth_linear_amplitude.py
+++ b/nifty5/library/smooth_linear_amplitude.py
@@ -169,10 +169,11 @@ def SLAmplitude(*, target, n_pix, a, k0, sm, sv, im, iv, za=None, zq=None,
     iv : float
         Prior standard deviation of y-intercept of power law.
     za : float, optional
-        The alpha-parameter of the inverse-gamma distribution.
-        Setting the a seperate prior on the zeroGmode of the amplitude model.
+        Parameter of the optional zero mode prior (inverse-gamma): alpha
+        See :class:`InverseGammaOperator` for interpretation.
     zq : float, optional
-        The q-parameter of the inverse-gamma distribution.
+        Parameter of the optional zero mode prior (inverse-gamma): q
+        See :class:`InverseGammaOperator` for interpretation.
 
     Returns
     -------
@@ -192,6 +193,7 @@ def SLAmplitude(*, target, n_pix, a, k0, sm, sv, im, iv, za=None, zq=None,
     if za != None and zq != None:
         separate_zero_mode_prior = True
         za, zq = float(za), float(zq)
+        print(keys[2] + " mean: ", (zq/(1+za)))
     else:
         separate_zero_mode_prior = False
         if za != None or zq != None:
@@ -220,14 +222,13 @@ def SLAmplitude(*, target, n_pix, a, k0, sm, sv, im, iv, za=None, zq=None,
         return et @ loglog_ampl.exp()
     else:
         zero_mode = ValueInserter(et.target, (0,)*len(et.target.shape))
+        zero_mode = zero_mode @ InverseGammaOperator(
+            zero_mode.domain, za, zq) @ FieldAdapter(
+                zero_mode.domain, keys[2])
 
         mask = np.ones(et.target.shape)
         mask[(0,)*len(et.target.shape)] = 0.
         mask = from_global_data(et.target, mask)
         mask = DiagonalOperator(mask)
-        zero_mode = zero_mode @ InverseGammaOperator(
-            zero_mode.domain, za, zq) @ FieldAdapter(
-                zero_mode.domain, keys[2])
-        print(keys[2] + " mean: ", (zq/(1+za)))
 
-        return mask @ (et @ loglog_ampl.exp()) + zero_mode
+        return mask @ et @ loglog_ampl.exp() + zero_mode