Merge branch 'doc_fix' into 'NIFTy_6'

Fix Sphinx warnings

See merge request !573

docs/source/ift.rst

@@ -224,7 +224,7 @@ Thus, only the gradient of the KL is needed with respect to this, which can be e
 
 We stochastically estimate the KL-divergence and gradients with a set of samples drawn from the approximate posterior distribution.
 The particular structure of the covariance allows us to draw independent samples solving a certain system of equations.
-This KL-divergence for MGVI is implemented in the class :class:`~minimization.metric_gaussian_kl.MetricGaussianKL` within NIFTy6.
+This KL-divergence for MGVI is implemented in the class :class:`~nifty6.minimization.metric_gaussian_kl.MetricGaussianKL` within NIFTy6.
 
 
 The demo `getting_started_3.py` for example not only infers a field this way, but also the power spectrum of the process that has generated the field.

nifty6/operators/normal_operators.py

@@ -30,8 +30,8 @@ def NormalTransform(mean, sigma, key, N_copies=0):
     """Opchain that transforms standard normally distributed values to
     normally distributed values with given mean an standard deviation.
 
-    Parameters:
-    -----------
+    Parameters
+    ----------
     mean : float
         Mean of the field
     sigma : float
@@ -60,8 +60,8 @@ def LognormalTransform(mean, sigma, key, N_copies):
     """Opchain that transforms standard normally distributed values to
     log-normally distributed values with given mean an standard deviation.
 
-    Parameters:
-    -----------
+    Parameters
+    ----------
     mean : float
         Mean of the field
     sigma : float