doc tweaks

nifty4/field.py

@@ -44,8 +44,6 @@ class Field(object):
 
     dtype : type
         A numpy.type. Most common are float and complex.
-
-    copy : bool
     """
 
     def __init__(self, domain=None, val=None, dtype=None, copy=False,
@@ -77,6 +75,20 @@ class Field(object):
 
     @staticmethod
     def full(domain, val, dtype=None):
+        """Creates a Field with a given domain, filled with a constant value.
+
+        Parameters
+        ----------
+        domain : Domain, tuple of Domain, or DomainTuple
+            domain of the new Field
+        val : float/complex/int scalar
+            fill value. Data type of the field is inferred from val.
+
+        Returns
+        -------
+        Field
+            the newly created field
+        """
         if not np.isscalar(val):
             raise TypeError("val must be a scalar")
         return Field(DomainTuple.make(domain), val, dtype)
@@ -95,6 +107,20 @@ class Field(object):
 
     @staticmethod
     def full_like(field, val, dtype=None):
+        """Creates a Field from a template, filled with a constant value.
+
+        Parameters
+        ----------
+        field : Field
+            the template field, from which the domain is inferred
+        val : float/complex/int scalar
+            fill value. Data type of the field is inferred from val.
+
+        Returns
+        -------
+        Field
+            the newly created field
+        """
         if not isinstance(field, Field):
             raise TypeError("field must be of Field type")
         return Field.full(field._domain, val, dtype)

nifty4/library/wiener_filter_curvature.py

@@ -31,11 +31,11 @@ class WienerFilterCurvature(EndomorphicOperator):
 
     Parameters
     ----------
-    R: LinearOperator
+    R : LinearOperator
         The response operator of the Wiener filter measurement.
-    N: EndomorphicOperator
+    N : EndomorphicOperator
         The noise covariance.
-    S: EndomorphicOperator
+    S : DiagonalOperator
         The prior signal covariance
     inverter : Minimizer
         The minimizer to use during numerical inversion

nifty4/library/wiener_filter_energy.py

@@ -28,17 +28,19 @@ class WienerFilterEnergy(Energy):
 
     Parameters
     ----------
-    position: Field
+    position : Field
         The current map in harmonic space.
-    d: Field
+    d :  Field
         the data
-    R: LinearOperator
+    R : LinearOperator
         The response operator, description of the measurement process. It needs
         to map from harmonic signal space to data space.
-    N: EndomorphicOperator
+    N : EndomorphicOperator
         The noise covariance in data space.
-    S: EndomorphicOperator
+    S : EndomorphicOperator
         The prior signal covariance in harmonic space.
+    inverter : Minimizer
+        the minimization strategy to use for operator inversion
     """
 
     def __init__(self, position, d, R, N, S, inverter, _j=None):