MAINT: Fix missing doc, wrong doc order etc

adler-j · adler-j · commit 7507c52ecdb4 · 2017-01-25T12:15:01.000+01:00
diff --git a/odl/discr/discr_mappings.py b/odl/discr/discr_mappings.py
@@ -185,7 +185,7 @@ def __init__(self, ip_fset, partition, dspace, **kwargs):
 
         Parameters
         ----------
-        fset : `FunctionSet`
+        ip_fset : `FunctionSet`
             The non-discretized (abstract) set of functions to be
             discretized. The function domain must provide a
             `Set.contains_set` method.
diff --git a/odl/discr/grid.py b/odl/discr/grid.py
@@ -1097,8 +1097,10 @@ def uniform_grid(min_pt, max_pt, shape, nodes_on_bdry=True):
 
     Parameters
     ----------
-    min_pt, max_pt : float or sequence of float
-        Vectors of lower/upper ends of the intervals in the product.
+    min_pt : float or sequence of float
+        Vectors of lower ends of the intervals in the product.
+    max_pt : float or sequence of float
+        Vectors of upper ends of the intervals in the product.
     shape : int or sequence of ints
         Number of nodes per axis. Entries corresponding to degenerate axes
         must be equal to 1.
diff --git a/odl/discr/lp_discr.py b/odl/discr/lp_discr.py
@@ -1188,8 +1188,10 @@ def uniform_discr(min_pt, max_pt, shape, exponent=2.0, interp='nearest',
 
     Parameters
     ----------
-    min_pt, max_pt: float or sequence of floats
-        Minimum/maximum corners of the desired function domain.
+    min_pt : float or sequence of floats
+        Maximum corners of the desired function domain.
+    max_pt : float or sequence of floats
+        Minimum corners of the desired function domain.
     shape : int or sequence of ints
         Number of samples per axis.
     exponent : positive float, optional
@@ -1334,10 +1336,14 @@ def uniform_discr_fromdiscr(discr, min_pt=None, max_pt=None,
     ----------
     discr : `DiscreteLp`
         Uniformly discretized space used as a template.
-    min_pt, max_pt: float or sequence of floats
-        Minimum/maximum corners of the desired function domain.
-    shape : int or sequence of ints
+    min_pt : float or sequence of floats, optional
+        Minimum corners of the desired function domain.
+    max_pt : float or sequence of floats, optional
+        Maximum corners of the desired function domain.
+    shape : int or sequence of ints, optional
         Number of samples per axis.
+    cell_sides : array-like, optional
+        Side length of each cell.
     exponent : positive float, optional
         The parameter :math:`p` in :math:`L^p`. If the exponent is not
         equal to the default 2.0, the space has no inner product.
diff --git a/odl/operator/operator.py b/odl/operator/operator.py
@@ -45,9 +45,12 @@ def _default_call_out_of_place(op, x, **kwargs):
 
     Parameters
     ----------
-    x : `domain` element
-        An object in the operator domain. The operator is applied
-        to it.
+    op : `Operator`
+        Operator to call
+    x : ``op.domain`` element
+        Point in which to call the operator.
+    kwargs:
+        Optional arguments to the operator.
 
     Returns
     -------
@@ -65,17 +68,15 @@ def _default_call_in_place(op, x, out, **kwargs):
 
     Parameters
     ----------
-    x : `domain` element
-        An object in the operator domain. The operator is applied
-        to it.
-
-    out : `range` element
+    op : `Operator`
+        Operator to call
+    x : ``op.domain`` element
+        Point in which to call the operator.
+    out : ``op.range`` element
         An object in the operator range. The result of an operator
-        evaluation.
-
-    Returns
-    -------
-    None
+        evaluation is written here.
+    kwargs:
+        Optional arguments to the operator.
     """
     out.assign(op.range.element(op._call_out_of_place(x, **kwargs)))
 
@@ -168,9 +169,9 @@ def _dispatch_call_args(cls=None, bound_call=None, unbound_call=None,
     cls : `class`, optional
         The ``_call()`` method of this class is checked. If omitted,
         provide ``unbound_call`` instead to check directly.
-    bound_call: callable, optional
+    bound_call : callable, optional
         Check this bound method instead of ``cls``
-    unbound_call: callable, optional
+    unbound_call : callable, optional
         Check this unbound function instead of ``cls``
     attr : string, optional
         Check this attribute instead of ``_call``, e.g. ``__call__``
@@ -2021,8 +2022,8 @@ def __init__(self, operator, vector):
 
         Parameters
         ----------
-        op : `Operator`
-            The domain of ``op`` must be a ``vector.space``.
+        operator : `Operator`
+            The domain of ``operator`` must be a ``vector.space``.
         vector : ``op.domain`` element
             The fixed element to multiply with.
         """
diff --git a/odl/phantom/transmission.py b/odl/phantom/transmission.py
@@ -288,7 +288,7 @@ def forbild(space, resolution=False, ear=True, value_type='density',
         The format the phantom should be given in.
         'density' returns floats in the range [0, 1.8] (g/cm^3)
         'materials' returns indices in the range [0, 7].
-    scale : {'auto', 'cm', 'meters', 'mm'}
+    scale : {'auto', 'cm', 'meters', 'mm'}, optional
         Controls how ``space`` should be rescaled to fit the definition of
         the forbild phantom, which is defined on the square
         [-12.8, 12.8] x [-12.8, 12.8] cm.
diff --git a/odl/solvers/functional/default_functionals.py b/odl/solvers/functional/default_functionals.py
@@ -1190,7 +1190,7 @@ def __init__(self, space, prior=None):
         ----------
         space : `DiscreteLp` or `FnBase`
             Domain of the functional.
-        g : ``space`` `element-like`, optional
+        prior : ``space`` `element-like`, optional
             Data term, positive.
             Default: if None it is take as the one-element.
         """
@@ -1452,7 +1452,7 @@ def __init__(self, space, prior=None):
         ----------
         space : `DiscreteLp` or `FnBase`
             Domain of the functional.
-        g : ``space`` `element-like`, optional
+        prior : ``space`` `element-like`, optional
             Data term, positive.
             Default: if None it is take as the one-element.
         """
diff --git a/odl/solvers/functional/functional.py b/odl/solvers/functional/functional.py
@@ -819,7 +819,7 @@ def __init__(self, func, linear_term):
         ----------
         func : `Functional`
             Function corresponding to ``f``.
-        translation : `domain` element
+        linear_term : `domain` element
             Element in domain of ``func``, corresponding to the translation.
         """
         if not isinstance(func, Functional):
diff --git a/odl/solvers/nonsmooth/proximal_operators.py b/odl/solvers/nonsmooth/proximal_operators.py
@@ -343,7 +343,7 @@ def proximal_composition(proximal, operator, mu):
 
     Parameters
     ----------
-    prox_factory : callable
+    proximal : callable
         A factory function that, when called with a step size returns the
         proximal operator of ``F``
     operator : `Operator`
diff --git a/odl/solvers/util/callback.py b/odl/solvers/util/callback.py
@@ -137,7 +137,7 @@ def __init__(self, results=None, function=None):
         results : list, optional
             List in which to store the iterates.
             Default: new list (``[]``)
-        results : callable, optional
+        function : callable, optional
             Function to be called on all incoming results before storage.
             Default: copy
 
diff --git a/odl/trafos/wavelet.py b/odl/trafos/wavelet.py
@@ -372,6 +372,10 @@ def __init__(self, range, nlevels, wavelet, pad_mode='constant',
         range : `DiscreteLp`
             Domain of the forward wavelet transform (the "image domain"),
             which is the range of this inverse transform.
+        nlevels : positive int
+            Number of scaling levels to be used in the decomposition. The
+            maximum number of levels can be calculated with
+            `pywt.dwt_max_level`.
         wavelet : string or `pywt.Wavelet`
             Specification of the wavelet to be used in the transform.
             If a string is given, it is converted to a `pywt.Wavelet`.
@@ -393,12 +397,6 @@ def __init__(self, range, nlevels, wavelet, pad_mode='constant',
 
             ``'dmey'``: Discrete FIR approximation of the Meyer wavelet
 
-        nlevels : positive int
-            Number of scaling levels to be used in the decomposition. The
-            maximum number of levels can be calculated with
-            `pywt.dwt_max_level`.
-        variant : {'forward', 'inverse', 'adjoint'}
-            Wavelet transform variant to be created.
         pad_mode : string, optional
             Method to be used to extend the signal.
 
diff --git a/odl/util/numerics.py b/odl/util/numerics.py
@@ -321,7 +321,7 @@ def resize_array(arr, newshp, offset=None, pad_mode='constant', pad_const=0,
         Array to be resized.
     newshp : sequence of ints
         Desired shape of the output array.
-    offset: sequence of ints, optional
+    offset : sequence of ints, optional
         Specifies how many entries are added to/removed from the "left"
         side (corresponding to low indices) of ``arr``.
     pad_mode : string, optional
