cleanups

README.md

@@ -58,13 +58,13 @@ that apply to fields.
 <!-- -->
 
     Field.conjugate     Field.dim          Field.norm
-    Field.vdot          Field.set_val      Field.weight
+    Field.vdot          Field.weight
 
 -   [Operators](http://www.mpa-garching.mpg.de/ift/nifty/operator.html)
     -   `DiagonalOperator` - purely diagonal matrices in a specified
         basis
-    -   `ProjectionOperator` - projections onto subsets of a specified
-        basis
+    -   `FFTOperator` - conversion between spaces and their harmonic
+                        counterparts
     -   (and more)
 -   (and more)
 
@@ -110,12 +110,12 @@ For a quick start, you can browse through the [informal
 introduction](http://www.mpa-garching.mpg.de/ift/nifty/start.html) or
 dive into NIFTY by running one of the demonstrations, e.g.:
 
-    python demos/wiener_filter.py
+    python demos/wiener_filter_via_curvature.py
 
 Acknowledgement
 ---------------
 
-Please, acknowledge the use of NIFTY in your publication(s) by using a
+Please acknowledge the use of NIFTY in your publication(s) by using a
 phrase such as the following:
 
 > *"Some of the results in this publication have been derived using the

nifty/operators/power_projection_operator.py

@@ -23,7 +23,7 @@ from .. import dobj
 import numpy as np
 
 class PowerProjectionOperator(LinearOperator):
-    def __init__(self, domain, space, power_space=None):
+    def __init__(self, domain, space=None, power_space=None):
         super(PowerProjectionOperator, self).__init__()
 
         # Initialize domain and target
@@ -36,8 +36,6 @@ class PowerProjectionOperator(LinearOperator):
         hspace = self._domain[space]
         if not hspace.harmonic:
             raise ValueError("Operator acts on harmonic spaces only")
-        if isinstance(hspace, PowerSpace):
-            raise TypeError("Operator cannot act on PowerSpaces")
         if power_space is None:
             power_space = PowerSpace(hspace)
         else:
@@ -64,9 +62,7 @@ class PowerProjectionOperator(LinearOperator):
         pindex = self._target[self._space].pindex
         pindex = pindex.reshape((1, pindex.size, 1))
         arr = x.val.reshape(x.domain.collapsed_shape_for_domain(self._space))
-        out = dobj.zeros(self._domain.collapsed_shape_for_domain(self._space),
-              dtype=x.dtype)
-        out[()] = arr[(slice(None), pindex.ravel(), slice(None))]
+        out = arr[(slice(None), pindex.ravel(), slice(None))]
         return Field(self._domain, out.reshape(self._domain.shape))
 
     @property