version update.

README.rst

@@ -64,6 +64,8 @@ apply to fields.
     *   ``response_operator`` - exemplary responses that include a convolution,
         masking and projection
     *   ``propagator_operator`` - information propagator in Wiener filter theory
+    *   ``explicit_operator`` - linear operators with an explicit matrix
+        representation
     *   (and more)
 
 * (and more)
@@ -97,7 +99,7 @@ Requirements
 Download
 ........
 
-The latest release is tagged **v0.6.0** and is available as a source package
+The latest release is tagged **v0.7.0** and is available as a source package
 at `<https://github.com/mselig/nifty/tags>`_. The current version can be
 obtained by cloning the repository::
 
@@ -140,5 +142,7 @@ The NIFTY package is licensed under the
 `GPLv3 <http://www.gnu.org/licenses/gpl.html>`_ and is distributed *without any
 warranty*.
 
+----
+
 **NIFTY** project homepage: `<http://www.mpa-garching.mpg.de/ift/nifty/>`_
 

__init__.py

@@ -24,6 +24,7 @@ from nifty_core import *
 from nifty_cmaps import *
 from nifty_power import *
 from nifty_tools import *
+from nifty_explicit import *
 
 
 

demos/demo_wf3.py

@@ -63,15 +63,15 @@ j = R.adjoint_times(N.inverse_times(d))                               # define i
 
 class M_operator(operator):
 
-    def _multiply(self,x):
-        N,R = self.para
+    def _multiply(self, x):
+        N, R = self.para
         return R.adjoint_times(N.inverse_times(R.times(x)))
 
 
 C = explicify(S, newdomain=x_space, newtarget=x_space)                # explicify S
-M = M_operator(x_space,sym=True,uni=False,imp=True,para=(N,R))
+M = M_operator(x_space, sym=True, uni=False, imp=True, para=(N, R))
 M = explicify(M)                                                      # explicify M
-D = (C.inverse()+M).inverse()                                         # define information propagator
+D = (C.inverse() + M).inverse()                                       # define information propagator
 
 m = D(j)                                                              # reconstruct map
 

nifty_core.py

@@ -486,7 +486,7 @@ class _about(object): ## nifty support class for global settings
 
         """
         ## version
-        self._version = "0.6.8"
+        self._version = "0.7.0"
 
         ## switches and notifications
         self._errors = notification(default=True,ccode=notification._code)
@@ -8587,6 +8587,10 @@ class diagonal_operator(operator):
         bare entries that allow for correct interpretation of the matrix
         entries; e.g., as variance in case of an covariance operator.
 
+        The inverse applications of the diagonal operator feature a ``pseudo``
+        flag indicating if zero divison shall be ignored and return zero
+        instead of causing an error.
+
         Attributes
         ----------
         domain : space
@@ -9594,6 +9598,12 @@ class projection_operator(operator):
             Lower limit of the uniform distribution if ``random == "uni"``
             (default: 0).
 
+        Notes
+        -----
+        The application of the projection operator features a ``band`` keyword
+        specifying a single projection band (see examples) and a ``bandsup``
+        keyword specifying which projection bands to sum up.
+
         Examples
         --------
         >>> space = point_space(3)

nifty_power.py

@@ -41,7 +41,7 @@
 
 """
 from __future__ import division
-from scipy.interpolate import interp1d as ip ## conflicts with sphinx's autodoc
+from scipy.interpolate import interp1d as ip ## FIXME: conflicts with sphinx's autodoc
 #import numpy as np
 from nifty_core import *
 import smoothing as gs