Merge branch 'master' into fft_op

nifty/domain_object.py

@@ -17,13 +17,14 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 import abc
+from nifty.nifty_meta import NiftyMeta
 
 from keepers import Loggable,\
                     Versionable
 
 
 class DomainObject(Versionable, Loggable, object):
-    __metaclass__ = abc.ABCMeta
+    __metaclass__ = NiftyMeta
 
     def __init__(self):
         # _global_id is used in the Versioning module from keepers

nifty/energies/energy.py

@@ -16,10 +16,14 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
+from nifty.nifty_meta import NiftyMeta
+
 from keepers import Loggable
 
 
 class Energy(Loggable, object):
+    __metaclass__ = NiftyMeta
+
     def __init__(self, position):
         self._cache = {}
         try:

nifty/minimization/quasi_newton_minimizer.py

@@ -17,6 +17,7 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 import abc
+from nifty.nifty_meta import NiftyMeta
 
 import numpy as np
 
@@ -26,7 +27,7 @@ from .line_searching import LineSearchStrongWolfe
 
 
 class QuasiNewtonMinimizer(Loggable, object):
-    __metaclass__ = abc.ABCMeta
+    __metaclass__ = NiftyMeta
 
     def __init__(self, line_searcher=LineSearchStrongWolfe(), callback=None,
                  convergence_tolerance=1E-4, convergence_level=3,

nifty/nifty_meta.py

+# -*- coding: utf-8 -*-
+
+import abc
+
+
+class DocStringInheritor(type):
+    """
+    A variation on
+    http://groups.google.com/group/comp.lang.python/msg/26f7b4fcb4d66c95
+    by Paul McGuire
+    """
+    def __new__(meta, name, bases, clsdict):
+        if not('__doc__' in clsdict and clsdict['__doc__']):
+            for mro_cls in (mro_cls for base in bases
+                            for mro_cls in base.mro()):
+                doc = mro_cls.__doc__
+                if doc:
+                    clsdict['__doc__'] = doc
+                    break
+        for attr, attribute in clsdict.items():
+            if not attribute.__doc__:
+                for mro_cls in (mro_cls for base in bases
+                                for mro_cls in base.mro()
+                                if hasattr(mro_cls, attr)):
+                    doc = getattr(getattr(mro_cls, attr), '__doc__')
+                    if doc:
+                        if isinstance(attribute, property):
+                            clsdict[attr] = property(attribute.fget,
+                                                     attribute.fset,
+                                                     attribute.fdel,
+                                                     doc)
+                        else:
+                            attribute.__doc__ = doc
+                        break
+        return super(DocStringInheritor, meta).__new__(meta, name,
+                                                       bases, clsdict)
+
+
+class NiftyMeta(DocStringInheritor, abc.ABCMeta):
+    pass

nifty/operators/composed_operator/composed_operator.py

@@ -54,10 +54,6 @@ class ComposedOperator(LinearOperator):
                 self._target += op.target
         return self._target
 
-    @property
-    def implemented(self):
-        return True
-
     @property
     def unitary(self):
         return False

nifty/operators/diagonal_operator/diagonal_operator.py

@@ -30,13 +30,11 @@ class DiagonalOperator(EndomorphicOperator):
 
     # ---Overwritten properties and methods---
 
-    def __init__(self, domain=(), implemented=True,
+    def __init__(self, domain=(),
                  diagonal=None, bare=False, copy=True,
                  distribution_strategy=None):
         self._domain = self._parse_domain(domain)
 
-        self._implemented = bool(implemented)
-
         if distribution_strategy is None:
             if isinstance(diagonal, distributed_data_object):
                 distribution_strategy = diagonal.distribution_strategy
@@ -100,10 +98,6 @@ class DiagonalOperator(EndomorphicOperator):
     def domain(self):
         return self._domain
 
-    @property
-    def implemented(self):
-        return self._implemented
-
     @property
     def self_adjoint(self):
         if self._self_adjoint is None:
@@ -144,16 +138,12 @@ class DiagonalOperator(EndomorphicOperator):
                   distribution_strategy=self.distribution_strategy,
                   copy=copy)
 
-        # weight if the given values were `bare` and `implemented` is True
+        # weight if the given values were `bare` is True
         # do inverse weightening if the other way around
-        if bare and self.implemented:
+        if bare:
             # If `copy` is True, we won't change external data by weightening
             # Otherwise, inplace weightening would change the external field
             f.weight(inplace=copy)
-        elif not bare and not self.implemented:
-            # If `copy` is True, we won't change external data by weightening
-            # Otherwise, inplace weightening would change the external field
-            f.weight(inplace=copy, power=-1)
 
         # Reset the self_adjoint property:
         self._self_adjoint = None

nifty/operators/fft_operator/fft_operator.py

@@ -225,10 +225,6 @@ class FFTOperator(LinearOperator):
     def target(self):
         return self._target
 
-    @property
-    def implemented(self):
-        return True
-
     @property
     def unitary(self):
         return False

nifty/operators/linear_operator/linear_operator.py

@@ -17,6 +17,7 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 import abc
+from nifty.nifty_meta import NiftyMeta
 
 from keepers import Loggable
 from nifty.field import Field
@@ -24,7 +25,7 @@ import nifty.nifty_utilities as utilities
 
 
 class LinearOperator(Loggable, object):
-    __metaclass__ = abc.ABCMeta
+    __metaclass__ = NiftyMeta
 
     def __init__(self):
         pass
@@ -40,10 +41,6 @@ class LinearOperator(Loggable, object):
     def target(self):
         raise NotImplementedError
 
-    @abc.abstractproperty
-    def implemented(self):
-        raise NotImplementedError
-
     @abc.abstractproperty
     def unitary(self):
         raise NotImplementedError
@@ -54,9 +51,6 @@ class LinearOperator(Loggable, object):
     def times(self, x, spaces=None, **kwargs):
         spaces = self._check_input_compatibility(x, spaces)
 
-        if not self.implemented:
-            x = x.weight(spaces=spaces)
-
         y = self._times(x, spaces, **kwargs)
         return y
 
@@ -64,8 +58,6 @@ class LinearOperator(Loggable, object):
         spaces = self._check_input_compatibility(x, spaces, inverse=True)
 
         y = self._inverse_times(x, spaces, **kwargs)
-        if not self.implemented:
-            y = y.weight(power=-1, spaces=spaces)
         return y
 
     def adjoint_times(self, x, spaces=None, **kwargs):
@@ -74,8 +66,6 @@ class LinearOperator(Loggable, object):
 
         spaces = self._check_input_compatibility(x, spaces, inverse=True)
 
-        if not self.implemented:
-            x = x.weight(spaces=spaces)
         y = self._adjoint_times(x, spaces, **kwargs)
         return y
 
@@ -86,8 +76,6 @@ class LinearOperator(Loggable, object):
         spaces = self._check_input_compatibility(x, spaces)
 
         y = self._adjoint_inverse_times(x, spaces, **kwargs)
-        if not self.implemented:
-            y = y.weight(power=-1, spaces=spaces)
         return y
 
     def inverse_adjoint_times(self, x, spaces=None, **kwargs):
@@ -97,8 +85,6 @@ class LinearOperator(Loggable, object):
         spaces = self._check_input_compatibility(x, spaces)
 
         y = self._inverse_adjoint_times(x, spaces)
-        if not self.implemented:
-            y = y.weight(power=-1, spaces=spaces)
         return y
 
     def _times(self, x, spaces):

nifty/operators/projection_operator/projection_operator.py

@@ -101,10 +101,6 @@ class ProjectionOperator(EndomorphicOperator):
     def domain(self):
         return self._projection_field.domain
 
-    @property
-    def implemented(self):
-        return True
-
     @property
     def unitary(self):
         if self._unitary is None:

nifty/operators/propagator_operator/propagator_operator.py

@@ -74,10 +74,6 @@ class PropagatorOperator(InvertibleOperatorMixin, EndomorphicOperator):
     def domain(self):
         return self._domain
 
-    @property
-    def implemented(self):
-        return True
-
     @property
     def self_adjoint(self):
         return True

nifty/operators/smoothing_operator/smoothing_operator.py

@@ -53,10 +53,6 @@ class SmoothingOperator(EndomorphicOperator):
     def domain(self):
         return self._domain
 
-    @property
-    def implemented(self):
-        return True
-
     @property
     def self_adjoint(self):
         return True

nifty/plotting/plotly_wrapper.py

 from abc import ABCMeta, abstractmethod
+from nifty.nifty_meta import NiftyMeta
 
 
 class PlotlyWrapper(object):
-    __metaclass__ = ABCMeta
+    __metaclass__ = NiftyMeta
 
     @abstractmethod
     def to_plotly(self):

nifty/probing/prober/prober.py

@@ -16,8 +16,6 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
-import abc
-
 import numpy as np
 
 from nifty.field import Field
@@ -38,8 +36,6 @@ class Prober(object):
 
     """
 
-    __metaclass__ = abc.ABCMeta
-
     def __init__(self, domain=None, distribution_strategy=None, probe_count=8,
                  random_type='pm1', compute_variance=False):