no more abc

nifty5/domains/domain.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 from ..compat import *
 from ..utilities import NiftyMetaBase
 
@@ -31,7 +29,6 @@ class Domain(NiftyMetaBase()):
     def __init__(self):
         self._hash = None
 
-    @abc.abstractmethod
     def __repr__(self):
         raise NotImplementedError
 
@@ -84,7 +81,7 @@ class Domain(NiftyMetaBase()):
         """Returns the opposite of :meth:`.__eq__()`"""
         return not self.__eq__(x)
 
-    @abc.abstractproperty
+    @property
     def shape(self):
         """tuple of int: number of pixels along each axis
 
@@ -103,7 +100,7 @@ class Domain(NiftyMetaBase()):
         from ..dobj import local_shape
         return local_shape(self.shape)
 
-    @abc.abstractproperty
+    @property
     def size(self):
         """int: total number of pixels.
 

nifty5/domains/structured_domain.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 import numpy as np
 
 from ..compat import *
@@ -34,7 +32,7 @@ class StructuredDomain(Domain):
     are needed for power spectrum analysis and smoothing.
     """
 
-    @abc.abstractproperty
+    @property
     def scalar_dvol(self):
         """float or None : uniform cell volume, if applicable
 
@@ -63,7 +61,7 @@ class StructuredDomain(Domain):
         tmp = self.dvol
         return self.size * tmp if np.isscalar(tmp) else np.sum(tmp)
 
-    @abc.abstractproperty
+    @property
     def harmonic(self):
         """bool : True iff this domain is a harmonic domain."""
         raise NotImplementedError

nifty5/minimization/descent_minimizer.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 from ..compat import *
 from ..logger import logger
 from .line_search_strong_wolfe import LineSearchStrongWolfe
@@ -108,7 +106,6 @@ class DescentMinimizer(Minimizer):
     def reset(self):
         pass
 
-    @abc.abstractmethod
     def get_descent_direction(self, energy):
         """ Calculates the next descent direction.
 

nifty5/minimization/iteration_controller.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 from ..compat import *
 from ..utilities import NiftyMetaBase
 
@@ -44,7 +42,6 @@ class IterationController(NiftyMetaBase()):
 
     CONVERGED, CONTINUE, ERROR = list(range(3))
 
-    @abc.abstractmethod
     def start(self, energy):
         """Starts the iteration.
 
@@ -59,7 +56,6 @@ class IterationController(NiftyMetaBase()):
         """
         raise NotImplementedError
 
-    @abc.abstractmethod
     def check(self, energy):
         """Checks the state of the iteration. Called after every step.
 

nifty5/minimization/line_search.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 from ..compat import *
 from ..utilities import NiftyMetaBase
 
@@ -37,7 +35,6 @@ class LineSearch(NiftyMetaBase()):
     def __init__(self, preferred_initial_step_size=None):
         self.preferred_initial_step_size = preferred_initial_step_size
 
-    @abc.abstractmethod
     def perform_line_search(self, energy, pk, f_k_minus_1=None):
         """Find step size and advance.
 

nifty5/minimization/minimizer.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 from ..compat import *
 from ..utilities import NiftyMetaBase
 
@@ -28,7 +26,6 @@ class Minimizer(NiftyMetaBase()):
     """ A base class used by all minimizers."""
 
     # MR FIXME: the docstring is partially ignored by Sphinx. Why?
-    @abc.abstractmethod
     def __call__(self, energy, preconditioner=None):
         """ Performs the minimization of the provided Energy functional.
 

nifty5/operators/linear_operator.py

@@ -18,8 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
-
 import numpy as np
 
 from ..compat import *
@@ -179,7 +177,7 @@ class LinearOperator(Operator):
         other = self._toOperator(other, self.domain)
         return SumOperator.make([other, self], [False, True])
 
-    @abc.abstractproperty
+    @property
     def capability(self):
         """int : the supported operation modes
 
@@ -189,7 +187,6 @@ class LinearOperator(Operator):
         """
         raise NotImplementedError
 
-    @abc.abstractmethod
     def apply(self, x, mode):
         """ Applies the Operator to a given `x`, in a specified `mode`.
 

nifty5/operators/operator.py

 from __future__ import absolute_import, division, print_function
-import abc
 
 from ..compat import *
 from ..utilities import NiftyMetaBase
@@ -10,14 +9,14 @@ class Operator(NiftyMetaBase()):
     domain, and can also provide the Jacobian.
     """
 
-    @abc.abstractproperty
+    @property
     def domain(self):
         """DomainTuple or MultiDomain : the operator's input domain
 
             The domain on which the Operator's input Field lives."""
         raise NotImplementedError
 
-    @abc.abstractproperty
+    @property
     def target(self):
         """DomainTuple or MultiDomain : the operator's output domain
 
@@ -157,3 +156,46 @@ class _OpSum(_CombinedOperator):
 
     def __call__(self, x):
         raise NotImplementedError
+
+
+class SquaredNormOperator(Operator):
+    def __init__(self, domain):
+        super(SquaredNormOperator, self).__init__()
+        self._domain = domain
+        self._target = DomainTuple.scalar_domain()
+
+    @property
+    def domain(self):
+        return self._domain
+
+    @property
+    def target(self):
+        return self._target
+
+    def __call__(self, x):
+        return Field(self._target, x.vdot(x))
+
+
+class QuadraticFormOperator(Operator):
+    def __init__(self, op):
+        from .endomorphic_operator import EndomorphicOperator
+        super(QuadraticFormOperator, self).__init__()
+        if not isinstance(op, EndomorphicOperator):
+            raise TypeError("op must be an EndomorphicOperator")
+        self._op = op
+        self._target = DomainTuple.scalar_domain()
+
+    @property
+    def domain(self):
+        return self._op.domain
+
+    @property
+    def target(self):
+        return self._target
+
+    def __call__(self, x):
+        if isinstance(x, Linearization):
+            jac = self._op(x)
+            val = Field(self._target, 0.5 * x.vdot(jac))
+            return Linearization(val, jac)
+        return Field(self._target, 0.5 * x.vdot(self._op(x)))

nifty5/operators/relaxed_sum_operator.py

@@ -39,6 +39,12 @@ class RelaxedSumOperator(LinearOperator):
         self._capability = self.TIMES | self.ADJOINT_TIMES
         for op in ops:
             self._capability &= op.capability
+        #self._ops = []
+        #for op in ops:
+        #    if isinstance(op, RelaxedSumOperator):
+        #        self._ops += op._ops
+        #    else:
+        #        self._ops += [op]
 
     @property
     def domain(self):

nifty5/operators/vdot_operator.py

@@ -24,6 +24,7 @@ from ..compat import *
 from ..domain_tuple import DomainTuple
 from ..domains.unstructured_domain import UnstructuredDomain
 from .linear_operator import LinearOperator
+from .endomorphic_operator import EndomorphicOperator
 from ..sugar import full
 from ..field import Field
 
@@ -76,3 +77,39 @@ class SumReductionOperator(LinearOperator):
         if mode == self.TIMES:
             return Field(self._target, x.sum())
         return full(self._domain, x.local_data[()])
+
+
+class ConjugationOperator(EndomorphicOperator):
+    def __init__(self, domain):
+        super(ConjugationOperator, self).__init__()
+        self._domain = domain
+
+    @property
+    def domain(self):
+        return self._domain
+
+    @property
+    def capability(self):
+        return self._all_ops
+
+    def apply(self, x, mode):
+        self._check_input(x, mode)
+        return x.conjugate()
+
+
+class Realizer(EndomorphicOperator):
+    def __init__(self, domain):
+        super(Realizer, self).__init__()
+        self._domain = domain
+
+    @property
+    def domain(self):
+        return self._domain
+
+    @property
+    def capability(self):
+        return self.TIMES | self.ADJOINT_TIMES
+
+    def apply(self, x, mode):
+        self._check_input(x, mode)
+        return x.real

nifty5/utilities.py

@@ -18,7 +18,6 @@
 
 from __future__ import absolute_import, division, print_function
 
-import abc
 import collections
 from itertools import product
 
@@ -178,7 +177,7 @@ class _DocStringInheritor(type):
                                                         bases, clsdict)
 
 
-class NiftyMeta(_DocStringInheritor, abc.ABCMeta):
+class NiftyMeta(_DocStringInheritor):
     pass