Cosmetics

nifty5/domains/domain.py

@@ -27,6 +27,7 @@ from ..utilities import NiftyMetaBase
 class Domain(NiftyMetaBase()):
     """The abstract class repesenting a (structured or unstructured) domain.
     """
+
     def __init__(self):
         self._hash = None
 

nifty5/library/los_response.py

@@ -132,6 +132,7 @@ class LOSResponse(LinearOperator):
     every calling MPI task (i.e. the full LOS information has to be provided on
     every task).
     """
+
     def __init__(self, domain, starts, ends, sigmas_low=None, sigmas_up=None):
 
         super(LOSResponse, self).__init__()

nifty5/minimization/relaxed_newton.py

@@ -29,6 +29,7 @@ class RelaxedNewton(DescentMinimizer):
     The descent direction is determined by weighting the gradient at the
     current parameter position with the inverse local metric.
     """
+
     def __init__(self, controller, line_searcher=None):
         if line_searcher is None:
             line_searcher = LineSearchStrongWolfe(

nifty5/minimization/steepest_descent.py

@@ -28,5 +28,6 @@ class SteepestDescent(DescentMinimizer):
     Also known as 'gradient descent'. This algorithm simply follows the
     functional's gradient for minimization.
     """
+
     def get_descent_direction(self, energy):
         return -energy.gradient

nifty5/minimization/vl_bfgs.py

@@ -106,6 +106,7 @@ class _InformationStore(object):
     yy : numpy.ndarray
         2D circular buffer of scalar products between different elements of y.
     """
+
     def __init__(self, max_history_length, x0, gradient):
         self.max_history_length = max_history_length
         self.s = [None]*max_history_length

nifty5/models/binary_helpers.py

@@ -35,6 +35,7 @@ def _joint_position(model1, model2):
 
 class ScalarMul(Model):
     """Class representing a model multiplied by a scalar factor."""
+
     def __init__(self, factor, model):
         super(ScalarMul, self).__init__(model.position)
         # TODO -> floating
@@ -53,6 +54,7 @@ class ScalarMul(Model):
 
 class Add(Model):
     """Class representing the sum of two models."""
+
     def __init__(self, position, model1, model2):
         super(Add, self).__init__(position)
 
@@ -83,6 +85,7 @@ class Add(Model):
 
 class Mul(Model):
     """Class representing the pointwise product of two models."""
+
     def __init__(self, position, model1, model2):
         super(Mul, self).__init__(position)
 

nifty5/models/constant.py

@@ -39,6 +39,7 @@ class Constant(Model):
         - Position has no influence on value.
         - The Jacobian is a null matrix.
     """
+
     def __init__(self, position, constant):
         super(Constant, self).__init__(position)
         self._constant = constant

nifty5/models/model.py

@@ -47,6 +47,7 @@ class Model(NiftyMetaBase()):
     one automatically gets the value and Jacobian of the model. The 'at' method
     creates a new instance of the class.
     """
+
     def __init__(self, position):
         self._position = position
 

nifty5/models/multi_model.py

@@ -27,6 +27,7 @@ from .model import Model
 
 class MultiModel(Model):
     """ """
+
     def __init__(self, model, key):
         # TODO Rewrite it such that it takes a dictionary as input.
         # (just like MultiFields).

nifty5/models/variable.py

@@ -31,6 +31,7 @@ class Variable(Model):
     position : Field or MultiField
         The current position in parameter space.
     """
+
     def __init__(self, position):
         super(Variable, self).__init__(position)
 

nifty5/operators/null_operator.py

@@ -34,6 +34,7 @@ class NullOperator(LinearOperator):
     target : DomainTuple or MultiDomain
         output domain
     """
+
     def __init__(self, domain, target):
         from ..sugar import makeDomain
         self._domain = makeDomain(domain)

nifty5/operators/qht_operator.py

@@ -42,6 +42,7 @@ class QHTOperator(LinearOperator):
         The index of the domain on which the operator acts.
         target[space] must be a nonharmonic LogRGSpace.
     """
+
     def __init__(self, target, space=0):
         self._target = DomainTuple.make(target)
         self._space = infer_space(self._target, space)

nifty5/operators/scaling_operator.py

@@ -111,4 +111,4 @@ class ScalingOperator(EndomorphicOperator):
         fct = 1./np.sqrt(fct) if from_inverse else np.sqrt(fct)
         cls = Field if isinstance(self._domain, DomainTuple) else MultiField
         return cls.from_random(
-           random_type="normal", domain=self._domain, std=fct, dtype=dtype)
+            random_type="normal", domain=self._domain, std=fct, dtype=dtype)

nifty5/operators/selection_operator.py

@@ -35,6 +35,7 @@ class SelectionOperator(LinearOperator):
     key : :class:`str`
         String identifier of the wanted subdomain
     """
+
     def __init__(self, domain, key):
         self._domain = MultiDomain.make(domain)
         self._key = key

nifty5/utilities.py

@@ -89,7 +89,7 @@ def get_slice_list(shape, axes):
             slice_list = [
                 next(it_iter)
                 if axis else slice(None, None) for axis in axes_select
-                ]
+            ]
             yield slice_list
     else:
         yield [slice(None, None)]