more PEP8

nifty2go/nifty_utilities.py

@@ -23,6 +23,7 @@ from itertools import product
 import itertools
 from functools import reduce
 
+
 def get_slice_list(shape, axes):
     """
     Helper function which generates slice list(s) to traverse over all
@@ -111,6 +112,8 @@ def parse_domain(domain):
                 "Given object contains something that is not an "
                 "instance of DomainObject-class.")
     return domain
+
+
 def slicing_generator(shape, axes):
     """
     Helper function which generates slice list(s) to traverse over all
@@ -154,6 +157,7 @@ def slicing_generator(shape, axes):
         yield [slice(None, None)]
         return
 
+
 def bincount_axis(obj, minlength=None, weights=None, axis=None):
     if minlength is not None:
         length = max(np.amax(obj) + 1, minlength)

nifty2go/operators/diagonal_operator/diagonal_operator.py

@@ -98,7 +98,8 @@ class DiagonalOperator(EndomorphicOperator):
                                   operation=lambda z: z.adjoint().__mul__)
 
     def _inverse_times(self, x, spaces):
-        return self._times_helper(x, spaces, operation=lambda z: z.__rtruediv__)
+        return self._times_helper(x, spaces,
+                                  operation=lambda z: z.__rtruediv__)
 
     def _adjoint_inverse_times(self, x, spaces):
         return self._times_helper(x, spaces,
@@ -221,4 +222,4 @@ class DiagonalOperator(EndomorphicOperator):
         # here the actual multiplication takes place
         local_result = operation(reshaped_local_diagonal)(x.val)
 
-        return Field (x.domain,val=local_result)
+        return Field(x.domain, val=local_result)

nifty2go/operators/fft_operator/fft_operator.py

@@ -16,8 +16,6 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-import numpy as np
-
 from ... import nifty_utilities as utilities
 from ...spaces import RGSpace,\
                       GLSpace,\

nifty2go/operators/fft_operator/transformations/rgrgtransformation.py

@@ -20,7 +20,7 @@ from __future__ import division
 import numpy as np
 from .transformation import Transformation
 from .rg_transforms import SerialFFT
-from .... import RGSpace
+
 
 class RGRGTransformation(Transformation):
 
@@ -36,7 +36,6 @@ class RGRGTransformation(Transformation):
     def unitary(self):
         return True
 
-
     def transform(self, val, axes=None):
         """
         RG -> RG transform method.

nifty2go/operators/fft_operator/transformations/slicing_transformation.py

@@ -29,7 +29,7 @@ class SlicingTransformation(Transformation):
         return_shape = np.array(val.shape)
         return_shape[list(axes)] = self.codomain.shape
         return_shape = tuple(return_shape)
-        return_val = np.empty(return_shape,dtype=val.dtype)
+        return_val = np.empty(return_shape, dtype=val.dtype)
 
         for slice_list in utilities.get_slice_list(val.shape, axes):
             return_val[slice_list] = self._transformation_of_slice(

nifty2go/operators/fft_operator/transformations/transformation.py

@@ -21,7 +21,8 @@ import abc
 from future.utils import with_metaclass
 
 
-class Transformation(with_metaclass(abc.ABCMeta, type('NewBase', (object,), {}))):
+class Transformation(with_metaclass(abc.ABCMeta,
+                                    type('NewBase', (object,), {}))):
 
     def __init__(self, domain, codomain):
         self.domain = domain

nifty2go/operators/smoothing_operator/direct_smoothing_operator.py

@@ -186,9 +186,8 @@ class DirectSmoothingOperator(EndomorphicOperator):
 
         distance_array = x.domain[spaces[0]].get_distance_array()
 
-        #MR FIXME: this causes calls of log(0.) which should probably be avoided
         if self.log_distances:
-            np.log(np.maximum(distance_array,1e-15), out=distance_array)
+            np.log(np.maximum(distance_array, 1e-15), out=distance_array)
 
         augmented_data = x.val
         augmented_distance_array = distance_array

nifty2go/operators/smoothing_operator/fft_smoothing_operator.py

@@ -62,7 +62,6 @@ class FFTSmoothingOperator(EndomorphicOperator):
         coaxes = transformed_x.domain_axes[spaces[0]]
 
         kernel = codomain.get_distance_array()
-
         kernel = codomain.get_fft_smoothing_kernel_function(self.sigma)(kernel)
 
         # now, apply the kernel to transformed_x
@@ -77,15 +76,9 @@ class FFTSmoothingOperator(EndomorphicOperator):
 
         local_transformed_x *= local_kernel
 
-        transformed_x.val=local_transformed_x
-
-        smoothed_x = transformator.adjoint_times(transformed_x,
-                                                 spaces=spaces)
-
-        result = x.copy_empty()
-        result=smoothed_x
+        transformed_x.val = local_transformed_x
 
-        return result
+        return transformator.adjoint_times(transformed_x, spaces=spaces)
 
     def _get_transformator(self, dtype):
         if dtype not in self._transformator_cache:

nifty2go/spaces/gl_space/gl_space.py

@@ -24,6 +24,7 @@ import numpy as np
 from ..space import Space
 import pyHealpix
 
+
 class GLSpace(Space):
     """
         ..                 __
@@ -177,7 +178,7 @@ class GLSpace(Space):
 
     def get_default_codomain(self):
         from .. import LMSpace
-        return LMSpace(lmax=self.nlat-1,mmax=(self.nlon-1)//2)
+        return LMSpace(lmax=self.nlat-1, mmax=(self.nlon-1)//2)
 
     def check_codomain(self, codomain):
         from .. import LMSpace

nifty2go/spaces/power_space/power_space.py

@@ -16,7 +16,6 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-import ast
 import numpy as np
 
 from ...spaces.space import Space
@@ -137,7 +136,7 @@ class PowerSpace(Space):
             temp_rho = np.bincount(temp_pindex.flatten())
             assert not np.any(temp_rho == 0), "empty bins detected"
             temp_kindex = np.bincount(temp_pindex.flatten(),
-                weights=distance_array.flatten()) / temp_rho
+                                   weights=distance_array.flatten()) / temp_rho
             self._powerIndexCache[key] = (binbounds,
                                           temp_pindex,
                                           temp_kindex,
@@ -148,7 +147,6 @@ class PowerSpace(Space):
 
     @staticmethod
     def _compute_pindex(harmonic_partner, distance_array, binbounds):
-        pindex = np.empty(distance_array.shape,dtype=np.int)
         if binbounds is None:
             binbounds = harmonic_partner.get_natural_binbounds()
         return np.searchsorted(binbounds, distance_array)

nifty2go/spaces/rg_space/rg_space.py

@@ -230,7 +230,6 @@ class RGSpace(Space):
             raise AttributeError("The grid-distances of domain and codomain "
                                  "do not match.")
 
-
     # ---Added properties and methods---
 
     @property