Formatting

nifty6/field.py

@@ -649,7 +649,6 @@ class Field(object):
         scalar
             The result of the operation.
         """
-        from .sugar import sqrt
         if self.scalar_weight() is not None:
             return self._val.std()
         return np.sqrt(self.s_var())

nifty6/library/correlated_fields.py

@@ -36,7 +36,7 @@ from ..operators.endomorphic_operator import EndomorphicOperator
 from ..operators.harmonic_operators import HarmonicTransformOperator
 from ..operators.linear_operator import LinearOperator
 from ..operators.operator import Operator
-from ..operators.simple_linear_operators import FieldAdapter, ducktape
+from ..operators.simple_linear_operators import ducktape
 from ..probing import StatCalculator
 from ..sugar import full, makeDomain, makeField, makeOp
 
@@ -410,11 +410,9 @@ class CorrelatedFieldMaker:
             raise ValueError("length of dofdex needs to match total_N")
 
         if self._total_N > 0:
-            space = 1
             N = max(dofdex) + 1
             position_space = makeDomain((UnstructuredDomain(N), position_space))
         else:
-            space = 0
             N = 0
             position_space = makeDomain(position_space)
         prefix = str(prefix)
@@ -633,9 +631,9 @@ class CorrelatedFieldMaker:
         space = space + spaces[0]
         sub_spaces = set(spaces)
         sub_spaces.remove(space)
-        #Domain containing domain[space] and domain[0] iff total_N>0
+        # Domain containing domain[space] and domain[0] iff total_N>0
         sub_dom = makeDomain([samples[0].domain[ind]
-                              for ind in (set([0,])-set(spaces))|set([space,])])
+                              for ind in (set([0])-set(spaces)) | set([space])])
         co = ContractionOperator(sub_dom, len(sub_dom)-1)
         size = co.domain.size/co.target.size
         res = 0.

nifty6/operators/chain_operator.py

@@ -148,14 +148,3 @@ class ChainOperator(LinearOperator):
             c_inp, t_op = op.simplify_for_constant_input(c_inp)
             newop = t_op if newop is None else op(newop)
         return c_inp, newop
-
-#     def draw_sample(self, from_inverse=False, dtype=np.float64):
-#         from ..sugar import from_random
-#         if len(self._ops) == 1:
-#             return self._ops[0].draw_sample(from_inverse, dtype)
-#
-#         samp = from_random(random_type="normal", domain=self._domain,
-#                            dtype=dtype)
-#         for op in self._ops:
-#             samp = op.process_sample(samp, from_inverse)
-#         return samp

nifty6/operators/energy_operators.py

@@ -29,7 +29,7 @@ from .operator import Operator
 from .sampling_enabler import SamplingEnabler
 from .sandwich_operator import SandwichOperator
 from .scaling_operator import ScalingOperator
-from .simple_linear_operators import FieldAdapter, VdotOperator
+from .simple_linear_operators import VdotOperator
 
 
 class EnergyOperator(Operator):

nifty6/operators/harmonic_operators.py

@@ -17,7 +17,7 @@
 
 import numpy as np
 
-from .. import utilities, fft
+from .. import fft, utilities
 from ..domain_tuple import DomainTuple
 from ..domains.gl_space import GLSpace
 from ..domains.lm_space import LMSpace
@@ -248,7 +248,6 @@ class SHTOperator(LinearOperator):
 
     def _apply_spherical(self, x, mode):
         axes = x.domain.axes[self._space]
-        axis = axes[0]
         v = x.val
 
         p2h = not x.domain[self._space].harmonic