diff --git a/nifty5/data_objects/distributed_do.py b/nifty5/data_objects/distributed_do.py
index 3619e537678fbb39bbbc042510dc5a871c53a023..76d89b98dd1dcb3137029159ed676b70b562de36 100644
--- a/nifty5/data_objects/distributed_do.py
+++ b/nifty5/data_objects/distributed_do.py
@@ -264,7 +264,7 @@ def empty_like(a, dtype=None):
 
 def vdot(a, b):
     tmp = np.array(np.vdot(a._data, b._data))
-    if a._distaxis==-1:
+    if a._distaxis == -1:
         return tmp[()]
     res = np.empty((), dtype=tmp.dtype)
     _comm.Allreduce(tmp, res, MPI.SUM)
diff --git a/nifty5/extra/energy_and_model_tests.py b/nifty5/extra/energy_and_model_tests.py
index 074db220f100352825cfe068ff6630364c36d0b2..69e6695a7808b2d5cd9a7037875a89c582cb6c5d 100644
--- a/nifty5/extra/energy_and_model_tests.py
+++ b/nifty5/extra/energy_and_model_tests.py
@@ -93,8 +93,8 @@ def check_value_gradient_metric_consistency(op, loc, tol=1e-8, ntries=100):
             dgrad2 = (lin2.gradient-lin.gradient)/dirnorm
             xtol = tol * dirder.norm() / np.sqrt(dirder.size)
             if ((abs(numgrad-dirder) <= xtol).all() and
-                (abs(dgrad-dgrad2) <= xtol).all()):
-                    break
+                    (abs(dgrad-dgrad2) <= xtol).all()):
+                break
             dir = dir*0.5
             dirnorm *= 0.5
             loc2 = locmid
diff --git a/nifty5/field.py b/nifty5/field.py
index 815012127ca79e28277da7f7d3f3ccbc65562e2f..8e05ec9da0472fa4d9f144b746e136a4a5a57fcd 100644
--- a/nifty5/field.py
+++ b/nifty5/field.py
@@ -621,6 +621,7 @@ class Field(object):
     def positive_tanh(self):
         return 0.5*(1.+self.tanh())
 
+
 for op in ["__add__", "__radd__",
            "__sub__", "__rsub__",
            "__mul__", "__rmul__",
diff --git a/nifty5/library/amplitude_model.py b/nifty5/library/amplitude_model.py
index a7cadadccc20a1f83c855b3a7edaf6410108577c..ef53fe22101a5474b0a269da5300caeedd32b471 100644
--- a/nifty5/library/amplitude_model.py
+++ b/nifty5/library/amplitude_model.py
@@ -100,7 +100,7 @@ class AmplitudeModel(Operator):
     im, iv : y-intercept_mean, y-intercept_variance  of power_slope
     '''
     def __init__(self, s_space, Npixdof, ceps_a, ceps_k, sm, sv, im, iv,
-                         keys=['tau', 'phi']):
+                 keys=['tau', 'phi']):
         from ..operators.exp_transform import ExpTransform
         from ..operators.qht_operator import QHTOperator
         from ..operators.slope_operator import SlopeOperator
@@ -119,9 +119,11 @@ class AmplitudeModel(Operator):
         phi_sig = np.array([sv, iv])
 
         self._slope = SlopeOperator(param_space, logk_space, phi_sig)
-        self._norm_phi_mean = Field.from_global_data(param_space, phi_mean/phi_sig)
+        self._norm_phi_mean = Field.from_global_data(param_space,
+                                                     phi_mean/phi_sig)
 
-        self._domain = MultiDomain.make({keys[0]: dof_space, keys[1]: param_space})
+        self._domain = MultiDomain.make({keys[0]: dof_space,
+                                         keys[1]: param_space})
 
         kern = lambda k: _ceps_kernel(dof_space, k, ceps_a, ceps_k)
         cepstrum = create_cepstrum_amplitude_field(dof_space, kern)
diff --git a/nifty5/linearization.py b/nifty5/linearization.py
index dcc9fe5184c562d5f65bad1c2f2d0e4b186d301a..f1584aed87dabda4997aef5061cf3d2d96819d2a 100644
--- a/nifty5/linearization.py
+++ b/nifty5/linearization.py
@@ -47,8 +47,9 @@ class Linearization(object):
         return Linearization(self._val[name], FieldAdapter(dom, name))
 
     def __neg__(self):
-        return Linearization(-self._val, self._jac*(-1),
-                             None if self._metric is None else self._metric*(-1))
+        return Linearization(
+            -self._val, self._jac*(-1),
+            None if self._metric is None else self._metric*(-1))
 
     def __add__(self, other):
         if isinstance(other, Linearization):
@@ -77,8 +78,9 @@ class Linearization(object):
         if isinstance(other, Linearization):
             d1 = makeOp(self._val)
             d2 = makeOp(other._val)
-            return Linearization(self._val*other._val,
-                                 RelaxedSumOperator((d2*self._jac, d1*other._jac)))
+            return Linearization(
+                self._val*other._val,
+                RelaxedSumOperator((d2*self._jac, d1*other._jac)))
         if isinstance(other, (int, float, complex)):
             # if other == 0:
             #     return ...
@@ -100,8 +102,8 @@ class Linearization(object):
     def sum(self):
         from .sugar import full
         from .operators.vdot_operator import VdotOperator
-        return Linearization(full((),self._val.sum()),
-                             VdotOperator(full(self._jac.target,1))*self._jac)
+        return Linearization(full((), self._val.sum()),
+                             VdotOperator(full(self._jac.target, 1))*self._jac)
 
     def exp(self):
         tmp = self._val.exp()
@@ -132,4 +134,3 @@ class Linearization(object):
     def make_const(field):
         from .operators.null_operator import NullOperator
         return Linearization(field, NullOperator({}, field.domain))
-