flake8 fixes

Author: pancetta

pySDC/implementations/problem_classes/AllenCahn_MPIFFT.py

@@ -55,7 +55,8 @@ def __init__(self, problem_params, dtype_u=mesh, dtype_f=imex_mesh):
         # Creating FFT structure
         ndim = len(problem_params['nvars'])
         axes = tuple(range(ndim))
-        self.fft = PFFT(problem_params['comm'], list(problem_params['nvars']), axes=axes, dtype=np.float64, collapse=True)
+        self.fft = PFFT(problem_params['comm'], list(problem_params['nvars']), axes=axes, dtype=np.float64,
+                        collapse=True)
 
         # get test data to figure out type and dimensions
         tmp_u = newDistArray(self.fft, problem_params['spectral'])

pySDC/implementations/problem_classes/AllenCahn_Temp_MPIFFT.py

@@ -54,7 +54,8 @@ def __init__(self, problem_params, dtype_u=mesh, dtype_f=imex_mesh):
         # creating FFT structure
         ndim = len(problem_params['nvars'])
         axes = tuple(range(ndim))
-        self.fft = PFFT(problem_params['comm'], list(problem_params['nvars']), axes=axes, dtype=np.float64, collapse=True)
+        self.fft = PFFT(problem_params['comm'], list(problem_params['nvars']), axes=axes, dtype=np.float64,
+                        collapse=True)
 
         # get test data to figure out type and dimensions
         tmp_u = newDistArray(self.fft, problem_params['spectral'])

pySDC/implementations/problem_classes/PenningTrap_3D.py

@@ -191,10 +191,11 @@ def u_exact(self, t):
         Ip = u0[0][1] - Im
 
         # compute position in complex notation
-        w = np.complex128(Rp, Ip) * np.exp(-np.complex128(0, Op * t)) + np.complex128(Rm, Im) * np.exp(-np.complex128(0, Om * t))
+        w = np.complex128(Rp, Ip) * np.exp(-np.complex128(0, Op * t)) + np.complex128(Rm, Im) * \
+            np.exp(-np.complex128(0, Om * t))
         # compute velocity as time derivative of the position
-        dw = -1j * Op * np.complex128(Rp, Ip) * \
-            np.exp(-np.complex128(0, Op * t)) - 1j * Om * np.complex128(Rm, Im) * np.exp(-np.complex128(0, Om * t))
+        dw = -1j * Op * np.complex128(Rp, Ip) * np.exp(-np.complex128(0, Op * t)) - 1j * Om * np.complex128(Rm, Im) * \
+            np.exp(-np.complex128(0, Om * t))
 
         # get the appropriate real and imaginary parts
         u.pos[0, 0] = w.real