FFT_tools: add spaces after commas (PEP8) except tuple assignment

diff --git a/FFT_tools.py b/FFT_tools.py
index 7eb06a773d942aa7e6bee28e6313698d3c748374..13fd5a0c9e035936aab5b035750c14690712bf66 100644 (file)
--- a/FFT_tools.py
+++ b/FFT_tools.py
@@ -73,12 +73,12 @@ def _test_rfft(xs, Xs):
     #   X[k] = SUM x[m] exp (-j 2pi km /n)
     #          m=0
     # (see http://www.tramy.us/numpybook.pdf)
-    j = _numpy.complex(0,1)
+    j = _numpy.complex(0, 1)
     n = len(xs)
     Xa = []
     for k in range(n):
         Xa.append(sum([x * _numpy.exp(-j * 2 * _numpy.pi * k * m / n)
-                       for x,m in zip(xs,range(n))]))
+                       for x,m in zip(xs, range(n))]))
         if k < len(Xs):
             if (Xs[k] - Xa[k]) / _numpy.abs(Xa[k]) >= 1e-6:
                 raise ValueError(
@@ -99,7 +99,7 @@ def _test_rfft(xs, Xs):
 
 def _test_rfft_suite():
     print('Test numpy rfft definition')
-    xs = [1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1]
+    xs = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1]
     _test_rfft(xs, _numpy.fft.rfft(xs))
 
 
@@ -173,7 +173,7 @@ def _test_unitary_rfft_parsevals(xs, freq, freqs, Xs):
 
 def _test_unitary_rfft_parsevals_suite():
     print("Test unitary rfft on Parseval's theorem")
-    xs = [1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1]
+    xs = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1]
     dt = _numpy.pi
     freqs,Xs = unitary_rfft(xs, 1.0 / dt)
     _test_unitary_rfft_parsevals(xs, 1.0 / dt, freqs, Xs)
@@ -201,7 +201,7 @@ def _test_unitary_rfft_rect(
     #_test_unitary_rfft_parsevals(x, samp_freq, freq_axis, X)
 
     # remove the phase due to our time shift
-    j = _numpy.complex(0.0,1.0)  # sqrt(-1)
+    j = _numpy.complex(0.0, 1.0)  # sqrt(-1)
     for i in range(len(freq_axis)):
         f = freq_axis[i]
         inverse_phase_shift = _numpy.exp(j * 2.0 * _numpy.pi * time_shift * f)
@@ -255,7 +255,7 @@ def _test_unitary_rfft_gaussian(
     #_test_unitary_rfft_parsevals(x, samp_freq, freq_axis, X)
 
     # remove the phase due to our time shift
-    j = _numpy.complex(0.0,1.0)  # sqrt(-1)
+    j = _numpy.complex(0.0, 1.0)  # sqrt(-1)
     for i in range(len(freq_axis)):
         f = freq_axis[i]
         inverse_phase_shift = _numpy.exp(j * 2.0 * _numpy.pi * time_shift * f)
@@ -465,7 +465,7 @@ def _gaussian2(area, mean, std, t):
 
 
 def _test_unitary_power_spectrum_gaussian(
-    area=2.5, mean=5, std=1, samp_freq=10.24 ,samples=512):
+    area=2.5, mean=5, std=1, samp_freq=10.24, samples=512):
     x = _numpy.zeros((samples,), dtype=_numpy.float)
     mean = _numpy.float(mean)
     for i in range(samples):