pep8

wafo/objects.py

@@ -48,7 +48,7 @@ _wafocov_estimation = JITImport('wafo.covariance.estimation')
 _wafospec = JITImport('wafo.spectrum')
 
 __all__ = ['TimeSeries', 'LevelCrossings', 'CyclePairs', 'TurningPoints',
-           'sensortypeid', 'sensortype']
+           'CycleMatrix']
 
 
 def _invchi2(q, df):
@@ -905,7 +905,8 @@ class CyclePairs(PlotData):
 #                 for j in range(i + 1, n):  # = i+1:n
 #                     if F[i, j] != 0:
 #                         hi = h * _lamda[i, j]
-#                         F1 = np.exp(-1 / (2 * hi**2) * ((I - i)**2 + (J - j)**2))  # Gaussian kernel
+#                         # Gaussian kernel
+#                         F1 = np.exp(-1 / (2 * hi**2) * ((I - i)**2 + (J - j)**2))
 #                         F1 = F1 + F1.T                  # Mirror kernel in diagonal
 #                         F1 = np.triu(F1, 1 + NOsubzero)  # Set to zero below and on diagonal
 #                         F1 = F[i, j] * F1 / np.sum(F1)   # Normalize

wafo/spectrum/core.py

@@ -1153,7 +1153,7 @@ class SpecData1D(PlotData):
             pl = [10, 30, 50, 70, 90, 95, 99, 99.9]
             mmpdf.cl = qlevels(uvdens, pl, xi=(h, h))
             mmpdf.pl = pl
-        except:
+        except Exception:
             pass
         return mmpdf
 
@@ -1696,7 +1696,7 @@ class SpecData1D(PlotData):
         try:
             f.cl, f.pl = qlevels(f.f, [10, 30, 50, 70, 90, 95, 99, 99.9],
                                  f.args[0], f.args[1])
-        except:
+        except Exception:
             warnings.warn('Singularity likely in pdf')
 
         # Test of spec2mmtpdf
@@ -4257,6 +4257,7 @@ def test_mm_pdf():
     mm.plot()
     plotbackend.show()
 
+
 def test_docstrings():
     import doctest
     doctest.testmod()