pep8

wafo/containers.py

@@ -523,7 +523,7 @@ def transformdata_1d(x, f, plotflag):
     transform_id = np.mod(plotflag // 10, 10)
     transform = [lambda f, x: f,
                  lambda f, x: 1 - f,
-                 lambda f, x: cumtrapz(f, x),
+                 cumtrapz(f, x),
                  lambda f, x: 1 - cumtrapz(f, x),
                  lambda f, x: np.log(f),
                  lambda f, x: np.log1p(-f),

wafo/covariance/core.py

@@ -42,7 +42,7 @@ def _set_seed(iseed):
     if iseed is not None:
         try:
             random.set_state(iseed)
-        except:
+        except Exception:
             random.seed(iseed)
 
 

wafo/dctpack.py

@@ -347,7 +347,6 @@ def shiftdim(x, n=None):
         return x.reshape(no_leading_ones(x.shape))
     elif n >= 0:
         return x.transpose(np.roll(range(x.ndim), -n))
-    else:
     return x.reshape((1,) * -n + x.shape)
 
 
@@ -405,6 +404,7 @@ def example_dct2(debug=True):
         print(out)
     return out
 
+
 if __name__ == '__main__':
     from wafo.testing import test_docstrings
     test_docstrings(__file__)

wafo/integrate.py

@@ -1053,6 +1053,8 @@ class _Gaussq(object):
 
         self._plot_final_trace()
         return val, abserr
+
+
 gaussq = _Gaussq()
 
 
@@ -1259,6 +1261,7 @@ class _Quadgr(object):
 
         return q_val, err
 
+
 quadgr = _Quadgr()
 
 

wafo/integrate_oscillating.py

@@ -55,6 +55,8 @@ class PolyBasis(object):
 
     def __call__(self, t, k):
         return t**k
+
+
 poly_basis = PolyBasis()
 
 
@@ -73,6 +75,8 @@ class ChebyshevBasis(PolyBasis):
     def __call__(self, t, k):
         c = self._coefficients(k)
         return self.eval(t, c)
+
+
 chebyshev_basis = ChebyshevBasis()
 
 

wafo/kdetools/kernels.py

@@ -325,6 +325,7 @@ class _KernelMulti(_Kernel):
     p=3;  Multivariate Tri-weight Kernel
     p=4;  Multivariate Four-weight Kernel
     """
+
     def __init__(self, r=1.0, p=1, stats=None, name=''):
         self.p = p
         super(_KernelMulti, self).__init__(r, stats, name)
@@ -342,6 +343,7 @@ class _KernelMulti(_Kernel):
         x2 = x ** 2
         return ((1.0 - x2.sum(axis=0) / r ** 2).clip(min=0.0)) ** p
 
+
 mkernel_epanechnikov = _KernelMulti(p=1, stats=_stats_epan,
                                     name='epanechnikov')
 mkernel_biweight = _KernelMulti(p=2, stats=_stats_biwe, name='biweight')
@@ -356,6 +358,7 @@ class _KernelProduct(_KernelMulti):
     p=3;  1D product Tri-weight Kernel
     p=4;  1D product Four-weight Kernel
     """
+
     def norm_factor(self, d=1, n=None):
         r = self.r
         p = self.p
@@ -368,6 +371,7 @@ class _KernelProduct(_KernelMulti):
         pdf = (1 - (x / r) ** 2).clip(min=0.0) ** self.p
         return pdf.prod(axis=0)
 
+
 mkernel_p1epanechnikov = _KernelProduct(p=1, stats=_stats_epan,
                                         name='p1epanechnikov')
 mkernel_p1biweight = _KernelProduct(p=2, stats=_stats_biwe, name='p1biweight')
@@ -383,6 +387,8 @@ class _KernelRectangular(_Kernel):
     def norm_factor(self, d=1, n=None):
         r = self.r
         return (2 * r) ** d
+
+
 mkernel_rectangular = _KernelRectangular(stats=_stats_rect)
 
 
@@ -391,6 +397,8 @@ class _KernelTriangular(_Kernel):
     def _kernel(self, x):
         pdf = (1 - np.abs(x)).clip(min=0.0)
         return pdf.prod(axis=0)
+
+
 mkernel_triangular = _KernelTriangular(stats=_stats_tria)
 
 
@@ -425,6 +433,7 @@ class _KernelGaussian(_Kernel):
                                       ) / (sqrt(pi) * (2 * sigma) ** (r + 1))
         return psi_r
 
+
 mkernel_gaussian = _KernelGaussian(r=4.0, stats=_stats_gaus)
 _GAUSS_KERNEL = mkernel_gaussian
 
@@ -437,6 +446,8 @@ class _KernelLaplace(_Kernel):
 
     def norm_factor(self, d=1, n=None):
         return 2 ** d
+
+
 mkernel_laplace = _KernelLaplace(r=7.0, stats=_stats_lapl)
 
 
@@ -445,6 +456,8 @@ class _KernelLogistic(_Kernel):
     def _kernel(self, x):
         s = exp(x)
         return np.prod(s / (s + 1) ** 2, axis=0)
+
+
 mkernel_logistic = _KernelLogistic(r=7.0, stats=_stats_logi)
 
 _MKERNEL_DICT = dict(

wafo/numba_misc.py

@@ -588,5 +588,6 @@ def findrfc_astm(tp, t=None):
     # n = len(sig_rfc)
     return sig_rfc[:n - cnr[0]]
 
+
 if __name__ == '__main__':
     pass

wafo/objects.py

@@ -613,6 +613,7 @@ class CycleMatrix(PlotData):
     """
     Container class for Cycle Matrix data objects in WAFO
     """
+
     def __init__(self, *args, **kwds):
         self.kind = kwds.pop('kind', 'min2max')
         self.sigma = kwds.pop('sigma', None)
@@ -798,15 +799,25 @@ class CyclePairs(PlotData):
 
         nx = extr[0].argmax() + 1
         levels = extr[0, 0:nx]
-        if defnr == 2:  # This are upcrossings + maxima
-            dcount = cumsum(extr[1, 0:nx]) + extr[2, 0:nx] - extr[3, 0:nx]
-        elif defnr == 4:  # This are upcrossings + minima
+
+        def _upcrossings_and_maxima(extr, nx):
+            return cumsum(extr[1, 0:nx]) + extr[2, 0:nx] - extr[3, 0:nx]
+
+        def _upcrossings_and_minima(extr, nx):
             dcount = cumsum(extr[1, 0:nx])
             dcount[nx - 1] = dcount[nx - 2]
-        elif defnr == 1:  # This are only upcrossings
-            dcount = cumsum(extr[1, 0:nx]) - extr[3, 0:nx]
-        elif defnr == 3:  # This are upcrossings + minima + maxima
-            dcount = cumsum(extr[1, 0:nx]) + extr[2, 0:nx]
+            return dcount
+
+        def _upcrossings(extr, nx):
+            return cumsum(extr[1, 0:nx]) - extr[3, 0:nx]
+
+        def _upcrossings_minima_and_maxima(extr, nx):
+            return cumsum(extr[1, 0:nx]) + extr[2, 0:nx]
+
+        dcount = {1: _upcrossings,
+                  2: _upcrossings_and_maxima,
+                  3: _upcrossings_minima_and_maxima,
+                  4: _upcrossings_and_minima}[defnr](extr, nx)
         ylab = 'Count'
         if intensity:
             dcount = dcount / self.time
@@ -1142,7 +1153,7 @@ class TurningPoints(PlotData):
         ind = findrfc(self.data, max(h, 0.0), method)
         try:
             t = self.args[ind]
-        except:
+        except Exception:
             t = ind
         mean = self.mean
         sigma = self.sigma
@@ -1386,7 +1397,8 @@ class TimeSeries(PlotData):
         '''
         if isinstance(wname, tuple):
             wname = wname[0]
-        dof = int(dict(parzen=3.71, hanning=2.67,
+        dof = int(dict(parzen=3.71,
+                       hanning=2.67,
                        bartlett=3).get(wname, np.nan) * n / L)
         Be = dict(parzen=1.33, hanning=1,
                   bartlett=1.33).get(wname, np.nan) * 2 * pi / (L * dt)
@@ -1680,7 +1692,7 @@ class TimeSeries(PlotData):
         ind = findtp(self.data, max(h, 0.0), wavetype)
         try:
             t = self.args[ind]
-        except:
+        except Exception:
             t = ind
         mean = self.data.mean()
         sigma = self.data.std()
@@ -1710,7 +1722,7 @@ class TimeSeries(PlotData):
         ind = findtc(self.data, v, wavetype)[0]
         try:
             t = self.args[ind]
-        except:
+        except Exception:
             t = ind
         mean = self.data.mean()
         sigma = self.data.std()

wafo/padua.py

@@ -284,6 +284,8 @@ class _ExampleFunctions(object):
                          s.exp_fun100, s.cos30, s.constant, s.exp_xy, s.runge,
                          s.abs_cubed, s.gauss, s.exp_inv]
         return test_function[i](x, y)
+
+
 example_functions = _ExampleFunctions()
 
 

wafo/polynomial.py

@@ -2279,7 +2279,7 @@ def chebvalnd(c, *xi):
     """
     try:
         xi = np.array(xi, copy=0)
-    except:
+    except Exception:
         raise ValueError('x, y, z are incompatible')
     chebval = np.polynomial.chebyshev.chebval
     c = chebval(xi[0], c)

wafo/sg_filter/demos.py

@@ -469,6 +469,7 @@ def demo_hodrick_on_cardioid():
              x, y, 'r.',
              xs, ys, 'k', linewidth=2)
 
+
 if __name__ == '__main__':
     from wafo.testing import test_docstrings
     test_docstrings(__file__)