pep8

wafo/interpolate.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
 from __future__ import absolute_import, division
 import numpy as np
-import scipy.signal
 # import scipy.sparse.linalg  # @UnusedImport
 import scipy.sparse as sparse
 from numpy import ones, zeros, prod, sin, diff, pi, inf, vstack, linspace
@@ -106,12 +105,15 @@ def _get_turnpoint(xvals):
     turnpoint = 0
     last = len(xvals)
     if xvals[0] < xvals[1]:  # x is increasing?
-        compare = lambda a, b: a < b
+        def compare(a, b):
+            return a < b
     else:  # no, x is decreasing
-        compare = lambda a, b: a > b
+        def compare(a, b):
+            return a > b
 
     for i in range(1, last):  # yes
-        if compare(xvals[i], xvals[i - 1]): # search where x starts to fall or rise
+        # search where x starts to fall or rise
+        if compare(xvals[i], xvals[i - 1]):
             turnpoint = i
             break
 
@@ -245,36 +247,44 @@ def sgolay2d(z, window_size, order, derivative=None):
     Z = np.zeros((new_shape))
     # top band
     band = z[0, :]
-    Z[:half_size, half_size:-half_size] = band - np.abs(np.flipud(z[1:half_size + 1, :]) - band)
+    Z[:half_size, half_size:-half_size] = band - \
+        np.abs(np.flipud(z[1:half_size + 1, :]) - band)
     # bottom band
     band = z[-1, :]
-    Z[-half_size:, half_size:-half_size] = band + np.abs(np.flipud(z[-half_size - 1:-1, :]) - band)
+    Z[-half_size:, half_size:-half_size] = band + \
+        np.abs(np.flipud(z[-half_size - 1:-1, :]) - band)
     # left band
     band = np.tile(z[:, 0].reshape(-1, 1), [1, half_size])
-    Z[half_size:-half_size, :half_size] = band - np.abs(np.fliplr(z[:, 1:half_size + 1]) - band)
+    Z[half_size:-half_size, :half_size] = band - \
+        np.abs(np.fliplr(z[:, 1:half_size + 1]) - band)
     # right band
     band = np.tile(z[:, -1].reshape(-1, 1), [1, half_size])
-    Z[half_size:-half_size, -half_size:] = band + np.abs(np.fliplr(z[:, -half_size - 1:-1]) - band)
+    Z[half_size:-half_size, -half_size:] = band + \
+        np.abs(np.fliplr(z[:, -half_size - 1:-1]) - band)
     # central band
     Z[half_size:-half_size, half_size:-half_size] = z
 
     # top left corner
     band = z[0, 0]
     Z[:half_size, :half_size] = band - \
-        np.abs(np.flipud(np.fliplr(z[1:half_size + 1, 1:half_size + 1])) - band)
+        np.abs(
+            np.flipud(np.fliplr(z[1:half_size + 1, 1:half_size + 1])) - band)
     # bottom right corner
     band = z[-1, -1]
     Z[-half_size:, -half_size:] = band + \
-        np.abs(np.flipud(np.fliplr(z[-half_size - 1:-1, -half_size - 1:-1])) - band)
+        np.abs(
+            np.flipud(np.fliplr(z[-half_size - 1:-1, -half_size - 1:-1])) - band)
 
     # top right corner
     band = Z[half_size, -half_size:]
     Z[:half_size, -half_size:] = band - \
-        np.abs(np.flipud(Z[half_size + 1:2 * half_size + 1, -half_size:]) - band)
+        np.abs(
+            np.flipud(Z[half_size + 1:2 * half_size + 1, -half_size:]) - band)
     # bottom left corner
     band = Z[-half_size:, half_size].reshape(-1, 1)
     Z[-half_size:, :half_size] = band - \
-        np.abs(np.fliplr(Z[-half_size:, half_size + 1:2 * half_size + 1]) - band)
+        np.abs(
+            np.fliplr(Z[-half_size:, half_size + 1:2 * half_size + 1]) - band)
 
     # solve system and convolve
     sgn = {None: 1}.get(derivative, -1)
@@ -597,7 +607,8 @@ class SmoothSpline(PPform):
             di = di.T
             ci = ci.T
             ai = ai.T
-        coefs = vstack([val.ravel() for val in [di, ci, bi, ai] if val.size>0])
+        coefs = vstack([val.ravel()
+                        for val in [di, ci, bi, ai] if val.size > 0])
         return coefs
 
     def _compute_coefs(self, xx, yy, p=None, var=1):
@@ -978,6 +989,7 @@ class StinemanInterp(object):
     --------
     slopes, Pchip
     '''
+
     def __init__(self, x, y, yp=None, method='parabola', monotone=False):
         if yp is None:
             yp = slopes(x, y, method, monotone=monotone)
@@ -1214,7 +1226,6 @@ def test_smoothing_spline():
 
     plt.plot(x, y, x1, y1, '.', x1, dy1, 'ro', x1, y01, 'r-')
     plt.show('hold')
-    pass
     # tck = interpolate.splrep(x, y, s=len(x))