Simplified delete_text_object

wafo/graphutil.py

@@ -43,22 +43,17 @@ def delete_text_object(gidtxt, figure=None, axis=None, verbose=False):
     def lmatchfun(x):
         return _matchfun(x, gidtxt)
 
-    objs = axis.findobj(lmatchfun)
+    for handle in [axis, figure]:
-    for obj in objs:
+        objs = handle.findobj(lmatchfun)
-        try:
+        name = handle.__name__
-            axis.texts.remove(obj)
+        msg = "Tried to delete a non-existing {0} from {1}".format(gidtxt,
-        except:
+                                                                   name)
-            if verbose:
+        for obj in objs:
-                warnings.warn(
+            try:
-                    'Tried to delete a non-existing %s from axis' % gidtxt)
+                handle.texts.remove(obj)
-    objs = figure.findobj(lmatchfun)
+            except:
-    for obj in objs:
+                if verbose:
-        try:
+                    warnings.warn(msg)
-            figure.texts.remove(obj)
-        except:
-            if verbose:
-                warnings.warn(
-                    'Tried to delete a non-existing %s from figure' % gidtxt)
 
 
 def cltext(levels, percent=False, n=4, xs=0.036, ys=0.94, zs=0, figure=None,

wafo/sg_filter.py

@@ -464,7 +464,8 @@ class _Filter(object):
         # Search the smoothing parameter s that minimizes the GCV score
         s = 10.0 ** p
         Gamma = self.gamma(s)
-        if aow > 0.9:  # aow = 1 means that all of the data are equally weighted
+        if aow > 0.9:
+            # aow = 1 means that all of the data are equally weighted
             # very much faster: does not require any inverse DCT
             residual = DCTy.ravel() * (Gamma.ravel() - 1)
         else: