diff --git a/pylot/core/pick/utils.py b/pylot/core/pick/utils.py
index 097863ae..166816ad 100644
--- a/pylot/core/pick/utils.py
+++ b/pylot/core/pick/utils.py
@@ -324,6 +324,9 @@ def getSNR(X, TSNR, t1):
         print 'getSNR: Empty array isignal, check signal window!'
         return
 
+    # demean over entire snr window
+    x -= x[inoise[0]:isignal[-1]].mean()
+
     # calculate ratios
     noiselevel = np.sqrt(np.mean(np.square(x[inoise])))
     signallevel = np.sqrt(np.mean(np.square(x[isignal])))
@@ -352,9 +355,8 @@ def getnoisewin(t, t1, tnoise, tgap):
     :type: float
     '''
 
-    inoise = None
     # get noise window
-    inoise = np.where((t <= max([t1 - tgap, 0])) \
+    inoise, = np.where((t <= max([t1 - tgap, 0])) \
                       & (t >= max([t1 - tnoise - tgap, 0])))
     if np.size(inoise) < 1:
         print 'getnoisewin: Empty array inoise, check noise window!'
@@ -377,9 +379,8 @@ def getsignalwin(t, t1, tsignal):
     :type: float
     '''
 
-    inoise = None
     # get signal window
-    isignal = np.where((t <= min([t1 + tsignal, len(t)])) \
+    isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \
                        & (t >= t1))
     if np.size(isignal) < 1:
         print 'getsignalwin: Empty array isignal, check signal window!'
@@ -395,8 +396,8 @@ def wadaticheck(pickdic, dttolerance, iplot):
 
     : param: pickdic, dictionary containing picks and quality parameters
     : type:  dictionary
-    
-    : param: dttolerance, maximum adjusted deviation of S-P time from 
+
+    : param: dttolerance, maximum adjusted deviation of S-P time from
              S-P time regression
     : type:  float
 
@@ -425,15 +426,15 @@ def wadaticheck(pickdic, dttolerance, iplot):
 
 
     if len(SPtimes) >= 3:
-    	# calculate slope 
+    	# calculate slope
     	p1 = np.polyfit(Ppicks, SPtimes, 1)
     	wdfit = np.polyval(p1, Ppicks)
         wfitflag = 0
-     
+
         # calculate vp/vs ratio before check
         vpvsr = p1[0] + 1
         print 'wadaticheck: Average Vp/Vs ratio before check:', vpvsr
- 
+
         checkedPpicks = []
         checkedSpicks = []
         checkedSPtimes = []
@@ -445,7 +446,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
                 ii += 1
                 # check, if deviation is larger than adjusted
                 if wddiff >= dttolerance:
-                    # mark onset and downgrade S-weight to 9 
+                    # mark onset and downgrade S-weight to 9
                     # (not used anymore)
                     marker = 'badWadatiCheck'
                     pickdic[key]['S']['weight'] = 9
@@ -461,7 +462,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
                 pickdic[key]['S']['marked'] = marker
 
 
-    	# calculate new slope 
+    	# calculate new slope
     	p2 = np.polyfit(checkedPpicks, checkedSPtimes, 1)
     	wdfit2 = np.polyval(p2, checkedPpicks)
 
@@ -470,7 +471,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
         print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr
 
         checkedonsets = pickdic
- 
+
     else:
     	print 'wadaticheck: Not enough S-P times available for reliable regression!'
         print 'Skip wadati check!'