--- a/python/indicators.py	Mon Jul 15 12:13:08 2013 -0400
+++ b/python/indicators.py	Mon Jul 15 15:08:53 2013 -0400
@@ -96,21 +96,6 @@
             values.append(self.values[key]) 
         return values
 
-    @staticmethod
-    def getDLCSS(indic1, indic2, threshold, delta = float('inf') , method ='min' ):
-	''' compute the distance between two indicators using LCSS
-	two common methods are used: min or mean of the indicators length'''
-        print('Deprecated: this is not appropriate method for indicator comparison')
-        l1 = indic1.valueSorted
-        l2 = indic2.valueSorted
-        DLCSS = None
-        if method == 'min':
-            DLCSS = 1- (LCSS(l1,l2, threshold, delta, distance))/min(len(l1),len(l2))
-        if method == 'mean':
-            average = len(l1)+len(l2)/2
-            DLCSS = 1- ((LCSS(l1,l2, threshold, delta, distance))/average)
-        return DLCSS
-		
 
 def distanceForLCSS(x, y): # lambda x,y:abs(x-y)
     if x == None or y == None:
@@ -123,7 +108,7 @@
     ''' compute the LCSS between two indicators using LCSS'''
     from utils import LCSS
     if indicator1 and indicator2:
-        return LCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta)
+        return LCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta)
     else:
         return 0
 
@@ -132,21 +117,24 @@
     ie, the LCSS divided by the min or mean of the indicator lengths'''
     from utils import normalizedLCSS
     if indicator1 and indicator2:
-        return normalizedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method)
+        return normalizedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
     else:
         return 0.
 
 def computeDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min):
     ''' compute the LCSS distance between two indicators using LCSS'''
     from utils import DLCSS
-    return DLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method)
+    if indicator1 and indicator2:
+        return DLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
+    else:
+        return 1.
 
 # aligned LCSS computations
 def computeAlignedLCSS(indicator1, indicator2, threshold, delta = float('inf')):
     ''' compute the aligned LCSS between two indicators using LCSS'''
     from utils import alignedLCSS
     if indicator1 and indicator2:
-        return alignedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta)
+        return alignedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta)
     else:
         return 0
 
@@ -155,14 +143,17 @@
     ie, the LCSS divided by the min or mean of the indicator lengths'''
     from utils import normalizedAlignedLCSS
     if indicator1 and indicator2:
-        return normalizedAlignedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method)
+        return normalizedAlignedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
     else:
         return 0.
 
 def computeAlignedDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min):
     ''' compute the aligned LCSS distance between two indicators using LCSS'''
     from utils import alignedDLCSS
-    return alignedDLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method)
+    if indicator1 and indicator2:
+        return alignedDLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
+    else:
+        return 1.
 
 class SeverityIndicator(TemporalIndicator):
     '''Class for severity indicators