--- a/python/events.py	Mon Jun 29 15:47:30 2015 -0400
+++ b/python/events.py	Mon Jun 29 16:15:04 2015 -0400
@@ -192,16 +192,16 @@
             self.interactionInterval = moving.TimeInterval()
         self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[0], collisionCourseDotProducts))
         self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[1], collisionCourseAngles))
-        self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[2], distances))
+        self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[2], distances, mostSevereIsMax = False))
         self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[4], velocityAngles))
         self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[5], speedDifferentials))
 
         # if we have features, compute other indicators
         if self.roadUser1.hasFeatures() and self.roadUser2.hasFeatures():
-            minDistance={}
+            minDistances={}
             for instant in self.timeInterval:
-                minDistance[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant)
-            self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistance))
+                minDistances[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant)
+            self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistances, mostSevereIsMax = False))
 
     def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1, usePrototypes=False, route1= (-1,-1), route2=(-1,-1), prototypes={}, secondStepPrototypes={}, nMatching={}, objects=[], noiseEntryNums=[], noiseExitNums=[], minSimilarity=0.1, mostMatched=None, useDestination=True, useSpeedPrototype=True, acceptPartialLength=30, step=1):
         '''Computes all crossing and collision points at each common instant for two road users. '''

--- a/python/indicators.py	Mon Jun 29 15:47:30 2015 -0400
+++ b/python/indicators.py	Mon Jun 29 16:15:04 2015 -0400
@@ -2,6 +2,10 @@
 '''Class for indicators, temporal indicators, and safety indicators'''
 
 import moving
+#import matplotlib.nxutils as nx
+from matplotlib.pyplot import plot, ylim
+from matplotlib.pylab import find
+from numpy import array, arange, mean, floor, mean
 
 
 # need for a class representing the indicators, their units, how to print them in graphs...
@@ -74,7 +78,6 @@
         return [self.__getitem__(t) for t in self.timeInterval]
 
     def plot(self, options = '', xfactor = 1., yfactor = 1., timeShift = 0, **kwargs):
-        from matplotlib.pylab import plot,ylim
         if self.getTimeInterval().length() == 1:
             marker = 'o'
         else:
@@ -141,9 +144,6 @@
         self.mostSevereIsMax = mostSevereIsMax
 
     def getMostSevereValue(self, minNInstants=1): # TODO use np.percentile
-        from matplotlib.mlab import find
-        from numpy.core.multiarray import array
-        from numpy.core.fromnumeric import mean
         values = array(self.values.values())
         indices = range(len(values))
         if len(indices) >= minNInstants:
@@ -163,7 +163,6 @@
 
     ex: speeds and trajectory'''
 
-    from numpy import floor, mean
     assert len(indicatorValues) == trajectory.length()
     indicatorMap = {}
     for k in xrange(trajectory.length()):
@@ -178,28 +177,22 @@
         indicatorMap[k] = mean(indicatorMap[k])
     return indicatorMap
 
-def indicatorMapFromPolygon(value, polygon, squareSize):
-    '''Fills an indicator map with the value within the polygon
-    (array of Nx2 coordinates of the polygon vertices)'''
-    import matplotlib.nxutils as nx
-    from numpy.core.multiarray import array, arange
-    from numpy import floor
-
-    points = []
-    for x in arange(min(polygon[:,0])+squareSize/2, max(polygon[:,0]), squareSize):
-        for y in arange(min(polygon[:,1])+squareSize/2, max(polygon[:,1]), squareSize):
-            points.append([x,y])
-    inside = nx.points_inside_poly(array(points), polygon)
-    indicatorMap = {}
-    for i in xrange(len(inside)):
-        if inside[i]:
-            indicatorMap[(floor(points[i][0]/squareSize), floor(points[i][1]/squareSize))] = 0
-    return indicatorMap
+# def indicatorMapFromPolygon(value, polygon, squareSize):
+#     '''Fills an indicator map with the value within the polygon
+#     (array of Nx2 coordinates of the polygon vertices)'''
+#     points = []
+#     for x in arange(min(polygon[:,0])+squareSize/2, max(polygon[:,0]), squareSize):
+#         for y in arange(min(polygon[:,1])+squareSize/2, max(polygon[:,1]), squareSize):
+#             points.append([x,y])
+#     inside = nx.points_inside_poly(array(points), polygon)
+#     indicatorMap = {}
+#     for i in xrange(len(inside)):
+#         if inside[i]:
+#             indicatorMap[(floor(points[i][0]/squareSize), floor(points[i][1]/squareSize))] = 0
+#     return indicatorMap
 
 def indicatorMapFromAxis(value, limits, squareSize):
     '''axis = [xmin, xmax, ymin, ymax] '''
-    from numpy.core.multiarray import arange
-    from numpy import floor
     indicatorMap = {}
     for x in arange(limits[0], limits[1], squareSize):
         for y in arange(limits[2], limits[3], squareSize):
@@ -210,7 +203,6 @@
     '''Puts many indicator maps together 
     (averaging the values in each cell 
     if more than one maps has a value)'''
-    #from numpy import mean
     indicatorMap = {}
     for m in maps:
         for k,v in m.iteritems():