--- a/python/poly_utils.py	Wed Apr 03 22:55:18 2013 -0400
+++ b/python/poly_utils.py	Thu Apr 18 15:29:33 2013 -0400
@@ -6,26 +6,18 @@
 import numpy as np
 
 __metaclass__ = type
+from indicators import SeverityIndicator
 
-# inputs variables	
-#dirname= 'G:/0-phdstart/Code/trial/indicatorsNew/'
-#extension= '-indicatorsNew.csv'
-#indicatorsNames= {1:'Distance',2:'Cosine',3:'collision Course Angle',4:'Velocity Cosine',5:'Velocity Angle',6:'Speed Differential',7:'Collision Probability',8:'Severity Index',9:'TTC'}
-''' min Distance case'''
-dirname= 'G:/0-phdstart/Code/trial/minDistanceIndicator/'
-extension= '-minDistanceInd.csv'
-indicatorsNames= {1:'minDistance'}
 
-def loadNewInteractions(videoFilename,interactionType, roaduserNum1,roaduserNum2, selectedIndicators=[]):
+def loadNewInteractions(videoFilename,interactionType,dirname, extension, indicatorsNames, roaduserNum1,roaduserNum2, selectedIndicators=[]):
     '''Loads interactions from the POLY traffic event format'''
     from events import Interaction 
-    from indicators import SeverityIndicator
-    #filename= dirname + videoFilename + extension
-    filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs
+    filename= dirname + videoFilename + extension
+    #filename= dirname + interactionType+ '-' + videoFilename + extension # case of min distance todo: change the saving format to be matched with all outputs
     file = utils.openCheck(filename)
     if (not file):
         return []
-    interactions = []
+    #interactions = []
     interactionNum = 0
     data= np.loadtxt(filename)
     indicatorFrameNums= data[:,0]
@@ -43,7 +35,92 @@
             values[t] = [data[i,index] for index in selectedIndicators]
         inter.addIndicator(SeverityIndicator('selectedIndicators', values))	
 		
-    interactions.append(inter)
+    #interactions.append(inter)
     file.close()
-    return interactions
+    #return interactions
+    return inter
+
+# Plotting results
+
+frameRate = 15.
+
+# To run in directory that contains the directories that contain the results (Miss-xx and Incident-xx)
+#dirname = '/home/nicolas/Research/Data/kentucky-db/'
+
+interactingRoadUsers = {'Miss/0404052336': [(0,3)] # 0,2 and 1 vs 3
+                        #,
+                        #'Incident/0306022035': [(1,3)]
+                        #,
+                        #'Miss/0208030956': [(4,5),(5,7)]
+                        }
+
+
+def getIndicatorName(filename, withUnit = False):
+    if withUnit:
+        unit = ' (s)'
+    else:
+        unit = ''
+    if 'collision-point' in filename:
+        return 'TTC'+unit
+    elif 'crossing' in filename:
+        return 'pPET'+unit
+    elif 'probability' in filename:
+        return 'P(UEA)'
+
+def getMethodName(fileprefix):
+    if fileprefix == 'constant-velocity':
+        return 'Con. Vel.'
+    elif fileprefix == 'normal-adaptation':
+        return 'Norm. Ad.'
+    elif fileprefix == 'point-set':
+        return 'Pos. Set'
+    elif fileprefix == 'evasive-action':
+        return 'Ev. Act.'
+    elif fileprefix == 'point-set-evasive-action':
+        return 'Pos. Set'
+
+indicator2TimeIdx = {'TTC':2,'pPET':2, 'P(UEA)':3}
 
+def getDataAtInstant(data, i):
+    return data[data[:,2] == i]
+
+def getPointsAtInstant(data, i):
+    return getDataAtInstant(i)[3:5]
+
+def getIndicator(data, roadUserNumbers, indicatorName):
+    if data.ndim ==1:
+        data.shape = (1,data.shape[0])
+
+    # find the order for the roadUserNumbers
+    uniqueObj1 = np.unique(data[:,0])
+    uniqueObj2 = np.unique(data[:,1])
+    found = False
+    if roadUserNumbers[0] in uniqueObj1 and roadUserNumbers[1] in uniqueObj2:
+        objNum1 = roadUserNumbers[0]
+        objNum2 = roadUserNumbers[1]
+        found = True
+    if roadUserNumbers[1] in uniqueObj1 and roadUserNumbers[0] in uniqueObj2:
+        objNum1 = roadUserNumbers[1]
+        objNum2 = roadUserNumbers[0]
+        found = True
+
+    # get subset of data for road user numbers
+    if found:
+        roadUserData = data[np.logical_and(data[:,0] == objNum1, data[:,1] == objNum2),:]
+        if roadUserData.size > 0:
+            time = np.unique(roadUserData[:,indicator2TimeIdx[indicatorName]])
+            values = {}
+            if indicatorName == 'P(UEA)':
+                tmp = roadUserData[:,4]
+                for k,v in zip(time, tmp):
+                    values[k]=v
+                return SeverityIndicator(indicatorName, values, mostSevereIsMax = False, maxValue = 1.), roadUserData
+            else:
+                for i in xrange(time[0],time[-1]+1):
+                    try:
+						tmp = getDataAtInstant(roadUserData, i)
+						values[i] = np.sum(tmp[:,5]*tmp[:,6])/np.sum(tmp[:,5])/frameRate
+                    except IOError:
+                    	values[i] = np.inf
+                return SeverityIndicator(indicatorName, values, mostSevereIsMax = False), roadUserData
+    return None, None
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