--- a/python/pavement.py	Wed Feb 19 16:30:45 2014 -0500
+++ b/python/pavement.py	Wed Feb 19 16:33:49 2014 -0500
@@ -140,11 +140,12 @@
 
     return (somme_eau, somme_neige, neigeMTQ_sup_seuil, somme_abrasif, somme_sel, somme_lc, somme_lrg, somme_lrd, premiere_neige, autres_abrasifs)
 
-def ecWeatherIndicators(data, startDate, endDate, snowThreshold, minProportionMeasures = 0.):
+def ecWeatherIndicators(data, startDate, endDate, snowThreshold, datatype, minProportionMeasures = 0.):
     '''Computes the indicators from Environment Canada files
     (loaded as a recarray using csv2rec in data),
     between start and end dates (datetime.datetime objects)
 
+    dataType is to indicate Environnement Canada data ('ec') or else MTQ
     minProportionMeasures is proportion of measures necessary to consider the indicators'''
     from matplotlib.mlab import find
     nbre_jours_T_negatif,nbre_jours_gel_degel,pluie_tot,neige_tot,ecart_type_T = 0,0,0,0,0
@@ -156,27 +157,30 @@
     nDays = (endDate - startDate).days+1
     if startIndex.size != 0:
         for i in range(startIndex, startIndex+int(nDays)):
-            if data['tmax'][i] != '' and data['tmax'][i] != None:
-                tmax = float(data['tmax'][i].replace(',','.'))
+            if not np.isnan(data['tmax'][i]):
+                tmax = data['tmax'][i]            
             else:
                 tmax = None
-            if data['tmin'][i] != '' and data['tmin'][i] != None:
-                tmin = float(data['tmin'][i].replace(',','.'))
-            if data['pluie_tot'][i] != '' and data['pluie_tot'][i] != None:
-                pluie_tot  += float(data['pluie_tot'][i].replace(',','.'))
-            if data['neige_tot'][i] != '' and data['neige_tot'][i] != None:
-                neige_tot  += float(data['neige_tot'][i].replace(',','.'))
+            if not np.isnan(data['tmin'][i]):
+                tmin = data['tmin'][i]
+            else:
+                tmin = None
+            if datatype == 'ec':
+                if data['pluie_tot'][i] != None and not np.isnan(data['pluie_tot'][i]):
+                    pluie_tot  += data['pluie_tot'][i]
+                if data['neige_tot'][i] != None and not np.isnan(data['neige_tot'][i]):
+                    neige_tot  += data['neige_tot'][i]
             if tmax != None:
                 if tmax < 0:
                     nbre_jours_T_negatif += 1
-            if tmax != None and data['tmin'][i] != '' and data['tmin'][i] != None:
+            if tmax != None and tmin != None:
                 if tmax > 0 and tmin < 0:
                     nbre_jours_gel_degel += 1
                 for l in range(len(seuils_T)):
                     if tmax - tmin >=seuils_T[l]:
                         deltas_T[l] += 1
-            if data['tmoy'][i] != '' and data['tmoy'][i] != None:
-                tmoys.append(float(data['tmoy'][i].replace(',','.')))
+            if not np.isnan(data['tmoy'][i]):
+                tmoys.append(data['tmoy'][i])
             if tmax != None:
                 if tmax < 0:
                     compteur += 1
@@ -186,7 +190,7 @@
                 else:
                     compteur = 0
             nbre_jours_gel_consecutifs = max(nbre_jours_gel_consecutifs,compteur)
-    if float(len(tmoys))/nDays >= minProportionMeasures:
+    if len(tmoys) > 0 and float(len(tmoys))/nDays >= minProportionMeasures:
         if tmoys != []:
             ecart_type_T = np.std(tmoys)
         else: