Changing weights so that deviation is returned for all distribution models

pythonScripts/cModel.py

@@ -529,15 +529,15 @@ class model:
       par=pars[parName]
       #self.get parses the units
       v=self.get(parName)["value"]
-      if par['dist']=='lognormal':
+      #if par['dist']=='lognormal':
          #this is sigma^2_lnx
-         sln2=numpy.log(par["cv"]*par["cv"]+1)
+         #sln2=numpy.log(par["cv"]*par["cv"]+1)
          #have to multiplied by value to get the derivative 
          #with respect to lnx
-         return sln2*v*v
-      else:
+         #return sln2*v*v
+      #else:
          #for Gaussian, cv is sigma/value; get sigma by value multiplication
-         return par["cv"]*par["cv"]*v*v
+      return par["cv"]*par["cv"]*v*v
 
       
    def getMax(lutSE):