Changeset 1327

Timestamp:

May 6, 2014 9:23:56 AM (8 years ago)

Author:

vondreele

Message:

Better error trapping for SASD fitting LS.

Location:

trunk

Files:

• GSASIIpwdGUI.py (modified) (2 diffs)
• GSASIIsasd.py (modified) (2 diffs)

trunk/GSASIIpwdGUI.py

@@ -2793 +2793 @@
                 IInst = G2frame.PatternTree.GetItemPyData(G2gd.GetPatternTreeItemId(G2frame,Id, 'Instrument Parameters'))
 #                ISubstances = G2frame.PatternTree.GetItemPyData(G2gd.GetPatternTreeItemId(G2frame,Id, 'Substances'))
-                IfOK,result,varyList,sig,Rvals,covMatrix = G2sasd.ModelFit(IProfile,IProfDict,ILimits,ISample,IModel)
+                IfOK,result,varyList,sig,Rvals,covMatrix,Msg = G2sasd.ModelFit(IProfile,IProfDict,ILimits,ISample,IModel)
                 if not IfOK:
                     G2frame.ErrorDialog('Failed sequential refinement for data '+name,
-                        'You need to rethink your selection of parameters\n'+    \
+                        ' Msg: '+Msg+'\nYou need to rethink your selection of parameters\n'+    \
                         ' Model restored to previous version for'+name)
                     SeqResult['histNames'] = names[:i]
@@ -2831 +2831 @@
         elif data['Current'] == 'Particle fit':
             SaveState()
-            if not G2sasd.ModelFit(Profile,ProfDict,Limits,Sample,data)[0]:
-                G2frame.ErrorDialog('Failed refinement',
-                    'You need to rethink your selection of parameters\n'+    \
-                    ' Model restored to previous version')
+            Results = G2sasd.ModelFit(Profile,ProfDict,Limits,Sample,data)
+            if not Results[0]:
+                    G2frame.ErrorDialog('Failed refinement',
+                        ' Msg: '+Results[-1]+'\nYou need to rethink your selection of parameters\n'+    \
+                        ' Model restored to previous version')
             G2sasd.ModelFxn(Profile,ProfDict,Limits,Sample,data)
             RefreshPlots(True)

trunk/GSASIIsasd.py

@@ -1240 +1240 @@
     Rvals['GOF'] = chisq/(Ifin-Ibeg-len(varyList))       #reduced chi^2
     Ic[Ibeg:Ifin] = getSASD(Q[Ibeg:Ifin],levelTypes,parmDict)
+    Msg = 'Failed to converge'
     try:
+        Nans = np.isnan(result[0])
+        if np.any(Nans):
+            name = varyList[Nans.nonzero(True)[0]]
+            Msg = 'Nan result for '+name+'!'
+            raise ValueError
+        Negs = np.less_equal(result[0],0.)
+        if np.any(Negs):
+            name = varyList[Negs.nonzero(True)[0]]
+            Msg = 'negative coefficient for '+name+'!'
+            raise ValueError
         if len(covM):
             sig = np.sqrt(np.diag(covM)*Rvals['GOF'])
@@ -1249 +1260 @@
         SetModelParms()
         covMatrix = covM*Rvals['GOF']
-        return True,result,varyList,sig,Rvals,covMatrix
+        return True,result,varyList,sig,Rvals,covMatrix,''
     except (ValueError,TypeError):      #when bad LS refinement; covM missing or with nans
-        return False,0,0,0,0,0
+        return False,0,0,0,0,0,Msg
     
 def ModelFxn(Profile,ProfDict,Limits,Sample,sasdData):