Changeset 2758

Timestamp:

Mar 21, 2017 3:34:22 PM (5 years ago)

Author:

vondreele

Message:

implement L-BFGS-B and basinhopping (preliminary) minimizers for reflectometry

Location:

trunk

Files:

• GSASIIpwd.py (modified) (8 diffs)
• GSASIIpwdGUI.py (modified) (2 diffs)

trunk/GSASIIpwd.py

@@ -1914 +1914 @@
 
 def REFDRefine(Profile,ProfDict,Inst,Limits,Substances,data):
-    print 'fit REFD data'
+    print 'fit REFD data by '+data['Minimizer']
     
     def GetModelParms():
@@ -1920 +1920 @@
         varyList = []
         values = []
+        bounds = []
         for parm in ['Scale','FltBack']:
             parmDict[parm] = data[parm][0]
@@ -1925 +1926 @@
                 varyList.append(parm)
                 values.append(data[parm][0])
+                bounds.append(Bounds[parm])
         parmDict['nLayers'] = len(data['Layers'])
         for ilay,layer in enumerate(data['Layers']):
@@ -1934 +1936 @@
                     varyList.append(cid+parm)
                     values.append(layer[parm][0])
+                    bounds.append(Bounds[parm])
             parmDict[cid+'rho'] = Substances[name]['Scatt density']
             parmDict[cid+'irho'] = Substances[name].get('XImag density',0.)
-        return parmDict,varyList,values
+        return parmDict,varyList,values,bounds
     
     def SetModelParms():
@@ -1970 +1973 @@
         return M
     
+    def sumREFD(values,Q,Io,wt,parmDict,varyList):
+        parmDict.update(zip(varyList,values))
+        M = np.sqrt(wt)*(getREFD(Q,parmDict)-Io)
+        return np.sum(M**2)
+    
     def getREFD(Q,parmDict):
         Ic = np.ones_like(Q)*parmDict['FltBack']
@@ -1995 +2003 @@
     Ifin = np.searchsorted(Q,Qmax)+1    #include last point
     Ic[:] = 0
-    parmDict,varyList,values = GetModelParms()
+    Bounds = {'Scale':[data['Scale'][0]*.85,data['Scale'][0]/.85],'FltBack':[None,None],'DenMul':[0.,None],'Thick':[1.,None],'Rough':[0.,None]}
+    parmDict,varyList,values,bounds = GetModelParms()
+    Msg = 'Failed to converge'
     if varyList:
-        result = so.leastsq(calcREFD,values,full_output=True,epsfcn=1.e-8,   #ftol=Ftol,
-            args=(Q[Ibeg:Ifin],Io[Ibeg:Ifin],wtFactor*wt[Ibeg:Ifin],parmDict,varyList))
-        parmDict.update(zip(varyList,result[0]))
-        chisq = np.sum(result[2]['fvec']**2)
-        ncalc = result[2]['nfev']
-        covM = result[1]
+        if data['Minimizer'] == 'LMLS': 
+            result = so.leastsq(calcREFD,values,full_output=True,epsfcn=1.e-8,   #ftol=Ftol,
+                args=(Q[Ibeg:Ifin],Io[Ibeg:Ifin],wtFactor*wt[Ibeg:Ifin],parmDict,varyList))
+            parmDict.update(zip(varyList,result[0]))
+            chisq = np.sum(result[2]['fvec']**2)
+            ncalc = result[2]['nfev']
+            covM = result[1]
+            newVals = result[0]
+        elif data['Minimizer'] == 'Global':
+            result = so.basinhopping(sumREFD,values,minimizer_kwargs={'method':'L-BFGS-B',
+                'args':(Q[Ibeg:Ifin],Io[Ibeg:Ifin],wtFactor*wt[Ibeg:Ifin],parmDict,varyList)})
+            chisq = result.fun
+            ncalc = result.nfev
+            newVals = result.x
+            covM = []
+        elif data['Minimizer'] == 'L-BFGS-B':
+            result = so.minimize(sumREFD,values,method='L-BFGS-B',bounds=bounds,   #ftol=Ftol,
+                args=(Q[Ibeg:Ifin],Io[Ibeg:Ifin],wtFactor*wt[Ibeg:Ifin],parmDict,varyList))
+            parmDict.update(zip(varyList,result['x']))
+            chisq = result.fun
+            ncalc = result.nfev
+            newVals = result.x
+            covM = []
     else:   #nothing varied
         M = calcREFD(values,Q[Ibeg:Ifin],Io[Ibeg:Ifin],wtFactor*wt[Ibeg:Ifin],parmDict,varyList)
@@ -2016 +2043 @@
     Ic[Ibeg:Ifin] = getREFD(Q[Ibeg:Ifin],parmDict)
     Ib[Ibeg:Ifin] = parmDict['FltBack']
-    Msg = 'Failed to converge'
     try:
-        Nans = np.isnan(result[0])
+        if not len(varyList):
+            Msg += ' - nothing refined'
+            raise ValueError
+        Nans = np.isnan(newVals)
         if np.any(Nans):
             name = varyList[Nans.nonzero(True)[0]]
             Msg += ' Nan result for '+name+'!'
             raise ValueError
-        Negs = np.less_equal(result[0],0.)
+        Negs = np.less_equal(newVals,0.)
         if np.any(Negs):
             indx = Negs.nonzero()
@@ -2032 +2061 @@
         if len(covM):
             sig = np.sqrt(np.diag(covM)*Rvals['GOF'])
-            sigDict = dict(zip(varyList,sig))
+            covMatrix = covM*Rvals['GOF']
+        else:
+            sig = np.zeros(len(varyList))
+            covMatrix = []
+        sigDict = dict(zip(varyList,sig))
         print ' Results of reflectometry data modelling fit:'
         print 'Number of function calls:',ncalc,' Number of observations: ',Ifin-Ibeg,' Number of parameters: ',len(varyList)
         print 'Rwp = %7.2f%%, chi**2 = %12.6g, reduced chi**2 = %6.2f'%(Rvals['Rwp'],chisq,Rvals['GOF'])
         SetModelParms()
-        covMatrix = covM*Rvals['GOF']
         return True,result,varyList,sig,Rvals,covMatrix,parmDict,''
     except (ValueError,TypeError):      #when bad LS refinement; covM missing or with nans

trunk/GSASIIpwdGUI.py

@@ -4760 +4760 @@
         minimiz = wx.BoxSizer(wx.HORIZONTAL)
         minimiz.Add(wx.StaticText(G2frame.dataDisplay,label=' Minimizer: '),0,WACV)
-        minlist = ['LMLS','Global','BFGS',]
+        minlist = ['LMLS','Global','L-BFGS-B',]
         minSel = wx.ComboBox(G2frame.dataDisplay,value=data['Minimizer'],choices=minlist,
             style=wx.CB_READONLY|wx.CB_DROPDOWN)
@@ -4841 +4841 @@
             if invalid:
                 return
-            G2pwd.REFDModelFxn(Profile,Inst,Limits,Substances,data)
-            G2plt.PlotPatterns(G2frame,plotType='REFD')
+            wx.CallAfter(G2pwd.REFDModelFxn,Profile,Inst,Limits,Substances,data)
+            wx.CallAfter(G2plt.PlotPatterns,G2frame,plotType='REFD')
             wx.CallAfter(UpdateREFDModelsGrid,G2frame,data)