bring TOFgroup up to date with main

Merge remote-tracking branch 'origin/main' into TOFgroup

Author: briantoby

GSASII/GSASIIdataGUI.py

@@ -1619,7 +1619,7 @@ def GetDefaultParms(self,rd):
                 else:
                     rd.instmsg = 'default: '+dI.defaultIparm_lbl[res]
                     inst1,inst2 = self.ReadPowderInstprm(dI.defaultIparms[res],bank,rd)
-                    if rd.instdict.get('wave'):
+                    if rd.instdict.get('wave') and 'Lam' in inst1:
                         inst1['Lam'][0] = rd.instdict.get('wave')
                         inst1['Lam'][1] = rd.instdict.get('wave')
                     return [inst1,inst2]
@@ -8317,12 +8317,16 @@ def OnMergeHKL(event):
             if newHKL[5+Super] > 0.:
                 mergeRef.append(list(newHKL))
         dlg.Destroy()
-        print(' Duplicate reflection statistics:')
+        mtext = ' Duplicate reflection statistics:'
+        print(mtext)
+        Comments.append(mtext)
         for ihkl in range(MaxN):
             try:
-                print('Ndup hkl:',ihkl+1,' Number: ',Nmerge[ihkl+1][0],' Rej:',Nmerge[ihkl+1][1])
+                mtext = 'Ndup hkl: %d Number: %d Rej: %d'%(ihkl+1,Nmerge[ihkl+1][0],Nmerge[ihkl+1][1])
             except KeyError:
-                print('Ndup hkl:',ihkl+1,' Number: ',0)
+                mtext = 'Ndup hkl: %d Number:  0'%(ihkl+1)
+            print(mtext)
+            Comments.append(mtext)
         if Super:
             mergeRef = G2mth.sortArray(G2mth.sortArray(G2mth.sortArray(G2mth.sortArray(mergeRef,3),2),1),0)
         else:
@@ -8665,6 +8669,8 @@ def OnEditMag(**args):
             Super = 0
             SuperVec = []
         refList = data[1]['RefList']
+        nRef = refList.shape[0]
+        mainSizer.Add(wx.StaticText(G2frame.dataWindow,label=' Total Nref: %d'%nRef))
         FoMax = np.max(refList.T[5+data[1].get('Super',0)])
         page = G2frame.G2plotNB.nb.GetSelection()
         tab = ''

GSASII/GSASIIddataGUI.py

@@ -940,7 +940,7 @@ def OnFixVals(event):
                 UseList[G2frame.hist]['Extinction'][2].update({'Ma':[1.0,False]})
                 UseList[G2frame.hist]['Extinction'][2].update({'Mb':[0.0,False]})
             if 'Mc' not in UseList[G2frame.hist]['Extinction'][2]:
-                UseList[G2frame.hist]['Extinction'][2].update({'Mc':[1.0,False]})
+                UseList[G2frame.hist]['Extinction'][2].update({'Mc':[0.0,False]})
         elif 'PWDR' in UseList[G2frame.hist]['Histogram']:
             if 'LeBail' not in UseList[G2frame.hist]:
                 UseList[G2frame.hist]['LeBail'] = False

GSASII/GSASIIobj.py

@@ -1433,6 +1433,8 @@ def ReInitialize(self):
         self.instdict = {} # place items here that will be transferred to the instrument parameters
         self.pwdparms = {} # place parameters that are transferred directly to the tree
                            # here (typically from an existing GPX file)
+        self.selections = []
+        self.dnames = []
 ######################################################################
 class ImportSmallAngleData(ImportBaseclass):
     '''Defines a base class for the reading of files with small angle data.

GSASII/GSASIIpwd.py

@@ -2422,6 +2422,33 @@ def errPeakPos(values,peakDsp,peakPos,peakWt,dataType,parmDict,varyList):
         else:
             return peakWt*(calcPos-peakPos)
 
+    def dervPeakPos(values,peakDsp,peakPos,peakWt,dataType,parmDict,varyList):
+        dMdv = np.zeros(shape=(len(varyList),len(peakDsp)))
+        calcPos = G2lat.getPeakPos(dataType,parmDict,peakDsp)
+        if dataType[2] in ['A','B','C']:
+            const = 0.18/(np.pi*parmDict['radius'])
+        for iv,vary in enumerate(varyList):
+            if vary == 'Zero':
+                dMdv[iv,:] = 1.0
+            if vary == 'DisplaceX':
+                dMdv[iv,:] = -const*npcosd(calcPos)
+            if vary == 'DisplaceY':
+                dMdv[iv,:] = -const*npsind(calcPos)
+            if vary == 'Shift':
+                dMdv[iv,:] = -const*npcosd(calcPos/2.0)
+            if vary == 'Lam':
+                dpr = 180./np.pi
+                k = 1.0-parmDict['Lam']**2/(4.0*peakDsp**2)
+                k = dpr/np.sqrt(k)
+                dMdv[iv,:] = k/peakDsp
+            if vary == 'DifC':
+                dMdv[iv,:] = peakDsp
+            if vary == 'DifA':
+                dMdv[iv,:] = peakDsp**2
+            if vary == 'DifB':
+                dMdv[iv,:] = 1.0/peakDsp
+        return np.sqrt(peakWt)*dMdv                 
+
     def errPeakAlp(values,peakDsp,peakAlp,peakWt,dataType,parmDict,varyList):
         parmDict.update(dict(zip(varyList,values)))
         if dataType[2] in ['A','B']:
@@ -2431,6 +2458,19 @@ def errPeakAlp(values,peakDsp,peakAlp,peakWt,dataType,parmDict,varyList):
             calcAlp = parmDict['alpha']/peakDsp
         return peakWt*(calcAlp-peakAlp)
 
+    def dervPeakAlp(values,peakDsp,peakAlp,peakWt,dataType,parmDict,varyList):
+        dMdv = np.zeros(shape=(len(varyList),len(peakDsp)))
+        if dataType[2] in ['A','B']:
+            calcPos = G2lat.getPeakPos(dataType,parmDict,peakDsp)
+        for iv,vary in enumerate(varyList):
+            if vary == 'alpha':
+                dMdv[iv,:] = 1.0/peakDsp
+            if vary == 'alpha-0':
+                dMdv[iv,:] = 1.0
+            if vary == 'alpha-1':
+                dMdv[iv,:] = npsind(calcPos/2.)
+        return np.sqrt(peakWt)*dMdv                 
+            
     def errPeakBet(values,peakDsp,peakBet,peakWt,dataType,parmDict,varyList):
         parmDict.update(dict(zip(varyList,values)))
         if dataType[2] in ['A','B']:
@@ -2439,6 +2479,22 @@ def errPeakBet(values,peakDsp,peakBet,peakWt,dataType,parmDict,varyList):
         else: #'T'
             calcBet = parmDict['beta-0']+parmDict['beta-1']/peakDsp**4+parmDict['beta-q']/peakDsp**2
         return peakWt*(calcBet-peakBet)
+    
+    def dervPeakBet(values,peakDsp,peakBet,peakWt,dataType,parmDict,varyList):
+        dMdv = np.zeros(shape=(len(varyList),len(peakDsp)))
+        if dataType[2] in ['A','B']:
+            calcPos = G2lat.getPeakPos(dataType,parmDict,peakDsp)
+        for iv,vary in enumerate(varyList):
+            if vary == 'beta-0':
+                dMdv[iv,:] = 1.0
+            if vary == 'beta-1':
+                if dataType[2] in ['A','B']:
+                    dMdv[iv,:] = npsind(calcPos/2.)
+                else:
+                    dMdv[iv,:] = 1.0/peakDsp**4
+            if vary == 'beta-q':
+                dMdv[iv,:] = 1.0/peakDsp**2
+        return np.sqrt(peakWt)*dMdv                                
 
     def errPeakSig(values,peakDsp,peakSig,peakWt,dataType,parmDict,varyList):
         parmDict.update(dict(zip(varyList,values)))
@@ -2450,6 +2506,30 @@ def errPeakSig(values,peakDsp,peakSig,peakWt,dataType,parmDict,varyList):
             calcSig = parmDict['sig-0']+parmDict['sig-1']*peakDsp**2+parmDict['sig-2']*peakDsp**4+parmDict['sig-q']*peakDsp
         return peakWt*(calcSig-peakSig)
 
+    def dervPeakSig(values,peakDsp,peakSig,peakWt,dataType,parmDict,varyList):
+        dMdv = np.zeros(shape=(len(varyList),len(peakDsp)))
+        if dataType[2] in ['A','B','C']:
+            calcPos = G2lat.getPeakPos(dataType,parmDict,peakDsp)
+            tp = nptand(calcPos/2.0)
+            for iv,vary in enumerate(varyList):
+                if vary == 'U':
+                    dMdv[iv,:] = tp**2
+                if vary == 'V':
+                    dMdv[iv,:] = tp
+                if vary == 'W':
+                    dMdv[iv,:] = 1.
+        else:
+            for iv,vary in enumerate(varyList):
+                if vary == 'sig-0':
+                    dMdv[iv,:] = 1.0
+                if vary == 'sig-1':
+                    dMdv[iv,:] = peakDsp**2
+                if vary == 'sig-2':
+                    dMdv[iv,:] = peakDsp**4
+                if vary == 'sig-q':
+                    dMdv[iv,:] = peakDsp
+        return np.sqrt(peakWt)*dMdv                                                    
+    
     def outResult():
         chisq = np.sum(result[2]['fvec']**2)
         GOF = chisq/(len(peakPos)-len(posVary))       #reduced chi^2
@@ -2464,36 +2544,30 @@ def outResult():
             return []
         return sig
 
-    dataType = Inst['Type'][0]
-    peakPos,peakDsp,peakPosWt = SetPosData()
-    posDict,posVary = SetPosParms()
-    sigDsp,peakSig,peakSigWt = SetSigData()
-    sigDict,sigVary = SetSigParms()
-    if dataType[2] in ['A','B','T']:
-        alpDsp,peakAlp,peakAlpWt = SetAlpData()
-        alpDict,alpVary = SetAlpParms()
-        betDsp,peakBet,peakBetWt = SetBetData()
-        betDict,betVary = SetBetParms()
-        
+    dataType = Inst['Type'][0]       
     parmDict = {}
     Sigmas = {}
+    peakPos,peakDsp,peakPosWt = SetPosData()
+    posDict,posVary = SetPosParms()
     parmDict.update(posDict)
     if len(peakPos) > 5 and len(posVary):
         values =  np.array(Dict2Values(parmDict, posVary))
-        result = so.leastsq(errPeakPos,values,full_output=True,ftol=0.000001,
-            args=(peakDsp,peakPos,peakPosWt,dataType,parmDict,posVary))
+        result = so.leastsq(errPeakPos,values,Dfun=dervPeakPos,full_output=True,ftol=0.000001,
+            col_deriv=True,args=(peakDsp,peakPos,peakPosWt,dataType,parmDict,posVary))
         G2fil.G2Print('Position calibration:')
         Values2Dict(parmDict, posVary, result[0])
         sig = outResult()
         if  len(sig):
             Sigmas.update(zip(posVary,sig))
             GetInstParms(parmDict)
-    parmDict = {}
+    # parmDict = {}
+    sigDsp,peakSig,peakSigWt = SetSigData()
+    sigDict,sigVary = SetSigParms()
     parmDict.update(sigDict)
     if len(peakSig) > 5 and len(sigVary):
         values =  np.array(Dict2Values(parmDict, sigVary))
-        result = so.leastsq(errPeakSig,values,full_output=True,ftol=0.000001,
-            args=(sigDsp,peakSig,peakSigWt,dataType,parmDict,sigVary))
+        result = so.leastsq(errPeakSig,values,Dfun=dervPeakSig,full_output=True,ftol=0.000001,
+            col_deriv=True,args=(sigDsp,peakSig,peakSigWt,dataType,parmDict,sigVary))
         G2fil.G2Print('Sigma calibration:')
         Values2Dict(parmDict, sigVary, result[0])
         sig = outResult()
@@ -2503,12 +2577,14 @@ def outResult():
     else:
         G2fil.G2Print(' Sigma not calibrated: insufficient data or not selected')
     if dataType[2] in ['A','B','T']:
-        parmDict = {}
+        # parmDict = {}
+        alpDsp,peakAlp,peakAlpWt = SetAlpData()
+        alpDict,alpVary = SetAlpParms()
         parmDict.update(alpDict)
         if len(peakAlp) > 5 and len(alpVary):
             values =  np.array(Dict2Values(parmDict, alpVary))
-            result = so.leastsq(errPeakAlp,values,full_output=True,ftol=0.000001,
-                args=(alpDsp,peakAlp,peakAlpWt,dataType,parmDict,alpVary))
+            result = so.leastsq(errPeakAlp,values,Dfun=dervPeakAlp,full_output=True,ftol=0.000001,
+                col_deriv=True,args=(alpDsp,peakAlp,peakAlpWt,dataType,parmDict,alpVary))
             G2fil.G2Print('Alpha calibration:')
             Values2Dict(parmDict, alpVary, result[0])
             sig = outResult()
@@ -2517,12 +2593,14 @@ def outResult():
                 GetInstParms(parmDict)
         else:
             G2fil.G2Print(' Alpha not calibrated: insufficient data or not selected')
-        parmDict = {}
+        # parmDict = {}
+        betDsp,peakBet,peakBetWt = SetBetData()
+        betDict,betVary = SetBetParms()
         parmDict.update(betDict)
         if len(peakBet) > 5 and len(betVary):
             values =  np.array(Dict2Values(parmDict, betVary))
-            result = so.leastsq(errPeakBet,values,full_output=True,ftol=0.000001,
-                args=(betDsp,peakBet,peakBetWt,dataType,parmDict,betVary))
+            result = so.leastsq(errPeakBet,values,Dfun=dervPeakBet,full_output=True,ftol=0.000001,
+                col_deriv=True,args=(betDsp,peakBet,peakBetWt,dataType,parmDict,betVary))
             G2fil.G2Print('Beta calibration:')
             Values2Dict(parmDict, betVary, result[0])
             sig = outResult()
@@ -2691,8 +2769,13 @@ def BackgroundPrint(Background,sigDict):
         if 'BF mult' in sigDict:
             print('Background file mult: %.3f(%d)'%(Background[1]['background PWDR'][1],int(1000*sigDict['BF mult'])))
 
-    def SetInstParms(Inst):
+    def SetInstParms(Inst,peakVary):
+        # superesses refinement of instrument parameters if any corresponding peak parameter is refined
         dataType = Inst['Type'][0]
+        noAlp = any([True for vary in peakVary if 'alp' in vary])
+        noBet = any([True for vary in peakVary if 'bet' in vary])
+        noSig = any([True for vary in peakVary if 'sig' in vary])
+#        noGam = any([True for vary in peakVary if 'gam' in vary])
         insVary = []
         insNames = []
         insVals = []
@@ -2701,7 +2784,19 @@ def SetInstParms(Inst):
             insVals.append(Inst[parm][1])
             if parm in ['U','V','W','X','Y','Z','SH/L','I(L2)/I(L1)','alpha','A','B','C',
                 'beta-0','beta-1','beta-q','sig-0','sig-1','sig-2','sig-q','alpha-0','alpha-1'] and Inst[parm][2]:
-                    insVary.append(parm)
+                if 'alp' in parm and noAlp:
+                    Inst[parm][2] = False
+                    continue
+                elif 'bet' in parm and noBet:
+                    Inst[parm][2] = False
+                    continue
+                elif ('sig' in parm or parm in ['U','V','W']) and noSig:
+                    Inst[parm][2] = False
+                    continue
+                # elif parm in ['X','Y','Z'] and noGam:
+                #     Inst[parm][2] = False
+                #     continue
+                insVary.append(parm)
         instDict = dict(zip(insNames,insVals))
         if 'SH/L' in instDict:
             instDict['SH/L'] = max(instDict['SH/L'],0.002)
@@ -2925,8 +3020,8 @@ def errPeakProfile(values,xdata,ydata,fixback,weights,dataType,parmdict,varylist
     xFin = np.searchsorted(x,Limits[1])+1
     # find out what is varied
     bakType,bakDict,bakVary = SetBackgroundParms(Background)
-    dataType,insDict,insVary = SetInstParms(Inst)
     peakDict,peakVary = SetPeaksParms(Inst['Type'][0],Peaks)
+    dataType,insDict,insVary = SetInstParms(Inst,peakVary)
     parmDict = {}
     parmDict.update(bakDict)
     parmDict.update(insDict)

GSASII/GSASIIscriptable.py

@@ -588,13 +588,36 @@ def load_pwd_from_reader(reader, instprm, existingnames=[],bank=None):
     HistName = 'PWDR ' + G2obj.StripUnicode(reader.idstring, '_')
     HistName = G2obj.MakeUniqueLabel(HistName, existingnames)
 
-    try:
-        Iparm1, Iparm2 = instprm
-    except ValueError:
+    # get instrumental parameters from reader...
+    if instprm is None:
+        try:
+            Iparm1, Iparm2 = reader.pwdparms['Instrument Parameters']
+            print('Instrument parameters supplied in data file')
+        except KeyError as err:
+            Iparm1 = None  # signal error rather than raise exception inside an exception handler
+        if Iparm1 is None:
+            msg  = "The data file does not have any instrument params associated with it and none were provided."
+            raise Exception(msg)
+    
+    # ...or from a file...
+    elif isinstance(instprm, str):
         Iparm1, Iparm2 = load_iprms(instprm, reader, bank=bank)
         G2fil.G2Print('Instrument parameters read:',reader.instmsg)
-    except TypeError:  # instprm is None, get iparms from reader
-        Iparm1, Iparm2 = reader.pwdparms['Instrument Parameters']
+
+    # ...or from an input...
+    elif (
+        isinstance(instprm, (list, tuple)) 
+        and len(instprm) == 2 
+        and all(isinstance(i, dict) for i in instprm)
+        ):
+            Iparm1, Iparm2 = instprm
+            print('Instrument parameters supplied in script')
+
+    # ...else raise an error.
+    else:
+        msg = f"load_pwd... Error: Invalid instprm entered ({instprm!r})"
+        raise Exception(msg)
+
 
     if 'T' in Iparm1['Type'][0]:
         if not reader.clockWd and reader.GSAS:
@@ -1058,14 +1081,20 @@ def add_powder_histogram(self, datafile, iparams=None, phases=[],
         if not multiple: pwdrreaders = pwdrreaders[0:1]
         histlist = []
         if URL:
-            iparmfile = downloadFile(iparams)
-        else:
+            instprm = downloadFile(iparams)
+        elif iparams:
             try:
-                iparmfile = os.path.abspath(os.path.expanduser(iparams))
-            except:
-                pass
+                instprm = os.path.abspath(os.path.expanduser(iparams))
+            except TypeError: # iparams is not a file path
+                if isinstance(iparams, (list, tuple)):
+                    instprm = iparams
+                else:
+                    raise Exception(f"add_powder_histogram Error: Invalid iparams supplied ({iparams!r})")
+        else:
+            instprm = None # will error out unless the reader supplies them
+    
         for r in pwdrreaders:
-            histname, new_names, pwdrdata = load_pwd_from_reader(r, iparmfile,
+            histname, new_names, pwdrdata = load_pwd_from_reader(r, instprm,
                                           [h.name for h in self.histograms()],bank=instbank)
             if histname in self.data:
                 G2fil.G2Print("Warning - redefining histogram", histname)
@@ -3184,13 +3213,17 @@ def get_Covariance(self,varList):
             covArray = np.divide(np.divide(covMatrix,xvar),xvar.T)
 
         '''
+        for i in ('covMatrix','varyList','variables'):
+            if i not in self['Covariance']['data']:
+                raise G2ScriptException(f'No {i} found in project, has a refinement been run?')
         missing = [i for i in varList if i not in self['Covariance']['data']['varyList']]
         if missing:
             G2fil.G2Print('Warning: Variable(s) {} were not found in the varyList'.format(missing))
             return None
-        if 'parmDict' not in self['Covariance']['data']:
-            raise G2ScriptException('No parameters found in project, has a refinement been run?')
-        vals = [self['Covariance']['data']['parmDict'][i] for i in varList]
+        parmDict = dict(zip(
+            self['Covariance']['data']['varyList'],
+            self['Covariance']['data']['variables']))
+        vals = [parmDict[i] for i in varList]
         cov = G2mth.getVCov(varList,
                             self['Covariance']['data']['varyList'],
                             self['Covariance']['data']['covMatrix'])

GSASII/GSASIIstrMath.py

@@ -3587,7 +3587,7 @@ def GetHStrainShiftDerv(refl,im,SGData,phfx,hfx,calcControls,parmDict):
             dDijDict[item] *= refl[5+im]/refl[4+im]**2
     else:
         for item in dDijDict:
-            dDijDict[item] *= -parmDict[hfx+'difC']*refl[4+im]**3/2.
+            dDijDict[item] *= -parmDict[hfx+'difC']*refl[4+im]**2
     return dDijDict
 
 def GetDij(phfx,SGData,parmDict):