Changeset 4003

Timestamp:

May 29, 2019 6:22:27 PM (5 years ago)

Author:

toby

Message:

fix subtle bug in plotCovar where cursor showed only initial vals; add general parameter retrieval routines

Location:

trunk

Files:

• GSASIIdataGUI.py (modified) (2 diffs)
• GSASIIplot.py (modified) (5 diffs)
• GSASIIscriptable.py (modified) (6 diffs)

trunk/GSASIIdataGUI.py

@@ -6115 +6115 @@
             
     def PlotSelectedColRow(calltyp=''):
-        '''Called to plot a selected column or row. This is called after the event is processed
-        so that the column or row gets selected.
-        Single click on row: plots histogram
-        Double click on row: plots V-C matrix
-        Single or double click on column: plots values in column
+        '''Called to plot a selected column or row by clicking or 
+        double-clicking on a row or column label. N.B. This is called 
+        after the event is processed so that the column or row has been
+        selected.
+
+        :param str calltyp: ='single'/'double', specifies if this was 
+          a single- or double-click, where a single click on row 
+          plots histogram; Double click on row plots V-C matrix; 
+          Single or double click on column: plots values in column
         '''
         cols = G2frame.dataDisplay.GetSelectedCols()
@@ -6154 +6158 @@
         key = event.GetKeyCode()
         rows = G2frame.dataDisplay.GetSelectedRows()
-        print(key,rows)
+        #print(key,rows)
         event.Skip()
         wx.CallAfter(PlotSelectedColRow,'single')

trunk/GSASIIplot.py

@@ -6058 +6058 @@
             
 def PlotCovariance(G2frame,Data):
-    'needs a doc string'
-    if not Data:
-        print ('No covariance matrix available')
-        return
-    varyList = Data['varyList']
-    values = Data['variables']
-    covMatrix = Data['covMatrix']
-    sig = np.sqrt(np.diag(covMatrix))
-    xvar = np.outer(sig,np.ones_like(sig))
-    covArray = np.divide(np.divide(covMatrix,xvar),xvar.T)
-    title = G2obj.StripUnicode(' for\n'+Data['title'],'') # matplotlib 1.x does not like unicode
-    newAtomDict = Data.get('newAtomDict',{})
-    G2frame.G2plotNB.status.DestroyChildren() #get rid of special stuff on status bar
-
+    '''Plots the covariance matrix. Also shows values for parameters 
+    and their standard uncertainties (esd's) or the correlation between 
+    variables.
+    '''
     def OnPlotKeyPress(event):
         if event.key == 's':
@@ -6090 +6080 @@
             covFile.write('*' + 126*' ' + '*\n')
             covFile.write(128*'*' + '\n\n\n\n')
-            llen = len(varyList)
+            llen = len(Page.varyList)
             for start in range(0, llen, 8):  # split matrix into batches of 7 columns
                 if llen >= start + 8:
@@ -6098 +6088 @@
                 covFile.write(12*' ' + '\t')
                 for idx in range(start, stop):
-                    covFile.write('{:^12}\t'.format(varyList[idx]))
+                    covFile.write('{:^12}\t'.format(Page.varyList[idx]))
                 covFile.write('\n\n')
                 for line in range(llen):
-                    covFile.write('{:>12}\t'.format(varyList[line]))
+                    covFile.write('{:>12}\t'.format(Page.varyList[line]))
                     for idx in range(start, stop):
-                        covFile.write('{: 12.6f}\t'.format(covArray[line][idx]))
+                        covFile.write('{: 12.6f}\t'.format(Page.covArray[line][idx]))
                     covFile.write('\n')
                 covFile.write('\n\n\n')
             covFile.close()
-        PlotCovariance(G2frame,Data)
+        wx.CallAfter(PlotCovariance,G2frame,Data)
 
     def OnMotion(event):
         if event.button:
             ytics = imgAx.get_yticks()
-            ytics = np.where(ytics<len(varyList),ytics,-1)
-            ylabs = [np.where(0<=i ,varyList[int(i)],' ') for i in ytics]
+            ytics = np.where(ytics<len(Page.varyList),ytics,-1)
+            ylabs = [np.where(0<=i ,Page.varyList[int(i)],' ') for i in ytics]
             imgAx.set_yticklabels(ylabs)            
         if event.xdata and event.ydata:                 #avoid out of frame errors
             xpos = int(event.xdata+.5)
             ypos = int(event.ydata+.5)
-            if -1 < xpos < len(varyList) and -1 < ypos < len(varyList):
+            if -1 < xpos < len(Page.varyList) and -1 < ypos < len(Page.varyList):
                 if xpos == ypos:
-                    value = values[xpos]
-                    name = varyList[xpos]
-                    if varyList[xpos] in newAtomDict:
-                        name,value = newAtomDict[name]                        
-                    msg = '%s value = %.4g, esd = %.4g'%(name,value,sig[xpos])
+                    value = Page.values[xpos]
+                    name = Page.varyList[xpos]
+                    if Page.varyList[xpos] in Page.newAtomDict:
+                        name,value = Page.newAtomDict[name]                        
+                    msg = '%s value = %.4g, esd = %.4g'%(name,value,Page.sig[xpos])
                 else:
-                    msg = '%s - %s: %5.3f'%(varyList[xpos],varyList[ypos],covArray[xpos][ypos])
+                    msg = '%s - %s: %5.3f'%(Page.varyList[xpos],Page.varyList[ypos],Page.covArray[xpos][ypos])
                 Page.SetToolTipString(msg)
                 G2frame.G2plotNB.status.SetStatusText(msg,1)
                 
+    #==== PlotCovariance(G2frame,Data) starts here =========================
+    if not Data:
+        print ('No covariance matrix available')
+        return
     new,plotNum,Page,Plot,lim = G2frame.G2plotNB.FindPlotTab('Covariance','mpl')
     if not new:
@@ -6137 +6131 @@
         Page.canvas.mpl_connect('motion_notify_event', OnMotion)
         Page.canvas.mpl_connect('key_press_event', OnPlotKeyPress)
+    Page.varyList = Data['varyList']
+    Page.values = Data['variables']
+    covMatrix = Data['covMatrix']
+    Page.sig = np.sqrt(np.diag(covMatrix))
+    xvar = np.outer(Page.sig,np.ones_like(Page.sig))
+    Page.covArray = np.divide(np.divide(covMatrix,xvar),xvar.T)
+    title = G2obj.StripUnicode(' for\n'+Data['title'],'') # matplotlib 1.x does not like unicode
+    Page.newAtomDict = Data.get('newAtomDict',{})
+    G2frame.G2plotNB.status.DestroyChildren() #get rid of special stuff on status bar
     Page.Choice = ['s: to change colors','p: to save covariance as text file']
     Page.keyPress = OnPlotKeyPress
@@ -6143 +6146 @@
     G2frame.G2plotNB.status.SetStatusWidths([150,-1])   #need to reset field widths here    
     acolor = mpl.cm.get_cmap(G2frame.VcovColor)
-    Img = Plot.imshow(covArray,aspect='equal',cmap=acolor,interpolation='nearest',origin='lower',
+    Img = Plot.imshow(Page.covArray,aspect='equal',cmap=acolor,interpolation='nearest',origin='lower',
         vmin=-1.,vmax=1.)
     imgAx = Img.axes
     ytics = imgAx.get_yticks()
-    ylabs = [varyList[int(i)] for i in ytics[:-1]]
+    ylabs = [Page.varyList[int(i)] for i in ytics[:-1]]
     imgAx.set_yticklabels(ylabs)
     Page.figure.colorbar(Img)

trunk/GSASIIscriptable.py

@@ -131 +131 @@
 :meth:`G2Project.set_refinement`                      This is passed a single dict which is used to set parameters and flags.
                                                       These actions can be performed also in :meth:`G2Project.do_refinements`. 
+:meth:`G2Project.get_Variable'                        Retrieves the value and esd for a parameter
+:meth:`G2Project.get_Covariance'                      Retrieves values and covariance for a set of refined parameters
 ==================================================    ===============================================================================================================
 
@@ -240 +242 @@
 :meth:`G2SeqRefRes.histograms`                         Provides a list of histograms used in the Sequential Refinement 
 :meth:`G2SeqRefRes.get_cell_and_esd`                   Returns cell dimensions and standard uncertainies for a phase and histogram from the Sequential Refinement 
+:meth:`G2SeqRefRes.get_Variable'                       Retrieves the value and esd for a parameter from a particular histogram in the Sequential Refinement 
+:meth:`G2SeqRefRes.get_Covariance'                     Retrieves values and covariance for a set of refined parameters for a particular histogram 
 ==================================================    ===============================================================================================================
 
@@ -2638 +2642 @@
             for key in copysections: 
                 hist_out[key] = copy.deepcopy(hist_in[key])
+
+    def get_VaryList(self):
+        '''Returns a list of the refined variables in the 
+        last refinement cycle
+
+        :returns: a list of variables or None if no refinement has been
+          performed. 
+        '''
+        try:
+            return self['Covariance']['data']['varyList']
+        except:
+            return
+
+    def get_ParmList(self):
+        '''Returns a list of all the parameters defined in the 
+        last refinement cycle
+
+        :returns: a list of parameters or None if no refinement has been
+          performed. 
+        '''
+        try:
+            return list(self['Covariance']['data']['parmDict'].keys())
+        except:
+            return
         
+    def get_Variable(self,var):
+        '''Returns the value and standard uncertainty (esd) for a variable 
+        parameters, as defined in the last refinement cycle
+
+        :param str var: a variable name of form '<p>:<h>:<name>', such as 
+          ':0:Scale'
+        :returns: (value,esd) if the parameter is refined or 
+          (value, None) if the variable is in a constraint or is not 
+          refined or None if the parameter is not found. 
+        '''
+        if var not in self['Covariance']['data']['parmDict']:
+            return None
+        val = self['Covariance']['data']['parmDict'][var]
+        try:
+            pos = self['Covariance']['data']['varyList'].index(var)
+            esd = np.sqrt(self['Covariance']['data']['covMatrix'][pos,pos])
+            return (val,esd)
+        except ValueError:
+            return (val,None)
+
+    def get_Covariance(self,varList):
+        '''Returns the values and covariance matrix for a series of variable 
+        parameters. as defined in the last refinement cycle
+
+        :param tuple varList: a list of variable names of form '<p>:<h>:<name>'
+        :returns: (valueList,CovMatrix) where valueList contains the (n) values
+          in the same order as varList (also length n) and CovMatrix is a 
+          (n x n) matrix. If any variable name is not found in the varyList
+          then None is returned. 
+
+        Use this code, where sig provides standard uncertainties for 
+        parameters and where covArray provides the correlation between 
+        off-diagonal terms::
+
+            sig = np.sqrt(np.diag(covMatrix))
+            xvar = np.outer(sig,np.ones_like(sig))
+            covArray = np.divide(np.divide(covMatrix,xvar),xvar.T)
+
+        '''
+        missing = [i for i in varList if i not in self['Covariance']['data']['varyList']]
+        if missing:
+            print('Variable(s) {} were not found in the varyList'.format(missing))
+            return None
+        vals = [self['Covariance']['data']['parmDict'][i] for i in varList]
+        import GSASIImath as G2mth
+        cov = G2mth.getVCov(varList,
+                            self['Covariance']['data']['varyList'],
+                            self['Covariance']['data']['covMatrix'])
+        return (vals,cov)
+
 class G2AtomRecord(G2ObjectWrapper):
     """Wrapper for an atom record. Has convenient accessors via @property.
-
 
     Available accessors: label, type, refinement_flags, coordinates,
@@ -3798 +3875 @@
         print('printed',[lbl[i] for i in list(uniq)+[6]])
 
+    .. seealso::
+        :meth:`G2Project.seqref`
     '''
     def __init__(self, data, proj):
@@ -3916 +3995 @@
         return list(c)+[vol],cE,uniqCellIndx
     
+    def get_VaryList(self,hist):
+        '''Returns a list of the refined variables in the 
+        last refinement cycle for the selected histogram
+
+        :param hist: Specify a histogram or using the histogram name (str) 
+          or the index number (int) of the histogram in the sequential 
+          refinement (not the project), numbered starting from 0.
+        :returns: a list of variables or None if no refinement has been
+          performed. 
+        '''
+        try:
+            seqData,histData = self.RefData(hist)
+            return seqData['varyList']
+        except:
+            return
+
+    def get_ParmList(self,hist):
+        '''Returns a list of all the parameters defined in the 
+        last refinement cycle for the selected histogram
+
+        :param hist: Specify a histogram or using the histogram name (str) 
+          or the index number (int) of the histogram in the sequential 
+          refinement (not the project), numbered starting from 0.
+        :returns: a list of parameters or None if no refinement has been
+          performed. 
+        '''
+        try:
+            seqData,histData = self.RefData(hist)
+            return list(seqData['parmDict'].keys())
+        except:
+            return
+
+    def get_Variable(self,hist,var):
+        '''Returns the value and standard uncertainty (esd) for a variable 
+        parameters, as defined for the selected histogram 
+        in the last sequential refinement cycle
+
+        :param hist: Specify a histogram or using the histogram name (str) 
+          or the index number (int) of the histogram in the sequential 
+          refinement (not the project), numbered starting from 0.
+        :param str var: a variable name of form '<p>:<h>:<name>', such as 
+          ':0:Scale'
+        :returns: (value,esd) if the parameter is refined or 
+          (value, None) if the variable is in a constraint or is not 
+          refined or None if the parameter is not found. 
+        '''
+        try:
+            seqData,histData = self.RefData(hist)
+            val = seqData['parmDict'][var]
+        except:
+            return
+        try:
+            pos = seqData['varyList'].index(var)
+            esd = np.sqrt(seqData['covMatrix'][pos,pos])
+            return (val,esd)
+        except ValueError:
+            return (val,None)
+
+    def get_Covariance(self,hist,varList):
+        '''Returns the values and covariance matrix for a series of variable 
+        parameters, as defined for the selected histogram 
+        in the last sequential refinement cycle
+
+        :param hist: Specify a histogram or using the histogram name (str) 
+          or the index number (int) of the histogram in the sequential 
+          refinement (not the project), numbered starting from 0.
+        :param tuple varList: a list of variable names of form '<p>:<h>:<name>'
+        :returns: (valueList,CovMatrix) where valueList contains the (n) values
+          in the same order as varList (also length n) and CovMatrix is a 
+          (n x n) matrix. If any variable name is not found in the varyList
+          then None is returned. 
+
+        Use this code, where sig provides standard uncertainties for 
+        parameters and where covArray provides the correlation between 
+        off-diagonal terms::
+
+            sig = np.sqrt(np.diag(covMatrix))
+            xvar = np.outer(sig,np.ones_like(sig))
+            covArray = np.divide(np.divide(covMatrix,xvar),xvar.T)
+
+        '''
+        try:
+            seqData,histData = self.RefData(hist)
+        except:
+            print('Histogram {} not found in the sequential fit'.format(hist))
+            return
+        missing = [i for i in varList if i not in seqData['varyList']]
+        if missing:
+            print('Variable(s) {} were not found in the varyList'.format(missing))
+            return None
+        vals = [seqData['parmDict'][i] for i in varList]
+        import GSASIImath as G2mth
+        cov = G2mth.getVCov(varList,seqData['varyList'],seqData['covMatrix'])
+        return (vals,cov)
+    
     def RefData(self,hist):
         '''Provides access to the output from a particular histogram
@@ -3956 +4130 @@
        gpx.save('pdfcalc.gpx')
 
+    .. seealso::
+        :meth:`G2Project.pdf`
+        :meth:`G2Project.pdfs`
     """
     def __init__(self, data, name, proj):