Changeset 1245 for trunk

Timestamp:

Mar 12, 2014 11:15:28 AM (11 years ago)

Author:

vondreele

Message:

Make SASD plot default to log & show errors
SASD MaxEnt? result now matches Irena result

Location:

trunk

Files:

• GSASIIplot.py (modified) (1 diff)
• GSASIIsasd.py (modified) (8 diffs)

trunk/GSASIIplot.py ¶

@@ -699 +699 @@
         Plot = Page.figure.gca()          #get a fresh plot after clf()
     except ValueError:
+        if plottype == 'SASD':
+            G2frame.logPlot = True
+            G2frame.ErrorBars = True
         newPlot = True
         G2frame.Cmax = 1.0

trunk/GSASIIsasd.py ¶

@@ -105 +105 @@
     ''' Compute form factor for cylinders - can use numpy arrays
     param float: Q Q value array (A-1)
-    param float: L cylinder length (A)
-    param float: D cylinder diameter (A)
+    param float: L cylinder half length (A)
+    param float: R cylinder diameter (A)
     returns float: form factor
     '''
-    D = args[0]
-    return CylinderFF(Q,D/2.,L)    
+    R = args[0]
+    return CylinderFF(Q,R,2.*L)    
     
 def CylinderARFF(Q,R,args): 
@@ -205 +205 @@
     ''' Compute cylinder volume for length & diameter
     - numpy array friendly
-    param float: L length (A)
+    param float: L half length (A)
     param float: D diameter (A)
     returns float:volume (A^3)
     '''
-    return CylinderVol(D/2.,L)
+    return CylinderVol(D/2.,2.*L)
     
 def CylinderARVol(R,AR):
@@ -322 +322 @@
     '''
         
-    TEST_LIMIT        = 0.10                    # for convergence
+    TEST_LIMIT        = 0.05                    # for convergence
     CHI_SQR_LIMIT     = 0.01                    # maximum difference in ChiSqr for a solution
     SEARCH_DIRECTIONS = 3                       # <10.  This code requires value = 3
@@ -482 +482 @@
         chtarg = ctarg * chisq
         return w, chtarg, loop, a_new, fx, beta
+        
 #MaxEnt_SB starts here    
+
     if image_to_data == None:
         image_to_data = opus
@@ -583 +585 @@
 
         # calculate the normalized entropy
-        S = -sum((f/fSum) * numpy.log(f/fSum))      # normalized entropy, S&B eq. 1
+        S = sum((f/fSum) * numpy.log(f/fSum))      # normalized entropy, S&B eq. 1
         z = (datum - image_to_data (f, G)) / sigma  # standardized residuals
         chisq = sum(z*z)                            # report this ChiSq
 
         if report:
-            print "%3d/%3d" % ((iter+1), IterMax)
-            print " %5.2lf%% %8lg" % (100*test, S)
+            print " MaxEnt trial/max: %3d/%3d" % ((iter+1), IterMax)
+            print " Residual: %5.2lf%% Entropy: %8lg" % (100*test, S)
             if iter > 0:
                 value = 100*( math.sqrt(chisq/chtarg)-1)
             else:
                 value = 0
-            print " %12.5lg %10.4lf" % ( math.sqrt (chtarg/npt), value )
-            print "%12.6lg %8.2lf\n" % (fSum, 100*fChange/fSum)
+      #      print " %12.5lg %10.4lf" % ( math.sqrt(chtarg/npt), value )
+            print " Function sum: %.6lg Change from last: %.2lf%%\n" % (fSum,100*fChange/fSum)
 
         # See if we have finished our task.
         # do the hardest test first
         if (abs(chisq/chizer-1.0) < CHI_SQR_LIMIT) and  (test < TEST_LIMIT):
-            return f,image_to_data (f, G)     # solution FOUND returns here
-    
-    return f,image_to_data (f, G)       # no solution after IterMax iterations
+            print ' Convergence achieved.'
+            return chisq,f,image_to_data(f, G)     # solution FOUND returns here
+    print ' No convergence! Try increasing Error multiplier.'
+    return chisq,f,image_to_data(f, G)       # no solution after IterMax iterations
 
     
@@ -658 +661 @@
     G = G_matrix(qVec,r,rhosq,SphereFF,SphereVol,args=())
     
-    f_dr,Ic = MaxEnt_SB(I - bkg, dI*errFac, b, IterMax, G, report=report)
+    chisq,f_dr,Ic = MaxEnt_SB(I - bkg, dI*errFac, b, IterMax, G, report=report)
     if f_dr is None:
         print "no solution"
@@ -698 +701 @@
     Qmax = Limits[1][1]
     Contrast = Sample['Contrast'][1]
+    wtFactor = ProfDict['wtFactor']
     Ibeg = np.searchsorted(Q,Qmin)
     Ifin = np.searchsorted(Q,Qmax)
@@ -704 +708 @@
         Ic[Ibeg:Ifin] = Back[0]
     Gmat = G_matrix(Q[Ibeg:Ifin],Bins,Contrast,shapes[Shape][0],shapes[Shape][1],args=Parms)
-    BinMag,Ic[Ibeg:Ifin] = MaxEnt_SB(Io[Ibeg:Ifin]-Back[0],1./np.sqrt(wt[Ibeg:Ifin]),BinsBack,
-        data['Size']['MaxEnt']['Niter'],Gmat)
-    print BinMag.shape
-    data['Size']['Distribution'] = [Bins,Dbins,BinMag]
-    print np.sum(BinMag)
-        
-    
+    chisq,BinMag,Ic[Ibeg:Ifin] = MaxEnt_SB(Io[Ibeg:Ifin]-Back[0],1./np.sqrt(wtFactor*wt[Ibeg:Ifin]),BinsBack,
+        data['Size']['MaxEnt']['Niter'],Gmat,report=True)
+    print ' Final chi^2: %.3f'%(chisq)
+    Vols = shapes[Shape][1](Bins,Parms)
+    data['Size']['Distribution'] = [Bins,Dbins,BinMag/(2.*Dbins)]
+        
+