fixed a BAD bug that was setting to zero everything that was < 5% of the max in the images (i.e. the profile was calculated based on the internal copy used for fit instead of the original image)

alignment.py

@@ -81,7 +81,7 @@ fit_ret = collections.namedtuple("fit_ret",["init_pars","final_pars",\
   "final_transform1","final_transform2","im1","im2","E","p1","p1_sum","p2","p2_sum","fom","ratio","tneeded"] )
 
 def calcFOM(p1,p2,ratio):
-  idx = ( p1>p1.max()/10 ) & (p2>p2.max()/10)
+  idx = ( p1>p1.max()/10 )# & (p2>p2.max()/10)
   ratio = ratio[idx]
   return ratio.std()/ratio.mean()
   
@@ -142,13 +142,13 @@ def plotShot(im1,im2,transf1=None,transf2=None,fig=None,ax=None,res=None,E=defau
   if res is None:
     p1 = np.nansum(im1,axis=0)
     p2 = np.nansum(im2,axis=0)
-    pr = p1/p2
+    pr = p2/p1
   else:
     p1 = res.p1; p2 = res.p2; pr = res.ratio
   ax[3].plot(E,p1,lw=3)
   ax[4].plot(E,p1,lw=1)
   ax[4].plot(E,p2,lw=3)
-  idx = (p1>p1.max()/10.) & (p2>p2.max()/10)
+  idx = (p1>p1.max()/10.)
   ax[5].plot(E[idx],pr[idx])
   if res is not None:
     ax[5].set_title("FOM: %.2f"%res.fom)
@@ -427,6 +427,9 @@ def transformIminuit(im1,im2,init_transform=dict(),show=False,verbose=True,zeroT
   final_params = imin.fitarg.copy()
   t1,t2 = transforms(*imin.args)
   i1,i2 = model(*imin.args)
+
+  i1 = t1.transformImage(im1)
+  i2 = t2.transformImage(im2)
   if show:
     plotShot(i1,i2)
     fig = plt.gcf()