diff --git a/xanes_analyzeRun.py b/xanes_analyzeRun.py
index 2a12552..c6b7d2d 100644
--- a/xanes_analyzeRun.py
+++ b/xanes_analyzeRun.py
@@ -101,37 +101,8 @@ def showShots(im1,im2):
       a[0].plot(p1)
       a[1].plot(p2)
 
-def ratioOfAverage(p1,p2,threshold=0.03):
-  """ 
-   p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
-   calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
-  # check if they are 2D
-  if p1.ndim == 1:
-    p1 = p1[np.newaxis,:]
-    p2 = p2[np.newaxis,:]
-  # w1 and w2 are the weights
-  w1 = p1.copy(); w2 = p2.copy()
-  if threshold is not None:
-    # weights will be set to zero if intensity is smaller than 5% of max
-    # for each shots, get maximum
-    m1 = np.nanmax(p1,axis=1); m2 = np.nanmax(p2,axis=1)
-    # find where each spectrum is smaller than threshold*max_for_that_shot; they will be masked out
-    idx1 = p1 < (m1[:,np.newaxis]*threshold)
-    idx2 = p2 < (m2[:,np.newaxis]*threshold)
-    w1[idx1]=0
-    w2[idx2]=0
-  # using masked array because some pixel will have zero shots contributing
-  av1 = np.ma.average(p1,axis=0,weights=w1)
-  av1[av1.mask] = np.nan
-  av2 = np.ma.average(p2,axis=0,weights=w2)
-  av2[av2.mask] = np.nan
-  return av2/av1
-  
-def medianRatio(p1,p2,threshold=0.03):
-  """ 
-   p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
-   calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
-  # check if they are 2D
+
+def maskLowIntensity(p1,p2,threshold=0.03,squeeze=True):
   if p1.ndim == 1:
     p1 = p1[np.newaxis,:]
     p2 = p2[np.newaxis,:]
@@ -145,6 +116,28 @@ def medianRatio(p1,p2,threshold=0.03):
     idx = idx1 & idx2
     p1.mask = idx
     p2.mask = idx
+  if squeeze:
+    p1 = np.squeeze(p1);
+    p2 = np.squeeze(p2)
+  return p1,p2
+
+def ratioOfAverage(p1,p2,threshold=0.03):
+  """ 
+   p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
+   calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
+  p1,p2 = maskLowIntensity(p1,p2,threshold=threshold,squeeze=False)
+  # using masked array because some pixel will have zero shots contributing
+  av1 = np.ma.average(p1,axis=0,weights=p1)
+  av2 = np.ma.average(p2,axis=0,weights=p2)
+  return av2/av1
+
+
+ 
+def medianRatio(p1,p2,threshold=0.03):
+  """ 
+   p1 and p2 are the energy spectrum. if 2D the first index has to be the shot number
+   calculate median ratio taking into account only regions where p1 and p2 are > 5% of the max """
+  p1,p2 = maskLowIntensity(p1,p2,threshold=threshold,squeeze=False)
   ratio = p2/p1
   return np.ma.average(ratio,axis=0,weights=p1)
 
@@ -294,13 +287,30 @@ class AnalyzeRun(object):
       return ret
 
   def save(self,fname="auto",overwrite=False):
-    if len(self.results) == 0: print("self.results are empty, returning without saving")
+    if len(self.results) == 0:
+      print("self.results are empty, returning without saving")
     if not os.path.isdir(g_folder_out): os.makedirs(g_folder_out)
     if fname == "auto":
-      fname = g_folder_out+"/run%04d_analysis" % self.run
+      fname = g_folder_out+"/run%04d_analysis.npz" % self.run
     if os.path.exists(fname) and not overwrite:
       print("File %s exists, **NOT** saving, use overwrite=True is you want ..."%fname)
       return
+    h = dict()
+    h["roi1"] = (self.roi1.start,self.roi1.stop)
+    h["roi2"] = (self.roi2.start,self.roi2.stop)
+    if hasattr(self.data.scan,"scanmotor0"):
+      h["scanmot0"] = self.data.scan.scanmotor0
+    else:
+      h["scanmot0"] = 'notascan'
+    h["scanpos0"] = self.data.scan.scanmotor0_values
+    if hasattr(self.data.scan,"scanmotor1"):
+      h["scanmot1"] = self.data.scan.scanmotor1
+      h["scanpos1"] = self.data.scan.scanmotor1_values
+    h["results"] = self.results
+    h["E"] = self.E
+    np.savez(fname,**h)
+     #h["transform"] = self.initAlign
+    
 
   def load(self,fname="auto"):
     if fname == "auto": fname = g_folder_out+"/run%04d_analysis.npz" % self.run