Changeset fe2ade9 in sasview for DataLoader

Timestamp:

Mar 4, 2009 3:47:12 PM (16 years ago)

Author:

Jae Cho <jhjcho@…>

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

6c0568b

Parents:

eba08f1a

Message:

fixed a bug in slit smearing

File:

• DataLoader/qsmearing.py (modified) (6 diffs)

DataLoader/qsmearing.py

@@ -107 +107 @@
             
             for i in range(self.nbins):
-                sum += iq[i] * self._weights[q_i][i]
-                counts += self._weights[q_i][i]
-                
+                if iq[i]!=0 and self._weights[q_i][i]!=0:
+                    sum += iq[i] * self._weights[q_i][i] 
+                    counts += self._weights[q_i][i]
+                    #print "i,iq[i],self._weights[q_i][i] ",i,iq[i],self._weights[q_i][i]
             iq_smeared[q_i] = sum/counts 
-                
+            #print "q_i,iq_smeared[q_i]",q_i,iq[i],iq_smeared[q_i]
+            #print "iq[i],iq_smeared[q_i],sum,counts,self.nbins",iq[i], iq_smeared[q_i],sum,counts,self.nbins
         return iq_smeared    
     
@@ -156 +158 @@
             # For each q-value, compute the weight of each other q-bin
             # in the I(q) array
-            npts_h = self.npts if self.height>0 else 1
-            npts_w = self.npts if self.width>0 else 1
+            npts_h = self.nbins if self.height>0 else 1 #changed self.npts=>self.nbins
+            npts_w = self.nbins if self.width>0 else 1 #changed self.npts=>self.nbins
             
             # If both height and width are great than zero,
@@ -184 +186 @@
                     if q_i<self.nbins:
                         weights[i][q_i] = weights[i][q_i]+1.0
-                                
+
         self._weights = weights
         return self._weights
@@ -264 +266 @@
             q_min = q - 0.5*step
             q_max = q + 0.5*step
-            
             for j in range(self.nbins):
                 q_j = self.min + j*step
@@ -270 +271 @@
                 # Compute the fraction of the Gaussian contributing
                 # to the q bin between q_min and q_max
+                #value =  math.exp(-math.pow((q_max-q_j),2)/(2*math.pow(self.width[j],2) ))
+                #value +=  math.exp(-math.pow((q_max-q_j),2)/(2*math.pow(self.width[j],2) )) 
                 value =  scipy.special.erf( (q_max-q_j)/(math.sqrt(2.0)*self.width[j]) ) 
                 value -=scipy.special.erf( (q_min-q_j)/(math.sqrt(2.0)*self.width[j]) ) 
-
                 weights[i][j] += value
                                 
@@ -321 +323 @@
     if True:
         for i in range(10):
-            print x[i], sy[i]
+            print x[i],y[i], sy[i]
             #print q, ' : ', s.weight(q), s._compute_iq(q) 
             #print q, ' : ', s(q), s._compute_iq(q)