Changeset 7241d56 in sasview

Timestamp:

Dec 21, 2010 9:46:10 AM (14 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:

98eefdb

Parents:

7342634

Message:

improved edge behavior of Qsmearer

Location:

DataLoader

Files:

• extensions/smearer.cpp (modified) (1 diff)
• qsmearing.py (modified) (7 diffs)

DataLoader/extensions/smearer.cpp

@@ -285 +285 @@
                 // Normalize counts
                 iq_out[q_i] = (counts>0.0) ? sum/counts : 0;
-                //printf("\n iii=%g,%g ",iq_out[q_i], q_i);
         }
 }

DataLoader/qsmearing.py

@@ -167 +167 @@
         if first_bin < 0:
             first_bin = 0
-            
+        
         # With a model given, compute I for the extrapolated points and append
         # to the iq_in
@@ -175 +175 @@
                                                         first_bin, last_bin)
             iq_in_low = self.model.evalDistribution( \
-                                            self.qvalues[0:self.nbins_low])
+                                    numpy.fabs(self.qvalues[0:self.nbins_low]))
             iq_in_high = self.model.evalDistribution( \
                                             self.qvalues[(len(self.qvalues) - \
-                                            self.nbins_high - 1): -1])
+                                            self.nbins_high - 1):])
+            # Todo: find out who is sending iq[last_poin] = 0.
+            if iq_in[len(iq_in) - 1] == 0:
+                iq_in[len(iq_in) - 1] = iq_in_high[0]
+            # Append the extrapolated points to the data points
             if self.nbins_low > 0:                             
                 iq_in_temp = numpy.append(iq_in_low, iq_in)
             if self.nbins_high > 0:
-                iq_in_temp = numpy.append(iq_in_temp, iq_in_high)
+                iq_in_temp = numpy.append(iq_in_temp, iq_in_high[1:])
         else:
             temp_first = first_bin
             temp_last = last_bin
             iq_in_temp = iq_in
+        
         # Sanity check
         if len(iq_in_temp) != self.nbins:
@@ -203 +208 @@
             msg = "_BaseSmearer: could not smear, code = %g" % smear_output
             raise RuntimeError, msg
-        
-        
+
         temp_first += self.nbins_low
-        temp_last = self.nbins - (self.nbins_high + 1)
-
-        return iq_out[temp_first: (temp_last + 1)]
+        temp_last = self.nbins - self.nbins_high
+        
+        return iq_out[temp_first: temp_last]
     
     def _initialize_smearer(self):
@@ -256 +260 @@
         """
         #  For the first bin
-        if first_bin > 0:
-            # In the case that doesn't need lower q extrapolation data 
-            first_bin +=  self.nbins_low
-        else:
-            # In the case that needs low extrapolation data
-            first_bin = 0
+        # In the case that needs low extrapolation data
+        first_bin = 0
         # For last bin
         if last_bin >= self.nbins - (self.nbins_high + self.nbins_low + 1):
@@ -489 +489 @@
     # Length of the width
     length = len(width)
-    max_width = max(width)
+    width_low = math.fabs(width[0])
+    width_high = math.fabs(width[length -1])
     # Find bin sizes
     bin_size_low = math.fabs(data_x[1] - data_x[0])
-    bin_size_high = math.fabs(data_x[length -1] - data_x[length -2])
+    bin_size_high = math.fabs(data_x[length - 1] - data_x[length - 2])
+    # Compare width(dQ) to the data bin size and take smaller one as the bin 
+    # size of the extrapolation; this will correct some weird behavior 
+    # at the edge
+    if width_low < (bin_size_low):
+        bin_size_low = width_low / 2.0
+    if width_high < (bin_size_high):
+        bin_size_high = width_high / 2.0
+        
     # Number of q points required below the 1st data point in order to extend
     # them 3 times of the width (std)
-    nbins_low = math.ceil(3 * max_width / bin_size_low)
+    nbins_low = math.ceil(3 * width_low / bin_size_low)
     # Number of q points required above the last data point
-    nbins_high = math.ceil(3 * max_width / (bin_size_high))
+    nbins_high = math.ceil(3 * width_high / (bin_size_high))
     # Make null q points        
     extra_low = numpy.zeros(nbins_low)
@@ -509 +518 @@
         ind += 1
     # Remove the points <= 0
-    extra_low = extra_low[extra_low > 0]
-    nbins_low = len(extra_low)
+    #extra_low = extra_low[extra_low > 0]
+    #nbins_low = len(extra_low)
     # Reset ind for another extrapolation
     ind = 0
@@ -521 +530 @@
     data_x_ext = numpy.append(extra_low, data_x)
     data_x_ext = numpy.append(data_x_ext, extra_high)
+    
     # Redefine extra_low and high based on corrected nbins  
     # And note that it is not necessary for extra_width to be a non-zero