Changeset 804fefa in sasview for src/sas/sasgui/perspectives/fitting/model_thread.py

Timestamp:

Oct 5, 2016 1:03:32 PM (8 years ago)

Author:

Mathieu Doucet <doucetm@…>

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, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

6a0c75d1

Parents:

c807957

Message:

Add rescaled data (re #687)

File:

• src/sas/sasgui/perspectives/fitting/model_thread.py (modified) (3 diffs)

src/sas/sasgui/perspectives/fitting/model_thread.py

@@ -167 +167 @@
 
         # If we use a smearer, also return the unsmeared model
-        output_unsmeared = None
+        unsmeared_output = None
+        unsmeared_data = None
+        unsmeared_error = None
         ##smearer the ouput of the plot
         if self.smearer is not None:
@@ -173 +175 @@
                                                              self.qmax)
             mask = self.data.x[first_bin:last_bin+1]
-            output_unsmeared = numpy.zeros((len(self.data.x)))
-            output_unsmeared[first_bin:last_bin+1] = self.model.evalDistribution(mask)
-            output = self.smearer(output_unsmeared, first_bin, last_bin)
-            output_unsmeared = output_unsmeared[index]
+            unsmeared_output = numpy.zeros((len(self.data.x)))
+            unsmeared_output[first_bin:last_bin+1] = self.model.evalDistribution(mask)
+            output = self.smearer(unsmeared_output, first_bin, last_bin)
+            
+            # Rescale data to unsmeared model
+            unsmeared_data = numpy.zeros((len(self.data.x)))
+            unsmeared_error = numpy.zeros((len(self.data.x)))
+            unsmeared_data[first_bin:last_bin+1] = self.data.y[first_bin:last_bin+1]\
+                                                    * unsmeared_output[first_bin:last_bin+1]\
+                                                    / output[first_bin:last_bin+1]
+            unsmeared_error[first_bin:last_bin+1] = self.data.dy[first_bin:last_bin+1]\
+                                                    * unsmeared_output[first_bin:last_bin+1]\
+                                                    / output[first_bin:last_bin+1]
+            unsmeared_output=unsmeared_output[index]
+            unsmeared_data=unsmeared_data[index]
+            unsmeared_error=unsmeared_error
         else:
             output[index] = self.model.evalDistribution(self.data.x[index])
@@ -192 +206 @@
                       update_chisqr=self.update_chisqr,
                       source=self.source,
-                      unsmeared_model=output_unsmeared)
+                      unsmeared_model=unsmeared_output,
+                      unsmeared_data=unsmeared_data,
+                      unsmeared_error=unsmeared_error)
 
     def results(self):