Changes in src/sas/sasgui/perspectives/fitting/fitting.py [0900627:2d9526d] in sasview

File:

• src/sas/sasgui/perspectives/fitting/fitting.py (modified) (5 diffs)

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

@@ -1326 +1326 @@
 
                 is_data2d = issubclass(data.__class__, Data2D)
-                # Check consistency of arrays
+                #check consistency of arrays
                 if not is_data2d:
                     if len(res.theory) == len(res.index[res.index]) and \
@@ -1337 +1337 @@
                     new_theory[res.index == False] = np.nan
                     correct_result = True
-                # Get all fittable parameters of the current model
+                #get all fittable parameters of the current model
                 param_list = model.getParamList()
                 for param in model.getDispParamList():
-                    if '.' in param and param in param_list:
-                        # Ensure polydispersity results are displayed
-                        p1, p2 = param.split('.')
-                        if not model.is_fittable(p1) and not (p2 == 'width' and param in res.param_list)\
-                            and param in param_list:
-                            param_list.remove(param)
-                    elif not model.is_fittable(param) and \
+                    if not model.is_fittable(param) and \
                         param in param_list:
                         param_list.remove(param)
@@ -1367 +1361 @@
                     batch_outputs["Chi2"].append(ERROR)
                     for param in param_list:
-                        # Save value of  fixed parameters
+                        # save value of  fixed parameters
                         if param not in res.param_list:
                             batch_outputs[str(param)].append(ERROR)
                         else:
-                            # Save only fitted values
+                            #save only fitted values
                             batch_outputs[param].append(ERROR)
                             batch_inputs["error on %s" % str(param)].append(ERROR)
@@ -1748 +1742 @@
             @param unsmeared_error: data error, rescaled to unsmeared model
         """
-
         number_finite = np.count_nonzero(np.isfinite(y))
         np.nan_to_num(y)
@@ -1754 +1747 @@
                                          data_description=model.name,
                                          data_id=str(page_id) + " " + data.name)
+        plots_to_update = [] # List of plottables that have changed since last calculation
+        # Create the new theories
         if unsmeared_model is not None:
-            self.create_theory_1D(x, unsmeared_model, page_id, model, data, state,
+            unsmeared_model_plot = self.create_theory_1D(x, unsmeared_model, 
+                                  page_id, model, data, state,
                                   data_description=model.name + " unsmeared",
                                   data_id=str(page_id) + " " + data.name + " unsmeared")
+            plots_to_update.append(unsmeared_model_plot)
 
             if unsmeared_data is not None and unsmeared_error is not None:
-                self.create_theory_1D(x, unsmeared_data, page_id, model, data, state,
+                unsmeared_data_plot = self.create_theory_1D(x, unsmeared_data, 
+                                      page_id, model, data, state,
                                       data_description="Data unsmeared",
                                       data_id="Data  " + data.name + " unsmeared",
                                       dy=unsmeared_error)
-        # Comment this out until we can get P*S models with correctly populated parameters
-        #if sq_model is not None and pq_model is not None:
-        #    self.create_theory_1D(x, sq_model, page_id, model, data, state,
-        #                          data_description=model.name + " S(q)",
-        #                          data_id=str(page_id) + " " + data.name + " S(q)")
-        #    self.create_theory_1D(x, pq_model, page_id, model, data, state,
-        #                          data_description=model.name + " P(q)",
-        #                          data_id=str(page_id) + " " + data.name + " P(q)")
+                plots_to_update.append(unsmeared_data_plot)
+        if sq_model is not None and pq_model is not None:
+            sq_id = str(page_id) + " " + data.name + " S(q)"
+            sq_plot = self.create_theory_1D(x, sq_model, page_id, model, data, state,
+                                  data_description=model.name + " S(q)",
+                                  data_id=sq_id)
+            plots_to_update.append(sq_plot)
+            pq_id = str(page_id) + " " + data.name + " P(q)"
+            pq_plot = self.create_theory_1D(x, pq_model, page_id, model, data, state,
+                                  data_description=model.name + " P(q)",
+                                  data_id=pq_id)
+            plots_to_update.append(pq_plot)
+        # Update the P(Q), S(Q) and unsmeared theory plots if they exist
+        wx.PostEvent(self.parent, NewPlotEvent(plots=plots_to_update, 
+                                              action='update'))
 
         current_pg = self.fit_panel.get_page_by_id(page_id)