Changes in / [a3b7542:1c98850] in sasview

Location:

src/sas/qtgui

Files:

• MainWindow/DataExplorer.py (modified) (3 diffs)
• Utilities/GuiUtils.py (modified) (3 diffs)

src/sas/qtgui/MainWindow/DataExplorer.py

@@ -488 +488 @@
             params = value['fit_params']
             for page in params:
+                if not isinstance(page, dict):
+                    continue
+                if 'is_batch_fitting' not in page:
+                    continue
                 if page['is_batch_fitting'][0] != 'True':
                     continue
@@ -551 +555 @@
             if isinstance(new_data, (old_data1d, old_data2d)):
                 new_data = self.manager.create_gui_data(value[0], new_data.filename)
+            if hasattr(value[0], 'id'):
+                new_data.id = value[0].id
+                new_data.group_id = value[0].group_id
             assert isinstance(new_data, (Data1D, Data2D))
             # make sure the ID is retained
-            new_data.id = value[0].id
-            new_data.group_id = value[0].group_id
             properties = value[1]
             is_checked = properties['checked']
@@ -561 +566 @@
             items.append(new_item)
             model = self.theory_model
-            if value[0].is_data:
+            if new_data.is_data:
                 model = self.model
                 # Caption for the theories

src/sas/qtgui/Utilities/GuiUtils.py

@@ -1388 +1388 @@
         for p in params.parameters:
             p_name = p[1]
-            param_dict[p_name] = [str(p[0]), str(p[2]), None, str(p[5][1]), str(p[6][1])]
+            param_dict[p_name] = [str(p[0]), str(p[2]), None, str(p[5][1]), str(p[6][1]), []]
         # orientation parameters
         if params.is_2D:
@@ -1399 +1399 @@
                 if p[6][1] != "":
                     p_max = p[6][1]
-                param_dict[p_name] = [str(p[0]), str(p[2]), None, p_min, p_max]
+                param_dict[p_name] = [str(p[0]), str(p[2]), None, p_min, p_max, []]
 
         # disperse parameters
@@ -1426 +1426 @@
                 param_dict[p_name] = [p_opt, p_width, p_min, p_max, p_npts, p_nsigmas, p_disp]
 
+        param_dict['is_batch_fitting'] = ['False']
         content[params.data_id]['fit_params'] = param_dict
+
     return content