r11165 - /1.3/specific_fns/n_state_model.py -- April 28, 2010 - 17:50

Author: bugman
Date: Wed Apr 28 17:50:40 2010
New Revision: 11165

URL: http://svn.gna.org/viewcvs/relax?rev=11165&view=rev
Log:
Another fix for _update_model().

This was introduced in the last change.  The alignment tensors are only 
updated if alignment data
is loaded.


Modified:
    1.3/specific_fns/n_state_model.py

Modified: 1.3/specific_fns/n_state_model.py
URL: 
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/n_state_model.py?rev=11165&r1=11164&r2=11165&view=diff
==============================================================================
--- 1.3/specific_fns/n_state_model.py (original)
+++ 1.3/specific_fns/n_state_model.py Wed Apr 28 17:50:40 2010
@@ -1356,20 +1356,21 @@
         data_types = self._base_data_types()
 
         # Set up tensors for each alignment.
-        for id in cdp.align_ids:
-            # No tensors initialised.
-            if not hasattr(cdp, 'align_tensors'):
-                generic_fns.align_tensor.init(tensor=id, params=[0.0, 0.0, 
0.0, 0.0, 0.0])
-
-            # Find if the tensor corresponding to the id exists.
-            exists = False
-            for tensor in cdp.align_tensors:
-                if id == tensor.name:
-                    exists = True
-
-            # Initialise the tensor.
-            if not exists:
-                generic_fns.align_tensor.init(tensor=id, params=[0.0, 0.0, 
0.0, 0.0, 0.0])
+        if hasattr(cdp, 'align_ids'):
+            for id in cdp.align_ids:
+                # No tensors initialised.
+                if not hasattr(cdp, 'align_tensors'):
+                    generic_fns.align_tensor.init(tensor=id, params=[0.0, 
0.0, 0.0, 0.0, 0.0])
+
+                # Find if the tensor corresponding to the id exists.
+                exists = False
+                for tensor in cdp.align_tensors:
+                    if id == tensor.name:
+                        exists = True
+
+                # Initialise the tensor.
+                if not exists:
+                    generic_fns.align_tensor.init(tensor=id, params=[0.0, 
0.0, 0.0, 0.0, 0.0])
 
 
     def calculate(self, spin_id=None, verbosity=1, sim_index=None):