r14162 - /branches/gui_testing/auto_analyses/dauvergne_protocol.py -- August 05, 2011 - 10:13

Author: bugman
Date: Fri Aug  5 10:13:48 2011
New Revision: 14162

URL: http://svn.gna.org/viewcvs/relax?rev=14162&view=rev
Log:
Fix for the dauvergne_protocol auto-analysis 'final' model.

The final stage of the dauvergne_protocol was broken.  The data pipes here 
need to be created rather
than copied from the initial data pipe as results are being read into these 
pipes.


Modified:
    branches/gui_testing/auto_analyses/dauvergne_protocol.py

Modified: branches/gui_testing/auto_analyses/dauvergne_protocol.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/gui_testing/auto_analyses/dauvergne_protocol.py?rev=14162&r1=14161&r2=14162&view=diff
==============================================================================
--- branches/gui_testing/auto_analyses/dauvergne_protocol.py (original)
+++ branches/gui_testing/auto_analyses/dauvergne_protocol.py Fri Aug  5 
10:13:48 2011
@@ -622,9 +622,8 @@
                 if name not in dir_list:
                     raise RelaxError("The %s model must be optimised first." 
% name)
 
-            # Create the local_tm data pipe by copying.
-            self.interpreter.pipe.copy(self.pipe_name, 'local_tm')
-            self.interpreter.pipe.switch('local_tm')
+            # Create the local_tm data pipe.
+            self.interpreter.pipe.create('local_tm', 'mf')
 
             # Load the local tm diffusion model MI results.
             self.interpreter.results.read(file='results', 
dir=self.results_dir+'local_tm'+sep+'aic')
@@ -644,9 +643,8 @@
                     # Throw an error to prevent misuse of the script.
                     raise RelaxError("Multiple rounds of optimisation of the 
" + name + " (between 8 to 15) are required for the proper execution of this 
script.")
 
-                # Create the data pipe by copying.
-                self.interpreter.pipe.copy(self.pipe_name, model)
-                self.interpreter.pipe.switch(model)
+                # Create the data pipe.
+                self.interpreter.pipe.create(model, 'mf')
 
                 # Load the diffusion model results.
                 self.interpreter.results.read(file='results', 
dir=self.results_dir+model + sep+'round_'+repr(self.round)+sep+'opt')