r25145 - /trunk/auto_analyses/relax_disp.py -- August 21, 2014 - 09:57

Author: bugman
Date: Thu Aug 21 09:57:24 2014
New Revision: 25145

URL: http://svn.gna.org/viewcvs/relax?rev=25145&view=rev
Log:
The dispersion auto-analysis now handles the optional R1 parameter correctly.

The value.set user function was no longer setting the R1 parameter to the 
default value when the
grid search was deactivated, as it is no longer in MODEL_PARAMS.  So instead 
the new
is_r1_optimised() function is being used to decide if the value.set user 
function should set the
'r1' parameter value.

Modified:
    trunk/auto_analyses/relax_disp.py

Modified: trunk/auto_analyses/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/auto_analyses/relax_disp.py?rev=25145&r1=25144&r2=25145&view=diff
==============================================================================
--- trunk/auto_analyses/relax_disp.py   (original)
+++ trunk/auto_analyses/relax_disp.py   Thu Aug 21 09:57:24 2014
@@ -37,7 +37,7 @@
 from pipe_control.mol_res_spin import return_spin, spin_loop
 from pipe_control.pipes import has_pipe
 from prompt.interpreter import Interpreter
-from specific_analyses.relax_disp.data import has_exponential_exp_type, 
has_cpmg_exp_type, has_fixed_time_exp_type, has_r1rho_exp_type, loop_frq
+from specific_analyses.relax_disp.data import has_exponential_exp_type, 
has_cpmg_exp_type, has_fixed_time_exp_type, has_r1rho_exp_type, 
is_r1_optimised, loop_frq
 from specific_analyses.relax_disp.data import INTERPOLATE_DISP, 
INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, 
Y_AXIS_R2_EFF
 from specific_analyses.relax_disp.model import convert_no_rex, 
nesting_model, nesting_param
 from specific_analyses.relax_disp.variables import EQ_ANALYTIC, EQ_NUMERIC, 
EQ_SILICO, MODEL_LIST_ANALYTIC, MODEL_LIST_NEST, MODEL_LIST_NUMERIC, 
MODEL_LIST_R1RHO, MODEL_LIST_R1RHO_FULL, MODEL_NOREX, MODEL_NOREX_R1RHO, 
MODEL_PARAMS, MODEL_R2EFF, PARAMS_R20
@@ -436,8 +436,13 @@
 
                 # Default values.
                 else:
+                    # The standard parameters.
                     for param in MODEL_PARAMS[model]:
                         self.interpreter.value.set(param=param, index=None)
+
+                    # The optional R1 parameter.
+                    if is_r1_optimised(model=model):
+                        self.interpreter.value.set(param='r1', index=None)
 
         # Minimise.
         do_minimise = False