r21904 - in /trunk: docs/latex/dispersion.tex specific_analyses/relax_disp/parameters.py -- December 09, 2013 - 14:15

Author: bugman
Date: Mon Dec  9 14:15:50 2013
New Revision: 21904

URL: http://svn.gna.org/viewcvs/relax?rev=21904&view=rev
Log:
Turned off the dw dispersion parameter constraints for the 'NS R1rho 3-site' 
models.


Modified:
    trunk/docs/latex/dispersion.tex
    trunk/specific_analyses/relax_disp/parameters.py

Modified: trunk/docs/latex/dispersion.tex
URL: 
http://svn.gna.org/viewcvs/relax/trunk/docs/latex/dispersion.tex?rev=21904&r1=21903&r2=21904&view=diff
==============================================================================
--- trunk/docs/latex/dispersion.tex (original)
+++ trunk/docs/latex/dispersion.tex Mon Dec  9 14:15:50 2013
@@ -1476,6 +1476,7 @@
 \end{subequations}
 
 Note that the $\dw$ and $\dwH$ constraints are not used for any of the 
MMQ-type models as sign differentiation is possible.
+These constraints are also turned off for the `NS $\Ronerho$ 3-site linear' 
and `NS $\Ronerho$ 3-site' models.
 And that the $\pA \geqslant 0.85$ constraint is used instead of the $\pA 
\geqslant 0.5$ constraint for all models which require $\pA \gg \pB$.
 When not using the auto-analysis, constraints can be modified or turned off.
 

Modified: trunk/specific_analyses/relax_disp/parameters.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/parameters.py?rev=21904&r1=21903&r2=21904&view=diff
==============================================================================
--- trunk/specific_analyses/relax_disp/parameters.py (original)
+++ trunk/specific_analyses/relax_disp/parameters.py Mon Dec  9 14:15:50 2013
@@ -598,7 +598,7 @@
 
         # Chemical exchange difference (dw >= 0).
         elif param_name in ['dw', 'dw_AB', 'dw_AC', 'dw_BC', 'dwH', 
'dwH_AB', 'dwH_AC', 'dwH_BC']:
-            if not spins[0].model in MODEL_LIST_MMQ:
+            if not spins[0].model in MODEL_LIST_MMQ + [MODEL_NS_R1RHO_3SITE, 
MODEL_NS_R1RHO_3SITE_LINEAR]:
                 A.append(zero_array * 0.0)
                 A[j][param_index] = 1.0
                 b.append(0.0)