r26329 - /trunk/specific_analyses/n_state_model/api.py -- October 21, 2014 - 17:56

Author: bugman
Date: Tue Oct 21 17:56:08 2014
New Revision: 26329

URL: http://svn.gna.org/viewcvs/relax?rev=26329&view=rev
Log:
Bug fix for the N-state model grid search when only alignment tensor 
parameters are optimised.

The algorithm for splitting up the grid search to optimise each tensor 
separately, hence massively
collapsing the dimensionality of the problem, was being performed 
incorrectly.  The grid_search()
API method inc, lower, and upper arguments are lists of lists, but were only 
being treated as lists.


Modified:
    trunk/specific_analyses/n_state_model/api.py

Modified: trunk/specific_analyses/n_state_model/api.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/n_state_model/api.py?rev=26329&r1=26328&r2=26329&view=diff
==============================================================================
--- trunk/specific_analyses/n_state_model/api.py        (original)
+++ trunk/specific_analyses/n_state_model/api.py        Tue Oct 21 17:56:08 
2014
@@ -321,11 +321,11 @@
         """The grid search function.
 
         @param lower:           The lower bounds of the grid search which 
must be equal to the number of parameters in the model.
-        @type lower:            array of numbers
+        @type lower:            list of lists of floats
         @param upper:           The upper bounds of the grid search which 
must be equal to the number of parameters in the model.
-        @type upper:            array of numbers
+        @type upper:            list of lists of floats
         @param inc:             The increments for each dimension of the 
space for the grid search.  The number of elements in the array must equal to 
the number of parameters in the model.
-        @type inc:              array of int
+        @type inc:              list of lists of int
         @keyword scaling_matrix:    The per-model list of diagonal and 
square scaling matrices.
         @type scaling_matrix:       list of numpy rank-2, float64 array or 
list of None
         @param constraints:     If True, constraints are applied during the 
grid search (elinating parts of the grid).  If False, no constraints are used.
@@ -377,12 +377,12 @@
                 tensor.set('fixed', False)
 
                 # Grid search parameter subsets.
-                lower_sub = lower[i*5:i*5+5]
-                upper_sub = upper[i*5:i*5+5]
-                inc_sub = inc[i*5:i*5+5]
+                lower_sub = lower[0][i*5:i*5+5]
+                upper_sub = upper[0][i*5:i*5+5]
+                inc_sub = inc[0][i*5:i*5+5]
 
                 # Minimisation of the sub-grid.
-                self.minimise(min_algor='grid', lower=lower_sub, 
upper=upper_sub, inc=inc_sub, constraints=constraints, verbosity=verbosity, 
sim_index=sim_index)
+                self.minimise(min_algor='grid', lower=[lower_sub], 
upper=[upper_sub], inc=[inc_sub], scaling_matrix=[None], 
constraints=constraints, verbosity=verbosity, sim_index=sim_index)
 
                 # Fix the tensor again.
                 tensor.set('fixed', True)