r19471 - /branches/relax_disp/specific_analyses/relax_disp.py -- April 11, 2013 - 19:01

Author: bugman
Date: Thu Apr 11 19:01:06 2013
New Revision: 19471

URL: http://svn.gna.org/viewcvs/relax?rev=19471&view=rev
Log:
Fixes for the spin clustering for relaxation dispersion.

Both optimisation and Monte Carlo simulations were affected by these bugs.


Modified:
    branches/relax_disp/specific_analyses/relax_disp.py

Modified: branches/relax_disp/specific_analyses/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp.py?rev=19471&r1=19470&r2=19471&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp.py Thu Apr 11 19:01:06 
2013
@@ -984,7 +984,7 @@
             spin_index = int(index / 2 / cdp.curve_count)
 
             # The curve index and key.
-            exp_index = int((index - spin_index * 2) / 2)
+            exp_index = int((index - spin_index * cdp.curve_count * 2) / 2)
             curve_key = self._exp_curve_key_from_index(exp_index)
 
         # All other parameters.
@@ -1298,7 +1298,7 @@
             # Get the grid search minimisation options.
             lower_new, upper_new = None, None
             if match('^[Gg]rid', min_algor):
-                grid_size, inc, lower_new, upper_new, sparseness = 
self._grid_search_setup(spins=spins, param_vector=param_vector, lower=lower, 
upper=upper, inc=inc, scaling_matrix=scaling_matrix)
+                grid_size, inc_new, lower_new, upper_new, sparseness = 
self._grid_search_setup(spins=spins, param_vector=param_vector, lower=lower, 
upper=upper, inc=inc, scaling_matrix=scaling_matrix)
 
             # Linear constraints.
             A, b = None, None
@@ -1322,7 +1322,7 @@
 
             # Grid search.
             if search('^[Gg]rid', min_algor):
-                results = grid(func=model.func, args=(), num_incs=inc, 
lower=lower_new, upper=upper_new, A=A, b=b, sparseness=sparseness, 
verbosity=verbosity)
+                results = grid(func=model.func, args=(), num_incs=inc_new, 
lower=lower_new, upper=upper_new, A=A, b=b, sparseness=sparseness, 
verbosity=verbosity)
 
                 # Unpack the results.
                 param_vector, chi2, iter_count, warning = results