r11292 - /1.3/specific_fns/n_state_model.py -- July 08, 2010 - 11:49

Author: bugman
Date: Thu Jul  8 11:49:35 2010
New Revision: 11292

URL: http://svn.gna.org/viewcvs/relax?rev=11292&view=rev
Log:
Better support for the optimisation and mapping of the Ln3+ position.

The position is now treated in Angstrom, and is properly scaled.  A few 
additional API methods have
been added for the mapping of the optimisation space, and a few modified to 
support the Ln3+
position.




Modified:
    1.3/specific_fns/n_state_model.py

Modified: 1.3/specific_fns/n_state_model.py
URL: 
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/n_state_model.py?rev=11292&r1=11291&r2=11292&view=diff
==============================================================================
--- 1.3/specific_fns/n_state_model.py (original)
+++ 1.3/specific_fns/n_state_model.py Thu Jul  8 11:49:35 2010
@@ -61,6 +61,7 @@
 
         # Place methods into the API.
         self.overfit_deselect = self._overfit_deselect_dummy
+        self.return_conversion_factor = self._return_no_conversion_factor
         self.test_grid_ops = self._test_grid_ops_general
 
 
@@ -175,16 +176,20 @@
         if ('rdc' in data_types or 'pcs' in data_types) and not 
(hasattr(cdp.align_tensors, 'fixed') and cdp.align_tensors.fixed):
             pop_start = pop_start + 5*len(cdp.align_ids)
 
+        # The alignment parameters.
+        for i in range(5*len(cdp.align_ids)):
+            scaling_matrix[i, i] = 1e-4
+
         # Loop over the populations, and set the scaling factor.
         if cdp.model in ['2-domain', 'population']:
-            factor = 100.0
+            factor = 0.1
             for i in xrange(pop_start, pop_start + (cdp.N-1)):
                 scaling_matrix[i, i] = factor
 
         # The paramagnetic centre.
         if hasattr(cdp, 'paramag_centre_fixed') and not 
cdp.paramag_centre_fixed:
             for i in range(-3, 0):
-                scaling_matrix[i, i] = 1e10
+                scaling_matrix[i, i] = 1e2
 
         # Return the matrix.
         return scaling_matrix
@@ -1674,8 +1679,8 @@
 
                 # The paramagnetic centre.
                 elif hasattr(cdp, 'paramag_centre_fixed') and not 
cdp.paramag_centre_fixed and (n - i) <= 3:
-                    lower.append(-100e-10)
-                    upper.append(100e-10)
+                    lower.append(-100)
+                    upper.append(100)
 
                 # Otherwise this must be an alignment tensor component.
                 else:
@@ -1683,7 +1688,7 @@
                     upper.append(1e-3)
 
         # Minimisation.
-        self.minimise(min_algor='grid', min_options=[inc, lower, upper], 
constraints=constraints, verbosity=verbosity, sim_index=sim_index)
+        self.minimise(min_algor='grid', lower=lower, upper=upper, inc=inc, 
constraints=constraints, verbosity=verbosity, sim_index=sim_index)
 
 
     def is_spin_param(self, name):
@@ -1701,6 +1706,22 @@
 
         # All other parameters are global.
         return False
+
+
+    def map_bounds(self, param, spin_id=None):
+        """Create bounds for the OpenDX mapping function.
+
+        @param param:       The name of the parameter to return the lower 
and upper bounds of.
+        @type param:        str
+        @param spin_id:     The spin identification string (unused).
+        @type spin_id:      None
+        @return:            The upper and lower bounds of the parameter.
+        @rtype:             list of float
+        """
+
+        # Paramagnetic centre.
+        if search('^paramag_[xyz]$', param):
+            return [-100.0, 100.0]
 
 
     def minimise(self, min_algor=None, min_options=None, func_tol=None, 
grad_tol=None, max_iterations=None, constraints=False, scaling=True, 
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
@@ -1767,7 +1788,14 @@
 
         # Grid search.
         if search('^[Gg]rid', min_algor):
-            results = grid(func=model.func, args=(), 
num_incs=min_options[0], lower=min_options[1], upper=min_options[2], A=A, 
b=b, verbosity=verbosity)
+            # Scaling.
+            if scaling:
+                for i in xrange(len(param_vector)):
+                    lower[i] = lower[i] / scaling_matrix[i, i]
+                    upper[i] = upper[i] / scaling_matrix[i, i]
+
+            # The search.
+            results = grid(func=model.func, args=(), num_incs=inc, 
lower=lower, upper=upper, A=A, b=b, verbosity=verbosity)
 
             # Unpack the results.
             param_vector, func, iter_count, warning = results
@@ -2043,6 +2071,23 @@
                 obj = getattr(cdp, obj_name)
                 obj[index] = value[i]
 
+            # The paramagnetic centre.
+            if search('^paramag_[xyz]$', obj_name):
+                # Init.
+                if not hasattr(cdp, 'paramagnetic_centre'):
+                    cdp.paramagnetic_centre = zeros(3, float64)
+
+                # Set the coordinate.
+                if obj_name == 'paramag_x':
+                    index = 0
+                elif obj_name == 'paramag_y':
+                    index = 1
+                else:
+                    index = 2
+
+                # Set the value in Angstrom.
+                cdp.paramagnetic_centre[index] = value[i]
+
             # Set the spin parameters.
             else:
                 for spin in spin_loop(spin_id):