r4805 - /branches/N_state_model/specific_fns/n_state_model.py -- January 17, 2008 - 10:38

Author: bugman
Date: Thu Jan 17 10:38:55 2008
New Revision: 4805

URL: http://svn.gna.org/viewcvs/relax?rev=4805&view=rev
Log:
Completed the assemble_param_vector() method.


Modified:
    branches/N_state_model/specific_fns/n_state_model.py

Modified: branches/N_state_model/specific_fns/n_state_model.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/N_state_model/specific_fns/n_state_model.py?rev=4805&r1=4804&r2=4805&view=diff
==============================================================================
--- branches/N_state_model/specific_fns/n_state_model.py (original)
+++ branches/N_state_model/specific_fns/n_state_model.py Thu Jan 17 10:38:55 
2008
@@ -38,16 +38,40 @@
     """Class containing functions for the N-state model."""
 
     def assemble_param_vector(self, sim_index):
-        """Assemble all the parameters of the model into a single array."""
-
-        # Initialise.
-        param_vector = []
-
-        # Alias the current data pipe.
-        cdp = relax_data_store[relax_data_store.current_pipe]
-
-        # The probabilities.
-        #for i in xrange(len(cdp.align
+        """Assemble all the parameters of the model into a single array.
+
+        @param sim_index:       The index of the simulation to optimise.  
This should be None if
+                                normal optimisation is desired.
+        @type sim_index:        None or int
+        @return:                The parameter vector used for optimisation.
+        @rtype:                 numpy array
+        """
+
+        # Alias the current data pipe.
+        cdp = relax_data_store[relax_data_store.current_pipe]
+
+        # Monte Carlo simulation data structures.
+        if sim_index != None:
+            probs = cdp.probs_sim[sim_index]
+            alpha = cdp.alpha_sim[sim_index]
+            beta = cdp.beta_sim[sim_index]
+            gamma = cdp.gamma_sim[sim_index]
+
+        # Normal data structures.
+        else:
+            probs = cdp.probs
+            alpha = cdp.alpha
+            beta = cdp.beta
+            gamma = cdp.gamma
+
+        # The probabilities (exclude that of state N).
+        param_vector = probs[0:-2]
+
+        # The Euler angles.
+        for i in xrange(cdp.N):
+            param_vector.append(alpha[i])
+            param_vector.append(beta[i])
+            param_vector.append(gamma[i])
 
         # Return a numpy arrary.
         return array(param_vector, float64)