r4519 - /branches/N_state_model/specific_fns/n_state_model.py -- January 09, 2008 - 10:20

Author: bugman
Date: Wed Jan  9 10:20:19 2008
New Revision: 4519

URL: http://svn.gna.org/viewcvs/relax?rev=4519&view=rev
Log:
Added code to fetch the initial parameter vector.


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=4519&r1=4518&r2=4519&view=diff
==============================================================================
--- branches/N_state_model/specific_fns/n_state_model.py (original)
+++ branches/N_state_model/specific_fns/n_state_model.py Wed Jan  9 10:20:19 
2008
@@ -97,6 +97,9 @@
         @type sim_index:        None or int
         """
 
+        # Create the initial parameter vector.
+        param_vector = self.assemble_param_vector(sim_index=sim_index)
+
         # Set up the class instance containing the target function.
         model = N_state_opt()
 
@@ -108,12 +111,12 @@
 
         # Minimisation.
         if constraints:
-            results = generic_minimise(func=model.func, args=(), 
x0=self.param_vector, min_algor=min_algor, min_options=min_options, 
func_tol=func_tol, grad_tol=grad_tol, maxiter=max_iterations, A=A, b=b, 
full_output=1, print_flag=print_flag)
+            results = generic_minimise(func=model.func, args=(), 
x0=param_vector, min_algor=min_algor, min_options=min_options, 
func_tol=func_tol, grad_tol=grad_tol, maxiter=max_iterations, A=A, b=b, 
full_output=1, print_flag=print_flag)
         else:
-            results = generic_minimise(func=model.func, args=(), 
x0=self.param_vector, min_algor=min_algor, min_options=min_options, 
func_tol=func_tol, grad_tol=grad_tol, maxiter=max_iterations, full_output=1, 
print_flag=print_flag)
+            results = generic_minimise(func=model.func, args=(), 
x0=param_vector, min_algor=min_algor, min_options=min_options, 
func_tol=func_tol, grad_tol=grad_tol, maxiter=max_iterations, full_output=1, 
print_flag=print_flag)
         if results == None:
             return
-        self.param_vector, self.func, self.iter_count, self.f_count, 
self.g_count, self.h_count, self.warning = results
+        param_vector, func, iter_count, f_count, g_count, h_count, warning = 
results
 
 
     def return_data_name(self, name):