r4638 - /branches/N_state_model/specific_fns/n_state_model.py -- January 11, 2008 - 11:48

Author: bugman
Date: Fri Jan 11 11:48:26 2008
New Revision: 4638

URL: http://svn.gna.org/viewcvs/relax?rev=4638&view=rev
Log:
Removed the param_vector arg to the linear_constraints() method.

This structure is not needed as cdp.params can be used instead.


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=4638&r1=4637&r2=4638&view=diff
==============================================================================
--- branches/N_state_model/specific_fns/n_state_model.py (original)
+++ branches/N_state_model/specific_fns/n_state_model.py Fri Jan 11 11:48:26 
2008
@@ -77,7 +77,7 @@
         self.minimise(min_algor='grid', constraints=constraints, 
verbosity=verbosity, sim_index=sim_index)
 
 
-    def linear_constraints(self, param_vector):
+    def linear_constraints(self):
         """Function for setting up the linear constraint matrices A and b.
 
         Standard notation
@@ -111,22 +111,20 @@
         This example is for a 3-state model.
 
 
-        @param param_vector:    The array of parameter names.
-        @type param_vector:     array of str
         @return:                The matrices A and b.
         @rtype:                 tuple of len 2 of a numpy matrix and numpy 
array
         """
+
+        # Alias the current data pipe.
+        cdp = relax_data_store[relax_data_store.current_pipe]
 
         # Initialisation (0..j..m).
         A = []
         b = []
-        n = len(param_vector)
+        n = len(cdp.params)
         zero_array = zeros(n, float64)
         i = 0
         j = 0
-
-        # Alias the current data pipe.
-        cdp = relax_data_store[relax_data_store.current_pipe]
 
         # Loop over the parameters.
         for k in xrange(len(cdp.params)):
@@ -189,7 +187,7 @@
 
         # Linear constraints.
         if constraints:
-            A, b = self.linear_constraints(param_vector)
+            A, b = self.linear_constraints()
 
         # Set up the class instance containing the target function.
         model = N_state_opt()