r21423 - /trunk/target_functions/n_state_model.py -- November 13, 2013 - 15:33

Author: bugman
Date: Wed Nov 13 15:33:18 2013
New Revision: 21423

URL: http://svn.gna.org/viewcvs/relax?rev=21423&view=rev
Log:
A RelaxError is now raised for the N-state model optimisation with gradients 
when T = J+D data is used.

The gradients for this data type are not implemented yet, so it is better to 
prevent the user from
using this.


Modified:
    trunk/target_functions/n_state_model.py

Modified: trunk/target_functions/n_state_model.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/target_functions/n_state_model.py?rev=21423&r1=21422&r2=21423&view=diff
==============================================================================
--- trunk/target_functions/n_state_model.py (original)
+++ trunk/target_functions/n_state_model.py Wed Nov 13 15:33:18 2013
@@ -951,6 +951,10 @@
                             self.drdc_theta[align_index*5+3, align_index, j] 
= ave_rdc_tensor_dDij_dAmn(self.dip_const[j], self.dip_vect[j], self.N, 
self.dA[3], weights=self.probs)
                             self.drdc_theta[align_index*5+4, align_index, j] 
= ave_rdc_tensor_dDij_dAmn(self.dip_const[j], self.dip_vect[j], self.N, 
self.dA[4], weights=self.probs)
 
+                        # Add the J coupling to convert into the 
back-calculated T = J+D value.
+                        if self.T_flags[align_index, j]:
+                            raise RelaxError("Gradients for T = J+D data 
have not been implemented yet.")
+
             # Construct the Amn partial derivative components for the PCS.
             if not self.fixed_tensors[align_index]:
                 for j in range(self.num_spins):