Author: bugman
Date: Wed Jan 23 21:35:53 2013
New Revision: 18282
URL: http://svn.gna.org/viewcvs/relax?rev=18282&view=rev
Log:
Bug fix for the N-state model Hessian d2func_standard() method.
An index variable name was incorrect causing the population model to fail
with Newton optimisation.
Modified:
trunk/maths_fns/n_state_model.py
Modified: trunk/maths_fns/n_state_model.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/maths_fns/n_state_model.py?rev=18282&r1=18281&r2=18282&view=diff
==============================================================================
--- trunk/maths_fns/n_state_model.py (original)
+++ trunk/maths_fns/n_state_model.py Wed Jan 23 21:35:53 2013
@@ -1122,20 +1122,20 @@
# Calculate the RDC Hessian component.
for j in range(self.num_interatom):
if self.fixed_tensors[align_index] and
self.rdc_flag[align_index] and not self.missing_Dij[align_index, j]:
- self.d2Dij_theta[pc_index, i*5+0, align_index,
j] = self.d2Dij_theta[align_index*5+0, pc_index, align_index, j] =
rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[0],
absolute=self.absolute_rdc[align_index, j])
- self.d2Dij_theta[pc_index, i*5+1, align_index,
j] = self.d2Dij_theta[align_index*5+1, pc_index, align_index, j] =
rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[1],
absolute=self.absolute_rdc[align_index, j])
- self.d2Dij_theta[pc_index, i*5+2, align_index,
j] = self.d2Dij_theta[align_index*5+2, pc_index, align_index, j] =
rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[2],
absolute=self.absolute_rdc[align_index, j])
- self.d2Dij_theta[pc_index, i*5+3, align_index,
j] = self.d2Dij_theta[align_index*5+3, pc_index, align_index, j] =
rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[3],
absolute=self.absolute_rdc[align_index, j])
- self.d2Dij_theta[pc_index, i*5+4, align_index,
j] = self.d2Dij_theta[align_index*5+4, pc_index, align_index, j] =
rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[4],
absolute=self.absolute_rdc[align_index, j])
+ self.d2Dij_theta[pc_index, align_index*5+0,
align_index, j] = self.d2Dij_theta[align_index*5+0, pc_index, align_index, j]
= rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[0],
absolute=self.absolute_rdc[align_index, j])
+ self.d2Dij_theta[pc_index, align_index*5+1,
align_index, j] = self.d2Dij_theta[align_index*5+1, pc_index, align_index, j]
= rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[1],
absolute=self.absolute_rdc[align_index, j])
+ self.d2Dij_theta[pc_index, align_index*5+2,
align_index, j] = self.d2Dij_theta[align_index*5+2, pc_index, align_index, j]
= rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[2],
absolute=self.absolute_rdc[align_index, j])
+ self.d2Dij_theta[pc_index, align_index*5+3,
align_index, j] = self.d2Dij_theta[align_index*5+3, pc_index, align_index, j]
= rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[3],
absolute=self.absolute_rdc[align_index, j])
+ self.d2Dij_theta[pc_index, align_index*5+4,
align_index, j] = self.d2Dij_theta[align_index*5+4, pc_index, align_index, j]
= rdc_tensor(self.dip_const[j], self.dip_vect[j, c], self.dA[4],
absolute=self.absolute_rdc[align_index, j])
# Calculate the PCS Hessian component.
for j in range(self.num_spins):
if self.fixed_tensors[align_index] and
self.pcs_flag[align_index] and not self.missing_deltaij[align_index, j]:
- self.d2deltaij_theta[pc_index, i*5+0,
align_index, j] = self.d2deltaij_theta[align_index*5+0, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[0])
- self.d2deltaij_theta[pc_index, i*5+1,
align_index, j] = self.d2deltaij_theta[align_index*5+1, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[1])
- self.d2deltaij_theta[pc_index, i*5+2,
align_index, j] = self.d2deltaij_theta[align_index*5+2, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[2])
- self.d2deltaij_theta[pc_index, i*5+3,
align_index, j] = self.d2deltaij_theta[align_index*5+3, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[3])
- self.d2deltaij_theta[pc_index, i*5+4,
align_index, j] = self.d2deltaij_theta[align_index*5+4, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[4])
+ self.d2deltaij_theta[pc_index, align_index*5+0,
align_index, j] = self.d2deltaij_theta[align_index*5+0, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[0])
+ self.d2deltaij_theta[pc_index, align_index*5+1,
align_index, j] = self.d2deltaij_theta[align_index*5+1, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[1])
+ self.d2deltaij_theta[pc_index, align_index*5+2,
align_index, j] = self.d2deltaij_theta[align_index*5+2, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[2])
+ self.d2deltaij_theta[pc_index, align_index*5+3,
align_index, j] = self.d2deltaij_theta[align_index*5+3, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[3])
+ self.d2deltaij_theta[pc_index, align_index*5+4,
align_index, j] = self.d2deltaij_theta[align_index*5+4, pc_index,
align_index, j] = pcs_tensor(self.pcs_const[align_index, j, c],
self.paramag_unit_vect[j, c], self.dA[4])
# Construct the paramagnetic centre c partial derivative
components for the PCS.
if not self.centre_fixed:
r18282 - /trunk/maths_fns/n_state_model.py