r25147 - /trunk/specific_analyses/relax_disp/optimisation.py -- August 21, 2014 - 09:57

Author: bugman
Date: Thu Aug 21 09:57:28 2014
New Revision: 25147

URL: http://svn.gna.org/viewcvs/relax?rev=25147&view=rev
Log:
The dispersion back_calc_r2eff() function can now handle the dynamic R1 
parameter.

This required a call to r1_setup() to add or remove the parameter, and 
is_r1_optimised() to obtain
the r1_fit flag to be sent into the target function class.

Modified:
    trunk/specific_analyses/relax_disp/optimisation.py

Modified: trunk/specific_analyses/relax_disp/optimisation.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/optimisation.py?rev=25147&r1=25146&r2=25147&view=diff
==============================================================================
--- trunk/specific_analyses/relax_disp/optimisation.py  (original)
+++ trunk/specific_analyses/relax_disp/optimisation.py  Thu Aug 21 09:57:28 
2014
@@ -141,8 +141,10 @@
     values, errors, missing, frqs, frqs_H, exp_types, relax_times = 
return_r2eff_arrays(spins=[spin], spin_ids=[spin_id], fields=fields, 
field_count=field_count)
 
     # The offset and R1 data.
+    r1_setup()
     offsets, spin_lock_fields_inter, chemical_shifts, tilt_angles, 
Delta_omega, w_eff = return_offset_data(spins=[spin], spin_ids=[spin_id], 
field_count=field_count, spin_lock_offset=spin_lock_offset, 
fields=spin_lock_nu1)
     r1 = return_r1_data(spins=[spin], spin_ids=[spin_id], 
field_count=field_count)
+    r1_fit = is_r1_optimised(spin.model)
 
     # The dispersion data.
     recalc_tau = True
@@ -206,7 +208,7 @@
                         missing[ei][si][mi].append(zeros(num, int32))
 
     # Initialise the relaxation dispersion fit functions.
-    model = Dispersion(model=spin.model, num_params=param_num(spins=[spin]), 
num_spins=1, num_frq=field_count, exp_types=exp_types, values=values, 
errors=errors, missing=missing, frqs=frqs, frqs_H=frqs_H, 
cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1, 
chemical_shifts=chemical_shifts, offset=offsets, tilt_angles=tilt_angles, 
r1=r1, relax_times=relax_times, recalc_tau=recalc_tau)
+    model = Dispersion(model=spin.model, num_params=param_num(spins=[spin]), 
num_spins=1, num_frq=field_count, exp_types=exp_types, values=values, 
errors=errors, missing=missing, frqs=frqs, frqs_H=frqs_H, 
cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1, 
chemical_shifts=chemical_shifts, offset=offsets, tilt_angles=tilt_angles, 
r1=r1, relax_times=relax_times, recalc_tau=recalc_tau, r1_fit=r1_fit)
 
     # Make a single function call.  This will cause back calculation and the 
data will be stored in the class instance.
     chi2 = model.func(param_vector)