r25541 - /branches/est_par_error/test_suite/system_tests/relax_disp.py -- September 02, 2014 - 14:03

Author: tlinnet
Date: Tue Sep  2 14:03:31 2014
New Revision: 25541

URL: http://svn.gna.org/viewcvs/relax?rev=25541&view=rev
Log:
Modified systemtest, to minimise with BFGS, but it will fail.

task #7824(https://gna.org/task/index.php?7824): Model parameter ERROR 
estimation from Jacobian and Co-variance matrix of dispersion models.

Modified:
    branches/est_par_error/test_suite/system_tests/relax_disp.py

Modified: branches/est_par_error/test_suite/system_tests/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/est_par_error/test_suite/system_tests/relax_disp.py?rev=25541&r1=25540&r2=25541&view=diff
==============================================================================
--- branches/est_par_error/test_suite/system_tests/relax_disp.py        
(original)
+++ branches/est_par_error/test_suite/system_tests/relax_disp.py        Tue 
Sep  2 14:03:31 2014
@@ -7470,7 +7470,8 @@
             sim_boot = 50
 
             # Set algorithm.
-            min_algor = 'simplex'
+            #min_algor = 'simplex'
+            min_algor = 'BFGS'
             constraints = True
             if constraints:
                 min_options = ('%s'%(min_algor),)
@@ -7532,7 +7533,7 @@
 
                 # Init the Dispersion clas with data, so we can call 
functions in it.
                 tfunc = Dispersion(model=model, num_params=model_param_num, 
num_spins=num_spins, num_frq=field_count, exp_types=exp_types, 
values=values_err, 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, r1_fit=r1_fit)
-                results = generic_minimise(func=tfunc.func, args=(), 
x0=param_vector, min_algor=min_algor, min_options=min_options, A=A, b=b, 
full_output=True, print_flag=0)
+                results = generic_minimise(func=tfunc.func, 
dfunc=tfunc.dfunc, args=(), x0=param_vector, min_algor=min_algor, 
min_options=min_options, A=A, b=b, full_output=True, print_flag=0)
                 param_vector, chi2, iter_count, f_count, g_count, h_count, 
warning = results
 
                 # Get the parameters fitted in the model.