r19888 - /branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py -- June 06, 2013 - 14:20

Author: bugman
Date: Thu Jun  6 14:20:50 2013
New Revision: 19888

URL: http://svn.gna.org/viewcvs/relax?rev=19888&view=rev
Log:
Fix for the Relax_disp.test_exp_fit system test.

Now this checks the fitting of exponential curves without using the 
auto-analysis - the
auto-analysis is an overkill.


Modified:
    branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py

Modified: 
branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py?rev=19888&r1=19887&r2=19888&view=diff
==============================================================================
--- branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py 
(original)
+++ branches/relax_disp/test_suite/system_tests/scripts/relax_disp/exp_fit.py 
Thu Jun  6 14:20:50 2013
@@ -80,13 +80,22 @@
 relax_disp.cluster(cluster_id='test', spin_id=':1')
 relax_disp.cluster(cluster_id='cluster', spin_id=':1,3@N')
 
+# Error analysis.
+spectrum.error_analysis(subset=['nu_1kHz_relaxT_0.01', 
'nu_1kHz_relaxT_0.02', 'nu_1kHz_relaxT_0.04', 'nu_1kHz_relaxT_0.06', 
'nu_1kHz_relaxT_0.08', 'nu_1kHz_relaxT_0.10', 'nu_1kHz_relaxT_0.12', 
'nu_2kHz_relaxT_0.01', 'nu_2kHz_relaxT_0.02', 'nu_2kHz_relaxT_0.04', 
'nu_2kHz_relaxT_0.06', 'nu_2kHz_relaxT_0.08', 'nu_2kHz_relaxT_0.10', 
'nu_2kHz_relaxT_0.12'])
 
+# Set the model.
+relax_disp.select_model(model='R2eff')
 
-# Auto-analysis execution.
-##########################
+# Low precision optimisation.
+grid_search(inc=3, constraints=True, verbosity=1)
+minimise(min_algor='simplex', line_search=None, hessian_mod=None, 
hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, 
constraints=True, scaling=True, verbosity=1)
 
-# Do not change!
-Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, 
results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM)
+# Monte Carlo simulations.
+monte_carlo.setup(number=3)
+monte_carlo.create_data(method='back_calc')
+monte_carlo.initial_values()
+minimise(min_algor='simplex', func_tol=1e-25, grad_tol=None, 
max_iter=10000000, constraints=True, scaling=True, verbosity=1)
+monte_carlo.error_analysis()
 
 # Save the program state.
 state.save('devnull', force=True)