Hi Edward. When I run: ./relax -s Relax_disp.test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp I get: ------------------- Parameter values: [2.4392597217423719, 149801.17120634759] Function value: 252.36349493927844 Iterations: 135 Function calls: 281 Gradient calls: 0 Hessian calls: 0 Warning: None relax> eliminate(function=None, args=None) relax> monte_carlo.setup(number=5) relax> monte_carlo.create_data(method='back_calc') Traceback (most recent call last): File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/test_suite/system_tests/relax_disp.py", line 284, in test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py", line 118, in __init__ self.run() File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py", line 471, in run self.optimise(model=model) File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/auto_analyses/relax_disp.py", line 379, in optimise self.interpreter.monte_carlo.create_data() File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/prompt/uf_objects.py", line 221, in __call__ self._backend(*new_args, **uf_kargs) File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/monte_carlo.py", line 113, in create_data pack_sim_data(data_index, random) File "/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/specific_analyses/relax_disp/api.py", line 1609, in sim_pack_data raise RelaxError("Monte Carlo simulation data for the key '%s' already exists." % int_key) RelaxError: RelaxError: Monte Carlo simulation data for the key '1_0_46_0' already exists. --------------------- I have looked into: specific_analyses/relax_disp/api.py There it is: ---------------------------------------------- def sim_pack_data(self, data_id, sim_data): """Pack the Monte Carlo simulation data. @param data_id: The tuple of the spin container and the exponential curve identifying key, as yielded by the base_data_loop() generator method. @type data_id: SpinContainer instance and float @param sim_data: The Monte Carlo simulation data. @type sim_data: list of float """ # The R2eff model (with peak intensity base data). if cdp.model_type == 'R2eff': # Unpack the data. spin, exp_type, frq, offset, point = data_id # Initialise the data structure if needed. if not hasattr(spin, 'intensity_sim'): spin.intensity_sim = {} # Loop over each time point. ti = 0 for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): # Get the intensity keys. int_keys = find_intensity_keys(exp_type=exp_type, frq=frq, point=point, time=time) # Loop over the intensity keys. for int_key in int_keys: # Test if the simulation data point already exists. if int_key in spin.intensity_sim: raise RelaxError("Monte Carlo simulation data for the key '%s' already exists." % int_key) # Initialise the list. spin.intensity_sim[int_key] = [] # Loop over the simulations, appending the corresponding data. for i in range(cdp.sim_number): spin.intensity_sim[int_key].append(sim_data[i][ti]) # Increment the time index. ti += 1 --------------------- For me, this looks okay. Do you have an Idea why this is not working? Best Troels