Hi,
This looks like another rather stupid typo/mistake :) I added a print
statement for the int_keys variable and ran the test. There should
only be one key for a given {exp_type, frq, offset, point, time}
metadata set, but the printout shows this not to be the case. If you
carefully look at the find_intensity_keys() call, you will see that
one of these 5 bits of information are not sent in as an argument ;)
Regards,
Edward
On 27 February 2014 11:38, Troels Emtekær Linnet <[email protected]> wrote:
> 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
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