I tried to run the model-free analysis in RELAX-NMR, but I received an error message immediately after execution. The same error occurs even when using a dataset that previously ran without any issues in version 5.0.0.
Traceback (most recent call last):
File "/usr/software/relax/source/gui/analyses/execute.py", line 87, in run
self.run_analysis()
File "/usr/software/relax/source/gui/analyses/auto_model_free.py", line 838, in run_analysis
dauvergne_protocol.dAuvergne_protocol(pipe_name=self.data.pipe_name, pipe_bundle=self.data.pipe_bundle, results_dir=self.data.save_dir, diff_model=self.data.global_models, mf_models=self.data.mf_models, local_tm_models=self.data.local_tm_models, grid_inc=self.data.inc, diff_tensor_grid_inc=self.data.diff_tensor_grid_inc, mc_sim_num=self.data.mc_sim_num, max_iter=self.data.max_iter, conv_loop=self.data.conv_loop)
File "/usr/software/relax/source/auto_analyses/dauvergne_protocol.py", line 249, in init
self.execute()
File "/usr/software/relax/source/auto_analyses/dauvergne_protocol.py", line 607, in execute
self.multi_model(local_tm=True)
File "/usr/software/relax/source/auto_analyses/dauvergne_protocol.py", line 895, in multi_model
self.interpreter.minimise.grid_search(inc=self.grid_inc)
File "/usr/software/relax/source/prompt/uf_objects.py", line 161, in call
self._backend(new_args, *uf_kargs)
File "/usr/software/relax/source/pipe_control/minimise.py", line 173, in grid_search
model_lower, model_upper, model_inc = grid_setup(lower, upper, inc, verbosity=verbosity, skip_preset=skip_preset)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/software/relax/source/pipe_control/minimise.py", line 342, in grid_setup
elif values[i] in [None, {}, []]:
^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: The truth value of an empty array is ambiguous. Use array.size > 0 to check that an array is not empty.
Hi, I get the same (very similar) error message. When I try to run model-free analysis on NMR data.
Is there any solution for this?
I also, as Seungwoo Lee describes, run on quite good data that worked previously, or some year back at least.
best regards
Johan