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Runtime error in plotting branch #16

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MJC598 opened this issue May 3, 2021 · 1 comment
Open

Runtime error in plotting branch #16

MJC598 opened this issue May 3, 2021 · 1 comment
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@MJC598
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MJC598 commented May 3, 2021

When running the command: python run_bionet.py jsons/simulation_config.json on the plotting branch this error is generated. The x86_64 files have to be recompiled using nrnivmodl to fix the compatability errors in the .o/.c/.mod files

2021-05-03 13:48:30,082 [INFO] step:20000 t_sim:2000.00 ms
2021-05-03 13:48:30,085 [INFO] PGN firing rate = 3.00 Hz
2021-05-03 13:48:30,086 [INFO] Volume = 0.07 ml
2021-05-03 13:48:30,086 [INFO] Pressure = 9.97 cm H20
2021-05-03 13:48:30,086 [INFO] Bladder afferent firing rate = 0.48 Hz
Traceback (most recent call last):
File "/home/matt/anaconda3/envs/lut_vinnay/lib/python3.6/site-packages/bmtk/simulator/bionet/biosimulator.py", line 381, in post_fadvance
mod.block(self, time_step_interval)
File "/home/matt/repos/LUT_Prelim/feedback_loop.py", line 324, in block
self._activate_hln(sim, block_interval, bladaff_fr)
File "/home/matt/repos/LUT_Prelim/feedback_loop.py", line 61, in _activate_hln
spikes = psg.get_times(0)*1000 # convert sec to ms
File "/home/matt/anaconda3/envs/lut_vinnay/lib/python3.6/site-packages/bmtk/utils/reports/spike_trains/spike_train_buffer.py", line 153, in get_times
pop = self._pops[population]
KeyError: 'sonata:none'
NEURON: PyObject method call failed: post_fadvance
near line 0
^
advance()
step()
continuerun(60500)
run(60500)
Traceback (most recent call last):
File "run_bionet.py", line 55, in
run(sys.argv[-1])
File "run_bionet.py", line 46, in run
sim.run()
File "/home/matt/anaconda3/envs/lut_vinnay/lib/python3.6/site-packages/bmtk/simulator/bionet/biosimulator.py", line 342, in run
h.run(h.tstop) # <- runs simuation: works in parallel
RuntimeError: hoc error

@MJC598 MJC598 added the bug Something isn't working label May 3, 2021
@MJC598
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MJC598 commented May 5, 2021

This has since been noticed on master. It only happens occasionally and likely has to do with parallel execution differences between hardwares (specifically if its running on a CPU vs GPU).

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