Thanks for checking through these @VahidGh. Yes, neurotune (and pyelectro) have replaced optimalneuron. Unfortunately these files haven't been updated since that change.

Also in that time, libNeuroML has become more stable, pyramidal hasn't been updated much & jNeuroML is the most well tested way for running NeuroML2 models. Now the preferred pipeline is:

libNeuroML (create/edit model) -> NeuroML2 XML files -> jNeuroML (load) -> simulate -> check & optimise

libNeuroML (create/edit model) -> NeuroML2 XML files -> jNeuroML (load & export to NEURON) -> simulate -> check & optimise

as opposed to:

libNeuroML -> Pyramidal -> NEURON -> simulate -> check & optimise

My suggestions for updating this code are:

create a new LEMS file (e.g. based on this to run a simulation with just the current NeuroML2 muscle & an input current
get main.py running with the NeuroML2 muscle model
- load in ../NeuroML2/SingleCompMuscle.cell.nml & *.channel.nml using loaders.NeuroMLLoader.load in init() into one NeuroMLDocument
- adjust the values in the nml files using libNeuroML
- save this new NeuroML file (include cell & channels in one file) in a new file with unique name
- create a copy of the LEMS file above which uses this new cell
- run the new lems file with jNeuroML when run() is called in main.py and reload the saved trace for v in a local array
update run.py to use the updated main.py and use neurotune/pyelectro instead

Try my forks of neurotune and pyelectro, as I've retested & updated these recently.

Uh oh!

Update optimization.py to run with neurotune instead of optimalneuron #18

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