Inserting point sensors after running simulation NEURON

Dear supporter,
I am running some NEURON simulations that take a couple of days to finish. Now that they have finished I realize that I forgot to insert some point sensors for the currents and TMP before the start of the simulation, so I wanted to know if there is a way to analyze these parameters, after the simulations have already finished, without having to re-run them?
Thank you for your help,
Fede

Dear @fbattista8 ,
I am sorry that this happened to you, but unfortunately this is not possible. Sim4Life stores only the data in the sensors that have been initiated before the execution of the simulation.

Just to check.. are you using multi-threading option that permits you to run simulations in multiple cores, as many as allowed by your computational resources (or defined by you)? This may be speeding up your calculation if already not considered by you.

Best,
Antonino

Dear supporter,
If you mean checking the remote simulator for neuron solver in the preferences yes, otherwise I don't know what you mean could you elaborate please?

Dear @fbattista8,
If you are working on a remote PC connected through the network, then enabling the remote simulator makes sense. If you run the simulations in your own PC, then this option is not necessary. In both cases, you can use multi-threading to accelerate your EM-Neuronal simulation.

To activate this option, please go to the 'Solver' settings of your neuronal simulation, set the 'Parallelization Handling' option in the Properties panel to 'Manual' and change the 'Number of Threads'. If you know how many threads your PC allows, our suggestion is NOT to use all of them to avoid blocking your PC to just the neuronal simulation (you may want to still use your PC for other purposes). If you set 'Parallelization Handling' to 'Automatic', Sim4Life will instead automatically use all the resources available.

Since Sim4Life V5.0, Multi-threading will speedup the neuronal simulations in two different ways:
(1) by accelerating the loading of the neurons/axons models considerably (the performances are great!);
(2) by distributing the neuronal simulations to the N different threads, therefore reducing the duration of your neuronal simulation of a almost a factor N.

I hope this helps!

Dear supporter,
It did actually speed the process up quite a bit.
Thanks a bunch.

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