Please forgive our late reply; virtually the entire NEST development team is currently attending a conference and has been very busy with preparations.

There is no such thing as a "deep copy" for networks. It is also difficult to reset a network back to its initial state in a generic manner. However, it is possible to call nest.Simulate() repeatedly. Could it be a solution to simulate your network, perform analysis on the data recorded by the instrumentation, and then manually reset the network to a suitable initial state, before calling Simulate() again? This way, you would avoid the overhead of having to re-connect the network. The manual reset could involve e.g. resetting membrane potentials on the nodes in your network.

Please let us know if this works for you.

On Tue, Nov 26, 2019, at 12:39, alehr wrote:

Dear NEST developer,

I am wondering if my inquiry from November 11th has been looked at.

Thanks,

Andrew Lehr

Dear NEST developer,

I would like to initialize a network with neurons and connections and then run many simulations with it. It would be great if I could build the network one time and then deepcopy (or something similar) for each simulation. Is something like this possible?

Thanks,

Andrew Lehr

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