Hi!

Right now, there is no way of excluding connections with zero weights
from being connected other than resorting to one-to-one connections and
looping/checking manually. Feel free to add this feature request to our
issue tracker at https://github.com/nest/nest-simulator/issues

Cheers,
Jochen!


On 28.11.19 15:10, Petia Koprinkova wrote:
> Thank you very much Jochen for exhaustive answer!
>
> I was wandering what if I have generated sparse connectivity matrix W
> and use it to connect two populations of neurons at once? I am using
> connect all-to-all but with non-sparse matrix having zeros for missing
> connections now.
>
> Best wishes,
> Petia
>
> On Thursday, November 28, 2019, 3:24:54 PM GMT+2, Jochen Martin Eppler
> <j.eppler@fz-juelich.de> wrote:
>
>
> Dear Petia!
>
>  > My approach is the same as Andrew's but nevertheless it takes time to
>  > connect a complex network having multiple layers and
>  > feedback/feedforward connectivity even though I have prepared and saved
>  > all parameters in advance, esspecially if I want to have sparse
>  > connectivity.
>
> Of course it takes time to re-instantiate a network completely to do
> repeated experiments on pristine networks, but so would saving and
> loading. In fact, all our attempts to implement this functionality
> showed that it actually often takes *more* time to restore a network
> from disk than it would to just re-running the script that created it.
> The main reason for this is that memory and processors are lightning
> fast compared to disks.
>
> The other reason for not having any checkpointing functionality and
> removing ResetNetwork in NEST 3 is that is just crazy complicated to get
> this right. There are spike buffers in neurons and inside the NEST
> kernel, modified default values, random number generator states,
> internal flags indicating simulation phases, possibly open files, and so
> on and so forth. Because it is almost impossible to implement this in a
> way that is both complete and correct, we rather not provide it.
>
>  > I was also wandering is it possible to have sparse connectivity matrix W
>  > to be used in the following manner: connect(pop1, pop2, "all_to_all",
>  > W). Now I am generating full matrix with numerous zero elements but if I
>  > want to have dynamic synapses, initial zero weights might result in
>  > non-zero one after some time.
>
> You have to create all connections from the start if you want them to
> exhibit dynamic weight changes during the simulation. The only exception
> to this rule is structural plasticity:
> https://www.fz-juelich.de/ias/jsc/EN/Expertise/SimLab/slns/research/structural_plasticity/_node.html
>
> Best regards,
> Jochen!
>
>
>
>  > On Wednesday, November 27, 2019, 4:42:32 PM GMT+2, Simon Brodeur
>  > <simon.brodeur@usherbrooke.ca <mailto:simon.brodeur@usherbrooke.ca>>
> wrote:
>  >
>  >
>  > Hi Andrew,
>  >
>  > Is it because the network takes a long time to build?
>  > Are you working with very large networks that need to be spread on
>  > multiple machines?
>  >
>  > I am personally building networks with complex topologies, where
>  > creating the synaptic connections requires a lot of time since I do
>  > random sampling with constraint satisfaction directly in Python.
>  > I also need to compute per-synapse approximations of axonal delays,
>  > dendritic tree attenuations and much more. I do build the network once
>  > and have written some Python code that allow to pickle the necessary
>  > information (e.g. parameters of the neuron models, synaptic weights) to
>  > instantiate faster the network in NEST when I want to perform
>  > simulations. But that is just a custom solution, not general to any
> network.
>  >
>  > Cordially,
>  > Simon
>  >
>  > On Tue, 2019-11-26 at 12:39 +0100, alehr wrote:
>  >> Dear NEST developer,
>  >>
>  >> I am wondering if my inquiry from November 11th has been looked at.
>  >>
>  >> Thanks,
>  >> Andrew Lehr
>  >>
>  >> On Mon, Nov 11, 2019 at 1:52 PM alehr <alehr@mun.ca
> <mailto:alehr@mun.ca>
>  >> <mailto:alehr@mun.ca <mailto:alehr@mun.ca>>> wrote:
>  >>> 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
>  >> _______________________________________________
>  >> NEST Users mailing list --users@nest-simulator.org
> <mailto:--users@nest-simulator.org>  <mailto:users@nest-simulator.org
> <mailto:users@nest-simulator.org>>
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> <mailto:tousers-leave@nest-simulator.org> 
> <mailto:users-leave@nest-simulator.org
> <mailto:users-leave@nest-simulator.org>>
>  >>
>  > --
>  >
>  > ___________________________________________________
>  >
>  > *Simon Brodeur*
>  > /Étudiant au doctorat/
>  > Université de Sherbrooke
>  > Département génie électrique et génie informatique
>  > Laboratoire NECOTIS, C1-3036
>  > Tél. : (819) 821-8000 poste 62187
>  > Courriel: Simon.Brodeur@USherbrooke.ca
> <mailto:Simon.Brodeur@USherbrooke.ca>
> <mailto:Simon.Brodeur@USherbrooke.ca <mailto:Simon.Brodeur@USherbrooke.ca>>
>  >
>  > ___________________________________________________
>  >
>  > _______________________________________________
>  > NEST Users mailing list -- users@nest-simulator.org
> <mailto:users@nest-simulator.org>
>  > <mailto:users@nest-simulator.org <mailto:users@nest-simulator.org>>
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> <mailto:users-leave@nest-simulator.org>
>  > <mailto:users-leave@nest-simulator.org
> <mailto:users-leave@nest-simulator.org>>
>  >
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>  >
>
> --
> Dr. Jochen Martin Eppler
> Phone: +49(2461)61-96653
> ----------------------------------
> Simulation Laboratory Neuroscience
> Jülich Supercomputing Centre
> Institute for Advanced Simulation
>
>
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