I'm encountering the following error
nest::Model* nest::ModelManager::get_node_model(nest::index) const:
Assertion `m < node_models_.size()' failed.
when using the following code:
for iin range(16):
neurons = nest.Create('MyNeuron_0', 2)
The script uses a neuron model that I wrote in C++ and is loaded without
errors. The error is thrown upon nest.Connect(), and goes away if I
create the neurons using `MyNeuron` and not `MyNeuron_x` (copied) or if
the #vp and #threads is 1. I've used the model with NEST 2.20.0 without
problems, but I'd like to port the code to the latest version. Maybe I'm
just missing something new functionality/API related to CopyModel and
multiprocessing - have there been any critical changes in the model
Any help would be greatly appreciated.
Dear NEST users,
After trying multiple ideas, I am still facing the issue where my
installation is successful with an error message:
-- Configuring done
CMake Warning at cmake/UseCython.cmake:100 (add_library):
Cannot generate a safe runtime search path for target pynestkernel because
files in some directories may conflict with libraries in implicit
runtime library [libgomp.so.1] in /usr/lib/gcc/x86_64-linux-gnu/9 may
be hidden by files in:
Some of these libraries may not be found correctly.
Call Stack (most recent call first):
This leads to the failure of multiple tests. The summary of the tests and
logs for the failed tests is attached.
I must mention that I tested the installation by creating a neuron and it
It would be nice to get rid of the error, please see error_msg file to see
where it fails.
Thanks and Regards
Dear NESTML Users,
In the last post I fixed a problem that was related to the fact that in the 'izhikevich_solution.nestml' the first line was commented.
Now, after following the guide in "https://nestml.readthedocs.io/en/latest/installation.html" related to the NESTML
installation, I tried to follow the NESTML Izhikevich tutorial in "https://nestml.readthedocs.io/en/latest/tutorials/izhikevich/nestml_izhikev…". After installing the cmake with "pip install cmake", when I execute the following part of the tutorial:
I obtain the following error:
Warning: PyGSL is not available. The stiffness test will be skipped.
Warning: No module named 'pygsl'
Option "nest_path" does not exist in builder
CalledProcessError Traceback (most recent call last)
/opt/data/nestml/pynestml/codegeneration/nest_builder.py in build(self)
--> 150 subprocess.check_call(make_all_cmd, stderr=subprocess.STDOUT, shell=shell,
/usr/lib/python3.8/subprocess.py in check_call(*popenargs, **kwargs)
363 cmd = popenargs
--> 364 raise CalledProcessError(retcode, cmd)
365 return 0
CalledProcessError: Command '['make', 'all']' returned non-zero exit status 2.
During handling of the above exception, another exception occurred:
GeneratedCodeBuildException Traceback (most recent call last)
<ipython-input-2-f0909be085f4> in <module>
----> 1 generate_nest_target(input_path="izhikevich_solution.nestml",
/opt/data/nestml/pynestml/frontend/pynestml_frontend.py in generate_nest_target(input_path, target_path, install_path, logging_level, module_name, store_log, suffix, dev, codegen_opts)
181 A dictionary containing additional options for the target code generator.
--> 183 generate_target(input_path, target_platform="NEST", target_path=target_path, logging_level=logging_level,
184 module_name=module_name, store_log=store_log, suffix=suffix, install_path=install_path,
185 dev=dev, codegen_opts=codegen_opts)
/opt/data/nestml/pynestml/frontend/pynestml_frontend.py in generate_target(input_path, target_platform, target_path, install_path, logging_level, module_name, store_log, suffix, dev, codegen_opts)
--> 152 if not process() == 0:
153 raise Exception("Error(s) occurred while processing the model")
/opt/data/nestml/pynestml/frontend/pynestml_frontend.py in process()
279 if _builder is not None:
--> 280 _builder.build()
282 if FrontendConfiguration.store_log:
/opt/data/nestml/pynestml/codegeneration/nest_builder.py in build(self)
152 except subprocess.CalledProcessError as e:
--> 153 raise GeneratedCodeBuildException('Error occurred during \'make all\'! More detailed error messages can be found in stdout.')
155 # finally execute make install
GeneratedCodeBuildException: Error occurred during 'make all'! More detailed error messages can be found in stdout.
So, the "nest_path" keyword does not exist. Can anyone help me?
Dear NEST Users & Developers!
I would like to invite you to our next fortnightly Open NEST Developer
Video Conference, today
Monday February 28, 11.30-12.30 CET (UTC+1).
Feel free to join the meeting also just to bring your own questions for
direct discussion in the in-depth section.
As usual, in the Project team round, a contact person of each team will
give a short statement summarizing ongoing work in the team and
cross-cutting points that need discussion among the teams. The remainder
of the meeting we would go into a more in-depth discussion of topics
that came up on the mailing list or that are suggested by the teams.
* Review of NEST User Mailing List
* Project team round
* In-depth discussion
The agenda for this meeting is also available online, see
Looking forward to seeing you soon!
We use a virtual conference room provided by DFN (Deutsches Forschungsnetz).
You can use the web client to connect. We however encourage everyone to
use a headset for better audio quality or even a proper video
conferencing system (see below) or software when available.
* Visit https://conf.dfn.de/webapp/conference/97938800
* Enter your name and allow your browser to use camera and microphone
* The conference does not need a PIN to join, just click join and you're in.
In case you see a dfnconf logo and the phrase "Auf den
Meetingveranstalter warten", just be patient, the meeting host needs to
join first (a voice will tell you).
How to log in with a video conferencing system, depends on you VC system
- Using the H.323 protocol (eg Polycom): vc.dfn.net##97938800 or
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- By telephone: +49-30-200-97938800
For those who do not have a video conference system or suitable
software, Polycom provides a pretty good free app for iOS and Android,
so you can join from your tablet (Polycom RealPresence Mobile, available
from AppStore/PlayStore). Note that firewalls may interfere with
videoconferencing in various and sometimes confusing ways.
For more technical information on logging in from various VC systems,
please see http://vcc.zih.tu-dresden.de/index.php?linkid=22.214.171.124
Hey Nest Team,
Calling "NodeCollection.get" returns a dictionary containing the user declared "States" and "Parameters" with other keys such as "global_id", "recordables", and "synaptic_elements". In this context, I want to ask if there is a function in "nest" that returns exactly only the model declared "States" or "Parameters" without having these extra keys, and of course without having a prior knowledge of the "nestml" file from which the model was originated.
Am I correct in thinking that all rand generators provided for NEST use
std::thread? If I am not mistaken, it's an extension of POSIX threads
and I'd like to avoid it for my target offloading work.
Documentation for `tsodyks_synapse` says it is only compatible with `iaf_psc_exp` or `iaf_psc_exp_htum` neuron models. Would it be possible to use it with other `_exp`-type models with postsynaptic currents or conductances with exponential decay (for example, `aeif_cond_exp`)? If not, what could be a work around?
With best regards,
CST EECS KTH.
The NEST Initiative is excited to invite everyone interested in Neural Simulation Technology and the NEST Simulator to the NEST Conference 2022. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We particularly encourage young scientists to participate in the conference!
This year's conference will again take place as a virtual event on Thursday/Friday 23/24 June 2022.
For more information please visit the conference website
We are looking forward to seeing you all in June!
Hans Ekkehard Plesser and colleagues
Prof. Dr. Hans Ekkehard Plesser
Head, Department of Data Science
Faculty of Science and Technology
Norwegian University of Life Sciences
PO Box 5003, 1432 Aas, Norway
Phone +47 6723 1560
We would like to use neurons models with NMDA channels in our spiking neuron model. We're still unsure whether we will use a native neuron model in Nest or whether we will implement our own one in NESTML. My understanding is that the only model in Nest which does that is the Hill - Tononi model, which seems rather complex. How fast would you roughly expect a Hill - Tononi neuron network to run compared to a network made of aeif_cond_exp neurons?
Do you know by any chance any example of adex NESTML models which implement NMDA and Gaba_B channels?
Also, one last question not really related to the previous ones: Is there any way to model synaptic reliability in Nest?
Thanks a lot,