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Profiling PyNEST—easier than you think and some interesting results

by Hans Ekkehard Plesser

Hi everyone! I realized today that profiling PyNEST is easier than I thought. In iPython, you can just run run -p -s cumulative -D srn.prof ../src/pynest/examples/store_restore_network.py which will run the script, present a summary sorted by cumulative time and write binary profiling data (pstats format) to file srn.prof. Then run (gprof2dot available from, e.g., PiPy) gprof2dot -f pstats -o srn.dot srn.prof and finally dot -Tpdf srn.dot Both tools have lot's of options. In my case (an older version of the script above, currently under review in #1919, not yet in master), the attached PDF resulted, showing that getting connection properties indeed takes a lot of time. Note that the graph only resolves time spent in Python code, time spent in C++ code is hiding behind "run()". Below some more timing results from a network of 1000 neurons with 100,000 connections: In [16]: %time c = nest.GetConnections() CPU times: user 66.5 ms, sys: 8.09 ms, total: 74.6 ms Wall time: 75.7 ms In [17]: %time c = nest.GetConnections().weight CPU times: user 869 ms, sys: 75.3 ms, total: 944 ms Wall time: 955 ms In [18]: %time c = nest.GetConnections().get("weight", output="pandas") CPU times: user 1.69 s, sys: 186 ms, total: 1.88 s Wall time: 1.9 s Clearly, GetConnections() is quite fast, while reading out the weights costs. What maybe surprised me most is that turning the data as a Pandas DataFrame costs a whole second extra—I wonder if we do something suboptimal here. Best, Hans Ekkehard -- 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 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

3 years, 7 months

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Stop hanging simulations

by TOM BUGNON

Hi all, Under some circumstances simulations can slow down up to the point where the nest.Simulate() does not advance anymore and stays stuck at a given virtual time, with a "realtime factor" of 0. I suppose this can happen for instance when a network falls into a regime of runaway excitation in which a massive number of spikes are being exchanged. I'm looking for a way to stop the simulation in such a case, (say when the realtime factor goes below a set threshold, or when the output files are not updated for a certain duration), ideally in such a way that the program can continue running rather than crashing. If anyone has a suggestion about how to go around this issue I'd be happy to hear it. Thanks in advance! Best, Tom

3 years, 7 months

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Apologies for spam via NEST Users

by Hans Ekkehard Plesser

Dear NEST Users subscribers, In the last 24 hours, you unfortunately received two spam emails via NEST Users. This happened as someone exploited our approach of managing NEST Users based on trust. So far, we allow all registered subscribers to send mails to the list without further control, and we generally accept all subscription requests without double-checking that the requests really come from a person with a genuine interest in NEST. This time, someone exploited our trust to spread spam. We will review our policies to avoid undue spamming, but I do hope we will be able to continue in the spirit of trust that has so far been a hallmark of the NEST Community. Let me close with a bit of advertising of my own: Do not forget to submit your abstract to the NEST Conference 2021 at https://www.nest-simulator.org/conference! Best regards, Hans Ekkehard -- 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 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

3 years, 8 months

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Where to Buy Delta-8 Oil?

by taliamyers017＠gmail.com

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3 years, 8 months

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Delta-8 For Sale

by taliamyers017＠gmail.com

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3 years, 8 months

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Open NEST Developer Video Conference Monday 26 April 2021 11:30 CEST (UTC+2)

by Dennis Terhorst

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday 26 April, 11.30-12.30 CEST (UTC+2). 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. Today there will be an update and discussion about style guides for documentation and code. Agenda Welcome Review of NEST User Mailing List Project team round In-depth discussion * NEST Documentation Style Guide (#1986 <https://github.com/nest/nest-simulator/pull/1986>) * Single vs double quotes for Python strings? See also this discussion <https://github.com/nest/nest-simulator/pull/1986#discussion_r610373605> * Which well-established style guide to build on? See also this discussion <https://github.com/nest/nest-simulator/pull/1986#discussion_r613510749> The agenda for this meeting is also available online, see https://github.com/nest/nest-simulator/wiki/2021-04-26-Open-NEST-Developer-… Looking forward to seeing you soon! best, Dennis Terhorst ------------------ Log-in information ------------------ 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. Web client * 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). VC system/software How to log in with a video conferencing system, depends on you VC system or software. - Using the H.323 protocol (eg Polycom): vc.dfn.net##97938800 or 194.95.240.2##97938800 - Using the SIP protocol:97938800@vc.dfn.de - 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=1.1.3.4

3 years, 8 months

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New NEST Random Number Generators in Master

by Hans Ekkehard Plesser

Dear NEST Users and Developers! After a long and demanding process, we merged pull request #1549 into the NEST master branch earlier this afternoon. It replaces the old random number generator suite in NEST completely with a new one based on the C++ Standard Library and also providing generators from the Random123 library, including cryptographic generators. The most important change for users is that you can now much more easily seed generators and change the type of random number generator used. To seed, you only need a single seed—NEST will take care of everything else: nest.SetKernelStatus({'rng_seed': 12345}) is all it takes. To select a different RNG type, use nest.SetKernelStatus({'rng_type': 'mt19937'}) To see all available RNG types, use nest.GetKernelStatus('rng_types') For more information, see https://nest-simulator.readthedocs.io/en/latest/guides/nest2_to_nest3/nest2…. I hope this change will motivate everyone to even more systematically explore their models with a wide range of seeds and with different random number generator types. Existing simulation scripts, which otherwise are compatible with NEST master will only need to change the part of the script related to seeding and RNG selection. Because we now use a completely different internal architecture to provide random numbers, the actual sequence of random numbers provided will be different from before. This means that it is not possible to exactly reproduce spike trains obtained with the old RNG setup. Statistically, though, results shall be identical. If you should observe any unexpected deviations in results after switching to the new RNG scheme, please contact us! I would like to thank everyone who has contributed to this effort over a long time, especially Håkon and Jochen for their design and development work, and Johanna and Jasper for generating a lot of test data. With the new RNGs, the last major component for NEST3 is now integrated into the NEST master branch and we are very optimistic to finally make the NEST3 release before this summer. Best regards, Hans Ekkehard -- 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 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

3 years, 8 months

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Iaf - psc - delta neurons data

by Parva Alavian

Dear developers/users of nest, I am using the iaf-psc-delta neurons in my network and I need to access the information on the amount of excitatory and inhibitory input that each neuron is receiving in time in order to study balance.(so not just I-e but also the inputs that it is getting from other neurons in the randomly connected network). Can you please help me with this? It would also help if I knew where to find the indices of all the neurons that are presynaptic to a given neuron (a connectivity matrix). I would then be able to calculate the input current myself. Looking forward to hearing from you! Kind regards, Parva

3 years, 8 months

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Triplets STDP model

by Julia Gallinaro

Dear NEST community, I am working with the triplets STDP connection on NEST simulations, and I am interested in how the weight dynamics change when the spike trains are altered in some specific ways. In order to do that, I run a network simulation using NEST and the triplets STDP rule and save the full spike trains of two neurons which are synaptically connected (one pre and one post). I then recreate the weight changes on a code outside the NEST loop, so that I can manipulate the spike trains and observe what happens to the synaptic weights. Trying to validate this approach, though, I find that my code (outside NEST loop) generates different weight values than the NEST simulation when using the same spike trains generated during the simulation. I guess I have some error in my implementation of the triplets rule. I thought it could be something with the implementation of the delays, or the moment when the weights are measured in the simulation, but I have had no success trying to fix it yet. I know this is not exactly a NEST issue, but I thought I would give it a try and ask here at the list. In case someone has already worked with the triplets rule and could point me out to what is/could be wrong in my implementation, I would very much appreciate it :) Thanks! best, Júlia

3 years, 8 months

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CreateLayer problem with dictionary

by xotazu＠cvc.uab.es

Hello, I am having a basic problem creating layers with topology (pyhton 3.6 and NEST 2.20.1). It always complains about the dictionary sent to CreateLayer, telling it is a number. The code below correctly prints <class 'dict'> but prints this error: Traceback (most recent call last): File "test/binary_gdf.py", line 9, in <module> kk=tp.CreateLayer({'extent': [1, 1],'rows': 20, 'columns': 20,'elements' : 'izhikevich','edge_wrap':True}) File "/home/neurobit/local/nest-py3/lib64/python3.6/site-packages/nest/topology/hl_api.py", line 650, in CreateLayer return topology_func('{ CreateLayer } Map', specs) File "/home/neurobit/local/nest-py3/lib64/python3.6/site-packages/nest/topology/ll_api.py", line 61, in topology_func return nest.ll_api.sli_func(slifunc, *args) File "/home/neurobit/local/nest-py3/lib64/python3.6/site-packages/nest/ll_api.py", line 182, in sli_func sli_run(slifun) # SLI support code to execute s on args File "/home/neurobit/local/nest-py3/lib64/python3.6/site-packages/nest/ll_api.py", line 132, in catching_sli_run raise exceptionCls(commandname, message) nest.lib.hl_api_exceptions.TypeMismatch: ('TypeMismatch in CreateLayer_D: Expected datatype: doubletype\nProvided datatype: integertype', 'TypeMismatch', <SLILiteral: CreateLayer_D>, ': Expected datatype: doubletype\nProvided datatype: integertype') Any help would be nice :-) Xavier ---- import nest import nest.topology as tp nest.SetKernelStatus({"overwrite_files": True}) my_dict = {'extent': [1, 1],'rows': 20, 'columns': 20,'elements' : 'izhikevich','edge_wrap':True} print(type(my_dict)) kk=tp.CreateLayer(my_dict)

3 years, 8 months

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