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Add Bouhadjar sequence learning network tutorial #1026

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@clinssen clinssen commented Apr 19, 2024

Should be merged after #1027.

  • Add the following notes:
    lambda_plus is increasing facilitation: too many daps, decrease facilitation!
    lambda_minus is increasing depression: too many daps, increase depression!
    if you see overlap, increase lambda_h a bit
    
  • eliminate the use of the "parameters" Python package

C.A.P. Linssen added 30 commits May 10, 2023 16:01
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github-actions bot commented Oct 16, 2024

🐰 Bencher Report

Branch1026/merge
Testbedubuntu-latest

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tests/nest_continuous_benchmarking/test_nest_continuous_benchmarking.py::TestNESTContinuousBenchmarking::test_stdp_nn_synapse📈 view plot
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3,867,834,361.40
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clinssen commented Nov 5, 2024

It seems as though the second line in the following snippet from the notebook causes an extreme memory consumption:

connections = nest.GetConnections(synapse_model=...)
connections.set({'Wmin': connections.weight})

There are around 165000 connections.

Edit: spun off to nest/nest-simulator#3359.

@clinssen clinssen requested a review from pnbabu November 7, 2024 00:16
@clinssen clinssen marked this pull request as ready for review November 7, 2024 00:16
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Thanks for this excellent tutorial! I have a few minor comments:

  • When you describe the different terms in the STDP rule in the text, could you refer to the equation by number? For example, the second term on the right-hand side in (1)...
  • Any reason behind setting the number of threads to 1?
  • Under "Generating code with NESTML", do we need the try and except?
    • Remove the following lines
"""module_name = "/tmp/nestml_target_68digoes/nestml_27fd8d9de14b408f9e6181b2f2310d41_module.so"
neuron_model_name = "iaf_psc_exp_nonlineardendrite_neuron_nestml__with_stdsp_synapse_nestml"
synapse_model_name = "stdsp_synapse_nestml__with_iaf_psc_exp_nonlineardendrite_neuron_nestml" """
  • The fig just before Experiment 2 is a bit hard to read. Can the three panels be a bit further apart?

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@pnbabu: much obliged for the review! I have cleaned up the notebook and the neuron model; this should address all your comments.

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