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Merge pull request #2767 from nicolossus/port_test_issue_77
Port `issue-77.sli` from SLI-2-Py
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| # -*- coding: utf-8 -*- | ||
| # | ||
| # test_issue_77.py | ||
| # | ||
| # This file is part of NEST. | ||
| # | ||
| # Copyright (C) 2004 The NEST Initiative | ||
| # | ||
| # NEST is free software: you can redistribute it and/or modify | ||
| # it under the terms of the GNU General Public License as published by | ||
| # the Free Software Foundation, either version 2 of the License, or | ||
| # (at your option) any later version. | ||
| # | ||
| # NEST is distributed in the hope that it will be useful, | ||
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| # GNU General Public License for more details. | ||
| # | ||
| # You should have received a copy of the GNU General Public License | ||
| # along with NEST. If not, see <http://www.gnu.org/licenses/>. | ||
|
|
||
| """ | ||
| Regression test for Issue #77 (GitHub). | ||
| """ | ||
|
|
||
| import pytest | ||
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| import nest | ||
|
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| # The following models will not be tested: | ||
| skip_models = [ | ||
| "erfc_neuron", # binary neuron | ||
| "ginzburg_neuron", # binary neuron | ||
| "mcculloch_pitts_neuron", # binary neuron | ||
| "gif_pop_psc_exp", # population model, not suitable for STDP | ||
| "gauss_rate_ipn", # rate neuron | ||
| "lin_rate_ipn", # rate neuron | ||
| "lin_rate_opn", # rate neuron | ||
| "siegert_neuron", # rate neuron | ||
| "sigmoid_rate_gg_1998_ipn", # rate neuron | ||
| "sigmoid_rate_ipn", # rate neuron | ||
| "tanh_rate_ipn", # rate neuron | ||
| "tanh_rate_opn", # rate neuron | ||
| "threshold_lin_rate_ipn", # rate neuron | ||
| "threshold_lin_rate_opn", # rate neuron | ||
| "rate_transformer_gauss", # rate transformer | ||
| "rate_transformer_lin", # rate transformer | ||
| "rate_transformer_sigmoid", # rate transformer | ||
| "rate_transformer_sigmoid_gg_1998", # rate transformer | ||
| "rate_transformer_tanh", # rate transformer | ||
| "rate_transformer_threshold_lin", # rate transformer | ||
| "spike_train_injector", # generator neuron, does not support spike input | ||
| "music_cont_in_proxy", # MUSIC device | ||
| "music_cont_out_proxy", # MUSIC device | ||
| "music_event_in_proxy", # MUSIC device | ||
| "music_event_out_proxy", # MUSIC device | ||
| "music_message_in_proxy", # MUSIC device | ||
| "music_rate_in_proxy", # MUSIC device | ||
| "music_rate_out_proxy", # MUSIC device | ||
| ] | ||
|
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||
| # The following models require connections to rport 1 or other specific parameters: | ||
| extra_params = { | ||
| "aeif_psc_alpha": {"initial_weight": 80.0}, | ||
| "aeif_psc_delta": {"initial_weight": 80.0}, | ||
| "aeif_psc_exp": {"initial_weight": 80.0}, | ||
| "aeif_cond_alpha_multisynapse": { | ||
| "params": {"E_rev": [-20.0], "tau_syn": [2.0]}, | ||
| "receptor_type": 1, | ||
| }, | ||
| "aeif_cond_beta_multisynapse": { | ||
| "params": {"E_rev": [-20.0], "tau_rise": [1.0], "tau_decay": [2.0]}, | ||
| "receptor_type": 1, | ||
| }, | ||
| "iaf_cond_alpha_mc": {"receptor_type": 1}, | ||
| "iaf_psc_alpha_multisynapse": {"params": {"tau_syn": [1.0]}, "receptor_type": 1}, | ||
| "iaf_psc_exp_multisynapse": {"params": {"tau_syn": [1.0]}, "receptor_type": 1}, | ||
| "gif_cond_exp_multisynapse": {"params": {"tau_syn": [1.0]}, "receptor_type": 1}, | ||
| "gif_psc_exp_multisynapse": {"params": {"tau_syn": [1.0]}, "receptor_type": 1}, | ||
| "glif_cond": {"params": {"tau_syn": [0.2], "E_rev": [0.0]}, "receptor_type": 1}, | ||
| "glif_psc": {"params": {"tau_syn": [1.0]}, "receptor_type": 1}, | ||
| "ht_neuron": {"receptor_type": 1}, | ||
| "pp_cond_exp_mc_urbanczik": {"receptor_type": 1}, | ||
| } | ||
|
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||
| models = [ | ||
| model | ||
| for model in nest.node_models | ||
| if (nest.GetDefaults(model, "element_type") == "neuron") and model not in skip_models | ||
| ] | ||
|
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|
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| @pytest.mark.parametrize("model", models) | ||
| def test_register_outgoing_spikes(model): | ||
| """ | ||
| Ensure that all neuron models register outgoing spikes with archiving node. | ||
| The test sends a very high-rate Poisson spike train into the neuron that | ||
| should make any type of model neuron fire and checks both `t_spike` entry | ||
| of the neuron (>0 if neuron has spiked) and checks that the connection | ||
| weight differs from the initial value 1.0. | ||
| """ | ||
| nest.ResetKernel() | ||
|
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| nrn = nest.Create(model) | ||
|
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| if model in extra_params: | ||
| if "params" in extra_params[model]: | ||
| nrn.set(extra_params[model].get("params")) | ||
|
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| # if the model is compartmental, we need to add at least a root compartment | ||
| if "compartments" in nest.GetDefaults(model): | ||
| nrn.compartments = {"parent_idx": -1} | ||
| nrn.receptors = {"comp_idx": 0, "receptor_type": "AMPA"} | ||
|
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| pg = nest.Create("poisson_generator", params={"rate": 1e5}) | ||
| parrot = nest.Create("parrot_neuron_ps") | ||
| srec = nest.Create("spike_recorder") | ||
|
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| # need to connect via parrot since generators cannot connect with | ||
| # plastic synapses. | ||
| nest.Connect(pg, parrot) | ||
|
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| receptor_type = 0 | ||
| initial_weight = 10.0 | ||
| if model in extra_params: | ||
| if "receptor_type" in extra_params[model]: | ||
| receptor_type = extra_params[model].get("receptor_type") | ||
| if "initial_weight" in extra_params[model]: | ||
| initial_weight = extra_params[model].get("initial_weight") | ||
|
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| syn_spec = { | ||
| "synapse_model": "stdp_synapse", | ||
| "weight": initial_weight, | ||
| "receptor_type": receptor_type, | ||
| } | ||
|
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| nest.Connect(parrot, nrn, "one_to_one", syn_spec) | ||
| nest.Connect(nrn, srec) | ||
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| nest.Simulate(100.0) | ||
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| num_spikes = srec.n_events | ||
| t_last_spike = nrn.t_spike | ||
| weight_after_sim = nest.GetConnections(parrot).get("weight") | ||
|
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| assert num_spikes > 0 | ||
| assert t_last_spike > 0 | ||
| assert weight_after_sim != initial_weight |
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