Merge remote-tracking branch 'upstream/master' into spinnaker-new

.github/workflows/nestml-build.yml

@@ -2,6 +2,10 @@ name: NESTML build
 
 on: [push, pull_request]
 
+concurrency:
+ group: ${{ github.workflow }}-${{ github.ref }}
+ cancel-in-progress: true
+
 jobs:
 
  link_checker:
@@ -119,7 +123,7 @@ jobs:
  runs-on: ubuntu-latest
  strategy:
  matrix:
- nest_branch: ["v2.20.2", "v3.0", "v3.1", "v3.2", "v3.3", "v3.4", "master"]
+ nest_branch: ["v2.20.2", "v3.0", "v3.5", "master"]
  fail-fast: false
  steps:
  # Checkout the repository contents

README.md

@@ -31,3 +31,11 @@ NESTML is free software: you can redistribute it and/or modify it under the term
 NESTML 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 NESTML. If not, see <http://www.gnu.org/licenses/>.
+
+## Acknowledgements
+
+This software was initially supported by the JARA-HPC Seed Fund *NESTML - A modeling language for spiking neuron and synapse models for NEST* and the Initiative and Networking Fund of the Helmholtz Association and the Helmholtz Portfolio Theme *Simulation and Modeling for the Human Brain*.
+
+This software was developed in part or in whole in the Human Brain Project, funded from the European Union's Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreements No. 720270, No. 785907 and No. 945539 (Human Brain Project SGA1, SGA2 and SGA3).
+
+

doc/models_library/ignore_and_fire.rst

@@ -0,0 +1,68 @@
+ignore_and_fire
+###############
+
+
+ignore_and_fire - Neuron generating spikes at fixed intervals irrespective of inputs 
+
+Description
++++++++++++
+
+The ``ignore_and_fire`` neuron is a neuron model generating spikes at a predefined ``firing_rate`` with a constant inter-spike interval ("fire"), irrespective of its inputs ("ignore"). In this simplest version of the ``ignore_and_fire`` neuron, the inputs from other neurons or devices are not processed at all (*). The ``ignore_and_fire`` neuron is primarily used for neuronal-network model verification and validation purposes, in particular, to evaluate the correctness and performance of connectivity generation and inter-neuron communication. It permits an easy scaling of the network size and/or connectivity without affecting the output spike statistics. The amount of network traffic is predefined by the user, and therefore fully controllable and predictable, irrespective of the network size and structure. 
+
+To create asynchronous activity for a population of ``ignore_and_fire`` neurons, the firing ``phase``s can be randomly initialised. Note that the firing ``phase`` is a real number, defined as the time to the next spike relative to the firing period.
+
+(*) The model can easily be extended and equipped with any arbitrary input processing (such as calculating input currents with alpha-function shaped PSC kernels or updating the gating variables in the Hodgkin-Huxley model) or (after-) spike generation dynamics to make it more similar and comparable to other non-ignorant neuron models. In such extended ignore_and_fire models, the spike emission process would still be decoupled from the intrinsic neuron dynamics.
+
+Authors
++++++++
+
+Tetzlaff (February 2021; January 2022)
+
+
+
+
+Parameters
+++++++++++
+.. csv-table::
+ :header: "Name", "Physical unit", "Default value", "Description"
+ :widths: auto
+
+
+ "firing_rate", "Bq", "10.0Bq", "# firing rate"
+
+
+
+State variables
++++++++++++++++
+
+.. csv-table::
+ :header: "Name", "Physical unit", "Default value", "Description"
+ :widths: auto
+
+
+ "phase", "real", "1.0", "# relative time to next spike (in (0,1])"
+
+
+
+
+Equations
++++++++++
+
+
+
+
+
+Source code
++++++++++++
+
+The model source code can be found in the NESTML models repository here: `ignore_and_fire <https://github.com/nest/nestml/tree/master/models/neurons/ignore_and_fire.nestml>`_.
+
+Characterisation
+++++++++++++++++
+
+.. include:: ignore_and_fire_characterisation.rst
+
+
+.. footer::
+
+ Generated at 2023-08-08 15:01:40.284515

doc/models_library/index.rst

@@ -292,6 +292,15 @@ Wang-Buzsaki model with multiple synapses
 
 Source file: `wb_cond_multisyn.nestml <https://www.github.com/nest/nestml/blob/master/models/neurons/wb_cond_multisyn.nestml>`_
 
+
+:doc:`ignore_and_fire <ignore_and_fire>`
+------------------------------------
+
+Neuron generating spikes at fixed intervals irrespective of inputs
+
+Source file: `ignore_and_fire.nestml <https://www.github.com/nest/nestml/blob/master/models/neurons/ignore_and_fire.nestml>`_
+
+
 Synapse models
 ~~~~~~~~~~~~~~
 

doc/nestml_language/nestml_language_concepts.rst

@@ -512,6 +512,21 @@ The following functions are predefined in NESTML and can be used out of the box:
  * - ``tanh``
  - x
  - Returns the hyperbolic tangent of x. The type of x and the return type are Real.
+ * - ``erf``
+ - x
+ - Returns the error function of x. The type of x and the return type are Real.
+ * - ``erfc``
+ - x
+ - Returns the complementary error function of x. The type of x and the return type are Real.
+ * - ``ceil``
+ - x
+ - Returns the ceil of x. The type of x and the return type are Real.
+ * - ``floor``
+ - x
+ - Returns the floor of x. The type of x and the return type are Real.
+ * - ``round``
+ - x
+ - Returns the rounded value of x. The type of x and the return type are Real.
  * - ``random_normal``
  - mean, std
  - Returns a sample from a normal (Gaussian) distribution with parameters "mean" and "standard deviation"