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Merge pull request #231 from NeuroML/development
Changes for NeuroML v2.3.1 release
2 parents 352244c + 42f1581 commit 50aacc6

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‎.github/workflows/ci.yml‎

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on:
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push:
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branches: [ master, development, experimental, documentation_update, osb* ]
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branches: [ master, development, experimental, documentation_update, osb*, update* ]
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pull_request:
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branches: [ master, development, experimental, documentation_update, osb* ]
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branches: [ master, development, experimental, documentation_update, osb*, update* ]
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jobs:
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build:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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java: [ '8', '11', '16', '17', '19' ]
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java: [ '8', '11', '16', '17', '19', '21' ]
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steps:
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- uses: actions/checkout@v3
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- uses: actions/checkout@v4
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- name: Set up JDK ${{ matrix.java }}
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uses: actions/setup-java@v3
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uses: actions/setup-java@v4
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with:
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java-version: ${{ matrix.java }}
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java-package: jdk
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distribution: 'adopt'
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distribution: 'temurin'
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- name: Install NeuroML 2 with Maven
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run: |

‎.github/workflows/omv-ci.yml‎

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branches: [ master, development, experimental, documentation_update, osb* ]
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branches: [ master, development, experimental, documentation_update, osb*, update* ]
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pull_request:
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branches: [ master, development, experimental, documentation_update, osb* ]
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branches: [ master, development, experimental, documentation_update, osb*, update* ]
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jobs:
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strategy:
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fail-fast: false
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matrix:
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python-version: [ 3.9 ]
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python-version: [ "3.9" ]
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engine:
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- jNeuroML
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- jNeuroML_Brian2
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- PyLEMS_NeuroML2
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steps:
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- uses: actions/checkout@v3
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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‎.gitignore‎

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/LEMSexamples/tmp
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arm64
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/examples/NML2_SingleCompHHCell.nml__flattened.xml
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/LEMSexamples/morphologies/*.mod
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/LEMSexamples/morphologies/*.c
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/LEMSexamples/morphologies/*.so
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*eden.py
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*netpyne.py
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*nrn.py
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/LEMSexamples/morphologies/*.dat
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/LEMSexamples/morphologies/*.hoc
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/LEMSexamples/morphologies/NET_m_in_b_in.net.nml
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/LEMSexamples/morphologies/simulator.props
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/LEMSexamples/morphologies/NET_m_in_b_out.net.nml
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/LEMSexamples/morphologies/NET_m_out_b_in.net.nml

‎.travis.yml‎

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‎HISTORY.md‎

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**Only contributors who are not [NeuroML Editors](https://docs.neuroml.org/NeuroMLOrg/Board.html) are specifically pointed out below.**
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v2.3.1 / 2024-08-25
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--------------------
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* **Renamed the main Schema from NeuroML_v2.3.xsd to [NeuroML_v2.3.1.xsd](https://github.com/NeuroML/NeuroML2/blob/master/Schemas/NeuroML2/NeuroML_v2.3.1).**
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* Adds support for external <morphology>/<biophysicalProperties> in cell element. Also simulator mappings for NEURON/NetPyNE support this. See [here](https://docs.neuroml.org/Userdocs/ImportingMorphologyFiles.html#neuroml2) for more details. Multiple examples of NeuroML2/LEMS files using this feature can be found [here](https://github.com/NeuroML/NeuroML2/tree/development/LEMSexamples/morphologies).
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* pyNeuroML analysis feature updates: better support for analysing kinetic scheme based channels in `pynml-channelanalysis`; better support for plotting generated spike trains with `pynml-plotspikes`.
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* Improved testing of Java based libraries on latest versions of Java and recent Mac OS versions.
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* Improved support for adding RDF annotations to NeuroML files.
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* Added ability to load (a subset of) XPPAUT files with `pynml-xpp` and export the model to LEMS or back to XPPAUT.
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* Improvements to handling of SBML and SED-ML files - added to pynml ability to validate both formats, or run SED-ML files which refer to SBML models using simulator tellurium.
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* Added option to archive NeuroML models as COMBINE Archives with `pynml-archive`.
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* Initial support for sending archived NeuroML models to Biosimulations.org for simulation.
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* Improved ability for pynml and related tools to detect the correct file type (NeuroML or LEMS) for the appropriate export/simulation option, and give advice when an incorrect file is provided.
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* Updates to `pynml-plotmorph` for plotting morphologies in 2D, and in 3D with VisPy.
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v2.3 / 2023-09-20
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‎LEMSexamples/morphologies/.test.jnml.omt‎

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# Script for running automated tests on OSB, see https://github.com/OpenSourceBrain/osb-model-validation
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target: LEMS_m_in_b_in.xml
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engine: jNeuroML
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mep: .test.mep
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experiments:
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Current clamp pyramidal:
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observables:
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spike times:
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file:
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path: pyramidal_soma_0.dat
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columns: [0,1]
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scaling: [1000, 1000]
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spike detection:
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method: threshold
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threshold: 0
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tolerance: 0.004018425953151025

‎LEMSexamples/morphologies/.test.jnmleden.multi.omt‎

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# Script for running automated tests on OSB, see https://github.com/OpenSourceBrain/osb-model-validation
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target: LEMS_pyrfull_in.xml
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engine: jNeuroML_EDEN
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mep: .test.multi.mep
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experiments:
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Current clamp pyramidal:
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observables:
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spike times:
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file:
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path: pyramidals_0.0.dat
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columns: [0,1]
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scaling: [1000, 1000]
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spike detection:
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method: threshold
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threshold: 0
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tolerance: 0.017719626168224333
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‎LEMSexamples/morphologies/.test.jnmleden.multi.out.omt‎

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# Script for running automated tests on OSB, see https://github.com/OpenSourceBrain/osb-model-validation
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target: LEMS_pyrfull_out.xml
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engine: jNeuroML_EDEN
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mep: .test.multi.mep
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experiments:
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Current clamp pyramidal:
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observables:
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spike times:
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file:
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path: pyramidals_0.0.dat
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columns: [0,1]
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scaling: [1000, 1000]
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spike detection:
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method: threshold
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threshold: 0
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tolerance: 0.017719626168224333
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‎LEMSexamples/morphologies/.test.jnmleden.omt‎

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# Script for running automated tests on OSB, see https://github.com/OpenSourceBrain/osb-model-validation
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target: LEMS_m_in_b_in.xml
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engine: jNeuroML_EDEN
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mep: .test.mep
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experiments:
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Current clamp pyramidal:
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observables:
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spike times:
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file:
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path: pyramidal_soma_0.dat
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columns: [0,1]
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scaling: [1000, 1000]
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spike detection:
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method: threshold
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threshold: 0
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tolerance: 0.0024858998690222445

‎LEMSexamples/morphologies/.test.jnmleden.out.omt‎

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# Script for running automated tests on OSB, see https://github.com/OpenSourceBrain/osb-model-validation
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target: LEMS_m_out_b_out.xml
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engine: jNeuroML_EDEN
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mep: .test.mep
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experiments:
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Current clamp pyramidal:
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observables:
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spike times:
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file:
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path: pyramidal_soma_0.dat
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columns: [0,1]
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scaling: [1000, 1000]
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spike detection:
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method: threshold
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threshold: 0
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tolerance: 0.0024858998690222445

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