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pgleesonpgleeson
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Merge pull request #30 from NeuroML/development
Mainly work on MDF support
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‎.github/workflows/ci.yml‎

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- name: Install some simulators for testing
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run: |
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pip install cython
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if [[ ${{ matrix.python-version }} != 2.7 ]]; then omv install PyNEST; fi
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#pip install cython
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omv install NEURON
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omv install NetPyNE
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pip install NetPyNE # strange issues on py3.7 with omv install...
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omv install PyNN
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omv install jNeuroML
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omv install Brian2
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if [[ ${{ matrix.python-version }} != 2.7 ]]; then omv install PyNEST; fi
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omv list -V # list installed engines
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- name: Run pytest
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run: |
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pip install pytest tables # tables for Sonata test file
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cd neuromllite/test/
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pytest -v
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- name: Run tests
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- name: Regenerate and test
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run: |
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export PATH=$PATH:$JNML_HOME
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echo "===================="
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# All tests
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./regenerateAndTest.sh
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- name: Run OMV tests
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run: |
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omv all -V --engine=jNeuroML_NEURON # limited for now, issues with nest...
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- name: OMV final version info
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run: |

‎examples/BBP_5percent.json‎

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{
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"BBP_5percent": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"network_reader": {
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"type": "BBPConnectomeReader",
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"parameters": {

‎examples/Example10_Lorenz.json‎

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{
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"Example10_Lorenz": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"parameters": {
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"N": 1,
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"sigma": 10,

‎examples/Example10_Lorenz.mdf.yaml‎

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default_initial_value: z0
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time_derivative: ( x * y - b * z) / sec
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input_ports: {}
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output_ports: {}
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output_ports:
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x:
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value: x
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y:
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value: y
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z:
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value: z
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notes: "Cell: [Cell (lorenzCell), lems_source_file = test_files/Lorenz1963.xml,\
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\ parameters = {'sigma': 'sigma', 'b': 'b', 'r': 'r', 'x0':\
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\ 'x0', 'y0': 'y0', 'z0': 'z0'}] is defined in /home/padraig/NeuroMLlite/examples/test_files/Lorenz1963.xml\
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\ 'x0', 'y0': 'y0', 'z0': 'z0'}] is defined in test_files/Lorenz1963.xml\
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\ and in Lems is: Component, id: lorenzCell, type: lorenz,\n\
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\ parameters: {'sigma': '10', 'b': '2.67', 'r': '28', 'x0':\
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\ '1.0', 'y0': '1.0', 'z0': '1.0'}\n parent: None\n"

‎examples/Example11_Synapses.json‎

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{
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"Example11_Synapses": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"parameters": {
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"input_amp": 0.23,
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"weight": 1.01

‎examples/Example11_Synapses.net.nml‎

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<neuroml xmlns="http://www.neuroml.org/schema/neuroml2" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.2.xsd" id="Example11_Synapses">
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<notes>Generated by NeuroMLlite v0.4.1
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<notes>Generated by NeuroMLlite v0.4.2
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Generated network: Example11_Synapses
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Generation seed: 1234
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NeuroMLlite parameters:

‎examples/Example1_TestNetwork.json‎

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{
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"TestNetwork": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"notes": "A simple network with 2 populations & projection between them. No info yet on what the cells are so network can't be simulated.",
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"populations": {
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"pop0": {

‎examples/Example2_TestNetwork.json‎

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{
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"Example2_TestNetwork": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"notes": "A simple network with 2 populations & projection between them. Cells are specified to be NeuroML 2 HH cell models & pre population is given a spiking input.",
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"cells": {
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"hhcell": {

‎examples/Example2_TestNetwork.net.nml‎

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<neuroml xmlns="http://www.neuroml.org/schema/neuroml2" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.2.xsd" id="Example2_TestNetwork">
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<notes>Generated by NeuroMLlite v0.4.1
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<notes>Generated by NeuroMLlite v0.4.2
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Generated network: Example2_TestNetwork
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Generation seed: 1234</notes>
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<include href="test_files/inputs.nml"/>

‎examples/Example3_Network.json‎

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{
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"Example3_Network": {
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"version": "NeuroMLlite v0.4.1",
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"version": "NeuroMLlite v0.4.2",
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"notes": "Example 3: simple network with 2 populations of NeuroML2 cells, a projection between them and spiking input.",
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"cells": {
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"hhcell": {

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