Add eden tests

Author: pgleeson

.github/workflows/omv-ci.yml

@@ -15,25 +15,25 @@ jobs:
       fail-fast: false
       matrix:
         python-version: [ 3.9 ]
-        engine: [ jNeuroML, jNeuroML_NEURON, jNeuroML_validate, jNeuroML_Moose ]
+        engine: [ jNeuroML, jNeuroML_NEURON, jNeuroML_validate, jNeuroML_Moose, jNeuroML_EDEN ]
 
     steps:
     - uses: actions/checkout@v2
-    
+
     - name: Set up Python  ${{ matrix.python-version }}
       uses: actions/setup-python@v2
       with:
         python-version:  ${{ matrix.python-version }}
-        
+
     - name: Install OMV
       run: |
         pip install git+https://github.com/OpenSourceBrain/osb-model-validation
         pip install scipy sympy matplotlib cython pandas tables
-        
+
     - name: Run OMV tests on engine ${{ matrix.engine }}
       run: |
         omv all -V --engine=${{ matrix.engine }}
-        
+
     - name: OMV final version info
       run: |
         omv list -V # list installed engines

.gitignore

@@ -24,3 +24,6 @@ simulations
 /neuroConstruct/generatedNeuroML2/LEMS_Test_Na_ChannelML.xml
 /neuroConstruct/generatedNeuroML2/*.json
 /neuroConstruct/generatedNeuroML2/*_moose.py
+*.gen.c
+*.gen.so
+*_eden.py

neuroConstruct/generatedNeuroML2/.test.big.jnmlnrn.omt

@@ -1,17 +1,40 @@
-# Script for running automated tests on OSB using Travis-CI, see https://github.com/borismarin/osb-model-validation  
+# Script for running automated tests on OSB using Travis-CI, see https://github.com/borismarin/osb-model-validation
 
 target: LEMS_MainenEtAl_PyramidalCell.xml
 engine: jNeuroML_NEURON
 mep: .test.big.mep
 experiments:
-  Current clamp:
+  Current clamp 1:
     observables:
       spike times:
-        file: 
+        file:
           path: NeuroMLBased_0.0.dat
           columns: [0,1]
           scaling: [1000, 1000]
-        spike detection: 
+        spike detection:
           method: threshold
           threshold: 0
         tolerance: 0
+  Current clamp 2:
+    observables:
+      spike times:
+          file:
+            path: NeuroMLBased_0.4197.dat
+            columns: [0,1]
+            scaling: [1000, 1000]
+          spike detection:
+            method: threshold
+            threshold: -20
+          tolerance: 0
+
+  Current clamp 3:
+    observables:
+      spike times:
+          file:
+            path: NeuroMLBased_0.5649.dat
+            columns: [0,1]
+            scaling: [1000, 1000]
+          spike detection:
+            method: threshold
+            threshold: 0
+          tolerance: 0

neuroConstruct/generatedNeuroML2/.test.big.mep

@@ -1,6 +1,12 @@
 system: Testing a single compartment cell
 
 experiments:
-  Current clamp:
+  Current clamp 1:
     expected:
       spike times: [29.11]
+  Current clamp 2:
+    expected:
+      spike times: [31.3]
+  Current clamp 3:
+    expected:
+      spike times: [28.71]

neuroConstruct/generatedNeuroML2/.test.jnml.omt

@@ -1,4 +1,4 @@
-# Script for running automated tests on OSB using Travis-CI, see https://github.com/borismarin/osb-model-validation  
+# Script for running automated tests on OSB using Travis-CI, see https://github.com/borismarin/osb-model-validation
 
 target: LEMS_OneComp.xml
 engine: jNeuroML
@@ -7,11 +7,11 @@ experiments:
   Current clamp:
     observables:
       spike times:
-        file: 
+        file:
           path: One_ChannelML_0.dat
           columns: [0,1]
           scaling: [1000, 1000]
-        spike detection: 
+        spike detection:
           method: threshold
           threshold: -46
-        tolerance: 0.00081
+        tolerance: 0.0008051529790659768

neuroConstruct/generatedNeuroML2/.test.jnmleden.omt

@@ -0,0 +1,17 @@
+# Script for running automated tests on OSB using Travis-CI, see https://github.com/borismarin/osb-model-validation
+
+target: LEMS_OneComp.xml
+engine: jNeuroML_EDEN
+mep: .test.mep
+experiments:
+  Current clamp:
+    observables:
+      spike times:
+        file:
+          path: One_ChannelML_0.dat
+          columns: [0,1]
+          scaling: [1000, 1000]
+        spike detection:
+          method: threshold
+          threshold: -46
+        tolerance: 0.0021748412353196243