OpenSourceBrain · pgleeson · Jun 16, 2025 · Jun 16, 2025 · Jun 16, 2025 · Aug 4, 2025
diff --git a/.github/workflows/omv-ci.yml b/.github/workflows/omv-ci.yml
@@ -33,18 +33,19 @@ jobs:
 
         pip install matplotlib "cython<3.1.0"  # let omv handle other deps...
 
+        pip list
+
 
     - name: Run OMV tests on engine ${{ matrix.engine }}
       run: |
         omv all -V --engine=${{ matrix.engine }}
 
     - name: Regenerate
       run: |
-        export JNML_HOME=/home/runner/jnml/jNeuroMLJar
-        export PATH=$JNML_HOME:$PATH
+        omv install pyNeuroML # required for regeneration (installs jnml too)...
         omv install PyNN # required for regeneration...
-        omv install pyNeuroML # required for regeneration...
-        omv install jNeuroML
+
+        which pynml
         which jnml
         ./regenerate.sh
 

diff --git a/NeuroML2/ConnectionsTest.net.nml b/NeuroML2/ConnectionsTest.net.nml
@@ -3,7 +3,7 @@
     This NeuroML 2 file has been generated from: 
         PyNN v0.11.0
         libNeuroML v0.6.8
-        pyNeuroML v1.3.19
+        pyNeuroML v1.3.22
     </notes>
     <IF_cond_alpha id="IF_cond_alpha_pop_pre" cm="1.0" i_offset="0.9" tau_syn_E="2.0" tau_syn_I="5.0" v_init="-65.0" tau_m="20.0" tau_refrac="5.0" v_reset="-65.0" v_rest="-65.0" v_thresh="-50.0" e_rev_E="0.0" e_rev_I="-70.0"/>
     <IF_cond_alpha id="IF_cond_alpha_pop_post" cm="1.0" i_offset="0.9" tau_syn_E="2.0" tau_syn_I="5.0" v_init="-65.0" tau_m="20.0" tau_refrac="5.0" v_reset="-65.0" v_rest="-65.0" v_thresh="-50.0" e_rev_E="0.0" e_rev_I="-70.0"/>
@@ -17,38 +17,38 @@
             <property tag="radius" value="5"/>
             <property tag="color" value="0 0.6 0"/>
             <instance id="0">
-                <location x="67.968888080621582" y="-70.657158602734654" z="-18.315070185150397"/>
+                <location x="33.296910100473951" y="27.713445085977749" z="71.994178947596652"/>
             </instance>
             <instance id="1">
-                <location x="60.184476562654041" y="60.493279624680454" z="-4.759239011557659"/>
+                <location x="10.842716843519874" y="0.917808021541955" z="-88.042274948325058"/>
             </instance>
             <instance id="2">
-                <location x="27.189024038368114" y="-73.036270319949594" z="-25.447207420452678"/>
+                <location x="3.024377766328068" y="-35.381277701842315" z="-12.305946508278009"/>
             </instance>
             <instance id="3">
-                <location x="-24.852298939173203" y="-12.272599182378062" z="3.750079672379081"/>
+                <location x="24.442208569430512" y="7.749172597723941" z="-30.581955153541294"/>
             </instance>
             <instance id="4">
-                <location x="24.133497816283622" y="10.517195276874403" z="-29.329915036014633"/>
+                <location x="-20.111452541723661" y="-28.866255226421032" z="-13.57805742975855"/>
             </instance>
         </population>
         <population id="pop_post" component="IF_cond_alpha_pop_post" size="5" type="populationList">
             <property tag="radius" value="5"/>
             <property tag="color" value="0 0.2 0.6"/>
             <instance id="0">
-                <location x="24.765200337632276" y="242.663676551724933" z="75.097696646567741"/>
+                <location x="48.092365001768435" y="247.384772297144536" z="-46.469829020515952"/>
             </instance>
             <instance id="1">
-                <location x="45.028559466580795" y="226.140823198868731" z="48.181218144946691"/>
+                <location x="40.668431248246016" y="236.274349388629332" z="72.850475010697707"/>
             </instance>
             <instance id="2">
-                <location x="52.54517028397283" y="161.954657204140887" z="-5.258407353297101"/>
+                <location x="39.11264242985402" y="127.561019162501267" z="17.073295935589638"/>
             </instance>
             <instance id="3">
-                <location x="-33.575509675391338" y="195.289896982416423" z="-19.682584593824927"/>
+                <location x="1.337202788724356" y="230.754475702777199" z="-50.029518811009808"/>
             </instance>
             <instance id="4">
-                <location x="-14.798277951638838" y="173.216535964582647" z="93.772913738872958"/>
+                <location x="-67.325840204631589" y="212.852557159341472" z="-10.922731240975093"/>
             </instance>
         </population>
         <projection id="pop_pre__TO__pop_post" presynapticPopulation="pop_pre" postsynapticPopulation="pop_post" synapse="syn__pop_pre__TO__pop_post">

diff --git a/NeuroML2/Inputs.net.nml b/NeuroML2/Inputs.net.nml
@@ -3,7 +3,7 @@
     This NeuroML 2 file has been generated from: 
         PyNN v0.11.0
         libNeuroML v0.6.8
-        pyNeuroML v1.3.19
+        pyNeuroML v1.3.22
     </notes>
     <pulseGenerator id="DCSource_DCSource_0" delay="50.0ms" duration="350.0ms" amplitude="0.9nA"/>
     <compoundInput id="ACSource_ACSource_1">

diff --git a/NeuroML2/LEMS_Sim_Inputs.xml b/NeuroML2/LEMS_Sim_Inputs.xml
@@ -4,7 +4,7 @@
     This LEMS file has been generated from: 
         PyNN v0.11.0
         libNeuroML v0.6.8
-        pyNeuroML v1.3.19
+        pyNeuroML v1.3.22
      -->
 
     <!-- Specify which component to run -->

diff --git a/NeuroML2/LEMS_Sim_PyNN_NeuroML2_Export.xml b/NeuroML2/LEMS_Sim_PyNN_NeuroML2_Export.xml
@@ -4,7 +4,7 @@
     This LEMS file has been generated from: 
         PyNN v0.11.0
         libNeuroML v0.6.8
-        pyNeuroML v1.3.19
+        pyNeuroML v1.3.22
      -->
 
     <!-- Specify which component to run -->

diff --git a/NeuroML2/PyNN_NeuroML2_Export.net.nml b/NeuroML2/PyNN_NeuroML2_Export.net.nml
@@ -3,7 +3,7 @@
     This NeuroML 2 file has been generated from: 
         PyNN v0.11.0
         libNeuroML v0.6.8
-        pyNeuroML v1.3.19
+        pyNeuroML v1.3.22
     </notes>
     <IF_curr_alpha id="IF_curr_alpha_pop_IF_curr_alpha" cm="1.0" i_offset="0.9" tau_syn_E="2.0" tau_syn_I="5.0" v_init="-65.0" tau_m="20.0" tau_refrac="10.0" v_reset="-62.0" v_rest="-65.0" v_thresh="-52.0"/>
     <IF_curr_exp id="IF_curr_exp_pop_IF_curr_exp" cm="1.0" i_offset="1.0" tau_syn_E="2.0" tau_syn_I="5.0" v_init="-65.0" tau_m="20.0" tau_refrac="8.0" v_reset="-70.0" v_rest="-65.0" v_thresh="-50.0"/>

diff --git a/PyNN/NeuroMLTest_PyNN0.9.py b/PyNN/NeuroMLTest_PyNN0.9.py
@@ -100,11 +100,18 @@ def get_source_id(spiketrain):
         elif 'channel_id' in spiketrain.annotations: # See https://github.com/NeuralEnsemble/PyNN/pull/762
             return spiketrain.annotations['channel_id']
 
+    def get_source_ids_as(analogsignal):
+        if 'source_ids' in analogsignal.annotations:
+            return analogsignal.annotations['source_ids']
+        elif 'channel_ids' in analogsignal.annotations: # See https://github.com/NeuralEnsemble/PyNN/pull/762
+            return analogsignal.annotations['channel_ids']
+
+
     for pop in [pop_IF_curr_alpha, pop_IF_curr_exp, pop_IF_cond_exp, pop_IF_cond_alpha,pop_EIF_cond_exp_isfa_ista, pop_HH_cond_exp, pop_post1,pop_post2]:
         data =  pop.get_data('v', gather=False)
         analogsignal = data.segments[0].analogsignals[0]
         name = analogsignal.name
-        source_ids = analogsignal.annotations['source_ids']
+        source_ids = get_source_ids_as(analogsignal)
         print('Saving data recorded for %s in pop %s, global ids: %s'%(name, pop.label, source_ids))
         for i in range(len(source_ids)):
             glob_id = source_ids[i]