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69 changes: 56 additions & 13 deletions src/main/java/org/neuroml/export/neuron/NeuronWriter.java
Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@
import org.lemsml.jlems.core.type.Property;
import org.lemsml.jlems.core.type.Requirement;
import org.lemsml.jlems.core.type.Target;
import org.lemsml.jlems.core.type.Meta;
import org.lemsml.jlems.core.type.dynamics.Case;
import org.lemsml.jlems.core.type.dynamics.ConditionalDerivedVariable;
import org.lemsml.jlems.core.type.dynamics.DerivedVariable;
Expand Down Expand Up @@ -329,7 +330,6 @@ public String getMainScript() throws GenerationException, NeuroMLException


Target target = lems.getTarget();

Component simCpt = target.getComponent();

String len = simCpt.getStringValue("length");
Expand All @@ -340,28 +340,58 @@ public String getMainScript() throws GenerationException, NeuroMLException
len = "" + Float.parseFloat(len) * 1000;
}

String dt = simCpt.getStringValue("step");
dt = dt.replaceAll("ms", "").trim();
if(dt.indexOf("s") > 0)
/* cvode usage:
* https://nrn.readthedocs.io/en/latest/hoc/simctrl/cvode.html
* - we do not currently support the local variable time step method
*/
boolean nrn_cvode = false;
String dt = "0.01";
/* defaults from NEURON */
String abs_tol = "None";
String rel_tol = "None";
LemsCollection<Meta> metas = simCpt.metas;
for(Meta m : metas)
{
dt = dt.replaceAll("s", "").trim();
dt = "" + Float.parseFloat(dt) * 1000;
HashMap<String, String> attributes = m.getAttributes();
if (attributes.getOrDefault("for", "").equals("neuron"))
{
if (attributes.getOrDefault("method", "").equals("cvode"))
{
nrn_cvode = true;
abs_tol = attributes.getOrDefault("abs_tolerance", abs_tol);
rel_tol = attributes.getOrDefault("rel_tolerance", rel_tol);
E.info("CVode with abs_tol="+abs_tol+" , rel_tol="+rel_tol+" selected for NEURON simulation");
}
}

}

if (nrn_cvode == false)
{
dt = simCpt.getStringValue("step");
dt = dt.replaceAll("ms", "").trim();
if(dt.indexOf("s") > 0)
{
dt = dt.replaceAll("s", "").trim();
dt = "" + Float.parseFloat(dt) * 1000;
}
}

main.append("class NeuronSimulation():\n\n");
int seed = DLemsWriter.DEFAULT_SEED;
if (simCpt.hasStringValue("seed"))
seed = Integer.parseInt(simCpt.getStringValue("seed"));

main.append(" def __init__(self, tstop, dt, seed="+seed+"):\n\n");
main.append(" def __init__(self, tstop, dt=None, seed="+seed+", abs_tol=None, rel_tol=None):\n\n");


Component targetComp = simCpt.getRefComponents().get("target");

main.append(bIndent+"print(\"\\n Starting simulation in NEURON of %sms generated from NeuroML2 model...\\n\"%tstop)\n\n");
main.append(bIndent+"self.setup_start = time.time()\n");
main.append(bIndent+"self.seed = seed\n");
main.append(bIndent+"self.abs_tol = abs_tol\n");
main.append(bIndent+"self.rel_tol = rel_tol\n");

if (target.reportFile!=null)
{
Expand Down Expand Up @@ -1306,8 +1336,14 @@ else if(cc.getComponentType().isOrExtends(NeuroMLElements.CONTINUOUS_CONNECTION_
main.append(toRec);

main.append(bIndent+"h.tstop = tstop\n\n");
main.append(bIndent+"h.dt = dt\n\n");
main.append(bIndent+"h.steps_per_ms = 1/h.dt\n\n");
main.append(bIndent+"if self.abs_tol is not None and self.rel_tol is not None:\n");
main.append(bIndent+" cvode = h.CVode()\n");
main.append(bIndent+" cvode.active(1)\n");
main.append(bIndent+" cvode.atol(self.abs_tol)\n");
main.append(bIndent+" cvode.rtol(self.rel_tol)\n");
main.append(bIndent+"else:\n");
main.append(bIndent+" h.dt = dt\n");
main.append(bIndent+" h.steps_per_ms = 1/h.dt\n\n");

if(!nogui)
{
Expand Down Expand Up @@ -1350,7 +1386,8 @@ else if(cc.getComponentType().isOrExtends(NeuroMLElements.CONTINUOUS_CONNECTION_
columnsPre.get(timeRef).add(bIndent+"h(' objectvar v_" + timeRef + " ')");
columnsPre.get(timeRef).add(bIndent+"h(' { v_" + timeRef + " = new Vector() } ')");
columnsPre.get(timeRef).add(bIndent+"h(' { v_" + timeRef + ".record(&t) } ')");
columnsPre.get(timeRef).add(bIndent+"h.v_" + timeRef + ".resize((h.tstop * h.steps_per_ms) + 1)");
columnsPre.get(timeRef).add(bIndent+"if self.abs_tol is None or self.rel_tol is None:\n");
columnsPre.get(timeRef).add(bIndent+" h.v_" + timeRef + ".resize((h.tstop * h.steps_per_ms) + 1)");

columnsPost0.get(timeRef).add(bIndent+"py_v_" + timeRef + " = [ t/1000 for t in h.v_" + timeRef + ".to_python() ] # Convert to Python list for speed...");

Expand Down Expand Up @@ -1410,7 +1447,8 @@ else if(cc.getComponentType().isOrExtends(NeuroMLElements.CONTINUOUS_CONNECTION_
columnsPre.get(outfileId).add(bIndent+"h(' objectvar v_" + colId + " ')");
columnsPre.get(outfileId).add(bIndent+"h(' { v_" + colId + " = new Vector() } ')");
columnsPre.get(outfileId).add(bIndent+"h(' { v_" + colId + ".record(&" + lqp.getNeuronVariableReference() + ") } ')");
columnsPre.get(outfileId).add(bIndent+"h.v_" + colId + ".resize((h.tstop * h.steps_per_ms) + 1)");
columnsPre.get(outfileId).add(bIndent+"if self.abs_tol is None or self.rel_tol is None:\n");
columnsPre.get(outfileId).add(bIndent+" h.v_" + colId + ".resize((h.tstop * h.steps_per_ms) + 1)");

float conv = NRNUtils.getNeuronUnitFactor(lqp.getDimension().getName());
String factor = (conv == 1) ? "" : " / " + conv;
Expand Down Expand Up @@ -1571,7 +1609,12 @@ else if (eofFormat.equals(EventWriter.FORMAT_ID_TIME))

main.append(bIndent+"self.initialized = True\n");
main.append(bIndent+"sim_start = time.time()\n");
main.append(bIndent+"print(\"Running a simulation of %sms (dt = %sms; seed=%s)\" % (h.tstop, h.dt, self.seed))\n\n");

main.append(bIndent+"if self.abs_tol is not None and self.rel_tol is not None:\n");
main.append(bIndent+" print(\"Running a simulation of %sms (cvode abs_tol = %sms, rel_tol = %sms; seed=%s)\" % (h.tstop, self.abs_tol, self.rel_tol, self.seed))\n");
main.append(bIndent+"else:\n");
main.append(bIndent+" print(\"Running a simulation of %sms (dt = %sms; seed=%s)\" % (h.tstop, h.dt, self.seed))\n\n");

main.append(bIndent+"try:\n");
main.append(bIndent+" h.run()\n");
main.append(bIndent+"except Exception as e:\n");
Expand Down Expand Up @@ -1709,7 +1752,7 @@ else if (eofFormat.equals(EventWriter.FORMAT_ID_TIME))

main.append("if __name__ == '__main__':\n\n");

main.append(" ns = NeuronSimulation(tstop="+len+", dt="+dt+", seed="+seed+")\n\n");
main.append(" ns = NeuronSimulation(tstop="+len+", dt="+dt+", seed="+seed+", abs_tol="+abs_tol+", rel_tol="+rel_tol+")\n\n");

main.append(" ns.run()\n\n");

Expand Down