Merge pull request #112 from NeuroML/feat/netpyne-cvode

netpyne: expose cvode bits from LEMS

src/main/java/org/lemsml/export/dlems/DLemsKeywords.java

@@ -2,79 +2,83 @@
 
 /**
  * @author matteocantarelli
- * 
+ *
  */
 public enum DLemsKeywords
 {
-	DT, 
-	SEED, 
-	REPORT_FILE, 
-    DYNAMICS, 
-    EVENTS, 
-    CONDITION, 
-    DIRECTION, 
-    EFFECT, 
-    NAME, 
-    TYPE, 
-    TITLE, 
-    PARAMETERS, 
-    STATE, 
-    STATE_FUNCTIONS, 
-    T_END, 
-    T_START, 
-    COMMENT, 
-    DUMP_TO_FILE, 
-    OUTPUT_FILE, 
-    SPIKE_FILE, 
-    SPIKE_FILE_FORMAT, 
-    EVENT_SELECTIONS, 
-    EVENT_SELECTION_ID, 
-    SELECT, 
-    EVENT_PORT, 
-    FILE_NAME, 
-    OUTPUT_COLUMNS, 
-    VARIABLE, 
-    QUANTITY, 
-    DISPLAY, 
-    ABSCISSA_AXIS, 
-    MIN, MAX, 
-    ORDINATE_AXIS, 
-    CURVES, 
-    ABSCISSA, 
-    ORDINATE, 
-    POPULATION, 
-    POPULATION_INDEX, 
-    SEGMENT_ID, 
-    SEGMENT_NAME, 
-    FRACTION_ALONG, 
-    COLOUR, 
-    POPULATIONS, 
-    SIZE, 
+    DT,
+    SEED,
+    REPORT_FILE,
+    DYNAMICS,
+    EVENTS,
+    CONDITION,
+    DIRECTION,
+    EFFECT,
+    NAME,
+    TYPE,
+    TITLE,
+    PARAMETERS,
+    STATE,
+    STATE_FUNCTIONS,
+    T_END,
+    T_START,
+    COMMENT,
+    DUMP_TO_FILE,
+    OUTPUT_FILE,
+    SPIKE_FILE,
+    SPIKE_FILE_FORMAT,
+    EVENT_SELECTIONS,
+    EVENT_SELECTION_ID,
+    SELECT,
+    EVENT_PORT,
+    FILE_NAME,
+    OUTPUT_COLUMNS,
+    VARIABLE,
+    QUANTITY,
+    DISPLAY,
+    ABSCISSA_AXIS,
+    MIN, MAX,
+    ORDINATE_AXIS,
+    CURVES,
+    ABSCISSA,
+    ORDINATE,
+    POPULATION,
+    POPULATION_INDEX,
+    SEGMENT_ID,
+    SEGMENT_NAME,
+    FRACTION_ALONG,
+    COLOUR,
+    POPULATIONS,
+    SIZE,
     SYNAPSES,
     SYNAPSE,
     COMPONENT,
-    PROJECTIONS, 
-    PRE_POPULATION, 
-    POST_POPULATION, 
+    PROJECTIONS,
+    PRE_POPULATION,
+    POST_POPULATION,
     CONNECTIONS,
-    PRE_CELL_ID, 
-    POST_CELL_ID, 
-    WEIGHT, 
-    DELAY, 
+    PRE_CELL_ID,
+    POST_CELL_ID,
+    WEIGHT,
+    DELAY,
     INPUTS,
-    
-    
+
+
     TEMPERATURE,
     NEURON_VARIABLE_NAME,
     NEURON_MECHANISM_NAME,
     NEURON_SECTION_NAME,
     NEURON_FRACT_ALONG,
     NEURON_VARIABLE_SCALE,
-
-    EXPORT_LIBRARY_VERSION;
 
-	public String get()
-	{
-		return this.toString().toLowerCase();
-	}
+    EXPORT_LIBRARY_VERSION,
+
+    CVODE,
+    ABS_TOL,
+    REL_TOL;
+
+    public String get()
+    {
+        return this.toString().toLowerCase();
+    }
 }

src/main/java/org/lemsml/export/dlems/DLemsWriter.java

@@ -31,7 +31,9 @@
 import org.lemsml.jlems.core.type.Dimension;
 import org.lemsml.jlems.core.type.FinalParam;
 import org.lemsml.jlems.core.type.Lems;
+import org.lemsml.jlems.core.type.LemsCollection;
 import org.lemsml.jlems.core.type.ParamValue;
+import org.lemsml.jlems.core.type.Meta;
 import org.lemsml.jlems.core.type.Target;
 import org.lemsml.jlems.core.type.dynamics.DerivedVariable;
 import org.lemsml.jlems.core.type.dynamics.IVisitable;
@@ -203,6 +205,38 @@ public String getMainScript() throws LEMSException, IOException
 
         g.writeStringField(DLemsKeywords.DT.get(), convertTime(simCpt.getParamValue("step")));
 
+        boolean nrn_cvode = false;
+        /* defaults from NEURON */
+        String abs_tol = "None";
+        String rel_tol = "None";
+        LemsCollection<Meta> metas = simCpt.metas;
+        for(Meta m : metas)
+        {
+            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 == true)
+        {
+            g.writeStringField(DLemsKeywords.CVODE.get(), "true");
+        }
+        else
+        {
+            g.writeStringField(DLemsKeywords.CVODE.get(), "false");
+        }
+        /* set them to something even if not provided by user */
+        g.writeStringField(DLemsKeywords.ABS_TOL.get(), abs_tol);
+        g.writeStringField(DLemsKeywords.REL_TOL.get(), rel_tol);
+
         int seed = DEFAULT_SEED;
         if (simCpt.hasStringValue("seed"))
             seed = Integer.parseInt(simCpt.getStringValue("seed"));

src/main/resources/netpyne/run.vm

@@ -14,7 +14,7 @@ import datetime
 
 class NetPyNESimulation():
 
-    def __init__(self, tstop=$t_end, dt=$dt, seed=123456789, save_json=False):
+    def __init__(self, tstop=$t_end, dt=$dt, seed=123456789, save_json=False, abs_tol=None):
 
         self.setup_start = time.time()
         #if ($report_file)
@@ -47,6 +47,13 @@ class NetPyNESimulation():
         self.simConfig.duration = self.simConfig.tstop = tstop # Duration of the simulation, in ms
         self.simConfig.dt = dt # Internal integration timestep to use
 
+        # cvode
+        if abs_tol is not None:
+            self.simConfig.cvode_active = True
+            self.simConfig.cvode_atol = abs_tol
+        else:
+            self.simConfig.cvode_active = False
+
         # Seeds for randomizers (connectivity, input stimulation and cell locations)
         # Note: locations and connections should be fully specified by the structure of the NeuroML,
         # so seeds for conn & loc shouldn't affect networks structure/behaviour
@@ -231,7 +238,7 @@ if __name__ == '__main__':
     save_json = '-json' in sys.argv
     no_run = '-norun' in sys.argv
 
-    ns = NetPyNESimulation(tstop=$t_end, dt=$dt, seed=$seed, save_json=save_json)
+    ns = NetPyNESimulation(tstop=$t_end, dt=$dt, seed=$seed, save_json=save_json, abs_tol=$abs_tol)
 
     if not no_run:
       ns.run()