Minor updates for NetworkBuilder

neuroml/hdf5/DefaultNetworkHandler.py

@@ -81,7 +81,7 @@ def handle_network(self, network_id, notes, temperature=None):
     #
     #  Should be overridden to create population array
     #  
-    def handle_population(self, population_id, component, size=-1, component_obj=None, properties={}):
+    def handle_population(self, population_id, component, size=-1, component_obj=None, properties={}, notes=None):
         sizeInfo = " as yet unspecified size"
         if size>=0:
             sizeInfo = " size: "+ str(size)+ " cells"

neuroml/hdf5/NetworkBuilder.py

@@ -27,6 +27,7 @@ class NetworkBuilder(DefaultNetworkHandler):
     populations = {}
     projections = {}
     projection_syns = {}
+    projection_types = {}
     projection_syns_pre = {}
     input_lists = {}
 
@@ -61,12 +62,16 @@ def handle_network(self, network_id, notes, temperature=None):
     #
     #  Overridden from DefaultNetworkHandler
     #    
-    def handle_population(self, population_id, component, size, component_obj=None, properties={}):
+    def handle_population(self, population_id, component, size, component_obj=None, properties={}, notes=None):
 
         if component_obj:
             self.nml_doc.append(component_obj)
 
         pop = neuroml.Population(id=population_id, component=component, size=size)
+
+        if notes and len(notes)>0:
+            pop.notes = notes
+
         self.populations[population_id] = pop
         self.network.populations.append(pop)
         for p in properties:
@@ -129,18 +134,23 @@ def handle_projection(self, id, prePop, postPop, synapse, hasWeights=False, hasD
             self.projection_syns_pre[id] = pre_synapse_obj.id
 
         self.projections[id] = proj
+        self.projection_types[id] = type
         self.weightDelays[id] = hasWeights or hasDelays
 
         self.log.debug("Projection: %s (%s) from %s to %s with syn: %s, weights: %s, delays: %s"%(id, type, prePop, postPop, synapse, hasWeights, hasDelays))
 
     #
     #  Overridden from DefaultNetworkHandler
     #
-    def finalise_projection(self, id, prePop, postPop, synapse=None, type="projection"):
+    def finalise_projection(self, id, prePop, postPop, synapse=None, type=None):
         '''
             Check whether handle_projection was not called, e.g. due to no connections present
         '''
-        self.log.debug("Projection: %s from %s to %s completed"%(id,prePop,postPop))
+        if type==None:
+            type=self.projection_types[id]
+
+        self.log.debug("Projection: %s (%s) from %s to %s completed"%(id,type,prePop,postPop))
+
         if type=="projection":
             present = False
             for p in self.network.projections:

neuroml/writers.py

@@ -10,7 +10,7 @@ def write(cls,nmldoc,file,close=True):
         via chain of responsibility pattern.
         """
 
-        if isinstance(file,str):
+        if isinstance(file,str) or isinstance(file,unicode):
             file = open(file,'w')
 
         #TODO: this should be extracted from the schema:
@@ -138,14 +138,14 @@ def __sanitize_doc(cls,neuroml_document):
 
     @classmethod
     def __file_handle(file):
-        if isinstance(cls,file,str):
+        if isinstance(cls,file,str) or isinstance(cls,file,unicode):
             import tables
             fileh = tables.open_file(filepath, mode = "w")
 
 
     @classmethod    
     def write(cls,neuroml_document,file):
-        if isinstance(file,str):
+        if isinstance(file,str) or isinstance(file,unicode):
             fileh = open(file, mode = 'w')
         else:
             fileh = file