Changeset 378

Timestamp:

06/20/08 13:01:57 (5 years ago)

Author:

apdavison

Message:

Removed a few debugging statements in neuron2.

Location:

trunk

Files:

• src/neuron2/__init__.py (modified) (3 diffs)
• src/neuron2/cells.py (modified) (2 diffs)
• test/neuron2tests.py (modified) (1 diff)

trunk/src/neuron2/__init__.py

@@ -254 +254 @@
         else:
             self.celltype = cellclass
-        
+
         # Build the arrays of cell ids
         # Cells on the local node are represented as ID objects, other cells by integers
@@ -532 +532 @@
                     'First cell on this node:',
                     '  ID: %(local_first_id)d',
-                    '  Parameters: %(cell_parameters)s',
-                   ]
+                    '  Parameters: %(cell_parameters)s']
             template = "\n".join(rows)
         context = self.__dict__.copy()
@@ -607 +606 @@
             connection_method(method_parameters)
         elif isinstance(method, common.Connector):
-            print "simulator.gid_counter = ", simulator.State.gid_counter
             method.connect(self)
             

trunk/src/neuron2/cells.py

@@ -117 +117 @@
             self.vtrace.record(self, 'v')
             self.record_times = neuron.Vector()
-            neuron.h('%s.record(&t)' % self.record_times.name)
+            neuron.h('tmp = %s.record(&t)' % self.record_times.name)
         else:
             self.vtrace = None
-            self.record_times
+            self.record_times = None
     
     def memb_init(self, v_init=None):
@@ -175 +175 @@
         if not self.do_not_record: # for VecStims, etc, recording doesn't make sense as we already have the spike times
             if active:
-                self.spiketimes.hoc_obj.printf()
                 self.rec = neuron.NetCon(self.source, None)
                 self.rec.record(self.spiketimes.hoc_obj)

trunk/test/neuron2tests.py

@@ -497 +497 @@
         neuron.run(100.0)
         spikes = spike_source.getSpikes()
-        print spikes
         spikes = spikes[:,0]
         if neuron.rank() == 0: