Changeset 971 for trunk

Timestamp:

05/27/11 23:46:00 (12 months ago)

Author:

emuller

Message:

Integrating Mike Hull's code for joining based on a Model built of heirarchical components

Location:

trunk/src

Files:

• neuron/nineml.py (modified) (3 diffs)
• nineml/cells.py (modified) (1 diff)

trunk/src/neuron/nineml.py

@@ -23 +23 @@
 import neuron
 from pyNN.models import BaseCellType
-from pyNN.nineml.cells import _build_nineml_celltype
+from pyNN.nineml.cells import _build_nineml_celltype, _mh_build_nineml_celltype
+from pyNN.nineml.cells import CoBaSyn 
 import logging
 import os
@@ -83 +84 @@
 
 
-def _compile_nmodl(nineml_component, weight_variables): # weight variables should really be within component
+def _compile_nmodl(nineml_component, weight_variables, hierarchical_mode=None): # weight variables should really be within component
     """
     Generate NMODL code for the 9ML component, run "nrnivmodl" and then load
@@ -115 +116 @@
 
 
+
+
+
+
+
+def nineml_celltype_from_model(name, nineml_model, synapse_components):
+    """
+    Return a new NineMLCellType subclass from a NineML model.
+    """
+    
+    dct = {'nineml_model':nineml_model,
+           'synapse_components':synapse_components,
+           'builder': _compile_nmodl} 
+    return _mh_build_nineml_celltype(name, (NineMLCellType,), dct)
+

trunk/src/nineml/cells.py

@@ -366 +366 @@
 
 
-
-
-
-
+class _mh_build_nineml_celltype(type):
+    """
+    Metaclass for building NineMLCellType subclasses
+    Called by nineml_celltype_from_model
+    """
+    def __new__(cls, name, bases, dct):
+        
+        
+        #Extract Parameters Back out from Dict:
+        nineml_model = dct['nineml_model']
+        synapse_components = dct['synapse_components']
+
+        # Reduce the model:                    
+        from nineml.abstraction_layer import models               
+        reduction_process = models.ModelToSingleComponentReducer(nineml_model, componentname=name)
+        reduced_component = reduction_process.reducedcomponent
+        
+        # New:
+        dct["combined_model"] = reduction_process.reducedcomponent
+        dct["default_parameters"] = dict( (name, 1.0) for name in reduced_component.parameters )
+        dct["default_initial_values"] = dict((name, 0.0) for name in reduced_component.state_variables)
+        dct["synapse_types"] = [syn.namespace for syn in synapse_components] 
+        dct["standard_receptor_type"] = (dct["synapse_types"] == ('excitatory', 'inhibitory'))
+        dct["injectable"] = True # need to determine this. How??
+        dct["conductance_based"] = True # how to determine this??
+        dct["model_name"] = name
+        
+        
+        dct["recordable"] = [port.name for port in reduced_component.analog_ports] + ['spikes', 'regime']
+        dct["weight_variables"] = dict([ (syn.namespace,syn.namespace+'_'+syn.weight_connector )
+                                         for syn in synapse_components ])
+        #{'cobaInhib':'cobaInhib_q', 'cobaExcit':'cobaExcit_q',}
+        
+        
+        logger.debug("Creating class '%s' with bases %s and dictionary %s" % (name, bases, dct))
+        # generate and compile NMODL code, then load the mechanism into NEUORN
+        dct["builder"](reduced_component, dct["weight_variables"], hierarchical_mode=True)
+        # TODO: weight variables should really be stored within combined_model
+        
+        return type.__new__(cls, name, bases, dct)
+        
+
+      
+class CoBaSyn(object):
+    def __init__(self, namespace, weight_connector):
+        self.namespace = namespace
+        self.weight_connector = weight_connector
+
+
+
+
+