def readNeuroMLFromFile(self,filename,params={}):
"""
For the format of params required to tweak what cells are loaded,
refer to the doc string of NetworkML.readNetworkMLFromFile().
Returns (populationDict,projectionDict),
see doc string of NetworkML.readNetworkML() for details.
"""
print "Loading neuroml file ... ", filename
moose.Neutral('/library') # creates /library in MOOSE tree; elif present, wraps
tree = ET.parse(filename)
root_element = tree.getroot()
self.model_dir = path.dirname( path.abspath( filename ) )
self.lengthUnits = root_element.attrib['lengthUnits']
self.temperature = CELSIUS_default # gets replaced below if tag for temperature is present
self.temperature_default = True
for meta_property in root_element.findall('.//{'+meta_ns+'}property'):
tagname = meta_property.attrib['tag']
if 'temperature' in tagname:
self.temperature = float(meta_property.attrib['value'])
self.temperature_default = False
if self.temperature_default:
print "Using default temperature of", self.temperature,"degrees Celsius."
self.nml_params = {
'temperature':self.temperature,
'model_dir':self.model_dir,
}
#print "Loading channels and synapses into MOOSE /library ..."
cmlR = ChannelML(self.nml_params)
for channels in root_element.findall('.//{'+neuroml_ns+'}channels'):
self.channelUnits = channels.attrib['units']
for channel in channels.findall('.//{'+cml_ns+'}channel_type'):
## ideally I should read in extra params
## from within the channel_type element and put those in also.
## Global params should override local ones.
cmlR.readChannelML(channel,params={},units=self.channelUnits)
for synapse in channels.findall('.//{'+cml_ns+'}synapse_type'):
cmlR.readSynapseML(synapse,units=self.channelUnits)
for ionConc in channels.findall('.//{'+cml_ns+'}ion_concentration'):
cmlR.readIonConcML(ionConc,units=self.channelUnits)
#print "Loading cell definitions into MOOSE /library ..."
mmlR = MorphML(self.nml_params)
self.cellsDict = {}
for cells in root_element.findall('.//{'+neuroml_ns+'}cells'):
for cell in cells.findall('.//{'+neuroml_ns+'}cell'):
cellDict = mmlR.readMorphML(cell,params={},lengthUnits=self.lengthUnits)
self.cellsDict.update(cellDict)
print "Loading individual cells into MOOSE root ... "
print self.cellsDict
nmlR = NetworkML(self.nml_params)
print self.cellsDict
return nmlR.readNetworkML(root_element,self.cellsDict,params=params,lengthUnits=self.lengthUnits)
def readNeuroMLFromFile(self,filename,params={}):
"""
For the format of params required to tweak what cells are loaded,
refer to the doc string of NetworkML.readNetworkMLFromFile().
Returns (populationDict,projectionDict),
see doc string of NetworkML.readNetworkML() for details.
"""
print "Loading neuroml file ... ", filename
tree = ET.parse(filename)
root_element = tree.getroot()
self.model_dir = path.dirname(path.abspath(filename))
try:
self.lengthUnits = root_element.attrib['lengthUnits']
except:
self.lengthUnits = root_element.attrib['length_units']
self.nml_params = {
'model_dir':self.model_dir,
}
if root_element.tag.rsplit('}')[1] == 'neuroml':
cellTag = neuroml_ns
else:
cellTag = mml_ns
mmlR = MorphML(self.nml_params)
self.cellsDict = {}
for cells in root_element.findall('.//{'+cellTag+'}cells'):
for cell in cells.findall('.//{'+cellTag+'}cell'):
cellDict = mmlR.readMorphML(cell,params={},length_units=self.lengthUnits)
self.cellsDict.update(cellDict)
if len(self.cellsDict) != 0:
return self.cellsDict
else:
nmlR = NetworkML(self.nml_params)
return nmlR.readNetworkML(root_element,self.cellsDict,params=params,lengthUnits=self.lengthUnits)