def build_mod(self, modfile_set):
modfile = ModFile(
modtxt=postsynaptic_mechanisms_exp2syn_nmda_mgblocktimedep_modfile.
get_exp2_syn_nmda_mg_block_time_dependance_modfile(),
name='UnusedParameterXXXExpSyn2')
modfile_set.append(modfile)
def template_build_mod(self, modfile_set):
return
if not self.is_mod_built:
modfile_set.append(
ModFile(modtxt=postsynaptic_mechanisms_expsyn_modfile.
getExpSynModfile(),
name='UnusedParameterXXXExpSyn'))
self.is_mod_built = True
def template_build_mod(self, modfile_set):
if not self.is_mod_built:
import postsynaptic_mechanisms_exp2syn_nmda_modfile_new
modfile = ModFile(
modtxt=postsynaptic_mechanisms_exp2syn_nmda_modfile_new.
get_exp2_syn_nmda_modfile(),
name='UnusedParameterXXXExpSyn2')
modfile_set.append(modfile)
def __init__(self, xml_filename, xsl_filename, **kwargs):
super( NeuroML_Via_XSL_ChannelNEURON, self).__init__(xml_filename=xml_filename, xsl_filename=xsl_filename, **kwargs)
xslt_root = etree.parse(open(self.xsl_filename))
xsl_transform = etree.XSLT(xslt_root)
xml_root = etree.parse(open(self.xml_filename))
self.modtxt = str(xsl_transform(xml_root))
nrnsuffix = ModFile.extract_nrn_suffix_from_text(self.modtxt)
self.nrnsuffix = nrnsuffix
self.NRNSUFFIX = nrnsuffix
# ISSUE 'A': Extract out the reversal potential; and set it manually since the XSL method does not work:
self.chlData = ChannelMLReader.LoadChlRaw(xml_filename)
def __init__(self, xml_filename, xsl_filename, **kwargs):
super( NeuroML_Via_XSL_ChannelNEURON, self).__init__(xml_filename=xml_filename, xsl_filename=xsl_filename, **kwargs)
xslt_root = etree.parse(open(self.xsl_filename))
xsl_transform = etree.XSLT(xslt_root)
xml_root = etree.parse(open(self.xml_filename))
self.modtxt = str(xsl_transform(xml_root))
nrnsuffix = ModFile.extract_nrn_suffix_from_text(self.modtxt)
#self.name = nrnsuffix
self.nrnsuffix = nrnsuffix
self.NRNSUFFIX = nrnsuffix
# ISSUE 'A': Extract out the reversal potential; and set it manually since the XSL method does not work:
self.chlData = ChannelMLReader.LoadChlRaw(xml_filename)
def build_mod(self, modfile_set):
if NEURONGapJunction.is_first_build:
NEURONGapJunction.is_first_build = False
modfile = ModFile(modtxt=gap_mod, name='GapJunction')
modfile_set.append(modfile)
def template_build_mod(self, modfile_set):
if not self.is_mod_built:
modfile_set.append(
ModFile(modtxt=self.nmodl_txt,
name='UnusedParameterXXXExpSyn2'))
self.is_mod_built = True
def build_mod(self, modfile_set):
modfile = ModFile(modtxt=currentclampsinwaveTxt,
name='NeuronSinWaveCurrentClmap')
modfile_set.append(modfile)
def build_mod(self, modfile_set):
modfile = ModFile(modtxt=postsynaptic_mechanisms_exp2syn_nmda_modfile.
get_exp2_syn_nmda_modfile(vdep=self.vdep),
name='UnusedParameterXXXExpSyn2')
modfile_set.append(modfile)
def create_modfile(self, modfile_set):
mod_file = ModFile(name='EqnSetModfile', modtxt=self.mod_text)
modfile_set.append(mod_file)
def build_mod(self, modfile_set):
import postsynaptic_mechanisms_exp2syn_modfile
modfile = ModFile(
modtxt=postsynaptic_mechanisms_exp2syn_modfile.getExp2SynModfile(),
name='UnusedParameterXXXExpSyn2')
modfile_set.append(modfile)
def create_modfile(self, modfile_set):
modfile_set.append(ModFile(name=self.name, modtxt=self.nmodl_txt))
def create_modfile(self, modfile_set):
modFile = ModFile(name='NeuroMLViaXSLChannelNEURON_%s'
% self.name, modtxt=self.modtxt)
modfile_set.append(modFile)