Python make_NMDA示例

示例#1

文件： loadMulti.py 项目： 2pysarthak/moose-examples

def loadElec():
	library = moose.Neutral( '/library' )
	moose.setCwe( '/library' )
	proto18.make_Ca()
	proto18.make_Ca_conc()
	proto18.make_K_AHP()
	proto18.make_K_C()
	proto18.make_Na()
	proto18.make_K_DR()
	proto18.make_K_A()
	proto18.make_glu()
	proto18.make_NMDA()
	proto18.make_Ca_NMDA()
	proto18.make_NMDA_Ca_conc()
	proto18.make_axon()
	model = moose.Neutral( '/model' )
	cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
	return cellId

示例#2

文件： TuringInNeuron.py 项目： lhhhu1990/moose

def loadElec():
    library = moose.Neutral( '/library' )
    moose.setCwe( '/library' )
    proto18.make_Ca()
    proto18.make_Ca_conc()
    proto18.make_K_AHP()
    proto18.make_K_C()
    proto18.make_Na()
    proto18.make_K_DR()
    proto18.make_K_A()
    proto18.make_glu()
    proto18.make_NMDA()
    proto18.make_Ca_NMDA()
    proto18.make_NMDA_Ca_conc()
    proto18.make_axon()
    model = moose.element( '/model' )
    cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
    return cellId

示例#3

文件： runcell18.py 项目： rgayatri23/moose-examples

	if ( os.path.exists( fname ) ):
		os.remove( fname )
	tab.xplot( fname, 'soma.Vm' )
	catab.xplot( fname, 'soma.Ca' )

library = moose.Neutral( '/library' )
moose.setCwe( '/library' )
proto18.make_Ca()
proto18.make_Ca_conc()
proto18.make_K_AHP()
proto18.make_K_C()
proto18.make_Na()
proto18.make_K_DR()
proto18.make_K_A()
proto18.make_glu()
proto18.make_NMDA()
proto18.make_Ca_NMDA()
proto18.make_NMDA_Ca_conc()
proto18.make_axon()

cellId = moose.loadModel( 'ca1_asym.p', '/cell', "hsolve" )
moose.le( cellId )
moose.le( '/cell/lat_14_1' )
#le( '/cell' )
graphs = moose.Neutral( '/graphs' )
tab = moose.Table( '/graphs/soma' )
catab = moose.Table( '/graphs/ca' )
soma = moose.element( '/cell/soma' )
soma.inject = 2e-10
moose.connect( tab, 'requestOut', soma, 'getVm' )
capool = moose.element( '/cell/soma/Ca_conc' )