def _addParameters(self, params):
from .. import sim
for label, param in params.items():
# regions
if 'regions' not in param:
print(
' Error creating State %s: "regions" parameter was missing' %
(label))
continue
if not isinstance(param['regions'], list):
param['regions'] = [param['regions']]
try:
nrnRegions = [
self.rxd['regions'][region]['hObj']
for region in param['regions']
]
except:
print(' Error creating State %s: could not find regions %s' %
(label, param['regions']))
if 'name' not in param:
param['name'] = None
if 'charge' not in param:
param['charge'] = 0
if 'value' not in param:
param['value'] = 0
if isinstance(param['value'], basestring):
funcStr = self._replaceRxDStr(param['value'],
constants=True,
regions=True,
species=True)
# create final function dynamically from string
importStr = ' from neuron import crxd as rxd \n from netpyne import sim'
afterDefStr = 'sim.net.rxd["parameters"]["%s"]["initialFunc"] = value' % (
label)
funcStr = 'def value (node): \n%s \n return %s \n%s' % (
importStr, funcStr, afterDefStr) # convert to lambda function
try:
exec(funcStr, {'rxd': rxd}, {'sim': sim})
value = sim.net.rxd["parameters"][label]["initialFunc"]
except:
print(
' Error creating Parameter %s: cannot evaluate "value" expression -- "%s"'
% (label, param['value']))
continue
else:
value = param['value']
# call rxd method to create Region
self.rxd['parameters'][label]['hObj'] = rxd.Parameter(
regions=nrnRegions,
value=value,
charge=param['charge'],
name=param['name'])
print(' Created Parameter %s' % (label))
# Who?
x = rxd.Species(
[cyt, org, cyt_org_membrane, cyt_ecs_membrane, ecs],
name="x",
d=1.0,
charge=1,
initial=0,
)
Xcyt = x[cyt]
Xorg = x[org]
Xecs = x[ecs]
# What? - produce X in cell 1
# parameter to limit production to cell 1
cell1_param = rxd.Parameter(org,
initial=lambda node: 1.0
if node.segment.sec == cell1 else 0)
# production with a rate following Michaels Menton kinetics
createX = rxd.Rate(Xorg, cell1_param[org] * 1.0 / (10.0 + Xorg))
# leak between organelles and cytosol
cyt_org_leak = rxd.MultiCompartmentReaction(Xcyt,
Xorg,
1e4,
1e4,
membrane=cyt_org_membrane,
membrane_flux=False)
from math import pi
e = 1.60217662e-19
d=1e3,
charge=1,
initial=init(10.0, 140.0),
ecs_boundary_conditions=140)
x = rxd.Species([cyt, mem, ecs], name='x', charge=1)
ki, ko, nai, nao, xi, xo = k[cyt], k[ecs], na[cyt], na[ecs], x[cyt], x[ecs]
# gates
ngate = rxd.State([cyt, mem], name='ngate', initial=0.24458654944007166)
mgate = rxd.State([cyt, mem], name='mgate', initial=0.028905534475191907)
hgate = rxd.State([cyt, mem], name='hgate', initial=0.7540796658225246)
# somaA parameter
pA = rxd.Parameter([cyt, mem],
name='paramA',
initial=lambda nd: 1 if nd.segment in somaA else 0)
#What
# gates
m_gate = rxd.Rate(mgate, (minf - mgate) / mtau)
h_gate = rxd.Rate(hgate, (hinf - hgate) / htau)
n_gate = rxd.Rate(ngate, (ninf - ngate) / ntau)
# Nernst potentials
ena = 1e3 * h.R * (h.celsius + 273.15) * log(nao / nai) / h.FARADAY
ek = 1e3 * h.R * (h.celsius + 273.15) * log(ko / ki) / h.FARADAY
gna = pA * gnabar * mgate**3 * hgate
gk = pA * gkbar * ngate**4
def Declare_Parameters(**kwargs):
"""helper function enabling clean declaration of parameters in top namespace"""
for key, value in kwargs.items():
globals()[key] = rxd.Parameter(r, name=key, initial=value)
from neuron import h, crxd as rxd
h.load_file("stdrun.hoc")
cell = h.Section(name="cell")
r = rxd.Region([cell])
def Declare_Parameters(**kwargs):
"""helper function enabling clean declaration of parameters in top namespace"""
for key, value in kwargs.items():
globals()[key] = rxd.Parameter(r, name=key, initial=value)
def Declare_Species(**kwargs):
"""helper function enabling clean declaration of species in top namespace"""
for key, value in kwargs.items():
globals()[key] = rxd.Species(r, name=key, initial=value)
k3 = rxd.Parameter(r, name="k3", initial=1.2)
k4 = rxd.Parameter(r, name="k4", initial=0.6)
P2 = rxd.Species(r, name="P2", initial=0.0614368)
T2 = rxd.Species(r, name="T2", initial=0.0145428)
C = rxd.Species(r, name="C", initial=0.207614)
h.finitialize(-65)
h.continuerun(72)
cyt = rxd.Region(h.allsec(), name='cyt', nrn_region='i')
# membrane
mem = rxd.Region(h.allsec(), name='cell_mem', geometry=rxd.membrane())
# extracellular
ecs = rxd.Extracellular(-100, -100, -100, 100, 100, 100, dx=33)
# Who? ions & gates
# intracellular sodium & potassium
na = rxd.Species([cyt, mem], name='na', d=1, charge=1, initial=10)
k = rxd.Species([cyt, mem], name='k', d=1, charge=1, initial=54.4)
# extracellular parameters provide a constant concentration for the Nernst potential and reactions.
kecs = rxd.Parameter(ecs, name='k_ecs', charge=1, value=2.5)
naecs = rxd.Parameter(ecs, name='na_ecs', charge=1, value=140)
# an undistinguished charged ion for the leak current
x = rxd.Species([cyt, mem, ecs], name='x', charge=1)
# define the various species and parameters on the intracellular and extracellular regions
ki, ko, nai, nao, xi, xo = k[cyt], kecs[ecs], na[cyt], naecs[ecs], x[cyt], x[
ecs]
# the gating states
ngate = rxd.State([cyt, mem], name='ngate', initial=0.24458654944007166)
mgate = rxd.State([cyt, mem], name='mgate', initial=0.028905534475191907)
hgate = rxd.State([cyt, mem], name='hgate', initial=0.7540796658225246)
# parameter to limit rxd reaction to somaA
def init(ics, ecs):
return lambda nd: ecs if isinstance(nd, rxd.node.NodeExtracellular
) else ics
# ions
k = rxd.Species([cyt, mem],
name='k',
d=1,
charge=1,
initial=54.4,
represents='CHEBI:29103')
kecs = rxd.Parameter([ecs],
name='k',
value=2.5,
charge=1,
represents='CHEBI:29103')
na = rxd.Species([cyt, mem],
name='na',
d=1,
charge=1,
initial=10.0,
represents='CHEBI:29101')
naecs = rxd.Parameter([ecs],
name='na_ecs',
value=140,
charge=1,
represents='CHEBI:29101')
def init(ics, ecs):
return lambda nd: ecs if isinstance(nd, rxd.node.NodeExtracellular
) else ics
# ions
k = rxd.Species([cyt, mem],
name="k",
d=1,
charge=1,
initial=54.4,
represents="CHEBI:29103")
kecs = rxd.Parameter([ecs],
name="k",
value=2.5,
charge=1,
represents="CHEBI:29103")
na = rxd.Species([cyt, mem],
name="na",
d=1,
charge=1,
initial=10.0,
represents="CHEBI:29101")
naecs = rxd.Parameter([ecs],
name="na",
value=140,
charge=1,
represents="CHEBI:29101")
k = rxd.Species([cyt, mem, ecs], name="k", d=1, charge=1, initial=init(54.4, 2.5))
na = rxd.Species([cyt, mem, ecs], name="na", d=1, charge=1, initial=init(10.0, 140.0))
x = rxd.Species([cyt, mem, ecs], name="x", charge=1)
ki, ko, nai, nao, xi, xo = k[cyt], k[ecs], na[cyt], na[ecs], x[cyt], x[ecs]
# gates
ngate = rxd.Species([cyt, mem], name="ngate", initial=0.24458654944007166)
mgate = rxd.Species([cyt, mem], name="mgate", initial=0.028905534475191907)
hgate = rxd.Species([cyt, mem], name="hgate", initial=0.7540796658225246)
# mycellA parameter
pA = rxd.Parameter(
[cyt, mem],
name="paramA",
initial=lambda nd: 1 if nd.segment.sec in mycellA.all else 0,
)
# What
# gates
m_gate = rxd.Rate(mgate, (minf - mgate) / mtau)
h_gate = rxd.Rate(hgate, (hinf - hgate) / htau)
n_gate = rxd.Rate(ngate, (ninf - ngate) / ntau)
# Nernst potentials
ena = 1e3 * h.R * (h.celsius + 273.15) * log(nao / nai) / h.FARADAY # 63
ek = 1e3 * h.R * (h.celsius + 273.15) * log(ko / ki) / h.FARADAY # -74
gna = pA * gnabar * mgate ** 3 * hgate
gk = pA * gkbar * ngate ** 4
from neuron import h, crxd as rxd
from matplotlib import pyplot
h.load_file('stdrun.hoc')
cell = h.Section(name='cell')
r = rxd.Region([cell])
def Declare_Parameters(**kwargs):
'''helper function enabling clean declaration of parameters in top namespace'''
for key, value in kwargs.items():
globals()[key] = rxd.Parameter(r, name=key, initial=value)
def Declare_Species(**kwargs):
'''helper function enabling clean declaration of species in top namespace'''
for key, value in kwargs.items():
globals()[key] = rxd.Species(r, name=key, initial=value)
k3 = rxd.Parameter(r, name='k3', initial=1.2)
k4 = rxd.Parameter(r, name='k4', initial=0.6)
P2 = rxd.Species(r, name='P2', initial=0.0614368)
T2 = rxd.Species(r, name='T2', initial=0.0145428)
C = rxd.Species(r, name='C', initial=0.207614)
h.finitialize(-65)
h.continuerun(72)
