def test_nml2(nogui=True):
global SCRIPT_DIR
filename = os.path.join(SCRIPT_DIR, 'test_files/passiveCell.nml')
mu.info('Loading: %s' % filename)
nml = moose.mooseReadNML2(filename)
if not nml:
mu.warn("Failed to parse NML2 file")
return
assert nml, "Expecting NML2 object"
msoma = nml.getComp(nml.doc.networks[0].populations[0].id, 0, 0)
data = moose.Neutral('/data')
pg = nml.getInput('pulseGen1')
inj = moose.Table('%s/pulse' % (data.path))
moose.connect(inj, 'requestOut', pg, 'getOutputValue')
vm = moose.Table('%s/Vm' % (data.path))
moose.connect(vm, 'requestOut', msoma, 'getVm')
simtime = 150e-3
moose.reinit()
moose.start(simtime)
print("Finished simulation!")
yvec = vm.vector
injvec = inj.vector * 1e12
m1, u1 = np.mean(yvec), np.std(yvec)
m2, u2 = np.mean(injvec), np.std(injvec)
assert np.isclose(m1, -0.0456943), m1
assert np.isclose(u1, 0.0121968), u1
assert np.isclose(m2, 26.64890), m2
assert np.isclose(u2, 37.70607574), u2
def run( nogui = True ):
global SCRIPT_DIR
filename = os.path.join(SCRIPT_DIR, 'test_files/passiveCell.nml' )
mu.info('Loading: %s' % filename )
nml = moose.mooseReadNML2( filename )
if not nml:
mu.warn( "Failed to parse NML2 file" )
return
assert nml, "Expecting NML2 object"
msoma = nml.getComp(nml.doc.networks[0].populations[0].id,0,0)
data = moose.Neutral('/data')
pg = nml.getInput('pulseGen1')
inj = moose.Table('%s/pulse' % (data.path))
moose.connect(inj, 'requestOut', pg, 'getOutputValue')
vm = moose.Table('%s/Vm' % (data.path))
moose.connect(vm, 'requestOut', msoma, 'getVm')
simtime = 150e-3
moose.reinit()
moose.start(simtime)
print("Finished simulation!")
t = np.linspace(0, simtime, len(vm.vector))
yvec = vm.vector
injvec = inj.vector * 1e12
m1, u1 = np.mean( yvec ), np.std( yvec )
m2, u2 = np.mean( injvec ), np.std( injvec )
assert np.isclose( m1, -0.0456943 ), m1
assert np.isclose( u1, 0.0121968 ), u1
assert np.isclose( m2, 26.64890 ), m2
assert np.isclose( u2, 37.70607574 ), u2
quit( 0 )
def run(nogui):
filename = 'passiveCell.nml'
print('Loading: %s'%filename)
reader = moose.mooseReadNML2( filename )
assert reader
reader.read(filename)
msoma = reader.getComp(reader.doc.networks[0].populations[0].id,0,0)
print(msoma)
data = moose.Neutral('/data')
pg = reader.getInput('pulseGen1')
inj = moose.Table('%s/pulse' % (data.path))
moose.connect(inj, 'requestOut', pg, 'getOutputValue')
vm = moose.Table('%s/Vm' % (data.path))
moose.connect(vm, 'requestOut', msoma, 'getVm')
simdt = 1e-6
plotdt = 1e-4
simtime = 150e-3
for i in range(8):
moose.setClock( i, simdt )
moose.setClock( 8, plotdt )
moose.reinit()
moose.start(simtime)
print("Finished simulation!")
t = np.linspace(0, simtime, len(vm.vector))
if not nogui:
import matplotlib.pyplot as plt
plt.subplot(211)
plt.plot(t, vm.vector * 1e3, label='Vm (mV)')
plt.legend()
plt.title('Vm')
plt.subplot(212)
plt.title('Input')
plt.plot(t, inj.vector * 1e9, label='injected (nA)')
#plt.plot(t, gK.vector * 1e6, label='K')
#plt.plot(t, gNa.vector * 1e6, label='Na')
plt.legend()
plt.show()
plt.close()
def run(nogui):
filename = 'passiveCell.nml'
print('Loading: %s' % filename)
reader = moose.mooseReadNML2(filename)
assert reader
reader.read(filename)
msoma = reader.getComp(reader.doc.networks[0].populations[0].id, 0, 0)
print(msoma)
data = moose.Neutral('/data')
pg = reader.getInput('pulseGen1')
inj = moose.Table('%s/pulse' % (data.path))
moose.connect(inj, 'requestOut', pg, 'getOutputValue')
vm = moose.Table('%s/Vm' % (data.path))
moose.connect(vm, 'requestOut', msoma, 'getVm')
simdt = 1e-6
plotdt = 1e-4
simtime = 150e-3
for i in range(8):
moose.setClock(i, simdt)
moose.setClock(8, plotdt)
moose.reinit()
moose.start(simtime)
print("Finished simulation!")
t = np.linspace(0, simtime, len(vm.vector))
if not nogui:
import matplotlib.pyplot as plt
plt.subplot(211)
plt.plot(t, vm.vector * 1e3, label='Vm (mV)')
plt.legend()
plt.title('Vm')
plt.subplot(212)
plt.title('Input')
plt.plot(t, inj.vector * 1e9, label='injected (nA)')
#plt.plot(t, gK.vector * 1e6, label='K')
#plt.plot(t, gNa.vector * 1e6, label='Na')
plt.legend()
plt.show()
plt.close()
# Load in the libraries and functions needed to create the model
import moose
import numpy as np
import pylab as plt
import plot_channel as pc
import util as u
# Use plt.ion to show the graphs that will be created for each channel type and for the simulation
plt.ion()
# Read the NML model into MOOSE
#filename = 'MScellupdated2.nml'
#filename = 'MScellupdated_SecDendRE.nml'
filename = 'MScellupdated_primDend.nml'
reader = moose.mooseReadNML2(filename)
# Define the variables to be used for the somatic current injection
pulse_dur = 400e-3
pulse_amp = 0.26e-9
pulse_delay1 = 100e-3
pulse_delay2 = 1e9
# Define the variables needed to view the underlying curves for the channel kinetics
plot_powers = True
VMIN = -120e-3
VMAX = 50e-3
CAMIN = 0.01e-3
CAMAX = 40e-3
channelList = ('kAf', 'kAs', 'kIR', 'Krp', 'naF')
# Graph the curves
# Load in the libraries and functions needed to create the model
import moose
import numpy as np
import pylab as plt
import plot_channel as pc
import util as u
# Use plt.ion to show the graphs that will be created for each channel type and for the simulation
plt.ion()
# Read the NML model into MOOSE
#filename = 'MScellupdated2.nml'
#filename = 'MScellupdated_SecDendRE.nml'
filename = 'MScellupdated_primDend.nml'
reader = moose.mooseReadNML2(filename)
# Define the variables to be used for the somatic current injection
pulse_dur = 400e-3
pulse_amp = 0.26e-9
pulse_delay1 = 100e-3
pulse_delay2 = 1e9
# Define the variables needed to view the underlying curves for the channel kinetics
plot_powers = True
VMIN = -120e-3
VMAX = 50e-3
CAMIN = 0.01e-3
CAMAX = 40e-3
channelList = ('kAf','kAs','kIR','Krp','naF')
# Graph the curves
# Load in the libraries and functions needed to create the model import moose import numpy as np import pylab as plt # Set plt to show the graphs that will be created for each channel type plt.ion() # Read the NML model into MOOSE filename = 'MScellupdated.nml' reader = moose.mooseReadNML2(filename, verbose=1)
