本文整理汇总了Python中moose.reinit函数的典型用法代码示例。如果您正苦于以下问题:Python reinit函数的具体用法?Python reinit怎么用?Python reinit使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了reinit函数的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
def main():
"""
This snippet shows the use of several objects.
This snippet sets up a StimulusTable to control a RandSpike which
sends its outputs to two places: to a SimpleSynHandler on an IntFire,
which is used to monitor spike arrival, and to various Stats objects.
Each of these are recorded and plotted.
The StimulusTable has a sine-wave waveform.
"""
make_model()
moose.reinit()
moose.start( runtime )
plots = moose.element( '/plots' )
plot1 = moose.element( '/plot1' )
plot2 = moose.element( '/plot2' )
plotf = moose.element( '/plotf' )
t = [i * dt for i in range( plot1.vector.size )]
pylab.plot( t, plots.vector, label='stimulus' )
pylab.plot( t, plot1.vector, label='spike rate mean' )
pylab.plot( t, plot2.vector, label='Vm mean' )
pylab.plot( t, plotf.vector, label='Vm' )
pylab.legend()
pylab.show()
'''
示例2: main
def main():
global synSpineList
global synDendList
numpy.random.seed( 1234 )
rdes = buildRdesigneur( )
for i in elecFileNames:
print(i)
rdes.cellProtoList = [ ['./cells/' + i, 'elec'] ]
rdes.buildModel( )
assert( moose.exists( '/model' ) )
synSpineList = moose.wildcardFind( "/model/elec/#head#/glu,/model/elec/#head#/NMDA" )
temp = set( moose.wildcardFind( "/model/elec/#/glu,/model/elec/#/NMDA" ) )
synDendList = list( temp - set( synSpineList ) )
moose.reinit()
buildPlots( rdes )
# Run for baseline, tetanus, and post-tetanic settling time
t1 = time.time()
probeStimulus( baselineTime )
tetanicStimulus( tetTime )
probeStimulus( postTetTime )
print(('real time = ', time.time() - t1))
printPsd( i + ".fig5" )
saveAndClearPlots( i + ".fig5" )
moose.delete( '/model' )
rdes.elecid = moose.element( '/' )
示例3: run
def run(nogui):
reader = NML2Reader(verbose=True)
filename = 'test_files/NML2_SingleCompHHCell.nml'
print('Loading: %s'%filename)
reader.read(filename, symmetric=True)
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 = 300e-3
#moose.showmsg( '/clock' )
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
vfile = open('moose_v_hh.dat','w')
for i in range(len(t)):
vfile.write('%s\t%s\n'%(t[i],vm.vector[i]))
vfile.close()
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.figure()
test_channel_gates()
plt.show()
plt.close()
示例4: simulate
def simulate(self,simtime=simtime,dt=dt,plotif=False,**kwargs):
self.dt = dt
self.simtime = simtime
self.T = np.ceil(simtime/dt)
self.trange = np.arange(0,self.simtime+dt,dt)
self._init_network(**kwargs)
if plotif:
self._init_plots()
# moose simulation
# moose auto-schedules
#moose.useClock( 0, '/network/syns', 'process' )
#moose.useClock( 1, '/network', 'process' )
#moose.useClock( 2, '/plotSpikes', 'process' )
#moose.useClock( 3, '/plotVms', 'process' )
#moose.useClock( 3, '/plotWeights', 'process' )
for i in range(10):
moose.setClock( i, dt )
t1 = time.time()
print('reinit MOOSE')
moose.reinit()
print(('reinit time t = ', time.time() - t1))
t1 = time.time()
print('starting')
moose.start(self.simtime)
print(('runtime, t = ', time.time() - t1))
if plotif:
self._plot()
示例5: singleCompt
def singleCompt( name, params ):
mod = moose.copy( '/library/' + name + '/' + name, '/model' )
A = moose.element( mod.path + '/A' )
Z = moose.element( mod.path + '/Z' )
Z.nInit = 1
Ca = moose.element( mod.path + '/Ca' )
CaStim = moose.element( Ca.path + '/CaStim' )
runtime = params['preStimTime'] + params['stimWidth'] + params['postStimTime']
steptime = 100
CaStim.expr += ' + x2 * (t > ' + str( runtime ) + ' ) * ( t < ' + str( runtime + steptime ) + ' )'
print(CaStim.expr)
tab = moose.Table2( '/model/' + name + '/Atab' )
#for i in range( 10, 19 ):
#moose.setClock( i, 0.01 )
ampl = moose.element( mod.path + '/ampl' )
phase = moose.element( mod.path + '/phase' )
moose.connect( tab, 'requestOut', A, 'getN' )
ampl.nInit = params['stimAmplitude'] * 1
phase.nInit = params['preStimTime']
ksolve = moose.Ksolve( mod.path + '/ksolve' )
stoich = moose.Stoich( mod.path + '/stoich' )
stoich.compartment = mod
stoich.ksolve = ksolve
stoich.path = mod.path + '/##'
runtime += 2 * steptime
moose.reinit()
moose.start( runtime )
t = np.arange( 0, runtime + 1e-9, tab.dt )
return name, t, tab.vector
示例6: main
def main():
"""
This example illustrates loading, and running a kinetic model
for a bistable positive feedback system, defined in kkit format.
This is based on Bhalla, Ram and Iyengar, Science 2002.
The core of this model is a positive feedback loop comprising of
the MAPK cascade, PLA2, and PKC. It receives PDGF and Ca2+ as
inputs.
This model is quite a large one and due to some stiffness in its
equations, it runs somewhat slowly.
The simulation illustrated here shows how the model starts out in
a state of low activity. It is induced to 'turn on' when a
a PDGF stimulus is given for 400 seconds.
After it has settled to the new 'on' state, model is made to
'turn off'
by setting the system calcium levels to zero for a while. This
is a somewhat unphysiological manipulation!
"""
solver = "gsl" # Pick any of gsl, gssa, ee..
#solver = "gssa" # Pick any of gsl, gssa, ee..
mfile = '../../genesis/acc35.g'
runtime = 2000.0
if ( len( sys.argv ) == 2 ):
solver = sys.argv[1]
modelId = moose.loadModel( mfile, 'model', solver )
# Increase volume so that the stochastic solver gssa
# gives an interesting output
compt = moose.element( '/model/kinetics' )
compt.volume = 5e-19
moose.reinit()
moose.start( 500 )
moose.element( '/model/kinetics/PDGFR/PDGF' ).concInit = 0.0001
moose.start( 400 )
moose.element( '/model/kinetics/PDGFR/PDGF' ).concInit = 0.0
moose.start( 2000 )
moose.element( '/model/kinetics/Ca' ).concInit = 0.0
moose.start( 500 )
moose.element( '/model/kinetics/Ca' ).concInit = 0.00008
moose.start( 2000 )
# Display all plots.
img = mpimg.imread( 'mapkFB.png' )
fig = plt.figure( figsize=(12, 10 ) )
png = fig.add_subplot( 211 )
imgplot = plt.imshow( img )
ax = fig.add_subplot( 212 )
x = moose.wildcardFind( '/model/#graphs/conc#/#' )
t = numpy.arange( 0, x[0].vector.size, 1 ) * x[0].dt
ax.plot( t, x[0].vector, 'b-', label=x[0].name )
ax.plot( t, x[1].vector, 'c-', label=x[1].name )
ax.plot( t, x[2].vector, 'r-', label=x[2].name )
ax.plot( t, x[3].vector, 'm-', label=x[3].name )
plt.ylabel( 'Conc (mM)' )
plt.xlabel( 'Time (seconds)' )
pylab.legend()
pylab.show()
示例7: deliverStim
def deliverStim(currTime):
global injectionCurrent
global spineVm
global somaVm
if numpy.fabs( currTime - baselineTime ) < frameRunTime/2.0 :
#start
eList = moose.wildcardFind( '/model/elec/#soma#' )
assert( len(eList) > 0 )
eList[0].inject = injectionCurrent
#print "1. injected current = ", injectionCurrent
injectionCurrent += deltaCurrent
#print "del stim first ", moose.element('/clock').currentTime
if numpy.fabs( currTime - baselineTime - currPulseTime) < frameRunTime/2.0 :
#end
eList = moose.wildcardFind( '/model/elec/#soma#' )
assert( len(eList) > 0 )
eList[0].inject = 0.0
#print "2. injected current = ", injectionCurrent
#print "del stim second ", moose.element('/clock').currentTime
if runtime - currTime < frameRunTime * 2.0 :
#print "3. reinit-ing"
somaVm.append( moose.element( '/graphs/VmTab' ).vector )
spineVm.append( moose.element( '/graphs/eSpineVmTab' ).vector )
iList.append(injectionCurrent)
if injectionCurrent < maxCurrent :
moose.reinit()
示例8: resetSimulation
def resetSimulation(self, runTime, updateInterval, simulationInterval):
self.runTime = runTime
self.updateInterval = updateInterval
self.simulationInterval = simulationInterval
self.pause = False
moose.reinit()
self.simulationReset.emit()
示例9: test
def test():
global finish_all_
os.environ['MOOSE_STREAMER_ADDRESS'] = 'http://127.0.0.1:%d'%port_
done = mp.Value('d', 0)
q = mp.Queue()
client = mp.Process(target=socket_client, args=(q, done))
client.start()
time.sleep(0.1)
print( '[INFO] Socket client is running now' )
ts = models.simple_model_a()
moose.reinit()
time.sleep(0.1)
# If TCP socket is created, some delay is often neccessary before start. Don't
# know why. probably some latency in a fresh TCP socket. A TCP guru can
# tell.
moose.start(50)
print( 'MOOSE is done' )
time.sleep(0.5)
done.value = 1
res = q.get()
client.join()
if not res:
raise RuntimeWarning('Nothing was streamed')
for k in res:
a = res[k][1::2]
b = moose.element(k).vector
print(k, len(a), len(b))
assert( (a==b).all())
print( 'Test 1 passed' )
示例10: resetAndStartSimulation
def resetAndStartSimulation(self):
"""TODO this should provide a clean scheduling through all kinds
of simulation or default scheduling should be implemented in MOOSE
itself. We need to define a policy for handling scheduling. It can
be pushed to the plugin-developers who should have knowledge of
the scheduling criteria for their domain."""
settings = config.MooseSetting()
try:
simdt_kinetics = float(settings[config.KEY_KINETICS_SIMDT])
except ValueError:
simdt_kinetics = 0.1
try:
simdt_electrical = float(settings[config.KEY_ELECTRICAL_SIMDT])
except ValueError:
simdt_electrical = 0.25e-4
try:
plotdt_kinetics = float(settings[config.KEY_KINETICS_PLOTDT])
except ValueError:
plotdt_kinetics = 0.1
try:
plotdt_electrical = float(settings[config.KEY_ELECTRICAL_PLOTDT])
except ValueError:
plotdt_electrical = 0.25e-3
try:
simtime = float(settings[config.KEY_SIMTIME])
except ValueError:
simtime = 1.0
moose.reinit()
view = self.plugin.getRunView()
moose.start(simtime)
if view.getCentralWidget().plotAll:
view.getCentralWidget().plotAllData()
self.setCurrentView('run')
示例11: run_single_channel
def run_single_channel(channelname, Gbar, simtime, simdt=testutils.SIMDT, plotdt=testutils.PLOTDT):
testId = uuid.uuid4().int
container = moose.Neutral('test%d' % (testId))
model_container = moose.Neutral('%s/model' % (container.path))
data_container = moose.Neutral('%s/data' % (container.path))
params = testutils.setup_single_compartment(
model_container, data_container,
channelbase.prototypes[channelname],
Gbar)
vm_data = params['Vm']
gk_data = params['Gk']
ik_data = params['Ik']
testutils.setup_clocks(simdt, plotdt)
testutils.assign_clocks(model_container, data_container)
moose.reinit()
print 'Starting simulation', testId, 'for', simtime, 's'
moose.start(simtime)
print 'Finished simulation'
vm_file = 'data/%s_Vm.dat' % (channelname)
gk_file = 'data/%s_Gk.dat' % (channelname)
ik_file = 'data/%s_Ik.dat' % (channelname)
tseries = np.array(range(len(vm_data.vec))) * simdt
print 'Vm:', len(vm_data.vec), 'Gk', len(gk_data.vec), 'Ik', len(ik_data.vec)
data = np.c_[tseries, vm_data.vec]
np.savetxt(vm_file, data)
print 'Saved Vm in', vm_file
print len(gk_data.vec), len(vm_data.vec)
data = np.c_[tseries, gk_data.vec]
np.savetxt(gk_file, data)
print 'Saved Gk in', gk_file
data = np.c_[tseries, ik_data.vec]
np.savetxt(ik_file, data)
print 'Saved Gk in', ik_file
return params
示例12: main
def main():
"""
A toy compartmental neuronal + chemical model that causes bad things
to happen to the hsolver, as of 28 May 2013. Hopefully this will
become irrelevant soon.
"""
fineDt = 1e-5
coarseDt = 5e-5
make_spiny_compt()
make_plots()
for i in range( 8 ):
moose.setClock( i, fineDt )
moose.setClock( 8, coarseDt )
moose.reinit()
moose.start( 0.1 )
display_plots( 'instab.plot' )
# make Hsolver and rerun
hsolve = moose.HSolve( '/n/hsolve' )
for i in range( 8 ):
moose.setClock( i, coarseDt )
hsolve.dt = coarseDt
hsolve.target = '/n/compt'
moose.reinit()
moose.start( 0.1 )
display_plots( 'h_instab.plot' )
pylab.show()
示例13: main
def main():
makeModel()
'''
'''
ksolve = moose.Ksolve( '/model/compartment/ksolve' )
stoich = moose.Stoich( '/model/compartment/stoich' )
stoich.compartment = moose.element( '/model/compartment' )
stoich.ksolve = ksolve
stoich.path = "/model/compartment/##"
#solver.method = "rk5"
#mesh = moose.element( "/model/compartment/mesh" )
#moose.connect( mesh, "remesh", solver, "remesh" )
'''
moose.setClock( 5, 1.0 ) # clock for the solver
moose.useClock( 5, '/model/compartment/ksolve', 'process' )
'''
moose.reinit()
moose.start( 100.0 ) # Run the model for 100 seconds.
func = moose.element( '/model/compartment/d/func' )
if useY:
func.expr = "-y0 + 10*y1"
else:
func.expr = "-x0 + 10*x1"
moose.start( 100.0 ) # Run the model for 100 seconds.
#moose.showfields( '/model/compartment/d' )
#moose.showfields( '/model/compartment/d/func' )
print func.x.value
print moose.element( '/model/compartment/b' ).n
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
quit()
示例14: main
def main():
makeModel()
gsolve = moose.Gsolve("/model/compartment/gsolve")
stoich = moose.Stoich("/model/compartment/stoich")
stoich.compartment = moose.element("/model/compartment")
stoich.ksolve = gsolve
stoich.path = "/model/compartment/##"
# solver.method = "rk5"
# mesh = moose.element( "/model/compartment/mesh" )
# moose.connect( mesh, "remesh", solver, "remesh" )
moose.setClock(5, 1.0) # clock for the solver
moose.useClock(5, "/model/compartment/gsolve", "process")
moose.reinit()
moose.start(100.0) # Run the model for 100 seconds.
a = moose.element("/model/compartment/a")
b = moose.element("/model/compartment/b")
# move most molecules over to bgsolve
b.conc = b.conc + a.conc * 0.9
a.conc = a.conc * 0.1
moose.start(100.0) # Run the model for 100 seconds.
# move most molecules back to a
a.conc = a.conc + b.conc * 0.99
b.conc = b.conc * 0.01
moose.start(100.0) # Run the model for 100 seconds.
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
quit()
示例15: test_elec_alone
def test_elec_alone():
eeDt = 2e-6
hSolveDt = 2e-5
runTime = 0.02
make_spiny_compt()
make_elec_plots()
head2 = moose.element( '/n/head2' )
moose.setClock( 0, 2e-6 )
moose.setClock( 1, 2e-6 )
moose.setClock( 2, 2e-6 )
moose.setClock( 8, 0.1e-3 )
moose.useClock( 0, '/n/##[ISA=Compartment]', 'init' )
moose.useClock( 1, '/n/##[ISA=Compartment]', 'process' )
moose.useClock( 2, '/n/##[ISA=ChanBase],/n/##[ISA=SynBase],/n/##[ISA=CaConc],/n/##[ISA=SpikeGen]','process')
moose.useClock( 8, '/graphs/elec/#', 'process' )
moose.reinit()
moose.start( runTime )
dump_plots( 'instab.plot' )
print "||||", len(moose.wildcardFind('/##[ISA=HHChannel]'))
# make Hsolver and rerun
hsolve = moose.HSolve( '/n/hsolve' )
moose.useClock( 1, '/n/hsolve', 'process' )
hsolve.dt = 20e-6
hsolve.target = '/n/compt'
moose.le( '/n' )
for dt in ( 20e-6, 50e-6, 100e-6 ):
print 'running at dt =', dt
moose.setClock( 0, dt )
moose.setClock( 1, dt )
moose.setClock( 2, dt )
hsolve.dt = dt
moose.reinit()
moose.start( runTime )
dump_plots( 'h_instab' + str( dt ) + '.plot' )