def setupSolver(self, path = '/hsolve'):
"""Setting up HSolver """
hsolve = moose.HSolve( path )
hsolve.dt = self.simDt
moose.setClock(1, self.simDt)
moose.useClock(1, hsolve.path, 'process')
hsolve.target = self.cablePath
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.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")
moose.setClock(0, dt)
moose.setClock(1, dt)
moose.setClock(2, dt)
moose.setClock(3, dt)
moose.setClock(9, 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()
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.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' )
moose.setClock( 0, dt )
moose.setClock( 1, dt )
moose.setClock( 2, dt )
moose.setClock( 3, dt )
moose.setClock( 9, dt )
t1 = time.time()
print 'reinit MOOSE -- takes a while ~20s.'
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()
def test_crossing_single():
"""This function creates an ematrix of two PulseGen elements and
another ematrix of two Table elements.
The two pulsegen elements have same amplitude but opposite phase.
Table[0] is connected to PulseGen[1] and Table[1] to Pulsegen[0].
In the plot you should see two square pulses of opposite phase.
"""
size = 2
pg = moose.PulseGen('pulsegen', size)
for ix, ii in enumerate(pg.vec):
pulse = moose.element(ii)
pulse.delay[0] = 1.0
pulse.width[0] = 2.0
pulse.level[0] = (-1)**ix
tab = moose.Table('table', size)
moose.connect(tab.vec[0], 'requestOut', pg.vec[1], 'getOutputValue', 'Single')
moose.connect(tab.vec[1], 'requestOut', pg.vec[0], 'getOutputValue', 'Single')
print 'Neighbors:'
for t in tab.vec:
print t.path
for n in moose.element(t).neighbors['requestOut']:
print 'requestOut <-', n.path
moose.setClock(0, 0.1)
moose.useClock(0, '/##', 'process')
moose.start(5)
for ii in tab.vec:
t = moose.Table(ii).vector
print len(t)
pylab.plot(t)
pylab.show()
def setup_hdf5_output(model, neuron, filename=None, compartments=DEFAULT_HDF5_COMPARTMENTS):
# Make sure /hdf5 exists
if not moose.exists(HDF5WRITER_NAME):
print('creating', HDF5WRITER_NAME)
writer = moose.HDF5DataWriter(HDF5WRITER_NAME)
#writer = moose.NSDFWriter(HDF5WRITER_NAME)
writer.mode = 2 # Truncate existing file
if filename is not None:
writer.filename = filename
moose.useClock(8, HDF5WRITER_NAME, 'process')
else:
print('using', HDF5WRITER_NAME)
writer = moose.element(HDF5WRITER_NAME)
for typenum,neur_type in enumerate(neuron.keys()):
for ii,compname in enumerate(compartments): #neur_comps):
comp=moose.element(neur_type+'/'+compname)
moose.connect(writer, 'requestOut', comp, 'getVm')
if model.calYN:
for typenum,neur_type in enumerate(neuron.keys()):
for ii,compname in enumerate(compartments): #neur_comps):
comp=moose.element(neur_type+'/'+compname)
for child in comp.children:
if child.className in {"CaConc", "ZombieCaConc"}:
cal = moose.element(comp.path+'/'+child.name)
moose.connect(writer, 'requestOut', cal, 'getCa')
elif child.className == 'DifShell':
cal = moose.element(comp.path+'/'+child.name)
moose.connect(writer, 'requestOut', cal, 'getC')
return writer
def main():
make_spiny_compt()
make_plots()
moose.setClock( 0, 1e-5 )
moose.setClock( 1, 1e-5 )
moose.setClock( 2, 1e-5 )
moose.setClock( 8, 0.1e-3 )
moose.useClock( 0, '/n/#', 'init' )
moose.useClock( 1, '/n/#', 'process' )
moose.useClock( 2, '/n/#/#', 'process' )
moose.useClock( 8, '/graphs/#', 'process' )
moose.reinit()
moose.start( 0.1 )
dump_plots( 'instab.plot' )
# make Hsolver and rerun
hsolve = moose.HSolve( '/n/hsolve' )
moose.useClock( 1, '/n/hsolve', 'process' )
moose.setClock( 0, 2e-5 )
moose.setClock( 1, 2e-5 )
moose.setClock( 2, 2e-5 )
hsolve.dt = 2e-5
hsolve.target = '/n/compt'
moose.reinit()
moose.start( 0.1 )
dump_plots( 'h_instab.plot' )
def testElecAlone():
makeSpinyCompt()
makeElecPlots()
head2 = moose.element( '/n/head2' )
kchan = moose.element( '/n/compt/K' )
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/#', 'init' )
#moose.useClock( 1, '/n/#', 'process' )
#moose.useClock( 2, '/n/#/#', 'process' )
#print moose.wildcardFind( '/n/##[ISA=SpikeGen]' )
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( 0.1 )
dumpPlots( 'instab.plot' )
# make Hsolver and rerun
hsolve = moose.HSolve( '/n/hsolve' )
moose.useClock( 1, '/n/hsolve', 'process' )
moose.setClock( 0, 2e-5 )
moose.setClock( 1, 2e-5 )
moose.setClock( 2, 2e-5 )
hsolve.dt = 2e-5
hsolve.target = '/n/compt'
moose.reinit()
#print kchan, ', Gbar = ', kchan.Gbar
#kchan.Gbar = 0.1e-3
#print 'Gbar = ', kchan.Gbar
moose.start( 0.11 )
dumpPlots( 'h_instab.plot' )
def assign_clocks(model_container_list, simdt, plotdt):
"""
Assign clocks to elements under the listed paths.
This should be called only after all model components have been
created. Anything created after this will not be scheduled.
"""
global inited
# `inited` is for avoiding double scheduling of the same object
if not inited:
print(('SimDt=%g, PlotDt=%g' % (simdt, plotdt)))
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.setClock(3, simdt)
moose.setClock(4, plotdt)
for path in model_container_list:
print(('Scheduling elements under:', path))
moose.useClock(0, '%s/##[TYPE=Compartment]' % (path), 'init')
moose.useClock(1, '%s/##[TYPE=Compartment]' % (path), 'process')
moose.useClock(2, '%s/##[TYPE=SynChan],%s/##[TYPE=HHChannel]' % (path, path), 'process')
moose.useClock(3, '%s/##[TYPE=SpikeGen],%s/##[TYPE=PulseGen]' % (path, path), 'process')
moose.useClock(4, '/data/##[TYPE=Table]', 'process')
inited = True
moose.reinit()
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()
def main():
"""
Example of Interpol object.
"""
simtime = 1.0
simdt = 0.001
model = moose.Neutral('/model')
data = moose.Neutral('/data')
interpol = moose.Interpol('/model/sin')
vec = np.sin(np.linspace(-3.14, 3.14, 100))
interpol.vector = vec
interpol.xmax = 3.14
interpol.xmin = -3.14
recorded = moose.Table('/data/output')
moose.connect(recorded, 'requestOut', interpol, 'getY')
stimtab = moose.StimulusTable('/model/x')
stimtab.stepSize = 0.0
# stimtab.startTime = 0.0
# stimtab.stopTime = simtime
stimtab.vector = np.linspace(-4, 4, 1000)
print((stimtab.vector))
print((interpol.vector))
moose.connect(stimtab, 'output', interpol, 'input')
moose.setClock(0, simdt)
moose.useClock(0, '/data/##,/model/##', 'process')
moose.reinit()
moose.start(simtime)
plt.plot(np.linspace(0, simtime, len(recorded.vector)), recorded.vector, 'b-+', label='interpolated')
plt.plot(np.linspace(0, simtime, len(vec)), vec, 'r-+', label='original')
plt.show()
def example():
"""In this example we create a square-pulse generator object and
record the output using a table.
The steps are:
1. Create a PulseGen element `pulse`.
2. Set `delay[0]=1.0`, `width[0]=0.2`, `level[0]=0.5`, so it
generates 0.2 s wide square pulses with 0.5 amplitude every 1 s.
3. Create a Table element `tab`.
4. Connect the `outputValue` field of `pulse` to `tab`.
5. We set tick-interval of ticks 0 and 1 to 0.01 and schedule
`pulse` on tick 0 and `tab` on tick 1.
5. Run the simulation for 5 s and save data to the ascii file
`output_tabledemo.csv`.
"""
pg = moose.PulseGen('pulse')
pg.delay[0] = 1.0
pg.width[0] = 0.2
pg.level[0] = 0.5
tab = moose.Table('tab')
moose.connect(tab, 'requestOut', pg, 'getOutputValue')
moose.setClock(0, 0.01)
moose.setClock(1, 0.01)
moose.useClock(0, pg.path, 'process')
moose.useClock(1, tab.path, 'process')
moose.reinit()
moose.start(5.0)
tab.plainPlot('output_tabledemo.csv')
def main():
makeModel()
solver = moose.GslStoich("/model/compartment/solver")
solver.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/solver", "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 b
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.
for x in moose.wildcardFind("/model/graphs/conc#"):
moose.element(x[0]).xplot("scriptKineticSolver.plot", x[0].name)
quit()
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' )
def testNeuroMeshMultiscale():
useHsolve = 0
runtime = 0.5
elecDt = 10e-6
chemDt = 0.005
ePlotDt = 0.5e-3
cPlotDt = 0.005
plotName = 'nm.plot'
makeNeuroMeshModel()
print "after model is completely done"
for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
makeChemPlots()
makeElecPlots()
makeCaPlots()
for i in range( 10 ):
moose.setClock( i, elecDt )
for i in range( 10, 20 ):
moose.setClock( i, chemDt )
moose.setClock( 8, ePlotDt )
moose.setClock( 18, cPlotDt )
if useHsolve:
hsolve = moose.HSolve( '/model/elec/hsolve' )
#moose.useClock( 1, '/model/elec/hsolve', 'process' )
hsolve.dt = elecDt
hsolve.target = '/model/elec/compt'
moose.reinit()
#soma = moose.element( '/model/elec/soma' )
'''
else:
moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
#moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
#moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
'''
moose.useClock( 18, '/graphs/chem/#', 'process' )
moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
moose.element( '/model/elec/soma' ).inject = 2e-10
moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
moose.reinit()
moose.start( runtime )
# moose.element( '/model/elec/soma' ).inject = 0
# moose.start( 0.25 )
makeGraphics( cPlotDt, ePlotDt )
def main():
"""
This demo shows how to start, stop, and continue a simulation.
This is commonly done when we want to run a model till settling, then
change a parameter or deliver a stimulus, and then continue the
simulation.
Here, the model is just the output of a PulseGen object which
generates periodic pulses.
The demo shows how to start the simulation. using the
*moose.reinit* command to reset the model to its initial state,
and *moose.start* command to run the model for the specified duration.
We issue multiple *moose.start* commands and do different things to
the model between them. First, we change the delay of the pulseGen.
Then we show a number of ways to assign the timestep (dt) to the
table object in the simulation.
Note that throughout this simulation the pulsegen is going at a
uniform rate, it is just being sampled by the output table at
different intervals.
"""
dt = 0.1
steps = 100
simtime = dt * steps
# Pulsegen is on tick 0, we can pre-emptively set its dt.
moose.setClock(0, dt)
table = setup_model()
pulse = moose.element("/model/pulse")
# The 'tick' field is on every object, we can use this to set its dt.
moose.setClock(table.tick, dt)
moose.reinit()
clock = moose.element("/clock")
print dt
print "dt = ", dt, ", Total simulation time = ", simtime
print "Running simulation for", simtime, "seconds"
moose.start(simtime)
print "Simulator time:", clock.currentTime
# Here we change the pulse delay and then run again.
pulse.delay[0] = 1.0
moose.start(simtime)
# We change the table tick and use a different dt for it:
table.tick = 2
moose.setClock(table.tick, dt * 2)
moose.start(simtime)
# Here is yet another way to change clocks used by the table
moose.useClock(9, "/model/pulse/tab", "process")
print table.tick
moose.setClock(9, dt / 2.0)
moose.start(simtime)
# Finally, here we change the pulse delay to 1 second and run again.
print "Simulator time at end of simulation", clock.currentTime
pylab.plot(pylab.linspace(0, clock.currentTime, len(table.vector)), table.vector)
pylab.show()
def makeModel():
# create container for model
r0 = 1e-6 # m
r1 = 0.5e-6 # m. Note taper.
num = 200
diffLength = 1e-6 # m
comptLength = num * diffLength # m
diffConst = 20e-12 # m^2/sec
concA = 1 # millimolar
dt4 = 0.02 # for the diffusion
dt5 = 0.2 # for the reaction
mfile = '../../Genesis_files/M1719.g'
model = moose.Neutral( 'model' )
compartment = moose.CylMesh( '/model/kinetics' )
# load in model
modelId = moose.loadModel( mfile, '/model', 'ee' )
a = moose.element( '/model/kinetics/a' )
b = moose.element( '/model/kinetics/b' )
c = moose.element( '/model/kinetics/c' )
ac = a.concInit
bc = b.concInit
cc = c.concInit
compartment.r0 = r0
compartment.r1 = r1
compartment.x0 = 0
compartment.x1 = comptLength
compartment.diffLength = diffLength
assert( compartment.numDiffCompts == num )
# Assign parameters
for x in moose.wildcardFind( '/model/kinetics/##[ISA=PoolBase]' ):
#print 'pools: ', x, x.name
x.diffConst = diffConst
# Make solvers
ksolve = moose.Ksolve( '/model/kinetics/ksolve' )
dsolve = moose.Dsolve( '/model/dsolve' )
# Set up clocks. The dsolver to know before assigning stoich
moose.setClock( 4, dt4 )
moose.setClock( 5, dt5 )
moose.useClock( 4, '/model/dsolve', 'process' )
# Ksolve must be scheduled after dsolve.
moose.useClock( 5, '/model/kinetics/ksolve', 'process' )
stoich = moose.Stoich( '/model/kinetics/stoich' )
stoich.compartment = compartment
stoich.ksolve = ksolve
stoich.dsolve = dsolve
stoich.path = "/model/kinetics/##"
print 'dsolve.numPools, num = ', dsolve.numPools, num
b.vec[num-1].concInit *= 1.01 # Break symmetry.
def main(): # Schedule the whole lot moose.setClock( 4, 0.1 ) # for the computational objects moose.setClock( 5, 0.2 ) # clock for the solver moose.setClock( 8, 1.0 ) # for the plots # The wildcard uses # for single level, and ## for recursive. compartment = makeModel() ksolve = moose.Ksolve( '/model/compartment/ksolve' ) stoich = moose.Stoich( '/model/compartment/stoich' ) stoich.compartment = compartment stoich.ksolve = ksolve ksolve.stoich = stoich stoich.path = "/model/compartment/##" state = moose.SteadyState( '/model/compartment/state' ) #solver.method = "rk5" #mesh = moose.element( "/model/compartment/mesh" ) #moose.connect( mesh, "remesh", solver, "remesh" ) #moose.useClock( 4, '/model/compartment/##', 'process' ) moose.useClock( 5, '/model/compartment/ksolve', 'process' ) moose.useClock( 8, '/model/graphs/#', 'process' ) moose.reinit() state.stoich = stoich state.showMatrices() state.convergenceCriterion = 1e-7 for i in range( 0, 100 ): getState( ksolve, state ) # state.randomInit() # moose.start( 50.0 ) # Run the model for 100 seconds. # state.resettle() # print ksolve.nVec[0], sum( ksolve.nVec[0] ) # print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus 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 b 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()
def main():
utils.parser
nml.loadNeuroML_L123('./two_cells_nml_1.8/two_cells.nml')
#mumbl.loadMumbl("./two_cells_nml_1.8/mumbl.xml")
table1 = utils.recordTarget('/tableA', '/cells/purkinjeGroup_0/Dend_37_41', 'vm')
table2 = utils.recordTarget('/tableB', '/cells/granuleGroup_0/Soma_0', 'vm')
moose.setClock(0, 5e-6)
moose.useClock(0, '/##', 'process')
moose.useClock(0, '/##', 'init')
moose.reinit()
utils.run(0.1)
graphviz.writeGraphviz(__file__+".dot", ignore='/library')
def main():
# Schedule the whole lot
moose.setClock( 4, 0.1 ) # for the computational objects
moose.setClock( 5, 0.1 ) # clock for the solver
moose.setClock( 8, 1.0 ) # for the plots
# The wildcard uses # for single level, and ## for recursive.
#compartment = makeModel()
moose.loadModel( '../Genesis_files/M1719.cspace', '/model', 'ee' )
compartment = moose.element( 'model/kinetics' )
compartment.name = 'compartment'
ksolve = moose.Ksolve( '/model/compartment/ksolve' )
stoich = moose.Stoich( '/model/compartment/stoich' )
stoich.compartment = compartment
stoich.ksolve = ksolve
#ksolve.stoich = stoich
stoich.path = "/model/compartment/##"
state = moose.SteadyState( '/model/compartment/state' )
moose.useClock( 5, '/model/compartment/ksolve', 'process' )
moose.useClock( 8, '/model/graphs/#', 'process' )
moose.reinit()
state.stoich = stoich
#state.showMatrices()
state.convergenceCriterion = 1e-7
moose.le( '/model/graphs' )
a = moose.element( '/model/compartment/a' )
b = moose.element( '/model/compartment/b' )
c = moose.element( '/model/compartment/c' )
for i in range( 0, 100 ):
getState( ksolve, state )
moose.start( 100.0 ) # Run the model for 100 seconds.
b = moose.element( '/model/compartment/b' )
c = moose.element( '/model/compartment/c' )
# move most molecules over to b
b.conc = b.conc + c.conc * 0.95
c.conc = c.conc * 0.05
moose.start( 100.0 ) # Run the model for 100 seconds.
# move most molecules back to a
c.conc = c.conc + b.conc * 0.95
b.conc = b.conc * 0.05
moose.start( 100.0 ) # Run the model for 100 seconds.
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
quit()
def testNeuroMeshMultiscale():
runtime = 0.5
#elecDt = 0.2e-6
elecDt = 10e-6
chemDt = 0.0025
ePlotDt = 0.5e-3
cPlotDt = 0.0025
plotName = 'nm.plot'
makeNeuroMeshModel()
print "after model is completely done"
for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
makeChemPlots()
makeElecPlots()
makeCaPlots()
for i in range (10):
moose.setClock( i, elecDt )
for i in range ( 10, 20 ):
moose.setClock( i, chemDt )
moose.setClock( 8, ePlotDt )
moose.setClock( 18, cPlotDt )
moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
moose.useClock( 18, '/graphs/chem/#', 'process' )
hsolve = moose.HSolve( '/model/elec/hsolve' )
hsolve.dt = elecDt
hsolve.target = '/model/elec/compt'
plotlist = makeGraphics()
moose.reinit()
moose.element( '/model/elec/soma' ).inject = 2e-10
moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
moose.reinit()
numDivs = 200
partialRuntime = runtime / numDivs
max_voxel = find_max_voxel()
voxel_val_dict = {'spine':numpy.zeros((max_voxel, numDivs)),
'dend':numpy.zeros((max_voxel, numDivs)),
'elec':numpy.zeros((max_voxel, numDivs)),
'spineCaM':numpy.zeros((max_voxel, numDivs)),
'psdCaM':numpy.zeros((max_voxel, numDivs))}
for i in range( numDivs ):
moose.start( partialRuntime )
voxel_val_dict = updateGraphics( plotlist, voxel_val_dict, i ) #Edited by Chaitanya
# moose.element( '/model/elec/soma' ).inject = 0
# moose.start( 0.25 )
save_NSDF(cPlotDt, ePlotDt, voxel_val_dict, [max_voxel, numDivs, partialRuntime]) #Edited by Chaitanya
finalizeGraphics( plotlist, cPlotDt, ePlotDt )
def setup_model():
model_container = moose.Neutral('/model')
pulse = moose.PulseGen('/model/pulse')
pulse.level[0] = 1.0
pulse.delay[0] = 0.5
pulse.width[0] = 0.5
table = moose.Table('%s/tab' % (pulse.path))
moose.connect(table, 'requestOut', pulse, 'getOutputValue')
moose.setClock(0, 0.1)
moose.setClock(1, 0.1)
moose.setClock(2, 0.1)
moose.useClock(0, '%s,%s' % (pulse.path, table.path), 'process')
return table
def run_simulation(container, simdt, simtime):
"""Schedule and run a simulation"""
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.setClock(3, simdt)
moose.useClock(0, container.path + '/##[ISA=HSolve]', 'process')
moose.useClock(1, container.path + '/##[ISA=Compartment]', 'init')
moose.useClock(2, container.path + '/##[ISA=Compartment]', 'process')
moose.useClock(3, container.path + '/##[ISA=PulseGen]', 'process')
moose.useClock(3, container.path + '/##[ISA=Table]', 'process')
moose.reinit()
moose.start(simtime)
def setup_model():
model_container = moose.Neutral("/model")
pulse = moose.PulseGen("/model/pulse")
pulse.level[0] = 1.0
pulse.delay[0] = 0.5
pulse.width[0] = 0.5
table = moose.Table("%s/tab" % (pulse.path))
moose.connect(table, "requestData", pulse, "get_output")
moose.setClock(0, 0.1)
moose.setClock(1, 0.1)
moose.setClock(2, 0.1)
moose.useClock(0, "%s,%s" % (pulse.path, table.path), "process")
return table
def assignClocks(self,modelpath,modeltype):
if modeltype == MooseHandler.type_kkit:
#self.mooseHandler.updateClocks(MooseHandler.DEFAULT_SIMDT_KKIT, MooseHandler.DEFAULT_PLOTDT_KKIT)
#script auto asigns clocks!
pass
elif modeltype == MooseHandler.type_neuroml:
#self.mooseHandler.updateClocks(MooseHandler.DEFAULT_SIMDT, MooseHandler.DEFAULT_PLOTDT)
#print MooseHandler.DEFAULT_SIMDT, MooseHandler.DEFAULT_PLOTDT
if moose.exists('/cells'):
#use Aditya's method to assign clocks - also reinits!
## Exponential Euler
#mooseUtils.resetSim(['/cells','/elec'], MooseHandler.DEFAULT_SIMDT, MooseHandler.DEFAULT_PLOTDT, simmethod='ee')
## HSolve
mooseUtils.resetSim(['/cells','/elec'], MooseHandler.DEFAULT_SIMDT, MooseHandler.DEFAULT_PLOTDT)
else:
print "This NeuroML model does not have any <population> of cells."
print "You need to load a NetworkML or NeuroML level 3 model."
elif modeltype == MooseHandler.type_python:
#specific for the hopfield tutorial!
#self.mooseHandler.updateClocks(MooseHandler.DEFAULT_SIMDT, MooseHandler.DEFAULT_PLOTDT)
clock = 1e-4
self.simControlSimdtLineEdit.setText(str(clock))
self.simControlPlotdtLineEdit.setText(str(clock))
self.mooseHandler.updateClocks(clock, clock) #simdt,plotdt
moose.useClock(1, '/hopfield/##[TYPE=IntFire]', 'process')
moose.useClock(2, '/hopfield/##[TYPE=PulseGen]', 'process')
moose.useClock(2, '/hopfield/##[TYPE=SpikeGen]', 'process')
moose.useClock(8, '/hopfield/##[TYPE=Table]', 'process')
else:
print 'Clocks have not been assigned! - GUI does not support this format yet'
def setupCurrentStepModel(testId, celltype, pulsearray, dt):
"""Setup a single cell simulation.
simid - integer identifying the model
celltype - str cell type
pulsearray - an nx3 array with row[i] = (delay[i], width[i], level[i]) of current injection.
"""
modelContainer = moose.Neutral("/test%d" % (testId))
dataContainer = moose.Neutral("/data%d" % (testId))
cell = TCR("%s/TCR" % (modelContainer.path)) # moose.copy(cells.TCR.prototype, modelContainer.path)#
pulsegen = moose.PulseGen("%s/pulse" % (modelContainer.path))
pulsegen.count = len(pulsearray)
for ii in range(len(pulsearray)):
pulsegen.delay[ii] = pulsearray[ii][0]
pulsegen.width[ii] = pulsearray[ii][1]
pulsegen.level[ii] = pulsearray[ii][2]
moose.connect(pulsegen, "output", cell.soma, "injectMsg")
somaVm = moose.Table("%s/vm" % (dataContainer.path))
moose.connect(somaVm, "requestOut", cell.soma, "getVm")
pulseTable = moose.Table("%s/pulse" % (dataContainer.path))
moose.connect(pulseTable, "requestOut", pulsegen, "getOutputValue")
setupClocks(dt)
moose.useClock(0, "%s/##[ISA=Compartment]" % (cell.path), "init")
moose.useClock(1, "%s/##[ISA=Compartment]" % (cell.path), "process")
moose.useClock(7, pulsegen.path, "process")
moose.useClock(8, "%s/##" % (dataContainer.path), "process")
return {"cell": cell, "stimulus": pulsegen, "vmTable": somaVm, "stimTable": pulseTable}
def main():
utils.parser
p = os.path.join(modeldir, "two_cells_nml_1.8/two_cells.nml")
nml.loadNeuroML_L123(p)
# mumbl.loadMumbl("./two_cells_nml_1.8/mumbl.xml")
table1 = utils.recordTarget("/tableA", "/cells/purkinjeGroup_0/Dend_37_41", "vm")
table2 = utils.recordTarget("/tableB", "/cells/granuleGroup_0/Soma_0", "vm")
moose.setClock(0, 5e-6)
moose.useClock(0, "/##", "process")
moose.useClock(0, "/##", "init")
moose.reinit()
utils.run(0.1, verify=True)
graphviz.writeGraphviz("test_mumble.dot", ignore="/library")
utils.plotRecords({"Dend 37": table1, "Soma 0": table2}, outfile="%s.png" % sys.argv[0], subplot=True)
def testChemAlone():
nid = makeChemInCubeMesh()
moose.le( '/n' )
makeChemPlots()
moose.setClock( 5, 1e-2 )
moose.setClock( 6, 1e-2 )
moose.setClock( 7, 1.0 )
moose.setClock( 8, 1.0 )
moose.setClock( 9, 1.0 )
moose.useClock( 5, '/n/##', 'init' )
moose.useClock( 6, '/n/##', 'process' )
#moose.useClock( 7, '/graphs/#', 'process' )
moose.useClock( 8, '/graphs/#', 'process' )
moose.reinit()
moose.start( 100 )
dumpPlots( 'chem.plot' )
# Make ksolver and rerun.
ksolve = moose.GslStoich( '/n/solver' )
ksolve.path = '/n/##'
ksolve.method = 'rk5'
moose.useClock( 5, '/n/solver', 'process' )
moose.setClock( 5, 1 )
moose.setClock( 6, 1 )
moose.reinit()
moose.start( 100 )
dumpPlots( 'kchem.plot' )
def testModel( useSolver ): elecDt = 20e-6 chemDt = 1e-4 plotDt = 2e-4 plotName = 'gn.plot' if ( useSolver ): elecDt = 50e-6 chemDt = 2e-3 plotName = 'mcs.plot' makeModel() moose.setClock( 0, elecDt ) moose.setClock( 1, elecDt ) moose.setClock( 2, elecDt ) moose.setClock( 5, chemDt ) moose.setClock( 6, chemDt ) moose.setClock( 7, plotDt ) moose.setClock( 8, plotDt ) moose.useClock( 0, '/model/##[ISA=Compartment]', 'init' ) moose.useClock( 1, '/model/##[ISA=Compartment],/model/##[ISA=SpikeGen]', 'process' ) moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=ChanBase],/model/##[ISA=CaConc]','process') moose.useClock( 8, '/graphs/#', 'process' ) moose.reinit() moose.start( 0.1 ) dumpPlots( plotName )
def example():
pg = moose.PulseGen('pulse')
pg.delay[0] = 1.0
pg.width[0] = 0.2
pg.level[0] = 0.5
tab = moose.Table('tab')
moose.connect(tab, 'requestOut', pg, 'getOutputValue')
moose.setClock(0, 0.01)
moose.setClock(1, 0.01)
moose.useClock(0, pg.path, 'process')
moose.useClock(1, tab.path, 'process')
moose.reinit()
moose.start(5.0)
tab.plainPlot('output_tabledemo.csv')
def setupCurrentStepModel(testId, celltype, pulsearray, dt):
"""Setup a single cell simulation.
simid - integer identifying the model
celltype - str cell type
pulsearray - an nx3 array with row[i] = (delay[i], width[i], level[i]) of current injection.
"""
modelContainer = moose.Neutral('/test%d' % (testId))
dataContainer = moose.Neutral('/data%d' % (testId))
cell = TCR('%s/TCR' % (modelContainer.path)) # moose.copy(cells.TCR.prototype, modelContainer.path)#
pulsegen = moose.PulseGen('%s/pulse' % (modelContainer.path))
pulsegen.count = len(pulsearray)
for ii in range(len(pulsearray)):
pulsegen.delay[ii] = pulsearray[ii][0]
pulsegen.width[ii] = pulsearray[ii][1]
pulsegen.level[ii] = pulsearray[ii][2]
moose.connect(pulsegen, 'output', cell.soma, 'injectMsg')
somaVm = moose.Table('%s/vm' % (dataContainer.path))
moose.connect(somaVm, 'requestOut', cell.soma, 'getVm')
pulseTable = moose.Table('%s/pulse' % (dataContainer.path))
moose.connect(pulseTable, 'requestOut', pulsegen, 'getOutputValue')
setupClocks(dt)
moose.useClock(0, '%s/##[ISA=Compartment]' % (cell.path), 'init')
moose.useClock(1, '%s/##[ISA=Compartment]' % (cell.path), 'process')
moose.useClock(7, pulsegen.path, 'process')
moose.useClock(8, '%s/##' % (dataContainer.path), 'process')
return {'cell': cell,
'stimulus': pulsegen,
'vmTable': somaVm,
'stimTable': pulseTable
}
def main():
utils.parser
nml.loadNeuroML_L123('./two_cells_nml_1.8/two_cells.nml')
#mumbl.loadMumbl("./two_cells_nml_1.8/mumbl.xml")
table1 = utils.recordTarget('/tableA', '/cells/purkinjeGroup_0/Dend_37_41',
'vm')
table2 = utils.recordTarget('/tableB', '/cells/granuleGroup_0/Soma_0',
'vm')
moose.setClock(0, 5e-6)
moose.useClock(0, '/##', 'process')
moose.useClock(0, '/##', 'init')
moose.reinit()
utils.run(0.1, verify=True)
graphviz.writeGraphviz(__file__ + ".dot", ignore='/library')
utils.plotTables([table1, table2])
def test_one_to_one(size=2):
pg = moose.PulseGen('pulsegen', size)
for ix, ii in enumerate(pg.vec):
pulse = moose.element(ii)
pulse.delay[0] = 1.0
pulse.width[0] = 2.0
pulse.level[0] = (-1)**ix
tab = moose.Table('pulseamp', size)
moose.connect(tab, 'requestOut', pg, 'getOutputValue', 'OneToOne')
moose.setClock(0, 0.1)
moose.useClock(0, '/##', 'process')
moose.start(5)
for ii in tab.vec:
t = moose.Table(ii).vector
pylab.plot(t)
pylab.show()
def main():
# Schedule the whole lot
moose.setClock(4, 0.1) # for the computational objects
moose.setClock(5, 0.2) # clock for the solver
moose.setClock(8, 1.0) # for the plots
# The wildcard uses # for single level, and ## for recursive.
#compartment = makeModel()
moose.loadModel('../../genesis/M1719.g', '/model', 'ee')
compartment = moose.element('model/kinetics')
compartment.name = 'compartment'
ksolve = moose.Ksolve('/model/compartment/ksolve')
stoich = moose.Stoich('/model/compartment/stoich')
stoich.compartment = compartment
stoich.ksolve = ksolve
#ksolve.stoich = stoich
stoich.path = "/model/compartment/##"
state = moose.SteadyState('/model/compartment/state')
moose.useClock(5, '/model/compartment/ksolve', 'process')
moose.useClock(8, '/model/graphs/#', 'process')
moose.reinit()
state.stoich = stoich
#state.showMatrices()
state.convergenceCriterion = 1e-7
for i in range(0, 50):
getState(ksolve, state)
moose.start(100.0) # Run the model for 100 seconds.
b = moose.element('/model/compartment/b')
c = moose.element('/model/compartment/c')
# move most molecules over to b
b.conc = b.conc + c.conc * 0.95
c.conc = c.conc * 0.05
moose.start(100.0) # Run the model for 100 seconds.
# move most molecules back to a
c.conc = c.conc + b.conc * 0.95
b.conc = b.conc * 0.05
moose.start(100.0) # Run the model for 100 seconds.
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
quit()
def main():
runtime = 400
dt4 = 0.02 # for the diffusion
dt5 = 0.2 # for the reaction
# Set up clocks. The dsolver to know before assigning stoich
moose.setClock( 4, dt4 )
moose.setClock( 5, dt5 )
model = moose.Neutral( '/model' )
cellId = loadElec()
makeChemModel( cellId )
moose.useClock( 4, '/model/compartment/dsolve', 'process' )
# Ksolve must be scheduled after dsolve.
moose.useClock( 5, '/model/compartment/ksolve', 'process' )
print("finished loading")
moose.reinit()
for i in range( 10 ):
moose.start( runtime / 10 ) # Run the model for 10 seconds.
# print 'done', i
displayPlots( i )
print("finished running")
"""
a = moose.element( '/model/compartment/a' )
b = moose.element( '/model/compartment/b' )
s = moose.element( '/model/compartment/s' )
atot = sum( a.vec.conc )
btot = sum( b.vec.conc )
stot = sum( s.vec.conc )
print "a = ", a.vec.conc
print "b = ", b.vec.conc
print "s = ", s.vec.conc
print 'tot = ', atot, btot, atot + btot + stot
displayPlots()
"""
"""
dsolve = moose.element( '/model/compartment/dsolve' )
x = dsolve.nVec[0]
print dsolve.numPools, x, sum(x)
print dsolve.nVec[1], sum( dsolve.nVec[1] )
print dsolve.nVec[2], sum( dsolve.nVec[2] )
print dsolve.nVec[3], sum( dsolve.nVec[3] )
"""
quit()
def testNeuroMeshMultiscale():
runtime = 0.5
#elecDt = 0.2e-6
elecDt = 10e-6
chemDt = 0.0025
ePlotDt = 0.5e-3
cPlotDt = 0.0025
plotName = 'nm.plot'
makeNeuroMeshModel()
print "after model is completely done"
for i in moose.wildcardFind('/model/chem/#/#/#/transloc#'):
print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
makeChemPlots()
makeElecPlots()
makeCaPlots()
for i in range(10):
moose.setClock(i, elecDt)
for i in range(10, 20):
moose.setClock(i, chemDt)
moose.setClock(8, ePlotDt)
moose.setClock(18, cPlotDt)
moose.useClock(8, '/graphs/elec/#,/graphs/ca/#', 'process')
moose.useClock(18, '/graphs/chem/#', 'process')
hsolve = moose.HSolve('/model/elec/hsolve')
hsolve.dt = elecDt
hsolve.target = '/model/elec/compt'
plotlist = makeGraphics()
moose.reinit()
moose.element('/model/elec/soma').inject = 2e-10
moose.element('/model/chem/psd/Ca').concInit = 0.001
moose.element('/model/chem/spine/Ca').concInit = 0.002
moose.element('/model/chem/dend/DEND/Ca').concInit = 0.003
moose.reinit()
numDivs = 200
partialRuntime = runtime / numDivs
for i in range(numDivs):
moose.start(partialRuntime)
updateGraphics(plotlist)
# moose.element( '/model/elec/soma' ).inject = 0
# moose.start( 0.25 )
finalizeGraphics(plotlist, cPlotDt, ePlotDt)
def multilevel_pulsegen():
"""Demonstrates a pulsegen with multiple levels, delays and
widths."""
pg = moose.PulseGen('pulsegen')
pg.count = 5
for ii in range(pg.count):
pg.level[ii] = ii + 1
pg.width[ii] = 0.1
pg.delay[ii] = 0.5 * (ii + 1)
tab = moose.Table('tab')
moose.connect(tab, 'requestOut', pg, 'getOutputValue')
moose.setClock(0, 0.01)
moose.useClock(0, '%s,%s' % (pg.path, tab.path), 'process')
moose.reinit()
moose.start(20.0)
plt.plot(tab.vector)
plt.show()
def run(self, runtime, simdt=1e-6):
self.squid_axon.updateEk()
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.setClock(3, simdt)
if not self.clocks_assigned:
moose.useClock(0, '%s/#[TYPE=Compartment]' % (self.path), 'init')
moose.useClock(0, '%s/#[TYPE=PulseGen]' % (self.path), 'process')
moose.useClock(1, '%s/#[TYPE=Compartment]' % (self.path),
'process')
moose.useClock(2, '%s/#[TYPE=HHChannel]' % (self.squid_axon.path),
'process')
moose.useClock(3, '%s/#[TYPE=Table]' % (self.path), 'process')
self.clocks_assigned = True
moose.reinit()
moose.start(runtime)
def stimulus_table_demo():
model = moose.Neutral('/model')
data = moose.Neutral('/data')
# This is the stimulus generator
stimtable = moose.StimulusTable('/model/stim')
recorded = moose.Table('/data/stim')
moose.connect(recorded, 'requestOut', stimtable, 'getOutputValue')
simtime = 100
simdt = 1e-3
# Inter-stimulus-intervals with rate=20/s
rate = 20
np.random.seed(1) # ensure repeatability
isi = np.random.exponential(rate, int(simtime / rate))
# The stimulus times are the cumulative sum of the inter-stimulus intervals.
stimtimes = np.cumsum(isi)
# Select only stimulus times that are within simulation time -
# this may leave out some possible stimuli at the end, but the
# exoected number of Poisson events within simtime is
# simtime/rate.
stimtimes = stimtimes[stimtimes < simtime]
ts = np.arange(0, simtime, simdt)
# Find the indices of table entries corresponding to time of stimulus
stimidx = np.searchsorted(ts, stimtimes)
stim = np.zeros(len(ts))
# Since linear interpolation is forced, we need at least three
# consecutive entries to have same value to get correct
# magnitude. And still we shall be off by at least one time step.
indices = np.concatenate((stimidx - 1, stimidx, stimidx + 1))
stim[indices] = 1.0
stimtable.vector = stim
stimtable.stepSize = 0 # This forces use of current time as x value for interpolation
stimtable.stopTime = simtime
moose.setClock(0, simdt)
moose.useClock(0, '/model/##,/data/##', 'process')
moose.reinit()
moose.start(simtime)
plt.plot(np.linspace(0, simtime, len(recorded.vector)),
recorded.vector,
'r-+',
label='generated stimulus')
plt.plot(ts, stim, 'b-x', label='originally assigned values')
plt.ylim((-1, 2))
plt.legend()
plt.title('Exmaple of StimulusTable')
plt.show()
def chirp(gen_name="chirp", amp=1, f0=1, f1=50, T=0.8, start=0.1, end=0.5, simdt=10E-5, phase=0, amp_offset=0):
''' Chirp injection stimultus
'''
chirper = moose.element('/chirpgen') if moose.exists('/chirpgen') else moose.Neutral('/chirpgen')
func_1 = moose.Func(chirper.path + '/' + gen_name)
func_1.mode = 3
func_1.expr = '{A}*cos(2*pi*(({f1}-{f0})/{T})*x^2 + 2*pi*{f1}*x + {p})+{o}'.format(f0=f0, f1=f1, T=T, A=amp,
p=phase, o=amp_offset)
input = moose.StimulusTable(chirper.path + '/xtab')
xarr = np.arange(start, end, simdt)
input.vector = xarr
input.startTime = 0.0
input.stepPosition = xarr[0]
input.stopTime = xarr[-1] - xarr[0]
moose.connect(input, 'output', func_1, 'xIn')
moose.useClock(0, '%s/##[TYPE=StimulusTable]' % (chirper.path), 'process')
moose.useClock(0, '%s/##[TYPE=Func]' % (chirper.path), 'process')
return func_1
def main():
"""
This example illustrates how to set up a kinetic solver and kinetic model
using the scripting interface. Normally this would be done using the
Shell::doLoadModel command, and normally would be coordinated by the
SimManager as the base of the entire model.
This example creates a bistable model having two enzymes and a reaction.
One of the enzymes is autocatalytic.
The model is set up to run using Exponential Euler integration.
"""
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()
def main():
solver = "gsl"
makeModel()
if (len(sys.argv) == 2):
solver = sys.argv[1]
stoich = moose.Stoich('/model/compartment/stoich')
stoich.compartment = moose.element('/model/compartment')
if (solver == 'gssa'):
gsolve = moose.Gsolve('/model/compartment/ksolve')
stoich.ksolve = gsolve
else:
ksolve = moose.Ksolve('/model/compartment/ksolve')
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.
a = moose.element('/model/compartment/a')
b = moose.element('/model/compartment/b')
# move most molecules over to b
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()
try:
raw_input('Press any key to quit')
except NameError as e:
input('Press any key to quit')
def main():
solver = "gsl"
makeModel()
if (len(sys.argv) == 2):
solver = sys.argv[1]
stoich = moose.Stoich('/model/compartment/stoich')
stoich.compartment = moose.element('/model/compartment')
if (solver == 'gssa'):
gsolve = moose.Gsolve('/model/compartment/ksolve')
stoich.ksolve = gsolve
else:
ksolve = moose.Ksolve('/model/compartment/ksolve')
stoich.ksolve = ksolve
stoich.path = "/model/compartment/##"
moose.setClock(5, 1.0) # clock for the solver
moose.useClock(5, '/model/compartment/ksolve', 'process')
runSim()
makeDisplay()
print("Hit 'enter' to exit")
sys.stdin.read(1)
quit()
def simulate(self, simTime, simDt, plotDt=None):
'''Simulate the cable
'''
self.simDt = simDt
self.setupDUT()
# Setup clocks
moose.setClock(0, self.simDt)
# Use clocks
moose.useClock(0, '/##', 'process')
moose.useClock(0, '/##', 'init')
utils.dump("STEP", [
"Simulating cable for {} sec".format(simTime),
" simDt: %s" % self.simDt
])
utils.verify()
moose.reinit()
self.setupSolver()
moose.start(simTime)
def main():
"""
Example of using multithreading to run a MOOSE simulation in
parallel with querying MOOSE objects involved. See the documentatin
of the classes to get an idea of this demo's function.
"""
pg = moose.PulseGen('pg')
pg.firstDelay = 10.0
pg.firstLevel = 10.0
pg.firstWidth = 5.0
tab = moose.Table('tab')
moose.connect(tab, 'requestOut', pg, 'getOutputValue')
moose.setClock(0, 1.0)
moose.useClock(0, 'pg,tab', 'process')
t1 = WorkerThread(10000)
t2 = StatusThread(tab)
t2.start()
t1.start()
status_queue.get(True)
tab.xplot('threading_demo.dat', 'pulsegen_output')
print(('Ending threading_demo: final length of table', len(tab.vector)))
def main():
utils.parser
p = os.path.join(modeldir, 'two_cells_nml_1.8/two_cells.nml')
nml.loadNeuroML_L123(p)
#mumbl.loadMumbl("./two_cells_nml_1.8/mumbl.xml")
table1 = utils.recordTarget('/tableA', '/cells/purkinjeGroup_0/Dend_37_41',
'vm')
table2 = utils.recordTarget('/tableB', '/cells/granuleGroup_0/Soma_0',
'vm')
moose.setClock(0, 5e-6)
moose.useClock(0, '/##', 'process')
moose.useClock(0, '/##', 'init')
moose.reinit()
utils.run(0.1, verify=True)
graphviz.writeGraphviz('test_mumble.dot', ignore='/library')
utils.plotRecords({
'Dend 37': table1,
'Soma 0': table2
},
outfile='%s.png' % sys.argv[0],
subplot=True)
def testNeuroMeshMultiscale():
useHsolve = 0
runtime = 0.5
elecDt = 10e-6
chemDt = 0.005
ePlotDt = 0.5e-3
cPlotDt = 0.005
plotName = 'nm.plot'
makeNeuroMeshModel()
print("after model is completely done")
for i in moose.wildcardFind('/model/chem/#/#/#/transloc#'):
print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
makeChemPlots()
makeElecPlots()
makeCaPlots()
for i in range(10):
moose.setClock(i, elecDt)
for i in range(10, 20):
moose.setClock(i, chemDt)
moose.setClock(8, ePlotDt)
moose.setClock(18, cPlotDt)
if useHsolve:
hsolve = moose.HSolve('/model/elec/hsolve')
#moose.useClock( 1, '/model/elec/hsolve', 'process' )
hsolve.dt = elecDt
hsolve.target = '/model/elec/compt'
moose.reinit()
#soma = moose.element( '/model/elec/soma' )
moose.useClock(18, '/graphs/chem/#', 'process')
moose.useClock(8, '/graphs/elec/#,/graphs/ca/#', 'process')
moose.element('/model/elec/soma').inject = 2e-10
moose.element('/model/chem/psd/Ca').concInit = 0.001
moose.element('/model/chem/spine/Ca').concInit = 0.002
moose.element('/model/chem/dend/DEND/Ca').concInit = 0.003
moose.reinit()
moose.start(runtime)
makeGraphics(cPlotDt, ePlotDt)
def setupSteadyState(simdt, plotDt):
ksolve = moose.Ksolve('/model/kinetics/ksolve')
stoich = moose.Stoich('/model/kinetics/stoich')
stoich.compartment = moose.element('/model/kinetics')
stoich.ksolve = ksolve
#ksolve.stoich = stoich
stoich.path = "/model/kinetics/##"
state = moose.SteadyState('/model/kinetics/state')
#### Set clocks here
moose.useClock(4, "/model/kinetics/##[]", "process")
moose.setClock(4, float(simdt))
moose.setClock(5, float(simdt))
moose.useClock(5, '/model/kinetics/ksolve', 'process')
moose.useClock(8, '/model/graphs/#', 'process')
moose.setClock(8, float(plotDt))
moose.reinit()
state.stoich = stoich
state.showMatrices()
state.convergenceCriterion = 1e-8
return ksolve, state
def simulate(self, simTime, simDt=1e-3, plotDt=None):
'''Simulate the cable '''
if plotDt is None:
plotDt = simDt / 2
self.simDt = simDt
self.plotDt = plotDt
self.setupDUT()
# Setup clocks
utils.dump("STEP", "Setting up the clocks ... ")
moose.setClock(0, self.simDt)
moose.setClock(1, self.simDt)
moose.setClock(2, self.simDt)
## Use clocksc
moose.useClock(0, '/cable/##'.format(self.cablePath), 'process')
moose.useClock(1, '/cable/##'.format(self.cablePath), 'init')
moose.useClock(2, '{}/##'.format(self.tablePath), 'process')
utils.dump("STEP", [
"Simulating cable for {} sec".format(simTime),
" simDt: %s, plotDt: %s" % (self.simDt, self.plotDt)
])
self.setupHSolve()
moose.reinit()
utils.verify()
moose.start(simTime)
def test_elec_alone(dump_dir):
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' )
dump_data(dump_dir, 'instab')
# 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' )
dump_data(dump_dir, 'h_instab' + str(dt))
def run(self, key):
try:
Vm = self.Vm_tables[key]
u = self.u_tables[key]
except KeyError as e:
Vm = moose.Table(self.data_container.path + '/' + key + '_Vm')
nrn = self.neurons[key]
moose.connect(Vm, 'requestOut', nrn, 'getVm')
utable = moose.Table(self.data_container.path + '/' + key + '_u')
utable.connect('requestOut', self.neurons[key], 'getU')
self.Vm_tables[key] = Vm
self.u_tables[key] = utable
try:
Im = self.inject_tables[key]
except KeyError as e:
Im = moose.Table(
self.data_container.path + '/' + key +
'_inject') # May be different for non-pulsegen sources.
Im.connect('requestOut', self._get_neuron(key), 'getIm')
self.inject_tables[key] = Im
self.simtime = IzhikevichDemo.parameters[key][7] * 1e-3
for obj in moose.wildcardFind('%s/##' % (self.model_container.path)):
if obj not in self.scheduled:
moose.useClock(0, obj.path, 'process')
self.scheduled[obj] = True
for obj in moose.wildcardFind('%s/##' % (self.data_container.path)):
if obj not in self.scheduled:
moose.useClock(2, obj.path, 'process')
self.scheduled[obj] = True
moose.reinit()
moose.start(self.simtime)
while moose.isRunning():
time.sleep(100)
time = linspace(0, IzhikevichDemo.parameters[key][7], len(Vm.vector))
# DEBUG
nrn = self._get_neuron(key)
print(('a = %g, b = %g, c = %g, d = %g, initVm = %g, initU = %g' %
(nrn.a, nrn.b, nrn.c, nrn.d, nrn.initVm, nrn.initU)))
#! DEBUG
return (time, Vm, Im)
def main():
dt4 = 0.01
dt5 = 0.01
runtime = 10.0 # seconds
# Set up clocks. The dsolver to know before assigning stoich
moose.setClock( 4, dt4 )
moose.setClock( 5, dt5 )
makeModel()
moose.useClock( 4, '/model/compartment/dsolve', 'process' )
# Ksolve must be scheduled after dsolve.
moose.useClock( 5, '/model/compartment/ksolve', 'process' )
moose.reinit()
moose.start( runtime ) # Run the model
a = moose.element( '/model/compartment/a' )
b = moose.element( '/model/compartment/b' )
c = moose.element( '/model/compartment/c' )
d = moose.element( '/model/compartment/d' )
atot = sum( a.vec.conc )
btot = sum( b.vec.conc )
ctot = sum( c.vec.conc )
dtot = sum( d.vec.conc )
print(('tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot))
displayPlots()
moose.start( runtime ) # Run the model
atot = sum( a.vec.conc )
btot = sum( b.vec.conc )
ctot = sum( c.vec.conc )
dtot = sum( d.vec.conc )
print(('tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot))
quit()
def schedule():
moose.setClock(0, dt)
moose.setClock(1, dt)
moose.setClock(2, dt)
moose.setClock(3, dt)
moose.useClock(0, '/model/##[ISA=Compartment]', 'init')
moose.useClock(1, '/model/##', 'process')
moose.useClock(3, '/data/##', 'process')
moose.reinit()
def simulate(runTime, dt):
""" Simulate the cable """
moose.useClock(0, '/cable/##', 'process')
moose.useClock(0, '/cable/##', 'init')
moose.useClock(1, '/##', 'process')
moose.reinit()
setupSolver(hsolveDt=dt)
utils.verify()
moose.start(runTime)
def test_crossing_single():
"""This function creates an ematrix of two PulseGen elements and
another ematrix of two Table elements.
The two pulsegen elements have same amplitude but opposite phase.
Table[0] is connected to PulseGen[1] and Table[1] to Pulsegen[0].
In the plot you should see two square pulses of opposite phase.
"""
size = 2
pg = moose.PulseGen('pulsegen', size)
for ix, ii in enumerate(pg.vec):
pulse = moose.element(ii)
pulse.delay[0] = 1.0
pulse.width[0] = 2.0
pulse.level[0] = (-1)**ix
tab = moose.Table('table', size)
moose.connect(tab.vec[0], 'requestOut', pg.vec[1], 'getOutputValue',
'Single')
moose.connect(tab.vec[1], 'requestOut', pg.vec[0], 'getOutputValue',
'Single')
print 'Neighbors:'
for t in tab.vec:
print t.path
for n in moose.element(t).neighbors['requestOut']:
print 'requestOut <-', n.path
moose.setClock(0, 0.1)
moose.useClock(0, '/##', 'process')
moose.start(5)
for ii in tab.vec:
t = moose.Table(ii).vector
print len(t)
pylab.plot(t)
pylab.show()
def run_simulation(self):
# Setup data recording
data = moose.Neutral('/data')
Vm = moose.Table('/data/Vm')
moose.connect(Vm, 'requestData', self.compartments[0], 'get_Vm')
# Now schedule the sequence of operations and time resolutions
moose.setClock(0, self.dt)
moose.setClock(1, self.dt)
moose.setClock(2, self.dt)
moose.setClock(3, self.dt)
moose.setClock(4, self.dt)
#quite a hack:
current_clamp = self.current_clamp
# useClock: First argument is clock no.
# Second argument is a wildcard path matching all elements of type Compartment
# Last argument is the processing function to be executed at each tick of clock 0
moose.useClock(0, '/model/#[TYPE=Compartment]', 'init')
moose.useClock(1, '/model/#[TYPE=Compartment]', 'process')
moose.useClock(2, Vm.path, 'process')
moose.useClock(3, current_clamp.path, 'process')
moose.useClock(4, '/model/#/#[TYPE=HHChannel]', 'process')
# Now initialize everything and get set
moose.reinit()
moose.start(self.sim_time)
#handle to the global clock:
clock = moose.Clock('/clock')
#vectors:
self.rec_v = Vm.vec
self.t_final = clock.currentTime
def simulate( runTime, dt):
""" Simulate the cable """
moose.useClock(0, '/cable/##', 'process')
moose.useClock(0, '/cable/##', 'init')
moose.useClock(1, '/##', 'process')
moose.reinit()
setupSolver( hsolveDt = dt )
t = time.time( )
moose.start( runTime )
print( 'Time taken to simulate %f = %f' % ( runTime, time.time() - t ) )
def test_symcompartment():
"""This example demonstrates the use of SymCompartment class of MOOSE."""
model = moose.Neutral('model')
soma = moose.SymCompartment('%s/soma' % (model.path))
soma.Em = -60e-3
soma.Rm = 1000402560
soma.Cm = 2.375043912e-11
soma.Ra = 233957.7812
d1 = moose.SymCompartment('%s/d1' % (model.path))
d1.Rm = 397887392
d1.Cm = 2.261946489e-12
d1.Ra = 24867960
d2 = moose.SymCompartment('%s/d2' % (model.path))
d2.Rm = 2.877870285e+10
d2.Cm = 8.256105218e-13
d2.Ra = 20906072
moose.connect(d1, 'proximal', soma, 'distal')
moose.connect(d2, 'proximal', soma, 'distal')
moose.connect(d1, 'sibling', d2, 'sibling')
pg = moose.PulseGen('/model/pulse')
pg.delay[0] = 10e-3
pg.width[0] = 20e-3
pg.level[0] = 1e-6
pg.delay[1] = 1e9
moose.connect(pg, 'output', d1, 'injectMsg')
data = moose.Neutral('/data')
tab_soma = moose.Table('%s/soma_Vm' % (data.path))
tab_d1 = moose.Table('%s/d1_Vm' % (data.path))
tab_d2 = moose.Table('%s/d2_Vm' % (data.path))
moose.connect(tab_soma, 'requestOut', soma, 'getVm')
moose.connect(tab_d1, 'requestOut', d1, 'getVm')
moose.connect(tab_d2, 'requestOut', d2, 'getVm')
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.useClock(
0, '/model/##[ISA=Compartment]', 'init'
) # This is allowed because SymCompartment is a subclass of Compartment
moose.useClock(1, '/model/##', 'process')
moose.useClock(2, '/data/##[ISA=Table]', 'process')
moose.reinit()
moose.start(simtime)
t = np.linspace(0, simtime, len(tab_soma.vector))
data_matrix = np.vstack((t, tab_soma.vector, tab_d1.vector, tab_d2.vector))
np.savetxt('symcompartment.txt', data_matrix.transpose())
pylab.plot(t, tab_soma.vector, label='Vm_soma')
pylab.plot(t, tab_d1.vector, label='Vm_d1')
pylab.plot(t, tab_d2.vector, label='Vm_d2')
pylab.show()
def makeSolvers(elecDt):
# Put in the solvers, see how they fare.
# Here we kludge in a single chem solver for the whole system.
ksolve = moose.Ksolve('/model/ksolve')
stoich = moose.Stoich('/model/stoich')
stoich.compartment = moose.element('/model/chem/neuroMesh')
stoich.ksolve = ksolve
stoich.path = '/model/chem/##'
moose.useClock(5, '/model/ksolve', 'init')
moose.useClock(6, '/model/ksolve', 'process')
# Here is the elec solver
hsolve = moose.HSolve('/model/hsolve')
moose.useClock(1, '/model/hsolve', 'process')
hsolve.dt = elecDt
hsolve.target = '/model/elec/compt'
def test_symcompartment():
model = moose.Neutral('model')
soma = moose.SymCompartment('%s/soma' % (model.path))
soma.Em = -60e-3
soma.Rm = 1e9
soma.Cm = 1e-11
soma.Ra = 1e6
d1 = moose.SymCompartment('%s/d1' % (model.path))
d1.Rm = 1e8
d1.Cm = 1e-10
d1.Ra = 1e7
d2 = moose.SymCompartment('%s/d2' % (model.path))
d2.Rm = 1e8
d2.Cm = 1e-10
d2.Ra = 2e7
moose.connect(d1, 'proximal', soma, 'distal')
moose.connect(d2, 'proximal', soma, 'distal')
moose.connect(d1, 'sibling', d2, 'sibling')
pg = moose.PulseGen('/model/pulse')
pg.delay[0] = 10e-3
pg.width[0] = 20e-3
pg.level[0] = 1e-6
pg.delay[1] = 1e9
moose.connect(pg, 'output', d1, 'injectMsg')
data = moose.Neutral('/data')
tab_soma = moose.Table('%s/soma_Vm' % (data.path))
tab_d1 = moose.Table('%s/d1_Vm' % (data.path))
tab_d2 = moose.Table('%s/d2_Vm' % (data.path))
moose.connect(tab_soma, 'requestOut', soma, 'getVm')
moose.connect(tab_d1, 'requestOut', d1, 'getVm')
moose.connect(tab_d2, 'requestOut', d2, 'getVm')
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.useClock(
0, '/model/##[ISA=Compartment]', 'init'
) # This is allowed because SymCompartment is a subclass of Compartment
moose.useClock(1, '/model/##', 'process')
moose.useClock(2, '/data/##[ISA=Table]', 'process')
moose.reinit()
moose.start(simtime)
t = np.linspace(0, simtime, len(tab_soma.vector))
data_matrix = np.vstack((t, tab_soma.vector, tab_d1.vector, tab_d2.vector))
np.savetxt('symcompartment.txt', data_matrix.transpose())
pylab.plot(t, tab_soma.vector, label='Vm_soma')
pylab.plot(t, tab_d1.vector, label='Vm_d1')
pylab.plot(t, tab_d2.vector, label='Vm_d2')
pylab.show()
def example():
model = moose.Neutral('/model')
comp = moose.Compartment('/model/c')
hdfwriter = moose.HDF5DataWriter('h')
hdfwriter.mode = 2 # Truncate existing file
moose.connect(hdfwriter, 'requestOut', comp, 'getVm')
moose.connect(hdfwriter, 'requestOut', comp, 'getIm')
hdfwriter.filename = 'output_hdfdemo.h5'
hdfwriter.compressor = 'zlib'
hdfwriter.compression = 7
# Flush data from memory to disk after accumulating every 1K entries.
hdfwriter.flushLimit = 1024
# We allow simple attributes of type string, double and long.
# This allows for file-level metadata/annotation.
hdfwriter.stringAttr['note'] = 'This is a test.'
# All paths are taken relative to the root. The last token is the name
# of the attribute.
hdfwriter.doubleAttr['{}/vm/a_double_attribute'.format(
comp.path)] = 3.141592
hdfwriter.longAttr['an_int_attribute'] = 8640
# In addition, vectors of string, long and double can also be stored
# as attributes.
hdfwriter.stringVecAttr['stringvec'] = ['I wonder', 'why', 'I wonder']
hdfwriter.doubleVecAttr['{}/dvec'.format(comp.path)] = [3.141592, 2.71828]
hdfwriter.longVecAttr['{}/lvec'.format(comp.path)] = [3, 14, 1592, 271828]
vm_tab = moose.Table('Vm')
moose.connect(vm_tab, 'requestOut', comp, 'getVm')
moose.setClock(0, 1e-3)
moose.setClock(1, 1e-3)
moose.setClock(2, 1e-3)
moose.useClock(0, '/model/c', 'init')
moose.useClock(1, '/##[TYPE!=HDF5DataWriter]', 'process')
moose.useClock(2, '/##[TYPE=HDF5DataWriter]', 'process')
moose.reinit()
comp.inject = 0.1
moose.start(30.0)
hdfwriter.close()
vm_tab.plainPlot('hdfdemo_Vm.csv')
print(('Finished simulation. Data was saved in', hdfwriter.filename))
