Python moose.connect函数代码示例

def createFunction(fb,setpool,objB,objA):
    fapath1 = fb.path.replace(objB,objA)
    fapath = fapath1.replace('[0]','')

    if not moose.exists(fapath):
        # if fb.parent.className in ['CubeMesh','CyclMesh']:
        #   des = moose.Function('/'+objA+'/'+fb.parent.name+'/'+fb.name)
        # elif fb.parent.className in ['Pool','ZombiePool','BufPool','ZombieBufPool']:
        #   for akey in list(poolListina[findCompartment(fb).name]):
        #       if fb.parent.name == akey.name:
        #           des = moose.Function(akey.path+'/'+fb.name)
        des = moose.Function(fapath)
    else:
        des = moose.element(fapath)
    inputB = moose.element(fb.path+'/x').neighbors["input"]
    moose.connect(des, 'valueOut', moose.element(setpool),'setN' )
    inputA = []
    inputA = moose.element(fapath+'/x').neighbors["input"]
    if not inputA:
        for src in inputB:
            pool = ((src.path).replace(objB,objA)).replace('[0]','')
            numVariables = des.numVars
            expr = ""
            expr = (des.expr+'+'+'x'+str(numVariables))
            expr = expr.lstrip("0 +")
            expr = expr.replace(" ","")
            des.expr = expr
            moose.connect( pool, 'nOut', des.x[numVariables], 'input' )

def create_cell():
    """Create a single-compartment Hodgking-Huxley neuron with a
    synaptic channel. 

    This uses the :func:`ionchannel.create_1comp_neuron` function for
    model creation.

    Returns a dict containing the neuron, the synchan and the
    synhandler for accessing the synapse,
    """
    neuron = create_1comp_neuron('/neuron')
    #: SynChan for post synaptic neuron
    synchan = moose.SynChan('/neuron/synchan')
    synchan.Gbar = 1e-8
    synchan.tau1 = 2e-3
    synchan.tau2 = 2e-3
    msg = moose.connect(neuron, 'channel', synchan, 'channel')
    #: Create SynHandler to handle spike event input and set the
    #: activation input of synchan
    synhandler = moose.SimpleSynHandler('/neuron/synhandler')
    synhandler.synapse.num = 1
    synhandler.synapse[0].delay = 5e-3
    moose.connect(synhandler, 'activationOut', synchan, 'activation')
    return {'neuron': neuron,
            'synchan': synchan,
            'synhandler': synhandler}

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()

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

def main( runTime ):
    try:
        moose.delete('/acc92')
        print("Deleted old model")
    except Exception as  e:
        print("Could not clean. model not loaded yet")

    moose.loadModel('acc92_caBuff.g',loadpath,'gsl')  
    ca = moose.element(loadpath+'/kinetics/Ca')
    pr = moose.element(loadpath+'/kinetics/protein')
    clockdt = moose.Clock('/clock').dts 
    moose.setClock(8, 0.1)#simdt
    moose.setClock(18, 0.1)#plotdt
    print clockdt
    print " \t \t simdt ", moose.Clock('/clock').dts[8],"plotdt ",moose.Clock('/clock').dts[18]
    ori =  ca.concInit
    tablepath = loadpath+'/kinetics/Ca'
    tableele = moose.element(tablepath)
    table = moose.Table2(tablepath+'.con')
    x = moose.connect(table, 'requestOut', tablepath, 'getConc')
    tablepath1 = loadpath+'/kinetics/protein'
    tableele1 = moose.element(tablepath1)
    table1 = moose.Table2(tablepath1+'.con')
    x1 = moose.connect(table1, 'requestOut', tablepath1, 'getConc')

    ca.concInit = ori
    print("[INFO] Running for 4000 with Ca.conc %s " % ca.conc)
    moose.start(4000)

    ca.concInit = 5e-03
    print("[INFO] Running for 20 with Ca.conc %s " % ca.conc)
    moose.start(20)

    ca.concInit = ori
    moose.start( runTime ) #here give the interval time 

    ca.concInit = 5e-03
    print("[INFO] Running for 20 with Ca.conc %s " % ca.conc)
    moose.start(20)

    ca.concInit = ori
    print("[INFO] Running for 2000 with Ca.conc %s " % ca.conc)
    moose.start(2000)

    pylab.figure()
    pylab.subplot(2, 1, 1)
    t = numpy.linspace(0.0, moose.element("/clock").runTime, len(table.vector)) # sec
    pylab.plot( t, table.vector, label="Ca Conc (interval- 8000s)" )
    pylab.legend()
    pylab.subplot(2, 1, 2)
    t1 = numpy.linspace(0.0, moose.element("/clock").runTime, len(table1.vector)) # sec
    pylab.plot( t1, table1.vector, label="Protein Conc (interval- 8000s)" )
    pylab.legend()
    pylab.savefig( os.path.join( dataDir, '%s_%s.png' % (table1.name, runTime) ) )

    print('[INFO] Saving data to csv files in %s' % dataDir)
    tabPath1 = os.path.join( dataDir, '%s_%s.csv' % (table.name, runTime))
    numpy.savetxt(tabPath1, numpy.matrix([t, table.vector]).T, newline='\n')
    tabPath2 = os.path.join( dataDir, '%s_%s.csv' % (table1.name, runTime) )
    numpy.savetxt(tabPath2, numpy.matrix([t1, table1.vector]).T, newline='\n')

def main():
    """ This example illustrates loading, running of an SBML model defined in XML format.\n
	The model 00001-sbml-l3v1.xml is taken from l3v1 SBML testcase.\n
	Plots are setup.\n
	Model is run for 20sec.\n
	As a general rule we created model under '/path/model' and plots under '/path/graphs'.\n
    """

    mfile =  os.path.join( script_dir, 'chem_models/00001-sbml-l3v1.xml')
    runtime = 20.0
        
    # Loading the sbml file into MOOSE, models are loaded in path/model
    sbmlId = moose.readSBML(mfile,'sbml')
    

    s1 = moose.element('/sbml/model/compartment/S1')
    s2= moose.element('/sbml/model/compartment/S2')
                      
    # Creating MOOSE Table, Table2 is for the chemical model
    graphs = moose.Neutral( '/sbml/graphs' )
    outputs1 = moose.Table2 ( '/sbml/graphs/concS1')
    outputs2 = moose.Table2 ( '/sbml/graphs/concS2')

    # connect up the tables
    moose.connect( outputs1,'requestOut', s1, 'getConc' );
    moose.connect( outputs2,'requestOut', s2, 'getConc' );

        
    # Reset and Run
    moose.reinit()
    moose.start(runtime)

def setup_model(model_path, synapse_locations, passive=False, solver='hsolve'):
    """Set up a single cell model under `model_path` with synapses
    created in the compartments listed in `synapse_locations`.


    `model_path` - location where the model should be created.

    `synapse_locations`: compartment names for the synapses.

    """
    cell = moose.copy(make_prototype(passive), model_path)
    if solver.lower() == 'hsolve':
        hsolve = moose.HSolve( '%s/solve' % (cell.path))
        hsolve.dt = simdt
        hsolve.target = cell.path
    syninfo_list = []
    for compname in synapse_locations:
        comppath = '%s/%s' % (cell.path, compname)
        print('1111 Creating synapse in', comppath)
        compartment = moose.element(comppath)
        syninfo = make_synapse(compartment)
        syninfo_list.append(syninfo)
        # connect  pulse stimulus
        stim_path = '%s/%s/stim' % (cell.path, compname)
        print('2222 Creating stimuls in', stim_path)
        stim = moose.PulseGen(stim_path)
        moose.connect(stim, 'output', syninfo['spike'], 'Vm')
        syninfo['stimulus'] = stim
    return {'neuron': cell,
            'syninfo': syninfo_list}

def make_synapse(path):
    """Create a synapse with two time constants."""
    syn = moose.SynChan(path)
    syn.tau1 = 5.0 # ms
    syn.tau2 = 1.0 # ms
    syn.Gbar = 1.0 # mS
    syn.Ek = 0.0
    synsh = moose.SimpleSynHandler( path + '/sh' )
    synsh.synapse.num = 1
    # syn.bufferTime = 1.0 # ms
    synsh.synapse.delay = 1.0
    synsh.synapse.weight = 1.0
    print(('Synapses:', len(synsh.synapse), 'w=', synsh.synapse[0].weight))
    spikegen = moose.SpikeGen('%s/spike' % (syn.parent.path))
    spikegen.edgeTriggered = False # Make it fire continuously when input is high
    spikegen.refractT = 10.0 # With this setting it will fire at 1 s / 10 ms = 100 Hz
    spikegen.threshold = 0.5
    # This will send alternatind -1 and +1 to SpikeGen to make it fire
    spike_stim = moose.PulseGen('%s/spike_stim' % (syn.parent.path))
    spike_stim.delay[0] = 50.0
    spike_stim.level[0] = 1.0
    spike_stim.width[0] = 100.0
    moose.connect(spike_stim, 'output', spikegen, 'Vm')
    m = moose.connect(spikegen, 'spikeOut', synsh.synapse[0], 'addSpike')
    return syn, spikegen

def main():
    ######## Put your favourite cell model here ######
    ##This one is from PMID 22730554: Suo et al J. Mol Cell Biol 2012
    filename = 'cells/ko20x-07.CNG.swc'
    moose.Neutral( '/library' )
    rdes = rd.rdesigneur( \
            cellProto = [[ filename, 'elec' ] ],\
            passiveDistrib = passiveDistrib_,
            chanProto = chanProto_,
            chanDistrib = chanDistrib_
        )
    rdes.buildModel( '/model' )
    moose.reinit()

    ################## Now we store plots ########################
    somaVm = moose.Table( '/somaVm' )
    moose.connect( somaVm, 'requestOut', rdes.soma, 'getVm' )
    ################## Now we set up the display ########################
    compts = moose.wildcardFind( "/model/elec/#[ISA=CompartmentBase]" )
    compts[0].inject = inject

    print("Setting Up 3D Display")
    app = QtGui.QApplication(sys.argv)
    vm_viewer = create_vm_viewer(rdes, somaVm)
    vm_viewer.show()
    vm_viewer.start()
    return app.exec_()

 def _addSpine( self, parent, spineProto, pos, angle, x, y, z, size, k ):
     spine = moose.copy( spineProto, parent.parent, 'spine' + str(k) )
     kids = spine[0].children
     coords = []
     ppos = np.array( [parent.x0, parent.y0, parent.z0] )
     for i in kids:
         #print i.name, k
         j = i[0]
         j.name += str(k)
         #print 'j = ', j
         coords.append( [j.x0, j.y0, j.z0] )
         coords.append( [j.x, j.y, j.z] )
         self._scaleSpineCompt( j, size )
         moose.move( i, self.elecid )
     origin = coords[0]
     #print 'coords = ', coords
     # Offset it so shaft starts from surface of parent cylinder
     origin[0] -= parent.diameter / 2.0 
     coords = np.array( coords )
     coords -= origin # place spine shaft base at origin.
     rot = np.array( [x, [0,0,0], [0,0,0]] )
     coords = np.dot( coords, rot )
     moose.delete( spine )
     moose.connect( parent, "raxial", kids[0], "axial" )
     self._reorientSpine( kids, coords, ppos, pos, size, angle, x, y, z )

def create_squid():
    """Create a single compartment squid model."""
    parent = moose.Neutral ('/n' )
    compt = moose.Compartment( '/n/compt' )
    Em = EREST_ACT + 10.613e-3
    compt.Em = Em
    compt.initVm = EREST_ACT
    compt.Cm = 7.85e-9
    compt.Rm = 4.2e5
    compt.Ra = 7639.44e3
    nachan = moose.HHChannel( '/n/compt/Na' )
    nachan.Xpower = 3
    xGate = moose.HHGate(nachan.path + '/gateX')    
    xGate.setupAlpha(Na_m_params +
                      [VDIVS, VMIN, VMAX])
    nachan.Ypower = 1
    yGate = moose.HHGate(nachan.path + '/gateY')
    yGate.setupAlpha(Na_h_params + 
                      [VDIVS, VMIN, VMAX])
    nachan.Gbar = 0.942e-3
    nachan.Ek = 115e-3+EREST_ACT
    moose.connect(nachan, 'channel', compt, 'channel', 'OneToOne')

    kchan = moose.HHChannel( '/n/compt/K' )
    kchan.Xpower = 4.0
    xGate = moose.HHGate(kchan.path + '/gateX')    
    xGate.setupAlpha(K_n_params +
                      [VDIVS, VMIN, VMAX])
    kchan.Gbar = 0.2836e-3
    kchan.Ek = -12e-3+EREST_ACT
    moose.connect(kchan, 'channel', compt, 'channel', 'OneToOne')
    return compt

def make_spiny_compt(root_path, number,synInput):
    comptLength = 100e-6
    comptDia = 4e-6
    numSpines = Number_Of_Spines
    cell = moose.Neutral (root_path+"/cell"+str(number))
    
    compt = create_squid(cell)
    compt.inject = INJECT_CURRENT
    compt.x0 = 0
    compt.y0 = 0
    compt.z0 = 0
    compt.x = comptLength
    compt.y = 0
    compt.z = 0
    compt.length = comptLength
    compt.diameter = comptDia
    
    for i in range( numSpines ):
        r = create_spine_with_receptor( compt, cell, i, i/float(numSpines) )
        r.synapse.num = 1
        syn = moose.element( r.path + '/synapse' )
        moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
        syn.weight = 0.2
        syn.delay = i * 1.0e-4
        """

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 create_population(container, size):
    """Create a population of `size` single compartmental neurons with Na+
    and K+ channels. Also create SpikeGen objects and SynChan objects
    connected to these which can act as plug points for setting up
    synapses later.

    This uses ..ref::`ionchannel.create_1comp_neuron`.

    """
    path = container.path
    print path, size, type(path)
    comps = create_1comp_neuron("{}/neuron".format(path), number=size)
    synpath = path + "/synchan"
    print synpath, size, type(size)
    synchan = moose.vec(synpath, n=size, dtype="SynChan")
    synchan.Gbar = 1e-8
    synchan.tau1 = 2e-3
    synchan.tau2 = 2e-3
    m = moose.connect(comps, "channel", synchan, "channel", "OneToOne")
    synhandler = moose.vec("{}/synhandler".format(path), n=size, dtype="SimpleSynHandler")
    moose.connect(synhandler, "activationOut", synchan, "activation", "OneToOne")
    spikegen = moose.vec("{}/spikegen".format(path), n=size, dtype="SpikeGen")
    spikegen.threshold = 0.0
    m = moose.connect(comps, "VmOut", spikegen, "Vm", "OneToOne")
    return {"compartment": comps, "spikegen": spikegen, "synchan": synchan, "synhandler": synhandler}

def make_spiny_compt():
    comptLength = 100e-6
    comptDia = 4e-6
    numSpines = 5
    compt = create_squid()
    compt.inject = 1e-7
    compt.x0 = 0
    compt.y0 = 0
    compt.z0 = 0
    compt.x = comptLength
    compt.y = 0
    compt.z = 0
    compt.length = comptLength
    compt.diameter = comptDia
    synInput = moose.SpikeGen( '/n/compt/synInput' )
    synInput.refractT = 47e-3
    synInput.threshold = -1.0
    synInput.edgeTriggered = 0
    synInput.Vm( 0 )
    cell = moose.element( '/n' )
    for i in range( numSpines ):
        r = create_spine_with_receptor( compt, cell, i, i/float(numSpines) )
        r.synapse.num = 1
        syn = moose.element( r.path + '/synapse' )
        moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
        syn.weight = 0.2
        syn.delay = i * 1.0e-4
        """