PurkinjeCell.hoc

//  ******************************************************
// 
//     File generated by: neuroConstruct v1.6.0
// 
//  ******************************************************

{load_file("nrngui.hoc")}

//  Initialising stopwatch for timing setup

{startsw()}

print ""
print "*****************************************************"
print ""
print "    neuroConstruct generated NEURON simulation "
print "    for project: /Users/hashmup/nC_projects/PurkinjeCell.ncx/PurkinjeCell.ncx "
print ""
print "    Description: An initial implementation in NeuroML of the Purkinje Cell model from De Schutter, E. and Bower, J. M. (1994). Based on Arnd Roth el al's conversion of the original GENESIS code to NEURON.  "
print "     "
print "    Note: conversion not fully complete. Press Validate for details. Also, there are long standing issues about getting GENESIS and NEURON behaviour of the Purkinje cell to match. Contact P. Gleeson or A. Roth for more details on current status of this model."
print "    "
print "    ChannelML files need to be updated to post v1.7.3 format (though they still work file with existing XSL mappings for NEURON & GENESIS)"
print "    "
print "    "
print ""
print "    Simulation Configuration: SimConfig: Default Simulation Configuration "
print "    This is the default configuration of the Cell Groups, stimulations, plots, etc for this project "
print " "
print  "*****************************************************"

strdef pwd
{system("pwd", pwd)}
print ""
print "Current working dir: ", pwd

objectvar allCells
{allCells = new List()}


//  A flag to signal simulation was generated by neuroConstruct 

{nC = 1}


//  Including neuroConstruct utilities file 

{load_file("nCtools.hoc")}

//  Including neuroConstruct cell check file 

{load_file("cellCheck.hoc")}

//  Getting hostname

objref strFuncs
{strFuncs = new StringFunctions()}
strdef host
{system("hostname", host)}
if (strFuncs.len(host)>0) {
    strFuncs.left(host, strFuncs.len(host)-1) 
} else {
    host = "????" 
}


//  Simulation running in serial mode, setting default host id

{hostid = 0}


//  Initializes random-number generator

{use_mcell_ran4(1)}

{mcell_ran4_init(1587749884)}

//////////////////////////////////////////////////////////////////////
//   Cell group 0: SampleCellGroup has cells of type: SomaOnly_all
//////////////////////////////////////////////////////////////////////


//  Adding cell template file: SomaOnly_all.hoc for cell group SampleCellGroup

{ load_file("SomaOnly_all.hoc") }

//  Adding 1 cells of type SomaOnly_all in region SampleRegion

{n_SampleCellGroup = 1}

{n_SampleCellGroup_local = 0 } // actual number created on this host

objectvar a_SampleCellGroup[n_SampleCellGroup]

proc addCell_SampleCellGroup() {
    strdef reference
    sprint(reference, "SampleCellGroup_%d", $1)
    a_SampleCellGroup[$1] = new SomaOnly_all(reference, "SomaOnly_all", "A single segment/compartment cell with all channels which have been successfully translated to ChannelML")
    allCells.append(a_SampleCellGroup[$1])
}

for i = 0, n_SampleCellGroup-1 {
    addCell_SampleCellGroup(i)
    n_SampleCellGroup_local = n_SampleCellGroup_local +1 

}


//  Placing these cells in a region described by: Rectangular Box from point: (0.0, 0.0, 0.0) to (100.0, 50.0, 100.0)


//  Packing has been generated by: Random: num: 1, edge: 1, overlap: 1, other overlap: 0

{a_SampleCellGroup[0].position(43.629883,29.56268,64.92487)}

//////////////////////////////////////////////////////////////////////
//   Cell group 1: OrigChansCellGroup has cells of type: SomaOnly_origChans_all
//////////////////////////////////////////////////////////////////////


//  Adding cell template file: SomaOnly_origChans_all.hoc for cell group OrigChansCellGroup

{ load_file("SomaOnly_origChans_all.hoc") }

//  Adding 1 cells of type SomaOnly_origChans_all in region SampleRegion

{n_OrigChansCellGroup = 1}

{n_OrigChansCellGroup_local = 0 } // actual number created on this host

objectvar a_OrigChansCellGroup[n_OrigChansCellGroup]

proc addCell_OrigChansCellGroup() {
    strdef reference
    sprint(reference, "OrigChansCellGroup_%d", $1)
    a_OrigChansCellGroup[$1] = new SomaOnly_origChans_all(reference, "SomaOnly_origChans_all", "A single segment/compartment cell")
    allCells.append(a_OrigChansCellGroup[$1])
}

for i = 0, n_OrigChansCellGroup-1 {
    addCell_OrigChansCellGroup(i)
    n_OrigChansCellGroup_local = n_OrigChansCellGroup_local +1 

}


//  Placing these cells in a region described by: Rectangular Box from point: (0.0, 0.0, 0.0) to (100.0, 50.0, 100.0)


//  Packing has been generated by: Random: num: 1, edge: 1, overlap: 1, other overlap: 0

{a_OrigChansCellGroup[0].position(28.38983,23.009413,20.715052)}






//////////////////////////////////////////////////////////////////////
//   Setting initial parameters
//////////////////////////////////////////////////////////////////////

strdef simConfig
{simConfig = "Default Simulation Configuration"}
{celsius = 37.0}




proc initialiseValues0() {


//  Setting initial vals in cell group: SampleCellGroup which has 1 cells


//  Giving all cells an initial potential of: -68.0

    for i = 0, n_SampleCellGroup-1 {
        forsec a_SampleCellGroup[i].all  v = -68.0

    }


//  Setting initial vals in cell group: OrigChansCellGroup which has 1 cells


//  Giving all cells an initial potential of: -68.0

    for i = 0, n_OrigChansCellGroup-1 {
        forsec a_OrigChansCellGroup[i].all  v = -68.0

    }

}

objref fih0
{fih0 = new FInitializeHandler(0, "initialiseValues0()")}



//////////////////////////////////////////////////////////////////////
//   Adding Network Connections
//////////////////////////////////////////////////////////////////////


//////////////////////////////////////////////////////////////////////
//   Adding 2 stimulation(s)
//////////////////////////////////////////////////////////////////////

{ n_stim_SampleIClamp = 1 }
objectvar stim_SampleIClamp[n_stim_SampleIClamp]


//  Note: the stimulation was specified as being at a point 0.5 along segment: Soma

//  in section: Soma. For NEURON, this translates to a point 0.5 along section: Soma

a_SampleCellGroup[0].Soma {
    stim_SampleIClamp[0] = new CurrentClampExt(0.5)
    stim_SampleIClamp[0].del = 100.0
    stim_SampleIClamp[0].dur = 100.0
    stim_SampleIClamp[0].amp = 0.1
    stim_SampleIClamp[0].repeat = 0
}

{ n_stim_Input_0 = 1 }
objectvar stim_Input_0[n_stim_Input_0]


//  Note: the stimulation was specified as being at a point 0.5 along segment: Soma

//  in section: Soma. For NEURON, this translates to a point 0.5 along section: Soma

a_OrigChansCellGroup[0].Soma {
    stim_Input_0[0] = new CurrentClampExt(0.5)
    stim_Input_0[0].del = 100.0
    stim_Input_0[0].dur = 100.0
    stim_Input_0[0].amp = 0.1
    stim_Input_0[0].repeat = 0
}


access SomaOnly_all[0].Soma

//////////////////////////////////////////////////////////////////////
//   Settings for running the demo
//////////////////////////////////////////////////////////////////////


tstop = 300.0
dt = 0.005
steps_per_ms = 200.0

//////////////////////////////////////////////////////////////////////
//   Adding 14 plot(s)
//////////////////////////////////////////////////////////////////////


//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.v(0.5)

objref GraphWin_2
GraphWin_2 = new Graph(0)
{GraphWin_2.size(0, tstop,-90.0,50.0)}
{GraphWin_2.view(0, -90.0, tstop, 140.0, 80, 330, 330, 250)}
{
    GraphWin_2.addexpr("a_OrigChansCellGroup[0].Soma.v", "a_OrigChansCellGroup[0].Soma.v(0.5)", 1, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_2)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.v(0.5)

{
    GraphWin_2.addexpr("a_SampleCellGroup[0].Soma.v", "a_SampleCellGroup[0].Soma.v(0.5)", 2, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_2)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.z_K2_nmodl(0.5)

objref GraphWin_8
GraphWin_8 = new Graph(0)
{GraphWin_8.size(0, tstop,0.0,1.0)}
{GraphWin_8.view(0, 0.0, tstop, 1.0, 80, 330, 330, 250)}
{
    GraphWin_8.addexpr("a_OrigChansCellGroup[0].Soma.z_K2_nmodl", "a_OrigChansCellGroup[0].Soma.z_K2_nmodl(0.5)", 1, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_8)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.m_K2_nmodl(0.5)

{
    GraphWin_8.addexpr("a_OrigChansCellGroup[0].Soma.m_K2_nmodl", "a_OrigChansCellGroup[0].Soma.m_K2_nmodl(0.5)", 2, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_8)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.z_K2(0.5)

{
    GraphWin_8.addexpr("a_SampleCellGroup[0].Soma.z_K2", "a_SampleCellGroup[0].Soma.z_K2(0.5)", 3, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_8)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.m_K2(0.5)

{
    GraphWin_8.addexpr("a_SampleCellGroup[0].Soma.m_K2", "a_SampleCellGroup[0].Soma.m_K2(0.5)", 4, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_8)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.ica(0.5)

objref GraphWin_7
GraphWin_7 = new Graph(0)
{GraphWin_7.size(0, tstop,-0.4,0.02)}
{GraphWin_7.view(0, -0.4, tstop, 0.42000002, 80, 330, 330, 250)}
{
    GraphWin_7.addexpr("a_OrigChansCellGroup[0].Soma.ica", "a_OrigChansCellGroup[0].Soma.ica(0.5)", 1, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_7)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.ica(0.5)

{
    GraphWin_7.addexpr("a_SampleCellGroup[0].Soma.ica", "a_SampleCellGroup[0].Soma.ica(0.5)", 2, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_7)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.cai(0.5)

objref GraphWin_6
GraphWin_6 = new Graph(0)
{GraphWin_6.size(0, tstop,0.0,0.01)}
{GraphWin_6.view(0, 0.0, tstop, 0.01, 80, 330, 330, 250)}
{
    GraphWin_6.addexpr("a_OrigChansCellGroup[0].Soma.cai", "a_OrigChansCellGroup[0].Soma.cai(0.5)", 1, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_6)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.cai(0.5)

{
    GraphWin_6.addexpr("a_SampleCellGroup[0].Soma.cai", "a_SampleCellGroup[0].Soma.cai(0.5)", 2, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_6)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.h_CaP_nmodl(0.5)

objref GraphWin_5
GraphWin_5 = new Graph(0)
{GraphWin_5.size(0, tstop,0.0,1.0)}
{GraphWin_5.view(0, 0.0, tstop, 1.0, 80, 330, 330, 250)}
{
    GraphWin_5.addexpr("a_OrigChansCellGroup[0].Soma.h_CaP_nmodl", "a_OrigChansCellGroup[0].Soma.h_CaP_nmodl(0.5)", 1, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_5)
}

//   This code pops up a plot of a_OrigChansCellGroup[0].Soma.m_CaP_nmodl(0.5)

{
    GraphWin_5.addexpr("a_OrigChansCellGroup[0].Soma.m_CaP_nmodl", "a_OrigChansCellGroup[0].Soma.m_CaP_nmodl(0.5)", 2, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_5)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.h_CaP(0.5)

{
    GraphWin_5.addexpr("a_SampleCellGroup[0].Soma.h_CaP", "a_SampleCellGroup[0].Soma.h_CaP(0.5)", 3, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_5)
}

//   This code pops up a plot of a_SampleCellGroup[0].Soma.m_CaP(0.5)

{
    GraphWin_5.addexpr("a_SampleCellGroup[0].Soma.m_CaP", "a_SampleCellGroup[0].Soma.m_CaP(0.5)", 4, 1, 0.8, 0.9, 2)
    graphList[0].append(GraphWin_5)
}

//////////////////////////////////////////////////////////////////////
//   Adding blocks of native NEURON code
//////////////////////////////////////////////////////////////////////


//  Hoc commands to run at location: Type 2, Before return from finitialize()

objref fih_2
fih_2 = new FInitializeHandler(2.0, "callfi2()")
proc callfi2() {
forall if (ismembrane("na_ion")) {
		
	print "Rev pot of na being changed for section ", secname()
	ena = 45
}


forall if (ismembrane("k_ion")) {
		
	print "Rev pot of k being changed for section ", secname()
	ek = -85
}



forall if (ismembrane("ca_ion")) {
		
	print "Rev pot of k being changed for section ", secname()

	// Should be: cai = 4e-5 

	cai = 4e-5

	cao = 2.4

                             eca = 12.5*log(cao/cai)
                              ion_style("ca_ion", 1, 1, 0, 0, 0)
}

}

//  End of hoc commands to run at location: Type 2, Before return from finitialize()


//////////////////////////////////////////////////////////////////////
//   This will run a full simulation of 60001 steps when the hoc file is executed
//////////////////////////////////////////////////////////////////////


//  Recording 14 variable(s)

objref v_time
objref f_time
objref propsFile

v_time = new Vector()
{ v_time.record(&t) }
{ v_time.resize(60001) }
f_time = new File()


//  Saving VOLTAGE on only one seg, id: 0, in the only cell in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0)

objref v_OrigChansCellGroup_seg_Soma_v[1]
for i=0, 0 {
    { v_OrigChansCellGroup_seg_Soma_v[i] = new Vector() }
    { v_OrigChansCellGroup_seg_Soma_v[i].record(&a_OrigChansCellGroup[i].Soma.v(0.5))} 
    { v_OrigChansCellGroup_seg_Soma_v[i].resize(60001) }
}
objref f_OrigChansCellGroup_seg_Soma_v[1]


//  Saving VOLTAGE on only one seg, id: 0, in the only cell in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0)

objref v_SampleCellGroup_seg_Soma_v[1]
for i=0, 0 {
    { v_SampleCellGroup_seg_Soma_v[i] = new Vector() }
    { v_SampleCellGroup_seg_Soma_v[i].record(&a_SampleCellGroup[i].Soma.v(0.5))} 
    { v_SampleCellGroup_seg_Soma_v[i].resize(60001) }
}
objref f_SampleCellGroup_seg_Soma_v[1]


//  Saving K2_nmodl:z on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl
{ v_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl.record(&a_OrigChansCellGroup[0].Soma.z_K2_nmodl(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl


//  Saving K2_nmodl:m on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl
{ v_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl.record(&a_OrigChansCellGroup[0].Soma.m_K2_nmodl(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl


//  Saving K2:z on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_z_K2
{ v_SampleCellGroup_cn0_seg_Soma_z_K2 = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_z_K2.record(&a_SampleCellGroup[0].Soma.z_K2(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_z_K2.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_z_K2


//  Saving K2:m on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_m_K2
{ v_SampleCellGroup_cn0_seg_Soma_m_K2 = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_m_K2.record(&a_SampleCellGroup[0].Soma.m_K2(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_m_K2.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_m_K2


//  Saving ica on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_ica
{ v_OrigChansCellGroup_cn0_seg_Soma_ica = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_ica.record(&a_OrigChansCellGroup[0].Soma.ica(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_ica.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_ica


//  Saving CaP:CURR_DENS:ca on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_ica
{ v_SampleCellGroup_cn0_seg_Soma_ica = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_ica.record(&a_SampleCellGroup[0].Soma.ica(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_ica.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_ica


//  Saving cai on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_cai
{ v_OrigChansCellGroup_cn0_seg_Soma_cai = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_cai.record(&a_OrigChansCellGroup[0].Soma.cai(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_cai.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_cai


//  Saving cad:CONC:ca on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_cai
{ v_SampleCellGroup_cn0_seg_Soma_cai = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_cai.record(&a_SampleCellGroup[0].Soma.cai(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_cai.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_cai


//  Saving CaP_nmodl:h on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl
{ v_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl.record(&a_OrigChansCellGroup[0].Soma.h_CaP_nmodl(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl


//  Saving CaP_nmodl:m on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl
{ v_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl = new Vector() }
{ v_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl.record(&a_OrigChansCellGroup[0].Soma.m_CaP_nmodl(0.5)) }
{ v_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl.resize(60001) }
objref f_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl


//  Saving CaP:h on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_h_CaP
{ v_SampleCellGroup_cn0_seg_Soma_h_CaP = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_h_CaP.record(&a_SampleCellGroup[0].Soma.h_CaP(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_h_CaP.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_h_CaP


//  Saving CaP:m on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Creating vector for segment: Soma(ID: 0) in cell number: 0

objref v_SampleCellGroup_cn0_seg_Soma_m_CaP
{ v_SampleCellGroup_cn0_seg_Soma_m_CaP = new Vector() }
{ v_SampleCellGroup_cn0_seg_Soma_m_CaP.record(&a_SampleCellGroup[0].Soma.m_CaP(0.5)) }
{ v_SampleCellGroup_cn0_seg_Soma_m_CaP.resize(60001) }
objref f_SampleCellGroup_cn0_seg_Soma_m_CaP

strdef simReference
simReference = "Sim_672"



strdef simsDir
simsDir = "/Users/hashmup/nC_projects/PurkinjeCell.ncx/simulations/"


//  Note: to change location of the generated simulation files, just change value of targetDir
//  e.g. targetDir="" or targetDir="aSubDir/"

strdef targetDir
{ sprint(targetDir, "%s%s/", simsDir, simReference)}


//  Single simulation run...

strdef date
// Note: not showing date/time of start/stop of simulation. This requires Cygwin to be installed// which includes the "date" unix command. Install under c:\cygwin

setuptime = stopsw()

print "Setup time for simulation: ",setuptime," seconds"

print "Starting simulation of duration ",tstop,"ms, dt: ",dt,"ms, reference: ",simReference,""

{currenttime = startsw()}
//////////////////////////////////////////////////////////////////////
//   Main run statement
//////////////////////////////////////////////////////////////////////

{run()}

{realruntime = startsw() - currenttime}
print "Finished simulation in ", realruntime ,"seconds"

print "Storing the data..."

strdef timeFilename

//  Saving VOLTAGE on only one seg, id: 0, in the only cell in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0)

for i=0, 0 {
    f_OrigChansCellGroup_seg_Soma_v[i] = new File()
    strdef filename
    {sprint(filename, "%sOrigChansCellGroup_%d.dat", targetDir, i)}
    f_OrigChansCellGroup_seg_Soma_v[i].wopen(filename)
    v_OrigChansCellGroup_seg_Soma_v[i].printf(f_OrigChansCellGroup_seg_Soma_v[i])
    f_OrigChansCellGroup_seg_Soma_v[i].close()
}


//  Saving VOLTAGE on only one seg, id: 0, in the only cell in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0)

for i=0, 0 {
    f_SampleCellGroup_seg_Soma_v[i] = new File()
    strdef filename
    {sprint(filename, "%sSampleCellGroup_%d.dat", targetDir, i)}
    f_SampleCellGroup_seg_Soma_v[i].wopen(filename)
    v_SampleCellGroup_seg_Soma_v[i].printf(f_SampleCellGroup_seg_Soma_v[i])
    f_SampleCellGroup_seg_Soma_v[i].close()
}


//  Saving K2_nmodl:z on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.K2_nmodl_z.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl.printf(f_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl)}
{f_OrigChansCellGroup_cn0_seg_Soma_z_K2_nmodl.close()}


//  Saving K2_nmodl:m on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.K2_nmodl_m.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl.printf(f_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl)}
{f_OrigChansCellGroup_cn0_seg_Soma_m_K2_nmodl.close()}


//  Saving K2:z on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_z_K2 = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.K2_z.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_z_K2.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_z_K2.printf(f_SampleCellGroup_cn0_seg_Soma_z_K2)}
{f_SampleCellGroup_cn0_seg_Soma_z_K2.close()}


//  Saving K2:m on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_m_K2 = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.K2_m.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_m_K2.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_m_K2.printf(f_SampleCellGroup_cn0_seg_Soma_m_K2)}
{f_SampleCellGroup_cn0_seg_Soma_m_K2.close()}


//  Saving ica on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_ica = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.ica.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_ica.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_ica.printf(f_OrigChansCellGroup_cn0_seg_Soma_ica)}
{f_OrigChansCellGroup_cn0_seg_Soma_ica.close()}


//  Saving CaP:CURR_DENS:ca on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_ica = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.CaP_CURR_DENS_ca.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_ica.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_ica.printf(f_SampleCellGroup_cn0_seg_Soma_ica)}
{f_SampleCellGroup_cn0_seg_Soma_ica.close()}


//  Saving cai on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_cai = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.cai.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_cai.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_cai.printf(f_OrigChansCellGroup_cn0_seg_Soma_cai)}
{f_OrigChansCellGroup_cn0_seg_Soma_cai.close()}


//  Saving cad:CONC:ca on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_cai = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.cad_CONC_ca.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_cai.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_cai.printf(f_SampleCellGroup_cn0_seg_Soma_cai)}
{f_SampleCellGroup_cn0_seg_Soma_cai.close()}


//  Saving CaP_nmodl:h on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.CaP_nmodl_h.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl.printf(f_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl)}
{f_OrigChansCellGroup_cn0_seg_Soma_h_CaP_nmodl.close()}


//  Saving CaP_nmodl:m on only one seg, id: 0, in only cell: 0 in OrigChansCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl = new File()
strdef filename
{sprint(filename, "%sOrigChansCellGroup_%d.CaP_nmodl_m.dat", targetDir, 0)}
{f_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl.wopen(filename)}
{v_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl.printf(f_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl)}
{f_OrigChansCellGroup_cn0_seg_Soma_m_CaP_nmodl.close()}


//  Saving CaP:h on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_h_CaP = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.CaP_h.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_h_CaP.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_h_CaP.printf(f_SampleCellGroup_cn0_seg_Soma_h_CaP)}
{f_SampleCellGroup_cn0_seg_Soma_h_CaP.close()}


//  Saving CaP:m on only one seg, id: 0, in only cell: 0 in SampleCellGroup


//  Saving vector for segment: Soma(ID: 0) in cell number: 0

f_SampleCellGroup_cn0_seg_Soma_m_CaP = new File()
strdef filename
{sprint(filename, "%sSampleCellGroup_%d.CaP_m.dat", targetDir, 0)}
{f_SampleCellGroup_cn0_seg_Soma_m_CaP.wopen(filename)}
{v_SampleCellGroup_cn0_seg_Soma_m_CaP.printf(f_SampleCellGroup_cn0_seg_Soma_m_CaP)}
{f_SampleCellGroup_cn0_seg_Soma_m_CaP.close()}


{ sprint(timeFilename, "%s%s", targetDir, "time.dat")}
{ f_time.wopen(timeFilename) }
{ v_time.printf(f_time) }
{ f_time.close() }

{savetime = stopsw()}

propsFile = new File()
strdef propsFilename
{sprint(propsFilename, "%ssimulator.props", targetDir)}
{propsFile.wopen(propsFilename)}
{propsFile.printf("#This is a list of properties generated by NEURON during the simulation run\n")}
{propsFile.printf("Host=%s\n", host)}
{propsFile.printf("RealSimulationTime=%g\n", realruntime)}
{propsFile.printf("SimulationSaveTime=%g\n", savetime)}
{propsFile.printf("SimulationSetupTime=%g\n", setuptime)}
{propsFile.printf("NEURONversion=%s\n", nrnversion())}
{propsFile.close()}

print "Data stored in ",savetime, "secs in directory: ", targetDir


//   This code pops up a simple Run Control

{
xpanel("RunControl", 0)
v_init = -60.0
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
t = 0
xvalue("t","t", 2 )
tstop = 300.0
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.005
 xvalue("dt","dt", 1,"setdt()", 0, 1 )
xpanel(80,80)
}